repo stringlengths 2 99 | file stringlengths 13 225 | code stringlengths 0 18.3M | file_length int64 0 18.3M | avg_line_length float64 0 1.36M | max_line_length int64 0 4.26M | extension_type stringclasses 1
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imgclsmob | imgclsmob-master/chainer_/chainercv2/models/seresnet_cifar.py | """
SE-ResNet for CIFAR/SVHN, implemented in Chainer.
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',
... | 23,331 | 36.391026 | 120 | py |
imgclsmob | imgclsmob-master/chainer_/chainercv2/models/resnetd.py | """
ResNet(D) with dilation for ImageNet-1K, implemented in Chainer.
Original paper: 'Deep Residual Learning for Image Recognition,' https://arxiv.org/abs/1512.03385.
"""
__all__ = ['ResNetD', 'resnetd50b', 'resnetd101b', 'resnetd152b']
import os
import chainer.functions as F
import chainer.links as L
from ch... | 10,036 | 34.094406 | 120 | py |
imgclsmob | imgclsmob-master/chainer_/chainercv2/models/quartznet.py | """
QuartzNet for ASR, implemented in Chainer.
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'... | 13,081 | 42.899329 | 119 | py |
imgclsmob | imgclsmob-master/chainer_/chainercv2/models/preresnet.py | """
PreResNet for ImageNet-1K, implemented in Chainer.
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... | 27,215 | 32.766749 | 120 | py |
imgclsmob | imgclsmob-master/chainer_/chainercv2/models/lednet.py | """
LEDNet for image segmentation, implemented in Chainer.
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 chainer.functions as F
from chainer import Chain
... | 19,734 | 31.246732 | 117 | py |
imgclsmob | imgclsmob-master/chainer_/chainercv2/models/hardnet.py | """
HarDNet for ImageNet-1K, implemented in Chainer.
Original paper: 'HarDNet: A Low Memory Traffic Network,' https://arxiv.org/abs/1909.00948.
"""
__all__ = ['HarDNet', 'hardnet39ds', 'hardnet68ds', 'hardnet68', 'hardnet85']
import os
import chainer.functions as F
import chainer.links as L
from chainer impor... | 22,589 | 35.028708 | 120 | py |
imgclsmob | imgclsmob-master/chainer_/chainercv2/models/sinet.py | """
SINet for image segmentation, implemented in Chainer.
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 chainer.functi... | 36,537 | 31.917117 | 118 | py |
imgclsmob | imgclsmob-master/chainer_/chainercv2/models/shufflenetv2b.py | """
ShuffleNet V2 for ImageNet-1K, implemented in Chainer. 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', '... | 12,881 | 32.115681 | 115 | py |
imgclsmob | imgclsmob-master/chainer_/chainercv2/models/sparsenet.py | """
SparseNet for ImageNet-1K, implemented in Chainer.
Original paper: 'Sparsely Aggregated Convolutional Networks,' https://arxiv.org/abs/1801.05895.
"""
__all__ = ['SparseNet', 'sparsenet121', 'sparsenet161', 'sparsenet169', 'sparsenet201', 'sparsenet264']
import os
import math
import chainer.functions as F... | 12,001 | 30.751323 | 115 | py |
imgclsmob | imgclsmob-master/chainer_/chainercv2/models/menet.py | """
MENet for ImageNet-1K, implemented in Chainer.
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_... | 16,444 | 33.118257 | 116 | py |
imgclsmob | imgclsmob-master/chainer_/chainercv2/models/voca.py | """
VOCA for speech-driven facial animation, implemented in Chainer.
Original paper: 'Capture, Learning, and Synthesis of 3D Speaking Styles,' https://arxiv.org/abs/1905.03079.
"""
__all__ = ['VOCA', 'voca8flame']
import os
import chainer.functions as F
import chainer.links as L
from chainer import Chain
from... | 6,615 | 29.915888 | 115 | py |
imgclsmob | imgclsmob-master/chainer_/chainercv2/models/shakeshakeresnet_cifar.py | """
Shake-Shake-ResNet for CIFAR/SVHN, implemented in Chainer.
Original paper: 'Shake-Shake regularization,' https://arxiv.org/abs/1705.07485.
"""
__all__ = ['CIFARShakeShakeResNet', 'shakeshakeresnet20_2x16d_cifar10', 'shakeshakeresnet20_2x16d_cifar100',
'shakeshakeresnet20_2x16d_svhn', 'shakeshake... | 14,965 | 34.548694 | 120 | py |
imgclsmob | imgclsmob-master/chainer_/chainercv2/models/wrn_cifar.py | """
WRN for CIFAR/SVHN, implemented in Chainer.
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... | 11,367 | 33.871166 | 115 | py |
imgclsmob | imgclsmob-master/chainer_/chainercv2/models/inceptionresnetv2.py | """
InceptionResNetV2 for ImageNet-1K, implemented in Chainer.
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 chainer.functions as F
import chai... | 10,482 | 33.59736 | 117 | py |
imgclsmob | imgclsmob-master/chainer_/chainercv2/models/ghostnet.py | """
GhostNet for ImageNet-1K, implemented in Chainer.
Original paper: 'GhostNet: More Features from Cheap Operations,' https://arxiv.org/abs/1911.11907.
"""
__all__ = ['GhostNet', 'ghostnet']
import os
import math
import chainer.functions as F
from chainer import Chain
from functools import partial
from chain... | 13,315 | 31.79803 | 115 | py |
imgclsmob | imgclsmob-master/chainer_/chainercv2/models/efficientnet.py | """
EfficientNet for ImageNet-1K, implemented in Chainer.
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',... | 38,516 | 36.761765 | 120 | py |
imgclsmob | imgclsmob-master/chainer_/chainercv2/models/channelnet.py | """
ChannelNet for ImageNet-1K, implemented in Chainer.
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 chainer.functions as F
import chainer.link... | 19,610 | 31.14918 | 117 | py |
imgclsmob | imgclsmob-master/chainer_/chainercv2/models/pnasnet.py | """
PNASNet for ImageNet-1K, implemented in Chainer.
Original paper: 'Progressive Neural Architecture Search,' https://arxiv.org/abs/1712.00559.
"""
__all__ = ['PNASNet', 'pnasnet5large']
import os
import chainer.functions as F
import chainer.links as L
from chainer import Chain
from functools import partial... | 18,807 | 30.139073 | 120 | py |
imgclsmob | imgclsmob-master/chainer_/chainercv2/models/efficientnetedge.py | """
EfficientNet-Edge for ImageNet-1K, implemented in Chainer.
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... | 15,366 | 37.610553 | 118 | py |
imgclsmob | imgclsmob-master/chainer_/chainercv2/models/squeezenext.py | """
SqueezeNext for ImageNet-1K, implemented in Chainer.
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 chainer.f... | 12,675 | 32.010417 | 119 | py |
imgclsmob | imgclsmob-master/chainer_/chainercv2/models/xdensenet.py | """
X-DenseNet for ImageNet-1K, implemented in Chainer.
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',
... | 17,412 | 30.717668 | 117 | py |
imgclsmob | imgclsmob-master/chainer_/chainercv2/models/diaresnet_cifar.py | """
DIA-ResNet for CIFAR/SVHN, implemented in Chainer.
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', ... | 19,930 | 35.841035 | 120 | py |
imgclsmob | imgclsmob-master/chainer_/chainercv2/models/resdropresnet_cifar.py | """
ResDrop-ResNet for CIFAR/SVHN, implemented in Chainer.
Original paper: 'Deep Networks with Stochastic Depth,' https://arxiv.org/abs/1603.09382.
"""
__all__ = ['CIFARResDropResNet', 'resdropresnet20_cifar10', 'resdropresnet20_cifar100', 'resdropresnet20_svhn']
import os
from chainer import backend
from cha... | 10,196 | 33.103679 | 119 | py |
imgclsmob | imgclsmob-master/chainer_/chainercv2/models/bisenet.py | """
BiSeNet for CelebAMask-HQ, implemented in Chainer.
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 chainer.functions as F
from chainer import Cha... | 13,212 | 29.943794 | 119 | py |
imgclsmob | imgclsmob-master/chainer_/chainercv2/models/resnet.py | """
ResNet for ImageNet-1K, implemented in Chainer.
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', '... | 25,928 | 32.370656 | 120 | py |
imgclsmob | imgclsmob-master/chainer_/chainercv2/models/simpleposemobile_coco.py | """
SimplePose(Mobile) for COCO Keypoint, implemented in Chainer.
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_... | 12,638 | 38.870662 | 120 | py |
imgclsmob | imgclsmob-master/chainer_/chainercv2/models/cbamresnet.py | """
CBAM-ResNet for ImageNet-1K, implemented in Chainer.
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 chainer.functions as F
i... | 13,242 | 29.726218 | 115 | py |
imgclsmob | imgclsmob-master/chainer_/chainercv2/models/diracnetv2.py | """
DiracNetV2 for ImageNet-1K, implemented in Chainer.
Original paper: 'DiracNets: Training Very Deep Neural Networks Without Skip-Connections,'
https://arxiv.org/abs/1706.00388.
"""
__all__ = ['DiracNetV2', 'diracnet18v2', 'diracnet34v2']
import os
import chainer.functions as F
import chainer.links as L... | 8,791 | 29.109589 | 115 | py |
imgclsmob | imgclsmob-master/chainer_/chainercv2/models/sepreresnet_cifar.py | """
SE-PreResNet for CIFAR/SVHN, implemented in Chainer.
Original paper: 'Squeeze-and-Excitation Networks,' https://arxiv.org/abs/1709.01507.
"""
__all__ = ['CIFARSEPreResNet', 'sepreresnet20_cifar10', 'sepreresnet20_cifar100', 'sepreresnet20_svhn',
'sepreresnet56_cifar10', 'sepreresnet56_cifar100',... | 24,348 | 37.22449 | 119 | py |
imgclsmob | imgclsmob-master/chainer_/chainercv2/models/danet.py | """
DANet for image segmentation, implemented in Chainer.
Original paper: 'Dual Attention Network for Scene Segmentation,' https://arxiv.org/abs/1809.02983.
"""
__all__ = ['DANet', 'danet_resnetd50b_cityscapes', 'danet_resnetd101b_cityscapes']
import os
import chainer.functions as F
from chainer import link
... | 12,551 | 30.938931 | 116 | py |
imgclsmob | imgclsmob-master/chainer_/chainercv2/models/mobilenetv2.py | """
MobileNetV2 for ImageNet-1K, implemented in Chainer.
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... | 13,097 | 34.02139 | 120 | py |
imgclsmob | imgclsmob-master/chainer_/chainercv2/models/squeezenet.py | """
SqueezeNet for ImageNet-1K, implemented in Chainer.
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... | 12,298 | 31.885027 | 118 | py |
imgclsmob | imgclsmob-master/chainer_/chainercv2/models/nin_cifar.py | """
NIN for CIFAR/SVHN, implemented in Chainer.
Original paper: 'Network In Network,' https://arxiv.org/abs/1312.4400.
"""
__all__ = ['CIFARNIN', 'nin_cifar10', 'nin_cifar100', 'nin_svhn']
import os
import chainer.functions as F
import chainer.links as L
from chainer import Chain
from functools import partial... | 8,429 | 31.548263 | 115 | py |
imgclsmob | imgclsmob-master/chainer_/chainercv2/models/vgg.py | """
VGG for ImageNet-1K, implemented in Chainer.
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... | 13,926 | 30.724374 | 117 | py |
imgclsmob | imgclsmob-master/chainer_/chainercv2/models/resnet_cub.py | """
ResNet for CUB-200-2011, implemented in Chainer.
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', ... | 13,734 | 34.955497 | 117 | py |
imgclsmob | imgclsmob-master/chainer_/chainercv2/models/bagnet.py | """
BagNet for ImageNet-1K, implemented in Chainer.
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 chainer.functions as F
impo... | 11,198 | 30.546479 | 116 | py |
imgclsmob | imgclsmob-master/chainer_/chainercv2/models/airnet.py | """
AirNet for ImageNet-1K, implemented in Chainer.
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... | 12,994 | 30.01432 | 115 | py |
imgclsmob | imgclsmob-master/chainer_/chainercv2/models/mnasnet.py | """
MnasNet for ImageNet-1K, implemented in Chainer.
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 chainer.functions as F
import chainer.links as L
from ... | 14,700 | 33.91924 | 118 | py |
imgclsmob | imgclsmob-master/chainer_/chainercv2/models/pyramidnet_cifar.py | """
PyramidNet for CIFAR/SVHN, implemented in Chainer.
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... | 23,657 | 32.509915 | 120 | py |
imgclsmob | imgclsmob-master/chainer_/chainercv2/models/preresnet_cifar.py | """
PreResNet for CIFAR/SVHN, implemented in Chainer.
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', '... | 24,311 | 35.892261 | 120 | py |
imgclsmob | imgclsmob-master/chainer_/chainercv2/models/alphapose_coco.py | """
AlphaPose for COCO Keypoint, implemented in Chainer.
Original paper: 'RMPE: Regional Multi-person Pose Estimation,' https://arxiv.org/abs/1612.00137.
"""
__all__ = ['AlphaPose', 'alphapose_fastseresnet101b_coco']
import os
from chainer import Chain
from chainer.serializers import load_npz
from .common imp... | 6,223 | 32.283422 | 116 | py |
imgclsmob | imgclsmob-master/chainer_/chainercv2/models/pyramidnet.py | """
PyramidNet for ImageNet-1K, implemented in Chainer.
Original paper: 'Deep Pyramidal Residual Networks,' https://arxiv.org/abs/1610.02915.
"""
__all__ = ['PyramidNet', 'pyramidnet101_a360', 'PyrUnit']
import os
import chainer.functions as F
import chainer.links as L
from chainer import Chain
from functools... | 11,789 | 29.544041 | 115 | py |
imgclsmob | imgclsmob-master/chainer_/chainercv2/models/seresnet.py | """
SE-ResNet for ImageNet-1K, implemented in Chainer.
Original paper: 'Squeeze-and-Excitation Networks,' https://arxiv.org/abs/1709.01507.
"""
__all__ = ['SEResNet', 'seresnet10', 'seresnet12', 'seresnet14', 'seresnet16', 'seresnet18', 'seresnet26',
'seresnetbc26b', 'seresnet34', 'seresnetbc38b', '... | 18,495 | 32.446655 | 118 | py |
imgclsmob | imgclsmob-master/chainer_/chainercv2/models/seresnet_cub.py | """
SE-ResNet for CUB-200-2011, implemented in Chainer.
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_... | 13,761 | 35.407407 | 120 | py |
imgclsmob | imgclsmob-master/chainer_/chainercv2/models/densenet.py | """
DenseNet for ImageNet-1K, implemented in Chainer.
Original paper: 'Densely Connected Convolutional Networks,' https://arxiv.org/abs/1608.06993.
"""
__all__ = ['DenseNet', 'densenet121', 'densenet161', 'densenet169', 'densenet201', 'DenseUnit', 'TransitionBlock']
import os
import chainer.functions as F
imp... | 10,417 | 31.354037 | 116 | py |
imgclsmob | imgclsmob-master/chainer_/chainercv2/models/seresnext.py | """
SE-ResNeXt for ImageNet-1K, implemented in Chainer.
Original paper: 'Squeeze-and-Excitation Networks,' https://arxiv.org/abs/1709.01507.
"""
__all__ = ['SEResNeXt', 'seresnext50_32x4d', 'seresnext101_32x4d', 'seresnext101_64x4d']
import os
import chainer.functions as F
import chainer.links as L
from chain... | 8,957 | 31.456522 | 115 | py |
imgclsmob | imgclsmob-master/chainer_/chainercv2/models/darts.py | """
DARTS for ImageNet-1K, implemented in Chainer.
Original paper: 'DARTS: Differentiable Architecture Search,' https://arxiv.org/abs/1806.09055.
"""
__all__ = ['DARTS', 'darts']
import os
import chainer.functions as F
import chainer.links as L
from chainer import Chain
from functools import partial
from chai... | 21,007 | 27.504749 | 115 | py |
imgclsmob | imgclsmob-master/chainer_/chainercv2/models/drn.py | """
DRN for ImageNet-1K, implemented in Chainer.
Original paper: 'Dilated Residual Networks,' https://arxiv.org/abs/1705.09914.
"""
__all__ = ['DRN', 'drnc26', 'drnc42', 'drnc58', 'drnd22', 'drnd38', 'drnd54', 'drnd105']
import os
import chainer.functions as F
import chainer.links as L
from chainer import Cha... | 19,329 | 29.488959 | 118 | py |
imgclsmob | imgclsmob-master/chainer_/chainercv2/models/mixnet.py | """
MixNet for ImageNet-1K, implemented in Chainer.
Original paper: 'MixConv: Mixed Depthwise Convolutional Kernels,' https://arxiv.org/abs/1907.09595.
"""
__all__ = ['MixNet', 'mixnet_s', 'mixnet_m', 'mixnet_l']
import os
import chainer.functions as F
import chainer.links as L
from chainer import Chain
from ... | 21,565 | 34.354098 | 116 | py |
imgclsmob | imgclsmob-master/chainer_/chainercv2/models/dabnet.py | """
DABNet for image segmentation, implemented in Chainer.
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 chainer.functions as F
import chainer.links as L
from ... | 17,130 | 29.428064 | 116 | py |
imgclsmob | imgclsmob-master/chainer_/chainercv2/models/cgnet.py | """
CGNet for image segmentation, implemented in Chainer.
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 chainer.functions as F
import chainer.links as L
from chainer i... | 14,152 | 29.767391 | 115 | py |
imgclsmob | imgclsmob-master/chainer_/chainercv2/models/wrn1bit_cifar.py | """
WRN-1bit for CIFAR/SVHN, implemented in Chainer.
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... | 25,496 | 31.031407 | 125 | py |
imgclsmob | imgclsmob-master/chainer_/chainercv2/models/condensenet.py | """
CondenseNet for ImageNet-1K, implemented in Chainer.
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 numpy as np
import chainer.function... | 15,017 | 28.679842 | 120 | py |
imgclsmob | imgclsmob-master/chainer_/chainercv2/models/fbnet.py | """
FBNet for ImageNet-1K, implemented in Chainer.
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 chainer.functions as F
import chainer.links as L
from ch... | 10,419 | 32.290735 | 116 | py |
imgclsmob | imgclsmob-master/chainer_/chainercv2/models/mobilenetv3.py | """
MobileNetV3 for ImageNet-1K, implemented in Chainer.
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... | 19,635 | 34.508137 | 118 | py |
imgclsmob | imgclsmob-master/chainer_/chainercv2/models/diaresnet.py | """
DIA-ResNet for ImageNet-1K, implemented in Chainer.
Original paper: 'DIANet: Dense-and-Implicit Attention Network,' https://arxiv.org/abs/1905.10671.
"""
__all__ = ['DIAResNet', 'diaresnet10', 'diaresnet12', 'diaresnet14', 'diaresnetbc14b', 'diaresnet16', 'diaresnet18',
'diaresnet26', 'diaresnet... | 25,200 | 33.055405 | 116 | py |
imgclsmob | imgclsmob-master/chainer_/chainercv2/models/lffd.py | """
LFFD for face detection, implemented in Chainer.
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 chainer.functions as F
from chainer import Chain
from ... | 11,287 | 33.31003 | 115 | py |
imgclsmob | imgclsmob-master/chainer_/chainercv2/models/sepreresnet.py | """
SE-PreResNet for ImageNet-1K, implemented in Chainer.
Original paper: 'Squeeze-and-Excitation Networks,' https://arxiv.org/abs/1709.01507.
"""
__all__ = ['SEPreResNet', 'sepreresnet10', 'sepreresnet12', 'sepreresnet14', 'sepreresnet16', 'sepreresnet18',
'sepreresnet26', 'sepreresnetbc26b', 'sepr... | 18,746 | 33.209854 | 119 | py |
imgclsmob | imgclsmob-master/chainer_/chainercv2/models/resnext.py | """
ResNeXt for ImageNet-1K, implemented in Chainer.
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... | 15,179 | 32.144105 | 119 | py |
imgclsmob | imgclsmob-master/chainer_/chainercv2/models/jasper.py | """
Jasper/DR for ASR, implemented in Chainer.
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... | 34,656 | 30.912523 | 117 | py |
imgclsmob | imgclsmob-master/chainer_/chainercv2/models/resneta.py | """
ResNet(A) with average downsampling for ImageNet-1K, implemented in Chainer.
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 ch... | 15,093 | 33.382688 | 115 | py |
imgclsmob | imgclsmob-master/chainer_/chainercv2/models/resnesta.py | """
ResNeSt(A) with average downsampling for ImageNet-1K, implemented Chainer.
Original paper: 'ResNeSt: Split-Attention Networks,' https://arxiv.org/abs/2004.08955.
"""
__all__ = ['ResNeStA', 'resnestabc14', 'resnesta18', 'resnestabc26', 'resnesta50', 'resnesta101', 'resnesta152',
'resnesta200', 'r... | 18,370 | 31.922939 | 115 | py |
imgclsmob | imgclsmob-master/chainer_/chainercv2/models/senet.py | """
SENet for ImageNet-1K, implemented in Chainer.
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 chainer.functions as F
import chainer.... | 13,603 | 29.918182 | 115 | py |
imgclsmob | imgclsmob-master/chainer_/chainercv2/models/diapreresnet_cifar.py | """
DIA-PreResNet for CIFAR/SVHN, implemented in Chainer.
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... | 20,602 | 36.665448 | 120 | py |
imgclsmob | imgclsmob-master/chainer_/chainercv2/models/simplepose_coco.py | """
SimplePose for COCO Keypoint, implemented in Chainer.
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... | 12,665 | 37.150602 | 118 | py |
imgclsmob | imgclsmob-master/chainer_/chainercv2/models/vovnet.py | """
VoVNet for ImageNet-1K, implemented in Chainer.
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 chainer.functions as F
import chai... | 10,504 | 30.930091 | 120 | py |
imgclsmob | imgclsmob-master/chainer_/chainercv2/models/espnetv2.py | """
ESPNetv2 for ImageNet-1K, implemented in Chainer.
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']
... | 17,736 | 31.366788 | 118 | py |
imgclsmob | imgclsmob-master/chainer_/chainercv2/models/shufflenet.py | """
ShuffleNet for ImageNet-1K, implemented in Chainer.
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',
... | 16,240 | 32.906054 | 120 | py |
imgclsmob | imgclsmob-master/chainer_/chainercv2/models/bamresnet.py | """
BAM-ResNet for ImageNet-1K, implemented in Chainer.
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 chainer.functions as F
import chainer.lin... | 13,941 | 29.845133 | 115 | py |
imgclsmob | imgclsmob-master/chainer_/chainercv2/models/resattnet.py | """
ResAttNet for ImageNet-1K, implemented in Chainer.
Original paper: 'Residual Attention Network for Image Classification,' https://arxiv.org/abs/1704.06904.
"""
__all__ = ['ResAttNet', 'resattnet56', 'resattnet92', 'resattnet128', 'resattnet164', 'resattnet200', 'resattnet236',
'resattnet452']
i... | 21,611 | 30.096403 | 117 | py |
imgclsmob | imgclsmob-master/chainer_/chainercv2/models/centernet.py | """
CenterNet for ImageNet-1K, implemented in Chainer.
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... | 16,923 | 33.259109 | 118 | py |
imgclsmob | imgclsmob-master/chainer_/chainercv2/models/xdensenet_cifar.py | """
X-DenseNet for CIFAR/SVHN, implemented in Chainer.
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... | 13,033 | 34.906336 | 115 | py |
imgclsmob | imgclsmob-master/chainer_/chainercv2/models/ntsnet_cub.py | """
NTS-Net for CUB-200-2011, implemented in Chainer.
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 chainer.functions as F
import chainer.links as L
from chainer import Chain
... | 13,831 | 33.153086 | 115 | py |
imgclsmob | imgclsmob-master/chainer_/chainercv2/models/proxylessnas_cub.py | """
ProxylessNAS for CUB-200-2011, implemented in Chainer.
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']
... | 3,839 | 33.285714 | 120 | py |
imgclsmob | imgclsmob-master/chainer_/chainercv2/models/common.py | """
Common routines for models in Chainer.
"""
__all__ = ['round_channels', 'BreakBlock', 'ReLU6', 'HSwish', 'get_activation_layer', 'GlobalAvgPool2D',
'SelectableDense', 'DenseBlock', 'ConvBlock1d', 'conv1x1', 'conv3x3', 'depthwise_conv3x3', 'ConvBlock',
'conv1x1_block', 'conv3x3_block', 'co... | 68,471 | 30.510354 | 120 | py |
imgclsmob | imgclsmob-master/chainer_/chainercv2/models/lwopenpose_cmupan.py | """
Lightweight OpenPose 2D/3D for CMU Panoptic, implemented in Chainer.
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',
... | 22,569 | 33.563553 | 119 | py |
imgclsmob | imgclsmob-master/chainer_/chainercv2/models/rir_cifar.py | """
RiR for CIFAR/SVHN, implemented in Chainer.
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 chainer.functions as F
import chainer.links as L
fr... | 10,937 | 30.612717 | 119 | py |
imgclsmob | imgclsmob-master/chainer_/chainercv2/models/diapreresnet.py | """
DIA-PreResNet for ImageNet-1K, implemented in Chainer.
Original papers: 'DIANet: Dense-and-Implicit Attention Network,' https://arxiv.org/abs/1905.10671.
"""
__all__ = ['DIAPreResNet', 'diapreresnet10', 'diapreresnet12', 'diapreresnet14', 'diapreresnetbc14b', 'diapreresnet16',
'diapreresnet18', ... | 21,902 | 34.730832 | 119 | py |
imgclsmob | imgclsmob-master/chainer_/chainercv2/models/jasperdr.py | """
Jasper DR (Dense Residual) for ASR, implemented in Chainer.
Original paper: 'Jasper: An End-to-End Convolutional Neural Acoustic Model,' https://arxiv.org/abs/1904.03288.
"""
__all__ = ['jasperdr10x5_en', 'jasperdr10x5_en_nr']
from .jasper import get_jasper
def jasperdr10x5_en(classes=29, **kwargs):
... | 2,668 | 30.77381 | 119 | py |
imgclsmob | imgclsmob-master/chainer_/chainercv2/models/deeplabv3.py | """
DeepLabv3 for image segmentation, implemented in Chainer.
Original paper: 'Rethinking Atrous Convolution for Semantic Image Segmentation,' https://arxiv.org/abs/1706.05587.
"""
__all__ = ['DeepLabv3', 'deeplabv3_resnetd50b_voc', 'deeplabv3_resnetd101b_voc', 'deeplabv3_resnetd152b_voc',
'deeplabv... | 21,837 | 38.06619 | 119 | py |
imgclsmob | imgclsmob-master/chainer_/chainercv2/models/fpenet.py | """
FPENet for image segmentation, implemented in Chainer.
Original paper: 'Feature Pyramid Encoding Network for Real-time Semantic Segmentation,'
https://arxiv.org/abs/1909.08599.
"""
__all__ = ['FPENet', 'fpenet_cityscapes']
import os
import chainer.functions as F
from chainer import Chain
from chainer.... | 13,217 | 29.883178 | 115 | py |
imgclsmob | imgclsmob-master/chainer_/chainercv2/models/irevnet.py | """
i-RevNet for ImageNet-1K, implemented in Chainer.
Original paper: 'i-RevNet: Deep Invertible Networks,' https://arxiv.org/abs/1802.07088.
"""
__all__ = ['IRevNet', 'irevnet301']
import os
import chainer.functions as F
import chainer.links as L
from chainer import Chain
from functools import partial
from c... | 15,501 | 30.962887 | 115 | py |
imgclsmob | imgclsmob-master/chainer_/chainercv2/models/model_store.py | """
Model store which provides pretrained models.
"""
__all__ = ['get_model_file']
import os
import zipfile
import logging
import hashlib
_model_sha1 = {name: (error, checksum, repo_release_tag) for name, error, checksum, repo_release_tag in [
('alexnet', '1610', 'd666015b6e4e82eccc5d6c47cd35282a8aede469', '... | 59,290 | 75.901427 | 116 | py |
imgclsmob | imgclsmob-master/chainer_/chainercv2/models/fastseresnet.py | """
Fast-SE-ResNet for ImageNet-1K, implemented in Chainer.
Original paper: 'Squeeze-and-Excitation Networks,' https://arxiv.org/abs/1709.01507.
"""
__all__ = ['FastSEResNet', 'fastseresnet101b']
import os
import chainer.functions as F
import chainer.links as L
from chainer import Chain
from functools import ... | 9,707 | 31.686869 | 115 | py |
imgclsmob | imgclsmob-master/chainer_/chainercv2/models/polynet.py | """
PolyNet for ImageNet-1K, implemented in Chainer.
Original paper: 'PolyNet: A Pursuit of Structural Diversity in Very Deep Networks,'
https://arxiv.org/abs/1611.05725.
"""
__all__ = ['PolyNet', 'polynet']
import os
import chainer.functions as F
import chainer.links as L
from chainer import Chain
from f... | 31,208 | 30.748728 | 120 | py |
imgclsmob | imgclsmob-master/chainer_/chainercv2/models/resnet_cifar.py | """
ResNet for CIFAR/SVHN, implemented in Chainer.
Original paper: 'Deep Residual Learning for Image Recognition,' https://arxiv.org/abs/1512.03385.
"""
__all__ = ['CIFARResNet', 'resnet20_cifar10', 'resnet20_cifar100', 'resnet20_svhn',
'resnet56_cifar10', 'resnet56_cifar100', 'resnet56_svhn',
... | 23,007 | 35.520635 | 120 | py |
imgclsmob | imgclsmob-master/chainer_/chainercv2/models/nasnet.py | """
NASNet-A for ImageNet-1K, implemented in Chainer.
Original paper: 'Learning Transferable Architectures for Scalable Image Recognition,'
https://arxiv.org/abs/1707.07012.
"""
__all__ = ['NASNet', 'nasnet_4a1056', 'nasnet_6a4032', 'nasnet_dual_path_sequential']
import os
import chainer.functions as F
im... | 40,375 | 29.244195 | 118 | py |
imgclsmob | imgclsmob-master/chainer_/chainercv2/models/resnext_cifar.py | """
ResNeXt for CIFAR/SVHN, implemented in Chainer.
Original paper: 'Aggregated Residual Transformations for Deep Neural Networks,' http://arxiv.org/abs/1611.05431.
"""
__all__ = ['CIFARResNeXt', 'resnext20_16x4d_cifar10', 'resnext20_16x4d_cifar100', 'resnext20_16x4d_svhn',
'resnext20_32x2d_cifar10'... | 22,926 | 37.275459 | 116 | py |
imgclsmob | imgclsmob-master/chainer_/chainercv2/models/densenet_cifar.py | """
DenseNet for CIFAR/SVHN, implemented in Chainer.
Original paper: 'Densely Connected Convolutional Networks,' https://arxiv.org/abs/1608.06993.
"""
__all__ = ['CIFARDenseNet', 'densenet40_k12_cifar10', 'densenet40_k12_cifar100', 'densenet40_k12_svhn',
'densenet40_k12_bc_cifar10', 'densenet40_k12_... | 29,342 | 36.910853 | 115 | py |
imgclsmob | imgclsmob-master/chainer_/chainercv2/models/bninception.py | """
BN-Inception for ImageNet-1K, implemented in Chainer.
Original paper: 'Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift,'
https://arxiv.org/abs/1502.03167.
"""
__all__ = ['BNInception', 'bninception']
import os
import chainer.functions as F
import chainer.li... | 17,722 | 31.82037 | 115 | py |
imgclsmob | imgclsmob-master/chainer_/chainercv2/models/zfnet.py | """
ZFNet for ImageNet-1K, implemented in Chainer.
Original paper: 'Visualizing and Understanding Convolutional Networks,' https://arxiv.org/abs/1311.2901.
"""
__all__ = ['zfnet', 'zfnetb']
import os
from chainer.serializers import load_npz
from .alexnet import AlexNet
def get_zfnet(version="a",
... | 3,469 | 27.211382 | 115 | py |
imgclsmob | imgclsmob-master/chainer_/chainercv2/models/peleenet.py | """
PeleeNet for ImageNet-1K, implemented in Chainer.
Original paper: 'Pelee: A Real-Time Object Detection System on Mobile Devices,' https://arxiv.org/abs/1804.06882.
"""
__all__ = ['PeleeNet', 'peleenet']
import os
import chainer.functions as F
import chainer.links as L
from chainer import Chain
from functo... | 11,514 | 29.382586 | 117 | py |
imgclsmob | imgclsmob-master/chainer_/chainercv2/models/__init__.py | 0 | 0 | 0 | py | |
imgclsmob | imgclsmob-master/chainer_/chainercv2/models/sharesnet.py | """
ShaResNet for ImageNet-1K, implemented in Chainer.
Original paper: 'ShaResNet: reducing residual network parameter number by sharing weights,'
https://arxiv.org/abs/1702.08782.
"""
__all__ = ['ShaResNet', 'sharesnet18', 'sharesnet34', 'sharesnet50', 'sharesnet50b', 'sharesnet101', 'sharesnet101b',
... | 20,387 | 32.205212 | 117 | py |
imgclsmob | imgclsmob-master/chainer_/chainercv2/models/ibppose_coco.py | """
IBPPose for COCO Keypoint, implemented in Chainer.
Original paper: 'Simple Pose: Rethinking and Improving a Bottom-up Approach for Multi-Person Pose Estimation,'
https://arxiv.org/abs/1911.10529.
"""
__all__ = ['IbpPose', 'ibppose_coco']
import os
import chainer.functions as F
from functools import pa... | 18,194 | 29.943878 | 117 | py |
imgclsmob | imgclsmob-master/chainer_/chainercv2/models/xception.py | """
Xception for ImageNet-1K, implemented in Chainer.
Original paper: 'Xception: Deep Learning with Depthwise Separable Convolutions,' https://arxiv.org/abs/1610.02357.
"""
__all__ = ['Xception', 'xception']
import os
import chainer.functions as F
import chainer.links as L
from chainer import Chain
from funct... | 12,358 | 29.291667 | 118 | py |
imgclsmob | imgclsmob-master/chainer_/chainercv2/models/darknet53.py | """
DarkNet-53 for ImageNet-1K, implemented in Chainer.
Original source: 'YOLOv3: An Incremental Improvement,' https://arxiv.org/abs/1804.02767.
"""
__all__ = ['DarkNet53', 'darknet53']
import os
import chainer.functions as F
import chainer.links as L
from chainer import Chain
from functools import partial
fr... | 6,985 | 31.193548 | 115 | py |
imgclsmob | imgclsmob-master/chainer_/chainercv2/models/mobilenet.py | """
MobileNet for ImageNet-1K, implemented in Chainer.
Original paper: 'MobileNets: Efficient Convolutional Neural Networks for Mobile Vision Applications,'
https://arxiv.org/abs/1704.04861.
"""
__all__ = ['MobileNet', 'mobilenet_w1', 'mobilenet_w3d4', 'mobilenet_wd2', 'mobilenet_wd4', 'get_mobilenet']
im... | 8,305 | 33.322314 | 119 | py |
imgclsmob | imgclsmob-master/chainer_/chainercv2/models/dpn.py | """
DPN for ImageNet-1K, implemented in Chainer.
Original paper: 'Dual Path Networks,' https://arxiv.org/abs/1707.01629.
"""
__all__ = ['DPN', 'dpn68', 'dpn68b', 'dpn98', 'dpn107', 'dpn131']
import os
import chainer.functions as F
import chainer.links as L
from chainer import Chain
from functools import parti... | 19,846 | 28.711078 | 115 | py |
imgclsmob | imgclsmob-master/chainer_/chainercv2/models/sknet.py | """
SKNet for ImageNet-1K, implemented in Chainer.
Original paper: 'Selective Kernel Networks,' https://arxiv.org/abs/1903.06586.
"""
__all__ = ['SKNet', 'sknet50', 'sknet101', 'sknet152']
import os
import chainer.functions as F
import chainer.links as L
from chainer import Chain
from functools import partial... | 11,401 | 29.983696 | 115 | py |
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