diff --git a/docs/mindarmour/docs/source_en/concept_drift_images.md b/docs/mindarmour/docs/source_en/concept_drift_images.md index 06e68276efec420fb6c68abd4744d8bea3876c03..78ccff4dc8e0c2148043bf47c5e9cc3ad3ce1660 100644 --- a/docs/mindarmour/docs/source_en/concept_drift_images.md +++ b/docs/mindarmour/docs/source_en/concept_drift_images.md @@ -16,7 +16,7 @@ This example provides a method for detecting a distribution change of image data 5. Execute the concept drift detection function. 6. View the execution result. -> This example is for CPUs, GPUs, and Atlas training series. Currently only supports GRAPH_MODE. You can download the complete sample code at . +> This example is for CPUs, GPUs, and Atlas training series. Currently only supports GRAPH_MODE. You can download the complete sample code at . ## Preparations diff --git a/docs/mindarmour/docs/source_en/concept_drift_time_series.md b/docs/mindarmour/docs/source_en/concept_drift_time_series.md index a7d87ae4c5f3287ecc27041eb20f11055d5dff82..75715ebda706d2a5156c1e02c94cd4b9fdf98448 100644 --- a/docs/mindarmour/docs/source_en/concept_drift_time_series.md +++ b/docs/mindarmour/docs/source_en/concept_drift_time_series.md @@ -16,7 +16,7 @@ The following is a simple example showing the overall process of detecting conce 3. Call the concept drift detection function. 4. View the execution result. -> You can obtain the complete executable sample code at . +> You can obtain the complete executable sample code at . ## Preparations diff --git a/docs/mindarmour/docs/source_en/differential_privacy_design.md b/docs/mindarmour/docs/source_en/differential_privacy_design.md index 83fd5a7dfa2ddf93035fe2e70656e09a7ac3d89b..d998fdc03e5d21a5f002002d04e6580d09329d85 100644 --- a/docs/mindarmour/docs/source_en/differential_privacy_design.md +++ b/docs/mindarmour/docs/source_en/differential_privacy_design.md @@ -40,10 +40,10 @@ Compared with traditional differential privacy, ZCDP and RDP provide stricter pr ## Code Implementation -- [mechanisms.py](https://atomgit.com/mindspore-lab/mindarmour/blob/master/mindarmour/privacy/diff_privacy/mechanisms/mechanisms.py): implements the noise generation mechanism required by differential privacy training, including simple Gaussian noise, adaptive Gaussian noise, and adaptive clipping Gaussian noise. -- [optimizer.py](https://atomgit.com/mindspore-lab/mindarmour/blob/master/mindarmour/privacy/diff_privacy/optimizer/optimizer.py): implements the fundamental logic of using the noise generation mechanism to add noise during backward propagation. -- [monitor.py](https://atomgit.com/mindspore-lab/mindarmour/blob/master/mindarmour/privacy/diff_privacy/monitor/monitor.py): implements the callback function for computing the differential privacy budget. During model training, the current differential privacy budget is returned. -- [model.py](https://atomgit.com/mindspore-lab/mindarmour/blob/master/mindarmour/privacy/diff_privacy/train/model.py): implements the logic of computing the loss and gradient as well as the gradient truncation logic of differential privacy training, which is the entry for users to use the differential privacy training capability. +- [mechanisms.py](https://atomgit.com/mindspore/mindarmour/blob/master/mindarmour/privacy/diff_privacy/mechanisms/mechanisms.py): implements the noise generation mechanism required by differential privacy training, including simple Gaussian noise, adaptive Gaussian noise, and adaptive clipping Gaussian noise. +- [optimizer.py](https://atomgit.com/mindspore/mindarmour/blob/master/mindarmour/privacy/diff_privacy/optimizer/optimizer.py): implements the fundamental logic of using the noise generation mechanism to add noise during backward propagation. +- [monitor.py](https://atomgit.com/mindspore/mindarmour/blob/master/mindarmour/privacy/diff_privacy/monitor/monitor.py): implements the callback function for computing the differential privacy budget. During model training, the current differential privacy budget is returned. +- [model.py](https://atomgit.com/mindspore/mindarmour/blob/master/mindarmour/privacy/diff_privacy/train/model.py): implements the logic of computing the loss and gradient as well as the gradient truncation logic of differential privacy training, which is the entry for users to use the differential privacy training capability. ## References diff --git a/docs/mindarmour/docs/source_en/evaluation_of_CNNCTC.md b/docs/mindarmour/docs/source_en/evaluation_of_CNNCTC.md index 06a0a51ace8bb1219b4a664da8b8ee862c89a774..97491e9613f31680f42e95f1f038b40b094a4e1a 100644 --- a/docs/mindarmour/docs/source_en/evaluation_of_CNNCTC.md +++ b/docs/mindarmour/docs/source_en/evaluation_of_CNNCTC.md @@ -6,7 +6,7 @@ This tutorial uses natural perturbation serving to evaluate the robustness of the OCR model, CNN-CTC. Multiple natural perturbation sample datasets are generated based on serving, and then the robustness of the CNN-CTC model is evaluated based on the model performance on the natural perturbation sample datasets. -> You can obtain the complete executable sample code at . +> You can obtain the complete executable sample code at . ## Environment Requirements @@ -63,7 +63,7 @@ In the preceding information, `%09d` indicates a string of 9 digits. Example: la ### Generating an Evaluation Dataset based on Natural Perturbation Serving -1. Start the serving server for generating natural perturbation samples. For details, see [Generating Natural Perturbation Samples Based on the Serving Server](https://atomgit.com/mindspore-lab/mindarmour/blob/master/examples/natural_robustness/serving/README.md#). +1. Start the serving server for generating natural perturbation samples. For details, see [Generating Natural Perturbation Samples Based on the Serving Server](https://atomgit.com/mindspore/mindarmour/blob/master/examples/natural_robustness/serving/README.md#). ```bash cd serving/server/ @@ -81,7 +81,7 @@ In the preceding information, `%09d` indicates a string of 9 digits. Example: la 2. The core code is described as follows: - 1. Configure the perturbation method. For details about the available perturbation methods and parameter configurations, see [transform/image](https://atomgit.com/mindspore-lab/mindarmour/tree/master/mindarmour/natural_robustness/transform/image). The following is a configuration example. + 1. Configure the perturbation method. For details about the available perturbation methods and parameter configurations, see [transform/image](https://atomgit.com/mindspore/mindarmour/tree/master/mindarmour/natural_robustness/transform/image). The following is a configuration example. ```python PerturbConfig = [ diff --git a/docs/mindarmour/docs/source_en/fault_injection.md b/docs/mindarmour/docs/source_en/fault_injection.md index f921b0cc6db0ccc29ee70c4f072d33234b12ee5d..59caf8ab7fc01dec6f5e73dccf1b8ec862862378 100644 --- a/docs/mindarmour/docs/source_en/fault_injection.md +++ b/docs/mindarmour/docs/source_en/fault_injection.md @@ -21,7 +21,7 @@ The following is a simple example showing the overall process of model fault inj 3. Call the fault injection module. 4. View the execution result. -> You can obtain the complete executable code at +> You can obtain the complete executable code at ## Preparations diff --git a/docs/mindarmour/docs/source_en/fuzzer_design.md b/docs/mindarmour/docs/source_en/fuzzer_design.md index a009a4616bf12d3a1cd83e75dbddccf698a44dbf..10a7e7c1d36a22bc0ccf8b8facdfa0b1334a0fd0 100644 --- a/docs/mindarmour/docs/source_en/fuzzer_design.md +++ b/docs/mindarmour/docs/source_en/fuzzer_design.md @@ -51,10 +51,10 @@ Through multiple rounds of mutations, you can obtain a series of variant data in ## Code Implementation -1. [fuzzing.py](https://atomgit.com/mindspore-lab/mindarmour/blob/master/mindarmour/fuzz_testing/fuzzing.py): overall fuzz testing process. -2. [model_coverage_metrics.py](https://atomgit.com/mindspore-lab/mindarmour/blob/master/mindarmour/fuzz_testing/model_coverage_metrics.py): neuron coverage rate metrics, including KMNC, NBC, and SNAC. -3. [image transform methods](https://atomgit.com/mindspore-lab/mindarmour/tree/master/mindarmour/natural_robustness/transform/image): image mutation methods, including a plurality of noise addition, blurring, brightness adjustment and affine transformation methods. -4. [adversarial attacks](https://atomgit.com/mindspore-lab/mindarmour/tree/master/mindarmour/adv_robustness/attacks): methods for generating adversarial examples based on white-box and black-box attacks. +1. [fuzzing.py](https://atomgit.com/mindspore/mindarmour/blob/master/mindarmour/fuzz_testing/fuzzing.py): overall fuzz testing process. +2. [model_coverage_metrics.py](https://atomgit.com/mindspore/mindarmour/blob/master/mindarmour/fuzz_testing/model_coverage_metrics.py): neuron coverage rate metrics, including KMNC, NBC, and SNAC. +3. [image transform methods](https://atomgit.com/mindspore/mindarmour/tree/master/mindarmour/natural_robustness/transform/image): image mutation methods, including a plurality of noise addition, blurring, brightness adjustment and affine transformation methods. +4. [adversarial attacks](https://atomgit.com/mindspore/mindarmour/tree/master/mindarmour/adv_robustness/attacks): methods for generating adversarial examples based on white-box and black-box attacks. ## References diff --git a/docs/mindarmour/docs/source_en/improve_model_security_nad.md b/docs/mindarmour/docs/source_en/improve_model_security_nad.md index e299f475ef2d9ae00863c67e37319577df02257d..93aa9bed752186467d2f270835c2adcdd082a809 100644 --- a/docs/mindarmour/docs/source_en/improve_model_security_nad.md +++ b/docs/mindarmour/docs/source_en/improve_model_security_nad.md @@ -15,7 +15,7 @@ At the beginning of AI algorithm design, related security threats are sometimes This section describes how to use MindSpore Armour in adversarial attack and defense on image classification tasks by taking the Fast Gradient Sign Method (FGSM) attack algorithm and Natural Adversarial Defense (NAD) algorithm as examples. > The current sample is for CPU, GPU and Atlas training series. You can find the complete executable sample code at -> +> ## Creating an Target Model diff --git a/docs/mindarmour/docs/source_en/mindarmour_install.md b/docs/mindarmour/docs/source_en/mindarmour_install.md index e1d4736a627d342825f15275c666ca9bfbe6c172..9cf05e21c54e01152d1c73f1e4a22502534eea7f 100644 --- a/docs/mindarmour/docs/source_en/mindarmour_install.md +++ b/docs/mindarmour/docs/source_en/mindarmour_install.md @@ -7,7 +7,7 @@ - The hardware platform should be Ascend, GPU or CPU. - See our [MindSpore Installation Guide](https://www.mindspore.cn/install/en) to install MindSpore. The versions of MindSpore Armour and MindSpore must be consistent. -- All other dependencies are included in [setup.py](https://atomgit.com/mindspore-lab/mindarmour/blob/master/setup.py). +- All other dependencies are included in [setup.py](https://atomgit.com/mindspore/mindarmour/blob/master/setup.py). ## Version dependency @@ -15,10 +15,10 @@ Due the dependency between MindSpore Armour and MindSpore, please follow the tab | MindSpore Armour Version | Branch | MindSpore Version | | ------------------ | --------------------------------------------------------- | ----------------- | -| 2.0.0 | [r2.0](https://atomgit.com/mindspore-lab/mindarmour/tree/r2.0/) | >=1.7.0 | -| 1.9.0 | [r1.9](https://atomgit.com/mindspore-lab/mindarmour/tree/r1.9/) | >=1.7.0 | -| 1.8.0 | [r1.8](https://atomgit.com/mindspore-lab/mindarmour/tree/r1.8/) | >=1.7.0 | -| 1.7.0 | [r1.7](https://atomgit.com/mindspore-lab/mindarmour/tree/r1.7/) | 1.7.0 | +| 2.0.0 | [r2.0](https://atomgit.com/mindspore/mindarmour/tree/r2.0/) | >=1.7.0 | +| 1.9.0 | [r1.9](https://atomgit.com/mindspore/mindarmour/tree/r1.9/) | >=1.7.0 | +| 1.8.0 | [r1.8](https://atomgit.com/mindspore/mindarmour/tree/r1.8/) | >=1.7.0 | +| 1.7.0 | [r1.7](https://atomgit.com/mindspore/mindarmour/tree/r1.7/) | 1.7.0 | ## Installation @@ -30,7 +30,7 @@ You can install MindSpore Armour either by pip or by source code. pip install https://ms-release.obs.cn-north-4.myhuaweicloud.com/{version}/MindArmour/any/mindarmour-{version}-py3-none-any.whl --trusted-host ms-release.obs.cn-north-4.myhuaweicloud.com -i https://pypi.tuna.tsinghua.edu.cn/simple ``` -> - When the network is connected, dependency items are automatically downloaded during .whl package installation. (For details about other dependency items, see [setup.py](https://atomgit.com/mindspore-lab/mindarmour/blob/master/setup.py)). In other cases, you need to manually install dependency items. +> - When the network is connected, dependency items are automatically downloaded during .whl package installation. (For details about other dependency items, see [setup.py](https://atomgit.com/mindspore/mindarmour/blob/master/setup.py)). In other cases, you need to manually install dependency items. > - `{version}` denotes the version of MindSpore Armour. For example, when you are downloading MindSpore Armour 1.3.0, `{version}` should be 1.3.0. ### Installation by Source Code diff --git a/docs/mindarmour/docs/source_en/protect_user_privacy_with_differential_privacy.md b/docs/mindarmour/docs/source_en/protect_user_privacy_with_differential_privacy.md index 70a95cd8a0746f0cd1d5b30b9b5e394d9256a075..c5e1c17a5c9d6a0dbc2883677dedc28d6af72c42 100644 --- a/docs/mindarmour/docs/source_en/protect_user_privacy_with_differential_privacy.md +++ b/docs/mindarmour/docs/source_en/protect_user_privacy_with_differential_privacy.md @@ -29,7 +29,7 @@ MindSpore Armour differential privacy module Differential-Privacy implements the The LeNet model and MNIST dataset are used as an example to describe how to use the differential privacy optimizer to train a neural network model on MindSpore. -> Because of the limit of CPU APIs, differential privacy training can only run on GPU or Ascend, except for CPU. This example is for the Atlas training series. You can download the complete sample code from . +> Because of the limit of CPU APIs, differential privacy training can only run on GPU or Ascend, except for CPU. This example is for the Atlas training series. You can download the complete sample code from . ## Implementation @@ -62,7 +62,7 @@ TAG = 'Lenet5_train' ### Configuring Parameters -1. Set the running environment, dataset path, model training parameters, checkpoint storage parameters, and differential privacy parameters. Replace `data_path` with your data path. For more configurations, see . +1. Set the running environment, dataset path, model training parameters, checkpoint storage parameters, and differential privacy parameters. Replace `data_path` with your data path. For more configurations, see . ```python cfg = edict({ diff --git a/docs/mindarmour/docs/source_en/protect_user_privacy_with_suppress_privacy.md b/docs/mindarmour/docs/source_en/protect_user_privacy_with_suppress_privacy.md index 7beeca992bc0febbbfd77292e3bb02863ac1f078..93f92906367a8e21fb414c4b57005e1ee72ffbec 100644 --- a/docs/mindarmour/docs/source_en/protect_user_privacy_with_suppress_privacy.md +++ b/docs/mindarmour/docs/source_en/protect_user_privacy_with_suppress_privacy.md @@ -14,7 +14,7 @@ Suppress-Privacy, a Suppress-Privacy module in MindSpore Armour, implements a su Here is an example showing that how to train a neural network model in MindSpore using the LeNet model, MNIST dataset, and the SuppressourPrivacy optimizer. -> This example is for the Atlas training series and you can download the full sample code at +> This example is for the Atlas training series and you can download the full sample code at ## Implementation @@ -49,7 +49,7 @@ TAG = 'Lenet5_Suppress_train' ### Parameter Configuration -1. Set the runtime environment, model training parameters, checkpoint storage parameters, and the batch_size parameter is recommended not to exceed 64. For more configurations, please refer to . +1. Set the runtime environment, model training parameters, checkpoint storage parameters, and the batch_size parameter is recommended not to exceed 64. For more configurations, please refer to . ```python cfg = edict({ @@ -245,12 +245,12 @@ ds_train = generate_mnist_dataset('MNIST_unzip/train', cfg.batch_size) To evaluate the effect of privacy suppression training on the protection of the dataset, we test it using an image reversal attack. This inverse attack can restore the original image based on the output of the original image at one layer of the neural network, mainly because the network "remembers" the features of the training set during the training process. -The principle of this attack method can be found in and the complete code implementation can be found in , The following describes detailed test steps: +The principle of this attack method can be found in and the complete code implementation can be found in , The following describes detailed test steps: 1. Preparation In order to compare with the suppressed privacy training, we need to get the CheckPoint file of the model using the regular training first. The model training can be referred to - [mindarmour/examples/common/networks/lenet5](https://atomgit.com/mindspore-lab/mindarmour/blob/master/examples/common/networks/lenet5/mnist_train.py), + [mindarmour/examples/common/networks/lenet5](https://atomgit.com/mindspore/mindarmour/blob/master/examples/common/networks/lenet5/mnist_train.py), It has the following directory structure: ```text diff --git a/docs/mindarmour/docs/source_en/test_model_security_fuzzing.md b/docs/mindarmour/docs/source_en/test_model_security_fuzzing.md index 365d8818d5f6cbaf589bdad02d4dc98c79600461..dbed6a6d1f89cf087b3ba1e9a2742ad3870f0515 100644 --- a/docs/mindarmour/docs/source_en/test_model_security_fuzzing.md +++ b/docs/mindarmour/docs/source_en/test_model_security_fuzzing.md @@ -10,7 +10,7 @@ The fuzz testing module of MindSpore Armour uses the neuron coverage rate as the The LeNet model and MNIST dataset are used as an example to describe how to use Fuzz testing. -> This example is for CPUs, GPUs, and Atlas training series. Currently only supports GRAPH_MODE. You can download the complete sample code at . +> This example is for CPUs, GPUs, and Atlas training series. Currently only supports GRAPH_MODE. You can download the complete sample code at . ## Implementation @@ -93,7 +93,7 @@ For details about the API configuration, see the `set_context`. The data mutation method must include the method based on the image pixel value changes. - The first two image transform methods support user-defined configuration parameters and randomly generated parameters by algorithms. For user-defined configuration parameters see the class methods corresponding to . For randomly generated parameters by algorithms you can set method's params to `'auto_param': [True]`. The mutation parameters are randomly generated within the recommended range. + The first two image transform methods support user-defined configuration parameters and randomly generated parameters by algorithms. For user-defined configuration parameters see the class methods corresponding to . For randomly generated parameters by algorithms you can set method's params to `'auto_param': [True]`. The mutation parameters are randomly generated within the recommended range. For details about how to set parameters based on the attack defense method, see the corresponding attack method class. diff --git a/docs/mindarmour/docs/source_en/test_model_security_membership_inference.md b/docs/mindarmour/docs/source_en/test_model_security_membership_inference.md index a73bebf0e785d762c8b797249389773cbb10c6e0..4a62d9c6be2892c9f1a9d666316e29cc7d80faa1 100644 --- a/docs/mindarmour/docs/source_en/test_model_security_membership_inference.md +++ b/docs/mindarmour/docs/source_en/test_model_security_membership_inference.md @@ -12,7 +12,7 @@ The following uses a VGG16 model and CIFAR-100 dataset as an example to describe > This example is for the Atlas training series. You can download the complete sample code in the following link: > -> +> ## Implementation diff --git a/docs/mindarmour/docs/source_zh_cn/concept_drift_images.md b/docs/mindarmour/docs/source_zh_cn/concept_drift_images.md index 7363a1582eb3ea31742920975ea3c4fa49cc0480..b25c5c192fadc4566ba87e7d8279cff6c11ec41d 100644 --- a/docs/mindarmour/docs/source_zh_cn/concept_drift_images.md +++ b/docs/mindarmour/docs/source_zh_cn/concept_drift_images.md @@ -17,7 +17,7 @@ 5. 执行概念漂移检测函数。 6. 查看结果。 -> 本例面向CPU、GPU、Atlas训练系列产品，目前仅支持GRAPH_MODE。你可以在这里找到完整可运行的样例代码：。 +> 本例面向CPU、GPU、Atlas训练系列产品，目前仅支持GRAPH_MODE。你可以在这里找到完整可运行的样例代码：。 ## 准备环节 diff --git a/docs/mindarmour/docs/source_zh_cn/concept_drift_time_series.md b/docs/mindarmour/docs/source_zh_cn/concept_drift_time_series.md index accb9dfde6e77bb415dc642851fe43a43af1c32e..a159dafb88c9203683f429385bc4b10341694fee 100644 --- a/docs/mindarmour/docs/source_zh_cn/concept_drift_time_series.md +++ b/docs/mindarmour/docs/source_zh_cn/concept_drift_time_series.md @@ -16,7 +16,7 @@ 3. 调用概念漂移检测函数。 4. 查看结果。 -> 你可以在这里找到完整可运行的样例代码：。 +> 你可以在这里找到完整可运行的样例代码：。 ## 准备环节 diff --git a/docs/mindarmour/docs/source_zh_cn/differential_privacy_design.md b/docs/mindarmour/docs/source_zh_cn/differential_privacy_design.md index 5c4f71987195792902346dd015ed22356b82d501..85dc0425d80db0b3a0d33008b4b48d674390e23b 100644 --- a/docs/mindarmour/docs/source_zh_cn/differential_privacy_design.md +++ b/docs/mindarmour/docs/source_zh_cn/differential_privacy_design.md @@ -40,10 +40,10 @@ Monitor提供RDP、ZCDP等回调函数，用于监测模型的差分隐私预算 ## 代码实现 -- [mechanisms.py](https://atomgit.com/mindspore-lab/mindarmour/blob/master/mindarmour/privacy/diff_privacy/mechanisms/mechanisms.py)：这个文件实现了差分隐私训练所需的噪声生成机制，包括简单高斯噪声、自适应高斯噪声、自适应裁剪高斯噪声等。 -- [optimizer.py](https://atomgit.com/mindspore-lab/mindarmour/blob/master/mindarmour/privacy/diff_privacy/optimizer/optimizer.py)：这个文件实现了使用噪声生成机制在反向传播时添加噪声的根本逻辑。 -- [monitor.py](https://atomgit.com/mindspore-lab/mindarmour/blob/master/mindarmour/privacy/diff_privacy/monitor/monitor.py)：实现了计算差分隐私预算的回调函数，模型训练过程中，会反馈当前的差分隐私预算。 -- [model.py](https://atomgit.com/mindspore-lab/mindarmour/blob/master/mindarmour/privacy/diff_privacy/train/model.py)：这个文件实现了计算损失和梯度的逻辑，差分隐私训练的梯度截断逻辑在此文件中实现，且model.py是用户使用差分隐私训练能力的入口。 +- [mechanisms.py](https://atomgit.com/mindspore/mindarmour/blob/master/mindarmour/privacy/diff_privacy/mechanisms/mechanisms.py)：这个文件实现了差分隐私训练所需的噪声生成机制，包括简单高斯噪声、自适应高斯噪声、自适应裁剪高斯噪声等。 +- [optimizer.py](https://atomgit.com/mindspore/mindarmour/blob/master/mindarmour/privacy/diff_privacy/optimizer/optimizer.py)：这个文件实现了使用噪声生成机制在反向传播时添加噪声的根本逻辑。 +- [monitor.py](https://atomgit.com/mindspore/mindarmour/blob/master/mindarmour/privacy/diff_privacy/monitor/monitor.py)：实现了计算差分隐私预算的回调函数，模型训练过程中，会反馈当前的差分隐私预算。 +- [model.py](https://atomgit.com/mindspore/mindarmour/blob/master/mindarmour/privacy/diff_privacy/train/model.py)：这个文件实现了计算损失和梯度的逻辑，差分隐私训练的梯度截断逻辑在此文件中实现，且model.py是用户使用差分隐私训练能力的入口。 ## 参考文献 diff --git a/docs/mindarmour/docs/source_zh_cn/evaluation_of_CNNCTC.md b/docs/mindarmour/docs/source_zh_cn/evaluation_of_CNNCTC.md index 5dfa7990177744d28ed7d9252cb0854e2af14fd1..af3e8f716d78397911eafbdd1f615e6fb0cfaf81 100644 --- a/docs/mindarmour/docs/source_zh_cn/evaluation_of_CNNCTC.md +++ b/docs/mindarmour/docs/source_zh_cn/evaluation_of_CNNCTC.md @@ -6,7 +6,7 @@ 本教程主要演示利用自然扰动serving服务，对OCR模型CNN-CTC做一个简单的鲁棒性评测。先基于serving生成多种自然扰动样本数据集，然后根据CNN-CTC模型在自然扰动样本数据集上的表现来评估模型的鲁棒性。 -> 你可以在这里找到完整可运行的样例代码：。 +> 你可以在这里找到完整可运行的样例代码：。 ## 环境要求 @@ -63,7 +63,7 @@ ### 基于自然扰动serving生成评测数据集 -1. 启动自然扰动serving服务。具体说明参考：[自然扰动样本生成serving服务](https://atomgit.com/mindspore-lab/mindarmour/blob/master/examples/natural_robustness/serving/README.md#) +1. 启动自然扰动serving服务。具体说明参考：[自然扰动样本生成serving服务](https://atomgit.com/mindspore/mindarmour/blob/master/examples/natural_robustness/serving/README.md#) ```bash cd serving/server/ @@ -81,7 +81,7 @@ 2. 核心代码说明： - 1. 配置扰动方法，目前可选的扰动方法及参数配置参考[image transform methods](https://atomgit.com/mindspore-lab/mindarmour/tree/master/mindarmour/natural_robustness/transform/image)。下面是一个配置例子。 + 1. 配置扰动方法，目前可选的扰动方法及参数配置参考[image transform methods](https://atomgit.com/mindspore/mindarmour/tree/master/mindarmour/natural_robustness/transform/image)。下面是一个配置例子。 ```python PerturbConfig = [ diff --git a/docs/mindarmour/docs/source_zh_cn/fault_injection.md b/docs/mindarmour/docs/source_zh_cn/fault_injection.md index d72342eb16ee4f6462f8ecde8c6ef87445e29ac0..2932360e0090f8851627d7ce4745079893556910 100644 --- a/docs/mindarmour/docs/source_zh_cn/fault_injection.md +++ b/docs/mindarmour/docs/source_zh_cn/fault_injection.md @@ -18,7 +18,7 @@ 3. 调用故障注入模块。 4. 查看结果。 -> 你可以在这里找到完整可运行的样例代码：。 +> 你可以在这里找到完整可运行的样例代码：。 ## 准备环节 diff --git a/docs/mindarmour/docs/source_zh_cn/fuzzer_design.md b/docs/mindarmour/docs/source_zh_cn/fuzzer_design.md index 4134dc709cc3ddd4e5a7a98f0a34766dda365d95..954c2351330373ae1043bf864dd09117858247cc 100644 --- a/docs/mindarmour/docs/source_zh_cn/fuzzer_design.md +++ b/docs/mindarmour/docs/source_zh_cn/fuzzer_design.md @@ -51,10 +51,10 @@ Fuzz Testing架构主要包括三个模块： ## 代码实现 -1. [fuzzing.py](https://atomgit.com/mindspore-lab/mindarmour/blob/master/mindarmour/fuzz_testing/fuzzing.py)：Fuzzer总体流程。 -2. [model_coverage_metrics.py](https://atomgit.com/mindspore-lab/mindarmour/blob/master/mindarmour/fuzz_testing/model_coverage_metrics.py)：神经元覆盖率指标，包括KMNC，NBC，SNAC。 -3. [image transform methods](https://atomgit.com/mindspore-lab/mindarmour/tree/master/mindarmour/natural_robustness/transform/image)：图像变异方法，包括多种加噪、模糊、亮度调整、仿射变化方法。 -4. [adversarial attacks](https://atomgit.com/mindspore-lab/mindarmour/tree/master/mindarmour/adv_robustness/attacks)：对抗样本攻击方法，包含多种黑盒、白盒攻击方法。 +1. [fuzzing.py](https://atomgit.com/mindspore/mindarmour/blob/master/mindarmour/fuzz_testing/fuzzing.py)：Fuzzer总体流程。 +2. [model_coverage_metrics.py](https://atomgit.com/mindspore/mindarmour/blob/master/mindarmour/fuzz_testing/model_coverage_metrics.py)：神经元覆盖率指标，包括KMNC，NBC，SNAC。 +3. [image transform methods](https://atomgit.com/mindspore/mindarmour/tree/master/mindarmour/natural_robustness/transform/image)：图像变异方法，包括多种加噪、模糊、亮度调整、仿射变化方法。 +4. [adversarial attacks](https://atomgit.com/mindspore/mindarmour/tree/master/mindarmour/adv_robustness/attacks)：对抗样本攻击方法，包含多种黑盒、白盒攻击方法。 ## 参考文献 diff --git a/docs/mindarmour/docs/source_zh_cn/improve_model_security_nad.md b/docs/mindarmour/docs/source_zh_cn/improve_model_security_nad.md index 9f08e6c433ab2016313d9e687fcb5f1f9afd58a4..d8d39841142f4b0dfcabc2ecdc02341d3d139d44 100644 --- a/docs/mindarmour/docs/source_zh_cn/improve_model_security_nad.md +++ b/docs/mindarmour/docs/source_zh_cn/improve_model_security_nad.md @@ -15,7 +15,7 @@ AI算法设计之初普遍未考虑相关的安全威胁，使得AI算法的判 这里通过图像分类任务上的对抗性攻防，以攻击算法FGSM和防御算法NAD为例，介绍MindSpore Armour在对抗攻防上的使用方法。 > 本例面向CPU、GPU、Atlas训练系列产品，你可以在这里下载完整的样例代码： -> +> ## 建立被攻击模型 diff --git a/docs/mindarmour/docs/source_zh_cn/mindarmour_install.md b/docs/mindarmour/docs/source_zh_cn/mindarmour_install.md index f9adae612f53d233c6b75a5958db8ba513d8b663..9d484d5a5a1139271e59d73615261231ff3e6272 100644 --- a/docs/mindarmour/docs/source_zh_cn/mindarmour_install.md +++ b/docs/mindarmour/docs/source_zh_cn/mindarmour_install.md @@ -7,7 +7,7 @@ - 硬件平台为Ascend、GPU或CPU。 - 参考[MindSpore安装指南](https://www.mindspore.cn/install)，完成MindSpore的安装。 MindSpore Armour与MindSpore的版本需保持一致。 -- 其余依赖请参见[setup.py](https://atomgit.com/mindspore-lab/mindarmour/blob/master/setup.py)。 +- 其余依赖请参见[setup.py](https://atomgit.com/mindspore/mindarmour/blob/master/setup.py)。 ## MindSpore版本依赖关系 @@ -15,10 +15,10 @@ | MindSpore Armour | 分支 | MindSpore | | ---------- | --------------------------------------------------------- | --------- | -| 2.0.0 | [r2.0](https://atomgit.com/mindspore-lab/mindarmour/tree/r2.0/) | >=1.7.0 | -| 1.9.0 | [r1.9](https://atomgit.com/mindspore-lab/mindarmour/tree/r1.9/) | >=1.7.0 | -| 1.8.0 | [r1.8](https://atomgit.com/mindspore-lab/mindarmour/tree/r1.8/) | >=1.7.0 | -| 1.7.0 | [r1.7](https://atomgit.com/mindspore-lab/mindarmour/tree/r1.7/) | 1.7.0 | +| 2.0.0 | [r2.0](https://atomgit.com/mindspore/mindarmour/tree/r2.0/) | >=1.7.0 | +| 1.9.0 | [r1.9](https://atomgit.com/mindspore/mindarmour/tree/r1.9/) | >=1.7.0 | +| 1.8.0 | [r1.8](https://atomgit.com/mindspore/mindarmour/tree/r1.8/) | >=1.7.0 | +| 1.7.0 | [r1.7](https://atomgit.com/mindspore/mindarmour/tree/r1.7/) | 1.7.0 | ## 安装方式 @@ -30,7 +30,7 @@ pip install https://ms-release.obs.cn-north-4.myhuaweicloud.com/{version}/MindArmour/any/mindarmour-{version}-py3-none-any.whl --trusted-host ms-release.obs.cn-north-4.myhuaweicloud.com -i https://pypi.tuna.tsinghua.edu.cn/simple ``` -> - 在联网状态下，安装whl包时会自动下载MindSpore Armour安装包的依赖项（依赖项详情参见[setup.py](https://atomgit.com/mindspore-lab/mindarmour/blob/master/setup.py)），其余情况需自行安装。 +> - 在联网状态下，安装whl包时会自动下载MindSpore Armour安装包的依赖项（依赖项详情参见[setup.py](https://atomgit.com/mindspore/mindarmour/blob/master/setup.py)），其余情况需自行安装。 > - `{version}`表示MindSpore Armour版本号，例如下载1.3.0版本MindSpore Armour时，`{version}`应写为1.3.0。 ### 源码安装 diff --git a/docs/mindarmour/docs/source_zh_cn/protect_user_privacy_with_differential_privacy.md b/docs/mindarmour/docs/source_zh_cn/protect_user_privacy_with_differential_privacy.md index c51cab3ff1d105482f0e28a75325a9fc8f2e183f..e5cbb5863cb33f7b2675c607688feef06a77477c 100644 --- a/docs/mindarmour/docs/source_zh_cn/protect_user_privacy_with_differential_privacy.md +++ b/docs/mindarmour/docs/source_zh_cn/protect_user_privacy_with_differential_privacy.md @@ -30,7 +30,7 @@ MindSpore Armour的差分隐私模块Differential-Privacy，实现了差分隐 这里以LeNet模型，MNIST 数据集为例，说明如何在MindSpore上使用差分隐私优化器训练神经网络模型。 > 由于API支持的限制，差分隐私训练目前只支持在GPU或者Ascend服务器上面进行，不支持CPU。 -本例面向Atlas训练系列产品，你可以在这里下载完整的样例代码： +本例面向Atlas训练系列产品，你可以在这里下载完整的样例代码： ## 实现阶段 @@ -63,7 +63,7 @@ TAG = 'Lenet5_train' ### 参数配置 -1. 设置运行环境、数据集路径、模型训练参数、checkpoint存储参数、差分隐私参数，`data_path`数据路径替换成你的数据集所在路径。更多配置可以参考。 +1. 设置运行环境、数据集路径、模型训练参数、checkpoint存储参数、差分隐私参数，`data_path`数据路径替换成你的数据集所在路径。更多配置可以参考。 ```python cfg = edict({ diff --git a/docs/mindarmour/docs/source_zh_cn/protect_user_privacy_with_suppress_privacy.md b/docs/mindarmour/docs/source_zh_cn/protect_user_privacy_with_suppress_privacy.md index 77561ac9cf14b8fa50ba3306a4b75bd2b093814d..88586dc0b2d9ddd096cb7ad6edd7f22aed73501e 100644 --- a/docs/mindarmour/docs/source_zh_cn/protect_user_privacy_with_suppress_privacy.md +++ b/docs/mindarmour/docs/source_zh_cn/protect_user_privacy_with_suppress_privacy.md @@ -12,7 +12,7 @@ MindSpore Armour的抑制隐私模块Suppress-Privacy，实现了抑制隐私优 这里以LeNet模型，MNIST 数据集为例，说明如何在MindSpore上使用抑制隐私优化器训练神经网络模型。 -> 本例面向Atlas训练系列产品，你可以在这里下载完整的样例代码： +> 本例面向Atlas训练系列产品，你可以在这里下载完整的样例代码： ## 实现阶段 @@ -48,7 +48,7 @@ TAG = 'Lenet5_Suppress_train' ### 参数配置 -1. 设置运行环境、模型训练参数、checkpoint存储参数，batch_size参数建议不要超过64。更多配置可以参考。 +1. 设置运行环境、模型训练参数、checkpoint存储参数，batch_size参数建议不要超过64。更多配置可以参考。 ```python cfg = edict({ @@ -243,13 +243,13 @@ ds_train = generate_mnist_dataset('MNIST_unzip/train', cfg.batch_size) 为了评估抑制隐私训练对数据集的保护效果，我们使用图像逆向攻击进行测试， 这种逆向攻击可以根据原始图片在神经网络某一层的输出来反向还原出原始图片，主要原因是网络在训练的过程中“记住”了训练集的特征， -这种攻击方法的原理可以参考，完整的代码实现可以参考 +这种攻击方法的原理可以参考，完整的代码实现可以参考 ，下面介绍详细的测试步骤： 1. 准备工作 为了和抑制隐私训练进行对比，我们需要先使用常规训练得到模型的CheckPoint文件。模型训练可以参考 - [mindarmour/examples/common/networks/lenet5](https://atomgit.com/mindspore-lab/mindarmour/blob/master/examples/common/networks/lenet5/mnist_train.py) ， + [mindarmour/examples/common/networks/lenet5](https://atomgit.com/mindspore/mindarmour/blob/master/examples/common/networks/lenet5/mnist_train.py) ， 它的目录结构如下： ```text diff --git a/docs/mindarmour/docs/source_zh_cn/test_model_security_fuzzing.md b/docs/mindarmour/docs/source_zh_cn/test_model_security_fuzzing.md index 07bca6d962d01bbf243e1bf367dd7502a1466809..9292baa31e9573694fd3dc3485c0fdc8ceb09920 100644 --- a/docs/mindarmour/docs/source_zh_cn/test_model_security_fuzzing.md +++ b/docs/mindarmour/docs/source_zh_cn/test_model_security_fuzzing.md @@ -10,7 +10,7 @@ MindSpore Armour的fuzz_testing模块以神经元覆盖率作为测试评价准 这里以LeNet模型，MNIST数据集为例，说明如何使用Fuzzer。 -> 本例面向CPU、GPU、Atlas训练系列产品，目前仅支持GRAPH_MODE。你可以在这里下载完整的样例代码：。 +> 本例面向CPU、GPU、Atlas训练系列产品，目前仅支持GRAPH_MODE。你可以在这里下载完整的样例代码：。 ## 实现阶段 @@ -93,7 +93,7 @@ ms.set_context(mode=ms.GRAPH_MODE, device_target="Ascend") 数据变异方法中一定要包含基于图像像素值变化的方法。 - 前两种类型的图像变化方法，支持用户自定义配置参数，也支持算法随机选择参数。用户自定义参数配置范围请参考: + 前两种类型的图像变化方法，支持用户自定义配置参数，也支持算法随机选择参数。用户自定义参数配置范围请参考: 中对应的类方法。算法随机选择参数，则`params`设置为`'auto_param': [True]`，参数将在推荐范围内随机生成。 基于对抗攻击方法的参数配置请参考对应的攻击方法类。 diff --git a/docs/mindarmour/docs/source_zh_cn/test_model_security_membership_inference.md b/docs/mindarmour/docs/source_zh_cn/test_model_security_membership_inference.md index 594a48e68833a9cd943c19bc35ead5c10d43de8b..6e74e8f6a91c8b390670a1b75aef67797e2d40d1 100644 --- a/docs/mindarmour/docs/source_zh_cn/test_model_security_membership_inference.md +++ b/docs/mindarmour/docs/source_zh_cn/test_model_security_membership_inference.md @@ -12,7 +12,7 @@ >本例面向Atlas训练系列产品，您可以在这里下载完整的样例代码： > -> +> ## 实现阶段 diff --git a/docs/mindchemistry/docs/source_en/index.rst b/docs/mindchemistry/docs/source_en/index.rst index 2946e59a30fcd8969b17b03f09f774c40bbb684b..227acfc86d3d87905af3ebbdd786fbc8f6f3ef29 100644 --- a/docs/mindchemistry/docs/source_en/index.rst +++ b/docs/mindchemistry/docs/source_en/index.rst @@ -172,7 +172,7 @@ Contribution Guide ------------------ - Please click here to see how to contribute your code: `Contribution - Guide `__ + Guide `__ License ------- diff --git a/docs/mindchemistry/docs/source_en/quick_start/quick_start.ipynb b/docs/mindchemistry/docs/source_en/quick_start/quick_start.ipynb index 151cb2584f32b90831b5181a410a74ffc7b82d4c..7eb7b5dc38920bdfd7a05a20a7758bc0144a7cb7 100644 --- a/docs/mindchemistry/docs/source_en/quick_start/quick_start.ipynb +++ b/docs/mindchemistry/docs/source_en/quick_start/quick_start.ipynb @@ -81,7 +81,7 @@ "cell_type": "markdown", "metadata": {}, "source": [ - "The following `src` can be downloaded in [allegro/src](https://atomgit.com/mindspore-lab/mindscience/tree/master/MindChemistry/applications/allegro/src)." + "The following `src` can be downloaded in [allegro/src](https://atomgit.com/mindspore/mindscience/tree/master/MindChemistry/applications/allegro/src)." ] }, { @@ -115,7 +115,7 @@ "cell_type": "markdown", "metadata": {}, "source": [ - "You can get parameters of model, data and optimizer from [config](https://atomgit.com/mindspore-lab/mindscience/blob/master/MindChemistry/applications/allegro/rmd.yaml)." + "You can get parameters of model, data and optimizer from [config](https://atomgit.com/mindspore/mindscience/blob/master/MindChemistry/applications/allegro/rmd.yaml)." ] }, { diff --git a/docs/mindchemistry/docs/source_en/user/molecular_prediction.md b/docs/mindchemistry/docs/source_en/user/molecular_prediction.md index 79a8aa1299c3ec6c599d5148749475fb74eaa563..679ee4119611e81878153a9f0a2958277c38958c 100644 --- a/docs/mindchemistry/docs/source_en/user/molecular_prediction.md +++ b/docs/mindchemistry/docs/source_en/user/molecular_prediction.md @@ -10,7 +10,7 @@ Prediction of crystalline material properties. We integrate the Matformer model | Function | Model | Training | Inferring | Back-end | |:--------------------------------|:------------------------------------------------------------------------------------------------------| :--- | :--- |:---------| -| Property prediction | [Nequip](https://atomgit.com/mindspore-lab/mindscience/tree/master/MindChemistry/applications/nequip) | √ | √ | Ascend | -| Property prediction | [Allgro](https://atomgit.com/mindspore-lab/mindscience/tree/master/MindChemistry/applications/allegro) | √ | √ | Ascend | -| Electronic structure prediction | [Deephe3nn](https://atomgit.com/mindspore-lab/mindscience/tree/master/MindChemistry/applications/deephe3nn) | √ | √ | Ascend | -| Prediction of crystalline material properties | [Matformer](https://atomgit.com/mindspore-lab/mindscience/tree/master/MindChemistry/applications/matformer) | √ | √ | Ascend | \ No newline at end of file +| Property prediction | [Nequip](https://atomgit.com/mindspore/mindscience/tree/master/MindChemistry/applications/nequip) | √ | √ | Ascend | +| Property prediction | [Allgro](https://atomgit.com/mindspore/mindscience/tree/master/MindChemistry/applications/allegro) | √ | √ | Ascend | +| Electronic structure prediction | [Deephe3nn](https://atomgit.com/mindspore/mindscience/tree/master/MindChemistry/applications/deephe3nn) | √ | √ | Ascend | +| Prediction of crystalline material properties | [Matformer](https://atomgit.com/mindspore/mindscience/tree/master/MindChemistry/applications/matformer) | √ | √ | Ascend | \ No newline at end of file diff --git a/docs/mindchemistry/docs/source_en/user/structure_generation.md b/docs/mindchemistry/docs/source_en/user/structure_generation.md index a5ac020932561c6f6006250ea327f3531cfcbd17..19f6dcc16cac7d4f637fbda8307c188fa155e8f7 100644 --- a/docs/mindchemistry/docs/source_en/user/structure_generation.md +++ b/docs/mindchemistry/docs/source_en/user/structure_generation.md @@ -8,4 +8,4 @@ Structure generation, which is a structure generation model based on deep learni | Function | Model | Training | Inferring | Back-end | |:---------------------| :-------------------- | :--- | :--- |:-----------| -| structure generation | [DiffCSP](https://atomgit.com/mindspore-lab/mindscience/tree/master/MindChemistry/applications/diffcsp) | √ | √ | Ascend | +| structure generation | [DiffCSP](https://atomgit.com/mindspore/mindscience/tree/master/MindChemistry/applications/diffcsp) | √ | √ | Ascend | diff --git a/docs/mindchemistry/docs/source_zh_cn/index.rst b/docs/mindchemistry/docs/source_zh_cn/index.rst index a3f3fdde676eb18a5de5f0789d2f4ee6526a195e..d224173b0ea3b763361da8990fc8f373c4c8004e 100644 --- a/docs/mindchemistry/docs/source_zh_cn/index.rst +++ b/docs/mindchemistry/docs/source_zh_cn/index.rst @@ -133,7 +133,7 @@ wujian, wangyuheng, Lin Peijia, gengchenhua, caowenbin, Siyu Yang 贡献指南 -------- -- 如何贡献您的代码，请点击此处查看：\ `贡献指南 `__ +- 如何贡献您的代码，请点击此处查看：\ `贡献指南 `__ 许可证 ------ diff --git a/docs/mindchemistry/docs/source_zh_cn/quick_start/quick_start.ipynb b/docs/mindchemistry/docs/source_zh_cn/quick_start/quick_start.ipynb index fddd9281bcba2843d136946a1916d48b969e95e4..1cbb70dc43564e4e093a250d78481e4d14d12812 100644 --- a/docs/mindchemistry/docs/source_zh_cn/quick_start/quick_start.ipynb +++ b/docs/mindchemistry/docs/source_zh_cn/quick_start/quick_start.ipynb @@ -81,7 +81,7 @@ "cell_type": "markdown", "metadata": {}, "source": [ - "下述`src`可以在[allegro/src](https://atomgit.com/mindspore-lab/mindscience/tree/master/MindChemistry/applications/allegro/src)下载。" + "下述`src`可以在[allegro/src](https://atomgit.com/mindspore/mindscience/tree/master/MindChemistry/applications/allegro/src)下载。" ] }, { @@ -115,7 +115,7 @@ "cell_type": "markdown", "metadata": {}, "source": [ - "模型涉及的参数、优化器、数据配置见[config](https://atomgit.com/mindspore-lab/mindscience/blob/master/MindChemistry/applications/allegro/rmd.yaml)。" + "模型涉及的参数、优化器、数据配置见[config](https://atomgit.com/mindspore/mindscience/blob/master/MindChemistry/applications/allegro/rmd.yaml)。" ] }, { diff --git a/docs/mindchemistry/docs/source_zh_cn/user/molecular_prediction.md b/docs/mindchemistry/docs/source_zh_cn/user/molecular_prediction.md index d621cb850735515fee1366246b695ef004ecc1fc..f53e7e99ae5d052161c1da23badb7877815d9e74 100644 --- a/docs/mindchemistry/docs/source_zh_cn/user/molecular_prediction.md +++ b/docs/mindchemistry/docs/source_zh_cn/user/molecular_prediction.md @@ -10,7 +10,7 @@ | 功能 | 模型 | 训练 | 推理 | 后端 | | :------------- |:----------------------------------------------------------------------------------------------------------------| :--- | :--- | :-------- | -| 分子预测| [Nequip](https://atomgit.com/mindspore-lab/mindscience/tree/master/MindChemistry/applications/nequip) | √ | √ | Ascend | -| 分子预测| [Allgro](https://atomgit.com/mindspore-lab/mindscience/tree/master/MindChemistry/applications/allegro) | √ | √ | Ascend | -| 电子结构预测| [Deephe3nn](https://atomgit.com/mindspore-lab/mindscience/tree/master/MindChemistry/applications/deephe3nn) | √ | √ | Ascend | -| 晶体材料性质预测| [Matformer](https://atomgit.com/mindspore-lab/mindscience/tree/master/MindChemistry/applications/matformer) | √ | √ | Ascend | \ No newline at end of file +| 分子预测| [Nequip](https://atomgit.com/mindspore/mindscience/tree/master/MindChemistry/applications/nequip) | √ | √ | Ascend | +| 分子预测| [Allgro](https://atomgit.com/mindspore/mindscience/tree/master/MindChemistry/applications/allegro) | √ | √ | Ascend | +| 电子结构预测| [Deephe3nn](https://atomgit.com/mindspore/mindscience/tree/master/MindChemistry/applications/deephe3nn) | √ | √ | Ascend | +| 晶体材料性质预测| [Matformer](https://atomgit.com/mindspore/mindscience/tree/master/MindChemistry/applications/matformer) | √ | √ | Ascend | \ No newline at end of file diff --git a/docs/mindchemistry/docs/source_zh_cn/user/structure_generation.md b/docs/mindchemistry/docs/source_zh_cn/user/structure_generation.md index c16dac7852278b3b5d04074d6b3d1229ab33f487..ae4a65a8795e343a6f54e561a1435fa429417e39 100644 --- a/docs/mindchemistry/docs/source_zh_cn/user/structure_generation.md +++ b/docs/mindchemistry/docs/source_zh_cn/user/structure_generation.md @@ -8,4 +8,4 @@ | 功能 | 模型 | 训练 | 推理 | 后端 | | :------------- | :-------------------- | :--- | :--- | :-------- | -| 结构生成| [DiffCSP](https://atomgit.com/mindspore-lab/mindscience/tree/master/MindChemistry/applications/diffcsp) | √ | √ | Ascend | +| 结构生成| [DiffCSP](https://atomgit.com/mindspore/mindscience/tree/master/MindChemistry/applications/diffcsp) | √ | √ | Ascend | diff --git a/docs/mindearth/docs/source_en/dem-super-resolution/DEM-SRNet.ipynb b/docs/mindearth/docs/source_en/dem-super-resolution/DEM-SRNet.ipynb index 43c53db2c3ec873aec859c81be6967e1b955ac04..80e1998190f5425cb5be480ac63bf1864ef452b8 100644 --- a/docs/mindearth/docs/source_en/dem-super-resolution/DEM-SRNet.ipynb +++ b/docs/mindearth/docs/source_en/dem-super-resolution/DEM-SRNet.ipynb @@ -84,7 +84,7 @@ "id": "663eb08c-8528-4d7b-83d3-a45247e4c20b", "metadata": {}, "source": [ - "The following `src` can be downloaded in [DEM super-resolution/src](https://atomgit.com/mindspore-lab/mindscience/tree/master/MindEarth/applications/dem-super-resolution/src)." + "The following `src` can be downloaded in [DEM super-resolution/src](https://atomgit.com/mindspore/mindscience/tree/master/MindEarth/applications/dem-super-resolution/src)." ] }, { @@ -105,7 +105,7 @@ "id": "9d5a5b11-f2b6-412d-b70b-cd7f65b61863", "metadata": {}, "source": [ - "You can get parameters of model, data and optimizer from [DEM-SRNet.yaml](https://atomgit.com/mindspore-lab/mindscience/blob/master/MindEarth/applications/dem-super-resolution/DEM-SRNet.yaml)." + "You can get parameters of model, data and optimizer from [DEM-SRNet.yaml](https://atomgit.com/mindspore/mindscience/blob/master/MindEarth/applications/dem-super-resolution/DEM-SRNet.yaml)." ] }, { @@ -139,7 +139,7 @@ "\n", "Download the training, validation and test datasets from [dataset](https://download.mindspore.cn/mindscience/mindearth/dataset/dem_dataset.zip) to `./dataset`.\n", "\n", - "Modify the parameter of `root_dir` in the [DEM-SRNet.yaml](https://atomgit.com/mindspore-lab/mindscience/blob/master/MindEarth/applications/dem-super-resolution/DEM-SRNet.yaml), which set the directory for dataset.\n", + "Modify the parameter of `root_dir` in the [DEM-SRNet.yaml](https://atomgit.com/mindspore/mindscience/blob/master/MindEarth/applications/dem-super-resolution/DEM-SRNet.yaml), which set the directory for dataset.\n", "\n", "The `./dataset` is hosted with the following directory structure:\n", "\n", diff --git a/docs/mindearth/docs/source_en/index.rst b/docs/mindearth/docs/source_en/index.rst index 1887a5433183ca0e3ca33f3ba93e6520ec895cf9..1284659cee03d586379739435d03105a65c4b228 100644 --- a/docs/mindearth/docs/source_en/index.rst +++ b/docs/mindearth/docs/source_en/index.rst @@ -3,13 +3,13 @@ MindSpore Earth Introduction Weather phenomena are closely related to human production and life, social economy, military activities and other aspects. Accurate weather forecasts can mitigate the impact of disaster weather events, avoid economic losses, and generate continuous fiscal revenue, such as energy, agriculture, transportation and entertainment industries. At present, the weather forecast mainly adopts numerical weather prediction models, which processes the observation data collected by meteorological satellites, observation stations and radars, solves the atmospheric dynamic equations describing weather evolution, and then provides weather and climate prediction information. The prediction process of numerical prediction model involves a lot of computation, which consumes a long time and a large amount of computation resources. Compared with the numerical prediction model, the data-driven deep learning model can effectively reduce the computational cost by several orders of magnitude. -`MindSpore Earth `_ is an earth science suite developed based on MindSpore. It supports AI meteorological prediction of short-term, medium-term, and long-term weather and catastrophic weather such as precipitation and typhoon. The aim is to provide efficient and easy-to-use AI meteorological prediction software for industrial scientific research engineers, college teachers and students. +`MindSpore Earth `_ is an earth science suite developed based on MindSpore. It supports AI meteorological prediction of short-term, medium-term, and long-term weather and catastrophic weather such as precipitation and typhoon. The aim is to provide efficient and easy-to-use AI meteorological prediction software for industrial scientific research engineers, college teachers and students. .. raw:: html -Code repository address: +Code repository address: .. toctree:: :glob: diff --git a/docs/mindearth/docs/source_en/medium-range/FourCastNet.ipynb b/docs/mindearth/docs/source_en/medium-range/FourCastNet.ipynb index c8a9a6804352571b1d677baa7011193561f08531..c5b1185b4de1490c9383e2e61c8eada4d66248db 100644 --- a/docs/mindearth/docs/source_en/medium-range/FourCastNet.ipynb +++ b/docs/mindearth/docs/source_en/medium-range/FourCastNet.ipynb @@ -111,7 +111,7 @@ "cell_type": "markdown", "metadata": {}, "source": [ - "The following `src` can be downloaded in [FourCastNet/src](https://atomgit.com/mindspore-lab/mindscience/tree/master/MindEarth/applications/medium-range/fourcastnet/src)." + "The following `src` can be downloaded in [FourCastNet/src](https://atomgit.com/mindspore/mindscience/tree/master/MindEarth/applications/medium-range/fourcastnet/src)." ] }, { @@ -137,7 +137,7 @@ "cell_type": "markdown", "metadata": {}, "source": [ - "You can get parameters of model, data and optimizer from [FourCastNet.yaml](https://atomgit.com/mindspore-lab/mindscience/blob/master/MindEarth/applications/medium-range/fourcastnet/configs/FourCastNet.yaml)." + "You can get parameters of model, data and optimizer from [FourCastNet.yaml](https://atomgit.com/mindspore/mindscience/blob/master/MindEarth/applications/medium-range/fourcastnet/configs/FourCastNet.yaml)." ] }, { @@ -182,7 +182,7 @@ "\n", "Download the statistic, training and validation dataset from [dataset](https://download.mindspore.cn/mindscience/mindearth/dataset/WeatherBench_1.4_69/) to `./dataset`.\n", "\n", - "Modify the parameter of `root_dir` in the [FourCastNet.yaml](https://atomgit.com/mindspore-lab/mindscience/blob/master/MindEarth/applications/medium-range/fourcastnet/configs/FourCastNet.yaml), which sets the directory for dataset.\n", + "Modify the parameter of `root_dir` in the [FourCastNet.yaml](https://atomgit.com/mindspore/mindscience/blob/master/MindEarth/applications/medium-range/fourcastnet/configs/FourCastNet.yaml), which sets the directory for dataset.\n", "\n", "The `./dataset` is hosted with the following directory structure:\n", "\n", diff --git a/docs/mindearth/docs/source_en/medium-range/fuxi.ipynb b/docs/mindearth/docs/source_en/medium-range/fuxi.ipynb index 96efe16c4181f6678bff20b6ff3822f32686157e..a47f017c8e6873790432b0d480a7d9b3cce2a702 100644 --- a/docs/mindearth/docs/source_en/medium-range/fuxi.ipynb +++ b/docs/mindearth/docs/source_en/medium-range/fuxi.ipynb @@ -89,7 +89,7 @@ "id": "062e7adc", "metadata": {}, "source": [ - "The following `src` can be downloaded in [fuxi/src](https://atomgit.com/mindspore-lab/mindscience/tree/master/MindEarth/applications/medium-range/fuxi/src)." + "The following `src` can be downloaded in [fuxi/src](https://atomgit.com/mindspore/mindscience/tree/master/MindEarth/applications/medium-range/fuxi/src)." ] }, { @@ -123,7 +123,7 @@ "id": "18b670e4", "metadata": {}, "source": [ - "You can get parameters of model, data and optimizer from [config](https://atomgit.com/mindspore-lab/mindscience/raw/master/MindEarth/applications/medium-range/fuxi/configs/FuXi.yaml)." + "You can get parameters of model, data and optimizer from [config](https://atomgit.com/mindspore/mindscience/raw/master/MindEarth/applications/medium-range/fuxi/configs/FuXi.yaml)." ] }, { diff --git a/docs/mindearth/docs/source_en/medium-range/graphcast.ipynb b/docs/mindearth/docs/source_en/medium-range/graphcast.ipynb index 7be860a6363a7a8b5c52e465c4117ba6125061fe..315d0bb03664c401897fdf0c0c9abd1fc269a19c 100644 --- a/docs/mindearth/docs/source_en/medium-range/graphcast.ipynb +++ b/docs/mindearth/docs/source_en/medium-range/graphcast.ipynb @@ -126,7 +126,7 @@ "cell_type": "markdown", "metadata": {}, "source": [ - "The following `src` can be downloaded in [graphcast/src](https://atomgit.com/mindspore-lab/mindscience/tree/master/MindEarth/applications/medium-range/graphcast/src)." + "The following `src` can be downloaded in [graphcast/src](https://atomgit.com/mindspore/mindscience/tree/master/MindEarth/applications/medium-range/graphcast/src)." ] }, { @@ -160,7 +160,7 @@ "cell_type": "markdown", "metadata": {}, "source": [ - "You can get parameters of model, data and optimizer from [config](https://atomgit.com/mindspore-lab/mindscience/blob/master/MindEarth/applications/medium-range/graphcast/configs/GraphCast_1.4.yaml)." + "You can get parameters of model, data and optimizer from [config](https://atomgit.com/mindspore/mindscience/blob/master/MindEarth/applications/medium-range/graphcast/configs/GraphCast_1.4.yaml)." ] }, { @@ -187,7 +187,7 @@ "\n", "Download the statistic, training and validation dataset from [dataset](https://download.mindspore.cn/mindscience/mindearth/dataset/WeatherBench_1.4_69/) to `./dataset`.\n", "\n", - "Modify the parameter of `root_dir` in the [GraphCast_1.4.yaml](https://atomgit.com/mindspore-lab/mindscience/blob/master/MindEarth/applications/medium-range/graphcast/configs/GraphCast_1.4.yaml), which set the directory for dataset.\n", + "Modify the parameter of `root_dir` in the [GraphCast_1.4.yaml](https://atomgit.com/mindspore/mindscience/blob/master/MindEarth/applications/medium-range/graphcast/configs/GraphCast_1.4.yaml), which set the directory for dataset.\n", "\n", "The `./dataset` is hosted with the following directory structure:\n", "\n", diff --git a/docs/mindearth/docs/source_en/medium-range/graphcast_tp.ipynb b/docs/mindearth/docs/source_en/medium-range/graphcast_tp.ipynb index a4e4169d60ef396ec4f0dcf8af1849314854e187..668f30eaa144c76ddf671f345f14a9b11ecad063 100644 --- a/docs/mindearth/docs/source_en/medium-range/graphcast_tp.ipynb +++ b/docs/mindearth/docs/source_en/medium-range/graphcast_tp.ipynb @@ -54,7 +54,7 @@ "cell_type": "markdown", "metadata": {}, "source": [ - "The following `src` can be downloaded in [graphcast/src](https://atomgit.com/mindspore-lab/mindscience/tree/master/MindEarth/applications/medium-range/graphcast/src)." + "The following `src` can be downloaded in [graphcast/src](https://atomgit.com/mindspore/mindscience/tree/master/MindEarth/applications/medium-range/graphcast/src)." ] }, { @@ -87,7 +87,7 @@ "cell_type": "markdown", "metadata": {}, "source": [ - "You can get parameters of model, data and optimizer from [config](https://atomgit.com/mindspore-lab/mindscience/blob/master/MindEarth/applications/medium-range/graphcast/configs/GraphCastTp.yaml). Set `tp: True` in `GraphCastTp.yaml`." + "You can get parameters of model, data and optimizer from [config](https://atomgit.com/mindspore/mindscience/blob/master/MindEarth/applications/medium-range/graphcast/configs/GraphCastTp.yaml). Set `tp: True` in `GraphCastTp.yaml`." ] }, { diff --git a/docs/mindearth/docs/source_en/medium-range/vit_kno.ipynb b/docs/mindearth/docs/source_en/medium-range/vit_kno.ipynb index 1e6b96494d92f1dcab8f86affb9cbe88fb643164..454d25b400e917d27383960840ccfc7b278bf2eb 100644 --- a/docs/mindearth/docs/source_en/medium-range/vit_kno.ipynb +++ b/docs/mindearth/docs/source_en/medium-range/vit_kno.ipynb @@ -65,7 +65,7 @@ "cell_type": "markdown", "metadata": {}, "source": [ - "The following `src` can be downloaded in [ViT-KNO/src](https://atomgit.com/mindspore-lab/mindscience/tree/master/MindEarth/applications/medium-range/koopman_vit/src)." + "The following `src` can be downloaded in [ViT-KNO/src](https://atomgit.com/mindspore/mindscience/tree/master/MindEarth/applications/medium-range/koopman_vit/src)." ] }, { @@ -83,7 +83,7 @@ "cell_type": "markdown", "metadata": {}, "source": [ - "You can get parameters of model, data and optimizer from [vit_kno.yaml](https://atomgit.com/mindspore-lab/mindscience/blob/master/MindEarth/applications/medium-range/koopman_vit/configs/vit_kno_1.4.yaml)." + "You can get parameters of model, data and optimizer from [vit_kno.yaml](https://atomgit.com/mindspore/mindscience/blob/master/MindEarth/applications/medium-range/koopman_vit/configs/vit_kno_1.4.yaml)." ] }, { @@ -120,7 +120,7 @@ "\n", "Download the statistic, training and validation dataset from [dataset](https://download.mindspore.cn/mindscience/mindearth/dataset/WeatherBench_1.4_69/) to `./dataset`.\n", "\n", - "Modify the parameter of `root_dir` in the [vit_kno.yaml](https://atomgit.com/mindspore-lab/mindscience/blob/master/MindEarth/applications/medium-range/koopman_vit/configs/vit_kno_1.4.yaml), which set the directory for dataset.\n", + "Modify the parameter of `root_dir` in the [vit_kno.yaml](https://atomgit.com/mindspore/mindscience/blob/master/MindEarth/applications/medium-range/koopman_vit/configs/vit_kno_1.4.yaml), which set the directory for dataset.\n", "\n", "The `./dataset` is hosted with the following directory structure:\n", "\n", diff --git a/docs/mindearth/docs/source_en/mindearth_install.md b/docs/mindearth/docs/source_en/mindearth_install.md index 38197f6013c1367d41be1a18a39d389fd7a0bf57..8ec765423406ded368fd9b85cd6959c711ea8623 100644 --- a/docs/mindearth/docs/source_en/mindearth_install.md +++ b/docs/mindearth/docs/source_en/mindearth_install.md @@ -6,7 +6,7 @@ - The hardware platform should be Ascend, GPU. - See our [MindSpore Installation Guide](https://www.mindspore.cn/install/en) to install MindSpore. -- All other dependencies are included in [requirements.txt](https://atomgit.com/mindspore-lab/mindscience/blob/master/MindEarth/requirements.txt). +- All other dependencies are included in [requirements.txt](https://atomgit.com/mindspore/mindscience/blob/master/MindEarth/requirements.txt). ## Installation diff --git a/docs/mindearth/docs/source_en/nowcasting/DgmrNet.ipynb b/docs/mindearth/docs/source_en/nowcasting/DgmrNet.ipynb index 2ac3deaff396265e4ac31b5c402d269e283c5e37..6c7c94ba4158e39b76509c1d85cf6350c4f9c3f7 100644 --- a/docs/mindearth/docs/source_en/nowcasting/DgmrNet.ipynb +++ b/docs/mindearth/docs/source_en/nowcasting/DgmrNet.ipynb @@ -79,7 +79,7 @@ "id": "34d2a2d1-262c-49e3-aeea-89082e311a03", "metadata": {}, "source": [ - "The following `src` can be downloaded in [Dgmr/src](https://atomgit.com/mindspore-lab/mindscience/tree/master/MindEarth/applications/nowcasting/dgmr/src)." + "The following `src` can be downloaded in [Dgmr/src](https://atomgit.com/mindspore/mindscience/tree/master/MindEarth/applications/nowcasting/dgmr/src)." ] }, { @@ -101,7 +101,7 @@ "id": "697fecae-a3af-4836-98b7-eaf150b95779", "metadata": {}, "source": [ - "You can get parameters of model, data and optimizer from [DgmrNet.yaml](https://atomgit.com/mindspore-lab/mindscience/blob/master/MindEarth/applications/nowcasting/dgmr/DgmrNet.yaml)." + "You can get parameters of model, data and optimizer from [DgmrNet.yaml](https://atomgit.com/mindspore/mindscience/blob/master/MindEarth/applications/nowcasting/dgmr/DgmrNet.yaml)." ] }, { @@ -135,7 +135,7 @@ "\n", "Download the training and validation dataset from [dataset](https://download.mindspore.cn/mindscience/mindearth/dataset/dgmr_dataset.zip) to `./dataset`.\n", "\n", - "Modify the parameter of `root_dir` in the [DgmrNet.yaml](https://atomgit.com/mindspore-lab/mindscience/blob/master/MindEarth/applications/nowcasting/dgmr/DgmrNet.yaml), which set the directory for dataset.\n", + "Modify the parameter of `root_dir` in the [DgmrNet.yaml](https://atomgit.com/mindspore/mindscience/blob/master/MindEarth/applications/nowcasting/dgmr/DgmrNet.yaml), which set the directory for dataset.\n", "\n", "The `./dataset` is hosted with the following directory structure:\n", "\n", diff --git a/docs/mindearth/docs/source_en/nowcasting/Nowcastnet.ipynb b/docs/mindearth/docs/source_en/nowcasting/Nowcastnet.ipynb index 13852e47281353f0e9a1ad1477fca7f311148919..c8c44a3563bc7c8a26d4915bf6be8c4a330afcdf 100644 --- a/docs/mindearth/docs/source_en/nowcasting/Nowcastnet.ipynb +++ b/docs/mindearth/docs/source_en/nowcasting/Nowcastnet.ipynb @@ -150,7 +150,7 @@ "source": [ "## Data Construction\n", "\n", - "Download the statistic, training and validation dataset from [dataset](https://download-mindspore.osinfra.cn/mindscience/mindearth/dataset/nowcastnet/tiny_datasets/) to `./dataset`. Modify the parameter of `root_dir` in the [Nowcastnet.yaml](https://atomgit.com/mindspore-lab/mindscience/blob/master/MindEarth/applications/nowcasting/Nowcastnet/configs/Nowcastnet.yaml), which set the directory for dataset.\n", + "Download the statistic, training and validation dataset from [dataset](https://download-mindspore.osinfra.cn/mindscience/mindearth/dataset/nowcastnet/tiny_datasets/) to `./dataset`. Modify the parameter of `root_dir` in the [Nowcastnet.yaml](https://atomgit.com/mindspore/mindscience/blob/master/MindEarth/applications/nowcasting/Nowcastnet/configs/Nowcastnet.yaml), which set the directory for dataset.\n", "\n", "The `./dataset` is hosted with the following directory structure:\n", "\n", diff --git a/docs/mindearth/docs/source_en/nowcasting/prediffnet.ipynb b/docs/mindearth/docs/source_en/nowcasting/prediffnet.ipynb index 54da2565593f66187c5d4ffce7c118ef0ded3d99..e4c3fb9b266144f994ac3ed922d9d4cffd255397 100644 --- a/docs/mindearth/docs/source_en/nowcasting/prediffnet.ipynb +++ b/docs/mindearth/docs/source_en/nowcasting/prediffnet.ipynb @@ -70,7 +70,7 @@ "id": "415eb386-b9ef-42af-9ab6-f98c9d8151da", "metadata": {}, "source": [ - "The following src can be downloaded from [PreDiff/src](https://atomgit.com/mindspore-lab/mindscience/tree/master/MindEarth/applications/nowcasting/PreDiff/src)." + "The following src can be downloaded from [PreDiff/src](https://atomgit.com/mindspore/mindscience/tree/master/MindEarth/applications/nowcasting/PreDiff/src)." ] }, { @@ -113,7 +113,7 @@ "id": "7272ed00-61ef-439c-a420-b3bcefc13965", "metadata": {}, "source": [ - "The parameters of the model, data, optimizer, etc. can be configured in the [configuration file](https://atomgit.com/mindspore-lab/mindscience/tree/master/MindEarth/applications/nowcasting/PreDiff/configs)." + "The parameters of the model, data, optimizer, etc. can be configured in the [configuration file](https://atomgit.com/mindspore/mindscience/tree/master/MindEarth/applications/nowcasting/PreDiff/configs)." ] }, { diff --git a/docs/mindearth/docs/source_zh_cn/dem-super-resolution/DEM-SRNet.ipynb b/docs/mindearth/docs/source_zh_cn/dem-super-resolution/DEM-SRNet.ipynb index 4d0963a88c15a59adad6b190a8773158782d6bae..c4db37545f6c80b898267b01a8935d287c3290a7 100644 --- a/docs/mindearth/docs/source_zh_cn/dem-super-resolution/DEM-SRNet.ipynb +++ b/docs/mindearth/docs/source_zh_cn/dem-super-resolution/DEM-SRNet.ipynb @@ -83,7 +83,7 @@ "id": "663eb08c-8528-4d7b-83d3-a45247e4c20b", "metadata": {}, "source": [ - " `src` 文件可以从[DEM super-resolution/src](https://atomgit.com/mindspore-lab/mindscience/tree/master/MindEarth/applications/dem-super-resolution/src)下载。" + " `src` 文件可以从[DEM super-resolution/src](https://atomgit.com/mindspore/mindscience/tree/master/MindEarth/applications/dem-super-resolution/src)下载。" ] }, { @@ -104,7 +104,7 @@ "id": "9d5a5b11-f2b6-412d-b70b-cd7f65b61863", "metadata": {}, "source": [ - "model、data和optimizer的参数可以通过加载[DEM-SRNet.yaml](https://atomgit.com/mindspore-lab/mindscience/blob/master/MindEarth/applications/dem-super-resolution/DEM-SRNet.yaml)文件获取。" + "model、data和optimizer的参数可以通过加载[DEM-SRNet.yaml](https://atomgit.com/mindspore/mindscience/blob/master/MindEarth/applications/dem-super-resolution/DEM-SRNet.yaml)文件获取。" ] }, { @@ -138,7 +138,7 @@ "\n", "从[dataset](https://download.mindspore.cn/mindscience/mindearth/dataset/dem_dataset.zip)下载训练数据集、验证数据集、测试数据集到当前目录`./dataset`。\n", "\n", - "修改[DEM-SRNet.yaml](https://atomgit.com/mindspore-lab/mindscience/blob/master/MindEarth/applications/dem-super-resolution/DEM-SRNet.yaml)配置文件中的`root_dir`参数，该参数设置了数据集的路径。\n", + "修改[DEM-SRNet.yaml](https://atomgit.com/mindspore/mindscience/blob/master/MindEarth/applications/dem-super-resolution/DEM-SRNet.yaml)配置文件中的`root_dir`参数，该参数设置了数据集的路径。\n", "\n", "`./dataset`中的目录结构如下所示：\n", "\n", diff --git a/docs/mindearth/docs/source_zh_cn/index.rst b/docs/mindearth/docs/source_zh_cn/index.rst index 1e56fc363a708a6357de95f3381b44bf69dea676..a5f3f29d66eb1b71f61ab6318ef1e9088675f04f 100644 --- a/docs/mindearth/docs/source_zh_cn/index.rst +++ b/docs/mindearth/docs/source_zh_cn/index.rst @@ -3,13 +3,13 @@ MindSpore Earth介绍 天气现象与人类的生产生活、社会经济、军事活动等方方面面都密切相关，准确的天气预报能够在灾害天气事件中减轻影响、避免经济损失，还能创造持续不断地财政收入，例如能源、农业、交通和娱乐行业。目前，天气预报主要采用数值天气预报模式，通过处理由气象卫星、观测台站、雷达等收集到的观测资料，求解描写天气演变的大气动力学方程组，进而提供天气气候的预测信息。数值预报模式的预测过程涉及大量计算，耗费较长时间与较大的计算资源。相较于数值预报模式，数据驱动的深度学习模型能够有效地将计算成本降低数个量级。 -`MindSpore Earth `_ 是基于昇思MindSpore开发的地球科学领域套件，支持短临、中期、长期等多时空尺度以及降水、台风等灾害性天气的AI气象预测，旨在于为广大的工业界科研工程人员、高校老师及学生提供高效易用的AI气象预测软件。 +`MindSpore Earth `_ 是基于昇思MindSpore开发的地球科学领域套件，支持短临、中期、长期等多时空尺度以及降水、台风等灾害性天气的AI气象预测，旨在于为广大的工业界科研工程人员、高校老师及学生提供高效易用的AI气象预测软件。 .. raw:: html -代码仓地址: +代码仓地址: .. toctree:: :glob: diff --git a/docs/mindearth/docs/source_zh_cn/medium-range/FourCastNet.ipynb b/docs/mindearth/docs/source_zh_cn/medium-range/FourCastNet.ipynb index 47d212f6cdad907884685a5531d2f61357a6b166..4a340cff324b266a2ff03f3f3509b7e9791e25e8 100644 --- a/docs/mindearth/docs/source_zh_cn/medium-range/FourCastNet.ipynb +++ b/docs/mindearth/docs/source_zh_cn/medium-range/FourCastNet.ipynb @@ -111,7 +111,7 @@ "cell_type": "markdown", "metadata": {}, "source": [ - " `src` 文件可以从[FourCastNet/src](https://atomgit.com/mindspore-lab/mindscience/tree/master/MindEarth/applications/medium-range/fourcastnet/src)下载。" + " `src` 文件可以从[FourCastNet/src](https://atomgit.com/mindspore/mindscience/tree/master/MindEarth/applications/medium-range/fourcastnet/src)下载。" ] }, { @@ -137,7 +137,7 @@ "cell_type": "markdown", "metadata": {}, "source": [ - "model、data和optimizer的参数可以通过加载yaml文件获取（[FourCastNet.yaml](https://atomgit.com/mindspore-lab/mindscience/blob/master/MindEarth/applications/medium-range/fourcastnet/configs/FourCastNet.yaml)）。" + "model、data和optimizer的参数可以通过加载yaml文件获取（[FourCastNet.yaml](https://atomgit.com/mindspore/mindscience/blob/master/MindEarth/applications/medium-range/fourcastnet/configs/FourCastNet.yaml)）。" ] }, { @@ -182,7 +182,7 @@ "\n", "在[dataset](https://download.mindspore.cn/mindscience/mindearth/dataset/WeatherBench_1.4_69/)路径下，下载正则化参数、训练数据集验证数据集到 `./dataset`目录。\n", "\n", - "修改[FourCastNet.yaml](https://atomgit.com/mindspore-lab/mindscience/blob/master/MindEarth/applications/medium-range/fourcastnet/configs/FourCastNet.yaml)配置文件中的`root_dir`参数，该参数设置了数据集的路径。\n", + "修改[FourCastNet.yaml](https://atomgit.com/mindspore/mindscience/blob/master/MindEarth/applications/medium-range/fourcastnet/configs/FourCastNet.yaml)配置文件中的`root_dir`参数，该参数设置了数据集的路径。\n", "\n", "`./dataset`中的目录结构如下所示：\n", "\n", diff --git a/docs/mindearth/docs/source_zh_cn/medium-range/fuxi.ipynb b/docs/mindearth/docs/source_zh_cn/medium-range/fuxi.ipynb index f80e9a7a421346af7170696c22671ee9339746ff..c3d1f5900474f08a0c4b27ffd0a8393954beddf5 100644 --- a/docs/mindearth/docs/source_zh_cn/medium-range/fuxi.ipynb +++ b/docs/mindearth/docs/source_zh_cn/medium-range/fuxi.ipynb @@ -89,7 +89,7 @@ "id": "062e7adc", "metadata": {}, "source": [ - "下述`src`可以在[fuxi/src](https://atomgit.com/mindspore-lab/mindscience/tree/master/MindEarth/applications/medium-range/fuxi/src)下载。\n" + "下述`src`可以在[fuxi/src](https://atomgit.com/mindspore/mindscience/tree/master/MindEarth/applications/medium-range/fuxi/src)下载。\n" ] }, { @@ -123,7 +123,7 @@ "id": "18b670e4", "metadata": {}, "source": [ - "可以在[配置文件](https://atomgit.com/mindspore-lab/mindscience/raw/master/MindEarth/applications/medium-range/fuxi/configs/FuXi.yaml)中配置模型、数据和优化器等参数。" + "可以在[配置文件](https://atomgit.com/mindspore/mindscience/raw/master/MindEarth/applications/medium-range/fuxi/configs/FuXi.yaml)中配置模型、数据和优化器等参数。" ] }, { diff --git a/docs/mindearth/docs/source_zh_cn/medium-range/graphcast.ipynb b/docs/mindearth/docs/source_zh_cn/medium-range/graphcast.ipynb index 907ec248a71f4a9560074ec160a29fe2090413d6..b75262ccf29bd7df6187ea2604d3277fc1beb652 100644 --- a/docs/mindearth/docs/source_zh_cn/medium-range/graphcast.ipynb +++ b/docs/mindearth/docs/source_zh_cn/medium-range/graphcast.ipynb @@ -126,7 +126,7 @@ "cell_type": "markdown", "metadata": {}, "source": [ - "下述`src`可以在[graphcast/src](https://atomgit.com/mindspore-lab/mindscience/tree/master/MindEarth/applications/medium-range/graphcast/src)下载。" + "下述`src`可以在[graphcast/src](https://atomgit.com/mindspore/mindscience/tree/master/MindEarth/applications/medium-range/graphcast/src)下载。" ] }, { @@ -160,7 +160,7 @@ "cell_type": "markdown", "metadata": {}, "source": [ - "模型涉及的参数、优化器、数据配置见[config](https://atomgit.com/mindspore-lab/mindscience/blob/master/MindEarth/applications/medium-range/graphcast/configs/GraphCast_1.4.yaml)。" + "模型涉及的参数、优化器、数据配置见[config](https://atomgit.com/mindspore/mindscience/blob/master/MindEarth/applications/medium-range/graphcast/configs/GraphCast_1.4.yaml)。" ] }, { @@ -187,7 +187,7 @@ "\n", "在[dataset](https://download.mindspore.cn/mindscience/mindearth/dataset/WeatherBench_1.4_69/)路径下，下载正则化参数、训练数据集验证数据集到 `./dataset`目录。\n", "\n", - "修改[GraphCast_1.4.yaml](https://atomgit.com/mindspore-lab/mindscience/blob/master/MindEarth/applications/medium-range/graphcast/configs/GraphCast_1.4.yaml)配置文件中的`root_dir`参数，该参数设置了数据集的路径。\n", + "修改[GraphCast_1.4.yaml](https://atomgit.com/mindspore/mindscience/blob/master/MindEarth/applications/medium-range/graphcast/configs/GraphCast_1.4.yaml)配置文件中的`root_dir`参数，该参数设置了数据集的路径。\n", "\n", "`./dataset`中的目录结构如下所示：\n", "\n", diff --git a/docs/mindearth/docs/source_zh_cn/medium-range/graphcast_tp.ipynb b/docs/mindearth/docs/source_zh_cn/medium-range/graphcast_tp.ipynb index 3695a2caf8b83c79bd2214088415fed38b58e473..e31b58f04fcdfd19872d71e0f28975521cf9c6ec 100644 --- a/docs/mindearth/docs/source_zh_cn/medium-range/graphcast_tp.ipynb +++ b/docs/mindearth/docs/source_zh_cn/medium-range/graphcast_tp.ipynb @@ -53,7 +53,7 @@ "cell_type": "markdown", "metadata": {}, "source": [ - "下述`src`可以在[graphcast/src](https://atomgit.com/mindspore-lab/mindscience/tree/master/MindEarth/applications/medium-range/graphcast/src)下载" + "下述`src`可以在[graphcast/src](https://atomgit.com/mindspore/mindscience/tree/master/MindEarth/applications/medium-range/graphcast/src)下载" ] }, { @@ -86,7 +86,7 @@ "cell_type": "markdown", "metadata": {}, "source": [ - "模型涉及的参数、优化器、数据配置见configs。执行降水代码时，[GraphCastTp.yaml](https://atomgit.com/mindspore-lab/mindscience/blob/master/MindEarth/applications/medium-range/graphcast/configs/GraphCastTp.yaml)文件中的`tp`需要设置为`True`。" + "模型涉及的参数、优化器、数据配置见configs。执行降水代码时，[GraphCastTp.yaml](https://atomgit.com/mindspore/mindscience/blob/master/MindEarth/applications/medium-range/graphcast/configs/GraphCastTp.yaml)文件中的`tp`需要设置为`True`。" ] }, { diff --git a/docs/mindearth/docs/source_zh_cn/medium-range/vit_kno.ipynb b/docs/mindearth/docs/source_zh_cn/medium-range/vit_kno.ipynb index dd9c3c139b71aa3e5b6fd45d837476d089966723..e9eaa61c99201ff97b13eb3e7574bfa342701030 100644 --- a/docs/mindearth/docs/source_zh_cn/medium-range/vit_kno.ipynb +++ b/docs/mindearth/docs/source_zh_cn/medium-range/vit_kno.ipynb @@ -65,7 +65,7 @@ "cell_type": "markdown", "metadata": {}, "source": [ - " `src` 文件可以从[ViT-KNO/src](https://atomgit.com/mindspore-lab/mindscience/tree/master/MindEarth/applications/medium-range/koopman_vit/src)下载。" + " `src` 文件可以从[ViT-KNO/src](https://atomgit.com/mindspore/mindscience/tree/master/MindEarth/applications/medium-range/koopman_vit/src)下载。" ] }, { @@ -83,7 +83,7 @@ "cell_type": "markdown", "metadata": {}, "source": [ - "model、data和optimizer的参数可以通过加载yaml文件获取（[vit_kno.yaml](https://atomgit.com/mindspore-lab/mindscience/blob/master/MindEarth/applications/medium-range/koopman_vit/configs/vit_kno_1.4.yaml)）。" + "model、data和optimizer的参数可以通过加载yaml文件获取（[vit_kno.yaml](https://atomgit.com/mindspore/mindscience/blob/master/MindEarth/applications/medium-range/koopman_vit/configs/vit_kno_1.4.yaml)）。" ] }, { @@ -119,7 +119,7 @@ "\n", "在[dataset](https://download.mindspore.cn/mindscience/mindearth/dataset/WeatherBench_1.4_69/)路径下，下载正则化参数、训练数据集、验证数据集到 `./dataset`目录。\n", "\n", - "修改[vit_kno.yaml](https://atomgit.com/mindspore-lab/mindscience/blob/master/MindEarth/applications/medium-range/koopman_vit/configs/vit_kno_1.4.yaml)配置文件中的`root_dir`参数，该参数设置了数据集的路径。\n", + "修改[vit_kno.yaml](https://atomgit.com/mindspore/mindscience/blob/master/MindEarth/applications/medium-range/koopman_vit/configs/vit_kno_1.4.yaml)配置文件中的`root_dir`参数，该参数设置了数据集的路径。\n", "\n", "`./dataset`中的目录结构如下所示：\n", "\n", diff --git a/docs/mindearth/docs/source_zh_cn/mindearth_install.md b/docs/mindearth/docs/source_zh_cn/mindearth_install.md index 1fb5c8061a4cc9c0be9e47637d262ed6bb6598e1..7b56e2de003bf8999c13f9e8cbf3adc0592122f2 100644 --- a/docs/mindearth/docs/source_zh_cn/mindearth_install.md +++ b/docs/mindearth/docs/source_zh_cn/mindearth_install.md @@ -6,7 +6,7 @@ - 硬件平台为Ascend、GPU。 - 参考[MindSpore安装指南](https://www.mindspore.cn/install)，完成MindSpore的安装。 -- 其余依赖请参见[requirements.txt](https://atomgit.com/mindspore-lab/mindscience/blob/master/MindEarth/requirements.txt)。 +- 其余依赖请参见[requirements.txt](https://atomgit.com/mindspore/mindscience/blob/master/MindEarth/requirements.txt)。 ## 安装方式 diff --git a/docs/mindearth/docs/source_zh_cn/nowcasting/DgmrNet.ipynb b/docs/mindearth/docs/source_zh_cn/nowcasting/DgmrNet.ipynb index 3c7e37d2e0dc3d502114cf318179a49025d8b8ee..83c7c50a1dac72b5cc067f3d161a12f825be5c6c 100644 --- a/docs/mindearth/docs/source_zh_cn/nowcasting/DgmrNet.ipynb +++ b/docs/mindearth/docs/source_zh_cn/nowcasting/DgmrNet.ipynb @@ -79,7 +79,7 @@ "id": "34d2a2d1-262c-49e3-aeea-89082e311a03", "metadata": {}, "source": [ - " `src` 文件可以从[Dgmr/src](https://atomgit.com/mindspore-lab/mindscience/tree/master/MindEarth/applications/nowcasting/dgmr/src)下载。" + " `src` 文件可以从[Dgmr/src](https://atomgit.com/mindspore/mindscience/tree/master/MindEarth/applications/nowcasting/dgmr/src)下载。" ] }, { @@ -101,7 +101,7 @@ "id": "697fecae-a3af-4836-98b7-eaf150b95779", "metadata": {}, "source": [ - "model、data和optimizer的参数可以通过加载[DgmrNet.yaml](https://atomgit.com/mindspore-lab/mindscience/blob/master/MindEarth/applications/nowcasting/dgmr/DgmrNet.yaml)文件获取。" + "model、data和optimizer的参数可以通过加载[DgmrNet.yaml](https://atomgit.com/mindspore/mindscience/blob/master/MindEarth/applications/nowcasting/dgmr/DgmrNet.yaml)文件获取。" ] }, { @@ -134,7 +134,7 @@ "\n", "在[dataset](https://download.mindspore.cn/mindscience/mindearth/dataset/dgmr_dataset.zip)路径下，下载训练数据集、验证数据集、测试数据集到 `./dataset`目录。\n", "\n", - "修改[DgmrNet.yaml](https://atomgit.com/mindspore-lab/mindscience/blob/master/MindEarth/applications/nowcasting/dgmr/DgmrNet.yaml)配置文件中的`root_dir`参数，该参数设置了数据集的路径。\n", + "修改[DgmrNet.yaml](https://atomgit.com/mindspore/mindscience/blob/master/MindEarth/applications/nowcasting/dgmr/DgmrNet.yaml)配置文件中的`root_dir`参数，该参数设置了数据集的路径。\n", "\n", "`./dataset`中的目录结构如下所示：\n", "\n", diff --git a/docs/mindearth/docs/source_zh_cn/nowcasting/Nowcastnet.ipynb b/docs/mindearth/docs/source_zh_cn/nowcasting/Nowcastnet.ipynb index 4c1f6746c51d396017cebcd173cc7177d96d0982..9de3e362ba7cfc783d23c2a8b68a4ba769708ac5 100644 --- a/docs/mindearth/docs/source_zh_cn/nowcasting/Nowcastnet.ipynb +++ b/docs/mindearth/docs/source_zh_cn/nowcasting/Nowcastnet.ipynb @@ -156,7 +156,7 @@ "source": [ "## 创建数据集\n", "\n", - "在[dataset](https://download-mindspore.osinfra.cn/mindscience/mindearth/dataset/nowcastnet/tiny_datasets/)路径下，下载训练数据集，验证数据集到`./dataset`目录，修改[Nowcastnet.yaml](https://atomgit.com/mindspore-lab/mindscience/blob/master/MindEarth/applications/nowcasting/Nowcastnet/configs/Nowcastnet.yaml)配置文件中的`root_dir`。\n", + "在[dataset](https://download-mindspore.osinfra.cn/mindscience/mindearth/dataset/nowcastnet/tiny_datasets/)路径下，下载训练数据集，验证数据集到`./dataset`目录，修改[Nowcastnet.yaml](https://atomgit.com/mindspore/mindscience/blob/master/MindEarth/applications/nowcasting/Nowcastnet/configs/Nowcastnet.yaml)配置文件中的`root_dir`。\n", "\n", "`./dataset`中的目录结构如下所示：\n", "\n", diff --git a/docs/mindearth/docs/source_zh_cn/nowcasting/prediffnet.ipynb b/docs/mindearth/docs/source_zh_cn/nowcasting/prediffnet.ipynb index 6c7a15a346b23cb4949dad169a26e0be04b79e16..4b751a2b8bdd6fbfab27f203acd33bcc74b5fd83 100644 --- a/docs/mindearth/docs/source_zh_cn/nowcasting/prediffnet.ipynb +++ b/docs/mindearth/docs/source_zh_cn/nowcasting/prediffnet.ipynb @@ -70,7 +70,7 @@ "id": "415eb386-b9ef-42af-9ab6-f98c9d8151da", "metadata": {}, "source": [ - "下述src可以在[PreDiff/src](https://atomgit.com/mindspore-lab/mindscience/tree/master/MindEarth/applications/nowcasting/PreDiff/src)下载。" + "下述src可以在[PreDiff/src](https://atomgit.com/mindspore/mindscience/tree/master/MindEarth/applications/nowcasting/PreDiff/src)下载。" ] }, { @@ -113,7 +113,7 @@ "id": "7272ed00-61ef-439c-a420-b3bcefc13965", "metadata": {}, "source": [ - "可以在[配置文件](https://atomgit.com/mindspore-lab/mindscience/tree/master/MindEarth/applications/nowcasting/PreDiff/configs)中配置模型、数据和优化器等参数。" + "可以在[配置文件](https://atomgit.com/mindspore/mindscience/tree/master/MindEarth/applications/nowcasting/PreDiff/configs)中配置模型、数据和优化器等参数。" ] }, { diff --git a/docs/mindelec/docs/source_en/AD_FDTD_forward.md b/docs/mindelec/docs/source_en/AD_FDTD_forward.md index b5091ac9255d73e1ef1cb1fd65db90a3cac5b811..91dd559a1b009fea1b068ab0b89119980e1fc296 100644 --- a/docs/mindelec/docs/source_en/AD_FDTD_forward.md +++ b/docs/mindelec/docs/source_en/AD_FDTD_forward.md @@ -7,7 +7,7 @@ This tutorial introduces the method for solving electromagnetic positive problems provided by MindSpore Elec based on device-to-device differentiable FDTD. The process of solving Maxwell's equations by the finite-difference time-domain (FDTD) method is equivalent to a recurrent convolutional network (RCNN). The device-to-device differentiable FDTD can be obtained by rewriting the update process with the differentiable operator of MindSpore. Compared with the data-driven black-box model, the solution process of the differentiable FDTD method strictly satisfies the constraints of Maxwell's equations, and the accuracy is comparable to that of traditional numerical algorithms. > This example is for GPU processors and you can download the full sample code here: -> +> ## Maxwell's Equations diff --git a/docs/mindelec/docs/source_en/AD_FDTD_inverse.md b/docs/mindelec/docs/source_en/AD_FDTD_inverse.md index 7092fd85364a3f9770602afb2cadf275299a6325..bb29e520a74bfe1e6ec73fcc8fd3e6dd34c86e4a 100644 --- a/docs/mindelec/docs/source_en/AD_FDTD_inverse.md +++ b/docs/mindelec/docs/source_en/AD_FDTD_inverse.md @@ -7,7 +7,7 @@ This tutorial introduces the method for solving electromagnetic inverse problems provided by MindSpore Elec based on device-to-device differentiable FDTD. The process of solving Maxwell's equations by the finite-difference time-domain (FDTD) method is equivalent to a recurrent convolutional network (RCNN). The device-to-device differentiable FDTD can be obtained by rewriting the update process with the differentiable operator of MindSpore. Compared with the data-driven black-box model, the solution process of the differentiable FDTD method strictly satisfies the constraints of Maxwell's equations. Using MindSpore gradient-ased optimizer, differentiable FDTD can solve various EM inverse problems. > This example is for GPU processors and you can download the full sample code here: -> +> ## Maxwell's Equations diff --git a/docs/mindelec/docs/source_en/incremental_learning.md b/docs/mindelec/docs/source_en/incremental_learning.md index f7d0f9cb7c1795a118a8acb41bda3685cbf08543..400c7125c2d0f1ed9f6e468e76ae830416015050 100644 --- a/docs/mindelec/docs/source_en/incremental_learning.md +++ b/docs/mindelec/docs/source_en/incremental_learning.md @@ -9,7 +9,7 @@ The Physics-Informed Neural Networks (PINNs) is unable to solve parametric Parti This tutorial focuses on how to use Physics-Informed Auto-Decoder (PIAD) based on the MindSpore Elec toolkit to solve the parametric Maxwell’s equations with incremental training, which reduces the training time significantly. > This current sample is for Atlas training series. You can find the complete executable code at -> +> ## Problem Description diff --git a/docs/mindelec/docs/source_en/index.rst b/docs/mindelec/docs/source_en/index.rst index c86e432bfb3856fb8dc8c3df4bec1276a63c4241..e51ed285990d6ebad1620f0e90e8150729710571 100644 --- a/docs/mindelec/docs/source_en/index.rst +++ b/docs/mindelec/docs/source_en/index.rst @@ -11,7 +11,7 @@ MindSpore Elec has now achieved milestones in Huawei's terminal cell phone toler -Code repository address: +Code repository address: Data Building and Conversion ------------------------------ diff --git a/docs/mindelec/docs/source_en/intro_and_install.md b/docs/mindelec/docs/source_en/intro_and_install.md index 66e37e6e42b7eb45985faab5448bcb77156d1cbb..862f90323d946b6a6fe899528dfd3a5d47a6c944 100644 --- a/docs/mindelec/docs/source_en/intro_and_install.md +++ b/docs/mindelec/docs/source_en/intro_and_install.md @@ -8,7 +8,7 @@ Electromagnetic simulation refers to simulating the propagation characteristics MindSpore Elec is an AI electromagnetic simulation toolkit developed based on MindSpore. It consists of the electromagnetic model library, data build and conversion, simulation computation, and result visualization. End-to-end AI electromagnetic simulation is supported. Currently, Huawei has achieved phase achievements in the tolerance scenario of Huawei mobile phones. Compared with the commercial simulation software, the S parameter error of AI electromagnetic simulation is about 2%, and the end-to-end simulation speed is improved by more than 10 times. -MindSpore Elec contains several AI EM simulation cases. For more details, please click to view [case](https://atomgit.com/mindspore-lab/mindscience/tree/master/MindElec/examples). +MindSpore Elec contains several AI EM simulation cases. For more details, please click to view [case](https://atomgit.com/mindspore/mindscience/tree/master/MindElec/examples). In the future, MindSpore Elec will implement more simulation cases, and your contribution is welcome. @@ -19,7 +19,7 @@ In the future, MindSpore Elec will implement more simulation cases, and your con - The hardware platform should be Ascend, GPU or CPU. - See our [MindSpore Installation Guide](https://www.mindspore.cn/install/en) to install MindSpore. The versions of MindSpore Elec and MindSpore must be consistent. -- All other dependencies are included in [requirements.txt](https://atomgit.com/mindspore-lab/mindscience/blob/master/MindElec/requirements.txt). +- All other dependencies are included in [requirements.txt](https://atomgit.com/mindspore/mindscience/blob/master/MindElec/requirements.txt). ### Installation @@ -31,7 +31,7 @@ You can install MindSpore Elec either by pip or by source code. pip install https://ms-release.obs.cn-north-4.myhuaweicloud.com/{ms_version}/mindscience/{arch}/mindscience_mindelec_ascend-{me_version}-{python_version}-linux_{arch}.whl -i https://pypi.tuna.tsinghua.edu.cn/simple ``` -> - When the network is connected, dependency items are automatically downloaded during .whl package installation. (For details about other dependency items, see [setup.py](https://atomgit.com/mindspore-lab/mindscience/blob/master/MindElec/setup.py)), point cloud data sampling depends on [pythonocc](https://github.com/tpaviot/pythonocc-core), which you need to install manually. +> - When the network is connected, dependency items are automatically downloaded during .whl package installation. (For details about other dependency items, see [setup.py](https://atomgit.com/mindspore/mindscience/blob/master/MindElec/setup.py)), point cloud data sampling depends on [pythonocc](https://github.com/tpaviot/pythonocc-core), which you need to install manually. > - `{arch}` specifies system architecture, for example, when using x86-64 Linux, `{arch}` should be x86_64, and aarch64 for ARM system(64-bit). > - `{ms_version}` refers to the MindSpore version that matches with MindSpore Elec. For example, if you want to install MindSpore Elec 0.1.0, then,`{ms_version}` should be 1.5.0. > - `{me_version}` refers to the version of MindSpore Elec. For example, when you are downloading MindSpore Elec 0.1.0, `{me_version}` should be 0.1.0. diff --git a/docs/mindelec/docs/source_en/parameterization.md b/docs/mindelec/docs/source_en/parameterization.md index f47ed90116645d179aca6172731f926921815838..fedc296c7e000cd9547b1179e206706f082663b8 100644 --- a/docs/mindelec/docs/source_en/parameterization.md +++ b/docs/mindelec/docs/source_en/parameterization.md @@ -14,7 +14,7 @@ MindSpore Elec use AI model to directly obtain the S-parameters of the target to - The point cloud solution implements the mapping from the sampling point cloud of the antenna/phone to the simulation result. In this solution, the structure file of the mobile phone is converted into the point cloud tensor data, and the convolutional neural network is used to extract the structure features. Then, the final simulation result (S-parameters) are obtained through the mapping of multiple full-connected layers. The advantage of this solution is that it is applicable to complex working conditions where the number or types of structural parameters may change. > This current sample is for Atlas training series. You can find the complete executable code at -> +> ## Target Scenario @@ -40,7 +40,7 @@ There are 495 pairs of parameter-S11 samples. The training set and testing set a The data have been provided as .npy files, which can be downloaded from the following address: - + ## Parameterized Electromagnetic Simulation diff --git a/docs/mindelec/docs/source_en/point_cloud.md b/docs/mindelec/docs/source_en/point_cloud.md index 850327d321eebfa86d645fda2d0e26754099e07f..c37927536f0d908463bdf82f995b0d20af5e2204 100644 --- a/docs/mindelec/docs/source_en/point_cloud.md +++ b/docs/mindelec/docs/source_en/point_cloud.md @@ -9,7 +9,7 @@ This tutorial describes the deep learning electromagnetic simulation method base Conventional electromagnetic simulation usually uses finite element or finite-difference methods to compute electromagnetic fields. These methods require complex mesh division and iterative computation, which is time-consuming and affects product R&D efficiency. MindSpore Elec provides a new end-to-end electromagnetic field AI computation method. This method directly computes the electromagnetic field in the simulation area based on point cloud data without mesh division and iterative solution, greatly accelerating the overall simulation speed and facilitating efficient product R&D. > This current sample is for Atlas training series. You can find the complete executable code at -> +> ## Overall Process diff --git a/docs/mindelec/docs/source_en/time_domain_maxwell.md b/docs/mindelec/docs/source_en/time_domain_maxwell.md index 42c585b116061ac8380a3f2de1142b35fb3bd329..88c6007ce4b950bb527e5fcab58893c377b7325a 100644 --- a/docs/mindelec/docs/source_en/time_domain_maxwell.md +++ b/docs/mindelec/docs/source_en/time_domain_maxwell.md @@ -7,7 +7,7 @@ The rapid development of AI technology provides a new computing paradigm for scientific computing. The MindSpore Elec toolkit supports both data-driven and physics-driven AI methods to handle typical problems in the scientific computing field. The physics-driven AI method combines physical equations and initial boundary conditions to train the model. Compared with the data-driven method, the physics-driven method doesn’t require any labeled data. This tutorial focuses on physics-driven AI methods for solving point source time-domain Maxwell’s equations. > This current sample is for Atlas training series. You can find the complete executable code at -> +> ## Maxwell's Equations diff --git a/docs/mindelec/docs/source_zh_cn/AD_FDTD_forward.md b/docs/mindelec/docs/source_zh_cn/AD_FDTD_forward.md index 933caea80be581e35ab91b3d2c54531385f2f586..ac6108237af6cc3dd88bd50d4771554691879bea 100644 --- a/docs/mindelec/docs/source_zh_cn/AD_FDTD_forward.md +++ b/docs/mindelec/docs/source_zh_cn/AD_FDTD_forward.md @@ -7,7 +7,7 @@ 本教程介绍MindSpore Elec提供的基于端到端可微分FDTD求解电磁正问题的方法。时域有限差分（FDTD）方法求解麦克斯韦方程组的过程等价于一个循环卷积网络（RCNN）。利用MindSpore的可微分算子重写更新流程，便可得到端到端可微分FDTD。相比于数据驱动的黑盒模型，可微分FDTD方法的求解流程严格满足麦克斯韦方程组的约束，精度与传统数值算法精度相当。 > 本例面向GPU处理器，你可以在这里下载完整的样例代码： -> +> ## 麦克斯韦方程组 diff --git a/docs/mindelec/docs/source_zh_cn/AD_FDTD_inverse.md b/docs/mindelec/docs/source_zh_cn/AD_FDTD_inverse.md index 4aeb7b35ef0045a06d9a3558c6083dfa17dfea39..1e43dd43dab47f29362d08ce494625302b704303 100644 --- a/docs/mindelec/docs/source_zh_cn/AD_FDTD_inverse.md +++ b/docs/mindelec/docs/source_zh_cn/AD_FDTD_inverse.md @@ -7,7 +7,7 @@ 本教程介绍MindSpore Elec提供的基于端到端可微分FDTD求解电磁逆问题的方法。时域有限差分（FDTD）方法求解麦克斯韦方程组的过程等价于一个循环卷积网络（RCNN）。利用MindSpore的可微分算子重写更新流程，便可得到端到端可微分FDTD。相比于数据驱动的黑盒模型，可微分FDTD方法的求解流程严格满足麦克斯韦方程组的约束。利用MindSpore的基于梯度的优化器，可微分FDTD可求解各种电磁逆问题。 > 本例面向GPU处理器，你可以在这里下载完整的样例代码： -> +> ## 麦克斯韦方程组 diff --git a/docs/mindelec/docs/source_zh_cn/incremental_learning.md b/docs/mindelec/docs/source_zh_cn/incremental_learning.md index 4a21014945d71d70da79e1a2c5a9712e5058b0c9..88ed23b8f2340e606eb7c7672157586b43292ec6 100644 --- a/docs/mindelec/docs/source_zh_cn/incremental_learning.md +++ b/docs/mindelec/docs/source_zh_cn/incremental_learning.md @@ -9,7 +9,7 @@ 本教程重点介绍基于MindSpore Elec套件的物理信息自解码器（Physics-Informed Auto-Decoder）增量训练方法，该方法可以快速求解同一类方程，极大减少重新训练的时间。 > 本例面向Atlas训练系列产品，你可以在这里下载完整的样例代码： -> +> ## 问题描述 diff --git a/docs/mindelec/docs/source_zh_cn/index.rst b/docs/mindelec/docs/source_zh_cn/index.rst index a3d6a18c74e714207f3a5b049d9d593667876f21..d2dc1ab895757f2a6fc412db355ec90cbd7e556b 100644 --- a/docs/mindelec/docs/source_zh_cn/index.rst +++ b/docs/mindelec/docs/source_zh_cn/index.rst @@ -11,7 +11,7 @@ MindSpore Elec目前已在华为终端手机容差场景中取得阶段性成果 -代码仓地址： +代码仓地址： 数据构建及转换 ---------------- diff --git a/docs/mindelec/docs/source_zh_cn/intro_and_install.md b/docs/mindelec/docs/source_zh_cn/intro_and_install.md index c7f41fc1028b6a74f022150b243195023e80787c..23fb76b82daacf123d0b9099b6230e809ff6d2eb 100644 --- a/docs/mindelec/docs/source_zh_cn/intro_and_install.md +++ b/docs/mindelec/docs/source_zh_cn/intro_and_install.md @@ -8,7 +8,7 @@ MindSpore Elec是基于MindSpore开发的AI电磁仿真工具包，由数据构建及转换、仿真计算、以及结果可视化组成。可以支持端到端的AI电磁仿真。目前已在华为终端手机容差场景中取得阶段性成果，相比商业仿真软件，AI电磁仿真的S参数误差在2%左右，端到端仿真速度提升10+倍。 -MindSpore Elec中包含了多个AI电磁仿真案例，更多详情，请点击查看[案例](https://atomgit.com/mindspore-lab/mindscience/tree/master/MindElec/examples)。 +MindSpore Elec中包含了多个AI电磁仿真案例，更多详情，请点击查看[案例](https://atomgit.com/mindspore/mindscience/tree/master/MindElec/examples)。 未来，MindSpore Elec中将包含更多结合AI算法的电磁仿真案例，欢迎大家的关注和支持。 @@ -18,7 +18,7 @@ MindSpore Elec中包含了多个AI电磁仿真案例，更多详情，请点击 - 硬件平台为Ascend。 - 参考[MindSpore安装指南](https://www.mindspore.cn/install)，完成MindSpore的安装。 -- 其余依赖请参见[requirements.txt](https://atomgit.com/mindspore-lab/mindscience/blob/master/MindElec/requirements.txt)。 +- 其余依赖请参见[requirements.txt](https://atomgit.com/mindspore/mindscience/blob/master/MindElec/requirements.txt)。 ### 安装方式 @@ -30,7 +30,7 @@ MindSpore Elec中包含了多个AI电磁仿真案例，更多详情，请点击 pip install https://ms-release.obs.cn-north-4.myhuaweicloud.com/{ms_version}/mindscience/{arch}/mindscience_mindelec_ascend-{me_version}-{python_version}-linux_{arch}.whl -i https://pypi.tuna.tsinghua.edu.cn/simple ``` -> - 在联网状态下，安装whl包时会自动下载MindSpore Elec安装包的依赖项（依赖项详情参见[setup.py](https://atomgit.com/mindspore-lab/mindscience/blob/master/MindElec/setup.py)），点云数据采样依赖[pythonocc](https://github.com/tpaviot/pythonocc-core)，需自行安装。 +> - 在联网状态下，安装whl包时会自动下载MindSpore Elec安装包的依赖项（依赖项详情参见[setup.py](https://atomgit.com/mindspore/mindscience/blob/master/MindElec/setup.py)），点云数据采样依赖[pythonocc](https://github.com/tpaviot/pythonocc-core)，需自行安装。 > - `{arch}`表示系统架构，例如使用的Linux系统是x86架构64位时，`{arch}`应写为x86_64。如果系统是ARM架构64位，则写为aarch64。 > - `{ms_version}`表示与MindSpore Elec匹配的MindSpore版本号，例如下载0.1.0版本MindSpore Elec时，`{ms_version}`应写为1.5.0。 > - `{me_version}`表示MindSpore Elec版本号，例如下载0.1.0版本MindSpore Elec时，`{me_version}`应写为0.1.0。 diff --git a/docs/mindelec/docs/source_zh_cn/parameterization.md b/docs/mindelec/docs/source_zh_cn/parameterization.md index 2a2a6b21f1f4d51db5cc9447dd9b95db68aeb2b8..2a8470cdc552e53e91090da06f19be4cb35ccff4 100644 --- a/docs/mindelec/docs/source_zh_cn/parameterization.md +++ b/docs/mindelec/docs/source_zh_cn/parameterization.md @@ -14,7 +14,7 @@ MindSpore Elec通过AI方法跳过传统数值方法的迭代计算直接得到 - 点云方案实现的是从天线/手机的采样点云到仿真结果的映射，该方案先将手机结构文件转化为点云张量数据，（压缩后）使用卷积神经网络提取结构特征，再通过数层全连接层映射到最终的仿真结果（S参数），该方案的优点是适用于结构参数数量或种类可能发生变化的复杂工况。 > 本例面向Atlas训练系列产品，你可以在这里下载完整的样例代码： -> +> ## 目标场景 @@ -40,7 +40,7 @@ PEC金属板置于一定厚度的PCB长方体之上，呈现为左右对称蝶 该数据已经提供为.npy文件，可从以下地址下载。 - + ## 参数化电磁仿真 diff --git a/docs/mindelec/docs/source_zh_cn/point_cloud.md b/docs/mindelec/docs/source_zh_cn/point_cloud.md index a89f299e7982ae9324b96732c0033dba5af0d887..788b7b158b07334eacc08e30c18d979b604caa0d 100644 --- a/docs/mindelec/docs/source_zh_cn/point_cloud.md +++ b/docs/mindelec/docs/source_zh_cn/point_cloud.md @@ -9,7 +9,7 @@ 传统电磁仿真计算通常使用基于有限元或有限差分的方法计算电磁场，这些方法需要复杂的网格剖分与迭代计算，整体流程耗时长，影响产品研发效率。MindSpore Elec提供一种新的电磁场端到端AI计算方法，该方法基于点云数据，跳过网格剖分与迭代求解，直接计算仿真区域内电磁场，大幅提升整体仿真速度，助力产品高效研发。 > 本例面向Atlas训练系列产品，你可以在这里下载完整的样例代码： -> +> ## 整体流程 diff --git a/docs/mindelec/docs/source_zh_cn/time_domain_maxwell.md b/docs/mindelec/docs/source_zh_cn/time_domain_maxwell.md index 6e2f7f8c24dadeb587e1ce02da2e3955300038c9..a8b71fbffac382aa2b716eaf7226d05b6866671a 100644 --- a/docs/mindelec/docs/source_zh_cn/time_domain_maxwell.md +++ b/docs/mindelec/docs/source_zh_cn/time_domain_maxwell.md @@ -7,7 +7,7 @@ 人工智能技术的蓬勃发展为科学计算提供了新的范式。MindSpore Elec套件提供了物理驱动和数据驱动的AI方法。物理驱动的AI方法结合物理方程和初边界条件进行模型的训练，相比于数据驱动而言，其优势在于无需监督数据。本案例教程重点介绍物理驱动的AI方法求解点源时域麦克斯韦方程。 > 本例面向Atlas训练系列产品，你可以在这里下载完整的样例代码： -> +> ## 麦克斯韦方程组 diff --git a/docs/mindflow/docs/source_en/cfd_solver/acoustic.ipynb b/docs/mindflow/docs/source_en/cfd_solver/acoustic.ipynb index 95d09de75a0a1ccd301d68ed052cede669cecaa4..5b69daa36e28c58e6e7e24d91ed31aa2b8cf3b7d 100644 --- a/docs/mindflow/docs/source_en/cfd_solver/acoustic.ipynb +++ b/docs/mindflow/docs/source_en/cfd_solver/acoustic.ipynb @@ -55,7 +55,7 @@ "- $\\tilde{\\Delta}$ is the normalized Laplace operator, which is the Laplace operator when the grid spacing is 1.\n", "- $f^*$ the mask that marks the source position, with a value of 1 at the source and 0 at other positions.\n", "\n", - "The `src` package in this case can be downloaded at [src](https://atomgit.com/mindspore-lab/mindscience/tree/master/MindFlow/applications/cfd/acoustic/src)." + "The `src` package in this case can be downloaded at [src](https://atomgit.com/mindspore/mindscience/tree/master/MindFlow/applications/cfd/acoustic/src)." ] }, { @@ -85,9 +85,9 @@ "source": [ "## Define input parameters and output sampling method\n", "\n", - "The required inputs for this case are dimensional 2D velocity field, source location list, and source waveform. The input file name is specified in the [config.yaml](https://atomgit.com/mindspore-lab/mindscience/blob/master/MindFlow/applications/cfd/acoustic/config.yaml) file. For user convenience, pre-set inputs are provided [here](https://download-mindspore.osinfra.cn/mindscience/mindflow/dataset/applications/cfd/acoustic). Please download the data and put them in `./dataset` in the case directory. The data include the velocity field `velocity.npy`, source location list `srclocs.csv`, and source waveform `srcwaves.csv`. Users can modify the input parameters based on the input file format.\n", + "The required inputs for this case are dimensional 2D velocity field, source location list, and source waveform. The input file name is specified in the [config.yaml](https://atomgit.com/mindspore/mindscience/blob/master/MindFlow/applications/cfd/acoustic/config.yaml) file. For user convenience, pre-set inputs are provided [here](https://download-mindspore.osinfra.cn/mindscience/mindflow/dataset/applications/cfd/acoustic). Please download the data and put them in `./dataset` in the case directory. The data include the velocity field `velocity.npy`, source location list `srclocs.csv`, and source waveform `srcwaves.csv`. Users can modify the input parameters based on the input file format.\n", "\n", - "The output is a spatiotemporal distribution of the wavefield. To specify how the output is sampled in time and frequency, parameters such as `dt` and `nt` need to be specified in the [config.yaml](https://atomgit.com/mindspore-lab/mindscience/blob/master/MindFlow/applications/cfd/acoustic/config.yaml) file.\n", + "The output is a spatiotemporal distribution of the wavefield. To specify how the output is sampled in time and frequency, parameters such as `dt` and `nt` need to be specified in the [config.yaml](https://atomgit.com/mindspore/mindscience/blob/master/MindFlow/applications/cfd/acoustic/config.yaml) file.\n", "\n", "Since the sampling rate of the input source waveform in time may differ from the required output, interpolation needs to be performed." ] @@ -135,7 +135,7 @@ "source": [ "## Select desired frequency points\n", "\n", - "With the output sampling method determined, all the desired frequency points are in turn determined. However, in order to reduce computational load, it is also possible to select only a portion of the frequency points for calculation, while obtaining the remaining frequency points through interpolation. The specific frequency point downsampling method is specified by the `downsample_mode` and `downsample_rate` in the [config.yaml](https://atomgit.com/mindspore-lab/mindscience/blob/master/MindFlow/applications/cfd/acoustic/config.yaml) file. The default is no downsampling, which means solving all frequency points except $\\omega=0$." + "With the output sampling method determined, all the desired frequency points are in turn determined. However, in order to reduce computational load, it is also possible to select only a portion of the frequency points for calculation, while obtaining the remaining frequency points through interpolation. The specific frequency point downsampling method is specified by the `downsample_mode` and `downsample_rate` in the [config.yaml](https://atomgit.com/mindspore/mindscience/blob/master/MindFlow/applications/cfd/acoustic/config.yaml) file. The default is no downsampling, which means solving all frequency points except $\\omega=0$." ] }, { diff --git a/docs/mindflow/docs/source_en/cfd_solver/couette.ipynb b/docs/mindflow/docs/source_en/cfd_solver/couette.ipynb index a887173c1088e07c9500d73ad2deafb965f890d7..e16105394e31524fc96142e6daf7c1eb80a7b1f0 100644 --- a/docs/mindflow/docs/source_en/cfd_solver/couette.ipynb +++ b/docs/mindflow/docs/source_en/cfd_solver/couette.ipynb @@ -43,7 +43,7 @@ "u(0, t)=0, \\quad u(h, t)=U, \\quad t>0\n", "$$\n", "\n", - "The following `src` pacakage can be downloaded in [src](https://atomgit.com/mindspore-lab/mindscience/tree/master/MindFlow/applications/cfd/couette/src)." + "The following `src` pacakage can be downloaded in [src](https://atomgit.com/mindspore/mindscience/tree/master/MindFlow/applications/cfd/couette/src)." ] }, { @@ -74,7 +74,7 @@ "source": [ "## Defining Simulator and RunTime\n", "\n", - "The mesh, material, runtime, boundary conditions and numerical methods are defined in [couette.yaml](https://atomgit.com/mindspore-lab/mindscience/blob/master/MindFlow/applications/cfd/couette/couette.yaml)." + "The mesh, material, runtime, boundary conditions and numerical methods are defined in [couette.yaml](https://atomgit.com/mindspore/mindscience/blob/master/MindFlow/applications/cfd/couette/couette.yaml)." ] }, { diff --git a/docs/mindflow/docs/source_en/cfd_solver/lax_tube.ipynb b/docs/mindflow/docs/source_en/cfd_solver/lax_tube.ipynb index 9d581a1f5f71c39f09a879ea91c2c8e83181d786..92e279742fb660b54002b4edf11b483a4f605e4a 100644 --- a/docs/mindflow/docs/source_en/cfd_solver/lax_tube.ipynb +++ b/docs/mindflow/docs/source_en/cfd_solver/lax_tube.ipynb @@ -39,7 +39,7 @@ "\n", "The Neumann boundary condition is applied on both side of the tube.\n", "\n", - "The following `src` pacakage can be downloaded in [src](https://atomgit.com/mindspore-lab/mindscience/tree/master/MindFlow/applications/cfd/lax/src)." + "The following `src` pacakage can be downloaded in [src](https://atomgit.com/mindspore/mindscience/tree/master/MindFlow/applications/cfd/lax/src)." ] }, { @@ -66,7 +66,7 @@ "source": [ "## Defining Simulator and RunTime\n", "\n", - "The mesh, material, runtime, boundary conditions and numerical methods are defined in [numeric.yaml](https://atomgit.com/mindspore-lab/mindscience/blob/master/MindFlow/applications/cfd/lax/numeric.yaml)." + "The mesh, material, runtime, boundary conditions and numerical methods are defined in [numeric.yaml](https://atomgit.com/mindspore/mindscience/blob/master/MindFlow/applications/cfd/lax/numeric.yaml)." ] }, { diff --git a/docs/mindflow/docs/source_en/cfd_solver/riemann2d.ipynb b/docs/mindflow/docs/source_en/cfd_solver/riemann2d.ipynb index 5208f5a41b89f6370d62ba047aa3f747a73d999c..530f733c3101a4123623926c7e2f0091b1bb4b3c 100644 --- a/docs/mindflow/docs/source_en/cfd_solver/riemann2d.ipynb +++ b/docs/mindflow/docs/source_en/cfd_solver/riemann2d.ipynb @@ -44,7 +44,7 @@ "\\left(\\begin{matrix} \\rho \\\\ u \\\\ v \\\\ p \\\\\\end{matrix}\\right)_{x>0.5, y<0.5} = \\left(\\begin{matrix} 0.5323 \\\\ 0.0 \\\\ 1.206 \\\\ 0.3 \\\\\\end{matrix}\\right)\n", "$$\n", "\n", - "The following `src` pacakage can be downloaded in [src](https://atomgit.com/mindspore-lab/mindscience/tree/master/MindFlow/applications/cfd/riemann2d/src)." + "The following `src` pacakage can be downloaded in [src](https://atomgit.com/mindspore/mindscience/tree/master/MindFlow/applications/cfd/riemann2d/src)." ] }, { @@ -71,7 +71,7 @@ "source": [ "## Defining Simulator and RunTime\n", "\n", - "The mesh, material, runtime, boundary conditions and numerical methods are defined in [numeric.yaml](https://atomgit.com/mindspore-lab/mindscience/blob/master/MindFlow/applications/cfd/riemann2d/numeric.yaml)." + "The mesh, material, runtime, boundary conditions and numerical methods are defined in [numeric.yaml](https://atomgit.com/mindspore/mindscience/blob/master/MindFlow/applications/cfd/riemann2d/numeric.yaml)." ] }, { diff --git a/docs/mindflow/docs/source_en/cfd_solver/sod_tube.ipynb b/docs/mindflow/docs/source_en/cfd_solver/sod_tube.ipynb index c30075e774faac403416ec3678bf1b5f345d8c9e..83de853014157d6b424b0eed43bc304e7a43fd69 100644 --- a/docs/mindflow/docs/source_en/cfd_solver/sod_tube.ipynb +++ b/docs/mindflow/docs/source_en/cfd_solver/sod_tube.ipynb @@ -39,7 +39,7 @@ "\n", "The Neumann boundary condition is applied on both side of the tube.\n", "\n", - "The following `src` pacakage can be downloaded in [src](https://atomgit.com/mindspore-lab/mindscience/tree/master/MindFlow/applications/cfd/sod/src)." + "The following `src` pacakage can be downloaded in [src](https://atomgit.com/mindspore/mindscience/tree/master/MindFlow/applications/cfd/sod/src)." ] }, { @@ -66,7 +66,7 @@ "source": [ "## Defining Simulator and RunTime\n", "\n", - "The mesh, material, runtime, boundary conditions and numerical methods are defined in [numeric.yaml](https://atomgit.com/mindspore-lab/mindscience/blob/master/MindFlow/applications/cfd/sod/numeric.yaml)." + "The mesh, material, runtime, boundary conditions and numerical methods are defined in [numeric.yaml](https://atomgit.com/mindspore/mindscience/blob/master/MindFlow/applications/cfd/sod/numeric.yaml)." ] }, { diff --git a/docs/mindflow/docs/source_en/data_driven/2D_steady.ipynb b/docs/mindflow/docs/source_en/data_driven/2D_steady.ipynb index aa9401ae369771307bef23954fa71a60e08ee964..2c42313c3e7283ce66025b62f814b907b6a8eee9 100644 --- a/docs/mindflow/docs/source_en/data_driven/2D_steady.ipynb +++ b/docs/mindflow/docs/source_en/data_driven/2D_steady.ipynb @@ -131,7 +131,7 @@ "cell_type": "markdown", "metadata": {}, "source": [ - "The following `src` pacakage can be downloaded in [applications/data_driven/airfoil/2D_steady/src](https://atomgit.com/mindspore-lab/mindscience/tree/master/MindFlow/applications/data_driven/airfoil/2D_steady/src)." + "The following `src` pacakage can be downloaded in [applications/data_driven/airfoil/2D_steady/src](https://atomgit.com/mindspore/mindscience/tree/master/MindFlow/applications/data_driven/airfoil/2D_steady/src)." ] }, { @@ -168,7 +168,7 @@ "source": [ "## Configuring Network and Training Parameters\n", "\n", - "Read four types of parameters from the configuration file, which are model-related parameters (model), data-related parameters (data), optimizer-related parameters (optimizer), output-related parameters (ckpt) and validation-related parameters(eval). You can get these parameters from [config](https://atomgit.com/mindspore-lab/mindscience/blob/master/MindFlow/applications/data_driven/airfoil/2D_steady/configs/vit.yaml)." + "Read four types of parameters from the configuration file, which are model-related parameters (model), data-related parameters (data), optimizer-related parameters (optimizer), output-related parameters (ckpt) and validation-related parameters(eval). You can get these parameters from [config](https://atomgit.com/mindspore/mindscience/blob/master/MindFlow/applications/data_driven/airfoil/2D_steady/configs/vit.yaml)." ] }, { @@ -232,7 +232,7 @@ "source": [ "This file contains 2808 flow field data for 51 supercritical airfoils in the range of Ma=0.73 and different angles of attack (- 2.0 to 4.6). Where, the data dimensions of input are (13, 192, 384), 192, and 384 are the grid resolution after Jacobi conversion, and 13 are different feature dimensions, respectively ($AOA$, $x$, $y$, $x_{i,0}$, $y_{i,0}$, $\\xi_x$, $\\xi_y$, $\\eta_x$, $\\eta_y$, $x_\\xi$, $x_\\eta$, $y_\\xi$, $y_\\eta$).\n", "\n", - "The data dimension of Label is (288, 768), which can be passed through the patchify function in [utils.py](https://atomgit.com/mindspore-lab/mindscience/blob/master/MindFlow/applications/data_driven/airfoil/2D_steady/src/utils.py)(16 × 16). The flow field data (u, v, p) obtained after the operation can be restored to (3, 192, 384) through the unpatchify operation in [utils.py](https://atomgit.com/mindspore-lab/mindscience/blob/master/MindFlow/applications/data_driven/airfoil/2D_steady/src/utils.py). Users can customize and select based on their own network input and output design.\n", + "The data dimension of Label is (288, 768), which can be passed through the patchify function in [utils.py](https://atomgit.com/mindspore/mindscience/blob/master/MindFlow/applications/data_driven/airfoil/2D_steady/src/utils.py)(16 × 16). The flow field data (u, v, p) obtained after the operation can be restored to (3, 192, 384) through the unpatchify operation in [utils.py](https://atomgit.com/mindspore/mindscience/blob/master/MindFlow/applications/data_driven/airfoil/2D_steady/src/utils.py). Users can customize and select based on their own network input and output design.\n", "\n", "First, convert the CFD dataset into tensor data, and then convert the tensor data into MindRecord. Design an AI data efficient conversion tool to achieve feature extraction of complex boundary and non-standard data of airfoil flow fields. The information of x, y, and u before and after conversion is shown in the following figure.\n", "\n", @@ -533,7 +533,7 @@ "source": [ "## Model Inference\n", "\n", - "After model training is complete, you can call the train function in [train.py](https://atomgit.com/mindspore-lab/mindscience/blob/master/MindFlow/applications/data_driven/airfoil/2D_steady/train.py). If train_mode is set to \"eval\", inference can be performed. If train_mode is set to \"finetune\", transfer learning can be performed.\n", + "After model training is complete, you can call the train function in [train.py](https://atomgit.com/mindspore/mindscience/blob/master/MindFlow/applications/data_driven/airfoil/2D_steady/train.py). If train_mode is set to \"eval\", inference can be performed. If train_mode is set to \"finetune\", transfer learning can be performed.\n", "\n", "When designing a new airfoil, various initial boundary conditions (such as different angles of attack or Mach number) need to be considered for aerodynamic performance evaluation. In order to improve the generalization of the model and improve its utility in engineering scenarios, we can adopt the transfer learning mode. The method is as follows: pre-training the model in large-scale datasets, and fine-tuning the model in small datasets, so as to realize the inference generalization of the model to the new working conditions. Considering the trade-off between precision and time consumption, we considered four different size datasets to obtain different pre-trained models. Compared with pre-training on smaller datasets, pre-training requires less time, but the prediction precision is lower. Pre-training on larger data sets can produce more accurate results, but requires more pre-training time.\n", "\n", diff --git a/docs/mindflow/docs/source_en/data_driven/burgers_FNO1D.ipynb b/docs/mindflow/docs/source_en/data_driven/burgers_FNO1D.ipynb index 209451d8ba8cfa9428ec514981220004382e7bb9..403b43bcffbd0f05070d8116f9e95b94e7baa3d6 100644 --- a/docs/mindflow/docs/source_en/data_driven/burgers_FNO1D.ipynb +++ b/docs/mindflow/docs/source_en/data_driven/burgers_FNO1D.ipynb @@ -126,7 +126,7 @@ "cell_type": "markdown", "metadata": {}, "source": [ - "The following `src` pacakage can be downloaded in [applications/data_driven/burgers/fno1d/src](https://atomgit.com/mindspore-lab/mindscience/tree/master/MindFlow/applications/data_driven/burgers/fno1d/src)." + "The following `src` pacakage can be downloaded in [applications/data_driven/burgers/fno1d/src](https://atomgit.com/mindspore/mindscience/tree/master/MindFlow/applications/data_driven/burgers/fno1d/src)." ] }, { @@ -153,7 +153,7 @@ "cell_type": "markdown", "metadata": {}, "source": [ - "You can get parameters of model, data and optimizer from [config](https://atomgit.com/mindspore-lab/mindscience/blob/master/MindFlow/applications/data_driven/burgers/fno1d/configs/fno1d.yaml)." + "You can get parameters of model, data and optimizer from [config](https://atomgit.com/mindspore/mindscience/blob/master/MindFlow/applications/data_driven/burgers/fno1d/configs/fno1d.yaml)." ] }, { @@ -244,7 +244,7 @@ "\n", "- The Decoding layer corresponds to `FNO1D.fc1` and `FNO1D.fc2` in the case to obtain the final predictive value.\n", "\n", - "The initialization of the model based on the network above, parameters can be modified in [configuration file](https://atomgit.com/mindspore-lab/mindscience/blob/master/MindFlow/applications/data_driven/burgers/fno1d/configs/fno1d.yaml)." + "The initialization of the model based on the network above, parameters can be modified in [configuration file](https://atomgit.com/mindspore/mindscience/blob/master/MindFlow/applications/data_driven/burgers/fno1d/configs/fno1d.yaml)." ] }, { diff --git a/docs/mindflow/docs/source_en/data_driven/burgers_KNO1D.ipynb b/docs/mindflow/docs/source_en/data_driven/burgers_KNO1D.ipynb index d774a801f9421a37f13b869381c049e1bf5fad73..8ab558af242a2e53f7369ad1558cd37ee47470e5 100644 --- a/docs/mindflow/docs/source_en/data_driven/burgers_KNO1D.ipynb +++ b/docs/mindflow/docs/source_en/data_driven/burgers_KNO1D.ipynb @@ -146,7 +146,7 @@ } }, "source": [ - "The following `src` pacakage can be downloaded in [applications/data_driven/burgers/kno1d/src](https://atomgit.com/mindspore-lab/mindscience/tree/master/MindFlow/applications/data_driven/burgers/kno1d/src)." + "The following `src` pacakage can be downloaded in [applications/data_driven/burgers/kno1d/src](https://atomgit.com/mindspore/mindscience/tree/master/MindFlow/applications/data_driven/burgers/kno1d/src)." ] }, { @@ -190,7 +190,7 @@ } }, "source": [ - "You can get hyperparameters of model, data and optimizer from [config](https://atomgit.com/mindspore-lab/mindscience/blob/master/MindFlow/applications/data_driven/burgers/kno1d/configs/kno1d.yaml)." + "You can get hyperparameters of model, data and optimizer from [config](https://atomgit.com/mindspore/mindscience/blob/master/MindFlow/applications/data_driven/burgers/kno1d/configs/kno1d.yaml)." ] }, { diff --git a/docs/mindflow/docs/source_en/data_driven/burgers_SNO1D.ipynb b/docs/mindflow/docs/source_en/data_driven/burgers_SNO1D.ipynb index 6bf07f9551f9b8e6c8fdae3954544739d70eca18..73f9eadc7ff61504ba36320796bd0c36e730ad3f 100644 --- a/docs/mindflow/docs/source_en/data_driven/burgers_SNO1D.ipynb +++ b/docs/mindflow/docs/source_en/data_driven/burgers_SNO1D.ipynb @@ -128,7 +128,7 @@ "cell_type": "markdown", "metadata": {}, "source": [ - "The following `src` pacakage can be downloaded in [applications/data_driven/burgers/sno1d/src](https://atomgit.com/mindspore-lab/mindscience/tree/master/MindFlow/applications/data_driven/burgers/sno1d/src)." + "The following `src` pacakage can be downloaded in [applications/data_driven/burgers/sno1d/src](https://atomgit.com/mindspore/mindscience/tree/master/MindFlow/applications/data_driven/burgers/sno1d/src)." ] }, { @@ -240,7 +240,7 @@ "\n", "- The decoding layer corresponds to `SNO1D.decoder` and consists of two convolutions.The decoder is used to obtain the final prediction.\n", "\n", - "The initialization of the model based on the network above, parameters can be modified in [configuration file](https://atomgit.com/mindspore-lab/mindscience/blob/master/MindFlow/applications/data_driven/burgers/sno1d/configs/sno1d.yaml)." + "The initialization of the model based on the network above, parameters can be modified in [configuration file](https://atomgit.com/mindspore/mindscience/blob/master/MindFlow/applications/data_driven/burgers/sno1d/configs/sno1d.yaml)." ] }, { diff --git a/docs/mindflow/docs/source_en/data_driven/flow_around_sphere.ipynb b/docs/mindflow/docs/source_en/data_driven/flow_around_sphere.ipynb index df1db2d855391387ca053fcbefc1f2f162b079e9..0601cc6ca3b1aca75e32fc87adacb61617388082 100644 --- a/docs/mindflow/docs/source_en/data_driven/flow_around_sphere.ipynb +++ b/docs/mindflow/docs/source_en/data_driven/flow_around_sphere.ipynb @@ -749,7 +749,7 @@ } }, "source": [ - "After completing the model training, run [eval.py](https://atomgit.com/mindspore-lab/mindscience/blob/master/MindFlow/applications/data_driven/flow_around_sphere/eval.py) to control the read model path through both the console and configuration files. This will enable you to efficiently and accurately infer the long-term 3D flow field in the future, based on the initial flow field at any given moment." + "After completing the model training, run [eval.py](https://atomgit.com/mindspore/mindscience/blob/master/MindFlow/applications/data_driven/flow_around_sphere/eval.py) to control the read model path through both the console and configuration files. This will enable you to efficiently and accurately infer the long-term 3D flow field in the future, based on the initial flow field at any given moment." ] }, { diff --git a/docs/mindflow/docs/source_en/data_driven/navier_stokes_FNO2D.ipynb b/docs/mindflow/docs/source_en/data_driven/navier_stokes_FNO2D.ipynb index 4af400d0bc0a600761b89a796c220686d1e2dcbc..b7951b84348eaa1d442f6d6a0d425113f16bc250 100644 --- a/docs/mindflow/docs/source_en/data_driven/navier_stokes_FNO2D.ipynb +++ b/docs/mindflow/docs/source_en/data_driven/navier_stokes_FNO2D.ipynb @@ -126,7 +126,7 @@ "cell_type": "markdown", "metadata": {}, "source": [ - "The following `src` pacakage can be downloaded in [applications/data_driven/navier_stokes/fno2d/src](https://atomgit.com/mindspore-lab/mindscience/tree/master/MindFlow/applications/data_driven/navier_stokes/fno2d/src). Parameters can be modified in [config](https://atomgit.com/mindspore-lab/mindscience/blob/master/MindFlow/applications/data_driven/navier_stokes/fno2d/configs/fno2d.yaml)." + "The following `src` pacakage can be downloaded in [applications/data_driven/navier_stokes/fno2d/src](https://atomgit.com/mindspore/mindscience/tree/master/MindFlow/applications/data_driven/navier_stokes/fno2d/src). Parameters can be modified in [config](https://atomgit.com/mindspore/mindscience/blob/master/MindFlow/applications/data_driven/navier_stokes/fno2d/configs/fno2d.yaml)." ] }, { diff --git a/docs/mindflow/docs/source_en/data_driven/navier_stokes_FNO3D.ipynb b/docs/mindflow/docs/source_en/data_driven/navier_stokes_FNO3D.ipynb index 47d76ec3034351e059bf4c5cb0c3de2dbc963a6d..a358370bf230fb5e20b67b21f42179809c0add58 100644 --- a/docs/mindflow/docs/source_en/data_driven/navier_stokes_FNO3D.ipynb +++ b/docs/mindflow/docs/source_en/data_driven/navier_stokes_FNO3D.ipynb @@ -120,7 +120,7 @@ "cell_type": "markdown", "metadata": {}, "source": [ - "The following `src` pacakage can be downloaded in [applications/data_driven/navier_stokes/fno3d/src](https://atomgit.com/mindspore-lab/mindscience/tree/master/MindFlow/applications/data_driven/navier_stokes/fno3d/src).\n" + "The following `src` pacakage can be downloaded in [applications/data_driven/navier_stokes/fno3d/src](https://atomgit.com/mindspore/mindscience/tree/master/MindFlow/applications/data_driven/navier_stokes/fno3d/src).\n" ] }, { diff --git a/docs/mindflow/docs/source_en/data_driven/navier_stokes_KNO2D.ipynb b/docs/mindflow/docs/source_en/data_driven/navier_stokes_KNO2D.ipynb index 23d248cb2980aa58e4d1255e9c9bcd7f421be1e8..c8abf6ffd166b376c8f20020ec09b3d581edbc02 100644 --- a/docs/mindflow/docs/source_en/data_driven/navier_stokes_KNO2D.ipynb +++ b/docs/mindflow/docs/source_en/data_driven/navier_stokes_KNO2D.ipynb @@ -149,7 +149,7 @@ } }, "source": [ - "The following `src` pacakage can be downloaded in [applications/data_driven/navier_stokes/kno2d/src](https://atomgit.com/mindspore-lab/mindscience/tree/master/MindFlow/applications/data_driven/navier_stokes/kno2d/src)." + "The following `src` pacakage can be downloaded in [applications/data_driven/navier_stokes/kno2d/src](https://atomgit.com/mindspore/mindscience/tree/master/MindFlow/applications/data_driven/navier_stokes/kno2d/src)." ] }, { @@ -194,7 +194,7 @@ } }, "source": [ - "You can get hyperparameters of model, data and optimizer from [config](https://atomgit.com/mindspore-lab/mindscience/blob/master/MindFlow/applications/data_driven/navier_stokes/kno2d/configs/kno2d.yaml)." + "You can get hyperparameters of model, data and optimizer from [config](https://atomgit.com/mindspore/mindscience/blob/master/MindFlow/applications/data_driven/navier_stokes/kno2d/configs/kno2d.yaml)." ] }, { diff --git a/docs/mindflow/docs/source_en/data_driven/navier_stokes_SNO2D.ipynb b/docs/mindflow/docs/source_en/data_driven/navier_stokes_SNO2D.ipynb index f9010b790554a5d44ada61b2a0e9447d413a2176..89bfb45b8d25b63de23364245ee803d499ecbbd6 100644 --- a/docs/mindflow/docs/source_en/data_driven/navier_stokes_SNO2D.ipynb +++ b/docs/mindflow/docs/source_en/data_driven/navier_stokes_SNO2D.ipynb @@ -132,7 +132,7 @@ "cell_type": "markdown", "metadata": {}, "source": [ - "The following `src` pacakage can be downloaded in [applications/data_driven/navier_stokes/sno2d/src](https://atomgit.com/mindspore-lab/mindscience/tree/master/MindFlow/applications/data_driven/navier_stokes/sno2d/src)." + "The following `src` pacakage can be downloaded in [applications/data_driven/navier_stokes/sno2d/src](https://atomgit.com/mindspore/mindscience/tree/master/MindFlow/applications/data_driven/navier_stokes/sno2d/src)." ] }, { diff --git a/docs/mindflow/docs/source_en/data_driven/navier_stokes_SNO3D.ipynb b/docs/mindflow/docs/source_en/data_driven/navier_stokes_SNO3D.ipynb index cc8f7f64222404d3e31d3d2894d10283f9b9533e..2627676a823e500810a5ed4ad3859f9cce0cf426 100644 --- a/docs/mindflow/docs/source_en/data_driven/navier_stokes_SNO3D.ipynb +++ b/docs/mindflow/docs/source_en/data_driven/navier_stokes_SNO3D.ipynb @@ -120,7 +120,7 @@ "cell_type": "markdown", "metadata": {}, "source": [ - "The following `src` pacakage can be downloaded in [applications/data_driven/navier_stokes/sno3d/src](https://atomgit.com/mindspore-lab/mindscience/tree/master/MindFlow/applications/data_driven/navier_stokes/sno3d/src).\n" + "The following `src` pacakage can be downloaded in [applications/data_driven/navier_stokes/sno3d/src](https://atomgit.com/mindspore/mindscience/tree/master/MindFlow/applications/data_driven/navier_stokes/sno3d/src).\n" ] }, { diff --git a/docs/mindflow/docs/source_en/data_mechanism_fusion/pde_net.ipynb b/docs/mindflow/docs/source_en/data_mechanism_fusion/pde_net.ipynb index cf874535bf4c541278631532d6e4881733254842..0795bf8ecbb09d86683e50b7b632e5c974da527a 100644 --- a/docs/mindflow/docs/source_en/data_mechanism_fusion/pde_net.ipynb +++ b/docs/mindflow/docs/source_en/data_mechanism_fusion/pde_net.ipynb @@ -125,7 +125,7 @@ "cell_type": "markdown", "metadata": {}, "source": [ - "The following `src` pacakage can be downloaded in [applications/data_mechanism_fusion/pde_net/src](https://atomgit.com/mindspore-lab/mindscience/tree/master/MindFlow/applications/data_mechanism_fusion/pde_net/src)." + "The following `src` pacakage can be downloaded in [applications/data_mechanism_fusion/pde_net/src](https://atomgit.com/mindspore/mindscience/tree/master/MindFlow/applications/data_mechanism_fusion/pde_net/src)." ] }, { @@ -148,7 +148,7 @@ "cell_type": "markdown", "metadata": {}, "source": [ - "Parameter can be modified in [configuration file](https://atomgit.com/mindspore-lab/mindscience/blob/master/MindFlow/applications/data_mechanism_fusion/pde_net/configs/pde_net.yaml)." + "Parameter can be modified in [configuration file](https://atomgit.com/mindspore/mindscience/blob/master/MindFlow/applications/data_mechanism_fusion/pde_net/configs/pde_net.yaml)." ] }, { diff --git a/docs/mindflow/docs/source_en/data_mechanism_fusion/phympgn.ipynb b/docs/mindflow/docs/source_en/data_mechanism_fusion/phympgn.ipynb index 5a66fd69a6f7e6563b2e92cfd07f2ff00c884300..fd4fc24bc6dd14dcba88870ffc656421666c4f0d 100644 --- a/docs/mindflow/docs/source_en/data_mechanism_fusion/phympgn.ipynb +++ b/docs/mindflow/docs/source_en/data_mechanism_fusion/phympgn.ipynb @@ -115,7 +115,7 @@ "source": [ "- Make sure the required dependency libraries (such as MindSpore) have been installed\n", "- Ensure the [cylinder flow dataset](https://download-mindspore.osinfra.cn/mindscience/mindflow/dataset/applications/data_mechanism_fusion/PhyMPGN/) has been downloaded\n", - "- Verify that the data and model weight storage paths have been properly configured in the [yamls/train.yaml](https://atomgit.com/mindspore-lab/mindscience/blob/master/MindFlow/applications/data_mechanism_fusion/phympgn/yamls/train.yaml) configuration file" + "- Verify that the data and model weight storage paths have been properly configured in the [yamls/train.yaml](https://atomgit.com/mindspore/mindscience/blob/master/MindFlow/applications/data_mechanism_fusion/phympgn/yamls/train.yaml) configuration file" ] }, { diff --git a/docs/mindflow/docs/source_en/features/solve_pinns_by_mindflow.ipynb b/docs/mindflow/docs/source_en/features/solve_pinns_by_mindflow.ipynb index f88bcb2c110403a33b5d0f368ad010c15be8a7c1..c2657be9210c66956ac823a8aa5410ea062395aa 100644 --- a/docs/mindflow/docs/source_en/features/solve_pinns_by_mindflow.ipynb +++ b/docs/mindflow/docs/source_en/features/solve_pinns_by_mindflow.ipynb @@ -119,7 +119,7 @@ "source": [ "## Training Dataset Construction\n", "\n", - "In this case, random sampling is performed according to the domain, initial condition and boundary condition to generate training data sets. [Disk](https://mindspore.cn/mindflow/docs/en/master/geometry/mindflow.geometry.Disk.html#mindflow.geometry.Disk) and [CSGXOR](https://mindspore.cn/mindflow/docs/en/master/geometry/mindflow.geometry.CSGXOR.html#mindflow.geometry.CSGXOR) are used to make a geometry with input and output boundaries, as well as domain. Download data construction [Python script](https://atomgit.com/mindspore-lab/mindscience/blob/master/MindFlow/features/solve_pinns_by_mindflow/src/dataset.py)." + "In this case, random sampling is performed according to the domain, initial condition and boundary condition to generate training data sets. [Disk](https://mindspore.cn/mindflow/docs/en/master/geometry/mindflow.geometry.Disk.html#mindflow.geometry.Disk) and [CSGXOR](https://mindspore.cn/mindflow/docs/en/master/geometry/mindflow.geometry.CSGXOR.html#mindflow.geometry.CSGXOR) are used to make a geometry with input and output boundaries, as well as domain. Download data construction [Python script](https://atomgit.com/mindspore/mindscience/blob/master/MindFlow/features/solve_pinns_by_mindflow/src/dataset.py)." ] }, { @@ -417,7 +417,7 @@ "cell_type": "markdown", "metadata": {}, "source": [ - "The following `Poisson2D` problem is defined based on the [Poisson](https://mindspore.cn/mindflow/docs/en/master/pde/mindflow.pde.Poisson.html#mindflow.pde.Poisson) base class combined with the governing equations and boundary conditions defined above. Download `Poisson2D` [Python script](https://atomgit.com/mindspore-lab/mindscience/blob/master/MindFlow/features/solve_pinns_by_mindflow/src/model.py)." + "The following `Poisson2D` problem is defined based on the [Poisson](https://mindspore.cn/mindflow/docs/en/master/pde/mindflow.pde.Poisson.html#mindflow.pde.Poisson) base class combined with the governing equations and boundary conditions defined above. Download `Poisson2D` [Python script](https://atomgit.com/mindspore/mindscience/blob/master/MindFlow/features/solve_pinns_by_mindflow/src/model.py)." ] }, { @@ -479,7 +479,7 @@ "source": [ "## Model Training\n", "\n", - "With **MindSpore version >= 2.0.0**, we can use the functional programming for training neural networks. Download training [Python script](https://atomgit.com/mindspore-lab/mindscience/blob/master/MindFlow/features/solve_pinns_by_mindflow/train.py)." + "With **MindSpore version >= 2.0.0**, we can use the functional programming for training neural networks. Download training [Python script](https://atomgit.com/mindspore/mindscience/blob/master/MindFlow/features/solve_pinns_by_mindflow/train.py)." ] }, { @@ -509,7 +509,7 @@ "cell_type": "markdown", "metadata": {}, "source": [ - "Download the calculate function of training process in [Python script](https://atomgit.com/mindspore-lab/mindscience/blob/master/MindFlow/features/solve_pinns_by_mindflow/src/utils.py)." + "Download the calculate function of training process in [Python script](https://atomgit.com/mindspore/mindscience/blob/master/MindFlow/features/solve_pinns_by_mindflow/src/utils.py)." ] }, { @@ -800,7 +800,7 @@ "source": [ "## Model Evaluation and Visualization\n", "\n", - "After training, all data points in the flow field can be inferred. And related results can be visualized. Download visulization [Python script](https://atomgit.com/mindspore-lab/mindscience/blob/master/MindFlow/features/solve_pinns_by_mindflow/src/utils.py)." + "After training, all data points in the flow field can be inferred. And related results can be visualized. Download visulization [Python script](https://atomgit.com/mindspore/mindscience/blob/master/MindFlow/features/solve_pinns_by_mindflow/src/utils.py)." ] }, { diff --git a/docs/mindflow/docs/source_en/index.rst b/docs/mindflow/docs/source_en/index.rst index 589d60c827c8103d96a392c467f0d667f57122f9..d55ef40605b65ddff0e0644bbd9024c05a409917 100644 --- a/docs/mindflow/docs/source_en/index.rst +++ b/docs/mindflow/docs/source_en/index.rst @@ -3,13 +3,13 @@ MindSpore Flow Introduction Flow simulation aims to solve the fluid governing equation under a given boundary condition by numerical methods, so as to realize the flow analysis, prediction and control. It is widely used in engineering design in aerospace, ship manufacturing, energy and power industries. The numerical methods of traditional flow simulation, such as finite volume method and finite difference method, are mainly implemented by commercial software, requiring physical modeling, mesh generation, numerical dispersion, iterative solution and other steps. The simulation process is complex and the calculation cycle is long. AI has powerful learning fitting and natural parallel inference capabilities, which can improve the efficiency of the flow simulation. -`MindSpore Flow `_ is a flow simulation suite developed based on MindSpore. It supports AI flow simulation in industries such as aerospace, ship manufacturing, and energy and power. It aims to provide efficient and easy-to-use AI computing flow simulation software for industrial research engineers, university professors and students. +`MindSpore Flow `_ is a flow simulation suite developed based on MindSpore. It supports AI flow simulation in industries such as aerospace, ship manufacturing, and energy and power. It aims to provide efficient and easy-to-use AI computing flow simulation software for industrial research engineers, university professors and students. .. raw:: html -Code repository address: +Code repository address: .. toctree:: :glob: diff --git a/docs/mindflow/docs/source_en/mindflow_install.md b/docs/mindflow/docs/source_en/mindflow_install.md index 12787a5dab87066b73d1b0dad54743a25b1aec55..4de4d28ff80b018bd9c236778c2a4df9a5762b7e 100644 --- a/docs/mindflow/docs/source_en/mindflow_install.md +++ b/docs/mindflow/docs/source_en/mindflow_install.md @@ -6,7 +6,7 @@ - The hardware platform should be Ascend, GPU. - See our [MindSpore Installation Guide](https://www.mindspore.cn/install/en) to install MindSpore. -- All other dependencies are included in [requirements.txt](https://atomgit.com/mindspore-lab/mindscience/blob/master/MindFlow/requirements.txt). +- All other dependencies are included in [requirements.txt](https://atomgit.com/mindspore/mindscience/blob/master/MindFlow/requirements.txt). - MindSpore Flow requires MindSpore version >=2.5.0, and Python version requires >=3.9. ## Installation diff --git a/docs/mindflow/docs/source_en/physics_driven/burgers1D.ipynb b/docs/mindflow/docs/source_en/physics_driven/burgers1D.ipynb index 599c6f6f84c3239043adce71b14f42b5f8c82f86..d6eb1589f0b0088546babe519f2303a3da2ecf7e 100644 --- a/docs/mindflow/docs/source_en/physics_driven/burgers1D.ipynb +++ b/docs/mindflow/docs/source_en/physics_driven/burgers1D.ipynb @@ -86,7 +86,7 @@ "cell_type": "markdown", "metadata": {}, "source": [ - "The following `src` pacakage can be downloaded in [applications/physics_driven/burgers/src](https://atomgit.com/mindspore-lab/mindscience/tree/master/MindFlow/applications/physics_driven/burgers/src)." + "The following `src` pacakage can be downloaded in [applications/physics_driven/burgers/src](https://atomgit.com/mindspore/mindscience/tree/master/MindFlow/applications/physics_driven/burgers/src)." ] }, { diff --git a/docs/mindflow/docs/source_en/physics_driven/darcy2D.ipynb b/docs/mindflow/docs/source_en/physics_driven/darcy2D.ipynb index 1edabf6a68ed3d525bfeea0fb49a3cde167ed526..5fe7a4b07537637a8e815b362a22638f1a2805b3 100644 --- a/docs/mindflow/docs/source_en/physics_driven/darcy2D.ipynb +++ b/docs/mindflow/docs/source_en/physics_driven/darcy2D.ipynb @@ -80,7 +80,7 @@ "cell_type": "markdown", "metadata": {}, "source": [ - "The following `src` pacakage can be downloaded in [applications/physics_driven/darcy/src](https://atomgit.com/mindspore-lab/mindscience/tree/master/MindFlow/applications/physics_driven/darcy/src)." + "The following `src` pacakage can be downloaded in [applications/physics_driven/darcy/src](https://atomgit.com/mindspore/mindscience/tree/master/MindFlow/applications/physics_driven/darcy/src)." ] }, { diff --git a/docs/mindflow/docs/source_en/physics_driven/kovasznay.ipynb b/docs/mindflow/docs/source_en/physics_driven/kovasznay.ipynb index bb2e227af36937f50c01c0104882e9f1a0c6e8d3..d50b493e8a4bbee9bc1113f0c5dbf3a8443d8f42 100644 --- a/docs/mindflow/docs/source_en/physics_driven/kovasznay.ipynb +++ b/docs/mindflow/docs/source_en/physics_driven/kovasznay.ipynb @@ -77,7 +77,7 @@ "source": [ "## Creating the Dataset\n", "\n", - "In this tutorial, we randomly sample the solution domain and boundary conditions to generate the training dataset and test dataset. The specific method can be found in [src/dataset.py](https://atomgit.com/mindspore-lab/mindscience/blob/master/MindFlow/applications/physics_driven/navier_stokes/kovasznay/src/dataset.py)." + "In this tutorial, we randomly sample the solution domain and boundary conditions to generate the training dataset and test dataset. The specific method can be found in [src/dataset.py](https://atomgit.com/mindspore/mindscience/blob/master/MindFlow/applications/physics_driven/navier_stokes/kovasznay/src/dataset.py)." ] }, { diff --git a/docs/mindflow/docs/source_en/physics_driven/navier_stokes2D.ipynb b/docs/mindflow/docs/source_en/physics_driven/navier_stokes2D.ipynb index fac4e5e6a8c74d9a489f9c866b6ba5bb3e621f34..fad47e39811aa746687b29a924733026054846fc 100644 --- a/docs/mindflow/docs/source_en/physics_driven/navier_stokes2D.ipynb +++ b/docs/mindflow/docs/source_en/physics_driven/navier_stokes2D.ipynb @@ -89,7 +89,7 @@ "cell_type": "markdown", "metadata": {}, "source": [ - "The following `src` pacakage can be downloaded in [applications/physics_driven/navier_stokes/cylinder_flow_forward/src](https://atomgit.com/mindspore-lab/mindscience/tree/master/MindFlow/applications/physics_driven/navier_stokes/cylinder_flow_forward/src)." + "The following `src` pacakage can be downloaded in [applications/physics_driven/navier_stokes/cylinder_flow_forward/src](https://atomgit.com/mindspore/mindscience/tree/master/MindFlow/applications/physics_driven/navier_stokes/cylinder_flow_forward/src)." ] }, { diff --git a/docs/mindflow/docs/source_en/physics_driven/navier_stokes_inverse.ipynb b/docs/mindflow/docs/source_en/physics_driven/navier_stokes_inverse.ipynb index 183e483860146e1ff7d3d4f7b7319b48518b60d7..953bfa2c38e32b3b0609f921ae4d92d2fb74eea9 100644 --- a/docs/mindflow/docs/source_en/physics_driven/navier_stokes_inverse.ipynb +++ b/docs/mindflow/docs/source_en/physics_driven/navier_stokes_inverse.ipynb @@ -86,7 +86,7 @@ "cell_type": "markdown", "metadata": {}, "source": [ - "The following `src` package can be downloaded in [applications/physics_driven/navier_stokes/cylinder_flow_inverse/src](https://atomgit.com/mindspore-lab/mindscience/tree/master/MindFlow/applications/physics_driven/navier_stokes/cylinder_flow_inverse/src)" + "The following `src` package can be downloaded in [applications/physics_driven/navier_stokes/cylinder_flow_inverse/src](https://atomgit.com/mindspore/mindscience/tree/master/MindFlow/applications/physics_driven/navier_stokes/cylinder_flow_inverse/src)" ] }, { @@ -111,7 +111,7 @@ "cell_type": "markdown", "metadata": {}, "source": [ - "The following `inverse_navier_stokes.yaml` can be downloaded in [applications/physics_driven/navier_stokes/cylinder_flow_inverse/configs/navier_stokes_inverse.yaml](https://atomgit.com/mindspore-lab/mindscience/blob/master/MindFlow/applications/physics_driven/navier_stokes/cylinder_flow_inverse/configs/navier_stokes_inverse.yaml)." + "The following `inverse_navier_stokes.yaml` can be downloaded in [applications/physics_driven/navier_stokes/cylinder_flow_inverse/configs/navier_stokes_inverse.yaml](https://atomgit.com/mindspore/mindscience/blob/master/MindFlow/applications/physics_driven/navier_stokes/cylinder_flow_inverse/configs/navier_stokes_inverse.yaml)." ] }, { diff --git a/docs/mindflow/docs/source_en/physics_driven/periodic_hill.ipynb b/docs/mindflow/docs/source_en/physics_driven/periodic_hill.ipynb index 0aa866b3abf0b63b6e8bcd04a8355857547a38d7..8df8983f4af50bb88ad49a424383da518ce2d0bd 100644 --- a/docs/mindflow/docs/source_en/physics_driven/periodic_hill.ipynb +++ b/docs/mindflow/docs/source_en/physics_driven/periodic_hill.ipynb @@ -46,7 +46,7 @@ "source": [ "## Preparation\n", "\n", - "Import the required libraries for training. The [src](https://atomgit.com/mindspore-lab/mindscience/tree/master/MindFlow/applications/physics_driven/navier_stokes/periodic_hill/src) folder includes functions for dataset processing, network models, and loss calculation.\n", + "Import the required libraries for training. The [src](https://atomgit.com/mindspore/mindscience/tree/master/MindFlow/applications/physics_driven/navier_stokes/periodic_hill/src) folder includes functions for dataset processing, network models, and loss calculation.\n", "\n", "Training is conducted using the graph mode (GRAPH) of the MindSpore framework, and it takes place on the GPU (by default) or Ascend (single card)." ] @@ -85,7 +85,7 @@ "source": [ "## Loading Parameters\n", "\n", - "Import the configuration parameters for the dataset, model, and optimizer from the [rans.yaml](https://atomgit.com/mindspore-lab/mindscience/blob/master/MindFlow/applications/physics_driven/navier_stokes/periodic_hill/configs/rans.yaml) file." + "Import the configuration parameters for the dataset, model, and optimizer from the [rans.yaml](https://atomgit.com/mindspore/mindscience/blob/master/MindFlow/applications/physics_driven/navier_stokes/periodic_hill/configs/rans.yaml) file." ] }, { @@ -136,7 +136,7 @@ "source": [ "## Model Initialization\n", "\n", - "Initialize the RANS-PINNs model based on the configuration in [rans.yaml](https://atomgit.com/mindspore-lab/mindscience/blob/master/MindFlow/applications/physics_driven/navier_stokes/periodic_hill/configs/rans.yaml). Use the Mean Squared Error (MSE) loss function and the Adam optimizer." + "Initialize the RANS-PINNs model based on the configuration in [rans.yaml](https://atomgit.com/mindspore/mindscience/blob/master/MindFlow/applications/physics_driven/navier_stokes/periodic_hill/configs/rans.yaml). Use the Mean Squared Error (MSE) loss function and the Adam optimizer." ] }, { diff --git a/docs/mindflow/docs/source_en/physics_driven/poisson_geometry.ipynb b/docs/mindflow/docs/source_en/physics_driven/poisson_geometry.ipynb index db640b1ae38c763b280cc20b1ffa26c444f95140..d2dacded4d5c75e94922dbe9353e334a1d3e0896 100644 --- a/docs/mindflow/docs/source_en/physics_driven/poisson_geometry.ipynb +++ b/docs/mindflow/docs/source_en/physics_driven/poisson_geometry.ipynb @@ -54,7 +54,7 @@ "cell_type": "markdown", "metadata": {}, "source": [ - "The `poisson_cfg.yaml` file can be downloaded at [applications/physics_driven/poisson/point_source/poisson_cfg.yaml](https://atomgit.com/mindspore-lab/mindscience/blob/master/MindFlow/applications/physics_driven/poisson/point_source/poisson_cfg.yaml), and the `src` package can be downloaded at [applications/physics_driven/poisson/point_source/src](https://atomgit.com/mindspore-lab/mindscience/tree/master/MindFlow/applications/physics_driven/poisson/point_source/src).\n" + "The `poisson_cfg.yaml` file can be downloaded at [applications/physics_driven/poisson/point_source/poisson_cfg.yaml](https://atomgit.com/mindspore/mindscience/blob/master/MindFlow/applications/physics_driven/poisson/point_source/poisson_cfg.yaml), and the `src` package can be downloaded at [applications/physics_driven/poisson/point_source/src](https://atomgit.com/mindspore/mindscience/tree/master/MindFlow/applications/physics_driven/poisson/point_source/src).\n" ] }, { diff --git a/docs/mindflow/docs/source_en/physics_driven/poisson_point_source.ipynb b/docs/mindflow/docs/source_en/physics_driven/poisson_point_source.ipynb index c58d27f64a61b8131c9e26929ed116ecdeee2135..6dd33a0bb270100d6c165d812b84db52271c14c7 100644 --- a/docs/mindflow/docs/source_en/physics_driven/poisson_point_source.ipynb +++ b/docs/mindflow/docs/source_en/physics_driven/poisson_point_source.ipynb @@ -81,7 +81,7 @@ "source": [ "## Creating the Dataset\n", "\n", - "In this example, random sampling is performed in the solution domain, boundaries, and point source region (a rectangular area centered on the point source position) to generate the training dataset. See [src/dataset.py](https://atomgit.com/mindspore-lab/mindscience/tree/master/MindFlow/applications/physics_driven/poisson/point_source/src) for the implementation." + "In this example, random sampling is performed in the solution domain, boundaries, and point source region (a rectangular area centered on the point source position) to generate the training dataset. See [src/dataset.py](https://atomgit.com/mindspore/mindscience/tree/master/MindFlow/applications/physics_driven/poisson/point_source/src) for the implementation." ] }, { diff --git a/docs/mindflow/docs/source_en/physics_driven/taylor_green2D.ipynb b/docs/mindflow/docs/source_en/physics_driven/taylor_green2D.ipynb index dcb9b0adface99eb6aab434ccc0fef6b989fed84..c702712924c0ba13a896266480d084396cb7ccb6 100644 --- a/docs/mindflow/docs/source_en/physics_driven/taylor_green2D.ipynb +++ b/docs/mindflow/docs/source_en/physics_driven/taylor_green2D.ipynb @@ -97,7 +97,7 @@ "cell_type": "markdown", "metadata": {}, "source": [ - "The following `src` pacakage can be downloaded in [applications/physics_driven/navier_stokes/taylor_green/src](https://atomgit.com/mindspore-lab/mindscience/tree/master/MindFlow/applications/physics_driven/navier_stokes/taylor_green/src)." + "The following `src` pacakage can be downloaded in [applications/physics_driven/navier_stokes/taylor_green/src](https://atomgit.com/mindspore/mindscience/tree/master/MindFlow/applications/physics_driven/navier_stokes/taylor_green/src)." ] }, { @@ -121,7 +121,7 @@ "cell_type": "markdown", "metadata": {}, "source": [ - "The following `taylor_green_2D.yaml` can be downloaded in [applications/physics_driven/navier_stokes/taylor_green/configs/taylor_green_2D.yaml](https://atomgit.com/mindspore-lab/mindscience/blob/master/MindFlow/applications/physics_driven/navier_stokes/taylor_green/configs/taylor_green_2D.yaml)." + "The following `taylor_green_2D.yaml` can be downloaded in [applications/physics_driven/navier_stokes/taylor_green/configs/taylor_green_2D.yaml](https://atomgit.com/mindspore/mindscience/blob/master/MindFlow/applications/physics_driven/navier_stokes/taylor_green/configs/taylor_green_2D.yaml)." ] }, { diff --git a/docs/mindflow/docs/source_zh_cn/cfd_solver/acoustic.ipynb b/docs/mindflow/docs/source_zh_cn/cfd_solver/acoustic.ipynb index 4a3a55dc76e9572ba501a026586a002236845f9a..ccf46f1b39cbf4732cfeaf11eef4a369825235b8 100644 --- a/docs/mindflow/docs/source_zh_cn/cfd_solver/acoustic.ipynb +++ b/docs/mindflow/docs/source_zh_cn/cfd_solver/acoustic.ipynb @@ -55,7 +55,7 @@ "- $\\tilde{\\Delta}$ 为归一化 Laplace 算子，即网格间距均为 1 时的 Laplace 算子\n", "- $f^*$ 为标记震源位置的 mask，即在震源作用点为 1，其余位置为 0\n", "\n", - "本案例中 `src` 包可以在 [src](https://atomgit.com/mindspore-lab/mindscience/tree/master/MindFlow/applications/cfd/acoustic/src) 下载。" + "本案例中 `src` 包可以在 [src](https://atomgit.com/mindspore/mindscience/tree/master/MindFlow/applications/cfd/acoustic/src) 下载。" ] }, { @@ -85,9 +85,9 @@ "source": [ "## 定义输入参数和输出采样方式\n", "\n", - "本案例所需的输入为有量纲 2D 速度场、震源位置列表、震源波形，在文件 [config.yaml](https://atomgit.com/mindspore-lab/mindscience/blob/master/MindFlow/applications/cfd/acoustic/config.yaml) 中指定输入文件名。为了方便用户直接验证，本案例在本[链接](https://download-mindspore.osinfra.cn/mindscience/mindflow/dataset/applications/cfd/acoustic)中提供了预置的输入数据，请下载所需要的数据集，并保存在 `./dataset` 目录下。数据集包括速度场 `velocity.npy`、震源位置列表 `srclocs.csv`、震源波形 `srcwaves.csv`。用户可仿照输入文件格式自行修改输入参数。\n", + "本案例所需的输入为有量纲 2D 速度场、震源位置列表、震源波形，在文件 [config.yaml](https://atomgit.com/mindspore/mindscience/blob/master/MindFlow/applications/cfd/acoustic/config.yaml) 中指定输入文件名。为了方便用户直接验证，本案例在本[链接](https://download-mindspore.osinfra.cn/mindscience/mindflow/dataset/applications/cfd/acoustic)中提供了预置的输入数据，请下载所需要的数据集，并保存在 `./dataset` 目录下。数据集包括速度场 `velocity.npy`、震源位置列表 `srclocs.csv`、震源波形 `srcwaves.csv`。用户可仿照输入文件格式自行修改输入参数。\n", "\n", - "输出为时空分布的波场，为了明确输出如何在时间和频率上采样，需在 [config.yaml](https://atomgit.com/mindspore-lab/mindscience/blob/master/MindFlow/applications/cfd/acoustic/config.yaml) 文件中指定 `dt`, `nt` 等参数。\n", + "输出为时空分布的波场，为了明确输出如何在时间和频率上采样，需在 [config.yaml](https://atomgit.com/mindspore/mindscience/blob/master/MindFlow/applications/cfd/acoustic/config.yaml) 文件中指定 `dt`, `nt` 等参数。\n", "\n", "由于输入的震源波形在时间上的采样率可能与输出所要求的不一致，因此需对其进行插值。" ] @@ -135,7 +135,7 @@ "source": [ "## 选取待求频点\n", "\n", - "确定了输出采样方式即确定了所有待求频点。但为了减少计算量，也可以只选择部分频点进行求解，其余频点通过插值获得。具体的频点降采样方式由 [config.yaml](https://atomgit.com/mindspore-lab/mindscience/blob/master/MindFlow/applications/cfd/acoustic/config.yaml) 文件中的 `downsample_mode`, `downsample_rate` 指定。默认为不做降采样，即求解除 $\\omega=0$ 之外的所有频点。" + "确定了输出采样方式即确定了所有待求频点。但为了减少计算量，也可以只选择部分频点进行求解，其余频点通过插值获得。具体的频点降采样方式由 [config.yaml](https://atomgit.com/mindspore/mindscience/blob/master/MindFlow/applications/cfd/acoustic/config.yaml) 文件中的 `downsample_mode`, `downsample_rate` 指定。默认为不做降采样，即求解除 $\\omega=0$ 之外的所有频点。" ] }, { diff --git a/docs/mindflow/docs/source_zh_cn/cfd_solver/couette.ipynb b/docs/mindflow/docs/source_zh_cn/cfd_solver/couette.ipynb index 55e57349214a895a3685ecee12ed3f6cc82f9d42..0d0c8723d001154a747a757a99d26621b1a73e6d 100644 --- a/docs/mindflow/docs/source_zh_cn/cfd_solver/couette.ipynb +++ b/docs/mindflow/docs/source_zh_cn/cfd_solver/couette.ipynb @@ -43,7 +43,7 @@ "u(0, t)=0, \\quad u(h, t)=U, \\quad t>0\n", "$$\n", "\n", - "本案例中`src`包可以在[src](https://atomgit.com/mindspore-lab/mindscience/tree/master/MindFlow/applications/cfd/couette/src)下载。\n" + "本案例中`src`包可以在[src](https://atomgit.com/mindspore/mindscience/tree/master/MindFlow/applications/cfd/couette/src)下载。\n" ] }, { @@ -74,7 +74,7 @@ "source": [ "## 定义Simulator和RunTime\n", "\n", - "网格、材料、仿真时间、边界条件和数值方法的设置在文件[couette.yaml](https://atomgit.com/mindspore-lab/mindscience/blob/master/MindFlow/applications/cfd/couette/couette.yaml)中。" + "网格、材料、仿真时间、边界条件和数值方法的设置在文件[couette.yaml](https://atomgit.com/mindspore/mindscience/blob/master/MindFlow/applications/cfd/couette/couette.yaml)中。" ] }, { diff --git a/docs/mindflow/docs/source_zh_cn/cfd_solver/lax_tube.ipynb b/docs/mindflow/docs/source_zh_cn/cfd_solver/lax_tube.ipynb index d318259ad6f2b00af6c280758f34aa7b3086b8c8..7bfd68fef0374b96993812e7197ed5c0b25493f6 100644 --- a/docs/mindflow/docs/source_zh_cn/cfd_solver/lax_tube.ipynb +++ b/docs/mindflow/docs/source_zh_cn/cfd_solver/lax_tube.ipynb @@ -39,7 +39,7 @@ "\n", "在激波管两端，施加第二类边界条件。\n", "\n", - "本案例中`src`包可以在[src](https://atomgit.com/mindspore-lab/mindscience/tree/master/MindFlow/applications/cfd/lax/src)下载。\n" + "本案例中`src`包可以在[src](https://atomgit.com/mindspore/mindscience/tree/master/MindFlow/applications/cfd/lax/src)下载。\n" ] }, { @@ -66,7 +66,7 @@ "source": [ "## 定义Simulator和RunTime\n", "\n", - "网格、材料、仿真时间、边界条件和数值方法的设置在文件[numeric.yaml](https://atomgit.com/mindspore-lab/mindscience/blob/master/MindFlow/applications/cfd/lax/numeric.yaml)中。" + "网格、材料、仿真时间、边界条件和数值方法的设置在文件[numeric.yaml](https://atomgit.com/mindspore/mindscience/blob/master/MindFlow/applications/cfd/lax/numeric.yaml)中。" ] }, { diff --git a/docs/mindflow/docs/source_zh_cn/cfd_solver/riemann2d.ipynb b/docs/mindflow/docs/source_zh_cn/cfd_solver/riemann2d.ipynb index 30dce83a0ea861155175f69f412a83c0aefb52db..163feceac935c725852700f8f0e2a3591703c070 100644 --- a/docs/mindflow/docs/source_zh_cn/cfd_solver/riemann2d.ipynb +++ b/docs/mindflow/docs/source_zh_cn/cfd_solver/riemann2d.ipynb @@ -44,7 +44,7 @@ "\\left(\\begin{matrix} \\rho \\\\ u \\\\ v \\\\ p \\\\\\end{matrix}\\right)_{x>0.5, y<0.5} = \\left(\\begin{matrix} 0.5323 \\\\ 0.0 \\\\ 1.206 \\\\ 0.3 \\\\\\end{matrix}\\right)\n", "$$\n", "\n", - "本案例中`src`包可以在[src](https://atomgit.com/mindspore-lab/mindscience/tree/master/MindFlow/applications/cfd/riemann2d/src)下载。" + "本案例中`src`包可以在[src](https://atomgit.com/mindspore/mindscience/tree/master/MindFlow/applications/cfd/riemann2d/src)下载。" ] }, { @@ -71,7 +71,7 @@ "source": [ "## 定义Simulator和RunTime\n", "\n", - "网格、材料、仿真时间、边界条件和数值方法的设置在文件[numeric.yaml](https://atomgit.com/mindspore-lab/mindscience/blob/master/MindFlow/applications/cfd/riemann2d/numeric.yaml)中。" + "网格、材料、仿真时间、边界条件和数值方法的设置在文件[numeric.yaml](https://atomgit.com/mindspore/mindscience/blob/master/MindFlow/applications/cfd/riemann2d/numeric.yaml)中。" ] }, { diff --git a/docs/mindflow/docs/source_zh_cn/cfd_solver/sod_tube.ipynb b/docs/mindflow/docs/source_zh_cn/cfd_solver/sod_tube.ipynb index 36bdcb787f9941449347ec2a602198fca8d17545..fc2f3b4a0eaec973be3509e1f69c2bfe0a759756 100644 --- a/docs/mindflow/docs/source_zh_cn/cfd_solver/sod_tube.ipynb +++ b/docs/mindflow/docs/source_zh_cn/cfd_solver/sod_tube.ipynb @@ -39,7 +39,7 @@ "\n", "在激波管两端，施加第二类边界条件。\n", "\n", - "本案例中`src`包可以在[src](https://atomgit.com/mindspore-lab/mindscience/tree/master/MindFlow/applications/cfd/sod/src)下载。" + "本案例中`src`包可以在[src](https://atomgit.com/mindspore/mindscience/tree/master/MindFlow/applications/cfd/sod/src)下载。" ] }, { @@ -66,7 +66,7 @@ "source": [ "## 定义Simulator和RunTime\n", "\n", - "网格、材料、仿真时间、边界条件和数值方法的设置在文件[numeric.yaml](https://atomgit.com/mindspore-lab/mindscience/blob/master/MindFlow/applications/cfd/sod/numeric.yaml)中。" + "网格、材料、仿真时间、边界条件和数值方法的设置在文件[numeric.yaml](https://atomgit.com/mindspore/mindscience/blob/master/MindFlow/applications/cfd/sod/numeric.yaml)中。" ] }, { diff --git a/docs/mindflow/docs/source_zh_cn/data_driven/2D_steady.ipynb b/docs/mindflow/docs/source_zh_cn/data_driven/2D_steady.ipynb index ae9f4336c25ab9ddd85073cfdb0aa158e7275095..63f2e8ac5f82a77ff2c903938253c61984461918 100644 --- a/docs/mindflow/docs/source_zh_cn/data_driven/2D_steady.ipynb +++ b/docs/mindflow/docs/source_zh_cn/data_driven/2D_steady.ipynb @@ -136,7 +136,7 @@ "cell_type": "markdown", "metadata": {}, "source": [ - "以下src文件可以在[applications/data_driven/airfoil/2D_steady/src](https://atomgit.com/mindspore-lab/mindscience/tree/master/MindFlow/applications/data_driven/airfoil/2D_steady/src)中下载。" + "以下src文件可以在[applications/data_driven/airfoil/2D_steady/src](https://atomgit.com/mindspore/mindscience/tree/master/MindFlow/applications/data_driven/airfoil/2D_steady/src)中下载。" ] }, { @@ -174,7 +174,7 @@ "source": [ "## 配置网络与训练参数\n", "\n", - "从配置文件中读取四类参数，分别为模型相关参数（model）、数据相关参数（data）、优化器相关参数（optimizer）、输出相关参数（ckpt）、验证相关参数（eval）。您可以从[config](https://atomgit.com/mindspore-lab/mindscience/blob/master/MindFlow/applications/data_driven/airfoil/2D_steady/configs/vit.yaml)获取这些参数。" + "从配置文件中读取四类参数，分别为模型相关参数（model）、数据相关参数（data）、优化器相关参数（optimizer）、输出相关参数（ckpt）、验证相关参数（eval）。您可以从[config](https://atomgit.com/mindspore/mindscience/blob/master/MindFlow/applications/data_driven/airfoil/2D_steady/configs/vit.yaml)获取这些参数。" ] }, { @@ -238,7 +238,7 @@ "source": [ "该文件包含2808个流场数据，为51个超临界翼型在Ma=0.73和不同攻角范围内（-2.0~4.6）的流场数据。其中，input的数据维度为（13, 192, 384），192和384为经过雅格比转换后的网格分辨率，13为不同的特征维度，分别为($AOA$, $x$, $y$, $x_{i,0}$, $y_{i,0}$, $\\xi_x$, $\\xi_y$, $\\eta_x$, $\\eta_y$, $x_\\xi$, $x_\\eta$, $y_\\xi$, $y_\\eta$)。\n", "\n", - "Label的数据维度为（288，768），可以经过[utils.py](https://atomgit.com/mindspore-lab/mindscience/blob/master/MindFlow/applications/data_driven/airfoil/2D_steady/src/utils.py)中的patchify 函数(16×16)操作后所得的流场数据（u,v,p），可以通过[utils.py](https://atomgit.com/mindspore-lab/mindscience/blob/master/MindFlow/applications/data_driven/airfoil/2D_steady/src/utils.py)中的unpatchify操作还原成（3, 192, 384），用户可根据自身网络输入输出设计进行个性化配置和选择。\n", + "Label的数据维度为（288，768），可以经过[utils.py](https://atomgit.com/mindspore/mindscience/blob/master/MindFlow/applications/data_driven/airfoil/2D_steady/src/utils.py)中的patchify 函数(16×16)操作后所得的流场数据（u,v,p），可以通过[utils.py](https://atomgit.com/mindspore/mindscience/blob/master/MindFlow/applications/data_driven/airfoil/2D_steady/src/utils.py)中的unpatchify操作还原成（3, 192, 384），用户可根据自身网络输入输出设计进行个性化配置和选择。\n", "\n", "首先将CFD的数据集转换成张量数据，然后将张量数据转换成MindRecord。设计AI数据高效转换工具，实现翼型流场复杂边界和非标数据的特征提取，转换前后的x，y和u的信息如下图所示。\n", "\n", @@ -539,7 +539,7 @@ "source": [ "## 模型推理\n", "\n", - "模型训练结束后即可通过调用[train.py](https://atomgit.com/mindspore-lab/mindscience/blob/master/MindFlow/applications/data_driven/airfoil/2D_steady/train.py)中的train函数，train_mode设置为eval可进行推理，设置为finetune可进行迁移学习。\n", + "模型训练结束后即可通过调用[train.py](https://atomgit.com/mindspore/mindscience/blob/master/MindFlow/applications/data_driven/airfoil/2D_steady/train.py)中的train函数，train_mode设置为eval可进行推理，设置为finetune可进行迁移学习。\n", "\n", "在设计新翼型时，需要考虑各种不同的初始边界条件（如不同的攻角或马赫数等），以进行气动性能的评估。为了提高模型的可推广性，从而提高其在工程场景中的效用，我们可以采用迁移学习的方式。具体做法为：先在大规模数据集预训练模型，最终在小数据集上进行快速的微调，从而实现模型对新工况的推理泛化。考虑到精度和时间消耗之间的权衡，我们一共考虑了四种不同大小的数据集去获取不同的预训练模型。与在较小数据集上进行预训练所需耗时较少，但预测精度较低；而在较大数据集上预训练，能够产生更准确的结果，但需要更多的预训练时间。\n", "\n", diff --git a/docs/mindflow/docs/source_zh_cn/data_driven/burgers_FNO1D.ipynb b/docs/mindflow/docs/source_zh_cn/data_driven/burgers_FNO1D.ipynb index 71a291bd8082a058f7b72572e6c5d655b7247dde..b9353cc6c415ff7ad101699561fb01261946ff78 100644 --- a/docs/mindflow/docs/source_zh_cn/data_driven/burgers_FNO1D.ipynb +++ b/docs/mindflow/docs/source_zh_cn/data_driven/burgers_FNO1D.ipynb @@ -130,7 +130,7 @@ "cell_type": "markdown", "metadata": {}, "source": [ - "下述`src`包可以在[applications/data_driven/burgers/fno1d/src](https://atomgit.com/mindspore-lab/mindscience/tree/master/MindFlow/applications/data_driven/burgers/fno1d/src)下载。" + "下述`src`包可以在[applications/data_driven/burgers/fno1d/src](https://atomgit.com/mindspore/mindscience/tree/master/MindFlow/applications/data_driven/burgers/fno1d/src)下载。" ] }, { @@ -157,7 +157,7 @@ "cell_type": "markdown", "metadata": {}, "source": [ - "从[config](https://atomgit.com/mindspore-lab/mindscience/blob/master/MindFlow/applications/data_driven/burgers/fno1d/configs/fno1d.yaml)中获得模型、数据、优化器的参数。" + "从[config](https://atomgit.com/mindspore/mindscience/blob/master/MindFlow/applications/data_driven/burgers/fno1d/configs/fno1d.yaml)中获得模型、数据、优化器的参数。" ] }, { @@ -248,7 +248,7 @@ "\n", "- Decoding layer对应代码中`FNO1D.fc1`与`FNO1D.fc2`，获得最终的预测值。\n", "\n", - "基于上述网络结构，进行模型初始化，其中模型参数可在[配置文件](https://atomgit.com/mindspore-lab/mindscience/blob/master/MindFlow/applications/data_driven/burgers/fno1d/configs/fno1d.yaml)中修改。" + "基于上述网络结构，进行模型初始化，其中模型参数可在[配置文件](https://atomgit.com/mindspore/mindscience/blob/master/MindFlow/applications/data_driven/burgers/fno1d/configs/fno1d.yaml)中修改。" ] }, { diff --git a/docs/mindflow/docs/source_zh_cn/data_driven/burgers_KNO1D.ipynb b/docs/mindflow/docs/source_zh_cn/data_driven/burgers_KNO1D.ipynb index 94e861616a76ad368c2347fefa3dcee1e73f7383..9938eec6cad4b0fb28837b08ff1d1ad84376a1de 100644 --- a/docs/mindflow/docs/source_zh_cn/data_driven/burgers_KNO1D.ipynb +++ b/docs/mindflow/docs/source_zh_cn/data_driven/burgers_KNO1D.ipynb @@ -145,7 +145,7 @@ } }, "source": [ - "下述`src`包可以在[applications/data_driven/burgers/kno1d/src](https://atomgit.com/mindspore-lab/mindscience/tree/master/MindFlow/applications/data_driven/burgers/kno1d/src)下载。" + "下述`src`包可以在[applications/data_driven/burgers/kno1d/src](https://atomgit.com/mindspore/mindscience/tree/master/MindFlow/applications/data_driven/burgers/kno1d/src)下载。" ] }, { @@ -189,7 +189,7 @@ } }, "source": [ - "从[config](https://atomgit.com/mindspore-lab/mindscience/blob/master/MindFlow/applications/data_driven/burgers/kno1d/configs/kno1d.yaml)中获得模型、数据、优化器的超参。" + "从[config](https://atomgit.com/mindspore/mindscience/blob/master/MindFlow/applications/data_driven/burgers/kno1d/configs/kno1d.yaml)中获得模型、数据、优化器的超参。" ] }, { diff --git a/docs/mindflow/docs/source_zh_cn/data_driven/burgers_SNO1D.ipynb b/docs/mindflow/docs/source_zh_cn/data_driven/burgers_SNO1D.ipynb index 5eff8ed6a65af6e0afeca741f1470086437b34e7..54cbf7240de469d22f2ab64b1dc9c4eda323fc33 100644 --- a/docs/mindflow/docs/source_zh_cn/data_driven/burgers_SNO1D.ipynb +++ b/docs/mindflow/docs/source_zh_cn/data_driven/burgers_SNO1D.ipynb @@ -125,7 +125,7 @@ "cell_type": "markdown", "metadata": {}, "source": [ - "下述`src`包可以在[applications/data_driven/burgers/sno1d/src](https://atomgit.com/mindspore-lab/mindscience/tree/master/MindFlow/applications/data_driven/burgers/sno1d/src)下载。" + "下述`src`包可以在[applications/data_driven/burgers/sno1d/src](https://atomgit.com/mindspore/mindscience/tree/master/MindFlow/applications/data_driven/burgers/sno1d/src)下载。" ] }, { @@ -152,7 +152,7 @@ "cell_type": "markdown", "metadata": {}, "source": [ - "从[config](https://atomgit.com/mindspore-lab/mindscience/blob/master/MindFlow/applications/data_driven/burgers/sno1d/configs/sno1d.yaml)中获得模型、数据、优化器的超参。" + "从[config](https://atomgit.com/mindspore/mindscience/blob/master/MindFlow/applications/data_driven/burgers/sno1d/configs/sno1d.yaml)中获得模型、数据、优化器的超参。" ] }, { @@ -232,7 +232,7 @@ "\n", "- 解码层对应`SNO1D.decoder`，由两个卷积组成。解码器用于获得最终预测。\n", "\n", - "基于上述网络结构，进行模型初始化，其中模型参数可在[配置文件](https://atomgit.com/mindspore-lab/mindscience/blob/master/MindFlow/applications/data_driven/burgers/sno1d/configs/sno1d.yaml)中修改。" + "基于上述网络结构，进行模型初始化，其中模型参数可在[配置文件](https://atomgit.com/mindspore/mindscience/blob/master/MindFlow/applications/data_driven/burgers/sno1d/configs/sno1d.yaml)中修改。" ] }, { diff --git a/docs/mindflow/docs/source_zh_cn/data_driven/flow_around_sphere.ipynb b/docs/mindflow/docs/source_zh_cn/data_driven/flow_around_sphere.ipynb index 58ba4dfec8bbb36bc1daad9eb44e845007163cd8..8bcf1bf0ca49a72aa25429d4cd92bdd30ada9c5d 100644 --- a/docs/mindflow/docs/source_zh_cn/data_driven/flow_around_sphere.ipynb +++ b/docs/mindflow/docs/source_zh_cn/data_driven/flow_around_sphere.ipynb @@ -747,7 +747,7 @@ } }, "source": [ - "模型训练结束后，运行[eval.py](https://atomgit.com/mindspore-lab/mindscience/blob/master/MindFlow/applications/data_driven/flow_around_sphere/eval.py)，通过控制台控制需要读取的模型路径，在给定任意时刻的初始流场的条件下，快速、准确的推理未来长时间的三维流场。" + "模型训练结束后，运行[eval.py](https://atomgit.com/mindspore/mindscience/blob/master/MindFlow/applications/data_driven/flow_around_sphere/eval.py)，通过控制台控制需要读取的模型路径，在给定任意时刻的初始流场的条件下，快速、准确的推理未来长时间的三维流场。" ] }, { diff --git a/docs/mindflow/docs/source_zh_cn/data_driven/navier_stokes_FNO2D.ipynb b/docs/mindflow/docs/source_zh_cn/data_driven/navier_stokes_FNO2D.ipynb index 312086886e9631bd736c6ec4be04be925a18053c..e498d861bf149cf3b7b7bfb815f0de00b0ad2b1d 100644 --- a/docs/mindflow/docs/source_zh_cn/data_driven/navier_stokes_FNO2D.ipynb +++ b/docs/mindflow/docs/source_zh_cn/data_driven/navier_stokes_FNO2D.ipynb @@ -130,8 +130,8 @@ "cell_type": "markdown", "metadata": {}, "source": [ - "下述`src`包可以在[applications/data_driven/navier_stokes/fno2d/src](https://atomgit.com/mindspore-lab/mindscience/tree/master/MindFlow/applications/data_driven/navier_stokes/fno2d/src)下载。\n", - "配置文件可在[config](https://atomgit.com/mindspore-lab/mindscience/blob/master/MindFlow/applications/data_driven/navier_stokes/fno2d/configs/fno2d.yaml)中修改。" + "下述`src`包可以在[applications/data_driven/navier_stokes/fno2d/src](https://atomgit.com/mindspore/mindscience/tree/master/MindFlow/applications/data_driven/navier_stokes/fno2d/src)下载。\n", + "配置文件可在[config](https://atomgit.com/mindspore/mindscience/blob/master/MindFlow/applications/data_driven/navier_stokes/fno2d/configs/fno2d.yaml)中修改。" ] }, { diff --git a/docs/mindflow/docs/source_zh_cn/data_driven/navier_stokes_FNO3D.ipynb b/docs/mindflow/docs/source_zh_cn/data_driven/navier_stokes_FNO3D.ipynb index 326a98285714412df810b0e7b6efbdc50a4eca68..8dbe0f8bcaf6f6229688b4e826d6c767c28b300e 100644 --- a/docs/mindflow/docs/source_zh_cn/data_driven/navier_stokes_FNO3D.ipynb +++ b/docs/mindflow/docs/source_zh_cn/data_driven/navier_stokes_FNO3D.ipynb @@ -124,7 +124,7 @@ "cell_type": "markdown", "metadata": {}, "source": [ - "下述`src`包可以在[applications/data_driven/navier_stokes/fno3d/src](https://atomgit.com/mindspore-lab/mindscience/tree/master/MindFlow/applications/data_driven/navier_stokes/fno3d/src)下载。\n" + "下述`src`包可以在[applications/data_driven/navier_stokes/fno3d/src](https://atomgit.com/mindspore/mindscience/tree/master/MindFlow/applications/data_driven/navier_stokes/fno3d/src)下载。\n" ] }, { diff --git a/docs/mindflow/docs/source_zh_cn/data_driven/navier_stokes_KNO2D.ipynb b/docs/mindflow/docs/source_zh_cn/data_driven/navier_stokes_KNO2D.ipynb index 25c7b5a0135a64e49ba29da68403271757a899a7..197bbef225a755a169b42ade48cdc3ed647b3859 100644 --- a/docs/mindflow/docs/source_zh_cn/data_driven/navier_stokes_KNO2D.ipynb +++ b/docs/mindflow/docs/source_zh_cn/data_driven/navier_stokes_KNO2D.ipynb @@ -149,7 +149,7 @@ } }, "source": [ - "下述`src`包可以在[applications/data_driven/navier_stokes/kno2d/src](https://atomgit.com/mindspore-lab/mindscience/tree/master/MindFlow/applications/data_driven/navier_stokes/kno2d/src)下载。" + "下述`src`包可以在[applications/data_driven/navier_stokes/kno2d/src](https://atomgit.com/mindspore/mindscience/tree/master/MindFlow/applications/data_driven/navier_stokes/kno2d/src)下载。" ] }, { @@ -194,7 +194,7 @@ } }, "source": [ - "从[config](https://atomgit.com/mindspore-lab/mindscience/blob/master/MindFlow/applications/data_driven/navier_stokes/kno2d/configs/kno2d.yaml)中获得模型、数据、优化器的超参。" + "从[config](https://atomgit.com/mindspore/mindscience/blob/master/MindFlow/applications/data_driven/navier_stokes/kno2d/configs/kno2d.yaml)中获得模型、数据、优化器的超参。" ] }, { diff --git a/docs/mindflow/docs/source_zh_cn/data_driven/navier_stokes_SNO2D.ipynb b/docs/mindflow/docs/source_zh_cn/data_driven/navier_stokes_SNO2D.ipynb index 003baba46deef376fe3151859dc5b046508ac100..3c13574b02a1aab2b2ea56d72cd38849998d7658 100644 --- a/docs/mindflow/docs/source_zh_cn/data_driven/navier_stokes_SNO2D.ipynb +++ b/docs/mindflow/docs/source_zh_cn/data_driven/navier_stokes_SNO2D.ipynb @@ -129,7 +129,7 @@ "cell_type": "markdown", "metadata": {}, "source": [ - "下述`src`包可以在[applications/data_driven/navier_stokes/sno2d/src](https://atomgit.com/mindspore-lab/mindscience/tree/master/MindFlow/applications/data_driven/navier_stokes/sno2d/src)下载。" + "下述`src`包可以在[applications/data_driven/navier_stokes/sno2d/src](https://atomgit.com/mindspore/mindscience/tree/master/MindFlow/applications/data_driven/navier_stokes/sno2d/src)下载。" ] }, { diff --git a/docs/mindflow/docs/source_zh_cn/data_driven/navier_stokes_SNO3D.ipynb b/docs/mindflow/docs/source_zh_cn/data_driven/navier_stokes_SNO3D.ipynb index 35cdddc9cc96b0287658144787e256c9222aaf3f..65c9eae707063674df3652d7d958b2e64dbbcab6 100644 --- a/docs/mindflow/docs/source_zh_cn/data_driven/navier_stokes_SNO3D.ipynb +++ b/docs/mindflow/docs/source_zh_cn/data_driven/navier_stokes_SNO3D.ipynb @@ -123,7 +123,7 @@ "cell_type": "markdown", "metadata": {}, "source": [ - "下述`src`包可以在[applications/data_driven/navier_stokes/sno3d/src](https://atomgit.com/mindspore-lab/mindscience/tree/master/MindFlow/applications/data_driven/navier_stokes/sno3d/src)下载。" + "下述`src`包可以在[applications/data_driven/navier_stokes/sno3d/src](https://atomgit.com/mindspore/mindscience/tree/master/MindFlow/applications/data_driven/navier_stokes/sno3d/src)下载。" ] }, { diff --git a/docs/mindflow/docs/source_zh_cn/data_mechanism_fusion/pde_net.ipynb b/docs/mindflow/docs/source_zh_cn/data_mechanism_fusion/pde_net.ipynb index 4bcdc81831d0695d5f1848101c846c3057495042..f7f6318cea5dc5fe3d3ac5a8e70688fa7a300e58 100644 --- a/docs/mindflow/docs/source_zh_cn/data_mechanism_fusion/pde_net.ipynb +++ b/docs/mindflow/docs/source_zh_cn/data_mechanism_fusion/pde_net.ipynb @@ -126,7 +126,7 @@ "cell_type": "markdown", "metadata": {}, "source": [ - "下述`src`可以在[applications/data_mechanism_fusion/pde_net/src](https://atomgit.com/mindspore-lab/mindscience/tree/master/MindFlow/applications/data_mechanism_fusion/pde_net/src)下载。" + "下述`src`可以在[applications/data_mechanism_fusion/pde_net/src](https://atomgit.com/mindspore/mindscience/tree/master/MindFlow/applications/data_mechanism_fusion/pde_net/src)下载。" ] }, { @@ -149,7 +149,7 @@ "cell_type": "markdown", "metadata": {}, "source": [ - "所有配置参数可以在[configuration file](https://atomgit.com/mindspore-lab/mindscience/blob/master/MindFlow/applications/data_mechanism_fusion/pde_net/configs/pde_net.yaml)修改。" + "所有配置参数可以在[configuration file](https://atomgit.com/mindspore/mindscience/blob/master/MindFlow/applications/data_mechanism_fusion/pde_net/configs/pde_net.yaml)修改。" ] }, { diff --git a/docs/mindflow/docs/source_zh_cn/data_mechanism_fusion/phympgn.ipynb b/docs/mindflow/docs/source_zh_cn/data_mechanism_fusion/phympgn.ipynb index 6146a3443486911aacaa708c4d8e92e22477d043..6cc01ddf57a171507a56dcec92617d6dfc5f58f7 100644 --- a/docs/mindflow/docs/source_zh_cn/data_mechanism_fusion/phympgn.ipynb +++ b/docs/mindflow/docs/source_zh_cn/data_mechanism_fusion/phympgn.ipynb @@ -117,7 +117,7 @@ "source": [ "- 确保已安装相关依赖库，如MindSpore等\n", "- 确保已下载好[圆柱绕流数据](https://download-mindspore.osinfra.cn/mindscience/mindflow/dataset/applications/data_mechanism_fusion/PhyMPGN/)\n", - "- 确保在[yamls/train.yaml](https://atomgit.com/mindspore-lab/mindscience/blob/master/MindFlow/applications/data_mechanism_fusion/phympgn/yamls/train.yaml)配置文件中已配置好数据和模型权重等相关保存路径" + "- 确保在[yamls/train.yaml](https://atomgit.com/mindspore/mindscience/blob/master/MindFlow/applications/data_mechanism_fusion/phympgn/yamls/train.yaml)配置文件中已配置好数据和模型权重等相关保存路径" ] }, { diff --git a/docs/mindflow/docs/source_zh_cn/features/solve_pinns_by_mindflow.ipynb b/docs/mindflow/docs/source_zh_cn/features/solve_pinns_by_mindflow.ipynb index d64db5511592cc01d3111ede8bf5bc324fe6967b..fda76c3bc17e05ea17ba57773e9b8acd98fb9d14 100644 --- a/docs/mindflow/docs/source_zh_cn/features/solve_pinns_by_mindflow.ipynb +++ b/docs/mindflow/docs/source_zh_cn/features/solve_pinns_by_mindflow.ipynb @@ -120,7 +120,7 @@ "source": [ "## 创建数据集\n", "\n", - "本案例根据求解域、边值条件进行随机采样，使用[Disk](https://mindspore.cn/mindflow/docs/zh-CN/master/geometry/mindflow.geometry.Disk.html#mindflow.geometry.Disk)和[CSGXOR](https://mindspore.cn/mindflow/docs/zh-CN/master/geometry/mindflow.geometry.CSGXOR.html#mindflow.geometry.CSGXOR)几何模块构建输入输出边界和作用域，生成训练数据集与测试数据集。`Disk`和`CSGXOR`由`MindSpore Flow`的[geometry](https://mindspore.cn/mindflow/docs/zh-CN/master/mindflow.geometry.html#)模块导入。下载数据生成的[Python文件](https://atomgit.com/mindspore-lab/mindscience/blob/master/MindFlow/features/solve_pinns_by_mindflow/src/dataset.py)。" + "本案例根据求解域、边值条件进行随机采样，使用[Disk](https://mindspore.cn/mindflow/docs/zh-CN/master/geometry/mindflow.geometry.Disk.html#mindflow.geometry.Disk)和[CSGXOR](https://mindspore.cn/mindflow/docs/zh-CN/master/geometry/mindflow.geometry.CSGXOR.html#mindflow.geometry.CSGXOR)几何模块构建输入输出边界和作用域，生成训练数据集与测试数据集。`Disk`和`CSGXOR`由`MindSpore Flow`的[geometry](https://mindspore.cn/mindflow/docs/zh-CN/master/mindflow.geometry.html#)模块导入。下载数据生成的[Python文件](https://atomgit.com/mindspore/mindscience/blob/master/MindFlow/features/solve_pinns_by_mindflow/src/dataset.py)。" ] }, { @@ -418,7 +418,7 @@ "cell_type": "markdown", "metadata": {}, "source": [ - "基于[Poisson](https://mindspore.cn/mindflow/docs/zh-CN/master/pde/mindflow.pde.Poisson.html#mindflow.pde.Poisson)基类结合上面定义的控制方程和边界条件，定义下述`Poisson2D`问题。`Poisson`基类由`MindSpore Flow`的[pde](https://mindspore.cn/mindflow/docs/zh-CN/master/mindflow.pde.html)模块导入。下载`Poisson2D`问题的[Python文件](https://atomgit.com/mindspore-lab/mindscience/blob/master/MindFlow/features/solve_pinns_by_mindflow/src/model.py)。" + "基于[Poisson](https://mindspore.cn/mindflow/docs/zh-CN/master/pde/mindflow.pde.Poisson.html#mindflow.pde.Poisson)基类结合上面定义的控制方程和边界条件，定义下述`Poisson2D`问题。`Poisson`基类由`MindSpore Flow`的[pde](https://mindspore.cn/mindflow/docs/zh-CN/master/mindflow.pde.html)模块导入。下载`Poisson2D`问题的[Python文件](https://atomgit.com/mindspore/mindscience/blob/master/MindFlow/features/solve_pinns_by_mindflow/src/model.py)。" ] }, { @@ -480,7 +480,7 @@ "source": [ "## 模型训练\n", "\n", - "使用**MindSpore >= 2.0.0**的版本，采用函数式编程的方式训练网络。下载训练的[Python文件](https://atomgit.com/mindspore-lab/mindscience/blob/master/MindFlow/features/solve_pinns_by_mindflow/train.py)。" + "使用**MindSpore >= 2.0.0**的版本，采用函数式编程的方式训练网络。下载训练的[Python文件](https://atomgit.com/mindspore/mindscience/blob/master/MindFlow/features/solve_pinns_by_mindflow/train.py)。" ] }, { @@ -510,7 +510,7 @@ "cell_type": "markdown", "metadata": {}, "source": [ - "下载训练过程计算损失的[Python文件](https://atomgit.com/mindspore-lab/mindscience/blob/master/MindFlow/features/solve_pinns_by_mindflow/src/utils.py)。" + "下载训练过程计算损失的[Python文件](https://atomgit.com/mindspore/mindscience/blob/master/MindFlow/features/solve_pinns_by_mindflow/src/utils.py)。" ] }, { @@ -801,7 +801,7 @@ "source": [ "## 模型推理及可视化\n", "\n", - "训练后可对流场内所有数据点进行推理，并可视化相关结果。下载可视化结果的[Python文件](https://atomgit.com/mindspore-lab/mindscience/blob/master/MindFlow/features/solve_pinns_by_mindflow/src/utils.py)。" + "训练后可对流场内所有数据点进行推理，并可视化相关结果。下载可视化结果的[Python文件](https://atomgit.com/mindspore/mindscience/blob/master/MindFlow/features/solve_pinns_by_mindflow/src/utils.py)。" ] }, { diff --git a/docs/mindflow/docs/source_zh_cn/index.rst b/docs/mindflow/docs/source_zh_cn/index.rst index d0a0ac954bb39a500835bb7d82993283641d38de..fa820fc452d40a8ad85e1bfcec5bfc8881d441c8 100644 --- a/docs/mindflow/docs/source_zh_cn/index.rst +++ b/docs/mindflow/docs/source_zh_cn/index.rst @@ -3,13 +3,13 @@ MindSpore Flow介绍 流体仿真是指通过数值计算对给定边界条件下的流体控制方程进行求解，从而实现流动的分析、预测和控制，其在航空航天、船舶制造以及能源电力等行业领域的工程设计中应用广泛。传统流体仿真的数值方法如有限体积、有限差分等，主要依赖商业软件实现，需要进行物理建模、网格划分、数值离散、迭代求解等步骤，仿真过程较为复杂，计算周期长。AI具备强大的学习拟合和天然的并行推理能力，可以有效地提升流体仿真效率。 -`MindSpore Flow `_ 是基于昇思MindSpore开发的流体仿真领域套件，支持航空航天、船舶制造以及能源电力等行业领域的AI流场模拟，旨在于为广大的工业界科研工程人员、高校老师及学生提供高效易用的AI计算流体仿真软件。 +`MindSpore Flow `_ 是基于昇思MindSpore开发的流体仿真领域套件，支持航空航天、船舶制造以及能源电力等行业领域的AI流场模拟，旨在于为广大的工业界科研工程人员、高校老师及学生提供高效易用的AI计算流体仿真软件。 .. raw:: html -代码仓地址: +代码仓地址: .. toctree:: :glob: diff --git a/docs/mindflow/docs/source_zh_cn/mindflow_install.md b/docs/mindflow/docs/source_zh_cn/mindflow_install.md index 7ad8764be274083b1db10834d31b4eaa445a04ff..cd741e869a1cf9311006975f92056d4eeb523cb1 100644 --- a/docs/mindflow/docs/source_zh_cn/mindflow_install.md +++ b/docs/mindflow/docs/source_zh_cn/mindflow_install.md @@ -6,7 +6,7 @@ - 硬件平台为Ascend、GPU。 - 参考[MindSpore安装指南](https://www.mindspore.cn/install)，完成MindSpore的安装。 -- 其余依赖请参见[requirements.txt](https://atomgit.com/mindspore-lab/mindscience/blob/master/MindFlow/requirements.txt)。 +- 其余依赖请参见[requirements.txt](https://atomgit.com/mindspore/mindscience/blob/master/MindFlow/requirements.txt)。 - MindSpore Flow需MindSpore版本>=2.5.0，Python版本需>=3.9。 ## 安装方式 diff --git a/docs/mindflow/docs/source_zh_cn/physics_driven/burgers1D.ipynb b/docs/mindflow/docs/source_zh_cn/physics_driven/burgers1D.ipynb index d8272bf5bd7bcde07f8992b8b1061d900bde69ce..013b3386416113a9c9ed5f11faf6b29e5932fae2 100644 --- a/docs/mindflow/docs/source_zh_cn/physics_driven/burgers1D.ipynb +++ b/docs/mindflow/docs/source_zh_cn/physics_driven/burgers1D.ipynb @@ -91,7 +91,7 @@ "cell_type": "markdown", "metadata": {}, "source": [ - "下述`src`包可以在[applications/physics_driven/burgers/src](https://atomgit.com/mindspore-lab/mindscience/tree/master/MindFlow/applications/physics_driven/burgers/src)下载。" + "下述`src`包可以在[applications/physics_driven/burgers/src](https://atomgit.com/mindspore/mindscience/tree/master/MindFlow/applications/physics_driven/burgers/src)下载。" ] }, { diff --git a/docs/mindflow/docs/source_zh_cn/physics_driven/darcy2D.ipynb b/docs/mindflow/docs/source_zh_cn/physics_driven/darcy2D.ipynb index 3c82afdc8ce8fc5ce47815d18abcb48bc087bbff..c76c1ecbcaf29f5ce3eb29852ed3338ff3bad82c 100644 --- a/docs/mindflow/docs/source_zh_cn/physics_driven/darcy2D.ipynb +++ b/docs/mindflow/docs/source_zh_cn/physics_driven/darcy2D.ipynb @@ -80,7 +80,7 @@ "cell_type": "markdown", "metadata": {}, "source": [ - "下述`src`包可以在[applications/physics_driven/darcy/src](https://atomgit.com/mindspore-lab/mindscience/tree/master/MindFlow/applications/physics_driven/darcy/src)下载。" + "下述`src`包可以在[applications/physics_driven/darcy/src](https://atomgit.com/mindspore/mindscience/tree/master/MindFlow/applications/physics_driven/darcy/src)下载。" ] }, { diff --git a/docs/mindflow/docs/source_zh_cn/physics_driven/kovasznay.ipynb b/docs/mindflow/docs/source_zh_cn/physics_driven/kovasznay.ipynb index ff4bd4077b7b120799dc312d7d15f83884d25e3b..681e2a119f35614282d2ae090d8a2d420811f9f4 100644 --- a/docs/mindflow/docs/source_zh_cn/physics_driven/kovasznay.ipynb +++ b/docs/mindflow/docs/source_zh_cn/physics_driven/kovasznay.ipynb @@ -77,7 +77,7 @@ "source": [ "## 创建数据集\n", "\n", - "本案例在求解域及边值条件进行随机采样，生成训练数据集与测试数据集。具体方法见[src/dataset.py](https://atomgit.com/mindspore-lab/mindscience/blob/master/MindFlow/applications/physics_driven/navier_stokes/kovasznay/src/dataset.py)。" + "本案例在求解域及边值条件进行随机采样，生成训练数据集与测试数据集。具体方法见[src/dataset.py](https://atomgit.com/mindspore/mindscience/blob/master/MindFlow/applications/physics_driven/navier_stokes/kovasznay/src/dataset.py)。" ] }, { diff --git a/docs/mindflow/docs/source_zh_cn/physics_driven/navier_stokes2D.ipynb b/docs/mindflow/docs/source_zh_cn/physics_driven/navier_stokes2D.ipynb index 7b7bbd3eadc5ddca979a3a05635efeea6011501f..e7d509ff8507e35fe1a0e29430c8b98d494f80e9 100644 --- a/docs/mindflow/docs/source_zh_cn/physics_driven/navier_stokes2D.ipynb +++ b/docs/mindflow/docs/source_zh_cn/physics_driven/navier_stokes2D.ipynb @@ -89,7 +89,7 @@ "cell_type": "markdown", "metadata": {}, "source": [ - "下述`src`包可以在[applications/physics_driven/navier_stokes/cylinder_flow_forward/src](https://atomgit.com/mindspore-lab/mindscience/tree/master/MindFlow/applications/physics_driven/navier_stokes/cylinder_flow_forward/src)下载。" + "下述`src`包可以在[applications/physics_driven/navier_stokes/cylinder_flow_forward/src](https://atomgit.com/mindspore/mindscience/tree/master/MindFlow/applications/physics_driven/navier_stokes/cylinder_flow_forward/src)下载。" ] }, { diff --git a/docs/mindflow/docs/source_zh_cn/physics_driven/navier_stokes_inverse.ipynb b/docs/mindflow/docs/source_zh_cn/physics_driven/navier_stokes_inverse.ipynb index 2fb8f697672e63fb505b4dae82332e32b890207c..2bbf3dfd8baff0da2ec6ee0ba3275f622940f287 100644 --- a/docs/mindflow/docs/source_zh_cn/physics_driven/navier_stokes_inverse.ipynb +++ b/docs/mindflow/docs/source_zh_cn/physics_driven/navier_stokes_inverse.ipynb @@ -86,7 +86,7 @@ "cell_type": "markdown", "metadata": {}, "source": [ - "下述 `src` 包可以在[applications/physics_driven/navier_stokes/cylinder_flow_inverse/src](https://atomgit.com/mindspore-lab/mindscience/tree/master/MindFlow/applications/physics_driven/navier_stokes/cylinder_flow_inverse/src) 下载。" + "下述 `src` 包可以在[applications/physics_driven/navier_stokes/cylinder_flow_inverse/src](https://atomgit.com/mindspore/mindscience/tree/master/MindFlow/applications/physics_driven/navier_stokes/cylinder_flow_inverse/src) 下载。" ] }, { @@ -111,7 +111,7 @@ "cell_type": "markdown", "metadata": {}, "source": [ - "下述`inverse_navier_stokes.yaml`文件可以在[applications/physics_driven/navier_stokes/cylinder_flow_inverse/configs/navier_stokes_inverse.yaml](https://atomgit.com/mindspore-lab/mindscience/blob/master/MindFlow/applications/physics_driven/navier_stokes/cylinder_flow_inverse/configs/navier_stokes_inverse.yaml)下载。" + "下述`inverse_navier_stokes.yaml`文件可以在[applications/physics_driven/navier_stokes/cylinder_flow_inverse/configs/navier_stokes_inverse.yaml](https://atomgit.com/mindspore/mindscience/blob/master/MindFlow/applications/physics_driven/navier_stokes/cylinder_flow_inverse/configs/navier_stokes_inverse.yaml)下载。" ] }, { diff --git a/docs/mindflow/docs/source_zh_cn/physics_driven/periodic_hill.ipynb b/docs/mindflow/docs/source_zh_cn/physics_driven/periodic_hill.ipynb index 45a8fe57a548d57756fce42d15181a21498a9033..c38b36ca75a147d90385351200a26a55bd8c4c6a 100644 --- a/docs/mindflow/docs/source_zh_cn/physics_driven/periodic_hill.ipynb +++ b/docs/mindflow/docs/source_zh_cn/physics_driven/periodic_hill.ipynb @@ -46,7 +46,7 @@ "source": [ "## 准备工作\n", "\n", - "导入训练所需函数库，其中[src文件夹](https://atomgit.com/mindspore-lab/mindscience/tree/master/MindFlow/applications/physics_driven/navier_stokes/periodic_hill/src)包括数据集处理函数、网络模型和损失值计算函数。\n", + "导入训练所需函数库，其中[src文件夹](https://atomgit.com/mindspore/mindscience/tree/master/MindFlow/applications/physics_driven/navier_stokes/periodic_hill/src)包括数据集处理函数、网络模型和损失值计算函数。\n", "\n", "训练默认采用MindSpore框架的静态图模式(GRAPH)，在GPU(默认)或Ascend进行训练(单卡)。" ] @@ -85,7 +85,7 @@ "source": [ "## 读取参数\n", "\n", - "从[rans.yaml](https://atomgit.com/mindspore-lab/mindscience/blob/master/MindFlow/applications/physics_driven/navier_stokes/periodic_hill/configs/rans.yaml)文件里导入相应的数据集、模型和优化器的参数配置。" + "从[rans.yaml](https://atomgit.com/mindspore/mindscience/blob/master/MindFlow/applications/physics_driven/navier_stokes/periodic_hill/configs/rans.yaml)文件里导入相应的数据集、模型和优化器的参数配置。" ] }, { diff --git a/docs/mindflow/docs/source_zh_cn/physics_driven/poisson_geometry.ipynb b/docs/mindflow/docs/source_zh_cn/physics_driven/poisson_geometry.ipynb index a9eebc9a6e104693390eea338db55cd8f3bf8962..4fe4d9ef5c0e90378fc2d10249aaa7b75a5193da 100644 --- a/docs/mindflow/docs/source_zh_cn/physics_driven/poisson_geometry.ipynb +++ b/docs/mindflow/docs/source_zh_cn/physics_driven/poisson_geometry.ipynb @@ -55,7 +55,7 @@ "cell_type": "markdown", "metadata": {}, "source": [ - "下述`poisson_cfg.yaml`配置文件可以在[applications/physics_driven/poisson/point_source/poisson_cfg.yaml](https://atomgit.com/mindspore-lab/mindscience/blob/master/MindFlow/applications/physics_driven/poisson/point_source/poisson_cfg.yaml)下载，`src`包可以在[applications/physics_driven/poisson/point_source/src](https://atomgit.com/mindspore-lab/mindscience/tree/master/MindFlow/applications/physics_driven/poisson/point_source/src)下载。\n" + "下述`poisson_cfg.yaml`配置文件可以在[applications/physics_driven/poisson/point_source/poisson_cfg.yaml](https://atomgit.com/mindspore/mindscience/blob/master/MindFlow/applications/physics_driven/poisson/point_source/poisson_cfg.yaml)下载，`src`包可以在[applications/physics_driven/poisson/point_source/src](https://atomgit.com/mindspore/mindscience/tree/master/MindFlow/applications/physics_driven/poisson/point_source/src)下载。\n" ] }, { diff --git a/docs/mindflow/docs/source_zh_cn/physics_driven/taylor_green2D.ipynb b/docs/mindflow/docs/source_zh_cn/physics_driven/taylor_green2D.ipynb index b55b585f96f6a80a27d4b4bc32f08feefbcec8aa..92f88dbdef14edf7eb2007fe4c7d7d2274eb0f80 100644 --- a/docs/mindflow/docs/source_zh_cn/physics_driven/taylor_green2D.ipynb +++ b/docs/mindflow/docs/source_zh_cn/physics_driven/taylor_green2D.ipynb @@ -96,7 +96,7 @@ "cell_type": "markdown", "metadata": {}, "source": [ - "下述`src`包可以在 [applications/physics_driven/navier_stokes/taylor_green/src](https://atomgit.com/mindspore-lab/mindscience/tree/master/MindFlow/applications/physics_driven/navier_stokes/taylor_green/src)下载。" + "下述`src`包可以在 [applications/physics_driven/navier_stokes/taylor_green/src](https://atomgit.com/mindspore/mindscience/tree/master/MindFlow/applications/physics_driven/navier_stokes/taylor_green/src)下载。" ] }, { @@ -120,7 +120,7 @@ "cell_type": "markdown", "metadata": {}, "source": [ - "下述`taylor_green_2D.yaml`配置文件可以在[applications/physics_driven/navier_stokes/taylor_green/configs/taylor_green_2D.yaml](https://atomgit.com/mindspore-lab/mindscience/blob/master/MindFlow/applications/physics_driven/navier_stokes/taylor_green/configs/taylor_green_2D.yaml)下载。" + "下述`taylor_green_2D.yaml`配置文件可以在[applications/physics_driven/navier_stokes/taylor_green/configs/taylor_green_2D.yaml](https://atomgit.com/mindspore/mindscience/blob/master/MindFlow/applications/physics_driven/navier_stokes/taylor_green/configs/taylor_green_2D.yaml)下载。" ] }, { diff --git a/docs/mindsponge/docs/source_en/index.rst b/docs/mindsponge/docs/source_en/index.rst index 05fbe9a7b6db39ec5ab55b1c9d9c2733cda3275e..338f9206ff09f0ec61eb5d344f187b5dee7afad7 100644 --- a/docs/mindsponge/docs/source_en/index.rst +++ b/docs/mindsponge/docs/source_en/index.rst @@ -44,7 +44,7 @@ and application scenarios, such as: - High throughput molecular simulation; - Molecular design, etc. -Code repository address: +Code repository address: Installation ------------ @@ -178,7 +178,7 @@ Contribution Guide ------------------ - Please click here to see how to contribute your code:\ `Contribution - Guide `__ + Guide `__ .. toctree:: :glob: diff --git a/docs/mindsponge/docs/source_en/user/basic.md b/docs/mindsponge/docs/source_en/user/basic.md index 44a031d9f9856fd6b1a8b5bced8b8f3dbd523b62..9d59fa5f54a22abc3ad6333b40a83074a4b88192 100644 --- a/docs/mindsponge/docs/source_en/user/basic.md +++ b/docs/mindsponge/docs/source_en/user/basic.md @@ -8,7 +8,7 @@ In fields such as biological computing and drug design, it is very expensive to | Function | Model | Training | Inferring | Back-end | | :----------- | :------------------------------ | :--- | :--- | :-------- | -| Molecular Compound Pre-training Model | [GROVER](https://atomgit.com/mindspore-lab/mindscience/pulls/441/files#) | √ | √ | GPU/Ascend | -| Molecular Compound Pre-training Model | [MGBERT](https://atomgit.com/mindspore-lab/mindscience/pulls/631/files#) | √ | √ | GPU/Ascend | +| Molecular Compound Pre-training Model | [GROVER](https://atomgit.com/mindspore/mindscience/pulls/441/files#) | √ | √ | GPU/Ascend | +| Molecular Compound Pre-training Model | [MGBERT](https://atomgit.com/mindspore/mindscience/pulls/631/files#) | √ | √ | GPU/Ascend | In the future, basic models such as protein pre-training will be provided. Please stay tuned. \ No newline at end of file diff --git a/docs/mindsponge/docs/source_en/user/design.md b/docs/mindsponge/docs/source_en/user/design.md index 5559eff223eba781a92cd8141d86c2a4fda8dfaa..b8cd9827fa9a8d6a7f67eebe7f7783374ecd4cfb 100644 --- a/docs/mindsponge/docs/source_en/user/design.md +++ b/docs/mindsponge/docs/source_en/user/design.md @@ -10,7 +10,7 @@ MindSpore SPONGE Biocomputing Toolkit provides a series of molecular design tool | Function | Model | Training | Inferring | Back-end | | :----------- | :------------------------------ | :--- | :--- | :-------- | -| Protein Sequence Design | [ProteinMPNN](https://atomgit.com/mindspore-lab/mindscience/blob/master/MindSPONGE/applications/model_cards/ProteinMPNN.MD) | × | √ | GPU/Ascend | -| Protein Sequence Design | [ESM-IF1](https://atomgit.com/mindspore-lab/mindscience/blob/master/MindSPONGE/applications/model_cards/ESM-IF1.md) | × | √ | GPU/Ascend | +| Protein Sequence Design | [ProteinMPNN](https://atomgit.com/mindspore/mindscience/blob/master/MindSPONGE/applications/model_cards/ProteinMPNN.MD) | × | √ | GPU/Ascend | +| Protein Sequence Design | [ESM-IF1](https://atomgit.com/mindspore/mindscience/blob/master/MindSPONGE/applications/model_cards/ESM-IF1.md) | × | √ | GPU/Ascend | In the future, we will also provide antibody sequence design, molecular generation and other tools. Please stay tuned. \ No newline at end of file diff --git a/docs/mindsponge/docs/source_en/user/property_prediction.md b/docs/mindsponge/docs/source_en/user/property_prediction.md index 842f47389340e899eb0c25dba1c73bbd0e06e8f9..afa3d95024cdff3cab83f195369b7cbafddc9bfa 100644 --- a/docs/mindsponge/docs/source_en/user/property_prediction.md +++ b/docs/mindsponge/docs/source_en/user/property_prediction.md @@ -10,6 +10,6 @@ Molecular property prediction is one of the most important tasks in the computer | :------------- | :-------------------- | :--- | :--- | :-------- | | Drug Interaction Prediction | KGNN | √ | √ | GPU/Ascend | | Drug Disease Association Prediction | DeepDR | √ | √ | GPU/Ascend | -| Protein-Ligand Affinity Prediction | [pafnucy](https://atomgit.com/mindspore-lab/mindscience/blob/master/MindSPONGE/applications/model_cards/pafnucy.md) | √ | √ | GPU/Ascend | +| Protein-Ligand Affinity Prediction | [pafnucy](https://atomgit.com/mindspore/mindscience/blob/master/MindSPONGE/applications/model_cards/pafnucy.md) | √ | √ | GPU/Ascend | Molecular docking, ADMET and other molecular property prediction networks will be provided in the future. Please stay tuned. \ No newline at end of file diff --git a/docs/mindsponge/docs/source_en/user/simulation.md b/docs/mindsponge/docs/source_en/user/simulation.md index ecc8d0a0454331a81ef16a71e282f54bcfb865d6..8157f02068bcf1d1ff092e69a921024d5e98446c 100644 --- a/docs/mindsponge/docs/source_en/user/simulation.md +++ b/docs/mindsponge/docs/source_en/user/simulation.md @@ -222,7 +222,7 @@ Thanks to the multi-tiered data structure of HDF5, H5MD itself is highly scalabl ## Tutorial -A tutorial on molecular dynamics simulations using the MindSpore SPONGE is available at [MindScience](https://atomgit.com/mindspore-lab/mindscience/tree/master/MindSPONGE/tutorials/basic). +A tutorial on molecular dynamics simulations using the MindSpore SPONGE is available at [MindScience](https://atomgit.com/mindspore/mindscience/tree/master/MindSPONGE/tutorials/basic). ## Reference diff --git a/docs/mindsponge/docs/source_en/user/structure_prediction.md b/docs/mindsponge/docs/source_en/user/structure_prediction.md index 9c8cc76475d92b9a53ea100f9c2412f2083e1464..d5e086249f54eeb86c5891221440c62882b5ef4a 100644 --- a/docs/mindsponge/docs/source_en/user/structure_prediction.md +++ b/docs/mindsponge/docs/source_en/user/structure_prediction.md @@ -10,10 +10,10 @@ Currently, a series of tools for protein and RNA structure prediction are availa | Function | Model | Training | Inferring | Back-end | | :------------- | :------------------------------------------- | :--- | :--- | :-------- | -| Single Chain Structure Prediction | [MEGA-Fold](https://atomgit.com/mindspore-lab/mindscience/blob/master/MindSPONGE/applications/model_cards/MEGAProtein.md) | √ | √ | GPU/Ascend | -| MSA Generation/Correction | [MEGA-EvoGen](https://atomgit.com/mindspore-lab/mindscience/blob/master/MindSPONGE/applications/model_cards/MEGAProtein.md) | √ | √ | GPU/Ascend | -| Structural Quality Assessment | [MEGA-Assessment](https://atomgit.com/mindspore-lab/mindscience/blob/master/MindSPONGE/applications/model_cards/MEGAProtein.md) | √ | √ | GPU/Ascend | -| Multi-chain Structure Prediction | [AlphaFold-Multimer](https://atomgit.com/mindspore-lab/mindscience/blob/master/MindSPONGE/applications/model_cards/afmultimer.md) | × | √ | GPU/Ascend | -| RNA Secondary Structure Prediction | [UFold](https://atomgit.com/mindspore-lab/mindscience/blob/master/MindSPONGE/applications/model_cards/UFold.md) | √ | √ | GPU/Ascend | +| Single Chain Structure Prediction | [MEGA-Fold](https://atomgit.com/mindspore/mindscience/blob/master/MindSPONGE/applications/model_cards/MEGAProtein.md) | √ | √ | GPU/Ascend | +| MSA Generation/Correction | [MEGA-EvoGen](https://atomgit.com/mindspore/mindscience/blob/master/MindSPONGE/applications/model_cards/MEGAProtein.md) | √ | √ | GPU/Ascend | +| Structural Quality Assessment | [MEGA-Assessment](https://atomgit.com/mindspore/mindscience/blob/master/MindSPONGE/applications/model_cards/MEGAProtein.md) | √ | √ | GPU/Ascend | +| Multi-chain Structure Prediction | [AlphaFold-Multimer](https://atomgit.com/mindspore/mindscience/blob/master/MindSPONGE/applications/model_cards/afmultimer.md) | × | √ | GPU/Ascend | +| RNA Secondary Structure Prediction | [UFold](https://atomgit.com/mindspore/mindscience/blob/master/MindSPONGE/applications/model_cards/UFold.md) | √ | √ | GPU/Ascend | In the future, we will further improve the function of molecular structure prediction, and introduce more tools for protein-ligand complex structure prediction and small molecule structure prediction of compounds. Stay tuned for more information. \ No newline at end of file diff --git a/docs/mindsponge/docs/source_zh_cn/index.rst b/docs/mindsponge/docs/source_zh_cn/index.rst index 188fee2db83412bb6eedb0c668d603bb395eb0ab..2bbccc07a0527a14c4c45d95363a1e2c674c7383 100644 --- a/docs/mindsponge/docs/source_zh_cn/index.rst +++ b/docs/mindsponge/docs/source_zh_cn/index.rst @@ -25,7 +25,7 @@ MindSpore SPONGE是一款基于MindSpore的计算生物领域套件，支持分 - 高通量的分子模拟； - 分子设计等。 -代码仓地址： +代码仓地址： MindSpore SPONGE 安装说明 ------------------------- @@ -136,7 +136,7 @@ SPONGE暑期学校第二季 `__\ 。 +- 如何贡献您的代码，请点击此处查看：\ `贡献指南 `__\ 。 .. toctree:: :glob: diff --git a/docs/mindsponge/docs/source_zh_cn/user/basic.md b/docs/mindsponge/docs/source_zh_cn/user/basic.md index 2cec1b86ebef326c0eba10bc6068ffb23a54060e..dfeb06abcb0370b7aeb72629f14f23cf1bbddcc2 100644 --- a/docs/mindsponge/docs/source_zh_cn/user/basic.md +++ b/docs/mindsponge/docs/source_zh_cn/user/basic.md @@ -8,7 +8,7 @@ | 功能 | 模型 | 训练 | 推理 | 后端 | | :----------- | :------------------------------ | :--- | :--- | :-------- | -| 小分子化合物预训练模型 | [GROVER](https://atomgit.com/mindspore-lab/mindscience/pulls/441/files#) | √ | √ | GPU/Ascend | -| 小分子化合物预训练模型 | [MGBERT](https://atomgit.com/mindspore-lab/mindscience/pulls/631/files#) | √ | √ | GPU/Ascend | +| 小分子化合物预训练模型 | [GROVER](https://atomgit.com/mindspore/mindscience/pulls/441/files#) | √ | √ | GPU/Ascend | +| 小分子化合物预训练模型 | [MGBERT](https://atomgit.com/mindspore/mindscience/pulls/631/files#) | √ | √ | GPU/Ascend | 后续将提供蛋白质预训练等基础模型，敬请期待。 \ No newline at end of file diff --git a/docs/mindsponge/docs/source_zh_cn/user/design.md b/docs/mindsponge/docs/source_zh_cn/user/design.md index 55ee91f406f1b294cb6b809d3005fcdb532a35bf..47f6296ef9f9135972a4337dae6fbc1fd285f5a3 100644 --- a/docs/mindsponge/docs/source_zh_cn/user/design.md +++ b/docs/mindsponge/docs/source_zh_cn/user/design.md @@ -10,7 +10,7 @@ MindSpore SPONGE生物计算工具包提供一系列基于深度生成模型的 | 功能 | 模型 | 训练 | 推理 | 后端 | | :----------- | :------------------------------ | :--- | :--- | :-------- | -| 蛋白质序列设计 | [ProteinMPNN](https://atomgit.com/mindspore-lab/mindscience/blob/master/MindSPONGE/applications/model_cards/ProteinMPNN.MD) | × | √ | GPU/Ascend | -| 蛋白质序列设计 | [ESM-IF1](https://atomgit.com/mindspore-lab/mindscience/blob/master/MindSPONGE/applications/model_cards/ESM-IF1.md) | × | √ | GPU/Ascend | +| 蛋白质序列设计 | [ProteinMPNN](https://atomgit.com/mindspore/mindscience/blob/master/MindSPONGE/applications/model_cards/ProteinMPNN.MD) | × | √ | GPU/Ascend | +| 蛋白质序列设计 | [ESM-IF1](https://atomgit.com/mindspore/mindscience/blob/master/MindSPONGE/applications/model_cards/ESM-IF1.md) | × | √ | GPU/Ascend | 未来我们还将提供抗体序列设计，分子生成等工具，敬请期待。 \ No newline at end of file diff --git a/docs/mindsponge/docs/source_zh_cn/user/property_prediction.md b/docs/mindsponge/docs/source_zh_cn/user/property_prediction.md index 01296b1bb6bfa20803e86f7bccaa14dd042d3f06..c5e3536f404d46bc3aef3e38ccaa4ec575535b4c 100644 --- a/docs/mindsponge/docs/source_zh_cn/user/property_prediction.md +++ b/docs/mindsponge/docs/source_zh_cn/user/property_prediction.md @@ -10,6 +10,6 @@ | :------------- | :-------------------- | :--- | :--- | :-------- | | 药物相互作用预测 | KGNN | √ | √ | GPU/Ascend | | 药物疾病关联预测 | DeepDR | √ | √ | GPU/Ascend | -| 蛋白质-配体亲和力预测 | [pafnucy](https://atomgit.com/mindspore-lab/mindscience/blob/master/MindSPONGE/applications/model_cards/pafnucy.md) | √ | √ | GPU/Ascend | +| 蛋白质-配体亲和力预测 | [pafnucy](https://atomgit.com/mindspore/mindscience/blob/master/MindSPONGE/applications/model_cards/pafnucy.md) | √ | √ | GPU/Ascend | 后续将提供分子对接，ADMET等分子性质预测网络，敬请期待。 \ No newline at end of file diff --git a/docs/mindsponge/docs/source_zh_cn/user/simulation.md b/docs/mindsponge/docs/source_zh_cn/user/simulation.md index 22567e476db90b0e9efff642a7ac66642b7c86ca..57f874e366ec11fa53356b685ca6517055569026 100644 --- a/docs/mindsponge/docs/source_zh_cn/user/simulation.md +++ b/docs/mindsponge/docs/source_zh_cn/user/simulation.md @@ -221,7 +221,7 @@ MindSpore SPONGE采用H5MD作为记录模拟轨迹的默认文件格式。H5MD ## 使用教程 -使用MindSpore SPONGE进行分子动力学模拟的教程可在[MindScience仓库](https://atomgit.com/mindspore-lab/mindscience/tree/master/MindSPONGE/tutorials/basic)进行查看。 +使用MindSpore SPONGE进行分子动力学模拟的教程可在[MindScience仓库](https://atomgit.com/mindspore/mindscience/tree/master/MindSPONGE/tutorials/basic)进行查看。 ## 参考文献 diff --git a/docs/mindsponge/docs/source_zh_cn/user/structure_prediction.md b/docs/mindsponge/docs/source_zh_cn/user/structure_prediction.md index c269bb5ca208de9a48933d6f40e07cf3eb263c8d..b3e970a77985d6269ddcc62f4dbd2d1b6c2aa27b 100644 --- a/docs/mindsponge/docs/source_zh_cn/user/structure_prediction.md +++ b/docs/mindsponge/docs/source_zh_cn/user/structure_prediction.md @@ -10,10 +10,10 @@ | 功能 | 模型 | 训练 | 推理 | 后端 | | :------------- | :------------------------------------------- | :--- | :--- | :-------- | -| 单链结构预测 | [MEGA-Fold](https://atomgit.com/mindspore-lab/mindscience/blob/master/MindSPONGE/applications/model_cards/MEGAProtein.md) | √ | √ | GPU/Ascend | -| MSA生成/修正 | [MEGA-EvoGen](https://atomgit.com/mindspore-lab/mindscience/blob/master/MindSPONGE/applications/model_cards/MEGAProtein.md) | √ | √ | GPU/Ascend | -| 结构质量评估 | [MEGA-Assessment](https://atomgit.com/mindspore-lab/mindscience/blob/master/MindSPONGE/applications/model_cards/MEGAProtein.md) | √ | √ | GPU/Ascend | -| 多链结构预测 | [AlphaFold-Multimer](https://atomgit.com/mindspore-lab/mindscience/blob/master/MindSPONGE/applications/model_cards/afmultimer.md) | × | √ | GPU/Ascend | -| RNA二级结构预测 | [UFold](https://atomgit.com/mindspore-lab/mindscience/blob/master/MindSPONGE/applications/model_cards/UFold.md) | √ | √ | GPU/Ascend | +| 单链结构预测 | [MEGA-Fold](https://atomgit.com/mindspore/mindscience/blob/master/MindSPONGE/applications/model_cards/MEGAProtein.md) | √ | √ | GPU/Ascend | +| MSA生成/修正 | [MEGA-EvoGen](https://atomgit.com/mindspore/mindscience/blob/master/MindSPONGE/applications/model_cards/MEGAProtein.md) | √ | √ | GPU/Ascend | +| 结构质量评估 | [MEGA-Assessment](https://atomgit.com/mindspore/mindscience/blob/master/MindSPONGE/applications/model_cards/MEGAProtein.md) | √ | √ | GPU/Ascend | +| 多链结构预测 | [AlphaFold-Multimer](https://atomgit.com/mindspore/mindscience/blob/master/MindSPONGE/applications/model_cards/afmultimer.md) | × | √ | GPU/Ascend | +| RNA二级结构预测 | [UFold](https://atomgit.com/mindspore/mindscience/blob/master/MindSPONGE/applications/model_cards/UFold.md) | √ | √ | GPU/Ascend | 未来我们将进一步完善分子结构预测的相关功能，推出蛋白质-配体复合结构预测以及化合物小分子结构预测等更多工具，敬请期待。 \ No newline at end of file diff --git a/docs/sciai/docs/source_en/build_model_with_sciai.md b/docs/sciai/docs/source_en/build_model_with_sciai.md index 3ae4477f211f67207525777ceeed289724680b61..b6abcdb7133aa56427e9f504ba92a1ff34a844d0 100644 --- a/docs/sciai/docs/source_en/build_model_with_sciai.md +++ b/docs/sciai/docs/source_en/build_model_with_sciai.md @@ -7,7 +7,7 @@ SciAI base framework consists of several modules covering network setup, network The following examples indicates the fundamental processes in using SciAI to build a neural network model. > You can download the full sample code here: -> +> ## Model Building Basics @@ -19,7 +19,7 @@ $$ f(x) = {x_1}^2 + sin(x_2) $$ -For the codes of this part, please refer to the [codes](https://atomgit.com/mindspore-lab/mindscience/blob/master/SciAI/tutorial/example_net.py). +For the codes of this part, please refer to the [codes](https://atomgit.com/mindspore/mindscience/blob/master/SciAI/tutorial/example_net.py). ### Setup Neural Networks @@ -177,7 +177,7 @@ $$ f(x) = \frac{x^2}{0.2 x^5 + 0.8}. $$ -For the codes of this part, please refer to [codes](https://atomgit.com/mindspore-lab/mindscience/blob/master/SciAI/tutorial/example_grad_net.py). +For the codes of this part, please refer to [codes](https://atomgit.com/mindspore/mindscience/blob/master/SciAI/tutorial/example_grad_net.py). ### Loss Definition diff --git a/docs/sciai/docs/source_en/installation.md b/docs/sciai/docs/source_en/installation.md index 11348b89230896a8fe898953f74f550abf1739f8..b80babb987edd3fc204d0f10170eff415b7144d4 100644 --- a/docs/sciai/docs/source_en/installation.md +++ b/docs/sciai/docs/source_en/installation.md @@ -9,7 +9,7 @@ - See [MindSpore Installation Guide](https://www.mindspore.cn/install/en) to install MindSpore. The versions of MindSpore Elec and MindSpore must be consistent. - All other dependencies are included - in [requirements.txt](https://atomgit.com/mindspore-lab/mindscience/blob/master/SciAI/requirements.txt). + in [requirements.txt](https://atomgit.com/mindspore/mindscience/blob/master/SciAI/requirements.txt). ## Installation diff --git a/docs/sciai/docs/source_en/launch_with_api.md b/docs/sciai/docs/source_en/launch_with_api.md index e9b3f20bd9421743fdbe6f135e008d9b24a4ca3d..194ffd375c838344b3b4fe908a198449bbea08a4 100644 --- a/docs/sciai/docs/source_en/launch_with_api.md +++ b/docs/sciai/docs/source_en/launch_with_api.md @@ -10,7 +10,7 @@ User can launch training and evaluation process with `AutoModel`. User can use the function `AutoModel.from_pretrained` to get the network models, which are supported in SciAI. -Here we use the model Conservative Physics-Informed Neural Networks (CPINNs) as example. For the codes of CPINNs model, please refer to the [link](https://atomgit.com/mindspore-lab/mindscience/tree/master/SciAI/sciai/model/cpinns). +Here we use the model Conservative Physics-Informed Neural Networks (CPINNs) as example. For the codes of CPINNs model, please refer to the [link](https://atomgit.com/mindspore/mindscience/tree/master/SciAI/sciai/model/cpinns). The fundamental idea about this model can be found in this [paper](https://www.sciencedirect.com/science/article/abs/pii/S0045782520302127). diff --git a/docs/sciai/docs/source_en/launch_with_scripts.md b/docs/sciai/docs/source_en/launch_with_scripts.md index 05427c15a6a003f1ececb9b57f7b90ae38e56afa..0ec85faf2a0f7bf9173bbc5c860fce47a081fac1 100644 --- a/docs/sciai/docs/source_en/launch_with_scripts.md +++ b/docs/sciai/docs/source_en/launch_with_scripts.md @@ -4,9 +4,9 @@ The models in MindSpore SciAI provides users with scripts for training and evaluation. -User can train or evaluate any model by running scripts, and the model parameters can be adjusted either through editing the config file or passing parameters in the command line. [This folder](https://atomgit.com/mindspore-lab/mindscience/tree/master/SciAI/sciai/model) contains all the models that support launching with scripts. +User can train or evaluate any model by running scripts, and the model parameters can be adjusted either through editing the config file or passing parameters in the command line. [This folder](https://atomgit.com/mindspore/mindscience/tree/master/SciAI/sciai/model) contains all the models that support launching with scripts. -The following content introduces the general process of training, evaluating models with scripts, taking Conservative Physics-Informed Neural Networks(CPINNs) as an example. For the codes of CPINNs model, please refer to the [link](https://atomgit.com/mindspore-lab/mindscience/tree/master/SciAI/sciai/model/cpinns). +The following content introduces the general process of training, evaluating models with scripts, taking Conservative Physics-Informed Neural Networks(CPINNs) as an example. For the codes of CPINNs model, please refer to the [link](https://atomgit.com/mindspore/mindscience/tree/master/SciAI/sciai/model/cpinns). The fundamental idea about this model can be found in this [paper](https://www.sciencedirect.com/science/article/abs/pii/S0045782520302127). @@ -19,7 +19,7 @@ git clone https://atomgit.com/mindspore-lab/mindscience source ./mindscience/SciAI/.env ``` -After a successful clone, user can start training or evaluating according to the `Quick Start` section in the [README.md](https://atomgit.com/mindspore-lab/mindscience/blob/master/SciAI/sciai/model/cpinns/README.md)(In case of CPINNs). +After a successful clone, user can start training or evaluating according to the `Quick Start` section in the [README.md](https://atomgit.com/mindspore/mindscience/blob/master/SciAI/sciai/model/cpinns/README.md)(In case of CPINNs). ```bash cd ./mindscience/SciAI/sciai/model/cpinns/ @@ -27,7 +27,7 @@ cd ./mindscience/SciAI/sciai/model/cpinns/ ## Training and Fine-tuning the Model -User can run script [train.py](https://atomgit.com/mindspore-lab/mindscience/blob/master/SciAI/sciai/model/cpinns/train.py) in each model directory to train the models. +User can run script [train.py](https://atomgit.com/mindspore/mindscience/blob/master/SciAI/sciai/model/cpinns/train.py) in each model directory to train the models. ```bash python ./train.py [--parameters] @@ -47,7 +47,7 @@ python ./train.py --load_ckpt true --load_ckpt_path {your_file}.ckpt [--paramete Using the optional parameter `[--parameters]`, user can configure the training process of the model, including learning rate, training epochs, data saving and loading paths and so on. -For details about the configurable parameters in each model, see the `Script Parameters` section in the [README.md](https://atomgit.com/mindspore-lab/mindscience/blob/master/SciAI/sciai/model/cpinns/README.md). +For details about the configurable parameters in each model, see the `Script Parameters` section in the [README.md](https://atomgit.com/mindspore/mindscience/blob/master/SciAI/sciai/model/cpinns/README.md). ## Evaluating the Model diff --git a/docs/sciai/docs/source_en/model_library.md b/docs/sciai/docs/source_en/model_library.md index 978db6f3587fcc2a770d574c3c8ec9310bb2be7d..6c28d867e7b59da81b61168f4ed3888e23cc39d2 100644 --- a/docs/sciai/docs/source_en/model_library.md +++ b/docs/sciai/docs/source_en/model_library.md @@ -7,68 +7,68 @@ The following table summarizes the current available neural networks and their c | Domain | Network | MindSpore Implementation and Parameters | Ascend | GPU | |---------------------|-----------------------------------------------------------------------------------------------------------------------|:----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------:|:------:|:---:| -| General Physics | [auq_pinns](https://www.sciencedirect.com/science/article/pii/S0021999119303584) | [link](https://atomgit.com/mindspore-lab/mindscience/blob/master/SciAI/sciai/model/auq_pinns/README.md#script-parameters) | ✅ | ✅ | -| General Physics | [cpinns](https://www.sciencedirect.com/science/article/abs/pii/S0045782520302127) | [link](https://atomgit.com/mindspore-lab/mindscience/blob/master/SciAI/sciai/model/cpinns/README.md#script-parameters) | ✅ | ✅ | -| General Physics | [deep_hpms](https://www.jmlr.org/papers/volume19/18-046/18-046.pdf) | [link](https://atomgit.com/mindspore-lab/mindscience/blob/master/SciAI/sciai/model/deep_hpms/README.md#script-parameters) | ✅ | ✅ | -| General Physics | [deep_ritz](https://arxiv.org/abs/1710.00211) | [link](https://atomgit.com/mindspore-lab/mindscience/blob/master/SciAI/sciai/model/deep_ritz/README.md#script-parameters) | ✅ | ✅ | -| General Physics | [deepbsde](https://www.pnas.org/doi/10.1073/pnas.1718942115) | [link](https://atomgit.com/mindspore-lab/mindscience/blob/master/SciAI/sciai/model/deepbsde/README.md#script-parameters) | | ✅ | -| General Physics | [deeponet](https://www.nature.com/articles/s42256-021-00302-5) | [link](https://atomgit.com/mindspore-lab/mindscience/blob/master/SciAI/sciai/model/deeponet/README.md#script-parameters) | ✅ | ✅ | -| General Physics | [dgm](https://arxiv.org/abs/1708.07469) | [link](https://atomgit.com/mindspore-lab/mindscience/blob/master/SciAI/sciai/model/dgm/README.md#script-parameters) | ✅ | ✅ | -| General Physics | [fbsnns](https://arxiv.org/abs/1804.07010) | [link](https://atomgit.com/mindspore-lab/mindscience/blob/master/SciAI/sciai/model/fbsnns/README.md#script-parameters) | ✅ | ✅ | -| General Physics | [fpinns](https://arxiv.org/abs/1811.08967) | [link](https://atomgit.com/mindspore-lab/mindscience/blob/master/SciAI/sciai/model/fpinns/README.md#script-parameters) | ✅ | ✅ | -| General Physics | [gradient_pathologies_pinns](https://arxiv.org/abs/2001.04536) | [link](https://atomgit.com/mindspore-lab/mindscience/blob/master/SciAI/sciai/model/gradient_pathologies_pinns/README.md#script-parameters) | ✅ | ✅ | -| General Physics | [hp_vpinns](https://arxiv.org/abs/2003.05385) | [link](https://atomgit.com/mindspore-lab/mindscience/blob/master/SciAI/sciai/model/hp_vpinns/README.md#script-parameters) | ✅ | ✅ | -| General Physics | [laaf](https://doi.org/10.1016/j.jcp.2019.109136) | [link](https://atomgit.com/mindspore-lab/mindscience/blob/master/SciAI/sciai/model/laaf/README.md#script-parameters) | ✅ | ✅ | -| General Physics | [mgnet](https://link.springer.com/article/10.1007/s11425-019-9547-2) | [link](https://atomgit.com/mindspore-lab/mindscience/blob/master/SciAI/sciai/model/mgnet/README.md#script-parameters) | ✅ | ✅ | -| General Physics | [multiscale_pinns](https://www.sciencedirect.com/science/article/abs/pii/S0045782521002759) | [link](https://atomgit.com/mindspore-lab/mindscience/blob/master/SciAI/sciai/model/multiscale_pinns/README.md#script-parameters) | ✅ | ✅ | -| General Physics | [pfnn](https://www.sciencedirect.com/science/article/abs/pii/S0021999120308597) | [link](https://atomgit.com/mindspore-lab/mindscience/blob/master/SciAI/sciai/model/pfnn/README_CN.md#脚本说明) | | ✅ | -| General Physics | [phygeonet](https://www.sciencedirect.com/science/article/abs/pii/S0021999120308536) | [link](https://atomgit.com/mindspore-lab/mindscience/blob/master/SciAI/sciai/model/phygeonet/README.md#script-parameters) | ✅ | ✅ | -| General Physics | [pi_deeponet](https://www.sciencedirect.com/science/article/abs/pii/S0021999122009184) | [link](https://atomgit.com/mindspore-lab/mindscience/blob/master/SciAI/sciai/model/pi_deeponet/README.md#script-parameters) | | ✅ | -| General Physics | [pinns](https://www.sciencedirect.com/science/article/abs/pii/S0021999118307125) | [link](https://atomgit.com/mindspore-lab/mindscience/blob/master/SciAI/sciai/model/pinns/README.md#script-parameters) | | ✅ | -| General Physics | [pinns_ntk](https://www.sciencedirect.com/science/article/pii/S002199912100663X) | [link](https://atomgit.com/mindspore-lab/mindscience/blob/master/SciAI/sciai/model/pinns_ntk/README.md#script-parameters) | ✅ | ✅ | -| General Physics | [ppinns](https://www.sciencedirect.com/science/article/abs/pii/S0045782520304357) | [link](https://atomgit.com/mindspore-lab/mindscience/blob/master/SciAI/sciai/model/ppinns/README.md#script-parameters) | ✅ | ✅ | -| General Physics | [xpinns](https://doi.org/10.4208/cicp.OA-2020-0164) | [link](https://atomgit.com/mindspore-lab/mindscience/blob/master/SciAI/sciai/model/xpinns/README.md#script-parameters) | ✅ | ✅ | -| Hamiltonian Systems | [sympnets](https://www.sciencedirect.com/science/article/pii/S0893608020303063) | [link](https://atomgit.com/mindspore-lab/mindscience/blob/master/SciAI/sciai/model/sympnets/README.md#script-parameters) | ✅ | ✅ | -| Fluid Dynamic | [hfm](https://www.science.org/doi/abs/10.1126/science.aaw4741) | [link](https://atomgit.com/mindspore-lab/mindscience/blob/master/SciAI/sciai/model/hfm/README.md#script-parameters) | ✅ | ✅ | -| Fluid Dynamic | [label_free_dnn_surrogate](https://www.sciencedirect.com/science/article/pii/S004578251930622X) | [link](https://atomgit.com/mindspore-lab/mindscience/blob/master/SciAI/sciai/model/label_free_dnn_surrogate/README.md#script-parameters) | ✅ | ✅ | -| Fluid Dynamic | [nsf_nets](https://www.sciencedirect.com/science/article/pii/S0021999120307257) | [link](https://atomgit.com/mindspore-lab/mindscience/blob/master/SciAI/sciai/model/nsf_nets/README.md#script-parameters) | ✅ | ✅ | -| Fluid Dynamic | [*burgers_fno](https://arxiv.org/abs/2010.08895) | [link](https://atomgit.com/mindspore-lab/mindscience/blob/master/MindFlow/applications/data_driven/burgers/fno1d/FNO1D.ipynb) | ✅ | ✅ | -| Fluid Dynamic | [*burgers_kno](https://arxiv.org/abs/2301.10022) | [link](https://atomgit.com/mindspore-lab/mindscience/blob/master/MindFlow/applications/data_driven/burgers/kno1d/KNO1D.ipynb) | ✅ | ✅ | -| Fluid Dynamic | [*navier_stokes_fno](https://arxiv.org/abs/2010.08895) | [link](https://atomgit.com/mindspore-lab/mindscience/blob/master/MindFlow/applications/data_driven/navier_stokes/fno2d/FNO2D.ipynb) | ✅ | ✅ | -| Fluid Dynamic | [*navier_stokes_kno](https://arxiv.org/abs/2301.10022) | [link](https://atomgit.com/mindspore-lab/mindscience/blob/master/MindFlow/applications/data_driven/navier_stokes/kno2d/KNO2D.ipynb) | ✅ | ✅ | -| Fluid Dynamic | [*navier_stokes_3d_fno](https://arxiv.org/abs/2010.08895) | [link](https://atomgit.com/mindspore-lab/mindscience/blob/master/MindFlow/applications/data_driven/navier_stokes/fno3d/FNO3D.ipynb) | ✅ | ✅ | -| Fluid Dynamic | [*pde_net](https://arxiv.org/abs/1710.09668) | [link](https://atomgit.com/mindspore-lab/mindscience/blob/master/MindFlow/applications/data_mechanism_fusion/pde_net/README.md) | ✅ | ✅ | -| Fluid Dynamic | [*percnn](https://www.nature.com/articles/s42256-023-00685-7) | [link](https://atomgit.com/mindspore-lab/mindscience/blob/master/MindFlow/applications/data_mechanism_fusion/percnn/README.md) | ✅ | ✅ | -| Elastodynamics | [pinn_elastodynamics](https://arxiv.org/abs/2006.08472) | [link](https://atomgit.com/mindspore-lab/mindscience/blob/master/SciAI/sciai/model/pinn_elastodynamics/README.md#script-parameters) | ✅ | ✅ | -| Thermodynamics | [pinn_heattransfer](https://arxiv.org/abs/1711.10561) | [link](https://atomgit.com/mindspore-lab/mindscience/blob/master/SciAI/sciai/model/pinn_heattransfer/README.md#script-parameters) | ✅ | ✅ | -| Meteorology | [enso](https://doi.org/10.1038/s41586-019-1559-7) | [link](https://atomgit.com/mindspore-lab/mindscience/blob/master/SciAI/sciai/model/enso/README.md#script-parameters) | ✅ | ✅ | -| Geology | [inversion_net](https://ieeexplore.ieee.org/abstract/document/8918045/) | [link](https://atomgit.com/mindspore-lab/mindscience/blob/master/SciAI/sciai/model/inversion_net/README.md#script-parameters) | ✅ | ✅ | -| Geology | [pinn_helmholtz](https://academic.oup.com/gji/article-abstract/228/3/1750/6409132) | [link](https://atomgit.com/mindspore-lab/mindscience/blob/master/SciAI/sciai/model/pinn_helmholtz/README.md#script-parameters) | ✅ | ✅ | -| Oceanic Physics | [ocean_model](https://gmd.copernicus.org/articles/12/4729/2019/) | [link](https://atomgit.com/mindspore-lab/mindscience/blob/master/SciAI/sciai/model/ocean_model/README.md#Model-Description) | | ✅ | -| Oceanic Physics | [pinns_swe](https://arxiv.org/abs/2104.00615) | [link](https://atomgit.com/mindspore-lab/mindscience/blob/master/SciAI/sciai/model/pinns_swe/README.md#script-parameters) | ✅ | ✅ | -| Electromagnetism | [maxwell_net](https://arxiv.org/abs/2107.06164) | [link](https://atomgit.com/mindspore-lab/mindscience/blob/master/SciAI/sciai/model/maxwell_net/README.md#script-parameters) | ✅ | ✅ | -| Electromagnetism | [*AD_FDTD_invert_f](https://www.mindspore.cn/mindelec/docs/en/r0.2/AD_FDTD.html) | [link](https://atomgit.com/mindspore-lab/mindscience/blob/master/MindElec/examples/AD_FDTD/fdtd_forward/README.md#script-parameters) | | ✅ | -| Electromagnetism | [*AD_FDTD_microstrip_filter](https://www.mindspore.cn/mindelec/docs/en/r0.2/AD_FDTD.html) | [link](https://atomgit.com/mindspore-lab/mindscience/blob/master/MindElec/examples/AD_FDTD/fdtd_forward/README.md#script-parameters) | | ✅ | -| Electromagnetism | [*AD_FDTD_inverse](https://www.mindspore.cn/mindelec/docs/en/r0.2/AD_FDTD.html) | [link](https://atomgit.com/mindspore-lab/mindscience/blob/master/MindElec/examples/AD_FDTD/fdtd_inverse/README.md#script-parameters) | | ✅ | -| Electromagnetism | [*frequency_domain_maxwell](https://arxiv.org/abs/2107.06164) | [link](https://atomgit.com/mindspore-lab/mindscience/blob/master/MindElec/examples/physics_driven/frequency_domain_maxwell/README.md#script-parameters) | ✅ | ✅ | -| Electromagnetism | [*frequency_domain_maxwell_3D_dielectric_slab](https://arxiv.org/abs/2107.06164) | [link](https://atomgit.com/mindspore-lab/mindscience/blob/master/MindElec/examples/physics_driven/frequency_domain_maxwell_3D/dielectric_slab_3d/README.md#脚本参数) | ✅ | ✅ | -| Electromagnetism | [*frequency_domain_maxwell_3D_waveguide_cavity](https://arxiv.org/abs/2107.06164) | [link](https://atomgit.com/mindspore-lab/mindscience/blob/master/MindElec/examples/physics_driven/frequency_domain_maxwell_3D/waveguide_cavity_3d/README.md#脚本参数) | ✅ | ✅ | -| Electromagnetism | [*meta_auto_decoder](https://arxiv.org/abs/2111.08823) | [link](https://atomgit.com/mindspore-lab/mindscience/blob/master/MindElec/examples/physics_driven/incremental_learning/README.md#script-parameters) | ✅ | ✅ | -| Electromagnetism | [*pinn_fwi](https://agupubs.onlinelibrary.wiley.com/doi/abs/10.1029/2021JB023120) | [link](https://atomgit.com/mindspore-lab/mindscience/blob/master/MindElec/examples/physics_driven/pinn_fwi/README.md) | ✅ | ✅ | -| Electromagnetism | [*SED_ANN](https://atomgit.com/mindspore-lab/mindscience/tree/master/MindElec/examples/data_driven/sed_ann) | [link](https://atomgit.com/mindspore-lab/mindscience/blob/master/MindElec/examples/data_driven/sed_ann/README_CN.md) | ✅ | ✅ | -| Electromagnetism | [*time_domain_maxwell](https://www.ijcai.org/proceedings/2022/533) | [link](https://atomgit.com/mindspore-lab/mindscience/blob/master/MindElec/examples/physics_driven/time_domain_maxwell/README.md#script-parameters) | ✅ | ✅ | -| Electromagnetism | [*metasurface_holograms](https://www.researching.cn/articles/OJ44d3746c3db8c1e1) | [link](https://atomgit.com/mindspore-lab/mindscience/blob/master/MindElec/examples/metasurface/metasurface_holograms/README.md#parameters) | ✅ | ✅ | -| Biology | [*MEGA-Fold](https://arxiv.org/abs/2206.12240v1) | [link (inference)](https://atomgit.com/mindspore-lab/mindscience/blob/master/MindSPONGE/applications/model_cards/MEGAProtein.md) [link (training)](https://atomgit.com/mindspore-lab/mindscience/blob/master/MindSPONGE/applications/model_cards/MEGAProtein.md) | ✅ | ✅ | -| Biology | [*MEGA-EvoGen](https://arxiv.org/abs/2208.09652) | [link](https://atomgit.com/mindspore-lab/mindscience/blob/master/MindSPONGE/applications/model_cards/MEGAProtein.md) | ✅ | ✅ | -| Biology | [*MEGA-Assessment](https://atomgit.com/mindspore-lab/mindscience/blob/master/MindSPONGE/applications/model_cards/MEGAProtein.md) | [link (inference)](https://atomgit.com/mindspore-lab/mindscience/blob/master/MindSPONGE/applications/model_cards/MEGAProtein.md) [link (training)](https://atomgit.com/mindspore-lab/mindscience/blob/master/MindSPONGE/applications/model_cards/MEGAProtein.md) | ✅ | ✅ | -| Biology | [*ColabDesign](https://www.biorxiv.org/content/10.1101/2021.11.10.468128.abstract) | [link](https://atomgit.com/mindspore-lab/mindscience/blob/master/MindSPONGE/applications/model_cards/ColabDesign.md) | ✅ | ✅ | -| Biology | [*DeepFRI](https://www.nature.com/articles/s41467-021-23303-9) | [link](https://atomgit.com/mindspore-lab/mindscience/blob/master/MindSPONGE/applications/model_cards/DeepFri.md) | ✅ | ✅ | -| Biology | [*Multimer](https://www.biorxiv.org/content/10.1101/2021.10.04.463034v1) | [link](https://atomgit.com/mindspore-lab/mindscience/blob/master/MindSPONGE/applications/model_cards/afmultimer.md) | ✅ | ✅ | -| Biology | [*ProteinMPNN](https://www.science.org/doi/abs/10.1126/science.add2187) | [link](https://atomgit.com/mindspore-lab/mindscience/blob/master/MindSPONGE/applications/model_cards/ProteinMPNN.MD) | ✅ | ✅ | -| Biology | [*UFold](https://doi.org/10.1093/nar/gkab1074) | [link](https://atomgit.com/mindspore-lab/mindscience/blob/master/MindSPONGE/applications/model_cards/UFold.md) | ✅ | ✅ | -| Biology | [*esm-if1](https://proceedings.mlr.press/v162/hsu22a.html) | [link](https://atomgit.com/mindspore-lab/mindscience/blob/master/MindSPONGE/applications/model_cards/ESM-IF1.md) | ✅ | ✅ | -| Biology | [*esm2](https://www.biorxiv.org/content/10.1101/2022.07.20.500902v1.full.pdf) | [link](https://atomgit.com/mindspore-lab/mindscience/blob/master/MindSPONGE/applications/model_cards/ESM-2.md) | ✅ | ✅ | -| Biology | [*grover](https://proceedings.neurips.cc/paper/2020/file/94aef38441efa3380a3bed3faf1f9d5d-Paper.pdf) | [link](https://atomgit.com/mindspore-lab/mindscience/blob/master/MindSPONGE/applications/model_cards/GROVER.MD) | ✅ | ✅ | +| General Physics | [auq_pinns](https://www.sciencedirect.com/science/article/pii/S0021999119303584) | [link](https://atomgit.com/mindspore/mindscience/blob/master/SciAI/sciai/model/auq_pinns/README.md#script-parameters) | ✅ | ✅ | +| General Physics | [cpinns](https://www.sciencedirect.com/science/article/abs/pii/S0045782520302127) | [link](https://atomgit.com/mindspore/mindscience/blob/master/SciAI/sciai/model/cpinns/README.md#script-parameters) | ✅ | ✅ | +| General Physics | [deep_hpms](https://www.jmlr.org/papers/volume19/18-046/18-046.pdf) | [link](https://atomgit.com/mindspore/mindscience/blob/master/SciAI/sciai/model/deep_hpms/README.md#script-parameters) | ✅ | ✅ | +| General Physics | [deep_ritz](https://arxiv.org/abs/1710.00211) | [link](https://atomgit.com/mindspore/mindscience/blob/master/SciAI/sciai/model/deep_ritz/README.md#script-parameters) | ✅ | ✅ | +| General Physics | [deepbsde](https://www.pnas.org/doi/10.1073/pnas.1718942115) | [link](https://atomgit.com/mindspore/mindscience/blob/master/SciAI/sciai/model/deepbsde/README.md#script-parameters) | | ✅ | +| General Physics | [deeponet](https://www.nature.com/articles/s42256-021-00302-5) | [link](https://atomgit.com/mindspore/mindscience/blob/master/SciAI/sciai/model/deeponet/README.md#script-parameters) | ✅ | ✅ | +| General Physics | [dgm](https://arxiv.org/abs/1708.07469) | [link](https://atomgit.com/mindspore/mindscience/blob/master/SciAI/sciai/model/dgm/README.md#script-parameters) | ✅ | ✅ | +| General Physics | [fbsnns](https://arxiv.org/abs/1804.07010) | [link](https://atomgit.com/mindspore/mindscience/blob/master/SciAI/sciai/model/fbsnns/README.md#script-parameters) | ✅ | ✅ | +| General Physics | [fpinns](https://arxiv.org/abs/1811.08967) | [link](https://atomgit.com/mindspore/mindscience/blob/master/SciAI/sciai/model/fpinns/README.md#script-parameters) | ✅ | ✅ | +| General Physics | [gradient_pathologies_pinns](https://arxiv.org/abs/2001.04536) | [link](https://atomgit.com/mindspore/mindscience/blob/master/SciAI/sciai/model/gradient_pathologies_pinns/README.md#script-parameters) | ✅ | ✅ | +| General Physics | [hp_vpinns](https://arxiv.org/abs/2003.05385) | [link](https://atomgit.com/mindspore/mindscience/blob/master/SciAI/sciai/model/hp_vpinns/README.md#script-parameters) | ✅ | ✅ | +| General Physics | [laaf](https://doi.org/10.1016/j.jcp.2019.109136) | [link](https://atomgit.com/mindspore/mindscience/blob/master/SciAI/sciai/model/laaf/README.md#script-parameters) | ✅ | ✅ | +| General Physics | [mgnet](https://link.springer.com/article/10.1007/s11425-019-9547-2) | [link](https://atomgit.com/mindspore/mindscience/blob/master/SciAI/sciai/model/mgnet/README.md#script-parameters) | ✅ | ✅ | +| General Physics | [multiscale_pinns](https://www.sciencedirect.com/science/article/abs/pii/S0045782521002759) | [link](https://atomgit.com/mindspore/mindscience/blob/master/SciAI/sciai/model/multiscale_pinns/README.md#script-parameters) | ✅ | ✅ | +| General Physics | [pfnn](https://www.sciencedirect.com/science/article/abs/pii/S0021999120308597) | [link](https://atomgit.com/mindspore/mindscience/blob/master/SciAI/sciai/model/pfnn/README_CN.md#脚本说明) | | ✅ | +| General Physics | [phygeonet](https://www.sciencedirect.com/science/article/abs/pii/S0021999120308536) | [link](https://atomgit.com/mindspore/mindscience/blob/master/SciAI/sciai/model/phygeonet/README.md#script-parameters) | ✅ | ✅ | +| General Physics | [pi_deeponet](https://www.sciencedirect.com/science/article/abs/pii/S0021999122009184) | [link](https://atomgit.com/mindspore/mindscience/blob/master/SciAI/sciai/model/pi_deeponet/README.md#script-parameters) | | ✅ | +| General Physics | [pinns](https://www.sciencedirect.com/science/article/abs/pii/S0021999118307125) | [link](https://atomgit.com/mindspore/mindscience/blob/master/SciAI/sciai/model/pinns/README.md#script-parameters) | | ✅ | +| General Physics | [pinns_ntk](https://www.sciencedirect.com/science/article/pii/S002199912100663X) | [link](https://atomgit.com/mindspore/mindscience/blob/master/SciAI/sciai/model/pinns_ntk/README.md#script-parameters) | ✅ | ✅ | +| General Physics | [ppinns](https://www.sciencedirect.com/science/article/abs/pii/S0045782520304357) | [link](https://atomgit.com/mindspore/mindscience/blob/master/SciAI/sciai/model/ppinns/README.md#script-parameters) | ✅ | ✅ | +| General Physics | [xpinns](https://doi.org/10.4208/cicp.OA-2020-0164) | [link](https://atomgit.com/mindspore/mindscience/blob/master/SciAI/sciai/model/xpinns/README.md#script-parameters) | ✅ | ✅ | +| Hamiltonian Systems | [sympnets](https://www.sciencedirect.com/science/article/pii/S0893608020303063) | [link](https://atomgit.com/mindspore/mindscience/blob/master/SciAI/sciai/model/sympnets/README.md#script-parameters) | ✅ | ✅ | +| Fluid Dynamic | [hfm](https://www.science.org/doi/abs/10.1126/science.aaw4741) | [link](https://atomgit.com/mindspore/mindscience/blob/master/SciAI/sciai/model/hfm/README.md#script-parameters) | ✅ | ✅ | +| Fluid Dynamic | [label_free_dnn_surrogate](https://www.sciencedirect.com/science/article/pii/S004578251930622X) | [link](https://atomgit.com/mindspore/mindscience/blob/master/SciAI/sciai/model/label_free_dnn_surrogate/README.md#script-parameters) | ✅ | ✅ | +| Fluid Dynamic | [nsf_nets](https://www.sciencedirect.com/science/article/pii/S0021999120307257) | [link](https://atomgit.com/mindspore/mindscience/blob/master/SciAI/sciai/model/nsf_nets/README.md#script-parameters) | ✅ | ✅ | +| Fluid Dynamic | [*burgers_fno](https://arxiv.org/abs/2010.08895) | [link](https://atomgit.com/mindspore/mindscience/blob/master/MindFlow/applications/data_driven/burgers/fno1d/FNO1D.ipynb) | ✅ | ✅ | +| Fluid Dynamic | [*burgers_kno](https://arxiv.org/abs/2301.10022) | [link](https://atomgit.com/mindspore/mindscience/blob/master/MindFlow/applications/data_driven/burgers/kno1d/KNO1D.ipynb) | ✅ | ✅ | +| Fluid Dynamic | [*navier_stokes_fno](https://arxiv.org/abs/2010.08895) | [link](https://atomgit.com/mindspore/mindscience/blob/master/MindFlow/applications/data_driven/navier_stokes/fno2d/FNO2D.ipynb) | ✅ | ✅ | +| Fluid Dynamic | [*navier_stokes_kno](https://arxiv.org/abs/2301.10022) | [link](https://atomgit.com/mindspore/mindscience/blob/master/MindFlow/applications/data_driven/navier_stokes/kno2d/KNO2D.ipynb) | ✅ | ✅ | +| Fluid Dynamic | [*navier_stokes_3d_fno](https://arxiv.org/abs/2010.08895) | [link](https://atomgit.com/mindspore/mindscience/blob/master/MindFlow/applications/data_driven/navier_stokes/fno3d/FNO3D.ipynb) | ✅ | ✅ | +| Fluid Dynamic | [*pde_net](https://arxiv.org/abs/1710.09668) | [link](https://atomgit.com/mindspore/mindscience/blob/master/MindFlow/applications/data_mechanism_fusion/pde_net/README.md) | ✅ | ✅ | +| Fluid Dynamic | [*percnn](https://www.nature.com/articles/s42256-023-00685-7) | [link](https://atomgit.com/mindspore/mindscience/blob/master/MindFlow/applications/data_mechanism_fusion/percnn/README.md) | ✅ | ✅ | +| Elastodynamics | [pinn_elastodynamics](https://arxiv.org/abs/2006.08472) | [link](https://atomgit.com/mindspore/mindscience/blob/master/SciAI/sciai/model/pinn_elastodynamics/README.md#script-parameters) | ✅ | ✅ | +| Thermodynamics | [pinn_heattransfer](https://arxiv.org/abs/1711.10561) | [link](https://atomgit.com/mindspore/mindscience/blob/master/SciAI/sciai/model/pinn_heattransfer/README.md#script-parameters) | ✅ | ✅ | +| Meteorology | [enso](https://doi.org/10.1038/s41586-019-1559-7) | [link](https://atomgit.com/mindspore/mindscience/blob/master/SciAI/sciai/model/enso/README.md#script-parameters) | ✅ | ✅ | +| Geology | [inversion_net](https://ieeexplore.ieee.org/abstract/document/8918045/) | [link](https://atomgit.com/mindspore/mindscience/blob/master/SciAI/sciai/model/inversion_net/README.md#script-parameters) | ✅ | ✅ | +| Geology | [pinn_helmholtz](https://academic.oup.com/gji/article-abstract/228/3/1750/6409132) | [link](https://atomgit.com/mindspore/mindscience/blob/master/SciAI/sciai/model/pinn_helmholtz/README.md#script-parameters) | ✅ | ✅ | +| Oceanic Physics | [ocean_model](https://gmd.copernicus.org/articles/12/4729/2019/) | [link](https://atomgit.com/mindspore/mindscience/blob/master/SciAI/sciai/model/ocean_model/README.md#Model-Description) | | ✅ | +| Oceanic Physics | [pinns_swe](https://arxiv.org/abs/2104.00615) | [link](https://atomgit.com/mindspore/mindscience/blob/master/SciAI/sciai/model/pinns_swe/README.md#script-parameters) | ✅ | ✅ | +| Electromagnetism | [maxwell_net](https://arxiv.org/abs/2107.06164) | [link](https://atomgit.com/mindspore/mindscience/blob/master/SciAI/sciai/model/maxwell_net/README.md#script-parameters) | ✅ | ✅ | +| Electromagnetism | [*AD_FDTD_invert_f](https://www.mindspore.cn/mindelec/docs/en/r0.2/AD_FDTD.html) | [link](https://atomgit.com/mindspore/mindscience/blob/master/MindElec/examples/AD_FDTD/fdtd_forward/README.md#script-parameters) | | ✅ | +| Electromagnetism | [*AD_FDTD_microstrip_filter](https://www.mindspore.cn/mindelec/docs/en/r0.2/AD_FDTD.html) | [link](https://atomgit.com/mindspore/mindscience/blob/master/MindElec/examples/AD_FDTD/fdtd_forward/README.md#script-parameters) | | ✅ | +| Electromagnetism | [*AD_FDTD_inverse](https://www.mindspore.cn/mindelec/docs/en/r0.2/AD_FDTD.html) | [link](https://atomgit.com/mindspore/mindscience/blob/master/MindElec/examples/AD_FDTD/fdtd_inverse/README.md#script-parameters) | | ✅ | +| Electromagnetism | [*frequency_domain_maxwell](https://arxiv.org/abs/2107.06164) | [link](https://atomgit.com/mindspore/mindscience/blob/master/MindElec/examples/physics_driven/frequency_domain_maxwell/README.md#script-parameters) | ✅ | ✅ | +| Electromagnetism | [*frequency_domain_maxwell_3D_dielectric_slab](https://arxiv.org/abs/2107.06164) | [link](https://atomgit.com/mindspore/mindscience/blob/master/MindElec/examples/physics_driven/frequency_domain_maxwell_3D/dielectric_slab_3d/README.md#脚本参数) | ✅ | ✅ | +| Electromagnetism | [*frequency_domain_maxwell_3D_waveguide_cavity](https://arxiv.org/abs/2107.06164) | [link](https://atomgit.com/mindspore/mindscience/blob/master/MindElec/examples/physics_driven/frequency_domain_maxwell_3D/waveguide_cavity_3d/README.md#脚本参数) | ✅ | ✅ | +| Electromagnetism | [*meta_auto_decoder](https://arxiv.org/abs/2111.08823) | [link](https://atomgit.com/mindspore/mindscience/blob/master/MindElec/examples/physics_driven/incremental_learning/README.md#script-parameters) | ✅ | ✅ | +| Electromagnetism | [*pinn_fwi](https://agupubs.onlinelibrary.wiley.com/doi/abs/10.1029/2021JB023120) | [link](https://atomgit.com/mindspore/mindscience/blob/master/MindElec/examples/physics_driven/pinn_fwi/README.md) | ✅ | ✅ | +| Electromagnetism | [*SED_ANN](https://atomgit.com/mindspore/mindscience/tree/master/MindElec/examples/data_driven/sed_ann) | [link](https://atomgit.com/mindspore/mindscience/blob/master/MindElec/examples/data_driven/sed_ann/README_CN.md) | ✅ | ✅ | +| Electromagnetism | [*time_domain_maxwell](https://www.ijcai.org/proceedings/2022/533) | [link](https://atomgit.com/mindspore/mindscience/blob/master/MindElec/examples/physics_driven/time_domain_maxwell/README.md#script-parameters) | ✅ | ✅ | +| Electromagnetism | [*metasurface_holograms](https://www.researching.cn/articles/OJ44d3746c3db8c1e1) | [link](https://atomgit.com/mindspore/mindscience/blob/master/MindElec/examples/metasurface/metasurface_holograms/README.md#parameters) | ✅ | ✅ | +| Biology | [*MEGA-Fold](https://arxiv.org/abs/2206.12240v1) | [link (inference)](https://atomgit.com/mindspore/mindscience/blob/master/MindSPONGE/applications/model_cards/MEGAProtein.md) [link (training)](https://atomgit.com/mindspore/mindscience/blob/master/MindSPONGE/applications/model_cards/MEGAProtein.md) | ✅ | ✅ | +| Biology | [*MEGA-EvoGen](https://arxiv.org/abs/2208.09652) | [link](https://atomgit.com/mindspore/mindscience/blob/master/MindSPONGE/applications/model_cards/MEGAProtein.md) | ✅ | ✅ | +| Biology | [*MEGA-Assessment](https://atomgit.com/mindspore/mindscience/blob/master/MindSPONGE/applications/model_cards/MEGAProtein.md) | [link (inference)](https://atomgit.com/mindspore/mindscience/blob/master/MindSPONGE/applications/model_cards/MEGAProtein.md) [link (training)](https://atomgit.com/mindspore/mindscience/blob/master/MindSPONGE/applications/model_cards/MEGAProtein.md) | ✅ | ✅ | +| Biology | [*ColabDesign](https://www.biorxiv.org/content/10.1101/2021.11.10.468128.abstract) | [link](https://atomgit.com/mindspore/mindscience/blob/master/MindSPONGE/applications/model_cards/ColabDesign.md) | ✅ | ✅ | +| Biology | [*DeepFRI](https://www.nature.com/articles/s41467-021-23303-9) | [link](https://atomgit.com/mindspore/mindscience/blob/master/MindSPONGE/applications/model_cards/DeepFri.md) | ✅ | ✅ | +| Biology | [*Multimer](https://www.biorxiv.org/content/10.1101/2021.10.04.463034v1) | [link](https://atomgit.com/mindspore/mindscience/blob/master/MindSPONGE/applications/model_cards/afmultimer.md) | ✅ | ✅ | +| Biology | [*ProteinMPNN](https://www.science.org/doi/abs/10.1126/science.add2187) | [link](https://atomgit.com/mindspore/mindscience/blob/master/MindSPONGE/applications/model_cards/ProteinMPNN.MD) | ✅ | ✅ | +| Biology | [*UFold](https://doi.org/10.1093/nar/gkab1074) | [link](https://atomgit.com/mindspore/mindscience/blob/master/MindSPONGE/applications/model_cards/UFold.md) | ✅ | ✅ | +| Biology | [*esm-if1](https://proceedings.mlr.press/v162/hsu22a.html) | [link](https://atomgit.com/mindspore/mindscience/blob/master/MindSPONGE/applications/model_cards/ESM-IF1.md) | ✅ | ✅ | +| Biology | [*esm2](https://www.biorxiv.org/content/10.1101/2022.07.20.500902v1.full.pdf) | [link](https://atomgit.com/mindspore/mindscience/blob/master/MindSPONGE/applications/model_cards/ESM-2.md) | ✅ | ✅ | +| Biology | [*grover](https://proceedings.neurips.cc/paper/2020/file/94aef38441efa3380a3bed3faf1f9d5d-Paper.pdf) | [link](https://atomgit.com/mindspore/mindscience/blob/master/MindSPONGE/applications/model_cards/GROVER.MD) | ✅ | ✅ | Note: the "*" in the model names indicates that these models have already been released at an earlier time by MindSpore and MindScience. \ No newline at end of file diff --git a/docs/sciai/docs/source_zh_cn/build_model_with_sciai.md b/docs/sciai/docs/source_zh_cn/build_model_with_sciai.md index b21d2a12ad1fbce2bd19b90e49333a0565d9158c..a5c61ae3b7ef2b3e97ec0ef8f2d9ddf47938f64c 100644 --- a/docs/sciai/docs/source_zh_cn/build_model_with_sciai.md +++ b/docs/sciai/docs/source_zh_cn/build_model_with_sciai.md @@ -7,7 +7,7 @@ SciAI基础框架由若干基础模块构成，涵盖有神经网络搭建、训 如下的示例展示了使用SciAI构建神经网络模型并进行训练的流程。 > 你可以在这里下载完整的样例代码： -> +> ## 模型构建基础 @@ -19,7 +19,7 @@ $$ f(x) = {x_1}^2 + sin(x_2) $$ -该部分完整代码请参考[代码](https://atomgit.com/mindspore-lab/mindscience/blob/master/SciAI/tutorial/example_net.py)。 +该部分完整代码请参考[代码](https://atomgit.com/mindspore/mindscience/blob/master/SciAI/tutorial/example_net.py)。 ### 模型搭建 @@ -177,7 +177,7 @@ $$ f(x) = \frac{x^2}{0.2 x^5 + 0.8} $$ -该部分完整代码请参考[代码](https://atomgit.com/mindspore-lab/mindscience/blob/master/SciAI/tutorial/example_grad_net.py)。 +该部分完整代码请参考[代码](https://atomgit.com/mindspore/mindscience/blob/master/SciAI/tutorial/example_grad_net.py)。 ### 损失函数定义 diff --git a/docs/sciai/docs/source_zh_cn/installation.md b/docs/sciai/docs/source_zh_cn/installation.md index ac66ba84ddc0a6cdfad08d8cd97abe0c13830b68..38a6148fd51d9a9093c6c99a1c69b5a147d62d63 100644 --- a/docs/sciai/docs/source_zh_cn/installation.md +++ b/docs/sciai/docs/source_zh_cn/installation.md @@ -7,7 +7,7 @@ - 硬件平台为Ascend或GPU。 - 参考[MindSpore安装指南](https://www.mindspore.cn/install)，完成MindSpore的安装。 -- 其余依赖请参见[requirements.txt](https://atomgit.com/mindspore-lab/mindscience/blob/master/SciAI/requirements.txt)。 +- 其余依赖请参见[requirements.txt](https://atomgit.com/mindspore/mindscience/blob/master/SciAI/requirements.txt)。 ## 安装方式 diff --git a/docs/sciai/docs/source_zh_cn/launch_with_api.md b/docs/sciai/docs/source_zh_cn/launch_with_api.md index 04b374ca15b4a3168f692fd44fc4c3cb369c5cc5..a058b14830df8010f05d25305f13183eb3c6793d 100644 --- a/docs/sciai/docs/source_zh_cn/launch_with_api.md +++ b/docs/sciai/docs/source_zh_cn/launch_with_api.md @@ -10,7 +10,7 @@ MindSpore SciAI为用户提供了高阶API接口`AutoModel`。借助`AutoModel` 用户可以使用`AutoModel.from_pretrained`接口获取已支持的网络模型。 -这里使用Conservatice Physics-Informed Neural Networks (CPINNs) 作为教学案例。CPINNs模型相关代码请参考[链接](https://atomgit.com/mindspore-lab/mindscience/tree/master/SciAI/sciai/model/cpinns)。 +这里使用Conservatice Physics-Informed Neural Networks (CPINNs) 作为教学案例。CPINNs模型相关代码请参考[链接](https://atomgit.com/mindspore/mindscience/tree/master/SciAI/sciai/model/cpinns)。 更多关于该模型的信息，请参考[论文](https://www.sciencedirect.com/science/article/abs/pii/S0045782520302127)。 diff --git a/docs/sciai/docs/source_zh_cn/launch_with_scripts.md b/docs/sciai/docs/source_zh_cn/launch_with_scripts.md index aea9d8c561b6fb7b849d15581cbf76e77e42643f..f3337bbfcca6c5330a1b878cc25aa444cff57ca4 100644 --- a/docs/sciai/docs/source_zh_cn/launch_with_scripts.md +++ b/docs/sciai/docs/source_zh_cn/launch_with_scripts.md @@ -4,9 +4,9 @@ MindSpore SciAI中的模型为用户提供了训练与评估的脚本文件。 -通过模型的脚本文件，用户可以直接启动某个模型的训练与评估，并通过修改配置文件或是传入命令行参数的方式调整模型参数。[该目录](https://atomgit.com/mindspore-lab/mindscience/tree/master/SciAI/sciai/model)中包含了所有支持脚本启动的模型。 +通过模型的脚本文件，用户可以直接启动某个模型的训练与评估，并通过修改配置文件或是传入命令行参数的方式调整模型参数。[该目录](https://atomgit.com/mindspore/mindscience/tree/master/SciAI/sciai/model)中包含了所有支持脚本启动的模型。 -下面使用模型Conservative Physics-Informed Neural Networks(CPINNs)介绍使用脚本训练、评估模型的基本通用流程。CPINNs模型相关代码请参考[链接](https://atomgit.com/mindspore-lab/mindscience/tree/master/SciAI/sciai/model/cpinns)。 +下面使用模型Conservative Physics-Informed Neural Networks(CPINNs)介绍使用脚本训练、评估模型的基本通用流程。CPINNs模型相关代码请参考[链接](https://atomgit.com/mindspore/mindscience/tree/master/SciAI/sciai/model/cpinns)。 更多关于该模型的信息，请参考[论文](https://www.sciencedirect.com/science/article/abs/pii/S0045782520302127)。 @@ -19,7 +19,7 @@ git clone https://atomgit.com/mindspore-lab/mindscience source ./mindscience/SciAI/.env ``` -克隆完成后，用户可以按照模型[README_CN.md](https://atomgit.com/mindspore-lab/mindscience/blob/master/SciAI/sciai/model/cpinns/README_CN.md)（以模型CPINNs为例）中的`快速开始`章节，使用脚本进行训练与推理。 +克隆完成后，用户可以按照模型[README_CN.md](https://atomgit.com/mindspore/mindscience/blob/master/SciAI/sciai/model/cpinns/README_CN.md)（以模型CPINNs为例）中的`快速开始`章节，使用脚本进行训练与推理。 ```bash cd ./mindscience/SciAI/sciai/model/cpinns/ @@ -27,7 +27,7 @@ cd ./mindscience/SciAI/sciai/model/cpinns/ ## 训练、微调模型 -用户可以使用训练脚本[train.py](https://atomgit.com/mindspore-lab/mindscience/blob/master/SciAI/sciai/model/cpinns/train.py)进行网络模型训练。 +用户可以使用训练脚本[train.py](https://atomgit.com/mindspore/mindscience/blob/master/SciAI/sciai/model/cpinns/train.py)进行网络模型训练。 ```bash python ./train.py [--parameters] @@ -47,7 +47,7 @@ python ./train.py --load_ckpt true --load_ckpt_path {your_file}.ckpt [--paramete 使用可选参数`[--parameters]`可以配置模型的训练过程，包括学习率、训练周期、数据读取保存路径等。 -具体可配置的参数列表请参考[README_CN.md](https://atomgit.com/mindspore-lab/mindscience/blob/master/SciAI/sciai/model/cpinns/README_CN.md)中`脚本参数`章节。 +具体可配置的参数列表请参考[README_CN.md](https://atomgit.com/mindspore/mindscience/blob/master/SciAI/sciai/model/cpinns/README_CN.md)中`脚本参数`章节。 ## 评估模型 diff --git a/docs/sciai/docs/source_zh_cn/model_library.md b/docs/sciai/docs/source_zh_cn/model_library.md index 44ca155f07c26401a9bcee2330b7f50059a8a8c8..ce448767ebb2535d401789572c458ff288cb8c96 100644 --- a/docs/sciai/docs/source_zh_cn/model_library.md +++ b/docs/sciai/docs/source_zh_cn/model_library.md @@ -6,67 +6,67 @@ SciAI基础模型库提供了丰富的科学计算高频模型，下表中汇总 | 领域 | 模型 | MindSpore实现与网络参数 | Ascend | GPU | |-------|--------------------------------------------------------------------------------------------------------------------------|:---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------:|:------:|:---:| -| 通用物理 | [auq_pinns](https://www.sciencedirect.com/science/article/pii/S0021999119303584) | [link](https://atomgit.com/mindspore-lab/mindscience/blob/master/SciAI/sciai/model/auq_pinns/README_CN.md#脚本参数) | ✅ | ✅ | -| 通用物理 | [cpinns](https://www.sciencedirect.com/science/article/abs/pii/S0045782520302127) | [link](https://atomgit.com/mindspore-lab/mindscience/blob/master/SciAI/sciai/model/cpinns/README_CN.md#脚本参数) | ✅ | ✅ | -| 通用物理 | [deep_hpms](https://www.jmlr.org/papers/volume19/18-046/18-046.pdf) | [link](https://atomgit.com/mindspore-lab/mindscience/blob/master/SciAI/sciai/model/deep_hpms/README_CN.md#脚本参数) | ✅ | ✅ | -| 通用物理 | [deep_ritz](https://arxiv.org/abs/1710.00211) | [link](https://atomgit.com/mindspore-lab/mindscience/blob/master/SciAI/sciai/model/deep_ritz/README_CN.md#脚本参数) | ✅ | ✅ | -| 通用物理 | [deepbsde](https://www.pnas.org/doi/10.1073/pnas.1718942115) | [link](https://atomgit.com/mindspore-lab/mindscience/blob/master/SciAI/sciai/model/deepbsde/README.md#script-parameters) | | ✅ | -| 通用物理 | [deeponet](https://www.nature.com/articles/s42256-021-00302-5) | [link](https://atomgit.com/mindspore-lab/mindscience/blob/master/SciAI/sciai/model/deeponet/README_CN.md#脚本参数) | | ✅ | -| 通用物理 | [dgm](https://arxiv.org/abs/1708.07469) | [link](https://atomgit.com/mindspore-lab/mindscience/blob/master/SciAI/sciai/model/dgm/README_CN.md#脚本参数) | ✅ | ✅ | -| 通用物理 | [fbsnns](https://arxiv.org/abs/1804.07010) | [link](https://atomgit.com/mindspore-lab/mindscience/blob/master/SciAI/sciai/model/fbsnns/README_CN.md#脚本参数) | ✅ | ✅ | -| 通用物理 | [fpinns](https://arxiv.org/abs/1811.08967) | [link](https://atomgit.com/mindspore-lab/mindscience/blob/master/SciAI/sciai/model/fpinns/README_CN.md#脚本参数) | ✅ | ✅ | -| 通用物理 | [gradient_pathologies_pinns](https://arxiv.org/abs/2001.04536) | [link](https://atomgit.com/mindspore-lab/mindscience/blob/master/SciAI/sciai/model/gradient_pathologies_pinns/README_CN.md#脚本参数) | ✅ | ✅ | -| 通用物理 | [hp_vpinns](https://arxiv.org/abs/2003.05385) | [link](https://atomgit.com/mindspore-lab/mindscience/blob/master/SciAI/sciai/model/hp_vpinns/README_CN.md#脚本参数) | ✅ | ✅ | -| 通用物理 | [laaf](https://doi.org/10.1016/j.jcp.2019.109136) | [link](https://atomgit.com/mindspore-lab/mindscience/blob/master/SciAI/sciai/model/laaf/README_CN.md#脚本参数) | ✅ | ✅ | -| 通用物理 | [mgnet](https://link.springer.com/article/10.1007/s11425-019-9547-2) | [link](https://atomgit.com/mindspore-lab/mindscience/blob/master/SciAI/sciai/model/mgnet/README_CN.md#脚本参数) | ✅ | ✅ | -| 通用物理 | [multiscale_pinns](https://www.sciencedirect.com/science/article/abs/pii/S0045782521002759) | [link](https://atomgit.com/mindspore-lab/mindscience/blob/master/SciAI/sciai/model/multiscale_pinns/README_CN.md#脚本参数) | ✅ | ✅ | -| 通用物理 | [pfnn](https://www.sciencedirect.com/science/article/abs/pii/S0021999120308597) | [link](https://atomgit.com/mindspore-lab/mindscience/blob/master/SciAI/sciai/model/pfnn/README_CN.md#脚本说明) | | ✅ | -| 通用物理 | [phygeonet](https://www.sciencedirect.com/science/article/abs/pii/S0021999120308536) | [link](https://atomgit.com/mindspore-lab/mindscience/blob/master/SciAI/sciai/model/phygeonet/README_CN.md#脚本参数) | ✅ | ✅ | -| 通用物理 | [pi_deeponet](https://www.sciencedirect.com/science/article/abs/pii/S0021999122009184) | [link](https://atomgit.com/mindspore-lab/mindscience/blob/master/SciAI/sciai/model/pi_deeponet/README_CN.md#脚本参数) | | ✅ | -| 通用物理 | [pinns](https://www.sciencedirect.com/science/article/abs/pii/S0021999118307125) | [link](https://atomgit.com/mindspore-lab/mindscience/blob/master/SciAI/sciai/model/pinns/README_CN.md#脚本参数) | | ✅ | -| 通用物理 | [pinns_ntk](https://www.sciencedirect.com/science/article/pii/S002199912100663X) | [link](https://atomgit.com/mindspore-lab/mindscience/blob/master/SciAI/sciai/model/pinns_ntk/README_CN.md#脚本参数) | ✅ | ✅ | -| 通用物理 | [ppinns](https://www.sciencedirect.com/science/article/abs/pii/S0045782520304357) | [link](https://atomgit.com/mindspore-lab/mindscience/blob/master/SciAI/sciai/model/ppinns/README_CN.md#脚本参数) | ✅ | ✅ | -| 通用物理 | [xpinns](https://doi.org/10.4208/cicp.OA-2020-0164) | [link](https://atomgit.com/mindspore-lab/mindscience/blob/master/SciAI/sciai/model/xpinns/README_CN.md#脚本参数) | ✅ | ✅ | -| 哈密顿系统 | [sympnets](https://www.sciencedirect.com/science/article/pii/S0893608020303063) | [link](https://atomgit.com/mindspore-lab/mindscience/blob/master/SciAI/sciai/model/sympnets/README_CN.md#脚本参数) | ✅ | ✅ | -| 流体力学 | [hfm](https://www.science.org/doi/abs/10.1126/science.aaw4741) | [link](https://atomgit.com/mindspore-lab/mindscience/blob/master/SciAI/sciai/model/hfm/README_CN.md#脚本参数) | ✅ | ✅ | -| 流体力学 | [label_free_dnn_surrogate](https://www.sciencedirect.com/science/article/pii/S004578251930622X) | [link](https://atomgit.com/mindspore-lab/mindscience/blob/master/SciAI/sciai/model/label_free_dnn_surrogate/README_CN.md#脚本参数) | ✅ | ✅ | -| 流体力学 | [nsf_nets](https://www.sciencedirect.com/science/article/pii/S0021999120307257) | [link](https://atomgit.com/mindspore-lab/mindscience/blob/master/SciAI/sciai/model/nsf_nets/README_CN.md#脚本参数) | ✅ | ✅ | -| 流体力学 | [*burgers_fno](https://arxiv.org/abs/2010.08895) | [link](https://atomgit.com/mindspore-lab/mindscience/blob/master/MindFlow/applications/data_driven/burgers/fno1d/FNO1D_CN.ipynb) | ✅ | ✅ | -| 流体力学 | [*burgers_kno](https://arxiv.org/abs/2301.10022) | [link](https://atomgit.com/mindspore-lab/mindscience/blob/master/MindFlow/applications/data_driven/burgers/kno1d/KNO1D_CN.ipynb) | ✅ | ✅ | -| 流体力学 | [*navier_stokes_fno](https://arxiv.org/abs/2010.08895) | [link](https://atomgit.com/mindspore-lab/mindscience/blob/master/MindFlow/applications/data_driven/navier_stokes/fno2d/FNO2D_CN.ipynb) | ✅ | ✅ | -| 流体力学 | [*navier_stokes_kno](https://arxiv.org/abs/2301.10022) | [link](https://atomgit.com/mindspore-lab/mindscience/blob/master/MindFlow/applications/data_driven/navier_stokes/kno2d/KNO2D_CN.ipynb) | ✅ | ✅ | -| 流体力学 | [*navier_stokes_3d_fno](https://arxiv.org/abs/2010.08895) | [link](https://atomgit.com/mindspore-lab/mindscience/blob/master/MindFlow/applications/data_driven/navier_stokes/fno3d/FNO3D_CN.ipynb) | ✅ | ✅ | -| 流体力学 | [*pde_net](https://arxiv.org/abs/1710.09668) | [link](https://atomgit.com/mindspore-lab/mindscience/blob/master/MindFlow/applications/data_mechanism_fusion/pde_net/README_CN.md) | ✅ | ✅ | -| 流体力学 | [*percnn](https://www.nature.com/articles/s42256-023-00685-7) | [link](https://atomgit.com/mindspore-lab/mindscience/blob/master/MindFlow/applications/data_mechanism_fusion/percnn/README_CN.md) | ✅ | ✅ | -| 弹性动力学 | [pinn_elastodynamics](https://arxiv.org/abs/2006.08472) | [link](https://atomgit.com/mindspore-lab/mindscience/blob/master/SciAI/sciai/model/pinn_elastodynamics/README_CN.md#脚本参数) | ✅ | ✅ | -| 热力学 | [pinn_heattransfer](https://arxiv.org/abs/1711.10561) | [link](https://atomgit.com/mindspore-lab/mindscience/blob/master/SciAI/sciai/model/pinn_heattransfer/README_CN.md#脚本参数) | ✅ | ✅ | -| 气象学 | [enso](https://doi.org/10.1038/s41586-019-1559-7) | [link](https://atomgit.com/mindspore-lab/mindscience/blob/master/SciAI/sciai/model/enso/README_CN.md#脚本参数) | ✅ | ✅ | -| 地质学 | [inversion_net](https://ieeexplore.ieee.org/abstract/document/8918045/) | [link](https://atomgit.com/mindspore-lab/mindscience/blob/master/SciAI/sciai/model/inversion_net/README_CN.md#脚本参数) | ✅ | ✅ | -| 地质学 | [pinn_helmholtz](https://academic.oup.com/gji/article-abstract/228/3/1750/6409132) | [link](https://atomgit.com/mindspore-lab/mindscience/blob/master/SciAI/sciai/model/pinn_helmholtz/README_CN.md#脚本参数) | ✅ | ✅ | -| 海洋物理 | [ocean_model](https://gmd.copernicus.org/articles/12/4729/2019/) | [link](https://atomgit.com/mindspore-lab/mindscience/blob/master/SciAI/sciai/model/ocean_model/README_CN.md#模型说明) | | ✅ | -| 海洋物理 | [pinns_swe](https://arxiv.org/abs/2104.00615) | [link](https://atomgit.com/mindspore-lab/mindscience/blob/master/SciAI/sciai/model/pinns_swe/README_CN.md#脚本参数) | ✅ | ✅ | -| 电磁学 | [maxwell_net](https://arxiv.org/abs/2107.06164) | [link](https://atomgit.com/mindspore-lab/mindscience/blob/master/SciAI/sciai/model/maxwell_net/README_CN.md#脚本参数) | ✅ | ✅ | -| 电磁学 | [*AD_FDTD_invert_f](https://www.mindspore.cn/mindelec/docs/zh-CN/r0.2/AD_FDTD.html) | [link](https://atomgit.com/mindspore-lab/mindscience/blob/master/MindElec/examples/AD_FDTD/fdtd_forward/README_CN.md#脚本参数) | | ✅ | -| 电磁学 | [*AD_FDTD_microstrip_filter](https://www.mindspore.cn/mindelec/docs/zh-CN/r0.2/AD_FDTD.html) | [link](https://atomgit.com/mindspore-lab/mindscience/blob/master/MindElec/examples/AD_FDTD/fdtd_forward/README_CN.md#脚本参数) | | ✅ | -| 电磁学 | [*AD_FDTD_inverse](https://www.mindspore.cn/mindelec/docs/zh-CN/r0.2/AD_FDTD.html) | [link](https://atomgit.com/mindspore-lab/mindscience/blob/master/MindElec/examples/AD_FDTD/fdtd_inverse/README_CN.md#脚本参数) | | ✅ | -| 电磁学 | [*frequency_domain_maxwell](https://arxiv.org/abs/2107.06164) | [link](https://atomgit.com/mindspore-lab/mindscience/blob/master/MindElec/examples/physics_driven/frequency_domain_maxwell/README_CN.md#脚本参数) | ✅ | ✅ | -| 电磁学 | [*frequency_domain_maxwell_3D_dielectric_slab](https://arxiv.org/abs/2107.06164) | [link](https://atomgit.com/mindspore-lab/mindscience/blob/master/MindElec/examples/physics_driven/frequency_domain_maxwell_3D/dielectric_slab_3d/README.md#脚本参数) | ✅ | ✅ | -| 电磁学 | [*frequency_domain_maxwell_3D_waveguide_cavity](https://arxiv.org/abs/2107.06164) | [link](https://atomgit.com/mindspore-lab/mindscience/blob/master/MindElec/examples/physics_driven/frequency_domain_maxwell_3D/waveguide_cavity_3d/README.md#脚本参数) | ✅ | ✅ | -| 电磁学 | [*meta_auto_decoder](https://arxiv.org/abs/2111.08823) | [link](https://atomgit.com/mindspore-lab/mindscience/blob/master/MindElec/examples/physics_driven/incremental_learning/README_CN.md#脚本参数) | ✅ | ✅ | -| 电磁学 | [*pinn_fwi](https://agupubs.onlinelibrary.wiley.com/doi/abs/10.1029/2021JB023120) | [link](https://atomgit.com/mindspore-lab/mindscience/blob/master/MindElec/examples/physics_driven/pinn_fwi/README.md#脚本参数) | ✅ | ✅ | -| 电磁学 | [*SED_ANN](https://atomgit.com/mindspore-lab/mindscience/tree/master/MindElec/examples/data_driven/sed_ann) | [link](https://atomgit.com/mindspore-lab/mindscience/blob/master/MindElec/examples/data_driven/sed_ann/README_CN.md#脚本参数) | ✅ | ✅ | -| 电磁学 | [*time_domain_maxwell](https://www.ijcai.org/proceedings/2022/533) | [link](https://atomgit.com/mindspore-lab/mindscience/blob/master/MindElec/examples/physics_driven/time_domain_maxwell/README_CN.md#脚本参数) | ✅ | ✅ | -| 电磁学 | [*metasurface_holograms](https://www.researching.cn/articles/OJ44d3746c3db8c1e1) | [link](https://atomgit.com/mindspore-lab/mindscience/blob/master/MindElec/examples/metasurface/metasurface_holograms/README_CN.md#脚本参数) | ✅ | ✅ | -| 生物 | [*MEGA-Fold](https://arxiv.org/abs/2206.12240v1) | [link (推理)](https://atomgit.com/mindspore-lab/mindscience/blob/master/MindSPONGE/applications/model_cards/MEGAProtein.md) [link (训练)](https://atomgit.com/mindspore-lab/mindscience/blob/master/MindSPONGE/applications/model_cards/MEGAProtein.md) | ✅ | ✅ | -| 生物 | [*MEGA-EvoGen](https://arxiv.org/abs/2208.09652) | [link](https://atomgit.com/mindspore-lab/mindscience/blob/master/MindSPONGE/applications/model_cards/MEGAProtein.md) | ✅ | ✅ | -| 生物 | [*MEGA-Assessment](https://atomgit.com/mindspore-lab/mindscience/blob/master/MindSPONGE/applications/model_cards/MEGAProtein.md) | [link (推理)](https://atomgit.com/mindspore-lab/mindscience/blob/master/MindSPONGE/applications/model_cards/MEGAProtein.md) [link (训练)](https://atomgit.com/mindspore-lab/mindscience/blob/master/MindSPONGE/applications/model_cards/MEGAProtein.md) | ✅ | ✅ | -| 生物 | [*ColabDesign](https://www.biorxiv.org/content/10.1101/2021.11.10.468128.abstract) | [link](https://atomgit.com/mindspore-lab/mindscience/blob/master/MindSPONGE/applications/model_cards/ColabDesign.md) | ✅ | ✅ | -| 生物 | [*DeepFRI](https://www.nature.com/articles/s41467-021-23303-9) | [link](https://atomgit.com/mindspore-lab/mindscience/blob/master/MindSPONGE/applications/model_cards/DeepFri.md) | ✅ | ✅ | -| 生物 | [*Multimer](https://www.biorxiv.org/content/10.1101/2021.10.04.463034v1) | [link](https://atomgit.com/mindspore-lab/mindscience/blob/master/MindSPONGE/applications/model_cards/afmultimer.md) | ✅ | ✅ | -| 生物 | [*ProteinMPNN](https://www.science.org/doi/abs/10.1126/science.add2187) | [link](https://atomgit.com/mindspore-lab/mindscience/blob/master/MindSPONGE/applications/model_cards/ProteinMPNN.MD) | ✅ | ✅ | -| 生物 | [*UFold](https://doi.org/10.1093/nar/gkab1074) | [link](https://atomgit.com/mindspore-lab/mindscience/blob/master/MindSPONGE/applications/model_cards/UFold.md) | ✅ | ✅ | -| 生物 | [*esm-if1](https://proceedings.mlr.press/v162/hsu22a.html) | [link](https://atomgit.com/mindspore-lab/mindscience/blob/master/MindSPONGE/applications/model_cards/ESM-IF1.md) | ✅ | ✅ | -| 生物 | [*esm2](https://www.biorxiv.org/content/10.1101/2022.07.20.500902v1.full.pdf) | [link](https://atomgit.com/mindspore-lab/mindscience/blob/master/MindSPONGE/applications/model_cards/ESM-2.md) | ✅ | ✅ | -| 生物 | [*grover](https://proceedings.neurips.cc/paper/2020/file/94aef38441efa3380a3bed3faf1f9d5d-Paper.pdf) | [link](https://atomgit.com/mindspore-lab/mindscience/blob/master/MindSPONGE/applications/model_cards/GROVER.MD) | ✅ | ✅ | +| 通用物理 | [auq_pinns](https://www.sciencedirect.com/science/article/pii/S0021999119303584) | [link](https://atomgit.com/mindspore/mindscience/blob/master/SciAI/sciai/model/auq_pinns/README_CN.md#脚本参数) | ✅ | ✅ | +| 通用物理 | [cpinns](https://www.sciencedirect.com/science/article/abs/pii/S0045782520302127) | [link](https://atomgit.com/mindspore/mindscience/blob/master/SciAI/sciai/model/cpinns/README_CN.md#脚本参数) | ✅ | ✅ | +| 通用物理 | [deep_hpms](https://www.jmlr.org/papers/volume19/18-046/18-046.pdf) | [link](https://atomgit.com/mindspore/mindscience/blob/master/SciAI/sciai/model/deep_hpms/README_CN.md#脚本参数) | ✅ | ✅ | +| 通用物理 | [deep_ritz](https://arxiv.org/abs/1710.00211) | [link](https://atomgit.com/mindspore/mindscience/blob/master/SciAI/sciai/model/deep_ritz/README_CN.md#脚本参数) | ✅ | ✅ | +| 通用物理 | [deepbsde](https://www.pnas.org/doi/10.1073/pnas.1718942115) | [link](https://atomgit.com/mindspore/mindscience/blob/master/SciAI/sciai/model/deepbsde/README.md#script-parameters) | | ✅ | +| 通用物理 | [deeponet](https://www.nature.com/articles/s42256-021-00302-5) | [link](https://atomgit.com/mindspore/mindscience/blob/master/SciAI/sciai/model/deeponet/README_CN.md#脚本参数) | | ✅ | +| 通用物理 | [dgm](https://arxiv.org/abs/1708.07469) | [link](https://atomgit.com/mindspore/mindscience/blob/master/SciAI/sciai/model/dgm/README_CN.md#脚本参数) | ✅ | ✅ | +| 通用物理 | [fbsnns](https://arxiv.org/abs/1804.07010) | [link](https://atomgit.com/mindspore/mindscience/blob/master/SciAI/sciai/model/fbsnns/README_CN.md#脚本参数) | ✅ | ✅ | +| 通用物理 | [fpinns](https://arxiv.org/abs/1811.08967) | [link](https://atomgit.com/mindspore/mindscience/blob/master/SciAI/sciai/model/fpinns/README_CN.md#脚本参数) | ✅ | ✅ | +| 通用物理 | [gradient_pathologies_pinns](https://arxiv.org/abs/2001.04536) | [link](https://atomgit.com/mindspore/mindscience/blob/master/SciAI/sciai/model/gradient_pathologies_pinns/README_CN.md#脚本参数) | ✅ | ✅ | +| 通用物理 | [hp_vpinns](https://arxiv.org/abs/2003.05385) | [link](https://atomgit.com/mindspore/mindscience/blob/master/SciAI/sciai/model/hp_vpinns/README_CN.md#脚本参数) | ✅ | ✅ | +| 通用物理 | [laaf](https://doi.org/10.1016/j.jcp.2019.109136) | [link](https://atomgit.com/mindspore/mindscience/blob/master/SciAI/sciai/model/laaf/README_CN.md#脚本参数) | ✅ | ✅ | +| 通用物理 | [mgnet](https://link.springer.com/article/10.1007/s11425-019-9547-2) | [link](https://atomgit.com/mindspore/mindscience/blob/master/SciAI/sciai/model/mgnet/README_CN.md#脚本参数) | ✅ | ✅ | +| 通用物理 | [multiscale_pinns](https://www.sciencedirect.com/science/article/abs/pii/S0045782521002759) | [link](https://atomgit.com/mindspore/mindscience/blob/master/SciAI/sciai/model/multiscale_pinns/README_CN.md#脚本参数) | ✅ | ✅ | +| 通用物理 | [pfnn](https://www.sciencedirect.com/science/article/abs/pii/S0021999120308597) | [link](https://atomgit.com/mindspore/mindscience/blob/master/SciAI/sciai/model/pfnn/README_CN.md#脚本说明) | | ✅ | +| 通用物理 | [phygeonet](https://www.sciencedirect.com/science/article/abs/pii/S0021999120308536) | [link](https://atomgit.com/mindspore/mindscience/blob/master/SciAI/sciai/model/phygeonet/README_CN.md#脚本参数) | ✅ | ✅ | +| 通用物理 | [pi_deeponet](https://www.sciencedirect.com/science/article/abs/pii/S0021999122009184) | [link](https://atomgit.com/mindspore/mindscience/blob/master/SciAI/sciai/model/pi_deeponet/README_CN.md#脚本参数) | | ✅ | +| 通用物理 | [pinns](https://www.sciencedirect.com/science/article/abs/pii/S0021999118307125) | [link](https://atomgit.com/mindspore/mindscience/blob/master/SciAI/sciai/model/pinns/README_CN.md#脚本参数) | | ✅ | +| 通用物理 | [pinns_ntk](https://www.sciencedirect.com/science/article/pii/S002199912100663X) | [link](https://atomgit.com/mindspore/mindscience/blob/master/SciAI/sciai/model/pinns_ntk/README_CN.md#脚本参数) | ✅ | ✅ | +| 通用物理 | [ppinns](https://www.sciencedirect.com/science/article/abs/pii/S0045782520304357) | [link](https://atomgit.com/mindspore/mindscience/blob/master/SciAI/sciai/model/ppinns/README_CN.md#脚本参数) | ✅ | ✅ | +| 通用物理 | [xpinns](https://doi.org/10.4208/cicp.OA-2020-0164) | [link](https://atomgit.com/mindspore/mindscience/blob/master/SciAI/sciai/model/xpinns/README_CN.md#脚本参数) | ✅ | ✅ | +| 哈密顿系统 | [sympnets](https://www.sciencedirect.com/science/article/pii/S0893608020303063) | [link](https://atomgit.com/mindspore/mindscience/blob/master/SciAI/sciai/model/sympnets/README_CN.md#脚本参数) | ✅ | ✅ | +| 流体力学 | [hfm](https://www.science.org/doi/abs/10.1126/science.aaw4741) | [link](https://atomgit.com/mindspore/mindscience/blob/master/SciAI/sciai/model/hfm/README_CN.md#脚本参数) | ✅ | ✅ | +| 流体力学 | [label_free_dnn_surrogate](https://www.sciencedirect.com/science/article/pii/S004578251930622X) | [link](https://atomgit.com/mindspore/mindscience/blob/master/SciAI/sciai/model/label_free_dnn_surrogate/README_CN.md#脚本参数) | ✅ | ✅ | +| 流体力学 | [nsf_nets](https://www.sciencedirect.com/science/article/pii/S0021999120307257) | [link](https://atomgit.com/mindspore/mindscience/blob/master/SciAI/sciai/model/nsf_nets/README_CN.md#脚本参数) | ✅ | ✅ | +| 流体力学 | [*burgers_fno](https://arxiv.org/abs/2010.08895) | [link](https://atomgit.com/mindspore/mindscience/blob/master/MindFlow/applications/data_driven/burgers/fno1d/FNO1D_CN.ipynb) | ✅ | ✅ | +| 流体力学 | [*burgers_kno](https://arxiv.org/abs/2301.10022) | [link](https://atomgit.com/mindspore/mindscience/blob/master/MindFlow/applications/data_driven/burgers/kno1d/KNO1D_CN.ipynb) | ✅ | ✅ | +| 流体力学 | [*navier_stokes_fno](https://arxiv.org/abs/2010.08895) | [link](https://atomgit.com/mindspore/mindscience/blob/master/MindFlow/applications/data_driven/navier_stokes/fno2d/FNO2D_CN.ipynb) | ✅ | ✅ | +| 流体力学 | [*navier_stokes_kno](https://arxiv.org/abs/2301.10022) | [link](https://atomgit.com/mindspore/mindscience/blob/master/MindFlow/applications/data_driven/navier_stokes/kno2d/KNO2D_CN.ipynb) | ✅ | ✅ | +| 流体力学 | [*navier_stokes_3d_fno](https://arxiv.org/abs/2010.08895) | [link](https://atomgit.com/mindspore/mindscience/blob/master/MindFlow/applications/data_driven/navier_stokes/fno3d/FNO3D_CN.ipynb) | ✅ | ✅ | +| 流体力学 | [*pde_net](https://arxiv.org/abs/1710.09668) | [link](https://atomgit.com/mindspore/mindscience/blob/master/MindFlow/applications/data_mechanism_fusion/pde_net/README_CN.md) | ✅ | ✅ | +| 流体力学 | [*percnn](https://www.nature.com/articles/s42256-023-00685-7) | [link](https://atomgit.com/mindspore/mindscience/blob/master/MindFlow/applications/data_mechanism_fusion/percnn/README_CN.md) | ✅ | ✅ | +| 弹性动力学 | [pinn_elastodynamics](https://arxiv.org/abs/2006.08472) | [link](https://atomgit.com/mindspore/mindscience/blob/master/SciAI/sciai/model/pinn_elastodynamics/README_CN.md#脚本参数) | ✅ | ✅ | +| 热力学 | [pinn_heattransfer](https://arxiv.org/abs/1711.10561) | [link](https://atomgit.com/mindspore/mindscience/blob/master/SciAI/sciai/model/pinn_heattransfer/README_CN.md#脚本参数) | ✅ | ✅ | +| 气象学 | [enso](https://doi.org/10.1038/s41586-019-1559-7) | [link](https://atomgit.com/mindspore/mindscience/blob/master/SciAI/sciai/model/enso/README_CN.md#脚本参数) | ✅ | ✅ | +| 地质学 | [inversion_net](https://ieeexplore.ieee.org/abstract/document/8918045/) | [link](https://atomgit.com/mindspore/mindscience/blob/master/SciAI/sciai/model/inversion_net/README_CN.md#脚本参数) | ✅ | ✅ | +| 地质学 | [pinn_helmholtz](https://academic.oup.com/gji/article-abstract/228/3/1750/6409132) | [link](https://atomgit.com/mindspore/mindscience/blob/master/SciAI/sciai/model/pinn_helmholtz/README_CN.md#脚本参数) | ✅ | ✅ | +| 海洋物理 | [ocean_model](https://gmd.copernicus.org/articles/12/4729/2019/) | [link](https://atomgit.com/mindspore/mindscience/blob/master/SciAI/sciai/model/ocean_model/README_CN.md#模型说明) | | ✅ | +| 海洋物理 | [pinns_swe](https://arxiv.org/abs/2104.00615) | [link](https://atomgit.com/mindspore/mindscience/blob/master/SciAI/sciai/model/pinns_swe/README_CN.md#脚本参数) | ✅ | ✅ | +| 电磁学 | [maxwell_net](https://arxiv.org/abs/2107.06164) | [link](https://atomgit.com/mindspore/mindscience/blob/master/SciAI/sciai/model/maxwell_net/README_CN.md#脚本参数) | ✅ | ✅ | +| 电磁学 | [*AD_FDTD_invert_f](https://www.mindspore.cn/mindelec/docs/zh-CN/r0.2/AD_FDTD.html) | [link](https://atomgit.com/mindspore/mindscience/blob/master/MindElec/examples/AD_FDTD/fdtd_forward/README_CN.md#脚本参数) | | ✅ | +| 电磁学 | [*AD_FDTD_microstrip_filter](https://www.mindspore.cn/mindelec/docs/zh-CN/r0.2/AD_FDTD.html) | [link](https://atomgit.com/mindspore/mindscience/blob/master/MindElec/examples/AD_FDTD/fdtd_forward/README_CN.md#脚本参数) | | ✅ | +| 电磁学 | [*AD_FDTD_inverse](https://www.mindspore.cn/mindelec/docs/zh-CN/r0.2/AD_FDTD.html) | [link](https://atomgit.com/mindspore/mindscience/blob/master/MindElec/examples/AD_FDTD/fdtd_inverse/README_CN.md#脚本参数) | | ✅ | +| 电磁学 | [*frequency_domain_maxwell](https://arxiv.org/abs/2107.06164) | [link](https://atomgit.com/mindspore/mindscience/blob/master/MindElec/examples/physics_driven/frequency_domain_maxwell/README_CN.md#脚本参数) | ✅ | ✅ | +| 电磁学 | [*frequency_domain_maxwell_3D_dielectric_slab](https://arxiv.org/abs/2107.06164) | [link](https://atomgit.com/mindspore/mindscience/blob/master/MindElec/examples/physics_driven/frequency_domain_maxwell_3D/dielectric_slab_3d/README.md#脚本参数) | ✅ | ✅ | +| 电磁学 | [*frequency_domain_maxwell_3D_waveguide_cavity](https://arxiv.org/abs/2107.06164) | [link](https://atomgit.com/mindspore/mindscience/blob/master/MindElec/examples/physics_driven/frequency_domain_maxwell_3D/waveguide_cavity_3d/README.md#脚本参数) | ✅ | ✅ | +| 电磁学 | [*meta_auto_decoder](https://arxiv.org/abs/2111.08823) | [link](https://atomgit.com/mindspore/mindscience/blob/master/MindElec/examples/physics_driven/incremental_learning/README_CN.md#脚本参数) | ✅ | ✅ | +| 电磁学 | [*pinn_fwi](https://agupubs.onlinelibrary.wiley.com/doi/abs/10.1029/2021JB023120) | [link](https://atomgit.com/mindspore/mindscience/blob/master/MindElec/examples/physics_driven/pinn_fwi/README.md#脚本参数) | ✅ | ✅ | +| 电磁学 | [*SED_ANN](https://atomgit.com/mindspore/mindscience/tree/master/MindElec/examples/data_driven/sed_ann) | [link](https://atomgit.com/mindspore/mindscience/blob/master/MindElec/examples/data_driven/sed_ann/README_CN.md#脚本参数) | ✅ | ✅ | +| 电磁学 | [*time_domain_maxwell](https://www.ijcai.org/proceedings/2022/533) | [link](https://atomgit.com/mindspore/mindscience/blob/master/MindElec/examples/physics_driven/time_domain_maxwell/README_CN.md#脚本参数) | ✅ | ✅ | +| 电磁学 | [*metasurface_holograms](https://www.researching.cn/articles/OJ44d3746c3db8c1e1) | [link](https://atomgit.com/mindspore/mindscience/blob/master/MindElec/examples/metasurface/metasurface_holograms/README_CN.md#脚本参数) | ✅ | ✅ | +| 生物 | [*MEGA-Fold](https://arxiv.org/abs/2206.12240v1) | [link (推理)](https://atomgit.com/mindspore/mindscience/blob/master/MindSPONGE/applications/model_cards/MEGAProtein.md) [link (训练)](https://atomgit.com/mindspore/mindscience/blob/master/MindSPONGE/applications/model_cards/MEGAProtein.md) | ✅ | ✅ | +| 生物 | [*MEGA-EvoGen](https://arxiv.org/abs/2208.09652) | [link](https://atomgit.com/mindspore/mindscience/blob/master/MindSPONGE/applications/model_cards/MEGAProtein.md) | ✅ | ✅ | +| 生物 | [*MEGA-Assessment](https://atomgit.com/mindspore/mindscience/blob/master/MindSPONGE/applications/model_cards/MEGAProtein.md) | [link (推理)](https://atomgit.com/mindspore/mindscience/blob/master/MindSPONGE/applications/model_cards/MEGAProtein.md) [link (训练)](https://atomgit.com/mindspore/mindscience/blob/master/MindSPONGE/applications/model_cards/MEGAProtein.md) | ✅ | ✅ | +| 生物 | [*ColabDesign](https://www.biorxiv.org/content/10.1101/2021.11.10.468128.abstract) | [link](https://atomgit.com/mindspore/mindscience/blob/master/MindSPONGE/applications/model_cards/ColabDesign.md) | ✅ | ✅ | +| 生物 | [*DeepFRI](https://www.nature.com/articles/s41467-021-23303-9) | [link](https://atomgit.com/mindspore/mindscience/blob/master/MindSPONGE/applications/model_cards/DeepFri.md) | ✅ | ✅ | +| 生物 | [*Multimer](https://www.biorxiv.org/content/10.1101/2021.10.04.463034v1) | [link](https://atomgit.com/mindspore/mindscience/blob/master/MindSPONGE/applications/model_cards/afmultimer.md) | ✅ | ✅ | +| 生物 | [*ProteinMPNN](https://www.science.org/doi/abs/10.1126/science.add2187) | [link](https://atomgit.com/mindspore/mindscience/blob/master/MindSPONGE/applications/model_cards/ProteinMPNN.MD) | ✅ | ✅ | +| 生物 | [*UFold](https://doi.org/10.1093/nar/gkab1074) | [link](https://atomgit.com/mindspore/mindscience/blob/master/MindSPONGE/applications/model_cards/UFold.md) | ✅ | ✅ | +| 生物 | [*esm-if1](https://proceedings.mlr.press/v162/hsu22a.html) | [link](https://atomgit.com/mindspore/mindscience/blob/master/MindSPONGE/applications/model_cards/ESM-IF1.md) | ✅ | ✅ | +| 生物 | [*esm2](https://www.biorxiv.org/content/10.1101/2022.07.20.500902v1.full.pdf) | [link](https://atomgit.com/mindspore/mindscience/blob/master/MindSPONGE/applications/model_cards/ESM-2.md) | ✅ | ✅ | +| 生物 | [*grover](https://proceedings.neurips.cc/paper/2020/file/94aef38441efa3380a3bed3faf1f9d5d-Paper.pdf) | [link](https://atomgit.com/mindspore/mindscience/blob/master/MindSPONGE/applications/model_cards/GROVER.MD) | ✅ | ✅ | 注： 带有“*”的网络模型为MindSpore与MindScience先前已发布网络。 \ No newline at end of file