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imgclsmob | imgclsmob-master/pytorch/metrics/cls_metrics.py | """
Evaluation Metrics for Image Classification.
"""
import numpy as np
import torch
from .metric import EvalMetric
__all__ = ['Top1Error', 'TopKError']
class Accuracy(EvalMetric):
"""
Computes accuracy classification score.
Parameters:
----------
axis : int, default 1
The axis that rep... | 8,783 | 33.996016 | 99 | py |
imgclsmob | imgclsmob-master/pytorch/metrics/det_metrics.py | """
Evaluation Metrics for Object Detection.
"""
import warnings
import numpy as np
import mxnet as mx
__all__ = ['CocoDetMApMetric']
class CocoDetMApMetric(mx.metric.EvalMetric):
"""
Detection metric for COCO bbox task.
Parameters:
----------
img_height : int
Processed image height.
... | 8,548 | 36.495614 | 119 | py |
imgclsmob | imgclsmob-master/pytorch/metrics/hpe_metrics.py | """
Evaluation Metrics for Human Pose Estimation.
"""
from .metric import EvalMetric
__all__ = ['CocoHpeOksApMetric']
class CocoHpeOksApMetric(EvalMetric):
"""
Detection metric for COCO Keypoint task.
Parameters:
----------
coco_annotations_file_path : str
COCO anotation file path.
... | 3,966 | 32.058333 | 98 | py |
imgclsmob | imgclsmob-master/pytorch/metrics/asr_metrics.py | """
Evaluation Metrics for Automatic Speech Recognition (ASR).
"""
from .metric import EvalMetric
__all__ = ['WER']
class WER(EvalMetric):
"""
Computes Word Error Rate (WER) for Automatic Speech Recognition (ASR).
Parameters:
----------
vocabulary : list of str
Vocabulary of the dataset... | 3,814 | 30.528926 | 114 | py |
imgclsmob | imgclsmob-master/pytorch/metrics/metric.py | """
Several base metrics.
"""
__all__ = ['EvalMetric', 'CompositeEvalMetric', 'check_label_shapes']
from collections import OrderedDict
def check_label_shapes(labels, preds, shape=False):
"""
Helper function for checking shape of label and prediction.
Parameters:
----------
labels : list of... | 9,289 | 27.323171 | 117 | py |
imgclsmob | imgclsmob-master/pytorch/datasets/imagenet1k_cls_dataset.py | """
ImageNet-1K classification dataset.
"""
import os
import math
import cv2
import numpy as np
from PIL import Image
from torchvision.datasets import ImageFolder
import torchvision.transforms as transforms
from .dataset_metainfo import DatasetMetaInfo
class ImageNet1K(ImageFolder):
"""
ImageNet-1K class... | 8,645 | 30.44 | 110 | py |
imgclsmob | imgclsmob-master/pytorch/datasets/hpe_dataset.py | """
Keypoint detection (2D single human pose estimation) dataset.
"""
import copy
import logging
import random
import cv2
import numpy as np
import torch
import torch.utils.data as data
class HpeDataset(data.Dataset):
def __init__(self,
cfg,
root,
image_set,... | 9,597 | 32.559441 | 110 | py |
imgclsmob | imgclsmob-master/pytorch/datasets/coco_hpe1_dataset.py | """
COCO keypoint detection (2D single human pose estimation) dataset.
"""
import os
import copy
import cv2
import numpy as np
import torch
import torch.utils.data as data
from .dataset_metainfo import DatasetMetaInfo
class CocoHpe1Dataset(data.Dataset):
"""
COCO keypoint detection (2D single human pose ... | 30,012 | 33.817865 | 119 | py |
imgclsmob | imgclsmob-master/pytorch/datasets/coco_det_dataset.py | """
MS COCO object detection dataset.
"""
import os
import cv2
import logging
import mxnet as mx
import numpy as np
from PIL import Image
import torch.utils.data as data
from .dataset_metainfo import DatasetMetaInfo
__all__ = ['CocoDetMetaInfo']
class CocoDetDataset(data.Dataset):
"""
MS COCO detection datas... | 27,185 | 35.688259 | 119 | py |
imgclsmob | imgclsmob-master/pytorch/datasets/seg_dataset.py | import random
import numpy as np
from PIL import Image, ImageOps, ImageFilter
import torch.utils.data as data
class SegDataset(data.Dataset):
"""
Segmentation base dataset.
Parameters:
----------
root : str
Path to the folder stored the dataset.
mode : str
'train', 'val', 'tes... | 3,366 | 33.010101 | 89 | py |
imgclsmob | imgclsmob-master/pytorch/datasets/coco_hpe2_dataset.py | """
COCO keypoint detection (2D multiple human pose estimation) dataset (for Lightweight OpenPose).
"""
import os
import json
import math
import cv2
from operator import itemgetter
import numpy as np
import torch
import torch.utils.data as data
from .dataset_metainfo import DatasetMetaInfo
class CocoHpe2Dataset(... | 20,780 | 39.747059 | 119 | py |
imgclsmob | imgclsmob-master/pytorch/datasets/svhn_cls_dataset.py | """
SVHN classification dataset.
"""
import os
from torchvision.datasets import SVHN
from .cifar10_cls_dataset import CIFAR10MetaInfo
class SVHNFine(SVHN):
"""
SVHN image classification dataset from http://ufldl.stanford.edu/housenumbers/.
Each sample is an image (in 3D NDArray) with shape (32, 32, 3... | 1,364 | 30.022727 | 93 | py |
imgclsmob | imgclsmob-master/pytorch/datasets/coco_hpe3_dataset.py | """
COCO keypoint detection (2D multiple human pose estimation) dataset (for IBPPose).
"""
import os
# import json
import math
import cv2
import numpy as np
import torch
from torch.nn import functional as F
import torch.utils.data as data
from .dataset_metainfo import DatasetMetaInfo
class CocoHpe3Dataset(data.D... | 23,180 | 40.101064 | 120 | py |
imgclsmob | imgclsmob-master/pytorch/datasets/asr_dataset.py | """
Automatic Speech Recognition (ASR) abstract dataset.
"""
__all__ = ['AsrDataset', 'asr_test_transform']
import torch.utils.data as data
import torchvision.transforms as transforms
from pytorch.pytorchcv.models.jasper import NemoAudioReader
class AsrDataset(data.Dataset):
"""
Automatic Speech Recogni... | 1,385 | 25.653846 | 68 | py |
imgclsmob | imgclsmob-master/pytorch/datasets/cifar10_cls_dataset.py | """
CIFAR-10 classification dataset.
"""
import os
from torchvision.datasets import CIFAR10
import torchvision.transforms as transforms
from .dataset_metainfo import DatasetMetaInfo
class CIFAR10Fine(CIFAR10):
"""
CIFAR-10 image classification dataset.
Parameters:
----------
root : str, def... | 2,897 | 30.5 | 73 | py |
imgclsmob | imgclsmob-master/pytorch/datasets/librispeech_asr_dataset.py | """
LibriSpeech ASR dataset.
"""
__all__ = ['LibriSpeech', 'LibriSpeechMetaInfo']
import os
import numpy as np
from .dataset_metainfo import DatasetMetaInfo
from .asr_dataset import AsrDataset, asr_test_transform
class LibriSpeech(AsrDataset):
"""
LibriSpeech dataset for Automatic Speech Recognition (AS... | 5,294 | 37.369565 | 119 | py |
imgclsmob | imgclsmob-master/pytorch/datasets/cub200_2011_cls_dataset.py | """
CUB-200-2011 classification dataset.
"""
import os
import numpy as np
import pandas as pd
from PIL import Image
import torch.utils.data as data
from .imagenet1k_cls_dataset import ImageNet1KMetaInfo
class CUB200_2011(data.Dataset):
"""
CUB-200-2011 fine-grained classification dataset.
Parameters... | 5,320 | 34.711409 | 94 | py |
imgclsmob | imgclsmob-master/pytorch/datasets/mcv_asr_dataset.py | """
Mozilla Common Voice ASR dataset.
"""
__all__ = ['McvDataset', 'McvMetaInfo']
import os
import re
import numpy as np
import pandas as pd
from .dataset_metainfo import DatasetMetaInfo
from .asr_dataset import AsrDataset, asr_test_transform
class McvDataset(AsrDataset):
"""
Mozilla Common Voice datase... | 14,287 | 41.906907 | 119 | py |
imgclsmob | imgclsmob-master/pytorch/datasets/voc_seg_dataset.py | """
Pascal VOC2012 semantic segmentation dataset.
"""
import os
import numpy as np
from PIL import Image
import torchvision.transforms as transforms
from .seg_dataset import SegDataset
from .dataset_metainfo import DatasetMetaInfo
class VOCSegDataset(SegDataset):
"""
Pascal VOC2012 semantic segmentation ... | 5,894 | 33.273256 | 90 | py |
imgclsmob | imgclsmob-master/pytorch/datasets/cifar100_cls_dataset.py | """
CIFAR-100 classification dataset.
"""
import os
from torchvision.datasets import CIFAR100
from .cifar10_cls_dataset import CIFAR10MetaInfo
class CIFAR100Fine(CIFAR100):
"""
CIFAR-100 image classification dataset.
Parameters:
----------
root : str, default '~/.torch/datasets/cifar100'
... | 1,132 | 25.97619 | 74 | py |
imgclsmob | imgclsmob-master/pytorch/datasets/hpatches_mch_dataset.py | """
HPatches image matching dataset.
"""
import os
import cv2
import numpy as np
import torch.utils.data as data
import torchvision.transforms as transforms
from .dataset_metainfo import DatasetMetaInfo
class HPatches(data.Dataset):
"""
HPatches (full image sequences) image matching dataset.
Info URL... | 4,450 | 33.773438 | 101 | py |
imgclsmob | imgclsmob-master/pytorch/pytorchcv/models/airnext.py | """
AirNeXt for ImageNet-1K, implemented in PyTorch.
Original paper: 'Attention Inspiring Receptive-Fields Network for Learning Invariant Representations,'
https://ieeexplore.ieee.org/document/8510896.
"""
__all__ = ['AirNeXt', 'airnext50_32x4d_r2', 'airnext101_32x4d_r2', 'airnext101_32x4d_r16']
import os... | 11,535 | 29.041667 | 115 | py |
imgclsmob | imgclsmob-master/pytorch/pytorchcv/models/pspnet.py | """
PSPNet for image segmentation, implemented in PyTorch.
Original paper: 'Pyramid Scene Parsing Network,' https://arxiv.org/abs/1612.01105.
"""
__all__ = ['PSPNet', 'pspnet_resnetd50b_voc', 'pspnet_resnetd101b_voc', 'pspnet_resnetd50b_coco',
'pspnet_resnetd101b_coco', 'pspnet_resnetd50b_ade20k', '... | 18,380 | 35.909639 | 120 | py |
imgclsmob | imgclsmob-master/pytorch/pytorchcv/models/dla.py | """
DLA for ImageNet-1K, implemented in PyTorch.
Original paper: 'Deep Layer Aggregation,' https://arxiv.org/abs/1707.06484.
"""
__all__ = ['DLA', 'dla34', 'dla46c', 'dla46xc', 'dla60', 'dla60x', 'dla60xc', 'dla102', 'dla102x', 'dla102x2', 'dla169']
import os
import torch
import torch.nn as nn
import torch.nn... | 19,884 | 29.734158 | 120 | py |
imgclsmob | imgclsmob-master/pytorch/pytorchcv/models/proxylessnas.py | """
ProxylessNAS for ImageNet-1K, implemented in PyTorch.
Original paper: 'ProxylessNAS: Direct Neural Architecture Search on Target Task and Hardware,'
https://arxiv.org/abs/1812.00332.
"""
__all__ = ['ProxylessNAS', 'proxylessnas_cpu', 'proxylessnas_gpu', 'proxylessnas_mobile', 'proxylessnas_mobile14',
... | 14,555 | 33.492891 | 118 | py |
imgclsmob | imgclsmob-master/pytorch/pytorchcv/models/isqrtcovresnet.py | """
iSQRT-COV-ResNet for ImageNet-1K, implemented in PyTorch.
Original paper: 'Towards Faster Training of Global Covariance Pooling Networks by Iterative Matrix Square Root
Normalization,' https://arxiv.org/abs/1712.01034.
"""
__all__ = ['iSQRTCOVResNet', 'isqrtcovresnet18', 'isqrtcovresnet34', 'isqrtcovre... | 15,872 | 33.885714 | 120 | py |
imgclsmob | imgclsmob-master/pytorch/pytorchcv/models/shufflenetv2.py | """
ShuffleNet V2 for ImageNet-1K, implemented in PyTorch.
Original paper: 'ShuffleNet V2: Practical Guidelines for Efficient CNN Architecture Design,'
https://arxiv.org/abs/1807.11164.
"""
__all__ = ['ShuffleNetV2', 'shufflenetv2_wd2', 'shufflenetv2_w1', 'shufflenetv2_w3d2', 'shufflenetv2_w2']
import os
... | 11,722 | 30.942779 | 115 | py |
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 |
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