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imgclsmob | imgclsmob-master/pytorch/pytorchcv/models/fishnet.py | """
FishNet for ImageNet-1K, implemented in PyTorch.
Original paper: 'FishNet: A Versatile Backbone for Image, Region, and Pixel Level Prediction,'
http://papers.nips.cc/paper/7356-fishnet-a-versatile-backbone-for-image-region-and-pixel-level-prediction.pdf.
"""
__all__ = ['FishNet', 'fishnet99', 'fishnet1... | 19,302 | 30.033762 | 119 | py |
imgclsmob | imgclsmob-master/pytorch/pytorchcv/models/hrnet.py | """
HRNet for ImageNet-1K, implemented in PyTorch.
Original paper: 'Deep High-Resolution Representation Learning for Visual Recognition,'
https://arxiv.org/abs/1908.07919.
"""
__all__ = ['hrnet_w18_small_v1', 'hrnet_w18_small_v2', 'hrnetv2_w18', 'hrnetv2_w30', 'hrnetv2_w32', 'hrnetv2_w40',
'hrne... | 22,226 | 32.83105 | 115 | py |
imgclsmob | imgclsmob-master/pytorch/pytorchcv/models/fcn8sd.py | """
FCN-8s(d) for image segmentation, implemented in PyTorch.
Original paper: 'Fully Convolutional Networks for Semantic Segmentation,' https://arxiv.org/abs/1411.4038.
"""
__all__ = ['FCN8sd', 'fcn8sd_resnetd50b_voc', 'fcn8sd_resnetd101b_voc', 'fcn8sd_resnetd50b_coco',
'fcn8sd_resnetd101b_coco', 'f... | 16,126 | 37.125296 | 120 | py |
imgclsmob | imgclsmob-master/pytorch/pytorchcv/models/selecsls.py | """
SelecSLS for ImageNet-1K, implemented in PyTorch.
Original paper: 'XNect: Real-time Multi-person 3D Human Pose Estimation with a Single RGB Camera,'
https://arxiv.org/abs/1907.00837.
"""
__all__ = ['SelecSLS', 'selecsls42', 'selecsls42b', 'selecsls60', 'selecsls60b', 'selecsls84']
import os
import tor... | 12,347 | 31.580475 | 115 | py |
imgclsmob | imgclsmob-master/pytorch/pytorchcv/models/inceptionv4.py | """
InceptionV4 for ImageNet-1K, implemented in PyTorch.
Original paper: 'Inception-v4, Inception-ResNet and the Impact of Residual Connections on Learning,'
https://arxiv.org/abs/1602.07261.
"""
__all__ = ['InceptionV4', 'inceptionv4']
import os
import torch
import torch.nn as nn
from .common import Conv... | 17,876 | 28.944724 | 115 | py |
imgclsmob | imgclsmob-master/pytorch/pytorchcv/models/regnet.py | """
RegNet for ImageNet-1K, implemented in PyTorch.
Original paper: 'Designing Network Design Spaces,' https://arxiv.org/abs/2003.13678.
"""
__all__ = ['RegNet', 'regnetx002', 'regnetx004', 'regnetx006', 'regnetx008', 'regnetx016', 'regnetx032', 'regnetx040',
'regnetx064', 'regnetx080', 'regnetx120'... | 24,321 | 32.874652 | 118 | py |
imgclsmob | imgclsmob-master/pytorch/pytorchcv/models/icnet.py | """
ICNet for image segmentation, implemented in PyTorch.
Original paper: 'ICNet for Real-Time Semantic Segmentation on High-Resolution Images,'
https://arxiv.org/abs/1704.08545.
"""
__all__ = ['ICNet', 'icnet_resnetd50b_cityscapes']
import os
import torch.nn as nn
from .common import conv1x1, conv1x1_blo... | 12,295 | 29.894472 | 115 | py |
imgclsmob | imgclsmob-master/pytorch/pytorchcv/models/mobilenetb.py | """
MobileNet(B) with simplified depthwise separable convolution block for ImageNet-1K, implemented in Gluon.
Original paper: 'MobileNets: Efficient Convolutional Neural Networks for Mobile Vision Applications,'
https://arxiv.org/abs/1704.04861.
"""
__all__ = ['mobilenetb_w1', 'mobilenetb_w3d4', 'mobilenet... | 3,794 | 32.289474 | 113 | py |
imgclsmob | imgclsmob-master/pytorch/pytorchcv/models/shakedropresnet_cifar.py | """
ShakeDrop-ResNet for CIFAR/SVHN, implemented in PyTorch.
Original paper: 'ShakeDrop Regularization for Deep Residual Learning,' https://arxiv.org/abs/1802.02375.
"""
__all__ = ['CIFARShakeDropResNet', 'shakedropresnet20_cifar10', 'shakedropresnet20_cifar100', 'shakedropresnet20_svhn']
import os
import tor... | 10,750 | 31.677812 | 119 | py |
imgclsmob | imgclsmob-master/pytorch/pytorchcv/models/inceptionresnetv1.py | """
InceptionResNetV1 for ImageNet-1K, implemented in PyTorch.
Original paper: 'Inception-v4, Inception-ResNet and the Impact of Residual Connections on Learning,'
https://arxiv.org/abs/1602.07261.
"""
__all__ = ['InceptionResNetV1', 'inceptionresnetv1', 'InceptionAUnit', 'InceptionBUnit', 'InceptionCUnit'... | 16,987 | 30.285451 | 117 | py |
imgclsmob | imgclsmob-master/pytorch/pytorchcv/models/scnet.py | """
SCNet for ImageNet-1K, implemented in PyTorch.
Original paper: 'Improving Convolutional Networks with Self-Calibrated Convolutions,'
http://mftp.mmcheng.net/Papers/20cvprSCNet.pdf.
"""
__all__ = ['SCNet', 'scnet50', 'scnet101', 'scneta50', 'scneta101']
import os
import torch
import torch.nn as nn
from... | 14,943 | 29.876033 | 115 | py |
imgclsmob | imgclsmob-master/pytorch/pytorchcv/models/igcv3.py | """
IGCV3 for ImageNet-1K, implemented in PyTorch.
Original paper: 'IGCV3: Interleaved Low-Rank Group Convolutions for Efficient Deep Neural Networks,'
https://arxiv.org/abs/1806.00178.
"""
__all__ = ['IGCV3', 'igcv3_w1', 'igcv3_w3d4', 'igcv3_wd2', 'igcv3_wd4']
import os
import torch.nn as nn
import torch... | 9,829 | 30.709677 | 115 | py |
imgclsmob | imgclsmob-master/pytorch/pytorchcv/models/seresnet_cifar.py | """
SE-ResNet for CIFAR/SVHN, implemented in PyTorch.
Original paper: 'Squeeze-and-Excitation Networks,' https://arxiv.org/abs/1709.01507.
"""
__all__ = ['CIFARSEResNet', 'seresnet20_cifar10', 'seresnet20_cifar100', 'seresnet20_svhn',
'seresnet56_cifar10', 'seresnet56_cifar100', 'seresnet56_svhn',
... | 24,036 | 36.324534 | 120 | py |
imgclsmob | imgclsmob-master/pytorch/pytorchcv/models/resnetd.py | """
ResNet(D) with dilation for ImageNet-1K, implemented in PyTorch.
Original paper: 'Deep Residual Learning for Image Recognition,' https://arxiv.org/abs/1512.03385.
"""
__all__ = ['ResNetD', 'resnetd50b', 'resnetd101b', 'resnetd152b']
import os
import torch.nn as nn
import torch.nn.init as init
from .common... | 9,674 | 32.362069 | 120 | py |
imgclsmob | imgclsmob-master/pytorch/pytorchcv/models/quartznet.py | """
QuartzNet for ASR, implemented in PyTorch.
Original paper: 'QuartzNet: Deep Automatic Speech Recognition with 1D Time-Channel Separable Convolutions,'
https://arxiv.org/abs/1910.10261.
"""
__all__ = ['quartznet5x5_en_ls', 'quartznet15x5_en', 'quartznet15x5_en_nr', 'quartznet15x5_fr', 'quartznet15x5_de'... | 13,675 | 42.141956 | 119 | py |
imgclsmob | imgclsmob-master/pytorch/pytorchcv/models/preresnet.py | """
PreResNet for ImageNet-1K, implemented in PyTorch.
Original paper: 'Identity Mappings in Deep Residual Networks,' https://arxiv.org/abs/1603.05027.
"""
__all__ = ['PreResNet', 'preresnet10', 'preresnet12', 'preresnet14', 'preresnetbc14b', 'preresnet16', 'preresnet18_wd4',
'preresnet18_wd2', 'pre... | 26,501 | 32.044888 | 120 | py |
imgclsmob | imgclsmob-master/pytorch/pytorchcv/models/lednet.py | """
LEDNet for image segmentation, implemented in PyTorch.
Original paper: 'LEDNet: A Lightweight Encoder-Decoder Network for Real-Time Semantic Segmentation,'
https://arxiv.org/abs/1905.02423.
"""
__all__ = ['LEDNet', 'lednet_cityscapes']
import os
import torch
import torch.nn as nn
from .common import c... | 13,638 | 29.241685 | 116 | py |
imgclsmob | imgclsmob-master/pytorch/pytorchcv/models/superpointnet.py | """
SuperPointNet for HPatches (image matching), implemented in PyTorch.
Original paper: 'SuperPoint: Self-Supervised Interest Point Detection and Description,'
https://arxiv.org/abs/1712.07629.
"""
__all__ = ['SuperPointNet', 'superpointnet']
import os
import torch
import torch.nn as nn
import torch.nn.i... | 11,418 | 31.719198 | 115 | py |
imgclsmob | imgclsmob-master/pytorch/pytorchcv/models/ibndensenet.py | """
IBN-DenseNet for ImageNet-1K, implemented in PyTorch.
Original paper: 'Two at Once: Enhancing Learning and Generalization Capacities via IBN-Net,'
https://arxiv.org/abs/1807.09441.
"""
__all__ = ['IBNDenseNet', 'ibn_densenet121', 'ibn_densenet161', 'ibn_densenet169', 'ibn_densenet201']
import os
impor... | 12,647 | 30.384615 | 115 | py |
imgclsmob | imgclsmob-master/pytorch/pytorchcv/models/hardnet.py | """
HarDNet for ImageNet-1K, implemented in PyTorch.
Original paper: 'HarDNet: A Low Memory Traffic Network,' https://arxiv.org/abs/1909.00948.
"""
__all__ = ['HarDNet', 'hardnet39ds', 'hardnet68ds', 'hardnet68', 'hardnet85']
import os
import torch
import torch.nn as nn
from .common import conv1x1_block, conv... | 21,984 | 34.176 | 115 | py |
imgclsmob | imgclsmob-master/pytorch/pytorchcv/models/sinet.py | """
SINet for image segmentation, implemented in PyTorch.
Original paper: 'SINet: Extreme Lightweight Portrait Segmentation Networks with Spatial Squeeze Modules and
Information Blocking Decoder,' https://arxiv.org/abs/1911.09099.
"""
__all__ = ['SINet', 'sinet_cityscapes']
import os
import torch
import t... | 33,876 | 30.929312 | 118 | py |
imgclsmob | imgclsmob-master/pytorch/pytorchcv/models/shufflenetv2b.py | """
ShuffleNet V2 for ImageNet-1K, implemented in PyTorch. The alternative version.
Original paper: 'ShuffleNet V2: Practical Guidelines for Efficient CNN Architecture Design,'
https://arxiv.org/abs/1807.11164.
"""
__all__ = ['ShuffleNetV2b', 'shufflenetv2b_wd2', 'shufflenetv2b_w1', 'shufflenetv2b_w3d2', '... | 12,431 | 30.553299 | 115 | py |
imgclsmob | imgclsmob-master/pytorch/pytorchcv/models/sparsenet.py | """
SparseNet for ImageNet-1K, implemented in PyTorch.
Original paper: 'Sparsely Aggregated Convolutional Networks,' https://arxiv.org/abs/1801.05895.
"""
__all__ = ['SparseNet', 'sparsenet121', 'sparsenet161', 'sparsenet169', 'sparsenet201', 'sparsenet264']
import os
import math
import torch
import torch.nn ... | 11,646 | 29.569554 | 115 | py |
imgclsmob | imgclsmob-master/pytorch/pytorchcv/models/menet.py | """
MENet for ImageNet-1K, implemented in PyTorch.
Original paper: 'Merging and Evolution: Improving Convolutional Neural Networks for Mobile Applications,'
https://arxiv.org/abs/1803.09127.
"""
__all__ = ['MENet', 'menet108_8x1_g3', 'menet128_8x1_g4', 'menet160_8x1_g8', 'menet228_12x1_g3', 'menet256_12x1_... | 15,917 | 31.956522 | 116 | py |
imgclsmob | imgclsmob-master/pytorch/pytorchcv/models/voca.py | """
VOCA for speech-driven facial animation, implemented in PyTorch.
Original paper: 'Capture, Learning, and Synthesis of 3D Speaking Styles,' https://arxiv.org/abs/1905.03079.
"""
__all__ = ['VOCA', 'voca8flame']
import os
import torch
import torch.nn as nn
import torch.nn.functional as F
from .common import... | 6,683 | 28.575221 | 115 | py |
imgclsmob | imgclsmob-master/pytorch/pytorchcv/models/shakeshakeresnet_cifar.py | """
Shake-Shake-ResNet for CIFAR/SVHN, implemented in PyTorch.
Original paper: 'Shake-Shake regularization,' https://arxiv.org/abs/1705.07485.
"""
__all__ = ['CIFARShakeShakeResNet', 'shakeshakeresnet20_2x16d_cifar10', 'shakeshakeresnet20_2x16d_cifar100',
'shakeshakeresnet20_2x16d_svhn', 'shakeshake... | 14,392 | 33.269048 | 120 | py |
imgclsmob | imgclsmob-master/pytorch/pytorchcv/models/sqnet.py | """
SQNet for image segmentation, implemented in PyTorch.
Original paper: 'Speeding up Semantic Segmentation for Autonomous Driving,'
https://openreview.net/pdf?id=S1uHiFyyg.
"""
__all__ = ['SQNet', 'sqnet_cityscapes']
import os
import torch
import torch.nn as nn
from .common import conv1x1_block, conv3x3... | 11,602 | 29.374346 | 115 | py |
imgclsmob | imgclsmob-master/pytorch/pytorchcv/models/wrn_cifar.py | """
WRN for CIFAR/SVHN, implemented in PyTorch.
Original paper: 'Wide Residual Networks,' https://arxiv.org/abs/1605.07146.
"""
__all__ = ['CIFARWRN', 'wrn16_10_cifar10', 'wrn16_10_cifar100', 'wrn16_10_svhn', 'wrn28_10_cifar10',
'wrn28_10_cifar100', 'wrn28_10_svhn', 'wrn40_8_cifar10', 'wrn40_8_cifar... | 11,329 | 33.126506 | 119 | py |
imgclsmob | imgclsmob-master/pytorch/pytorchcv/models/inceptionresnetv2.py | """
InceptionResNetV2 for ImageNet-1K, implemented in PyTorch.
Original paper: 'Inception-v4, Inception-ResNet and the Impact of Residual Connections on Learning,'
https://arxiv.org/abs/1602.07261.
"""
__all__ = ['InceptionResNetV2', 'inceptionresnetv2']
import os
import torch.nn as nn
from .common import... | 9,577 | 30.926667 | 117 | py |
imgclsmob | imgclsmob-master/pytorch/pytorchcv/models/ghostnet.py | """
GhostNet for ImageNet-1K, implemented in PyTorch.
Original paper: 'GhostNet: More Features from Cheap Operations,' https://arxiv.org/abs/1911.11907.
"""
__all__ = ['GhostNet', 'ghostnet']
import os
import math
import torch
import torch.nn as nn
from .common import round_channels, conv1x1, conv1x1_block, c... | 12,819 | 30.268293 | 115 | py |
imgclsmob | imgclsmob-master/pytorch/pytorchcv/models/efficientnet.py | """
EfficientNet for ImageNet-1K, implemented in PyTorch.
Original papers:
- 'EfficientNet: Rethinking Model Scaling for Convolutional Neural Networks,' https://arxiv.org/abs/1905.11946,
- 'Adversarial Examples Improve Image Recognition,' https://arxiv.org/abs/1911.09665.
"""
__all__ = ['EfficientNet',... | 37,745 | 35.933464 | 120 | py |
imgclsmob | imgclsmob-master/pytorch/pytorchcv/models/edanet.py | """
EDANet for image segmentation, implemented in PyTorch.
Original paper: 'Efficient Dense Modules of Asymmetric Convolution for Real-Time Semantic Segmentation,'
https://arxiv.org/abs/1809.06323.
"""
__all__ = ['EDANet', 'edanet_cityscapes']
import os
import torch
import torch.nn as nn
from .common impo... | 10,158 | 28.618076 | 115 | py |
imgclsmob | imgclsmob-master/pytorch/pytorchcv/models/channelnet.py | """
ChannelNet for ImageNet-1K, implemented in PyTorch.
Original paper: 'ChannelNets: Compact and Efficient Convolutional Neural Networks via Channel-Wise Convolutions,'
https://arxiv.org/abs/1809.01330.
"""
__all__ = ['ChannelNet', 'channelnet']
import os
import torch
import torch.nn as nn
import torch.n... | 18,471 | 29.633499 | 117 | py |
imgclsmob | imgclsmob-master/pytorch/pytorchcv/models/pnasnet.py | """
PNASNet for ImageNet-1K, implemented in PyTorch.
Original paper: 'Progressive Neural Architecture Search,' https://arxiv.org/abs/1712.00559.
"""
__all__ = ['PNASNet', 'pnasnet5large']
import os
import torch
import torch.nn as nn
import torch.nn.init as init
from .common import conv1x1
from .nasnet import... | 18,176 | 28.945634 | 118 | py |
imgclsmob | imgclsmob-master/pytorch/pytorchcv/models/efficientnetedge.py | """
EfficientNet-Edge for ImageNet-1K, implemented in PyTorch.
Original paper: 'EfficientNet: Rethinking Model Scaling for Convolutional Neural Networks,'
https://arxiv.org/abs/1905.11946.
"""
__all__ = ['EfficientNetEdge', 'efficientnet_edge_small_b', 'efficientnet_edge_medium_b', 'efficientnet_edge_large... | 14,866 | 35.799505 | 118 | py |
imgclsmob | imgclsmob-master/pytorch/pytorchcv/models/ibnresnext.py | """
IBN-ResNeXt for ImageNet-1K, implemented in PyTorch.
Original paper: 'Aggregated Residual Transformations for Deep Neural Networks,' http://arxiv.org/abs/1611.05431.
"""
__all__ = ['IBNResNeXt', 'ibn_resnext50_32x4d', 'ibn_resnext101_32x4d', 'ibn_resnext101_64x4d']
import os
import math
import torch.nn as... | 10,749 | 30.341108 | 118 | py |
imgclsmob | imgclsmob-master/pytorch/pytorchcv/models/squeezenext.py | """
SqueezeNext for ImageNet-1K, implemented in PyTorch.
Original paper: 'SqueezeNext: Hardware-Aware Neural Network Design,' https://arxiv.org/abs/1803.10615.
"""
__all__ = ['SqueezeNext', 'sqnxt23_w1', 'sqnxt23_w3d2', 'sqnxt23_w2', 'sqnxt23v5_w1', 'sqnxt23v5_w3d2', 'sqnxt23v5_w2']
import os
import torch.nn ... | 12,238 | 30.543814 | 119 | py |
imgclsmob | imgclsmob-master/pytorch/pytorchcv/models/xdensenet.py | """
X-DenseNet for ImageNet-1K, implemented in PyTorch.
Original paper: 'Deep Expander Networks: Efficient Deep Networks from Graph Theory,'
https://arxiv.org/abs/1711.08757.
"""
__all__ = ['XDenseNet', 'xdensenet121_2', 'xdensenet161_2', 'xdensenet169_2', 'xdensenet201_2', 'pre_xconv3x3_block',
... | 16,251 | 30.015267 | 117 | py |
imgclsmob | imgclsmob-master/pytorch/pytorchcv/models/linknet.py | """
LinkNet for image segmentation, implemented in PyTorch.
Original paper: 'LinkNet: Exploiting Encoder Representations for Efficient Semantic Segmentation,'
https://arxiv.org/abs/1707.03718.
"""
__all__ = ['LinkNet', 'linknet_cityscapes']
import os
import torch
import torch.nn as nn
from .common import ... | 9,565 | 29.5623 | 120 | py |
imgclsmob | imgclsmob-master/pytorch/pytorchcv/models/diaresnet_cifar.py | """
DIA-ResNet for CIFAR/SVHN, implemented in PyTorch.
Original paper: 'DIANet: Dense-and-Implicit Attention Network,' https://arxiv.org/abs/1905.10671.
"""
__all__ = ['CIFARDIAResNet', 'diaresnet20_cifar10', 'diaresnet20_cifar100', 'diaresnet20_svhn', 'diaresnet56_cifar10',
'diaresnet56_cifar100', ... | 19,959 | 35.489945 | 120 | py |
imgclsmob | imgclsmob-master/pytorch/pytorchcv/models/resdropresnet_cifar.py | """
ResDrop-ResNet for CIFAR/SVHN, implemented in PyTorch.
Original paper: 'Deep Networks with Stochastic Depth,' https://arxiv.org/abs/1603.09382.
"""
__all__ = ['CIFARResDropResNet', 'resdropresnet20_cifar10', 'resdropresnet20_cifar100', 'resdropresnet20_svhn']
import os
import torch
import torch.nn as nn
i... | 9,918 | 31.735974 | 119 | py |
imgclsmob | imgclsmob-master/pytorch/pytorchcv/models/bisenet.py | """
BiSeNet for CelebAMask-HQ, implemented in PyTorch.
Original paper: 'BiSeNet: Bilateral Segmentation Network for Real-time Semantic Segmentation,'
https://arxiv.org/abs/1808.00897.
"""
__all__ = ['BiSeNet', 'bisenet_resnet18_celebamaskhq']
import os
import torch
import torch.nn as nn
from .common impor... | 13,181 | 28.959091 | 120 | py |
imgclsmob | imgclsmob-master/pytorch/pytorchcv/models/resnet.py | """
ResNet for ImageNet-1K, implemented in PyTorch.
Original paper: 'Deep Residual Learning for Image Recognition,' https://arxiv.org/abs/1512.03385.
"""
__all__ = ['ResNet', 'resnet10', 'resnet12', 'resnet14', 'resnetbc14b', 'resnet16', 'resnet18_wd4', 'resnet18_wd2',
'resnet18_w3d4', 'resnet18', '... | 25,346 | 31.579692 | 120 | py |
imgclsmob | imgclsmob-master/pytorch/pytorchcv/models/simpleposemobile_coco.py | """
SimplePose(Mobile) for COCO Keypoint, implemented in PyTorch.
Original paper: 'Simple Baselines for Human Pose Estimation and Tracking,' https://arxiv.org/abs/1804.06208.
"""
__all__ = ['SimplePoseMobile', 'simplepose_mobile_resnet18_coco', 'simplepose_mobile_resnet50b_coco',
'simplepose_mobile_... | 12,743 | 37.735562 | 120 | py |
imgclsmob | imgclsmob-master/pytorch/pytorchcv/models/cbamresnet.py | """
CBAM-ResNet for ImageNet-1K, implemented in PyTorch.
Original paper: 'CBAM: Convolutional Block Attention Module,' https://arxiv.org/abs/1807.06521.
"""
__all__ = ['CbamResNet', 'cbam_resnet18', 'cbam_resnet34', 'cbam_resnet50', 'cbam_resnet101', 'cbam_resnet152']
import os
import torch
import torch.nn as... | 12,908 | 28.405467 | 115 | py |
imgclsmob | imgclsmob-master/pytorch/pytorchcv/models/diracnetv2.py | """
DiracNetV2 for ImageNet-1K, implemented in PyTorch.
Original paper: 'DiracNets: Training Very Deep Neural Networks Without Skip-Connections,'
https://arxiv.org/abs/1706.00388.
"""
__all__ = ['DiracNetV2', 'diracnet18v2', 'diracnet34v2']
import os
import torch.nn as nn
import torch.nn.init as init
cl... | 8,444 | 27.72449 | 115 | py |
imgclsmob | imgclsmob-master/pytorch/pytorchcv/models/sepreresnet_cifar.py | """
SE-PreResNet for CIFAR/SVHN, implemented in PyTorch.
Original paper: 'Squeeze-and-Excitation Networks,' https://arxiv.org/abs/1709.01507.
"""
__all__ = ['CIFARSEPreResNet', 'sepreresnet20_cifar10', 'sepreresnet20_cifar100', 'sepreresnet20_svhn',
'sepreresnet56_cifar10', 'sepreresnet56_cifar100',... | 24,663 | 37.298137 | 119 | py |
imgclsmob | imgclsmob-master/pytorch/pytorchcv/models/danet.py | """
DANet for image segmentation, implemented in Gluon.
Original paper: 'Dual Attention Network for Scene Segmentation,' https://arxiv.org/abs/1809.02983.
"""
__all__ = ['DANet', 'danet_resnetd50b_cityscapes', 'danet_resnetd101b_cityscapes', 'ScaleBlock']
import os
import torch
import torch.nn as nn
import to... | 12,721 | 30.568238 | 116 | py |
imgclsmob | imgclsmob-master/pytorch/pytorchcv/models/mobilenetv2.py | """
MobileNetV2 for ImageNet-1K, implemented in PyTorch.
Original paper: 'MobileNetV2: Inverted Residuals and Linear Bottlenecks,' https://arxiv.org/abs/1801.04381.
"""
__all__ = ['MobileNetV2', 'mobilenetv2_w1', 'mobilenetv2_w3d4', 'mobilenetv2_wd2', 'mobilenetv2_wd4', 'mobilenetv2b_w1',
'mobilenet... | 12,761 | 32.321149 | 120 | py |
imgclsmob | imgclsmob-master/pytorch/pytorchcv/models/squeezenet.py | """
SqueezeNet for ImageNet-1K, implemented in PyTorch.
Original paper: 'SqueezeNet: AlexNet-level accuracy with 50x fewer parameters and <0.5MB model size,'
https://arxiv.org/abs/1602.07360.
"""
__all__ = ['SqueezeNet', 'squeezenet_v1_0', 'squeezenet_v1_1', 'squeezeresnet_v1_0', 'squeezeresnet_v1_1']
imp... | 12,164 | 30.929134 | 118 | py |
imgclsmob | imgclsmob-master/pytorch/pytorchcv/models/nin_cifar.py | """
NIN for CIFAR/SVHN, implemented in PyTorch.
Original paper: 'Network In Network,' https://arxiv.org/abs/1312.4400.
"""
__all__ = ['CIFARNIN', 'nin_cifar10', 'nin_cifar100', 'nin_svhn']
import os
import torch.nn as nn
import torch.nn.init as init
class NINConv(nn.Module):
"""
NIN specific convolu... | 8,048 | 29.957692 | 115 | py |
imgclsmob | imgclsmob-master/pytorch/pytorchcv/models/vgg.py | """
VGG for ImageNet-1K, implemented in PyTorch.
Original paper: 'Very Deep Convolutional Networks for Large-Scale Image Recognition,'
https://arxiv.org/abs/1409.1556.
"""
__all__ = ['VGG', 'vgg11', 'vgg13', 'vgg16', 'vgg19', 'bn_vgg11', 'bn_vgg13', 'bn_vgg16', 'bn_vgg19', 'bn_vgg11b',
'bn_vgg13... | 13,528 | 29.678005 | 117 | py |
imgclsmob | imgclsmob-master/pytorch/pytorchcv/models/resnet_cub.py | """
ResNet for CUB-200-2011, implemented in PyTorch.
Original paper: 'Deep Residual Learning for Image Recognition,' https://arxiv.org/abs/1512.03385.
"""
__all__ = ['resnet10_cub', 'resnet12_cub', 'resnet14_cub', 'resnetbc14b_cub', 'resnet16_cub', 'resnet18_cub',
'resnet26_cub', 'resnetbc26b_cub', ... | 14,148 | 35.094388 | 117 | py |
imgclsmob | imgclsmob-master/pytorch/pytorchcv/models/bagnet.py | """
BagNet for ImageNet-1K, implemented in PyTorch.
Original paper: 'Approximating CNNs with Bag-of-local-Features models works surprisingly well on ImageNet,'
https://openreview.net/pdf?id=SkfMWhAqYQ.
"""
__all__ = ['BagNet', 'bagnet9', 'bagnet17', 'bagnet33']
import os
import torch.nn as nn
import torch... | 10,903 | 29.373259 | 116 | py |
imgclsmob | imgclsmob-master/pytorch/pytorchcv/models/airnet.py | """
AirNet for ImageNet-1K, implemented in PyTorch.
Original paper: 'Attention Inspiring Receptive-Fields Network for Learning Invariant Representations,'
https://ieeexplore.ieee.org/document/8510896.
"""
__all__ = ['AirNet', 'airnet50_1x64d_r2', 'airnet50_1x64d_r16', 'airnet101_1x64d_r2', 'AirBlock', 'Air... | 12,525 | 28.612293 | 115 | py |
imgclsmob | imgclsmob-master/pytorch/pytorchcv/models/mnasnet.py | """
MnasNet for ImageNet-1K, implemented in PyTorch.
Original paper: 'MnasNet: Platform-Aware Neural Architecture Search for Mobile,' https://arxiv.org/abs/1807.11626.
"""
__all__ = ['MnasNet', 'mnasnet_b1', 'mnasnet_a1', 'mnasnet_small']
import os
import torch.nn as nn
import torch.nn.init as init
from .comm... | 14,189 | 32.388235 | 118 | py |
imgclsmob | imgclsmob-master/pytorch/pytorchcv/models/pyramidnet_cifar.py | """
PyramidNet for CIFAR/SVHN, implemented in PyTorch.
Original paper: 'Deep Pyramidal Residual Networks,' https://arxiv.org/abs/1610.02915.
"""
__all__ = ['CIFARPyramidNet', 'pyramidnet110_a48_cifar10', 'pyramidnet110_a48_cifar100', 'pyramidnet110_a48_svhn',
'pyramidnet110_a84_cifar10', 'pyramidnet... | 23,823 | 32.413745 | 120 | py |
imgclsmob | imgclsmob-master/pytorch/pytorchcv/models/preresnet_cifar.py | """
PreResNet for CIFAR/SVHN, implemented in PyTorch.
Original papers: 'Identity Mappings in Deep Residual Networks,' https://arxiv.org/abs/1603.05027.
"""
__all__ = ['CIFARPreResNet', 'preresnet20_cifar10', 'preresnet20_cifar100', 'preresnet20_svhn',
'preresnet56_cifar10', 'preresnet56_cifar100', '... | 24,611 | 35.789238 | 120 | py |
imgclsmob | imgclsmob-master/pytorch/pytorchcv/models/alphapose_coco.py | """
AlphaPose for COCO Keypoint, implemented in PyTorch.
Original paper: 'RMPE: Regional Multi-person Pose Estimation,' https://arxiv.org/abs/1612.00137.
"""
__all__ = ['AlphaPose', 'alphapose_fastseresnet101b_coco']
import os
import torch
import torch.nn as nn
from .common import conv3x3, DucBlock, HeatmapMa... | 6,247 | 30.877551 | 116 | py |
imgclsmob | imgclsmob-master/pytorch/pytorchcv/models/pyramidnet.py | """
PyramidNet for ImageNet-1K, implemented in PyTorch.
Original paper: 'Deep Pyramidal Residual Networks,' https://arxiv.org/abs/1610.02915.
"""
__all__ = ['PyramidNet', 'pyramidnet101_a360', 'PyrUnit']
import os
import torch.nn as nn
import torch.nn.init as init
import torch.nn.functional as F
from .common ... | 11,038 | 28.126649 | 115 | py |
imgclsmob | imgclsmob-master/pytorch/pytorchcv/models/seresnet.py | """
SE-ResNet for ImageNet-1K, implemented in PyTorch.
Original paper: 'Squeeze-and-Excitation Networks,' https://arxiv.org/abs/1709.01507.
"""
__all__ = ['SEResNet', 'seresnet10', 'seresnet12', 'seresnet14', 'seresnet16', 'seresnet18', 'seresnet26',
'seresnetbc26b', 'seresnet34', 'seresnetbc38b', '... | 18,211 | 31.579606 | 118 | py |
imgclsmob | imgclsmob-master/pytorch/pytorchcv/models/seresnet_cub.py | """
SE-ResNet for CUB-200-2011, implemented in PyTorch.
Original paper: 'Squeeze-and-Excitation Networks,' https://arxiv.org/abs/1709.01507.
"""
__all__ = ['seresnet10_cub', 'seresnet12_cub', 'seresnet14_cub', 'seresnetbc14b_cub', 'seresnet16_cub',
'seresnet18_cub', 'seresnet26_cub', 'seresnetbc26b_... | 14,391 | 35.808184 | 120 | py |
imgclsmob | imgclsmob-master/pytorch/pytorchcv/models/densenet.py | """
DenseNet for ImageNet-1K, implemented in PyTorch.
Original paper: 'Densely Connected Convolutional Networks,' https://arxiv.org/abs/1608.06993.
"""
__all__ = ['DenseNet', 'densenet121', 'densenet161', 'densenet169', 'densenet201', 'DenseUnit', 'TransitionBlock']
import os
import torch
import torch.nn as n... | 9,930 | 29.556923 | 116 | py |
imgclsmob | imgclsmob-master/pytorch/pytorchcv/models/seresnext.py | """
SE-ResNeXt for ImageNet-1K, implemented in PyTorch.
Original paper: 'Squeeze-and-Excitation Networks,' https://arxiv.org/abs/1709.01507.
"""
__all__ = ['SEResNeXt', 'seresnext50_32x4d', 'seresnext101_32x4d', 'seresnext101_64x4d']
import os
import torch.nn as nn
import torch.nn.init as init
from .common im... | 8,721 | 29.929078 | 115 | py |
imgclsmob | imgclsmob-master/pytorch/pytorchcv/models/darts.py | """
DARTS for ImageNet-1K, implemented in PyTorch.
Original paper: 'DARTS: Differentiable Architecture Search,' https://arxiv.org/abs/1806.09055.
"""
__all__ = ['DARTS', 'darts']
import os
import torch
import torch.nn as nn
import torch.nn.init as init
from .common import conv1x1, Identity
from .nasnet import... | 20,291 | 26.683492 | 115 | py |
imgclsmob | imgclsmob-master/pytorch/pytorchcv/models/drn.py | """
DRN for ImageNet-1K, implemented in PyTorch.
Original paper: 'Dilated Residual Networks,' https://arxiv.org/abs/1705.09914.
"""
__all__ = ['DRN', 'drnc26', 'drnc42', 'drnc58', 'drnd22', 'drnd38', 'drnd54', 'drnd105']
import os
import torch.nn as nn
import torch.nn.init as init
class DRNConv(nn.Module):
... | 18,826 | 28.695584 | 118 | py |
imgclsmob | imgclsmob-master/pytorch/pytorchcv/models/mixnet.py | """
MixNet for ImageNet-1K, implemented in PyTorch.
Original paper: 'MixConv: Mixed Depthwise Convolutional Kernels,' https://arxiv.org/abs/1907.09595.
"""
__all__ = ['MixNet', 'mixnet_s', 'mixnet_m', 'mixnet_l']
import os
import torch
import torch.nn as nn
import torch.nn.init as init
from .common import rou... | 20,528 | 33.386935 | 116 | py |
imgclsmob | imgclsmob-master/pytorch/pytorchcv/models/dabnet.py | """
DABNet for image segmentation, implemented in PyTorch.
Original paper: 'DABNet: Depth-wise Asymmetric Bottleneck for Real-time Semantic Segmentation,'
https://arxiv.org/abs/1907.11357.
"""
__all__ = ['DABNet', 'dabnet_cityscapes']
import os
import torch
import torch.nn as nn
from .common import conv1x... | 16,345 | 28.505415 | 116 | py |
imgclsmob | imgclsmob-master/pytorch/pytorchcv/models/cgnet.py | """
CGNet for image segmentation, implemented in PyTorch.
Original paper: 'CGNet: A Light-weight Context Guided Network for Semantic Segmentation,'
https://arxiv.org/abs/1811.08201.
"""
__all__ = ['CGNet', 'cgnet_cityscapes']
import os
import torch
import torch.nn as nn
from .common import NormActivation,... | 13,575 | 28.577342 | 115 | py |
imgclsmob | imgclsmob-master/pytorch/pytorchcv/models/wrn1bit_cifar.py | """
WRN-1bit for CIFAR/SVHN, implemented in PyTorch.
Original paper: 'Training wide residual networks for deployment using a single bit for each weight,'
https://arxiv.org/abs/1802.08530.
"""
__all__ = ['CIFARWRN1bit', 'wrn20_10_1bit_cifar10', 'wrn20_10_1bit_cifar100', 'wrn20_10_1bit_svhn',
'wrn... | 24,899 | 30.558935 | 115 | py |
imgclsmob | imgclsmob-master/pytorch/pytorchcv/models/condensenet.py | """
CondenseNet for ImageNet-1K, implemented in PyTorch.
Original paper: 'CondenseNet: An Efficient DenseNet using Learned Group Convolutions,'
https://arxiv.org/abs/1711.09224.
"""
__all__ = ['CondenseNet', 'condensenet74_c4_g4', 'condensenet74_c8_g8']
import os
import torch
import torch.nn as nn
import ... | 14,732 | 28.059172 | 120 | py |
imgclsmob | imgclsmob-master/pytorch/pytorchcv/models/fbnet.py | """
FBNet for ImageNet-1K, implemented in PyTorch.
Original paper: 'FBNet: Hardware-Aware Efficient ConvNet Design via Differentiable Neural Architecture Search,'
https://arxiv.org/abs/1812.03443.
"""
__all__ = ['FBNet', 'fbnet_cb']
import os
import torch.nn as nn
import torch.nn.init as init
from .common... | 9,969 | 30.352201 | 116 | py |
imgclsmob | imgclsmob-master/pytorch/pytorchcv/models/visemenet.py | """
VisemeNet for speech-driven facial animation, implemented in PyTorch.
Original paper: 'VisemeNet: Audio-Driven Animator-Centric Speech Animation,' https://arxiv.org/abs/1805.09488.
"""
__all__ = ['VisemeNet', 'visemenet20']
import os
import torch
import torch.nn as nn
from .common import DenseBlock
clas... | 8,396 | 30.215613 | 119 | py |
imgclsmob | imgclsmob-master/pytorch/pytorchcv/models/fractalnet_cifar.py | """
FractalNet for CIFAR, implemented in PyTorch.
Original paper: 'FractalNet: Ultra-Deep Neural Networks without Residuals,' https://arxiv.org/abs/1605.07648.
"""
__all__ = ['CIFARFractalNet', 'fractalnet_cifar10', 'fractalnet_cifar100']
import os
import numpy as np
import torch
import torch.nn as nn
import ... | 15,954 | 31.038153 | 115 | py |
imgclsmob | imgclsmob-master/pytorch/pytorchcv/models/mobilenetv3.py | """
MobileNetV3 for ImageNet-1K, implemented in PyTorch.
Original paper: 'Searching for MobileNetV3,' https://arxiv.org/abs/1905.02244.
"""
__all__ = ['MobileNetV3', 'mobilenetv3_small_w7d20', 'mobilenetv3_small_wd2', 'mobilenetv3_small_w3d4',
'mobilenetv3_small_w1', 'mobilenetv3_small_w5d4', 'mobil... | 18,999 | 33.234234 | 118 | py |
imgclsmob | imgclsmob-master/pytorch/pytorchcv/models/diaresnet.py | """
DIA-ResNet for ImageNet-1K, implemented in PyTorch.
Original paper: 'DIANet: Dense-and-Implicit Attention Network,' https://arxiv.org/abs/1905.10671.
"""
__all__ = ['DIAResNet', 'diaresnet10', 'diaresnet12', 'diaresnet14', 'diaresnetbc14b', 'diaresnet16', 'diaresnet18',
'diaresnet26', 'diaresnet... | 24,132 | 32.058904 | 116 | py |
imgclsmob | imgclsmob-master/pytorch/pytorchcv/models/lffd.py | """
LFFD for face detection, implemented in PyTorch.
Original paper: 'LFFD: A Light and Fast Face Detector for Edge Devices,' https://arxiv.org/abs/1904.10633.
"""
__all__ = ['LFFD', 'lffd20x5s320v2_widerface', 'lffd25x8s560v1_widerface']
import os
import torch.nn as nn
from .common import conv3x3, conv1x1_bl... | 10,582 | 30.685629 | 115 | py |
imgclsmob | imgclsmob-master/pytorch/pytorchcv/models/sepreresnet.py | """
SE-PreResNet for ImageNet-1K, implemented in PyTorch.
Original paper: 'Squeeze-and-Excitation Networks,' https://arxiv.org/abs/1709.01507.
"""
__all__ = ['SEPreResNet', 'sepreresnet10', 'sepreresnet12', 'sepreresnet14', 'sepreresnet16', 'sepreresnet18',
'sepreresnet26', 'sepreresnetbc26b', 'sepr... | 18,420 | 32.371377 | 119 | py |
imgclsmob | imgclsmob-master/pytorch/pytorchcv/models/resnext.py | """
ResNeXt for ImageNet-1K, implemented in PyTorch.
Original paper: 'Aggregated Residual Transformations for Deep Neural Networks,' http://arxiv.org/abs/1611.05431.
"""
__all__ = ['ResNeXt', 'resnext14_16x4d', 'resnext14_32x2d', 'resnext14_32x4d', 'resnext26_16x4d', 'resnext26_32x2d',
'resnext26_32... | 14,857 | 31.090713 | 119 | py |
imgclsmob | imgclsmob-master/pytorch/pytorchcv/models/jasper.py | """
Jasper/DR for ASR, implemented in PyTorch.
Original paper: 'Jasper: An End-to-End Convolutional Neural Acoustic Model,' https://arxiv.org/abs/1904.03288.
"""
__all__ = ['Jasper', 'jasper5x3', 'jasper10x4', 'jasper10x5', 'get_jasper', 'MaskConv1d', 'NemoAudioReader',
'NemoMelSpecExtractor', 'CtcD... | 35,202 | 29.347414 | 117 | py |
imgclsmob | imgclsmob-master/pytorch/pytorchcv/models/resneta.py | """
ResNet(A) with average downsampling for ImageNet-1K, implemented in PyTorch.
Original paper: 'Deep Residual Learning for Image Recognition,' https://arxiv.org/abs/1512.03385.
"""
__all__ = ['ResNetA', 'resneta10', 'resnetabc14b', 'resneta18', 'resneta50b', 'resneta101b', 'resneta152b']
import os
import to... | 14,395 | 32.094253 | 115 | py |
imgclsmob | imgclsmob-master/pytorch/pytorchcv/models/resnesta.py | """
ResNeSt(A) with average downsampling for ImageNet-1K, implemented in PyTorch.
Original paper: 'ResNeSt: Split-Attention Networks,' https://arxiv.org/abs/2004.08955.
"""
__all__ = ['ResNeStA', 'resnestabc14', 'resnesta18', 'resnestabc26', 'resnesta50', 'resnesta101', 'resnesta152',
'resnesta200',... | 17,572 | 30.892922 | 115 | py |
imgclsmob | imgclsmob-master/pytorch/pytorchcv/models/senet.py | """
SENet for ImageNet-1K, implemented in PyTorch.
Original paper: 'Squeeze-and-Excitation Networks,' https://arxiv.org/abs/1709.01507.
"""
__all__ = ['SENet', 'senet16', 'senet28', 'senet40', 'senet52', 'senet103', 'senet154', 'SEInitBlock']
import os
import math
import torch.nn as nn
import torch.nn.init as... | 13,095 | 28.696145 | 115 | py |
imgclsmob | imgclsmob-master/pytorch/pytorchcv/models/diapreresnet_cifar.py | """
DIA-PreResNet for CIFAR/SVHN, implemented in PyTorch.
Original papers: 'DIANet: Dense-and-Implicit Attention Network,' https://arxiv.org/abs/1905.10671.
"""
__all__ = ['CIFARDIAPreResNet', 'diapreresnet20_cifar10', 'diapreresnet20_cifar100', 'diapreresnet20_svhn',
'diapreresnet56_cifar10', 'diap... | 20,604 | 36.327899 | 120 | py |
imgclsmob | imgclsmob-master/pytorch/pytorchcv/models/simplepose_coco.py | """
SimplePose for COCO Keypoint, implemented in PyTorch.
Original paper: 'Simple Baselines for Human Pose Estimation and Tracking,' https://arxiv.org/abs/1804.06208.
"""
__all__ = ['SimplePose', 'simplepose_resnet18_coco', 'simplepose_resnet50b_coco', 'simplepose_resnet101b_coco',
'simplepose_resne... | 12,777 | 36.145349 | 118 | py |
imgclsmob | imgclsmob-master/pytorch/pytorchcv/models/vovnet.py | """
VoVNet for ImageNet-1K, implemented in PyTorch.
Original paper: 'An Energy and GPU-Computation Efficient Backbone Network for Real-Time Object Detection,'
https://arxiv.org/abs/1904.09730.
"""
__all__ = ['VoVNet', 'vovnet27s', 'vovnet39', 'vovnet57']
import os
import torch.nn as nn
from .common import... | 10,220 | 29.601796 | 120 | py |
imgclsmob | imgclsmob-master/pytorch/pytorchcv/models/espnetv2.py | """
ESPNetv2 for ImageNet-1K, implemented in PyTorch.
Original paper: 'ESPNetv2: A Light-weight, Power Efficient, and General Purpose Convolutional Neural Network,'
https://arxiv.org/abs/1811.11431.
"""
__all__ = ['ESPNetv2', 'espnetv2_wd2', 'espnetv2_w1', 'espnetv2_w5d4', 'espnetv2_w3d2', 'espnetv2_w2']
... | 17,203 | 30.336976 | 118 | py |
imgclsmob | imgclsmob-master/pytorch/pytorchcv/models/shufflenet.py | """
ShuffleNet for ImageNet-1K, implemented in PyTorch.
Original paper: 'ShuffleNet: An Extremely Efficient Convolutional Neural Network for Mobile Devices,'
https://arxiv.org/abs/1707.01083.
"""
__all__ = ['ShuffleNet', 'shufflenet_g1_w1', 'shufflenet_g2_w1', 'shufflenet_g3_w1', 'shufflenet_g4_w1',
... | 15,779 | 31.875 | 120 | py |
imgclsmob | imgclsmob-master/pytorch/pytorchcv/models/bamresnet.py | """
BAM-ResNet for ImageNet-1K, implemented in PyTorch.
Original paper: 'BAM: Bottleneck Attention Module,' https://arxiv.org/abs/1807.06514.
"""
__all__ = ['BamResNet', 'bam_resnet18', 'bam_resnet34', 'bam_resnet50', 'bam_resnet101', 'bam_resnet152']
import os
import torch.nn as nn
import torch.nn.init as in... | 13,297 | 28.420354 | 115 | py |
imgclsmob | imgclsmob-master/pytorch/pytorchcv/models/resattnet.py | """
ResAttNet for ImageNet-1K, implemented in PyTorch.
Original paper: 'Residual Attention Network for Image Classification,' https://arxiv.org/abs/1704.06904.
"""
__all__ = ['ResAttNet', 'resattnet56', 'resattnet92', 'resattnet128', 'resattnet164', 'resattnet200', 'resattnet236',
'resattnet452']
i... | 20,035 | 28.464706 | 117 | py |
imgclsmob | imgclsmob-master/pytorch/pytorchcv/models/centernet.py | """
CenterNet for ImageNet-1K, implemented in PyTorch.
Original paper: 'Objects as Points,' https://arxiv.org/abs/1904.07850.
"""
__all__ = ['CenterNet', 'centernet_resnet18_voc', 'centernet_resnet18_coco', 'centernet_resnet50b_voc',
'centernet_resnet50b_coco', 'centernet_resnet101b_voc', 'centernet... | 16,535 | 32.204819 | 118 | py |
imgclsmob | imgclsmob-master/pytorch/pytorchcv/models/xdensenet_cifar.py | """
X-DenseNet for CIFAR/SVHN, implemented in PyTorch.
Original paper: 'Deep Expander Networks: Efficient Deep Networks from Graph Theory,'
https://arxiv.org/abs/1711.08757.
"""
__all__ = ['CIFARXDenseNet', 'xdensenet40_2_k24_bc_cifar10', 'xdensenet40_2_k24_bc_cifar100',
'xdensenet40_2_k24_bc_sv... | 12,852 | 33.831978 | 115 | py |
imgclsmob | imgclsmob-master/pytorch/pytorchcv/models/revnet.py | """
RevNet for ImageNet-1K, implemented in PyTorch.
Original paper: 'The Reversible Residual Network: Backpropagation Without Storing Activations,'
https://arxiv.org/abs/1707.04585.
"""
__all__ = ['RevNet', 'revnet38', 'revnet110', 'revnet164']
import os
from contextlib import contextmanager
import torch
... | 15,590 | 28.142056 | 115 | py |
imgclsmob | imgclsmob-master/pytorch/pytorchcv/models/ntsnet_cub.py | """
NTS-Net for CUB-200-2011, implemented in PyTorch.
Original paper: 'Learning to Navigate for Fine-grained Classification,' https://arxiv.org/abs/1809.00287.
"""
__all__ = ['NTSNet', 'ntsnet_cub']
import os
import numpy as np
import torch
import torch.nn as nn
import torch.nn.functional as F
import torch.nn... | 14,019 | 32.54067 | 115 | py |
imgclsmob | imgclsmob-master/pytorch/pytorchcv/models/proxylessnas_cub.py | """
ProxylessNAS for CUB-200-2011, implemented in Gluon.
Original paper: 'ProxylessNAS: Direct Neural Architecture Search on Target Task and Hardware,'
https://arxiv.org/abs/1812.00332.
"""
__all__ = ['proxylessnas_cpu_cub', 'proxylessnas_gpu_cub', 'proxylessnas_mobile_cub', 'proxylessnas_mobile14_cub']
f... | 4,155 | 32.788618 | 120 | py |
imgclsmob | imgclsmob-master/pytorch/pytorchcv/models/ibnresnet.py | """
IBN-ResNet for ImageNet-1K, implemented in PyTorch.
Original paper: 'Two at Once: Enhancing Learning and Generalization Capacities via IBN-Net,'
https://arxiv.org/abs/1807.09441.
"""
__all__ = ['IBNResNet', 'ibn_resnet50', 'ibn_resnet101', 'ibn_resnet152']
import os
import torch.nn as nn
import torch.... | 12,570 | 29.002387 | 115 | py |
imgclsmob | imgclsmob-master/pytorch/pytorchcv/models/common.py | """
Common routines for models in PyTorch.
"""
__all__ = ['round_channels', 'Identity', 'BreakBlock', 'Swish', 'HSigmoid', 'HSwish', 'get_activation_layer',
'SelectableDense', 'DenseBlock', 'ConvBlock1d', 'conv1x1', 'conv3x3', 'depthwise_conv3x3', 'ConvBlock',
'conv1x1_block', 'conv3x3_block'... | 74,363 | 30.902188 | 130 | py |
imgclsmob | imgclsmob-master/pytorch/pytorchcv/models/lwopenpose_cmupan.py | """
Lightweight OpenPose 2D/3D for CMU Panoptic, implemented in PyTorch.
Original paper: 'Real-time 2D Multi-Person Pose Estimation on CPU: Lightweight OpenPose,'
https://arxiv.org/abs/1811.12004.
"""
__all__ = ['LwOpenPose', 'lwopenpose2d_mobilenet_cmupan_coco', 'lwopenpose3d_mobilenet_cmupan_coco',
... | 21,152 | 31.643519 | 119 | py |
imgclsmob | imgclsmob-master/pytorch/pytorchcv/models/rir_cifar.py | """
RiR for CIFAR/SVHN, implemented in PyTorch.
Original paper: 'Resnet in Resnet: Generalizing Residual Architectures,' https://arxiv.org/abs/1603.08029.
"""
__all__ = ['CIFARRiR', 'rir_cifar10', 'rir_cifar100', 'rir_svhn', 'RiRFinalBlock']
import os
import torch
import torch.nn as nn
import torch.nn.init as... | 10,658 | 29.454286 | 119 | py |
imgclsmob | imgclsmob-master/pytorch/pytorchcv/models/unet.py | """
U-Net for image segmentation, implemented in PyTorch.
Original paper: 'U-Net: Convolutional Networks for Biomedical Image Segmentation,'
https://arxiv.org/abs/1505.04597.
"""
__all__ = ['UNet', 'unet_cityscapes']
import os
import torch
import torch.nn as nn
from .common import conv1x1, conv3x3_block, ... | 9,378 | 27.335347 | 115 | py |
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