From 3be59a9ddeba718c20f08e1648d57b1443cd2db7 Mon Sep 17 00:00:00 2001 From: Vvv6 <286738135@qq.com> Date: Thu, 20 Jul 2023 14:39:22 +0800 Subject: [PATCH 1/4] =?UTF-8?q?=E3=80=90pytorch=E3=80=91=E3=80=90contrib?= =?UTF-8?q?=E3=80=91=E3=80=90cv=E3=80=91=20GhostNet=20=E6=A8=A1=E5=9E=8B?= =?UTF-8?q?=E5=85=AC=E7=BD=91=E5=9C=B0=E5=9D=80=E6=95=B4=E6=94=B9?= MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit --- .../cv/classification/GhostNet/README.md | 4 + .../GhostNet/public_address_statement.md | 337 ++++++++++++++++++ .../GhostNet/timm/models/efficientnet.py | 13 +- .../GhostNet/timm/models/nfnet.py | 7 +- .../cv/classification/GhostNet/url.ini | 4 + 5 files changed, 361 insertions(+), 4 deletions(-) create mode 100644 PyTorch/contrib/cv/classification/GhostNet/public_address_statement.md create mode 100644 PyTorch/contrib/cv/classification/GhostNet/url.ini diff --git a/PyTorch/contrib/cv/classification/GhostNet/README.md b/PyTorch/contrib/cv/classification/GhostNet/README.md index c613228e8d..859667536b 100644 --- a/PyTorch/contrib/cv/classification/GhostNet/README.md +++ b/PyTorch/contrib/cv/classification/GhostNet/README.md @@ -182,3 +182,7 @@ ## FAQ 无。 + +# 公网地址说明 + +代码涉及公网地址参考 public_address_statement.md \ No newline at end of file diff --git a/PyTorch/contrib/cv/classification/GhostNet/public_address_statement.md b/PyTorch/contrib/cv/classification/GhostNet/public_address_statement.md new file mode 100644 index 0000000000..0e2585c465 --- /dev/null +++ b/PyTorch/contrib/cv/classification/GhostNet/public_address_statement.md @@ -0,0 +1,337 @@ +| 类型 | 开源代码地址 | 文件名 | 公网IP地址/公网URL地址/域名/邮箱地址 | 用途说明 | +|--------|--------------------------------------------------------------|----------------------------------------------|------------------------|----| +| 开源代码引入 | https://github.com/huggingface/pytorch-image-models/blob/d584e7f617a4d0f1a0b4838227bd1f8852dfa236/setup.py | GhostNet/setup.py | https://github.com/rwightman/pytorch-image-models | 开源地址 | +| 开源代码引入 | https://github.com/huggingface/pytorch-image-models/blob/d584e7f617a4d0f1a0b4838227bd1f8852dfa236/setup.py | GhostNet/setup.py | hello@rwightman.com | 作者邮箱 | +| 开源代码引入 | https://github.com/huggingface/pytorch-image-models/blob/d584e7f617a4d0f1a0b4838227bd1f8852dfa236/timm/models/byobnet.py | GhostNet/timm/models/byobnet.py | https://github.com/rwightman/pytorch-image-models/releases/download/v0.1-ger-weights/gernet_s-756b4751.pth | 下载权重文件 | +| 开源代码引入 | https://github.com/huggingface/pytorch-image-models/blob/d584e7f617a4d0f1a0b4838227bd1f8852dfa236/timm/models/byobnet.py | GhostNet/timm/models/byobnet.py | https://github.com/rwightman/pytorch-image-models/releases/download/v0.1-ger-weights/gernet_m-0873c53a.pth | 下载权重文件 | +| 开源代码引入 | https://github.com/huggingface/pytorch-image-models/blob/d584e7f617a4d0f1a0b4838227bd1f8852dfa236/timm/models/byobnet.py | GhostNet/timm/models/byobnet.py | 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https://github.com/huggingface/pytorch-image-models/blob/d584e7f617a4d0f1a0b4838227bd1f8852dfa236/timm/models/dla.py | GhostNet/timm/models/dla.py | http://dl.yf.io/dla/models/imagenet/dla102x2-262837b6.pth | 下载权重文件 | +| 开源代码引入 | https://github.com/huggingface/pytorch-image-models/blob/d584e7f617a4d0f1a0b4838227bd1f8852dfa236/timm/models/dla.py | GhostNet/timm/models/dla.py | http://dl.yf.io/dla/models/imagenet/dla169-0914e092.pth | 下载权重文件 | +| 开源代码引入 | https://github.com/huggingface/pytorch-image-models/blob/d584e7f617a4d0f1a0b4838227bd1f8852dfa236/timm/models/dla.py | GhostNet/timm/models/dla.py | https://github.com/rwightman/pytorch-image-models/releases/download/v0.1-res2net/res2net_dla60_4s-d88db7f9.pth | 下载权重文件 | +| 开源代码引入 | https://github.com/huggingface/pytorch-image-models/blob/d584e7f617a4d0f1a0b4838227bd1f8852dfa236/timm/models/dla.py | GhostNet/timm/models/dla.py | 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GhostNet/timm/models/resnet.py | https://imvl-automl-sh.oss-cn-shanghai.aliyuncs.com/darts/hyperml/hyperml/job_45402/outputs/ECAResNetLight_4f34b35b.pth | 下载权重文件 | +| 开源代码引入 | https://github.com/huggingface/pytorch-image-models/blob/d584e7f617a4d0f1a0b4838227bd1f8852dfa236/timm/models/resnet.py | GhostNet/timm/models/resnet.py | https://imvl-automl-sh.oss-cn-shanghai.aliyuncs.com/darts/hyperml/hyperml/job_45402/outputs/ECAResNet50D_833caf58.pth | 下载权重文件 | +| 开源代码引入 | https://github.com/huggingface/pytorch-image-models/blob/d584e7f617a4d0f1a0b4838227bd1f8852dfa236/timm/models/resnet.py | GhostNet/timm/models/resnet.py | https://imvl-automl-sh.oss-cn-shanghai.aliyuncs.com/darts/hyperml/hyperml/job_45899/outputs/ECAResNet50D_P_9c67f710.pth | 下载权重文件 | +| 开源代码引入 | https://github.com/huggingface/pytorch-image-models/blob/d584e7f617a4d0f1a0b4838227bd1f8852dfa236/timm/models/resnet.py | GhostNet/timm/models/resnet.py | 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https://storage.googleapis.com/bit_models/BiT-M-R101x1-ILSVRC2012.npz | 下载数据集 | +| 开源代码引入 | https://github.com/huggingface/pytorch-image-models/blob/d584e7f617a4d0f1a0b4838227bd1f8852dfa236/timm/models/resnetv2.py | GhostNet/timm/models/resnetv2.py | https://storage.googleapis.com/bit_models/BiT-M-R101x3-ILSVRC2012.npz | 下载数据集 | +| 开源代码引入 | https://github.com/huggingface/pytorch-image-models/blob/d584e7f617a4d0f1a0b4838227bd1f8852dfa236/timm/models/resnetv2.py | GhostNet/timm/models/resnetv2.py | https://storage.googleapis.com/bit_models/BiT-M-R152x2-ILSVRC2012.npz | 下载数据集 | +| 开源代码引入 | https://github.com/huggingface/pytorch-image-models/blob/d584e7f617a4d0f1a0b4838227bd1f8852dfa236/timm/models/resnetv2.py | GhostNet/timm/models/resnetv2.py | https://storage.googleapis.com/bit_models/BiT-M-R152x4-ILSVRC2012.npz | 下载数据集 | +| 开源代码引入 | https://github.com/huggingface/pytorch-image-models/blob/d584e7f617a4d0f1a0b4838227bd1f8852dfa236/timm/models/resnetv2.py | GhostNet/timm/models/resnetv2.py | https://storage.googleapis.com/bit_models/BiT-M-R50x1.npz | 下载数据集 | +| 开源代码引入 | https://github.com/huggingface/pytorch-image-models/blob/d584e7f617a4d0f1a0b4838227bd1f8852dfa236/timm/models/resnetv2.py | GhostNet/timm/models/resnetv2.py | https://storage.googleapis.com/bit_models/BiT-M-R50x3.npz | 下载数据集 | +| 开源代码引入 | https://github.com/huggingface/pytorch-image-models/blob/d584e7f617a4d0f1a0b4838227bd1f8852dfa236/timm/models/resnetv2.py | GhostNet/timm/models/resnetv2.py | https://storage.googleapis.com/bit_models/BiT-M-R101x1.npz | 下载数据集 | +| 开源代码引入 | https://github.com/huggingface/pytorch-image-models/blob/d584e7f617a4d0f1a0b4838227bd1f8852dfa236/timm/models/resnetv2.py | GhostNet/timm/models/resnetv2.py | https://storage.googleapis.com/bit_models/BiT-M-R101x3.npz | 下载数据集 | +| 开源代码引入 | https://github.com/huggingface/pytorch-image-models/blob/d584e7f617a4d0f1a0b4838227bd1f8852dfa236/timm/models/resnetv2.py | GhostNet/timm/models/resnetv2.py | 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https://github.com/huggingface/pytorch-image-models/blob/d584e7f617a4d0f1a0b4838227bd1f8852dfa236/timm/models/rexnet.py | GhostNet/timm/models/rexnet.py | https://github.com/rwightman/pytorch-image-models/releases/download/v0.1-rexnet/rexnetv1_150-bd1a6aa8.pth | 下载权重文件 | +| 开源代码引入 | https://github.com/huggingface/pytorch-image-models/blob/d584e7f617a4d0f1a0b4838227bd1f8852dfa236/timm/models/rexnet.py | GhostNet/timm/models/rexnet.py | https://github.com/rwightman/pytorch-image-models/releases/download/v0.1-rexnet/rexnetv1_200-8c0b7f2d.pth | 下载权重文件 | +| 开源代码引入 | https://github.com/huggingface/pytorch-image-models/blob/d584e7f617a4d0f1a0b4838227bd1f8852dfa236/timm/models/selecsls.py | GhostNet/timm/models/selecsls.py | https://github.com/rwightman/pytorch-image-models/releases/download/v0.1-selecsls/selecsls42b-8af30141.pth | 下载权重文件 | +| 开源代码引入 | https://github.com/huggingface/pytorch-image-models/blob/d584e7f617a4d0f1a0b4838227bd1f8852dfa236/timm/models/selecsls.py | 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https://github.com/rwightman/pytorch-image-models/releases/download/v0.1-tresnet/tresnet_m_448-bc359d10.pth | 下载权重文件 | +| 开源代码引入 | https://github.com/huggingface/pytorch-image-models/blob/d584e7f617a4d0f1a0b4838227bd1f8852dfa236/timm/models/tresnet.py | GhostNet/timm/models/tresnet.py | https://github.com/rwightman/pytorch-image-models/releases/download/v0.1-tresnet/tresnet_l_448-940d0cd1.pth | 下载权重文件 | +| 开源代码引入 | https://github.com/huggingface/pytorch-image-models/blob/d584e7f617a4d0f1a0b4838227bd1f8852dfa236/timm/models/tresnet.py | GhostNet/timm/models/tresnet.py | https://github.com/rwightman/pytorch-image-models/releases/download/v0.1-tresnet/tresnet_xl_448-8c1815de.pth | 下载权重文件 | +| 开源代码引入 | https://github.com/huggingface/pytorch-image-models/blob/d584e7f617a4d0f1a0b4838227bd1f8852dfa236/timm/models/vgg.py | GhostNet/timm/models/vgg.py | https://download.pytorch.org/models/vgg11-bbd30ac9.pth | 下载权重文件 | +| 开源代码引入 | https://github.com/huggingface/pytorch-image-models/blob/d584e7f617a4d0f1a0b4838227bd1f8852dfa236/timm/models/vgg.py | GhostNet/timm/models/vgg.py | https://download.pytorch.org/models/vgg13-c768596a.pth | 下载权重文件 | +| 开源代码引入 | https://github.com/huggingface/pytorch-image-models/blob/d584e7f617a4d0f1a0b4838227bd1f8852dfa236/timm/models/vgg.py | GhostNet/timm/models/vgg.py | https://download.pytorch.org/models/vgg16-397923af.pth | 下载权重文件 | +| 开源代码引入 | https://github.com/huggingface/pytorch-image-models/blob/d584e7f617a4d0f1a0b4838227bd1f8852dfa236/timm/models/vgg.py | GhostNet/timm/models/vgg.py | https://download.pytorch.org/models/vgg19-dcbb9e9d.pth | 下载权重文件 | +| 开源代码引入 | https://github.com/huggingface/pytorch-image-models/blob/d584e7f617a4d0f1a0b4838227bd1f8852dfa236/timm/models/vgg.py | GhostNet/timm/models/vgg.py | https://download.pytorch.org/models/vgg11_bn-6002323d.pth | 下载权重文件 | +| 开源代码引入 | https://github.com/huggingface/pytorch-image-models/blob/d584e7f617a4d0f1a0b4838227bd1f8852dfa236/timm/models/vgg.py | GhostNet/timm/models/vgg.py | https://download.pytorch.org/models/vgg13_bn-abd245e5.pth | 下载权重文件 | +| 开源代码引入 | https://github.com/huggingface/pytorch-image-models/blob/d584e7f617a4d0f1a0b4838227bd1f8852dfa236/timm/models/vgg.py | GhostNet/timm/models/vgg.py | https://download.pytorch.org/models/vgg16_bn-6c64b313.pth | 下载权重文件 | +| 开源代码引入 | https://github.com/huggingface/pytorch-image-models/blob/d584e7f617a4d0f1a0b4838227bd1f8852dfa236/timm/models/vgg.py | GhostNet/timm/models/vgg.py | https://download.pytorch.org/models/vgg19_bn-c79401a0.pth | 下载权重文件 | +| 开源代码引入 | https://github.com/huggingface/pytorch-image-models/blob/d584e7f617a4d0f1a0b4838227bd1f8852dfa236/timm/models/vision_transformer.py | GhostNet/timm/models/vision_transformer.py | https://github.com/rwightman/pytorch-image-models/releases/download/v0.1-weights/vit_small_p16_224-15ec54c9.pth | 下载权重文件 | +| 开源代码引入 | https://github.com/huggingface/pytorch-image-models/blob/d584e7f617a4d0f1a0b4838227bd1f8852dfa236/timm/models/vision_transformer.py | GhostNet/timm/models/vision_transformer.py | https://github.com/rwightman/pytorch-image-models/releases/download/v0.1-vitjx/jx_vit_base_p16_224-80ecf9dd.pth | 下载权重文件 | +| 开源代码引入 | https://github.com/huggingface/pytorch-image-models/blob/d584e7f617a4d0f1a0b4838227bd1f8852dfa236/timm/models/vision_transformer.py | GhostNet/timm/models/vision_transformer.py | https://github.com/rwightman/pytorch-image-models/releases/download/v0.1-vitjx/jx_vit_base_p16_384-83fb41ba.pth | 下载权重文件 | +| 开源代码引入 | https://github.com/huggingface/pytorch-image-models/blob/d584e7f617a4d0f1a0b4838227bd1f8852dfa236/timm/models/vision_transformer.py | GhostNet/timm/models/vision_transformer.py | https://github.com/rwightman/pytorch-image-models/releases/download/v0.1-vitjx/jx_vit_base_p32_384-830016f5.pth | 下载权重文件 | +| 开源代码引入 | https://github.com/huggingface/pytorch-image-models/blob/d584e7f617a4d0f1a0b4838227bd1f8852dfa236/timm/models/vision_transformer.py | GhostNet/timm/models/vision_transformer.py | https://github.com/rwightman/pytorch-image-models/releases/download/v0.1-vitjx/jx_vit_large_p16_224-4ee7a4dc.pth | 下载权重文件 | +| 开源代码引入 | https://github.com/huggingface/pytorch-image-models/blob/d584e7f617a4d0f1a0b4838227bd1f8852dfa236/timm/models/vision_transformer.py | GhostNet/timm/models/vision_transformer.py | https://github.com/rwightman/pytorch-image-models/releases/download/v0.1-vitjx/jx_vit_large_p16_384-b3be5167.pth | 下载权重文件 | +| 开源代码引入 | https://github.com/huggingface/pytorch-image-models/blob/d584e7f617a4d0f1a0b4838227bd1f8852dfa236/timm/models/vision_transformer.py | GhostNet/timm/models/vision_transformer.py | https://github.com/rwightman/pytorch-image-models/releases/download/v0.1-vitjx/jx_vit_large_p32_384-9b920ba8.pth | 下载权重文件 | +| 开源代码引入 | https://github.com/huggingface/pytorch-image-models/blob/d584e7f617a4d0f1a0b4838227bd1f8852dfa236/timm/models/vision_transformer.py | GhostNet/timm/models/vision_transformer.py | https://github.com/rwightman/pytorch-image-models/releases/download/v0.1-vitjx/jx_vit_base_patch16_224_in21k-e5005f0a.pth | 下载权重文件 | +| 开源代码引入 | https://github.com/huggingface/pytorch-image-models/blob/d584e7f617a4d0f1a0b4838227bd1f8852dfa236/timm/models/vision_transformer.py | GhostNet/timm/models/vision_transformer.py | https://github.com/rwightman/pytorch-image-models/releases/download/v0.1-vitjx/jx_vit_base_patch32_224_in21k-8db57226.pth | 下载权重文件 | +| 开源代码引入 | https://github.com/huggingface/pytorch-image-models/blob/d584e7f617a4d0f1a0b4838227bd1f8852dfa236/timm/models/vision_transformer.py | GhostNet/timm/models/vision_transformer.py | https://github.com/rwightman/pytorch-image-models/releases/download/v0.1-vitjx/jx_vit_large_patch16_224_in21k-606da67d.pth | 下载权重文件 | +| 开源代码引入 | https://github.com/huggingface/pytorch-image-models/blob/d584e7f617a4d0f1a0b4838227bd1f8852dfa236/timm/models/vision_transformer.py | GhostNet/timm/models/vision_transformer.py | https://github.com/rwightman/pytorch-image-models/releases/download/v0.1-vitjx/jx_vit_large_patch32_224_in21k-9046d2e7.pth | 下载权重文件 | +| 开源代码引入 | https://github.com/huggingface/pytorch-image-models/blob/d584e7f617a4d0f1a0b4838227bd1f8852dfa236/timm/models/vision_transformer.py | GhostNet/timm/models/vision_transformer.py | https://github.com/rwightman/pytorch-image-models/releases/download/v0.1-vitjx/jx_vit_base_resnet50_224_in21k-6f7c7740.pth | 下载权重文件 | +| 开源代码引入 | https://github.com/huggingface/pytorch-image-models/blob/d584e7f617a4d0f1a0b4838227bd1f8852dfa236/timm/models/vision_transformer.py | GhostNet/timm/models/vision_transformer.py | https://github.com/rwightman/pytorch-image-models/releases/download/v0.1-vitjx/jx_vit_base_resnet50_384-9fd3c705.pth | 下载权重文件 | +| 开源代码引入 | https://github.com/huggingface/pytorch-image-models/blob/d584e7f617a4d0f1a0b4838227bd1f8852dfa236/timm/models/vision_transformer.py | GhostNet/timm/models/vision_transformer.py | https://dl.fbaipublicfiles.com/deit/deit_tiny_patch16_224-a1311bcf.pth | 下载权重文件 | +| 开源代码引入 | https://github.com/huggingface/pytorch-image-models/blob/d584e7f617a4d0f1a0b4838227bd1f8852dfa236/timm/models/vision_transformer.py | GhostNet/timm/models/vision_transformer.py | https://dl.fbaipublicfiles.com/deit/deit_small_patch16_224-cd65a155.pth | 下载权重文件 | +| 开源代码引入 | https://github.com/huggingface/pytorch-image-models/blob/d584e7f617a4d0f1a0b4838227bd1f8852dfa236/timm/models/vision_transformer.py | GhostNet/timm/models/vision_transformer.py | https://dl.fbaipublicfiles.com/deit/deit_base_patch16_224-b5f2ef4d.pth | 下载权重文件 | +| 开源代码引入 | https://github.com/huggingface/pytorch-image-models/blob/d584e7f617a4d0f1a0b4838227bd1f8852dfa236/timm/models/vision_transformer.py | GhostNet/timm/models/vision_transformer.py | https://dl.fbaipublicfiles.com/deit/deit_base_patch16_384-8de9b5d1.pth | 下载权重文件 | +| 开源代码引入 | https://github.com/huggingface/pytorch-image-models/blob/d584e7f617a4d0f1a0b4838227bd1f8852dfa236/timm/models/vision_transformer.py | GhostNet/timm/models/vision_transformer.py | https://dl.fbaipublicfiles.com/deit/deit_tiny_distilled_patch16_224-b40b3cf7.pth | 下载权重文件 | +| 开源代码引入 | https://github.com/huggingface/pytorch-image-models/blob/d584e7f617a4d0f1a0b4838227bd1f8852dfa236/timm/models/vision_transformer.py | GhostNet/timm/models/vision_transformer.py | https://dl.fbaipublicfiles.com/deit/deit_small_distilled_patch16_224-649709d9.pth | 下载权重文件 | +| 开源代码引入 | https://github.com/huggingface/pytorch-image-models/blob/d584e7f617a4d0f1a0b4838227bd1f8852dfa236/timm/models/vision_transformer.py | GhostNet/timm/models/vision_transformer.py | https://dl.fbaipublicfiles.com/deit/deit_base_distilled_patch16_224-df68dfff.pth | 下载权重文件 | +| 开源代码引入 | https://github.com/huggingface/pytorch-image-models/blob/d584e7f617a4d0f1a0b4838227bd1f8852dfa236/timm/models/vision_transformer.py | GhostNet/timm/models/vision_transformer.py | https://dl.fbaipublicfiles.com/deit/deit_base_distilled_patch16_384-d0272ac0.pth | 下载权重文件 | +| 开源代码引入 | https://github.com/huggingface/pytorch-image-models/blob/d584e7f617a4d0f1a0b4838227bd1f8852dfa236/timm/models/vovnet.py | GhostNet/timm/models/vovnet.py | https://github.com/rwightman/pytorch-image-models/releases/download/v0.1-weights/ese_vovnet19b_dw-a8741004.pth | 下载权重文件 | +| 开源代码引入 | https://github.com/huggingface/pytorch-image-models/blob/d584e7f617a4d0f1a0b4838227bd1f8852dfa236/timm/models/vovnet.py | GhostNet/timm/models/vovnet.py | https://github.com/rwightman/pytorch-image-models/releases/download/v0.1-weights/ese_vovnet39b-f912fe73.pth | 下载权重文件 | +| 开源代码引入 | https://github.com/huggingface/pytorch-image-models/blob/d584e7f617a4d0f1a0b4838227bd1f8852dfa236/timm/models/xception.py | GhostNet/timm/models/xception.py | https://github.com/rwightman/pytorch-image-models/releases/download/v0.1-cadene/xception-43020ad28.pth | 下载权重文件 | +| 开源代码引入 | https://github.com/huggingface/pytorch-image-models/blob/d584e7f617a4d0f1a0b4838227bd1f8852dfa236/timm/models/xception_aligned.py | GhostNet/timm/models/xception_aligned.py | https://github.com/rwightman/pytorch-image-models/releases/download/v0.1-weights/tf_xception_41-e6439c97.pth | 下载权重文件 | +| 开源代码引入 | https://github.com/huggingface/pytorch-image-models/blob/d584e7f617a4d0f1a0b4838227bd1f8852dfa236/timm/models/xception_aligned.py | GhostNet/timm/models/xception_aligned.py | https://github.com/rwightman/pytorch-image-models/releases/download/v0.1-weights/tf_xception_65-c9ae96e8.pth | 下载权重文件 | +| 开源代码引入 | https://github.com/huggingface/pytorch-image-models/blob/d584e7f617a4d0f1a0b4838227bd1f8852dfa236/timm/models/xception_aligned.py | GhostNet/timm/models/xception_aligned.py | https://github.com/rwightman/pytorch-image-models/releases/download/v0.1-weights/tf_xception_71-8eec7df1.pth | 下载权重文件 | diff --git a/PyTorch/contrib/cv/classification/GhostNet/timm/models/efficientnet.py b/PyTorch/contrib/cv/classification/GhostNet/timm/models/efficientnet.py index f7b3abe5f2..1c1e049e35 100644 --- a/PyTorch/contrib/cv/classification/GhostNet/timm/models/efficientnet.py +++ b/PyTorch/contrib/cv/classification/GhostNet/timm/models/efficientnet.py @@ -24,6 +24,7 @@ An implementation of EfficienNet that covers variety of related models with effi Hacked together by / Copyright 2020 Ross Wightman """ +import os import torch import torch.nn as nn import torch.nn.functional as F @@ -40,6 +41,12 @@ from .registry import register_model __all__ = ['EfficientNet'] +cur_path = os.path.abspath(os.path.dirname(__file__)) +with open(os.path.join(cur_path, 'url.ini'), 'r') as f: + content = f.read() + efficientnet_el = content.split('efficientnet_el=')[1].split('\n')[0] + efficientnet_es_pruned75 = content.split('efficientnet_es_pruned75=')[1].split('\n')[0] + efficientnet_el_pruned70 = content.split('efficientnet_el_pruned70=')[1].split('\n')[0] def _cfg(url='', **kwargs): return { @@ -117,13 +124,13 @@ default_cfgs = { url='https://github.com/rwightman/pytorch-image-models/releases/download/v0.1-weights/efficientnet_em_ra2-66250f76.pth', input_size=(3, 240, 240), pool_size=(8, 8), crop_pct=0.882), 'efficientnet_el': _cfg( - url='https://github.com/DeGirum/pruned-models/releases/download/efficientnet_v1.0/efficientnet_el.pth', + url=efficientnet_el, input_size=(3, 300, 300), pool_size=(10, 10), crop_pct=0.904), 'efficientnet_es_pruned': _cfg( - url='https://github.com/DeGirum/pruned-models/releases/download/efficientnet_v1.0/efficientnet_es_pruned75.pth'), + url=efficientnet_es_pruned75), 'efficientnet_el_pruned': _cfg( - url='https://github.com/DeGirum/pruned-models/releases/download/efficientnet_v1.0/efficientnet_el_pruned70.pth', + url=efficientnet_el_pruned70, input_size=(3, 300, 300), pool_size=(10, 10), crop_pct=0.904), 'efficientnet_cc_b0_4e': _cfg(url=''), diff --git a/PyTorch/contrib/cv/classification/GhostNet/timm/models/nfnet.py b/PyTorch/contrib/cv/classification/GhostNet/timm/models/nfnet.py index c037c7ec9c..383687fc81 100644 --- a/PyTorch/contrib/cv/classification/GhostNet/timm/models/nfnet.py +++ b/PyTorch/contrib/cv/classification/GhostNet/timm/models/nfnet.py @@ -16,6 +16,7 @@ Status: Hacked together by / copyright Ross Wightman, 2021. """ +import os import math from dataclasses import dataclass, field from collections import OrderedDict @@ -31,6 +32,10 @@ from .registry import register_model from .layers import ClassifierHead, DropPath, AvgPool2dSame, ScaledStdConv2d, ScaledStdConv2dSame,\ get_act_layer, get_act_fn, get_attn, make_divisible +cur_path = os.path.abspath(os.path.dirname(__file__)) +with open(os.path.join(cur_path, 'url.ini'), 'r') as f: + content = f.read() + ecanfnet_l0_ra2 = content.split('ecanfnet_l0_ra2=')[1].split('\n')[0] def _dcfg(url='', **kwargs): return { @@ -105,7 +110,7 @@ default_cfgs = dict( nfnet_l0b=_dcfg( url='', pool_size=(7, 7), input_size=(3, 224, 224), test_input_size=(3, 288, 288)), eca_nfnet_l0=_dcfg( - url='https://github.com/rwightman/pytorch-image-models/releases/download/v0.1-weights/ecanfnet_l0_ra2-e3e9ac50.pth', + url=ecanfnet_l0_ra2, hf_hub='timm/eca_nfnet_l0', pool_size=(7, 7), input_size=(3, 224, 224), test_input_size=(3, 288, 288), crop_pct=1.0), diff --git a/PyTorch/contrib/cv/classification/GhostNet/url.ini b/PyTorch/contrib/cv/classification/GhostNet/url.ini new file mode 100644 index 0000000000..a91eed4809 --- /dev/null +++ b/PyTorch/contrib/cv/classification/GhostNet/url.ini @@ -0,0 +1,4 @@ +efficientnet_el=https://github.com/DeGirum/pruned-models/releases/download/efficientnet_v1.0/efficientnet_el.pth +efficientnet_es_pruned75=https://github.com/DeGirum/pruned-models/releases/download/efficientnet_v1.0/efficientnet_es_pruned75.pth +efficientnet_el_pruned70=https://github.com/DeGirum/pruned-models/releases/download/efficientnet_v1.0/efficientnet_el_pruned70.pth +ecanfnet_l0_ra2=https://github.com/rwightman/pytorch-image-models/releases/download/v0.1-weights/ecanfnet_l0_ra2-e3e9ac50.pth \ No newline at end of file -- Gitee From 07e0a37b1ab0be3f1462bae01de4e3db4a1d1e0a Mon Sep 17 00:00:00 2001 From: Vvv6 <286738135@qq.com> Date: Fri, 21 Jul 2023 11:11:44 +0800 Subject: [PATCH 2/4] =?UTF-8?q?=E3=80=90pytorch=E3=80=91=E3=80=90contrib?= =?UTF-8?q?=E3=80=91=E3=80=90cv=E3=80=91=20GhostNet=20=E6=A8=A1=E5=9E=8B?= =?UTF-8?q?=E5=85=AC=E7=BD=91=E5=9C=B0=E5=9D=80=E6=95=B4=E6=94=B9=EF=BC=8C?= =?UTF-8?q?=E6=B7=BB=E5=8A=A0license?= MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit --- .../GhostNet/timm/models/efficientnet.py | 38 +++++++------------ .../GhostNet/timm/models/nfnet.py | 30 +++++++-------- 2 files changed, 26 insertions(+), 42 deletions(-) diff --git a/PyTorch/contrib/cv/classification/GhostNet/timm/models/efficientnet.py b/PyTorch/contrib/cv/classification/GhostNet/timm/models/efficientnet.py index 1c1e049e35..e28aa0ff21 100644 --- a/PyTorch/contrib/cv/classification/GhostNet/timm/models/efficientnet.py +++ b/PyTorch/contrib/cv/classification/GhostNet/timm/models/efficientnet.py @@ -1,29 +1,17 @@ -""" PyTorch EfficientNet Family +# Copyright 2021 Huawei Technologies Co., Ltd +# +# Licensed under the BSD 3-Clause License (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# https://opensource.org/licenses/BSD-3-Clause +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. -An implementation of EfficienNet that covers variety of related models with efficient architectures: - -* EfficientNet (B0-B8, L2 + Tensorflow pretrained AutoAug/RandAug/AdvProp/NoisyStudent weight ports) - - EfficientNet: Rethinking Model Scaling for CNNs - https://arxiv.org/abs/1905.11946 - - CondConv: Conditionally Parameterized Convolutions for Efficient Inference - https://arxiv.org/abs/1904.04971 - - Adversarial Examples Improve Image Recognition - https://arxiv.org/abs/1911.09665 - - Self-training with Noisy Student improves ImageNet classification - https://arxiv.org/abs/1911.04252 - -* MixNet (Small, Medium, and Large) - - MixConv: Mixed Depthwise Convolutional Kernels - https://arxiv.org/abs/1907.09595 - -* MNasNet B1, A1 (SE), Small - - MnasNet: Platform-Aware Neural Architecture Search for Mobile - https://arxiv.org/abs/1807.11626 - -* FBNet-C - - FBNet: Hardware-Aware Efficient ConvNet Design via Differentiable NAS - https://arxiv.org/abs/1812.03443 - -* Single-Path NAS Pixel1 - - Single-Path NAS: Designing Hardware-Efficient ConvNets - https://arxiv.org/abs/1904.02877 - -* And likely more... - -Hacked together by / Copyright 2020 Ross Wightman -""" import os import torch import torch.nn as nn diff --git a/PyTorch/contrib/cv/classification/GhostNet/timm/models/nfnet.py b/PyTorch/contrib/cv/classification/GhostNet/timm/models/nfnet.py index 383687fc81..50adeb77ee 100644 --- a/PyTorch/contrib/cv/classification/GhostNet/timm/models/nfnet.py +++ b/PyTorch/contrib/cv/classification/GhostNet/timm/models/nfnet.py @@ -1,21 +1,17 @@ -""" Normalization Free Nets. NFNet, NF-RegNet, NF-ResNet (pre-activation) Models +# Copyright 2021 Huawei Technologies Co., Ltd +# +# Licensed under the BSD 3-Clause License (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# https://opensource.org/licenses/BSD-3-Clause +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. -Paper: `Characterizing signal propagation to close the performance gap in unnormalized ResNets` - - https://arxiv.org/abs/2101.08692 - -Paper: `High-Performance Large-Scale Image Recognition Without Normalization` - - https://arxiv.org/abs/2102.06171 - -Official Deepmind JAX code: https://github.com/deepmind/deepmind-research/tree/master/nfnets - -Status: -* These models are a work in progress, experiments ongoing. -* Pretrained weights for two models so far, more to come. -* Model details updated to closer match official JAX code now that it's released -* NF-ResNet, NF-RegNet-B, and NFNet-F models supported - -Hacked together by / copyright Ross Wightman, 2021. -""" import os import math from dataclasses import dataclass, field -- Gitee From 419b8167a1ac2dd569c97919e83ac843bd87a46b Mon Sep 17 00:00:00 2001 From: Vvv6 <286738135@qq.com> Date: Fri, 21 Jul 2023 15:02:55 +0800 Subject: [PATCH 3/4] =?UTF-8?q?=E3=80=90pytorch=E3=80=91=E3=80=90contrib?= =?UTF-8?q?=E3=80=91=E3=80=90cv=E3=80=91=20GhostNet=20=E6=A8=A1=E5=9E=8B?= =?UTF-8?q?=E5=85=AC=E7=BD=91=E5=9C=B0=E5=9D=80=E6=95=B4=E6=94=B9=EF=BC=8C?= =?UTF-8?q?=E4=BF=AE=E6=94=B9codecheck?= MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit --- .../GhostNet/timm/models/efficientnet.py | 201 ++++++++++++------ 1 file changed, 134 insertions(+), 67 deletions(-) diff --git a/PyTorch/contrib/cv/classification/GhostNet/timm/models/efficientnet.py b/PyTorch/contrib/cv/classification/GhostNet/timm/models/efficientnet.py index e28aa0ff21..123dfc09f9 100644 --- a/PyTorch/contrib/cv/classification/GhostNet/timm/models/efficientnet.py +++ b/PyTorch/contrib/cv/classification/GhostNet/timm/models/efficientnet.py @@ -61,37 +61,49 @@ default_cfgs = { 'mnasnet_small': _cfg(url=''), 'mobilenetv2_100': _cfg( - url='https://github.com/rwightman/pytorch-image-models/releases/download/v0.1-weights/mobilenetv2_100_ra-b33bc2c4.pth'), + url='https://github.com/rwightman/pytorch-image-models/releases/download/v0.1-weights/' + 'mobilenetv2_100_ra-b33bc2c4.pth'), 'mobilenetv2_110d': _cfg( - url='https://github.com/rwightman/pytorch-image-models/releases/download/v0.1-weights/mobilenetv2_110d_ra-77090ade.pth'), + url='https://github.com/rwightman/pytorch-image-models/releases/download/v0.1-weights/' + 'mobilenetv2_110d_ra-77090ade.pth'), 'mobilenetv2_120d': _cfg( - url='https://github.com/rwightman/pytorch-image-models/releases/download/v0.1-weights/mobilenetv2_120d_ra-5987e2ed.pth'), + url='https://github.com/rwightman/pytorch-image-models/releases/download/v0.1-weights/' + 'mobilenetv2_120d_ra-5987e2ed.pth'), 'mobilenetv2_140': _cfg( - url='https://github.com/rwightman/pytorch-image-models/releases/download/v0.1-weights/mobilenetv2_140_ra-21a4e913.pth'), + url='https://github.com/rwightman/pytorch-image-models/releases/download/v0.1-weights/' + 'mobilenetv2_140_ra-21a4e913.pth'), 'fbnetc_100': _cfg( - url='https://github.com/rwightman/pytorch-image-models/releases/download/v0.1-weights/fbnetc_100-c345b898.pth', + url='https://github.com/rwightman/pytorch-image-models/releases/download/v0.1-weights/' + 'fbnetc_100-c345b898.pth', interpolation='bilinear'), 'spnasnet_100': _cfg( - url='https://github.com/rwightman/pytorch-image-models/releases/download/v0.1-weights/spnasnet_100-048bc3f4.pth', + url='https://github.com/rwightman/pytorch-image-models/releases/download/v0.1-weights/' + 'spnasnet_100-048bc3f4.pth', interpolation='bilinear'), 'efficientnet_b0': _cfg( - url='https://github.com/rwightman/pytorch-image-models/releases/download/v0.1-weights/efficientnet_b0_ra-3dd342df.pth'), + url='https://github.com/rwightman/pytorch-image-models/releases/download/v0.1-weights/' + 'efficientnet_b0_ra-3dd342df.pth'), 'efficientnet_b1': _cfg( - url='https://github.com/rwightman/pytorch-image-models/releases/download/v0.1-weights/efficientnet_b1-533bc792.pth', + url='https://github.com/rwightman/pytorch-image-models/releases/download/v0.1-weights/' + 'efficientnet_b1-533bc792.pth', input_size=(3, 240, 240), pool_size=(8, 8)), 'efficientnet_b2': _cfg( - url='https://github.com/rwightman/pytorch-image-models/releases/download/v0.1-weights/efficientnet_b2_ra-bcdf34b7.pth', + url='https://github.com/rwightman/pytorch-image-models/releases/download/v0.1-weights/' + 'efficientnet_b2_ra-bcdf34b7.pth', input_size=(3, 260, 260), pool_size=(9, 9)), 'efficientnet_b2a': _cfg( - url='https://github.com/rwightman/pytorch-image-models/releases/download/v0.1-weights/efficientnet_b2_ra-bcdf34b7.pth', + url='https://github.com/rwightman/pytorch-image-models/releases/download/v0.1-weights/' + 'efficientnet_b2_ra-bcdf34b7.pth', input_size=(3, 288, 288), pool_size=(9, 9), crop_pct=1.0), 'efficientnet_b3': _cfg( - url='https://github.com/rwightman/pytorch-image-models/releases/download/v0.1-weights/efficientnet_b3_ra2-cf984f9c.pth', + url='https://github.com/rwightman/pytorch-image-models/releases/download/v0.1-weights/' + 'efficientnet_b3_ra2-cf984f9c.pth', input_size=(3, 300, 300), pool_size=(10, 10), crop_pct=0.904), 'efficientnet_b3a': _cfg( - url='https://github.com/rwightman/pytorch-image-models/releases/download/v0.1-weights/efficientnet_b3_ra2-cf984f9c.pth', + url='https://github.com/rwightman/pytorch-image-models/releases/download/v0.1-weights/' + 'efficientnet_b3_ra2-cf984f9c.pth', input_size=(3, 320, 320), pool_size=(10, 10), crop_pct=1.0), 'efficientnet_b4': _cfg( url='', input_size=(3, 380, 380), pool_size=(12, 12), crop_pct=0.922), @@ -107,9 +119,11 @@ default_cfgs = { url='', input_size=(3, 800, 800), pool_size=(25, 25), crop_pct=0.961), 'efficientnet_es': _cfg( - url='https://github.com/rwightman/pytorch-image-models/releases/download/v0.1-weights/efficientnet_es_ra-f111e99c.pth'), + url='https://github.com/rwightman/pytorch-image-models/releases/download/v0.1-weights/' + 'efficientnet_es_ra-f111e99c.pth'), 'efficientnet_em': _cfg( - url='https://github.com/rwightman/pytorch-image-models/releases/download/v0.1-weights/efficientnet_em_ra2-66250f76.pth', + url='https://github.com/rwightman/pytorch-image-models/releases/download/v0.1-weights/' + 'efficientnet_em_ra2-66250f76.pth', input_size=(3, 240, 240), pool_size=(8, 8), crop_pct=0.882), 'efficientnet_el': _cfg( url=efficientnet_el, @@ -126,7 +140,8 @@ default_cfgs = { 'efficientnet_cc_b1_8e': _cfg(url='', input_size=(3, 240, 240), pool_size=(8, 8), crop_pct=0.882), 'efficientnet_lite0': _cfg( - url='https://github.com/rwightman/pytorch-image-models/releases/download/v0.1-weights/efficientnet_lite0_ra-37913777.pth'), + url='https://github.com/rwightman/pytorch-image-models/releases/download/v0.1-weights/' + 'efficientnet_lite0_ra-37913777.pth'), 'efficientnet_lite1': _cfg( url='', input_size=(3, 240, 240), pool_size=(8, 8), crop_pct=0.882), @@ -140,157 +155,202 @@ default_cfgs = { url='', input_size=(3, 380, 380), pool_size=(12, 12), crop_pct=0.922), 'efficientnet_b1_pruned': _cfg( - url='https://imvl-automl-sh.oss-cn-shanghai.aliyuncs.com/darts/hyperml/hyperml/job_45403/outputs/effnetb1_pruned_9ebb3fe6.pth', - input_size=(3, 240, 240), pool_size=(8, 8), crop_pct=0.882, mean=IMAGENET_INCEPTION_MEAN, std=IMAGENET_INCEPTION_STD), + url='https://imvl-automl-sh.oss-cn-shanghai.aliyuncs.com/darts/hyperml/hyperml/job_45403/outputs/' + 'effnetb1_pruned_9ebb3fe6.pth', + input_size=(3, 240, 240), pool_size=(8, 8), crop_pct=0.882, + mean=IMAGENET_INCEPTION_MEAN, std=IMAGENET_INCEPTION_STD), 'efficientnet_b2_pruned': _cfg( - url='https://imvl-automl-sh.oss-cn-shanghai.aliyuncs.com/darts/hyperml/hyperml/job_45403/outputs/effnetb2_pruned_203f55bc.pth', - input_size=(3, 260, 260), pool_size=(9, 9), crop_pct=0.890, mean=IMAGENET_INCEPTION_MEAN, std=IMAGENET_INCEPTION_STD), + url='https://imvl-automl-sh.oss-cn-shanghai.aliyuncs.com/darts/hyperml/hyperml/job_45403/outputs/' + 'effnetb2_pruned_203f55bc.pth', + input_size=(3, 260, 260), pool_size=(9, 9), crop_pct=0.890, + mean=IMAGENET_INCEPTION_MEAN, std=IMAGENET_INCEPTION_STD), 'efficientnet_b3_pruned': _cfg( - url='https://imvl-automl-sh.oss-cn-shanghai.aliyuncs.com/darts/hyperml/hyperml/job_45403/outputs/effnetb3_pruned_5abcc29f.pth', - input_size=(3, 300, 300), pool_size=(10, 10), crop_pct=0.904, mean=IMAGENET_INCEPTION_MEAN, std=IMAGENET_INCEPTION_STD), + url='https://imvl-automl-sh.oss-cn-shanghai.aliyuncs.com/darts/hyperml/hyperml/job_45403/outputs/' + 'effnetb3_pruned_5abcc29f.pth', + input_size=(3, 300, 300), pool_size=(10, 10), crop_pct=0.904, + mean=IMAGENET_INCEPTION_MEAN, std=IMAGENET_INCEPTION_STD), 'tf_efficientnet_b0': _cfg( - url='https://github.com/rwightman/pytorch-image-models/releases/download/v0.1-weights/tf_efficientnet_b0_aa-827b6e33.pth', + url='https://github.com/rwightman/pytorch-image-models/releases/download/v0.1-weights/' + 'tf_efficientnet_b0_aa-827b6e33.pth', input_size=(3, 224, 224)), 'tf_efficientnet_b1': _cfg( - url='https://github.com/rwightman/pytorch-image-models/releases/download/v0.1-weights/tf_efficientnet_b1_aa-ea7a6ee0.pth', + url='https://github.com/rwightman/pytorch-image-models/releases/download/v0.1-weights/' + 'tf_efficientnet_b1_aa-ea7a6ee0.pth', input_size=(3, 240, 240), pool_size=(8, 8), crop_pct=0.882), 'tf_efficientnet_b2': _cfg( - url='https://github.com/rwightman/pytorch-image-models/releases/download/v0.1-weights/tf_efficientnet_b2_aa-60c94f97.pth', + url='https://github.com/rwightman/pytorch-image-models/releases/download/v0.1-weights/' + 'tf_efficientnet_b2_aa-60c94f97.pth', input_size=(3, 260, 260), pool_size=(9, 9), crop_pct=0.890), 'tf_efficientnet_b3': _cfg( - url='https://github.com/rwightman/pytorch-image-models/releases/download/v0.1-weights/tf_efficientnet_b3_aa-84b4657e.pth', + url='https://github.com/rwightman/pytorch-image-models/releases/download/v0.1-weights/' + 'tf_efficientnet_b3_aa-84b4657e.pth', input_size=(3, 300, 300), pool_size=(10, 10), crop_pct=0.904), 'tf_efficientnet_b4': _cfg( - url='https://github.com/rwightman/pytorch-image-models/releases/download/v0.1-weights/tf_efficientnet_b4_aa-818f208c.pth', + url='https://github.com/rwightman/pytorch-image-models/releases/download/v0.1-weights/' + 'tf_efficientnet_b4_aa-818f208c.pth', input_size=(3, 380, 380), pool_size=(12, 12), crop_pct=0.922), 'tf_efficientnet_b5': _cfg( - url='https://github.com/rwightman/pytorch-image-models/releases/download/v0.1-weights/tf_efficientnet_b5_ra-9a3e5369.pth', + url='https://github.com/rwightman/pytorch-image-models/releases/download/v0.1-weights/' + 'tf_efficientnet_b5_ra-9a3e5369.pth', input_size=(3, 456, 456), pool_size=(15, 15), crop_pct=0.934), 'tf_efficientnet_b6': _cfg( - url='https://github.com/rwightman/pytorch-image-models/releases/download/v0.1-weights/tf_efficientnet_b6_aa-80ba17e4.pth', + url='https://github.com/rwightman/pytorch-image-models/releases/download/v0.1-weights/' + 'tf_efficientnet_b6_aa-80ba17e4.pth', input_size=(3, 528, 528), pool_size=(17, 17), crop_pct=0.942), 'tf_efficientnet_b7': _cfg( - url='https://github.com/rwightman/pytorch-image-models/releases/download/v0.1-weights/tf_efficientnet_b7_ra-6c08e654.pth', + url='https://github.com/rwightman/pytorch-image-models/releases/download/v0.1-weights/' + 'tf_efficientnet_b7_ra-6c08e654.pth', input_size=(3, 600, 600), pool_size=(19, 19), crop_pct=0.949), 'tf_efficientnet_b8': _cfg( - url='https://github.com/rwightman/pytorch-image-models/releases/download/v0.1-weights/tf_efficientnet_b8_ra-572d5dd9.pth', + url='https://github.com/rwightman/pytorch-image-models/releases/download/v0.1-weights/' + 'tf_efficientnet_b8_ra-572d5dd9.pth', input_size=(3, 672, 672), pool_size=(21, 21), crop_pct=0.954), 'tf_efficientnet_b0_ap': _cfg( - url='https://github.com/rwightman/pytorch-image-models/releases/download/v0.1-weights/tf_efficientnet_b0_ap-f262efe1.pth', + url='https://github.com/rwightman/pytorch-image-models/releases/download/v0.1-weights/' + 'tf_efficientnet_b0_ap-f262efe1.pth', mean=IMAGENET_INCEPTION_MEAN, std=IMAGENET_INCEPTION_STD, input_size=(3, 224, 224)), 'tf_efficientnet_b1_ap': _cfg( - url='https://github.com/rwightman/pytorch-image-models/releases/download/v0.1-weights/tf_efficientnet_b1_ap-44ef0a3d.pth', + url='https://github.com/rwightman/pytorch-image-models/releases/download/v0.1-weights/' + 'tf_efficientnet_b1_ap-44ef0a3d.pth', mean=IMAGENET_INCEPTION_MEAN, std=IMAGENET_INCEPTION_STD, input_size=(3, 240, 240), pool_size=(8, 8), crop_pct=0.882), 'tf_efficientnet_b2_ap': _cfg( - url='https://github.com/rwightman/pytorch-image-models/releases/download/v0.1-weights/tf_efficientnet_b2_ap-2f8e7636.pth', + url='https://github.com/rwightman/pytorch-image-models/releases/download/v0.1-weights/' + 'tf_efficientnet_b2_ap-2f8e7636.pth', mean=IMAGENET_INCEPTION_MEAN, std=IMAGENET_INCEPTION_STD, input_size=(3, 260, 260), pool_size=(9, 9), crop_pct=0.890), 'tf_efficientnet_b3_ap': _cfg( - url='https://github.com/rwightman/pytorch-image-models/releases/download/v0.1-weights/tf_efficientnet_b3_ap-aad25bdd.pth', + url='https://github.com/rwightman/pytorch-image-models/releases/download/v0.1-weights/' + 'tf_efficientnet_b3_ap-aad25bdd.pth', mean=IMAGENET_INCEPTION_MEAN, std=IMAGENET_INCEPTION_STD, input_size=(3, 300, 300), pool_size=(10, 10), crop_pct=0.904), 'tf_efficientnet_b4_ap': _cfg( - url='https://github.com/rwightman/pytorch-image-models/releases/download/v0.1-weights/tf_efficientnet_b4_ap-dedb23e6.pth', + url='https://github.com/rwightman/pytorch-image-models/releases/download/v0.1-weights/' + 'tf_efficientnet_b4_ap-dedb23e6.pth', mean=IMAGENET_INCEPTION_MEAN, std=IMAGENET_INCEPTION_STD, input_size=(3, 380, 380), pool_size=(12, 12), crop_pct=0.922), 'tf_efficientnet_b5_ap': _cfg( - url='https://github.com/rwightman/pytorch-image-models/releases/download/v0.1-weights/tf_efficientnet_b5_ap-9e82fae8.pth', + url='https://github.com/rwightman/pytorch-image-models/releases/download/v0.1-weights/' + 'tf_efficientnet_b5_ap-9e82fae8.pth', mean=IMAGENET_INCEPTION_MEAN, std=IMAGENET_INCEPTION_STD, input_size=(3, 456, 456), pool_size=(15, 15), crop_pct=0.934), 'tf_efficientnet_b6_ap': _cfg( - url='https://github.com/rwightman/pytorch-image-models/releases/download/v0.1-weights/tf_efficientnet_b6_ap-4ffb161f.pth', + url='https://github.com/rwightman/pytorch-image-models/releases/download/v0.1-weights/' + 'tf_efficientnet_b6_ap-4ffb161f.pth', mean=IMAGENET_INCEPTION_MEAN, std=IMAGENET_INCEPTION_STD, input_size=(3, 528, 528), pool_size=(17, 17), crop_pct=0.942), 'tf_efficientnet_b7_ap': _cfg( - url='https://github.com/rwightman/pytorch-image-models/releases/download/v0.1-weights/tf_efficientnet_b7_ap-ddb28fec.pth', + url='https://github.com/rwightman/pytorch-image-models/releases/download/v0.1-weights/' + 'tf_efficientnet_b7_ap-ddb28fec.pth', mean=IMAGENET_INCEPTION_MEAN, std=IMAGENET_INCEPTION_STD, input_size=(3, 600, 600), pool_size=(19, 19), crop_pct=0.949), 'tf_efficientnet_b8_ap': _cfg( - url='https://github.com/rwightman/pytorch-image-models/releases/download/v0.1-weights/tf_efficientnet_b8_ap-00e169fa.pth', + url='https://github.com/rwightman/pytorch-image-models/releases/download/v0.1-weights/' + 'tf_efficientnet_b8_ap-00e169fa.pth', mean=IMAGENET_INCEPTION_MEAN, std=IMAGENET_INCEPTION_STD, input_size=(3, 672, 672), pool_size=(21, 21), crop_pct=0.954), 'tf_efficientnet_b0_ns': _cfg( - url='https://github.com/rwightman/pytorch-image-models/releases/download/v0.1-weights/tf_efficientnet_b0_ns-c0e6a31c.pth', + url='https://github.com/rwightman/pytorch-image-models/releases/download/v0.1-weights/' + 'tf_efficientnet_b0_ns-c0e6a31c.pth', input_size=(3, 224, 224)), 'tf_efficientnet_b1_ns': _cfg( - url='https://github.com/rwightman/pytorch-image-models/releases/download/v0.1-weights/tf_efficientnet_b1_ns-99dd0c41.pth', + url='https://github.com/rwightman/pytorch-image-models/releases/download/v0.1-weights/' + 'tf_efficientnet_b1_ns-99dd0c41.pth', input_size=(3, 240, 240), pool_size=(8, 8), crop_pct=0.882), 'tf_efficientnet_b2_ns': _cfg( - url='https://github.com/rwightman/pytorch-image-models/releases/download/v0.1-weights/tf_efficientnet_b2_ns-00306e48.pth', + url='https://github.com/rwightman/pytorch-image-models/releases/download/v0.1-weights/' + 'tf_efficientnet_b2_ns-00306e48.pth', input_size=(3, 260, 260), pool_size=(9, 9), crop_pct=0.890), 'tf_efficientnet_b3_ns': _cfg( - url='https://github.com/rwightman/pytorch-image-models/releases/download/v0.1-weights/tf_efficientnet_b3_ns-9d44bf68.pth', + url='https://github.com/rwightman/pytorch-image-models/releases/download/v0.1-weights/' + 'tf_efficientnet_b3_ns-9d44bf68.pth', input_size=(3, 300, 300), pool_size=(10, 10), crop_pct=0.904), 'tf_efficientnet_b4_ns': _cfg( - url='https://github.com/rwightman/pytorch-image-models/releases/download/v0.1-weights/tf_efficientnet_b4_ns-d6313a46.pth', + url='https://github.com/rwightman/pytorch-image-models/releases/download/v0.1-weights/' + 'tf_efficientnet_b4_ns-d6313a46.pth', input_size=(3, 380, 380), pool_size=(12, 12), crop_pct=0.922), 'tf_efficientnet_b5_ns': _cfg( - url='https://github.com/rwightman/pytorch-image-models/releases/download/v0.1-weights/tf_efficientnet_b5_ns-6f26d0cf.pth', + url='https://github.com/rwightman/pytorch-image-models/releases/download/v0.1-weights/' + 'tf_efficientnet_b5_ns-6f26d0cf.pth', input_size=(3, 456, 456), pool_size=(15, 15), crop_pct=0.934), 'tf_efficientnet_b6_ns': _cfg( - url='https://github.com/rwightman/pytorch-image-models/releases/download/v0.1-weights/tf_efficientnet_b6_ns-51548356.pth', + url='https://github.com/rwightman/pytorch-image-models/releases/download/v0.1-weights/' + 'tf_efficientnet_b6_ns-51548356.pth', input_size=(3, 528, 528), pool_size=(17, 17), crop_pct=0.942), 'tf_efficientnet_b7_ns': _cfg( - url='https://github.com/rwightman/pytorch-image-models/releases/download/v0.1-weights/tf_efficientnet_b7_ns-1dbc32de.pth', + url='https://github.com/rwightman/pytorch-image-models/releases/download/v0.1-weights/' + 'tf_efficientnet_b7_ns-1dbc32de.pth', input_size=(3, 600, 600), pool_size=(19, 19), crop_pct=0.949), 'tf_efficientnet_l2_ns_475': _cfg( - url='https://github.com/rwightman/pytorch-image-models/releases/download/v0.1-weights/tf_efficientnet_l2_ns_475-bebbd00a.pth', + url='https://github.com/rwightman/pytorch-image-models/releases/download/v0.1-weights/' + 'tf_efficientnet_l2_ns_475-bebbd00a.pth', input_size=(3, 475, 475), pool_size=(15, 15), crop_pct=0.936), 'tf_efficientnet_l2_ns': _cfg( - url='https://github.com/rwightman/pytorch-image-models/releases/download/v0.1-weights/tf_efficientnet_l2_ns-df73bb44.pth', + url='https://github.com/rwightman/pytorch-image-models/releases/download/v0.1-weights/' + 'tf_efficientnet_l2_ns-df73bb44.pth', input_size=(3, 800, 800), pool_size=(25, 25), crop_pct=0.96), 'tf_efficientnet_es': _cfg( - url='https://github.com/rwightman/pytorch-image-models/releases/download/v0.1-weights/tf_efficientnet_es-ca1afbfe.pth', + url='https://github.com/rwightman/pytorch-image-models/releases/download/v0.1-weights/' + 'tf_efficientnet_es-ca1afbfe.pth', mean=(0.5, 0.5, 0.5), std=(0.5, 0.5, 0.5), input_size=(3, 224, 224), ), 'tf_efficientnet_em': _cfg( - url='https://github.com/rwightman/pytorch-image-models/releases/download/v0.1-weights/tf_efficientnet_em-e78cfe58.pth', + url='https://github.com/rwightman/pytorch-image-models/releases/download/v0.1-weights/' + 'tf_efficientnet_em-e78cfe58.pth', mean=(0.5, 0.5, 0.5), std=(0.5, 0.5, 0.5), input_size=(3, 240, 240), pool_size=(8, 8), crop_pct=0.882), 'tf_efficientnet_el': _cfg( - url='https://github.com/rwightman/pytorch-image-models/releases/download/v0.1-weights/tf_efficientnet_el-5143854e.pth', + url='https://github.com/rwightman/pytorch-image-models/releases/download/v0.1-weights/' + 'tf_efficientnet_el-5143854e.pth', mean=(0.5, 0.5, 0.5), std=(0.5, 0.5, 0.5), input_size=(3, 300, 300), pool_size=(10, 10), crop_pct=0.904), 'tf_efficientnet_cc_b0_4e': _cfg( - url='https://github.com/rwightman/pytorch-image-models/releases/download/v0.1-weights/tf_efficientnet_cc_b0_4e-4362b6b2.pth', + url='https://github.com/rwightman/pytorch-image-models/releases/download/v0.1-weights/' + 'tf_efficientnet_cc_b0_4e-4362b6b2.pth', mean=IMAGENET_INCEPTION_MEAN, std=IMAGENET_INCEPTION_STD), 'tf_efficientnet_cc_b0_8e': _cfg( - url='https://github.com/rwightman/pytorch-image-models/releases/download/v0.1-weights/tf_efficientnet_cc_b0_8e-66184a25.pth', + url='https://github.com/rwightman/pytorch-image-models/releases/download/v0.1-weights/' + 'tf_efficientnet_cc_b0_8e-66184a25.pth', mean=IMAGENET_INCEPTION_MEAN, std=IMAGENET_INCEPTION_STD), 'tf_efficientnet_cc_b1_8e': _cfg( - url='https://github.com/rwightman/pytorch-image-models/releases/download/v0.1-weights/tf_efficientnet_cc_b1_8e-f7c79ae1.pth', + url='https://github.com/rwightman/pytorch-image-models/releases/download/v0.1-weights/' + 'tf_efficientnet_cc_b1_8e-f7c79ae1.pth', mean=IMAGENET_INCEPTION_MEAN, std=IMAGENET_INCEPTION_STD, input_size=(3, 240, 240), pool_size=(8, 8), crop_pct=0.882), 'tf_efficientnet_lite0': _cfg( - url='https://github.com/rwightman/pytorch-image-models/releases/download/v0.1-weights/tf_efficientnet_lite0-0aa007d2.pth', + url='https://github.com/rwightman/pytorch-image-models/releases/download/v0.1-weights/' + 'tf_efficientnet_lite0-0aa007d2.pth', mean=(0.5, 0.5, 0.5), std=(0.5, 0.5, 0.5), interpolation='bicubic', # should be bilinear but bicubic better match for TF bilinear at low res ), 'tf_efficientnet_lite1': _cfg( - url='https://github.com/rwightman/pytorch-image-models/releases/download/v0.1-weights/tf_efficientnet_lite1-bde8b488.pth', + url='https://github.com/rwightman/pytorch-image-models/releases/download/v0.1-weights/' + 'tf_efficientnet_lite1-bde8b488.pth', mean=(0.5, 0.5, 0.5), std=(0.5, 0.5, 0.5), input_size=(3, 240, 240), pool_size=(8, 8), crop_pct=0.882, interpolation='bicubic', # should be bilinear but bicubic better match for TF bilinear at low res ), 'tf_efficientnet_lite2': _cfg( - url='https://github.com/rwightman/pytorch-image-models/releases/download/v0.1-weights/tf_efficientnet_lite2-dcccb7df.pth', + url='https://github.com/rwightman/pytorch-image-models/releases/download/v0.1-weights/' + 'tf_efficientnet_lite2-dcccb7df.pth', mean=(0.5, 0.5, 0.5), std=(0.5, 0.5, 0.5), input_size=(3, 260, 260), pool_size=(9, 9), crop_pct=0.890, interpolation='bicubic', # should be bilinear but bicubic better match for TF bilinear at low res ), 'tf_efficientnet_lite3': _cfg( - url='https://github.com/rwightman/pytorch-image-models/releases/download/v0.1-weights/tf_efficientnet_lite3-b733e338.pth', + url='https://github.com/rwightman/pytorch-image-models/releases/download/v0.1-weights/' + 'tf_efficientnet_lite3-b733e338.pth', mean=(0.5, 0.5, 0.5), std=(0.5, 0.5, 0.5), input_size=(3, 300, 300), pool_size=(10, 10), crop_pct=0.904, interpolation='bilinear'), 'tf_efficientnet_lite4': _cfg( - url='https://github.com/rwightman/pytorch-image-models/releases/download/v0.1-weights/tf_efficientnet_lite4-741542c3.pth', + url='https://github.com/rwightman/pytorch-image-models/releases/download/v0.1-weights/' + 'tf_efficientnet_lite4-741542c3.pth', mean=(0.5, 0.5, 0.5), std=(0.5, 0.5, 0.5), input_size=(3, 380, 380), pool_size=(12, 12), crop_pct=0.920, interpolation='bilinear'), @@ -301,15 +361,19 @@ default_cfgs = { 'mixnet_l': _cfg( url='https://github.com/rwightman/pytorch-image-models/releases/download/v0.1-weights/mixnet_l-5a9a2ed8.pth'), 'mixnet_xl': _cfg( - url='https://github.com/rwightman/pytorch-image-models/releases/download/v0.1-weights/mixnet_xl_ra-aac3c00c.pth'), + url='https://github.com/rwightman/pytorch-image-models/releases/download/v0.1-weights/' + 'mixnet_xl_ra-aac3c00c.pth'), 'mixnet_xxl': _cfg(), 'tf_mixnet_s': _cfg( - url='https://github.com/rwightman/pytorch-image-models/releases/download/v0.1-weights/tf_mixnet_s-89d3354b.pth'), + url='https://github.com/rwightman/pytorch-image-models/releases/download/v0.1-weights/' + 'tf_mixnet_s-89d3354b.pth'), 'tf_mixnet_m': _cfg( - url='https://github.com/rwightman/pytorch-image-models/releases/download/v0.1-weights/tf_mixnet_m-0f4d8805.pth'), + url='https://github.com/rwightman/pytorch-image-models/releases/download/v0.1-weights/' + 'tf_mixnet_m-0f4d8805.pth'), 'tf_mixnet_l': _cfg( - url='https://github.com/rwightman/pytorch-image-models/releases/download/v0.1-weights/tf_mixnet_l-6c92e0c8.pth'), + url='https://github.com/rwightman/pytorch-image-models/releases/download/v0.1-weights/' + 'tf_mixnet_l-6c92e0c8.pth'), } _DEBUG = False @@ -607,7 +671,8 @@ def _gen_fbnetc(variant, channel_multiplier=1.0, pretrained=False, **kwargs): """ FBNet-C Paper: https://arxiv.org/abs/1812.03443 - Ref Impl: https://github.com/facebookresearch/maskrcnn-benchmark/blob/master/maskrcnn_benchmark/modeling/backbone/fbnet_modeldef.py + Ref Impl: https://github.com/facebookresearch/maskrcnn-benchmark/blob/master/maskrcnn_benchmark/ + modeling/backbone/fbnet_modeldef.py NOTE: the impl above does not relate to the 'C' variant here, that was derived from paper, it was used to confirm some building block details @@ -1119,7 +1184,8 @@ def efficientnet_es(pretrained=False, **kwargs): @register_model def efficientnet_es_pruned(pretrained=False, **kwargs): - """ EfficientNet-Edge Small Pruned. For more info: https://github.com/DeGirum/pruned-models/releases/tag/efficientnet_v1.0""" + """ EfficientNet-Edge Small Pruned. For more info: + https://github.com/DeGirum/pruned-models/releases/tag/efficientnet_v1.0""" model = _gen_efficientnet_edge( 'efficientnet_es_pruned', channel_multiplier=1.0, depth_multiplier=1.0, pretrained=pretrained, **kwargs) return model @@ -1141,7 +1207,8 @@ def efficientnet_el(pretrained=False, **kwargs): @register_model def efficientnet_el_pruned(pretrained=False, **kwargs): - """ EfficientNet-Edge-Large pruned. For more info: https://github.com/DeGirum/pruned-models/releases/tag/efficientnet_v1.0""" + """ EfficientNet-Edge-Large pruned. For more info: + https://github.com/DeGirum/pruned-models/releases/tag/efficientnet_v1.0""" model = _gen_efficientnet_edge( 'efficientnet_el_pruned', channel_multiplier=1.2, depth_multiplier=1.4, pretrained=pretrained, **kwargs) return model -- Gitee From 75547f0b54334a01a0b7c1497d032aa15d3340ce Mon Sep 17 00:00:00 2001 From: Vvv6 <286738135@qq.com> Date: Fri, 21 Jul 2023 16:52:43 +0800 Subject: [PATCH 4/4] =?UTF-8?q?=E3=80=90pytorch=E3=80=91=E3=80=90contrib?= =?UTF-8?q?=E3=80=91=E3=80=90cv=E3=80=91=20GhostNet=20=E6=A8=A1=E5=9E=8B?= =?UTF-8?q?=E5=85=AC=E7=BD=91=E5=9C=B0=E5=9D=80=E6=95=B4=E6=94=B9?= MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit --- .../GhostNet/timm/models/efficientnet.py | 6 ++-- .../GhostNet/timm/models/nfnet.py | 32 ++++++++++++------- 2 files changed, 25 insertions(+), 13 deletions(-) diff --git a/PyTorch/contrib/cv/classification/GhostNet/timm/models/efficientnet.py b/PyTorch/contrib/cv/classification/GhostNet/timm/models/efficientnet.py index 123dfc09f9..e9068ae0b8 100644 --- a/PyTorch/contrib/cv/classification/GhostNet/timm/models/efficientnet.py +++ b/PyTorch/contrib/cv/classification/GhostNet/timm/models/efficientnet.py @@ -1185,7 +1185,8 @@ def efficientnet_es(pretrained=False, **kwargs): @register_model def efficientnet_es_pruned(pretrained=False, **kwargs): """ EfficientNet-Edge Small Pruned. For more info: - https://github.com/DeGirum/pruned-models/releases/tag/efficientnet_v1.0""" + https://github.com/DeGirum/pruned-models/releases/tag/efficientnet_v1.0 + """ model = _gen_efficientnet_edge( 'efficientnet_es_pruned', channel_multiplier=1.0, depth_multiplier=1.0, pretrained=pretrained, **kwargs) return model @@ -1208,7 +1209,8 @@ def efficientnet_el(pretrained=False, **kwargs): @register_model def efficientnet_el_pruned(pretrained=False, **kwargs): """ EfficientNet-Edge-Large pruned. For more info: - https://github.com/DeGirum/pruned-models/releases/tag/efficientnet_v1.0""" + https://github.com/DeGirum/pruned-models/releases/tag/efficientnet_v1.0 + """ model = _gen_efficientnet_edge( 'efficientnet_el_pruned', channel_multiplier=1.2, depth_multiplier=1.4, pretrained=pretrained, **kwargs) return model diff --git a/PyTorch/contrib/cv/classification/GhostNet/timm/models/nfnet.py b/PyTorch/contrib/cv/classification/GhostNet/timm/models/nfnet.py index 50adeb77ee..f0319055ed 100644 --- a/PyTorch/contrib/cv/classification/GhostNet/timm/models/nfnet.py +++ b/PyTorch/contrib/cv/classification/GhostNet/timm/models/nfnet.py @@ -46,25 +46,32 @@ def _dcfg(url='', **kwargs): default_cfgs = dict( dm_nfnet_f0=_dcfg( - url='https://github.com/rwightman/pytorch-image-models/releases/download/v0.1-dnf-weights/dm_nfnet_f0-604f9c3a.pth', + url='https://github.com/rwightman/pytorch-image-models/releases/download/v0.1-dnf-weights/' + 'dm_nfnet_f0-604f9c3a.pth', pool_size=(6, 6), input_size=(3, 192, 192), test_input_size=(3, 256, 256), crop_pct=.9), dm_nfnet_f1=_dcfg( - url='https://github.com/rwightman/pytorch-image-models/releases/download/v0.1-dnf-weights/dm_nfnet_f1-fc540f82.pth', + url='https://github.com/rwightman/pytorch-image-models/releases/download/v0.1-dnf-weights/' + 'dm_nfnet_f1-fc540f82.pth', pool_size=(7, 7), input_size=(3, 224, 224), test_input_size=(3, 320, 320), crop_pct=0.91), dm_nfnet_f2=_dcfg( - url='https://github.com/rwightman/pytorch-image-models/releases/download/v0.1-dnf-weights/dm_nfnet_f2-89875923.pth', + url='https://github.com/rwightman/pytorch-image-models/releases/download/v0.1-dnf-weights/' + 'dm_nfnet_f2-89875923.pth', pool_size=(8, 8), input_size=(3, 256, 256), test_input_size=(3, 352, 352), crop_pct=0.92), dm_nfnet_f3=_dcfg( - url='https://github.com/rwightman/pytorch-image-models/releases/download/v0.1-dnf-weights/dm_nfnet_f3-d74ab3aa.pth', + url='https://github.com/rwightman/pytorch-image-models/releases/download/v0.1-dnf-weights/' + 'dm_nfnet_f3-d74ab3aa.pth', pool_size=(10, 10), input_size=(3, 320, 320), test_input_size=(3, 416, 416), crop_pct=0.94), dm_nfnet_f4=_dcfg( - url='https://github.com/rwightman/pytorch-image-models/releases/download/v0.1-dnf-weights/dm_nfnet_f4-0ac5b10b.pth', + url='https://github.com/rwightman/pytorch-image-models/releases/download/v0.1-dnf-weights/' + 'dm_nfnet_f4-0ac5b10b.pth', pool_size=(12, 12), input_size=(3, 384, 384), test_input_size=(3, 512, 512), crop_pct=0.951), dm_nfnet_f5=_dcfg( - url='https://github.com/rwightman/pytorch-image-models/releases/download/v0.1-dnf-weights/dm_nfnet_f5-ecb20ab1.pth', + url='https://github.com/rwightman/pytorch-image-models/releases/download/v0.1-dnf-weights/' + 'dm_nfnet_f5-ecb20ab1.pth', pool_size=(13, 13), input_size=(3, 416, 416), test_input_size=(3, 544, 544), crop_pct=0.954), dm_nfnet_f6=_dcfg( - url='https://github.com/rwightman/pytorch-image-models/releases/download/v0.1-dnf-weights/dm_nfnet_f6-e0f12116.pth', + url='https://github.com/rwightman/pytorch-image-models/releases/download/v0.1-dnf-weights/' + 'dm_nfnet_f6-e0f12116.pth', pool_size=(14, 14), input_size=(3, 448, 448), test_input_size=(3, 576, 576), crop_pct=0.956), nfnet_f0=_dcfg( @@ -113,8 +120,9 @@ default_cfgs = dict( nf_regnet_b0=_dcfg( url='', pool_size=(6, 6), input_size=(3, 192, 192), test_input_size=(3, 256, 256), first_conv='stem.conv'), nf_regnet_b1=_dcfg( - url='https://github.com/rwightman/pytorch-image-models/releases/download/v0.1-weights/nf_regnet_b1_256_ra2-ad85cfef.pth', - pool_size=(8, 8), input_size=(3, 256, 256), test_input_size=(3, 288, 288), first_conv='stem.conv'), # NOT to paper spec + url='https://github.com/rwightman/pytorch-image-models/releases/download/v0.1-weights/' + 'nf_regnet_b1_256_ra2-ad85cfef.pth', + pool_size=(8, 8), input_size=(3, 256, 256), test_input_size=(3, 288, 288), first_conv='stem.conv'), nf_regnet_b2=_dcfg( url='', pool_size=(8, 8), input_size=(3, 240, 240), test_input_size=(3, 272, 272), first_conv='stem.conv'), nf_regnet_b3=_dcfg( @@ -126,8 +134,10 @@ default_cfgs = dict( nf_resnet26=_dcfg(url='', first_conv='stem.conv'), nf_resnet50=_dcfg( - url='https://github.com/rwightman/pytorch-image-models/releases/download/v0.1-weights/nf_resnet50_ra2-9f236009.pth', - pool_size=(8, 8), input_size=(3, 256, 256), test_input_size=(3, 288, 288), crop_pct=0.94, first_conv='stem.conv'), + url='https://github.com/rwightman/pytorch-image-models/releases/download/v0.1-weights/' + 'nf_resnet50_ra2-9f236009.pth', + pool_size=(8, 8), input_size=(3, 256, 256), + test_input_size=(3, 288, 288), crop_pct=0.94, first_conv='stem.conv'), nf_resnet101=_dcfg(url='', first_conv='stem.conv'), nf_seresnet26=_dcfg(url='', first_conv='stem.conv'), -- Gitee