repo stringlengths 1 99 | file stringlengths 13 215 | code stringlengths 12 59.2M | file_length int64 12 59.2M | avg_line_length float64 3.82 1.48M | max_line_length int64 12 2.51M | extension_type stringclasses 1
value |
|---|---|---|---|---|---|---|
DialogID | DialogID-main/src/auto_text_classifier/atc/utils/adt_utils.py | '''
对抗训练
参考实现
https://fyubang.com/2019/10/15/adversarial-train/
'''
import torch
import numpy as np
from torch.autograd import Variable
# from loguru import logger
class FGM():
def __init__(self, model):
self.model = model
self.backup = {}
def attack(self, epsilon=1., emb_name='emb.'):
... | 7,143 | 31.770642 | 89 | py |
DialogID | DialogID-main/src/auto_text_classifier/atc/utils/data_utils.py | import os
import numpy as np
import pandas as pd
from sklearn.model_selection import KFold
from sklearn.model_selection import train_test_split
from transformers.data.processors.utils import InputFeatures
from torch.utils.data import Dataset, DataLoader, RandomSampler, SequentialSampler
def init_dir(dir_path):
"""... | 7,870 | 28.927757 | 109 | py |
DialogID | DialogID-main/src/auto_text_classifier/atc/utils/hf_train.py | import logging
import math
import os
import re
import shutil
import warnings
from contextlib import contextmanager
from pathlib import Path
from typing import Any, Callable, Dict, List, Optional, Tuple, Union
import random
import numpy as np
import torch
from packaging import version
from torch import nn
from torch.uti... | 43,013 | 41.170588 | 131 | py |
DialogID | DialogID-main/src/auto_text_classifier/atc/utils/hf_training_args.py | import dataclasses
import json
import logging
import os
from dataclasses import dataclass, field
from typing import Any, Dict, Optional, Tuple
from transformers.file_utils import cached_property, is_torch_available, torch_required
def is_torch_tpu_available():
return False
if is_torch_available():
import t... | 15,395 | 44.821429 | 119 | py |
baryrat | baryrat-master/docs/conf.py | # Configuration file for the Sphinx documentation builder.
#
# This file only contains a selection of the most common options. For a full
# list see the documentation:
# https://www.sphinx-doc.org/en/master/usage/configuration.html
# -- Path setup --------------------------------------------------------------
# If ex... | 2,008 | 33.050847 | 79 | py |
Adversarial-Counterfactual-Learning-and-Evaluation-for-Recommender-System | Adversarial-Counterfactual-Learning-and-Evaluation-for-Recommender-System-main/train_on_simulation.py | from typing import List
import os
import time
import argparse
from argparse import Namespace
import logging
from scipy import sparse as sp #type: ignore
import numpy as np #type: ignore
from sklearn.utils.extmath import randomized_svd #type: ignore
from tqdm import tqdm #type: ignore
import pandas as pd #type: ignore... | 11,375 | 43.787402 | 111 | py |
Adversarial-Counterfactual-Learning-and-Evaluation-for-Recommender-System | Adversarial-Counterfactual-Learning-and-Evaluation-for-Recommender-System-main/NCF_validation.py | from typing import List
import os
import time
import argparse
from argparse import Namespace
import logging
from scipy import sparse as sp #type: ignore
import numpy as np #type: ignore
from sklearn.utils.extmath import randomized_svd #type: ignore
from tqdm import tqdm #type: ignore
import pandas as pd #type: ignore... | 1,725 | 28.254237 | 99 | py |
Adversarial-Counterfactual-Learning-and-Evaluation-for-Recommender-System | Adversarial-Counterfactual-Learning-and-Evaluation-for-Recommender-System-main/robust_simulation.py | """Script to generate recommendation data from simulation"""
import argparse
from argparse import Namespace
import os
import pandas as pd #type: ignore
import torch #type: ignore
import numpy as np #type: ignore
from scipy import sparse as sp #type: ignore
from tqdm import tqdm #type: ignore
from acgan.data import Rat... | 6,198 | 43.92029 | 102 | py |
Adversarial-Counterfactual-Learning-and-Evaluation-for-Recommender-System | Adversarial-Counterfactual-Learning-and-Evaluation-for-Recommender-System-main/train_on_real.py | from typing import List
import os
import time
import argparse
from argparse import Namespace
import logging
from scipy import sparse as sp #type: ignore
import numpy as np #type: ignore
from sklearn.utils.extmath import randomized_svd #type: ignore
from tqdm import tqdm #type: ignore
import pandas as pd #type: ignore... | 10,239 | 43.716157 | 125 | py |
Adversarial-Counterfactual-Learning-and-Evaluation-for-Recommender-System | Adversarial-Counterfactual-Learning-and-Evaluation-for-Recommender-System-main/simulation.py | """Script to generate recommendation data from simulation"""
import argparse
from argparse import Namespace
import os
import pandas as pd #type: ignore
import torch #type: ignore
import numpy as np #type: ignore
from scipy import sparse as sp #type: ignore
from tqdm import tqdm #type: ignore
from acgan.data import Rat... | 6,208 | 44.654412 | 101 | py |
Adversarial-Counterfactual-Learning-and-Evaluation-for-Recommender-System | Adversarial-Counterfactual-Learning-and-Evaluation-for-Recommender-System-main/acgan/module.py | """Modules are to express the mathematical relationships between parameters.
Design note: The module shoudn't care about things like data transformations. It should be
as self-contained as possible. Dirty jobs should be done by the Model class which serves
as a bridge between reality(data) and the theory(module).
"""
... | 14,132 | 39.495702 | 134 | py |
Adversarial-Counterfactual-Learning-and-Evaluation-for-Recommender-System | Adversarial-Counterfactual-Learning-and-Evaluation-for-Recommender-System-main/acgan/data.py | import os
import argparse
import logging
from typing import Dict, List, Tuple, Optional, Set
import numpy as np # type: ignore
import pandas as pd # type: ignore
from scipy import sparse as sp # type: ignore
import torch # type: ignore
from torch.utils import data # type: ignore
from numpy.random import RandomSta... | 11,006 | 34.621359 | 117 | py |
Adversarial-Counterfactual-Learning-and-Evaluation-for-Recommender-System | Adversarial-Counterfactual-Learning-and-Evaluation-for-Recommender-System-main/acgan/recommender.py | from typing import List, Optional, Tuple, Dict, Set
import time
import logging
from tqdm import tqdm # type: ignore
from scipy import sparse as sp # type: ignore
import numpy as np # type: ignore
from sklearn.utils.extmath import randomized_svd # type: ignore
import torch # type: ignore
from torch import nn # ty... | 42,175 | 38.306617 | 152 | py |
imgclsmob | imgclsmob-master/eval_ke.py | """
Script for evaluating trained model on Keras (validate/test).
"""
import argparse
import time
import logging
import keras
from common.logger_utils import initialize_logging
from keras_.utils import prepare_ke_context, prepare_model, get_data_rec, get_data_generator, backend_agnostic_compile
def parse_args():... | 6,665 | 27.365957 | 118 | py |
imgclsmob | imgclsmob-master/load_model.py | """
Script for downloading model weights.
"""
import argparse
import numpy as np
def parse_args():
parser = argparse.ArgumentParser(description="Download model",
formatter_class=argparse.ArgumentDefaultsHelpFormatter)
parser.add_argument(
"--model",
ty... | 1,326 | 23.574074 | 92 | py |
imgclsmob | imgclsmob-master/eval_gl.py | """
Script for evaluating trained model on MXNet/Gluon (validate/test).
"""
import os
import time
import logging
import argparse
from sys import version_info
from common.logger_utils import initialize_logging
from gluon.utils import prepare_mx_context, prepare_model
from gluon.utils import calc_net_weight_count, v... | 11,941 | 31.53951 | 117 | py |
imgclsmob | imgclsmob-master/sotabench.py | from torchbench.image_classification import ImageNet
from pytorch.pytorchcv.models.model_store import _model_sha1
from pytorch.pytorchcv.model_provider import get_model as ptcv_get_model
import torchvision.transforms as transforms
import torch
import math
from sys import version_info
# import os
for model_name, model... | 1,645 | 39.146341 | 109 | py |
imgclsmob | imgclsmob-master/train_tf2.py | """
Script for training model on TensorFlow 2.0.
"""
import os
import logging
import argparse
import numpy as np
import random
import tensorflow as tf
from common.logger_utils import initialize_logging
from tensorflow2.tf2cv.model_provider import get_model
from tensorflow2.dataset_utils import get_dataset_metainfo... | 8,479 | 28.041096 | 102 | py |
imgclsmob | imgclsmob-master/eval_pt.py | """
Script for evaluating trained model on PyTorch (validate/test).
"""
import os
import time
import logging
import argparse
from sys import version_info
from common.logger_utils import initialize_logging
from pytorch.utils import prepare_pt_context, prepare_model
from pytorch.utils import calc_net_weight_count, v... | 13,989 | 29.347072 | 120 | py |
imgclsmob | imgclsmob-master/eval_gl_det.py | """
Script for evaluating trained model on MXNet/Gluon (validate/test).
"""
import os
import time
import logging
import argparse
from sys import version_info
from common.logger_utils import initialize_logging
from gluon.utils import prepare_mx_context, prepare_model
from gluon.utils import calc_net_weight_count, v... | 11,409 | 31.140845 | 117 | py |
imgclsmob | imgclsmob-master/train_ke.py | """
Script for training model on Keras.
"""
import argparse
import time
import logging
import os
import numpy as np
import random
import keras
from keras.models import load_model
from keras.callbacks import ModelCheckpoint
import mxnet as mx
from common.logger_utils import initialize_logging
from keras_.utils impo... | 8,801 | 26.85443 | 118 | py |
imgclsmob | imgclsmob-master/eval_tf2.py | """
Script for evaluating trained model on TensorFlow 2.0 (validate/test).
"""
import os
import time
import logging
import argparse
from sys import version_info
import tensorflow as tf
from common.logger_utils import initialize_logging
from tensorflow2.utils import prepare_model
from tensorflow2.tf2cv.models.model... | 9,076 | 29.979522 | 117 | py |
imgclsmob | imgclsmob-master/prep_model.py | """
Script for preparing the model for publication.
"""
import os
import argparse
import subprocess
import shutil
import re
import hashlib
import zipfile
import pandas as pd
def parse_args():
"""
Parse python script parameters.
Returns:
-------
ArgumentParser
Resulted args.
"""
... | 9,068 | 30.380623 | 119 | py |
imgclsmob | imgclsmob-master/convert_models.py | """
Script for converting models between frameworks (MXNet, Gluon, PyTroch, Chainer, Keras, TensorFlow).
"""
import argparse
import logging
import re
import numpy as np
from common.logger_utils import initialize_logging
def parse_args():
parser = argparse.ArgumentParser(description="Convert models (Gluon/PyT... | 87,933 | 51.435301 | 125 | py |
imgclsmob | imgclsmob-master/train_gl_mealv2.py | """
Script for training model on MXNet/Gluon.
"""
import argparse
import time
import logging
import os
import random
import numpy as np
import mxnet as mx
from mxnet import gluon
from mxnet import autograd as ag
from common.logger_utils import initialize_logging
from common.train_log_param_saver import TrainLogP... | 33,553 | 32.188922 | 119 | py |
imgclsmob | imgclsmob-master/train_pt.py | """
Script for training model on PyTorch.
"""
import os
import time
import logging
import argparse
import random
import numpy as np
import torch.nn as nn
import torch.backends.cudnn as cudnn
import torch.utils.data
from common.logger_utils import initialize_logging
from common.train_log_param_saver import TrainL... | 20,958 | 28.519718 | 119 | py |
imgclsmob | imgclsmob-master/train_gl.py | """
Script for training model on MXNet/Gluon.
"""
import argparse
import time
import logging
import os
import random
import numpy as np
import mxnet as mx
from mxnet import gluon
from mxnet import autograd as ag
from common.logger_utils import initialize_logging
from common.train_log_param_saver import TrainLogP... | 28,277 | 30.489978 | 119 | 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_/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.
... | 8,392 | 38.219626 | 119 | py |
imgclsmob | imgclsmob-master/chainer_/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
from chainercv.chainer_experimental.datasets.sliceable import GetterDataset
from .dataset_metainfo import DatasetMe... | 20,988 | 39.597679 | 119 | py |
imgclsmob | imgclsmob-master/chainer_/datasets/coco_hpe3_dataset.py | """
COCO keypoint detection (2D multiple human pose estimation) dataset (for IBPPose).
"""
import os
import math
import cv2
import numpy as np
from chainercv.chainer_experimental.datasets.sliceable import GetterDataset
from .dataset_metainfo import DatasetMetaInfo
class CocoHpe3Dataset(GetterDataset):
"""
... | 23,313 | 39.830123 | 120 | py |
imgclsmob | imgclsmob-master/tensorflow2/tf2cv/models/airnext.py | """
AirNeXt for ImageNet-1K, implemented in TensorFlow.
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... | 12,866 | 31.087282 | 115 | py |
imgclsmob | imgclsmob-master/tensorflow2/tf2cv/models/pspnet.py | """
PSPNet for image segmentation, implemented in TensorFlow.
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'... | 22,270 | 38.487589 | 119 | py |
imgclsmob | imgclsmob-master/tensorflow2/tf2cv/models/dla.py | """
DLA for ImageNet-1K, implemented in TensorFlow.
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 tensorflow as tf
import tensorflow.keras... | 22,786 | 31.599428 | 120 | py |
imgclsmob | imgclsmob-master/tensorflow2/tf2cv/models/proxylessnas.py | """
ProxylessNAS for ImageNet-1K, implemented in TensorFlow.
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'... | 15,845 | 35.178082 | 118 | py |
imgclsmob | imgclsmob-master/tensorflow2/tf2cv/models/shufflenetv2.py | """
ShuffleNet V2 for ImageNet-1K, implemented in TensorFlow.
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 ... | 13,783 | 32.784314 | 115 | py |
imgclsmob | imgclsmob-master/tensorflow2/tf2cv/models/hrnet.py | """
HRNet for ImageNet-1K, implemented in TensorFlow.
Original paper: 'Deep High-Resolution Representation Learning for Visual Recognition,'
https://arxiv.org/abs/1908.07919.
"""
__all__ = ['HRNet', 'hrnet_w18_small_v1', 'hrnet_w18_small_v2', 'hrnetv2_w18', 'hrnetv2_w30', 'hrnetv2_w32',
'hrnetv2... | 25,313 | 34.703808 | 115 | py |
imgclsmob | imgclsmob-master/tensorflow2/tf2cv/models/fcn8sd.py | """
FCN-8s(d) for image segmentation, implemented in TensorFlow.
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',... | 19,136 | 40.154839 | 119 | py |
imgclsmob | imgclsmob-master/tensorflow2/tf2cv/models/selecsls.py | """
SelecSLS for ImageNet-1K, implemented in TensorFlow.
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 ... | 13,913 | 33.698254 | 115 | py |
imgclsmob | imgclsmob-master/tensorflow2/tf2cv/models/inceptionv4.py | """
InceptionV4 for ImageNet-1K, implemented in TensorFlow.
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 tensorflow as tf
import tensorflow.keras.layers a... | 23,613 | 31.303694 | 120 | py |
imgclsmob | imgclsmob-master/tensorflow2/tf2cv/models/regnet.py | """
RegNet for ImageNet-1K, implemented in TensorFlow.
Original paper: 'Designing Network Design Spaces,' https://arxiv.org/abs/2003.13678.
"""
__all__ = ['RegNet', 'regnetx002', 'regnetx004', 'regnetx006', 'regnetx008', 'regnetx016', 'regnetx032', 'regnetx040',
'regnetx064', 'regnetx080', 'regnetx1... | 25,743 | 33.978261 | 118 | py |
imgclsmob | imgclsmob-master/tensorflow2/tf2cv/models/icnet.py | """
ICNet for image segmentation, implemented in TensorFlow.
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 tensorflow as tf
import tensorflow.keras.layers as n... | 15,700 | 31.985294 | 120 | py |
imgclsmob | imgclsmob-master/tensorflow2/tf2cv/models/mobilenetb.py | """
MobileNet(B) with simplified depthwise separable convolution block for ImageNet-1K, implemented in TensorFlow.
Original paper: 'MobileNets: Efficient Convolutional Neural Networks for Mobile Vision Applications,'
https://arxiv.org/abs/1704.04861.
"""
__all__ = ['mobilenetb_w1', 'mobilenetb_w3d4', 'mobi... | 3,684 | 34.095238 | 114 | py |
imgclsmob | imgclsmob-master/tensorflow2/tf2cv/models/inceptionresnetv1.py | """
InceptionResNetV1 for ImageNet-1K, implemented in TensorFlow.
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', 'InceptionCUn... | 20,969 | 32.127962 | 117 | py |
imgclsmob | imgclsmob-master/tensorflow2/tf2cv/models/scnet.py | """
SCNet for ImageNet-1K, implemented in TensorFlow.
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 tensorflow as tf
import tenso... | 17,161 | 31.751908 | 117 | py |
imgclsmob | imgclsmob-master/tensorflow2/tf2cv/models/igcv3.py | """
IGCV3 for ImageNet-1K, implemented in TensorFlow.
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 tensorflow as tf
import ... | 10,739 | 32.667712 | 115 | py |
imgclsmob | imgclsmob-master/tensorflow2/tf2cv/models/seresnet_cifar.py | """
SE-ResNet for CIFAR/SVHN, implemented in TensorFlow.
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'... | 23,745 | 36.692063 | 120 | py |
imgclsmob | imgclsmob-master/tensorflow2/tf2cv/models/resnetd.py | """
ResNet(D) with dilation for ImageNet-1K, implemented in TensorFlow.
Original paper: 'Deep Residual Learning for Image Recognition,' https://arxiv.org/abs/1512.03385.
"""
__all__ = ['ResNetD', 'resnetd50b', 'resnetd101b', 'resnetd152b']
import os
import tensorflow as tf
import tensorflow.keras.layers as nn... | 10,194 | 34.034364 | 120 | py |
imgclsmob | imgclsmob-master/tensorflow2/tf2cv/models/quartznet.py | """
QuartzNet for ASR, implemented in TensorFlow.
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_... | 13,642 | 43.439739 | 119 | py |
imgclsmob | imgclsmob-master/tensorflow2/tf2cv/models/preresnet.py | """
PreResNet for ImageNet-1K, implemented in TensorFlow.
Original papers: 'Identity Mappings in Deep Residual Networks,' https://arxiv.org/abs/1603.05027.
"""
__all__ = ['PreResNet', 'preresnet10', 'preresnet12', 'preresnet14', 'preresnetbc14b', 'preresnet16', 'preresnet18_wd4',
'preresnet18_wd2', ... | 28,922 | 33.107311 | 120 | py |
imgclsmob | imgclsmob-master/tensorflow2/tf2cv/models/lednet.py | """
LEDNet for image segmentation, implemented in TensorFlow.
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 tensorflow as tf
import tensorflow.keras.layer... | 22,964 | 31.94835 | 118 | py |
imgclsmob | imgclsmob-master/tensorflow2/tf2cv/models/ibndensenet.py | """
IBN-DenseNet for ImageNet-1K, implemented in TensorFlow.
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
im... | 14,434 | 32.414352 | 115 | py |
imgclsmob | imgclsmob-master/tensorflow2/tf2cv/models/hardnet.py | """
HarDNet for ImageNet-1K, implemented in TensorFlow.
Original paper: 'HarDNet: A Low Memory Traffic Network,' https://arxiv.org/abs/1909.00948.
"""
__all__ = ['HarDNet', 'hardnet39ds', 'hardnet68ds', 'hardnet68', 'hardnet85']
import os
import tensorflow as tf
import tensorflow.keras.layers as nn
from .comm... | 24,226 | 35.213752 | 115 | py |
imgclsmob | imgclsmob-master/tensorflow2/tf2cv/models/sinet.py | """
SINet for image segmentation, implemented in TensorFlow.
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 tensorflow ... | 41,973 | 33.014587 | 118 | py |
imgclsmob | imgclsmob-master/tensorflow2/tf2cv/models/shufflenetv2b.py | """
ShuffleNet V2 for ImageNet-1K, implemented in TensorFlow. 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'... | 14,161 | 32.559242 | 120 | py |
imgclsmob | imgclsmob-master/tensorflow2/tf2cv/models/menet.py | """
MENet for ImageNet-1K, implemented in TensorFlow.
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_12... | 18,147 | 33.112782 | 116 | py |
imgclsmob | imgclsmob-master/tensorflow2/tf2cv/models/voca.py | """
VOCA for speech-driven facial animation, implemented in TensorFlow.
Original paper: 'Capture, Learning, and Synthesis of 3D Speaking Styles,' https://arxiv.org/abs/1905.03079.
"""
__all__ = ['VOCA', 'voca8flame']
import os
import tensorflow as tf
import tensorflow.keras.layers as nn
from .common import Ba... | 8,094 | 32.589212 | 116 | py |
imgclsmob | imgclsmob-master/tensorflow2/tf2cv/models/wrn_cifar.py | """
WRN for CIFAR/SVHN, implemented in TensorFlow.
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_ci... | 11,768 | 34.342342 | 115 | py |
imgclsmob | imgclsmob-master/tensorflow2/tf2cv/models/inceptionresnetv2.py | """
InceptionResNetV2 for ImageNet-1K, implemented in TensorFlow.
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 tensorflow as tf
import tensorf... | 11,470 | 33.038576 | 117 | py |
imgclsmob | imgclsmob-master/tensorflow2/tf2cv/models/ghostnet.py | """
GhostNet for ImageNet-1K, implemented in TensorFlow.
Original paper: 'GhostNet: More Features from Cheap Operations,' https://arxiv.org/abs/1911.11907.
"""
__all__ = ['GhostNet', 'ghostnet']
import os
import math
import tensorflow as tf
import tensorflow.keras.layers as nn
from .common import round_channe... | 15,092 | 32.614699 | 115 | py |
imgclsmob | imgclsmob-master/tensorflow2/tf2cv/models/efficientnet.py | """
EfficientNet for ImageNet-1K, implemented in TensorFlow.
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__ = ['EfficientNe... | 40,223 | 36.804511 | 120 | py |
imgclsmob | imgclsmob-master/tensorflow2/tf2cv/models/pnasnet.py | """
PNASNet for ImageNet-1K, implemented in TensorFlow.
Original paper: 'Progressive Neural Architecture Search,' https://arxiv.org/abs/1712.00559.
"""
__all__ = ['PNASNet', 'pnasnet5large']
import os
import tensorflow as tf
import tensorflow.keras.layers as nn
from .common import MaxPool2d, conv1x1, SimpleS... | 23,512 | 31.253772 | 118 | py |
imgclsmob | imgclsmob-master/tensorflow2/tf2cv/models/efficientnetedge.py | """
EfficientNet-Edge for ImageNet-1K, implemented in TensorFlow.
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_la... | 15,845 | 37 | 118 | py |
imgclsmob | imgclsmob-master/tensorflow2/tf2cv/models/ibnresnext.py | """
IBN-ResNeXt for ImageNet-1K, implemented in TensorFlow.
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 tensorfl... | 12,035 | 32.620112 | 118 | py |
imgclsmob | imgclsmob-master/tensorflow2/tf2cv/models/squeezenext.py | """
SqueezeNext for ImageNet-1K, implemented in TensorFlow.
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 tensor... | 13,713 | 32.367397 | 119 | py |
imgclsmob | imgclsmob-master/tensorflow2/tf2cv/models/grmiposelite_coco.py | """
GRMIPose (Google PoseNet) for COCO Keypoint, implemented in TensorFlow (Lite).
Original paper: 'Towards Accurate Multi-person Pose Estimation in the Wild,' https://arxiv.org/abs/1701.01779.
"""
__all__ = ['GRMIPoseLite', 'grmiposelite_mobilenet_w1_coco']
import math
import numpy as np
import tensorflow as... | 6,726 | 32.137931 | 118 | py |
imgclsmob | imgclsmob-master/tensorflow2/tf2cv/models/bisenet.py | """
BiSeNet for CelebAMask-HQ, implemented in TensorFlow.
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 tensorflow as tf
import tensorflow.keras.la... | 17,516 | 32.429389 | 120 | py |
imgclsmob | imgclsmob-master/tensorflow2/tf2cv/models/resnet.py | """
ResNet for ImageNet-1K, implemented in TensorFlow.
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'... | 27,599 | 32.948339 | 120 | py |
imgclsmob | imgclsmob-master/tensorflow2/tf2cv/models/simpleposemobile_coco.py | """
SimplePose(Mobile) for COCO Keypoint, implemented in TensorFlow.
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_mobi... | 15,320 | 41.558333 | 120 | py |
imgclsmob | imgclsmob-master/tensorflow2/tf2cv/models/cbamresnet.py | """
CBAM-ResNet for ImageNet-1K, implemented in TensorFlow.
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 tensorflow as tf
impo... | 15,596 | 30.830612 | 115 | py |
imgclsmob | imgclsmob-master/tensorflow2/tf2cv/models/diracnetv2.py | """
DiracNetV2 for ImageNet-1K, implemented in TensorFlow.
Original paper: 'DiracNets: Training Very Deep Neural Networks Without Skip-Connections,'
https://arxiv.org/abs/1706.00388.
"""
__all__ = ['DiracNetV2', 'diracnet18v2', 'diracnet34v2']
import os
import tensorflow as tf
import tensorflow.keras.laye... | 9,781 | 30.152866 | 115 | py |
imgclsmob | imgclsmob-master/tensorflow2/tf2cv/models/sepreresnet_cifar.py | """
SE-PreResNet for CIFAR/SVHN, implemented in TensorFlow.
Original paper: 'Squeeze-and-Excitation Networks,' https://arxiv.org/abs/1709.01507.
"""
__all__ = ['CIFARSEPreResNet', 'sepreresnet20_cifar10', 'sepreresnet20_cifar100', 'sepreresnet20_svhn',
'sepreresnet56_cifar10', 'sepreresnet56_cifar10... | 24,762 | 37.511664 | 119 | py |
imgclsmob | imgclsmob-master/tensorflow2/tf2cv/models/danet.py | """
DANet for image segmentation, implemented in TensorFlow.
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 tensorflow as tf
import tensorflow.keras.layer... | 18,175 | 34.156673 | 120 | py |
imgclsmob | imgclsmob-master/tensorflow2/tf2cv/models/mobilenetv2.py | """
MobileNetV2 for ImageNet-1K, implemented in TensorFlow.
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',
'mobile... | 13,837 | 34.121827 | 120 | py |
imgclsmob | imgclsmob-master/tensorflow2/tf2cv/models/squeezenet.py | """
SqueezeNet for ImageNet-1K, implemented in TensorFlow.
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']
... | 13,417 | 32.212871 | 118 | py |
imgclsmob | imgclsmob-master/tensorflow2/tf2cv/models/vgg.py | """
VGG for ImageNet-1K, implemented in TensorFlow.
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_vg... | 14,207 | 31 | 117 | py |
imgclsmob | imgclsmob-master/tensorflow2/tf2cv/models/resnet_cub.py | """
ResNet for CUB-200-2011, implemented in TensorFlow.
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... | 14,084 | 35.489637 | 117 | py |
imgclsmob | imgclsmob-master/tensorflow2/tf2cv/models/bagnet.py | """
BagNet for ImageNet-1K, implemented in TensorFlow.
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 tensorflow as tf
import ... | 12,719 | 31.868217 | 116 | py |
imgclsmob | imgclsmob-master/tensorflow2/tf2cv/models/airnet.py | """
AirNet for ImageNet-1K, implemented in TensorFlow.
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', '... | 14,996 | 31.182403 | 115 | py |
imgclsmob | imgclsmob-master/tensorflow2/tf2cv/models/mnasnet.py | """
MnasNet for ImageNet-1K, implemented in TensorFlow.
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 tensorflow as tf
import tensorflow.keras.layers as ... | 15,818 | 33.997788 | 118 | py |
imgclsmob | imgclsmob-master/tensorflow2/tf2cv/models/pyramidnet_cifar.py | """
PyramidNet for CIFAR/SVHN, implemented in TensorFlow.
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', 'pyramid... | 24,103 | 32.711888 | 120 | py |
imgclsmob | imgclsmob-master/tensorflow2/tf2cv/models/preresnet_cifar.py | """
PreResNet for CIFAR/SVHN, implemented in TensorFlow.
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'... | 24,758 | 36.11994 | 120 | py |
imgclsmob | imgclsmob-master/tensorflow2/tf2cv/models/alphapose_coco.py | """
AlphaPose for COCO Keypoint, implemented in TensorFlow.
Original paper: 'RMPE: Regional Multi-person Pose Estimation,' https://arxiv.org/abs/1612.00137.
"""
__all__ = ['AlphaPose', 'alphapose_fastseresnet101b_coco']
import os
import tensorflow as tf
from .common import conv3x3, PixelShuffle, DucBlock, Hea... | 7,571 | 34.886256 | 116 | py |
imgclsmob | imgclsmob-master/tensorflow2/tf2cv/models/pyramidnet.py | """
PyramidNet for ImageNet-1K, implemented in TensorFlow.
Original paper: 'Deep Pyramidal Residual Networks,' https://arxiv.org/abs/1610.02915.
"""
__all__ = ['PyramidNet', 'pyramidnet101_a360', 'PyrUnit']
import os
import tensorflow as tf
import tensorflow.keras.layers as nn
from .common import Conv2d, Batc... | 13,503 | 30.699531 | 117 | py |
imgclsmob | imgclsmob-master/tensorflow2/tf2cv/models/seresnet.py | """
SE-ResNet for ImageNet-1K, implemented in TensorFlow.
Original paper: 'Squeeze-and-Excitation Networks,' https://arxiv.org/abs/1709.01507.
"""
__all__ = ['SEResNet', 'seresnet10', 'seresnet12', 'seresnet14', 'seresnet16', 'seresnet18', 'seresnet26',
'seresnetbc26b', 'seresnet34', 'seresnetbc38b'... | 19,070 | 32.694346 | 118 | py |
imgclsmob | imgclsmob-master/tensorflow2/tf2cv/models/seresnet_cub.py | """
SE-ResNet for CUB-200-2011, implemented in TensorFlow.
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', 'seresnetbc2... | 14,111 | 35.942408 | 120 | py |
imgclsmob | imgclsmob-master/tensorflow2/tf2cv/models/densenet.py | """
DenseNet for ImageNet-1K, implemented in TensorFlow.
Original paper: 'Densely Connected Convolutional Networks,' https://arxiv.org/abs/1608.06993.
"""
__all__ = ['DenseNet', 'densenet121', 'densenet161', 'densenet169', 'densenet201', 'DenseUnit', 'TransitionBlock']
import os
import tensorflow as tf
import... | 11,289 | 32.011696 | 116 | py |
imgclsmob | imgclsmob-master/tensorflow2/tf2cv/models/seresnext.py | """
SE-ResNeXt for ImageNet-1K, implemented in TensorFlow.
Original paper: 'Squeeze-and-Excitation Networks,' https://arxiv.org/abs/1709.01507.
"""
__all__ = ['SEResNeXt', 'seresnext50_32x4d', 'seresnext101_32x4d', 'seresnext101_64x4d']
import os
import tensorflow as tf
import tensorflow.keras.layers as nn
fr... | 9,503 | 31.772414 | 115 | py |
imgclsmob | imgclsmob-master/tensorflow2/tf2cv/models/drn.py | """
DRN for ImageNet-1K, implemented in TensorFlow.
Original paper: 'Dilated Residual Networks,' https://arxiv.org/abs/1705.09914.
"""
__all__ = ['DRN', 'drnc26', 'drnc42', 'drnc58', 'drnd22', 'drnd38', 'drnd54', 'drnd105']
import os
import tensorflow as tf
import tensorflow.keras.layers as nn
from .common im... | 21,693 | 30.44058 | 119 | py |
imgclsmob | imgclsmob-master/tensorflow2/tf2cv/models/mixnet.py | """
MixNet for ImageNet-1K, implemented in TensorFlow.
Original paper: 'MixConv: Mixed Depthwise Convolutional Kernels,' https://arxiv.org/abs/1907.09595.
"""
__all__ = ['MixNet', 'mixnet_s', 'mixnet_m', 'mixnet_l']
import os
import tensorflow as tf
import tensorflow.keras.layers as nn
from .common import rou... | 23,110 | 34.886646 | 116 | py |
imgclsmob | imgclsmob-master/tensorflow2/tf2cv/models/dabnet.py | """
DABNet for image segmentation, implemented in TensorFlow.
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 tensorflow as tf
import tensorflow.keras.layers as ... | 20,630 | 31.592417 | 120 | py |
imgclsmob | imgclsmob-master/tensorflow2/tf2cv/models/cgnet.py | """
CGNet for image segmentation, implemented in TensorFlow.
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 tensorflow as tf
import tensorflow.keras.layers as nn
from .... | 16,751 | 31.528155 | 118 | py |
imgclsmob | imgclsmob-master/tensorflow2/tf2cv/models/fbnet.py | """
FBNet for ImageNet-1K, implemented in TensorFlow.
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 tensorflow as tf
import tensorflow.keras.layers as nn... | 11,383 | 32.581121 | 116 | py |
imgclsmob | imgclsmob-master/tensorflow2/tf2cv/models/visemenet.py | """
VisemeNet for speech-driven facial animation, implemented in TensorFlow.
Original paper: 'VisemeNet: Audio-Driven Animator-Centric Speech Animation,' https://arxiv.org/abs/1805.09488.
"""
__all__ = ['VisemeNet', 'visemenet20']
import os
import tensorflow as tf
import tensorflow.keras.layers as nn
from .co... | 10,166 | 33.11745 | 119 | py |
imgclsmob | imgclsmob-master/tensorflow2/tf2cv/models/mobilenetv3.py | """
MobileNetV3 for ImageNet-1K, implemented in TensorFlow.
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', 'mo... | 20,951 | 34.572156 | 118 | py |
imgclsmob | imgclsmob-master/tensorflow2/tf2cv/models/lffd.py | """
LFFD for face detection, implemented in TensorFlow.
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 tensorflow as tf
import tensorflow.keras.layers as ... | 12,116 | 32.658333 | 115 | py |
imgclsmob | imgclsmob-master/tensorflow2/tf2cv/models/sepreresnet.py | """
SE-PreResNet for ImageNet-1K, implemented in TensorFlow.
Original paper: 'Squeeze-and-Excitation Networks,' https://arxiv.org/abs/1709.01507.
"""
__all__ = ['SEPreResNet', 'sepreresnet10', 'sepreresnet12', 'sepreresnet14', 'sepreresnet16', 'sepreresnet18',
'sepreresnet26', 'sepreresnetbc26b', 's... | 19,413 | 33.361062 | 119 | py |
imgclsmob | imgclsmob-master/tensorflow2/tf2cv/models/resnext.py | """
ResNeXt for ImageNet-1K, implemented in TensorFlow.
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... | 16,041 | 32.560669 | 119 | py |
imgclsmob | imgclsmob-master/tensorflow2/tf2cv/models/jasper.py | """
Jasper/DR for ASR, implemented in TensorFlow.
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', 'C... | 39,745 | 32.176962 | 119 | py |
imgclsmob | imgclsmob-master/tensorflow2/tf2cv/models/resneta.py | """
ResNet(A) with average downsampling for ImageNet-1K, implemented in TensorFlow.
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... | 15,634 | 33.667406 | 115 | py |
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