flowvision.models ############################## Pretrain Models for Visual Tasks Classification ============== The models subpackage contains definitions for the following model architectures for image classification: - `AlexNet`_ - `SqueezeNet`_ - `VGG`_ - `GoogLeNet`_ - `InceptionV3`_ - `ResNet`_ - `ResNeXt`_ - `DenseNet`_ - `ShuffleNetV2`_ - `MobileNetV2`_ - `MobileNetV3`_ - `MNASNet`_ - `GhostNet`_ - `Res2Net`_ - `EfficientNet`_ - `ReXNet`_ - `ViT`_ - `DeiT`_ - `PVT`_ - `Swin-Transformer`_ - `CSwin-Transformer`_ - `CrossFormer`_ - `Mlp_Mixer`_ - `ResMLP`_ - `gMLP`_ - `ConvMixer`_ .. _AlexNet: https://arxiv.org/abs/1404.5997 .. _VGG: https://arxiv.org/abs/1409.1556 .. _ResNet: https://arxiv.org/abs/1512.03385 .. _SqueezeNet: https://arxiv.org/abs/1602.07360 .. _DenseNet: https://arxiv.org/abs/1608.06993 .. _InceptionV3: https://arxiv.org/abs/1512.00567 .. _GoogLeNet: https://arxiv.org/abs/1409.4842 .. _ShuffleNetV2: https://arxiv.org/abs/1807.11164 .. _MobileNetV2: https://arxiv.org/abs/1801.04381 .. _MobileNetV3: https://arxiv.org/abs/1905.02244 .. _ResNeXt: https://arxiv.org/abs/1611.05431 .. _Res2Net: https://arxiv.org/abs/1904.01169 .. _ReXNet: https://arxiv.org/abs/2007.00992 .. _MNASNet: https://arxiv.org/abs/1807.11626 .. _GhostNet: https://arxiv.org/abs/1911.11907 .. _ViT: https://arxiv.org/abs/2010.11929 .. _DeiT: https://arxiv.org/abs/2012.12877 .. _PVT: https://arxiv.org/abs/2102.12122 .. _ResMLP: https://arxiv.org/abs/2105.03404 .. _Swin-Transformer: https://arxiv.org/abs/2103.14030 .. _CSwin-Transformer: https://arxiv.org/abs/2107.00652 .. _CrossFormer: https://arxiv.org/abs/2108.00154 .. _Mlp_Mixer: https://arxiv.org/abs/2105.01601 .. _ResMLP: https://arxiv.org/abs/2105.03404 .. _gMLP: https://arxiv.org/abs/2105.08050 .. _ConvMixer: https://openreview.net/pdf?id=TVHS5Y4dNvM .. _EfficientNet: https://arxiv.org/abs/1905.11946 .. currentmodule:: flowvision.models Alexnet ------- .. automodule:: flowvision.models :members: alexnet SqueezeNet ---------- .. automodule:: flowvision.models :members: squeezenet1_0, squeezenet1_1, VGG --- .. automodule:: flowvision.models :members: vgg11, vgg11_bn, vgg13, vgg13_bn, vgg16, vgg16_bn, vgg19, vgg19_bn, GoogLeNet --------- .. automodule:: flowvision.models :members: googlenet, InceptionV3 ----------- .. automodule:: flowvision.models :members: inception_v3, ResNet ------ .. automodule:: flowvision.models :members: resnet18, resnet34, resnet50, resnet101, resnet152, resnext50_32x4d, resnext101_32x8d, wide_resnet50_2, wide_resnet101_2, DenseNet -------- .. automodule:: flowvision.models :members: densenet121, densenet169, densenet201, densenet161, ShuffleNetV2 ------------ .. automodule:: flowvision.models :members: shufflenet_v2_x0_5, shufflenet_v2_x1_0, shufflenet_v2_x1_5, shufflenet_v2_x2_0, MobileNetV2 ----------- .. automodule:: flowvision.models :members: mobilenet_v2 MobileNetV3 ----------- .. automodule:: flowvision.models :members: mobilenet_v3_small, mobilenet_v3_large, MNASNet ------- .. automodule:: flowvision.models :members: mnasnet0_5, mnasnet0_75, mnasnet1_0, mnasnet1_3, GhostNet -------- .. automodule:: flowvision.models :members: ghostnet, Res2Net ------- .. automodule:: flowvision.models :members: res2net50_26w_4s, res2net50_26w_6s, res2net50_26w_8s, res2net50_48w_2s, res2net50_14w_8s, res2net101_26w_4s, EfficientNet ------------ .. automodule:: flowvision.models :members: efficientnet_b0, efficientnet_b1, efficientnet_b2, efficientnet_b3, efficientnet_b4, efficientnet_b5, efficientnet_b6, efficientnet_b7 ReXNet ------ .. automodule:: flowvision.models :members: rexnetv1_1_0, rexnetv1_1_3, rexnetv1_1_5, rexnetv1_2_0, rexnetv1_3_0, rexnet_lite_1_0, rexnet_lite_1_3, rexnet_lite_1_5, rexnet_lite_2_0, ViT ------ .. automodule:: flowvision.models :members: vit_tiny_patch16_224, vit_tiny_patch16_384, vit_small_patch32_224, vit_small_patch32_384, vit_small_patch16_224, vit_small_patch16_384, vit_base_patch32_224, vit_base_patch32_384, vit_base_patch16_224, vit_base_patch16_384, vit_base_patch8_224, vit_large_patch32_224, vit_large_patch32_384, vit_large_patch16_224, vit_large_patch16_384, vit_base_patch16_224_sam, vit_base_patch32_224_sam, vit_huge_patch14_224, vit_giant_patch14_224, vit_gigantic_patch14_224, vit_tiny_patch16_224_in21k, vit_small_patch32_224_in21k, vit_small_patch16_224_in21k, vit_base_patch32_224_in21k, vit_base_patch16_224_in21k, vit_base_patch8_224_in21k, vit_large_patch32_224_in21k, vit_large_patch16_224_in21k, vit_huge_patch14_224_in21k, vit_base_patch16_224_miil_in21k, vit_base_patch16_224_miil, DeiT ------ .. automodule:: flowvision.models :members: deit_tiny_patch16_224, deit_small_patch16_224, deit_base_patch16_224, deit_base_patch16_384, deit_tiny_distilled_patch16_224, deit_small_distilled_patch16_224, deit_base_distilled_patch16_224, deit_base_distilled_patch16_384, PVT ------ .. automodule:: flowvision.models :members: pvt_tiny, pvt_small, pvt_medium, pvt_large, Swin-Transformer ---------------- .. automodule:: flowvision.models :members: swin_tiny_patch4_window7_224, swin_small_patch4_window7_224, swin_base_patch4_window7_224, swin_base_patch4_window12_384, swin_base_patch4_window7_224_in22k_to_1k, swin_base_patch4_window12_384_in22k_to_1k, swin_large_patch4_window7_224_in22k_to_1k, swin_large_patch4_window12_384_in22k_to_1k, CSwin-Transformer ----------------- .. automodule:: flowvision.models :members: cswin_tiny_224, cswin_small_224, cswin_base_224, cswin_large_224, cswin_base_384, cswin_large_384, CrossFormer ----------- .. automodule:: flowvision.models :members: crossformer_tiny_patch4_group7_224, crossformer_small_patch4_group7_224, crossformer_base_patch4_group7_224, crossformer_large_patch4_group7_224, Mlp-Mixer --------- .. automodule:: flowvision.models :members: mlp_mixer_s16_224, mlp_mixer_s32_224, mlp_mixer_b16_224, mlp_mixer_b32_224, mlp_mixer_b16_224_in21k, mlp_mixer_l16_224, mlp_mixer_l32_224, mlp_mixer_l16_224_in21k, mlp_mixer_b16_224_miil, mlp_mixer_b16_224_miil_in21k, ResMLP ------ .. automodule:: flowvision.models :members: resmlp_12_224, resmlp_12_distilled_224, resmlp_12_224_dino, resmlp_24_224, resmlp_24_distilled_224, resmlp_24_224_dino, resmlp_36_224, resmlp_36_distilled_224, resmlp_big_24_224, resmlp_big_24_224_in22k_to_1k, resmlp_big_24_distilled_224, gMLP ---- .. automodule:: flowvision.models :members: gmlp_ti16_224, gmlp_s16_224, gmlp_b16_224, ConvMixer --------- .. automodule:: flowvision.models :members: convmixer_1536_20, convmixer_768_32_relu, convmixer_1024_20, Neural Style ============ .. currentmodule:: flowvision.models .. automodule:: flowvision.models :members: neural_style_transfer,