diff --git a/docs/lite/api/source_zh_cn/api_c/tensor_c.md b/docs/lite/api/source_zh_cn/api_c/tensor_c.md index 70529e13dc558de161603a150781e058fbd62ed7..d20f4a50d54b0d34dd75433d80987b8c7691f8ed 100644 --- a/docs/lite/api/source_zh_cn/api_c/tensor_c.md +++ b/docs/lite/api/source_zh_cn/api_c/tensor_c.md @@ -123,7 +123,7 @@ void MSTensorSetDataType(MSTensorHandle tensor, MSDataType type) MSDataType MSTensorGetDataType(const MSTensorHandle tensor) ``` -获取MSTensor的数据类型，具体数据类型见[MSDataType](https://www.mindspore.cn/lite/api/zh-CN/master/api_c/data_type_c.html#MSDataType)。 +获取MSTensor的数据类型，具体数据类型见[MSDataType](https://www.mindspore.cn/lite/api/zh-CN/master/api_c/data_type_c.html#msdatatype)。 - 参数 - `tensor`: 指向MSTensor的指针。 diff --git a/docs/mindelec/docs/source_en/incremental_learning.md b/docs/mindelec/docs/source_en/incremental_learning.md index 2093e833a0474cf4069e1f9b82967e6d31ed4e7d..7475100804086770fe0e9b0b344bb60e0b09ca7c 100644 --- a/docs/mindelec/docs/source_en/incremental_learning.md +++ b/docs/mindelec/docs/source_en/incremental_learning.md @@ -13,7 +13,7 @@ This tutorial focuses on how to use Physics-Informed Auto-Decoder (PIAD) based o ## Problem Description -This tutorial deals with the generalization of the medium parameters for the point source Maxwell's equations. For the specific form of the governing equation, the domain and the configuration of the excitation source, please refer to the [tutorial of the point source Maxwell problem](https://www.mindspore.cn/mindelec/docs/en/master/mindelec/time_domain_maxwell.html). +This tutorial deals with the generalization of the medium parameters for the point source Maxwell's equations. For the specific form of the governing equation, the domain and the configuration of the excitation source, please refer to the [tutorial of the point source Maxwell problem](https://www.mindspore.cn/mindelec/docs/en/master/time_domain_maxwell.html). ## Physics-Informed Auto-Decoder diff --git a/docs/mindelec/docs/source_zh_cn/incremental_learning.md b/docs/mindelec/docs/source_zh_cn/incremental_learning.md index 61253ab3738feb4700d5832ae1fb1463ae202419..8c693bd9876d062d20b266ad2899344d7663194b 100644 --- a/docs/mindelec/docs/source_zh_cn/incremental_learning.md +++ b/docs/mindelec/docs/source_zh_cn/incremental_learning.md @@ -13,7 +13,7 @@ ## 问题描述 -本案例处理点源麦克斯韦方程的介质参数泛化求解问题。控制方程的具体形式以及求解域和激励源配置可以参考[点源问题的求解教程](https://www.mindspore.cn/mindelec/docs/zh-CN/master/mindelec/time_domain_maxwell.html)。 +本案例处理点源麦克斯韦方程的介质参数泛化求解问题。控制方程的具体形式以及求解域和激励源配置可以参考[点源问题的求解教程](https://www.mindspore.cn/mindelec/docs/zh-CN/master/time_domain_maxwell.html)。 ## 基于物理信息的自解码器 diff --git a/docs/mindsponge/docs/source_en/cybertron.md b/docs/mindsponge/docs/source_en/cybertron.md index bcae3feaaf0530897c8d07073d287a501e5d605a..cb4b4df4eaa10e181083c1814004e5cfb120aa78 100644 --- a/docs/mindsponge/docs/source_en/cybertron.md +++ b/docs/mindsponge/docs/source_en/cybertron.md @@ -24,7 +24,7 @@ The three GNN molecular models can be directly called from Cybertron. ## Install -Please refer to [MindSPONGE Installation Tutorial](https://www.mindspore.cn/mindsponge/docs/en/master/mindsponge/intro.html)，Ensure that the pre dependency installation is complete. +Please refer to [MindSPONGE Installation Tutorial](https://www.mindspore.cn/mindsponge/docs/en/master/intro.html#installation). Ensure that the pre dependency installation is complete. Cybertron installation can be compiled and installed using source code. diff --git a/docs/mindsponge/docs/source_en/sponge.md b/docs/mindsponge/docs/source_en/sponge.md index 91e8cc96be660d9f950edb5a221505fb92617ebf..ac990f6c1a27ddad25dfd847cc4e42f8acba5782 100644 --- a/docs/mindsponge/docs/source_en/sponge.md +++ b/docs/mindsponge/docs/source_en/sponge.md @@ -12,7 +12,7 @@ Traditional molecular dynamics is a molecular dynamics simulation program based ### Install -Please refer to [MindSPONGE Installation Tutorial](https://www.mindspore.cn/mindsponge/docs/en/master/mindsponge/intro.html). +Please refer to [MindSPONGE Installation Tutorial](https://www.mindspore.cn/mindsponge/docs/en/master/intro.html#installation). Traditional molecular dynamics installation can be compiled and installed using source code. @@ -124,11 +124,11 @@ The structure of micromolecular dynamics is shown in the figure below: ### Install -The installation process of micromolecular dynamics is consistent with that of MindSPONGE. Please refer to [MindSPONGE Installation Tutorial](https://www.mindspore.cn/mindsponge/docs/en/master/mindsponge/intro.html) . +The installation process of micromolecular dynamics is consistent with that of MindSPONGE. Please refer to [MindSPONGE Installation Tutorial](https://www.mindspore.cn/mindsponge/docs/en/master/intro.html#installation). ### Basic usage -The basic application methods of micromolecular dynamics can be referred to [Initial experience of the case](https://www.mindspore.cn/mindsponge/docs/en/master/mindsponge/intro.html#examples) and subsequent API introduction documents [MindSPONGE APIs](https://www.mindspore.cn/mindsponge/docs/zh-CN/master/mindsponge.html). +The basic application methods of micromolecular dynamics can be referred to [Initial experience of the case](https://www.mindspore.cn/mindsponge/docs/en/master/intro.html#examples) and subsequent API introduction documents [MindSPONGE APIs](https://www.mindspore.cn/mindsponge/docs/zh-CN/master/mindsponge.callback.html). ### Case diff --git a/docs/mindsponge/docs/source_en/xponge.md b/docs/mindsponge/docs/source_en/xponge.md index 8f66995a97322a740582e2d4a47f336d95c968a9..ee6d79f0d71269ab00dc35c083427e8f576c32cd 100644 --- a/docs/mindsponge/docs/source_en/xponge.md +++ b/docs/mindsponge/docs/source_en/xponge.md @@ -14,7 +14,7 @@ Molecular system modeling tools are applicable to all operating systems (Windows ## Install -Please refer to [MindSPONGE Installation Tutorial](https://www.mindspore.cn/mindsponge/docs/en/master/mindsponge/intro.html) . +Please refer to [MindSPONGE Installation Tutorial](https://www.mindspore.cn/mindsponge/docs/en/master/intro.html#installation). | Dependent Name | instructions | Installation method | | :------- | :--------------------------------------------- | :---------------------- | diff --git a/docs/mindsponge/docs/source_zh_cn/cybertron.md b/docs/mindsponge/docs/source_zh_cn/cybertron.md index 65312c03a3995c32e3817ca956264ef0d96a987c..19830d993063e60847e33b770b0029ffd65eb095 100644 --- a/docs/mindsponge/docs/source_zh_cn/cybertron.md +++ b/docs/mindsponge/docs/source_zh_cn/cybertron.md @@ -24,7 +24,7 @@ Cybertron中内置三种GNN分子模型： SchNet[1]、 PhysNet[2]以及MolCT[3] ## 安装 -请参考[MindSPONGE安装教程](https://www.mindspore.cn/mindsponge/docs/zh-CN/master/mindsponge/intro.html#%E5%AE%89%E8%A3%85%E6%95%99%E7%A8%8B)，确保前置依赖已安装完成。 +请参考[MindSPONGE安装教程](https://www.mindspore.cn/mindsponge/docs/zh-CN/master/intro.html#%E5%AE%89%E8%A3%85%E6%95%99%E7%A8%8B)，确保前置依赖已安装完成。 Cybertron安装可使用源码编译安装。 diff --git a/docs/mindsponge/docs/source_zh_cn/sponge.md b/docs/mindsponge/docs/source_zh_cn/sponge.md index 2376b02d3d0bb089bf110831fd3fc77ba2fef819..1ee9c0a0ab0e62c94e546e70f11a47e8de1ae642 100644 --- a/docs/mindsponge/docs/source_zh_cn/sponge.md +++ b/docs/mindsponge/docs/source_zh_cn/sponge.md @@ -12,7 +12,7 @@ ### 安装 -请参考[MindSPONGE安装教程](https://www.mindspore.cn/mindsponge/docs/zh-CN/master/mindsponge/intro.html#%E5%AE%89%E8%A3%85%E6%95%99%E7%A8%8B)。 +请参考[MindSPONGE安装教程](https://www.mindspore.cn/mindsponge/docs/zh-CN/master/intro.html#%E5%AE%89%E8%A3%85%E6%95%99%E7%A8%8B)。 传统分子动力学安装可使用源码编译安装。 @@ -124,11 +124,11 @@ bond_in_file = tip4p_2880_system/Ih_bond.txt ### 安装 -可微分子动力学的安装流程与MindSPONGE的安装流程一致，请参考[MindSPONGE安装教程](https://www.mindspore.cn/mindsponge/docs/zh-CN/master/mindsponge/intro.html#%E5%AE%89%E8%A3%85%E6%95%99%E7%A8%8B)。 +可微分子动力学的安装流程与MindSPONGE的安装流程一致，请参考[MindSPONGE安装教程](https://www.mindspore.cn/mindsponge/docs/zh-CN/master/intro.html#%E5%AE%89%E8%A3%85%E6%95%99%E7%A8%8B)。 ### 基本使用 -可微分子动力学的基本使用方法可参考[案例初体验](https://www.mindspore.cn/mindsponge/docs/zh-CN/master/mindsponge/intro.html#%E6%A1%88%E4%BE%8B%E5%88%9D%E4%BD%93%E9%AA%8C)以及后续的API介绍文档[MindSPONGE APIs](https://www.mindspore.cn/mindsponge/docs/zh-CN/master/mindsponge.html)。 +可微分子动力学的基本使用方法可参考[案例初体验](https://www.mindspore.cn/mindsponge/docs/zh-CN/master/intro.html#%E6%A1%88%E4%BE%8B%E5%88%9D%E4%BD%93%E9%AA%8C)以及后续的API介绍文档[MindSPONGE APIs](https://www.mindspore.cn/mindsponge/docs/zh-CN/master/mindsponge.callback.html)。 ### 案例 diff --git a/docs/mindsponge/docs/source_zh_cn/xponge.md b/docs/mindsponge/docs/source_zh_cn/xponge.md index faaab0425d34d1ecba11c52586f1855ef0ef7d23..e79cf3f40b611f615f8d87aaee4721d2f83ad331 100644 --- a/docs/mindsponge/docs/source_zh_cn/xponge.md +++ b/docs/mindsponge/docs/source_zh_cn/xponge.md @@ -14,7 +14,7 @@ MindSPONGE软件中包含一个轻量化且易于定制的分子体系建模工 ## 安装 -请参考[MindSPONGE安装教程](https://www.mindspore.cn/mindsponge/docs/zh-CN/master/mindsponge/intro.html#%E5%AE%89%E8%A3%85%E6%95%99%E7%A8%8B)。 +请参考[MindSPONGE安装教程](https://www.mindspore.cn/mindsponge/docs/zh-CN/master/intro.html#%E5%AE%89%E8%A3%85%E6%95%99%E7%A8%8B)。 | 依赖名称 | 使用说明 | 安装方式 | | :------- | :--------------------------------------------- | :---------------------- | diff --git a/resource/release/release_list_en.md b/resource/release/release_list_en.md index cac4507924b6db0319ab560a82e119c26790f976..d652b1eea9a905ec2030398259bce78e91b31367 100644 --- a/resource/release/release_list_en.md +++ b/resource/release/release_list_en.md @@ -74,7 +74,7 @@ | |MindSpore Probability | [1.7.0](https://www.mindspore.cn/probability/docs/en/r1.7/mindspore.nn.probability.html)    [1.6.0](https://www.mindspore.cn/probability/docs/en/r1.6/mindspore.nn.probability.html)    [1.5.0](https://www.mindspore.cn/probability/api/en/r1.5/index.html)    [1.3.0](https://www.mindspore.cn/probability/api/en/r1.3/index.html)    [master](https://www.mindspore.cn/probability/docs/en/master/mindspore.nn.probability.html) | | |MindQuantum | [0.7.0](https://www.mindspore.cn/mindquantum/docs/en/r0.7/mindquantum.core.html)    [0.6.0](https://www.mindspore.cn/mindquantum/docs/en/r0.6/mindquantum.core.html)    [0.5.0](https://www.mindspore.cn/mindquantum/docs/en/r0.5/mindquantum.core.html)    [0.3.1](https://www.mindspore.cn/mindquantum/api/en/r0.3/index.html)    [0.2.0](https://www.mindspore.cn/mindquantum/api/en/r0.2/index.html)    [0.1.0](https://www.mindspore.cn/doc/api_python/en/r1.2/mindquantum/mindquantum.html)   
[master](https://www.mindspore.cn/mindquantum/docs/en/master/mindquantum.core.html) | | |MindSpore XAI | [1.8.1](https://www.mindspore.cn/xai/docs/en/r1.8/mindspore_xai.explainer.html)    [1.5.0](https://www.mindspore.cn/xai/api/en/r1.5/index.html)    [master](https://www.mindspore.cn/xai/docs/en/master/mindspore_xai.explainer.html) | -| |MindScience(MindElec and MindSPONGE) | [0.1.0](https://www.mindspore.cn/mindscience/api/en/r0.1/index.html)    [master](https://www.mindspore.cn/mindsponge/docs/en/master/mindsponge.html) | +| |MindScience(MindElec and MindSPONGE) | [0.1.0](https://www.mindspore.cn/mindscience/api/en/r0.1/index.html)    [master](https://www.mindspore.cn/mindsponge/docs/en/master/mindsponge.callback.html) | | |MindSpore Reinforcement | [0.5.0](https://www.mindspore.cn/reinforcement/docs/en/r0.5/reinforcement.html)    [0.3.0](https://www.mindspore.cn/reinforcement/docs/en/r0.3/reinforcement.html)    [0.2.1](https://www.mindspore.cn/reinforcement/docs/en/r0.2/reinforcement.html)    [0.1.0](https://www.mindspore.cn/reinforcement/api/en/r0.1/index.html)    [master](https://www.mindspore.cn/reinforcement/docs/en/master/reinforcement.html) | | |MindSpore Graph Learning | [0.1.0](https://www.mindspore.cn/graphlearning/docs/en/r0.1/mindspore_gl.dataset.html)    [master](https://www.mindspore.cn/graphlearning/docs/en/master/mindspore_gl.dataset.html) | | |MindSpore Vision | [0.1.0](https://www.mindspore.cn/vision/docs/en/r0.1/classification.html)    [master](https://www.mindspore.cn/vision/docs/en/master/classification.html) | diff --git a/resource/release/release_list_zh_cn.md b/resource/release/release_list_zh_cn.md index 5221bcf4db9e6403ee9a389a061914885ebed488..3d155d8b162d3122bcefb591b7f02ee1d5d63d39 100644 --- a/resource/release/release_list_zh_cn.md +++ b/resource/release/release_list_zh_cn.md @@ -74,7 +74,7 @@ | |MindSpore Probability | [1.7.0](https://www.mindspore.cn/probability/docs/zh-CN/r1.7/mindspore.nn.probability.html)    [1.6.0](https://www.mindspore.cn/probability/docs/zh-CN/r1.6/mindspore.nn.probability.html)    [1.5.0](https://www.mindspore.cn/probability/api/zh-CN/r1.5/index.html)    [1.3.0](https://www.mindspore.cn/probability/api/zh-CN/r1.3/index.html)    [master](https://www.mindspore.cn/probability/docs/zh-CN/master/mindspore.nn.probability.html) | | |MindQuantum | [0.7.0](https://www.mindspore.cn/mindquantum/docs/zh-CN/r0.7/mindquantum.core.html)    [0.6.0](https://www.mindspore.cn/mindquantum/docs/zh-CN/r0.6/mindquantum.core.html)    [0.5.0](https://www.mindspore.cn/mindquantum/docs/zh-CN/r0.5/mindquantum.core.html)    [0.3.1](https://www.mindspore.cn/mindquantum/api/zh-CN/r0.3/index.html)    [0.2.0](https://www.mindspore.cn/mindquantum/api/zh-CN/r0.2/index.html)    [0.1.0](https://www.mindspore.cn/doc/api_python/zh-CN/r1.2/mindquantum/mindquantum.html)    [master](https://www.mindspore.cn/mindquantum/docs/zh-CN/master/mindquantum.core.html) | | |MindSpore XAI | [1.8.1](https://www.mindspore.cn/xai/docs/zh-CN/r1.8/mindspore_xai.explainer.html)    [1.5.0](https://www.mindspore.cn/xai/api/zh-CN/r1.5/index.html)    [master](https://www.mindspore.cn/xai/docs/zh-CN/master/mindspore_xai.explainer.html) | -| |MindScience(MindElec and MindSPONGE) | [0.1.0](https://www.mindspore.cn/mindscience/api/zh-CN/r0.1/index.html)    [master](https://www.mindspore.cn/mindsponge/docs/zh-CN/master/mindsponge.html) | +| |MindScience(MindElec and MindSPONGE) | [0.1.0](https://www.mindspore.cn/mindscience/api/zh-CN/r0.1/index.html)    [master](https://www.mindspore.cn/mindsponge/docs/zh-CN/master/mindsponge.callback.html) | | |MindSpore Reinforcement | [0.5.0](https://www.mindspore.cn/reinforcement/docs/zh-CN/r0.5/reinforcement.html)    [0.3.0](https://www.mindspore.cn/reinforcement/docs/zh-CN/r0.3/reinforcement.html)    [0.2.1](https://www.mindspore.cn/reinforcement/docs/zh-CN/r0.2/reinforcement.html)    [0.1.0](https://www.mindspore.cn/reinforcement/api/zh-CN/r0.1/index.html)    [master](https://www.mindspore.cn/reinforcement/docs/zh-CN/master/reinforcement.html) | | |MindSpore Graph Learning | [0.1.0](https://www.mindspore.cn/graphlearning/docs/zh-CN/r0.1/mindspore_gl.dataset.html)    [master](https://www.mindspore.cn/graphlearning/docs/zh-CN/master/mindspore_gl.dataset.html) | | |MindSpore Vision | [0.1.0](https://www.mindspore.cn/vision/docs/zh-CN/r0.1/classification.html)    [master](https://www.mindspore.cn/vision/docs/zh-CN/master/classification.html) | diff --git a/tutorials/application/source_zh_cn/cv/transfer_learning.ipynb b/tutorials/application/source_zh_cn/cv/transfer_learning.ipynb index a126967444be4e620aa255c0834e6f2007715faf..9d172b691402dfa11b9cb962f1a3311785d9ad9d 100644 --- a/tutorials/application/source_zh_cn/cv/transfer_learning.ipynb +++ b/tutorials/application/source_zh_cn/cv/transfer_learning.ipynb @@ -11,7 +11,7 @@ "\n", "在实际应用场景中，由于训练数据集不足，所以很少有人会从头开始训练整个网络。普遍的做法是，在一个非常大的基础数据集上训练得到一个预训练模型，然后使用该模型来初始化网络的权重参数或作为固定特征提取器应用于特定的任务中。本章将使用迁移学习的方法对ImageNet数据集中的狼和狗图像进行分类。\n", "\n", - "> 迁移学习详细内容见[Stanford University CS231n](https://cs231n.github.io/transfer-learning/#tf)\n", + "> 迁移学习详细内容见[Stanford University CS231n](https://cs231n.github.io/transfer-learning/#tf)。\n", "\n", "## 数据准备\n", "\n",