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 |
|---|---|---|---|---|---|---|
byteps | byteps-master/example/mxnet/common/modelzoo.py | # Licensed to the Apache Software Foundation (ASF) under one
# or more contributor license agreements. See the NOTICE file
# distributed with this work for additional information
# regarding copyright ownership. The ASF licenses this file
# to you under the Apache License, Version 2.0 (the
# "License"); you may not u... | 4,181 | 64.34375 | 123 | py |
byteps | byteps-master/example/mxnet/common/data_byteps.py | # Licensed to the Apache Software Foundation (ASF) under one
# or more contributor license agreements. See the NOTICE file
# distributed with this work for additional information
# regarding copyright ownership. The ASF licenses this file
# to you under the Apache License, Version 2.0 (the
# "License"); you may not u... | 8,020 | 45.906433 | 110 | py |
byteps | byteps-master/example/keras/keras_mnist_advanced.py | from __future__ import print_function
from tensorflow import keras
from tensorflow.keras.datasets import mnist
from tensorflow.keras.models import Sequential
from tensorflow.keras.layers import Dense, Dropout, Flatten
from tensorflow.keras.layers import Conv2D, MaxPooling2D
from tensorflow.keras.preprocessing.image imp... | 5,054 | 38.80315 | 90 | py |
byteps | byteps-master/example/keras/keras_mnist.py | from __future__ import absolute_import, division, print_function
import keras
from keras.datasets import mnist
from keras.models import Sequential
from keras.layers import Dense, Dropout, Flatten
from keras.layers import Conv2D, MaxPooling2D
from keras import backend as K
import math
import tensorflow as tf
import byte... | 3,266 | 33.03125 | 90 | py |
byteps | byteps-master/example/keras/keras_synthetic_benchmark_tf2.py | from __future__ import absolute_import, division, print_function
import argparse
import os
import numpy as np
import timeit
import tensorflow as tf
import byteps.tensorflow.keras as bps
from tensorflow.keras import applications
tf.compat.v1.disable_eager_execution()
# Benchmark settings
parser = argparse.ArgumentPa... | 2,891 | 38.616438 | 89 | py |
byteps | byteps-master/example/keras/keras_imagenet_resnet50.py | # Copyright 2019 Bytedance Inc. or its affiliates. All Rights Reserved.
# Copyright 2017 Uber Technologies, Inc. All Rights Reserved.
#
# ResNet-50 model training using Keras and BytePS.
#
# This model is an example of a computation-intensive model that achieves good accuracy on an image
# classification task. It brin... | 8,697 | 46.791209 | 108 | py |
byteps | byteps-master/example/pytorch/train_imagenet_resnet50_byteps.py | from __future__ import print_function
import torch
import argparse
import torch.backends.cudnn as cudnn
import torch.nn.functional as F
import torch.optim as optim
import torch.utils.data.distributed
from torchvision import datasets, transforms, models
import byteps.torch as bps
import tensorboardX
import os
import ma... | 10,935 | 38.623188 | 90 | py |
byteps | byteps-master/example/pytorch/benchmark_byteps.py | from __future__ import print_function
import argparse
import torch.backends.cudnn as cudnn
import torch.nn.functional as F
import torch.optim as optim
import torch.utils.data.distributed
from torchvision import models
import byteps.torch as bps
import timeit
import numpy as np
import os, sys
# Benchmark settings
pars... | 4,331 | 31.818182 | 89 | py |
byteps | byteps-master/example/pytorch/train_imagenet_resnet_byteps_ddp.py | # this example is adapted from the official PyTorch example: https://github.com/pytorch/examples/blob/69d2798ec7fb4f87b320a1848203da5346675b95/imagenet/main.py
# example usage:
#
# bpslaunch python train_imagenet_resnet_byteps_ddp.py -a resnet18 --dist-url 'tcp://127.0.0.1:12345' --dist-backend 'nccl' --multiprocessin... | 16,533 | 37.630841 | 211 | py |
byteps | byteps-master/example/pytorch/elastic_benchmark_byteps.py | from __future__ import print_function
import argparse
import torch.backends.cudnn as cudnn
import torch.nn.functional as F
import torch.optim as optim
import torch.utils.data.distributed
from torchvision import models
import byteps.torch as bps
import timeit
import numpy as np
import os, sys
# Benchmark settings
pars... | 4,621 | 31.549296 | 89 | py |
byteps | byteps-master/example/pytorch/train_mnist_byteps.py | from __future__ import print_function
import argparse
import os
import torch.nn as nn
import torch.nn.functional as F
import torch.optim as optim
from torchvision import datasets, transforms
import torch.utils.data.distributed
import byteps.torch as bps
# Training settings
parser = argparse.ArgumentParser(description=... | 6,526 | 37.169591 | 88 | py |
byteps | byteps-master/example/pytorch/mnist-distributed.py | import os
from datetime import datetime
import argparse
import torch.multiprocessing as mp
import torchvision
import torchvision.transforms as transforms
import torch
import torch.nn as nn
import torch.distributed as dist
from torch.nn.parallel import DistributedDataParallel as DDP
def main():
parser = argparse.A... | 3,788 | 32.236842 | 115 | py |
byteps | byteps-master/example/pytorch/benchmark_cross_barrier_byteps.py | from __future__ import print_function
import argparse
import torch.backends.cudnn as cudnn
import torch.nn.functional as F
import torch.optim as optim
import torch.utils.data.distributed
from torchvision import models
import timeit
import numpy as np
import os
import byteps.torch.cross_barrier as bps
"""
This example... | 5,860 | 35.403727 | 119 | py |
byteps | byteps-master/example/pytorch/benchmark_byteps_ddp.py | from __future__ import print_function
import argparse
import torch.backends.cudnn as cudnn
import torch.nn.functional as F
import torch.optim as optim
import torch.utils.data.distributed
from torchvision import models
import byteps.torch as bps
import timeit
import numpy as np
import os, sys
from byteps.torch.parallel... | 4,433 | 32.089552 | 89 | py |
byteps | byteps-master/example/tensorflow/tensorflow2_keras_mnist.py | # Copyright 2020 Uber Technologies, Inc. All Rights Reserved.
# Copyright 2019 Uber Technologies, Inc. All Rights Reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.... | 3,929 | 40.368421 | 108 | py |
byteps | byteps-master/example/tensorflow/synthetic_benchmark.py |
from __future__ import absolute_import, division, print_function
import argparse
import os, sys
import numpy as np
import timeit
import byteps.tensorflow as bps
from tensorflow.keras import applications
import tensorflow as tf
# Benchmark settings
parser = argparse.ArgumentParser(description='TensorFlow Synthetic B... | 4,178 | 33.254098 | 104 | py |
byteps | byteps-master/example/tensorflow/tensorflow_keras_mnist.py | from __future__ import absolute_import, division, print_function
from tensorflow import keras
from tensorflow.keras.datasets import mnist
from tensorflow.keras.models import Sequential
from tensorflow.keras.layers import Dense, Dropout, Flatten
from tensorflow.keras.layers import Conv2D, MaxPooling2D
from tensorflow.ke... | 3,311 | 33.5 | 90 | py |
byteps | byteps-master/example/tensorflow/tensorflow2_mnist.py | import tensorflow as tf
import byteps.tensorflow as bps
bps.init()
# BytePS: pin GPU to be used to process local rank (one GPU per process)
gpus = tf.config.experimental.list_physical_devices('GPU')
for gpu in gpus:
tf.config.experimental.set_memory_growth(gpu, True)
if gpus:
tf.config.experimental.set_visibl... | 2,391 | 33.666667 | 86 | py |
byteps | byteps-master/example/tensorflow/tensorflow2_mnist_bps_MirroredStrategy.py | import tensorflow as tf
import numpy as np
import json
import os
import sys
import argparse
import byteps.tensorflow as bps
from byteps.tensorflow.distribute import MirroredStrategy
parser = argparse.ArgumentParser(description='TensorFlow Synthetic Benchmark',
formatter_class=argparse... | 2,699 | 35 | 88 | py |
byteps | byteps-master/example/tensorflow/tensorflow_mnist.py | #!/usr/bin/env python
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, softwar... | 6,554 | 39.96875 | 84 | py |
byteps | byteps-master/example/tensorflow/synthetic_benchmark_tf2.py | from __future__ import absolute_import, division, print_function
import argparse
import os
import numpy as np
import timeit
import tensorflow as tf
import byteps.tensorflow as bps
from tensorflow.keras import applications
# Benchmark settings
parser = argparse.ArgumentParser(description='TensorFlow Synthetic Benchma... | 4,311 | 35.542373 | 89 | py |
MnTTS | MnTTS-main/examples/tacotron2/train_tacotron2.py | # -*- coding: utf-8 -*-
# Copyright 2020 Minh Nguyen (@dathudeptrai)
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by ... | 18,412 | 33.807183 | 96 | py |
MnTTS | MnTTS-main/examples/fastspeech/train_fastspeech.py | # -*- coding: utf-8 -*-
# Copyright 2020 Minh Nguyen (@dathudeptrai)
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by ... | 13,591 | 33.762148 | 95 | py |
MnTTS | MnTTS-main/examples/fastspeech2/train_fastspeech2.py | # -*- coding: utf-8 -*-
# Copyright 2020 Minh Nguyen (@dathudeptrai)
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by ... | 14,458 | 33.590909 | 96 | py |
MnTTS | MnTTS-main/examples/hifigan/train_hifigan.py | # -*- coding: utf-8 -*-
# Copyright 2020 TensorFlowTTS Team
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicabl... | 10,464 | 31.101227 | 88 | py |
MnTTS | MnTTS-main/tensorflow_tts/models/base_model.py | # -*- coding: utf-8 -*-
# Copyright 2020 TensorFlowTTS Team.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicab... | 1,131 | 32.294118 | 74 | py |
MnTTS | MnTTS-main/tensorflow_tts/models/parallel_wavegan.py | # -*- coding: utf-8 -*-
# Copyright 2020 The TensorFlowTTS Team and Tomoki Hayashi (@kan-bayashi)
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENS... | 18,663 | 32.508079 | 112 | py |
MnTTS | MnTTS-main/tensorflow_tts/models/melgan.py | # -*- coding: utf-8 -*-
# Copyright 2020 The MelGAN Authors and Minh Nguyen (@dathudeptrai)
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
... | 17,807 | 34.687375 | 106 | py |
MnTTS | MnTTS-main/tensorflow_tts/models/tacotron2.py | # -*- coding: utf-8 -*-
# Copyright 2020 The Tacotron-2 Authors, Minh Nguyen (@dathudeptrai), Eren Gölge (@erogol) and Jae Yoo (@jaeyoo)
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# ... | 37,180 | 34.716619 | 112 | py |
MnTTS | MnTTS-main/tensorflow_tts/models/mb_melgan.py | # -*- coding: utf-8 -*-
# Copyright 2020 The Multi-band MelGAN Authors , Minh Nguyen (@dathudeptrai) and Tomoki Hayashi (@kan-bayashi)
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# ... | 6,890 | 34.704663 | 110 | py |
MnTTS | MnTTS-main/tensorflow_tts/models/hifigan.py | # -*- coding: utf-8 -*-
# Copyright 2020 The Hifigan Authors and TensorflowTTS Team.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unl... | 13,272 | 33.928947 | 91 | py |
MnTTS | MnTTS-main/tensorflow_tts/models/fastspeech2.py | # -*- coding: utf-8 -*-
# Copyright 2020 The FastSpeech2 Authors and Minh Nguyen (@dathudeptrai)
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE... | 12,399 | 38.616613 | 100 | py |
MnTTS | MnTTS-main/tensorflow_tts/models/fastspeech.py | # -*- coding: utf-8 -*-
# Copyright 2020 The FastSpeech Authors, The HuggingFace Inc. team and Minh Nguyen (@dathudeptrai)
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.a... | 33,971 | 36.372937 | 102 | py |
MnTTS | MnTTS-main/tensorflow_tts/optimizers/adamweightdecay.py | # -*- coding: utf-8 -*-
# Copyright 2019 The TensorFlow Authors. All Rights Reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Un... | 6,854 | 37.511236 | 88 | py |
MnTTS | MnTTS-main/tensorflow_tts/utils/utils.py | # -*- coding: utf-8 -*-
# Copyright 2019 Tomoki Hayashi
# MIT License (https://opensource.org/licenses/MIT)
"""Utility functions."""
import fnmatch
import os
import re
import tempfile
from pathlib import Path
import tensorflow as tf
MODEL_FILE_NAME = "model.h5"
CONFIG_FILE_NAME = "config.yml"
PROCESSOR_FILE_NAME =... | 3,053 | 30.163265 | 80 | py |
MnTTS | MnTTS-main/tensorflow_tts/utils/group_conv.py | # -*- coding: utf-8 -*-
# This code is copy from https://github.com/tensorflow/tensorflow/pull/36773.
"""Group Convolution Modules."""
from tensorflow.python.framework import tensor_shape
from tensorflow.python.keras import activations, constraints, initializers, regularizers
from tensorflow.python.keras.engine.base_l... | 23,944 | 41.989228 | 88 | py |
MnTTS | MnTTS-main/tensorflow_tts/utils/griffin_lim.py | # -*- coding: utf-8 -*-
# Copyright 2020 Minh Nguyen (@dathudeptrai)
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by ... | 6,824 | 39.868263 | 88 | py |
MnTTS | MnTTS-main/tensorflow_tts/utils/weight_norm.py | # -*- coding: utf-8 -*-
# Copyright 2019 The TensorFlow Probability Authors and Minh Nguyen (@dathudeptrai)
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licen... | 7,216 | 38.010811 | 102 | py |
MnTTS | MnTTS-main/tensorflow_tts/losses/stft.py | # -*- coding: utf-8 -*-
# Copyright 2020 Minh Nguyen (@dathudeptrai)
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by ... | 5,179 | 33.533333 | 97 | py |
MnTTS | MnTTS-main/tensorflow_tts/losses/spectrogram.py | # -*- coding: utf-8 -*-
# Copyright 2020 Minh Nguyen (@dathudeptrai)
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by ... | 2,697 | 31.902439 | 83 | py |
MnTTS | MnTTS-main/tensorflow_tts/trainers/base_trainer.py | # -*- coding: utf-8 -*-
# Copyright 2020 Minh Nguyen (@dathudeptrai)
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by ... | 36,562 | 35.165183 | 113 | py |
MnTTS | MnTTS-main/test/test_fastspeech.py | # -*- coding: utf-8 -*-
# Copyright 2020 Minh Nguyen (@dathudeptrai)
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by ... | 2,995 | 34.247059 | 86 | py |
MnTTS | MnTTS-main/test/test_tacotron2.py | # -*- coding: utf-8 -*-
# Copyright 2020 Minh Nguyen (@dathudeptrai)
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by ... | 5,329 | 34.533333 | 87 | py |
MnTTS | MnTTS-main/test/test_melgan_layers.py | # -*- coding: utf-8 -*-
# Copyright 2020 Minh Nguyen (@dathudeptrai)
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by ... | 2,965 | 30.892473 | 113 | py |
MnTTS | MnTTS-main/test/test_fastspeech2.py | # -*- coding: utf-8 -*-
# Copyright 2020 Minh Nguyen (@dathudeptrai)
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by ... | 4,805 | 35.969231 | 88 | py |
tenpy | tenpy-main/doc/conf.py | #!/usr/bin/env python3
# -*- coding: utf-8 -*-
# Copyright 2019-2023 TeNPy Developers, GNU GPLv3
#
import sys
import os
import inspect
import sphinx_rtd_theme
import io
import warnings
# ensure parent folder is in sys.path to allow import of tenpy
REPO_PREFIX = os.path.abspath(os.path.join(os.path.dirname(__file__), '... | 13,181 | 33.417755 | 151 | py |
silero-models | silero-models-master/hubconf.py | dependencies = ["torch"]
import sys
from src.silero import (
silero_stt,
silero_tts,
silero_te,
)
__all__ = [
"silero_stt",
"silero_tts",
"silero_te",
]
sys.path.append("src/silero")
| 210 | 11.411765 | 29 | py |
silero-models | silero-models-master/src/silero/utils.py | import os
import torch
import warnings
import torchaudio
from typing import List
from itertools import groupby
def read_batch(audio_paths: List[str]):
return [read_audio(audio_path)
for audio_path
in audio_paths]
def split_into_batches(lst: List[str],
batch_size: i... | 4,449 | 32.458647 | 93 | py |
silero-models | silero-models-master/src/silero/silero.py | import os
import torch
def silero_stt(language='en',
version='latest',
jit_model='jit',
**kwargs):
""" Silero Speech-To-Text Model(s)
language (str): language of the model, now available are ['en', 'de', 'es']
Returns a model, decoder object and a set of utils
... | 6,325 | 41.456376 | 147 | py |
silero-models | silero-models-master/src/silero/tts_utils.py | import os
import re
import torch
import warnings
def init_jit_model(model_url: str,
device: torch.device = torch.device('cpu')):
torch.set_grad_enabled(False)
model_dir = os.path.join(os.path.dirname(__file__), "model")
os.makedirs(model_dir, exist_ok=True)
model_path = os.path.joi... | 3,090 | 31.197917 | 101 | py |
flpytorch | flpytorch-main/setup.py | #!/usr/bin/env python3
import setuptools
with open("README.md", "r") as fh:
long_description = fh.read()
setuptools.setup(
name="fl_pytorch",
version="0.0.1",
author_email="konstantin.burlachenko@kaust.edu.sa,samuel.horvath@kaust.edu.sa,peter.richtarik@kaust.edu.sa",
description="Efficient Simula... | 737 | 29.75 | 112 | py |
flpytorch | flpytorch-main/fl_pytorch/opts.py | #!/usr/bin/env python3
import argparse
import time
from datetime import datetime
import os
import utils.gpu_utils as gpu_utils
import random
# Global simulation counter
gSimulationCounter = 0
def parse_args(args):
parser = initialise_arg_parser(args, 'FLPyTorch, running arguments.')
# SERVER OPTIMIZATION P... | 15,635 | 28.89675 | 124 | py |
flpytorch | flpytorch-main/fl_pytorch/run.py | #!/usr/bin/env python3
import os
import sys
import json
import socket
import math
import signal
# Import PyTorch root package import torch
import torch
from torch.utils.collect_env import get_pretty_env_info
import numpy as np
import time
import copy
import threading
import pickle
from utils import comm_socket
from... | 49,485 | 47.75468 | 136 | py |
flpytorch | flpytorch-main/fl_pytorch/gui/start.py | #!/usr/bin/env python3
# https://wiki.python.org/moin/PyQt
# https://www.riverbankcomputing.com/static/Docs/PyQt5/
# Example of path to designer in Windows OS: Python38/Lib/site-packages/qt5_applications/Qt/bin/designer.exe
import sys, platform, time, shutil, pickle, threading, math, socket
import datetime
import os... | 129,627 | 40.801999 | 203 | py |
flpytorch | flpytorch-main/fl_pytorch/gui/generated/ConfigWidget.py | # -*- coding: utf-8 -*-
# Form implementation generated from reading ui file './../forms/ConfigWidget.ui'
#
# Created by: PyQt5 UI code generator 5.15.4
#
# WARNING: Any manual changes made to this file will be lost when pyuic5 is
# run again. Do not edit this file unless you know what you are doing.
from PyQt5 imp... | 85,728 | 74.134969 | 436 | py |
flpytorch | flpytorch-main/fl_pytorch/gui/generated/LogWindow.py | # -*- coding: utf-8 -*-
# Form implementation generated from reading ui file './../forms/LogWindow.ui'
#
# Created by: PyQt5 UI code generator 5.15.4
#
# WARNING: Any manual changes made to this file will be lost when pyuic5 is
# run again. Do not edit this file unless you know what you are doing.
from PyQt5 import... | 7,538 | 56.992308 | 224 | py |
flpytorch | flpytorch-main/fl_pytorch/models/wideresnet_cifar.py | #!/usr/bin/env python3
# Import PyTorch root package import torch
import torch
import torch.nn as nn
import torch.nn.functional as F
class BasicBlock(nn.Module):
def __init__(self, in_planes, out_planes, stride, dropRate=0.0):
super(BasicBlock, self).__init__()
self.bn1 = nn.BatchNorm2d(in_planes... | 4,214 | 38.764151 | 116 | py |
flpytorch | flpytorch-main/fl_pytorch/models/femnist.py | #!/usr/bin/env python3
"""
CNN model for FEMNIST Dataset.
"""
from torch import nn
# Import PyTorch layers, activations and more
import torch.nn.functional as F
class FEMNIST(nn.Module):
def __init__(self, channel_1=32, channel_2=64, num_classes=62):
super(FEMNIST, self).__init__()
self.conv1 =... | 1,029 | 27.611111 | 72 | py |
flpytorch | flpytorch-main/fl_pytorch/models/vgg_cifar.py | #!/usr/bin/env python3
"""
VGG11/13/16/19 in Pytorch.
"""
import torch.nn as nn
cfg = {
'VGG11': [64, 'M', 128, 'M', 256, 256, 'M', 512, 512, 'M', 512, 512, 'M'],
'VGG13': [64, 64, 'M', 128, 128, 'M', 256, 256, 'M', 512, 512, 'M', 512, 512, 'M'],
'VGG16': [64, 64, 'M', 128, 128, 'M', 256, 256, 256, 'M', ... | 1,824 | 29.932203 | 117 | py |
flpytorch | flpytorch-main/fl_pytorch/models/resnet_cifarlike.py | #!/usr/bin/env python3
# From: https://github.com/kuangliu/pytorch-cifar
"""ResNet in PyTorch.
For Pre-activation ResNet, see 'preact_resnet.py'.
Reference:
[1] Kaiming He, Xiangyu Zhang, Shaoqing Ren, Jian Sun
Deep Residual Learning for Image Recognition. arXiv:1512.03385
"""
import torch.nn as nn
# Import Py... | 4,689 | 34 | 83 | py |
flpytorch | flpytorch-main/fl_pytorch/models/resnet_cifar.py | #!/usr/bin/env python3
# From https://github.com/akamaster/pytorch_resnet_cifar10/blob/master/resnet.py
"""
Properly implemented ResNet-s for CIFAR10 as described in paper [1].
The implementation and structure of this file is hugely influenced by [2]
which is implemented for ImageNet and doesn't have option A for id... | 4,928 | 32.304054 | 120 | py |
flpytorch | flpytorch-main/fl_pytorch/models/__init__.py | # ResNets from Torch Vision
from torchvision.models import resnet18 as tv_resnet18
from torchvision.models import resnet34 as tv_resnet34
from torchvision.models import resnet50 as tv_resnet50
# ResNets for CIFAR Datasets
from .resnet_cifar import resnet20
from .resnet_cifar import resnet32
from .resnet_cifar import r... | 1,323 | 33.842105 | 68 | py |
flpytorch | flpytorch-main/fl_pytorch/models/rnn.py | #!/usr/bin/env python3
"""
Reccurent Neural Network for Shakespeare Dataset
"""
# Import PyTorch root package import torch
import torch
import torch.nn as nn
class RNN(nn.Module):
def __init__(self, vocab_size=90, embedding_dim=8, hidden_dim=512, num_layers=2):
super(RNN, self).__init__()
# s... | 1,544 | 29.294118 | 101 | py |
flpytorch | flpytorch-main/fl_pytorch/models/mutils.py | #!/usr/bin/env python3
# Import PyTorch root package
import torch
# Import PyTorch layers, activations and more
# import torch.nn.functional as F
from utils.logger import Logger
def torch_layers_info(model: torch.nn.Module):
"""
Args:
model (nn.Module): Neural Networ... | 19,394 | 36.369942 | 264 | py |
flpytorch | flpytorch-main/fl_pytorch/scripts/dump_quality.py | #!/usr/bin/env python3
import math, sys, pickle, os
import numpy as np
import torch
sys.path.append(os.path.join(os.path.dirname(__file__), "./../"))
from utils import utils
if __name__ == "__main__":
files = sys.argv[1:]
if len(files) == 0:
print("# Tool for dump information about some tracking qu... | 1,275 | 29.380952 | 75 | py |
flpytorch | flpytorch-main/fl_pytorch/scripts/extract_cmdline_from_bin.py | #!/usr/bin/env python3
import math, sys, pickle, os
import numpy as np
import torch
sys.path.append(os.path.join(os.path.dirname(__file__), "./../"))
from utils import utils
if __name__ == "__main__":
python = "python"
files = sys.argv[1:]
if len(files) == 0:
print("# Tool for extracting com... | 1,054 | 26.051282 | 86 | py |
flpytorch | flpytorch-main/fl_pytorch/scripts/extract_cmdline_from_bin_nice.py | #!/usr/bin/env python3
import math, sys, pickle, os
import numpy as np
import torch
sys.path.append(os.path.join(os.path.dirname(__file__), "./../"))
from utils import utils
if __name__ == "__main__":
python = "python"
files = sys.argv[1:]
if len(files) == 0:
print("# Tool for extracting com... | 1,156 | 27.925 | 142 | py |
flpytorch | flpytorch-main/fl_pytorch/scripts/dump_configuration.py | #!/usr/bin/env python3
import math, sys, pickle, os
import numpy as np
import torch
sys.path.append(os.path.join(os.path.dirname(__file__), "./../"))
from utils import utils
if __name__ == "__main__":
files = sys.argv[1:]
if len(files) == 0:
print("# Tool for dump information about experiments insi... | 1,026 | 28.342857 | 82 | py |
flpytorch | flpytorch-main/fl_pytorch/scripts/prune_from_tensors.py | #!/usr/bin/env python3
import math, sys, pickle, os
import numpy as np
import torch
import copy
sys.path.append(os.path.join(os.path.dirname(__file__), "./../"))
from utils import utils
if __name__ == "__main__":
files = sys.argv[1:]
if len(files) == 0:
print("# Tool for prune away any tensors from... | 5,177 | 41.097561 | 139 | py |
flpytorch | flpytorch-main/fl_pytorch/data_preprocess/libsvm_dataset.py | from .fl_dataset import FLDataset
from .read_file_cache import cacheItemThreadSafe, cacheMakeKey, cacheGetItem
from utils.logger import Logger
from utils import execution_context
import numpy as np
from torchvision.datasets.utils import download_url
import os
import math
import torch
# Train datasets URL's for train... | 18,634 | 44.67402 | 307 | py |
flpytorch | flpytorch-main/fl_pytorch/data_preprocess/data_loader.py | #!/usr/bin/env python3
# Import PyTorch root package import torch
import torch
import torchvision
from torchvision import transforms
from .fl_datasets import FEMNIST, FLCifar100, FLCifar10, FLCifar10ByClass, Shakespeare, SHAKESPEARE_EVAL_BATCH_SIZE
from .artificial_dataset import ArificialDataset
from .libsvm_datase... | 9,055 | 37.21097 | 119 | py |
flpytorch | flpytorch-main/fl_pytorch/data_preprocess/fl_dataset.py | #!/usr/bin/env python3
from torch.utils.data import Dataset
class FLDataset(Dataset):
"""
Base class for Federated Datasets with pointers to clients.
"""
def set_client(self, index=None):
raise NotImplementedError
def load_data(self):
raise NotImplementedError
| 301 | 19.133333 | 63 | py |
flpytorch | flpytorch-main/fl_pytorch/data_preprocess/h5_tff_dataset.py | #!/usr/bin/env python3
import os
import h5py
from .read_file_cache import cacheItemThreadUnsafe, cacheMakeKey, cacheGetItem
from .fl_dataset import FLDataset
from torchvision.datasets.utils import download_url
from utils import execution_context
TFF_DATASETS = {
'cifar100_fl': 'https://storage.googleapis.com/tff... | 5,059 | 40.818182 | 166 | py |
flpytorch | flpytorch-main/fl_pytorch/data_preprocess/artificial_dataset.py | #!/usr/bin/env python3
from .read_file_cache import cacheItemThreadUnsafe, cacheMakeKey, cacheGetItem, cacheHasItem
from .fl_dataset import FLDataset
import numpy as np
# Import PyTorch root package import torch
import torch
import math
class ArificialDataset(FLDataset):
"""
Based FL class that loads H5 typ... | 7,454 | 36.275 | 120 | py |
flpytorch | flpytorch-main/fl_pytorch/data_preprocess/fl_datasets/femnist.py | import os
import numpy as np
import torchvision
from ..h5_tff_dataset import H5TFFDataset
class FEMNIST(H5TFFDataset):
"""
Federated Extended MNIST Dataset.
Clients corresponds to different person handwriting.
"""
def __init__(self, h5_path, train=True, client_id=None):
if train:
... | 1,068 | 30.441176 | 90 | py |
flpytorch | flpytorch-main/fl_pytorch/data_preprocess/fl_datasets/cifar10.py | from torchvision.datasets import CIFAR10
from torchvision import transforms
from PIL import Image
import numpy as np
class FLCifar10(CIFAR10):
"""
CIFAR10 Dataset.
num_clients clients that were allocated data_preprocess uniformly at random.
"""
def __init__(self, exec_ctx, args, root, train=True, ... | 3,643 | 34.72549 | 136 | py |
flpytorch | flpytorch-main/fl_pytorch/data_preprocess/fl_datasets/cifar10_by_class.py | from torchvision.datasets import CIFAR10
from PIL import Image
import numpy as np
import torch
class FLCifar10ByClass(CIFAR10):
"""
CIFAR10 Dataset.
num_clients clients that were allocated data_preprocess uniformly at random.
"""
def __init__(self, exec_ctx, args, root, train=True, transform=None, ... | 6,165 | 37.298137 | 140 | py |
flpytorch | flpytorch-main/fl_pytorch/data_preprocess/fl_datasets/shakespeare.py | import os
import numpy as np
# Import PyTorch root package import torch
import torch
from torch.utils.data import DataLoader
from ..h5_tff_dataset import H5TFFDataset
from ..fl_dataset import FLDataset
SHAKESPEARE_VOCAB = list('dhlptx@DHLPTX $(,048cgkoswCGKOSW[_#\'/37;?bfjnrvzBFJNRVZ"&*.26:\naeimquyAEIMQUY]!%)-159\... | 5,873 | 39.791667 | 117 | py |
flpytorch | flpytorch-main/fl_pytorch/fl_layers/utils.py | #!/usr/bin/env python3
# Import Tensor node in the computation graph
from torch import Tensor
def input_to_block_diag(x_array: Tensor) -> Tensor:
pass
| 158 | 16.666667 | 51 | py |
flpytorch | flpytorch-main/fl_pytorch/utils/worker_thread.py | #!/usr/bin/env python3
# Import PyTorch root package import torch
import torch
import threading
from . import buffer
class WorkerThread(threading.Thread):
"""Worker thread. It's goal execute deferred functions."""
def __init__(self):
threading.Thread.__init__(self)
self.cmds = buffer.Buff... | 3,710 | 32.736364 | 120 | py |
flpytorch | flpytorch-main/fl_pytorch/utils/model_funcs.py | #!/usr/bin/env python3
# Import PyTorch root package import torch
import torch
import random
from torch import nn
from torch.nn import DataParallel
import time
import copy
import math
import os
import json
from collections import OrderedDict
import numpy as np
from copy import deepcopy
import pickle
from torch.opt... | 39,950 | 41.009464 | 195 | py |
flpytorch | flpytorch-main/fl_pytorch/utils/thread_pool.py | #!/usr/bin/env python3
import time
# Import PyTorch root package import torch
import torch
from . import worker_thread
from . import gpu_utils
class ThreadPool:
"""Thread pool. Collectively execute assigned work."""
def __init__(self, number_of_workers=0):
"""
Constructor.
Args:
... | 4,898 | 33.020833 | 120 | py |
flpytorch | flpytorch-main/fl_pytorch/utils/execution_context.py | #!/usr/bin/env python3
import threading
import random
import time
import numpy as np
from . import thread_pool
class ExecutionContext:
"""Private execution data. Please do not manipulate directly, only with dedicated API"""
pass
def initExecutionContext():
"""Initialize thread specific execution cont... | 2,913 | 48.389831 | 120 | py |
flpytorch | flpytorch-main/fl_pytorch/utils/gpu_utils.py | #!/usr/bin/env python3
# Import PyTorch root package import torch
import torch
from . import logger
def is_target_dev_gpu(device):
""" Check that target device is gpu.
Args:
device: integer or string. If it's integer -1 stands for CPU, and value greater then or equal to
0 is a GPU number in... | 4,104 | 33.788136 | 120 | py |
flpytorch | flpytorch-main/fl_pytorch/utils/compressors.py | #!/usr/bin/env python3
# -*- coding: utf-8 -*-
# Import PyTorch root package import torch
import torch
import math
import numpy as np
class CompressorType:
IDENTICAL = 1 # Identical compressor
LAZY_COMPRESSOR = 2 # Lazy or Bernulli compressor
RANDK_COMPRESSOR = 3 # Rank-K... | 20,215 | 36.786916 | 120 | py |
flpytorch | flpytorch-main/fl_pytorch/utils/algorithms.py | #!/usr/bin/env python3
import random
import time
import copy
import math
# Import PyTorch root package import torch
import torch
import numpy as np
from utils import execution_context
from utils import model_funcs
from utils import compressors
from models import mutils
import utils
import a... | 94,490 | 40.736307 | 223 | py |
flpytorch | flpytorch-main/fl_pytorch/utils/fl_funcs.py | #!/usr/bin/env python3
import numpy as np
# Import PyTorch root package import torch
import torch
from copy import deepcopy
from .logger import Logger
def get_sampled_clients(num_clients, args, exec_ctx):
# clients are pre-sampled for deterministic participation among runs
if args.client_sampling_type == "... | 4,355 | 39.71028 | 137 | py |
flpytorch | flpytorch-main/fl_pytorch/utils/checkpointing.py | #!/usr/bin/env python3
import os
# Import PyTorch root package import torch
import torch
import shutil
import json
import copy
from utils.utils import get_model_str_from_obj
from utils.logger import Logger
from utils.utils import create_model_dir, create_metrics_dict
from utils import execution_context
import util... | 9,225 | 38.259574 | 147 | py |
flpytorch | flpytorch-main/docs/generate.py | #!/usr/bin/env python3
import glob, os, subprocess
# Create destantion folder for documentation
if not os.path.exists("./generated"):
os.makedirs("./generated")
gendocs_folder = os.path.abspath("generated")
print("Documentaiton will be generated in folder: ", gendocs_folder)
# Get path for template folder
temp... | 1,394 | 34.769231 | 130 | py |
robust_object_detection | robust_object_detection-main/test.py | import os
import torch
import argparse
from detectron2.config import CfgNode
from detectron2.evaluation import inference_on_dataset
from detectron2.utils.events import EventStorage
from detectron2.utils.logger import setup_logger
from src.evaluation.build import build_evaluator
from src.models.build import build_mode... | 2,610 | 41.112903 | 108 | py |
robust_object_detection | robust_object_detection-main/src/models/faster_rcnn.py | import torch
from typing import Dict, List
from detectron2.modeling.meta_arch.rcnn import GeneralizedRCNN
from detectron2.modeling.roi_heads.fast_rcnn import fast_rcnn_inference
from detectron2.modeling.meta_arch.build import META_ARCH_REGISTRY
from detectron2.utils.events import get_event_storage
@META_ARCH_REGISTRY... | 6,342 | 52.302521 | 169 | py |
robust_object_detection | robust_object_detection-main/src/models/retinanet.py | import torch
from typing import Dict, List
from detectron2.modeling.meta_arch.build import META_ARCH_REGISTRY
from detectron2.modeling.meta_arch.retinanet import RetinaNet, permute_to_N_HWA_K
from detectron2.structures import Boxes, Instances
from detectron2.utils.events import get_event_storage
from detectron2.layers ... | 6,244 | 46.310606 | 158 | py |
robust_object_detection | robust_object_detection-main/src/models/fcos.py | import torch
from typing import Dict, List
from detectron2.modeling.meta_arch.build import META_ARCH_REGISTRY
from detectron2.structures import ImageList
from .adet import OneStageDetector
@META_ARCH_REGISTRY.register()
class CustomFCOS(OneStageDetector):
'''
With train_forward() and compute_losses(), we can ... | 3,673 | 51.485714 | 133 | py |
robust_object_detection | robust_object_detection-main/src/models/build.py | import torch
from detectron2.modeling import build_model as build_architecture
from .faster_rcnn import CustomFasterRCNN
from .retinanet import CustomRetinaNet
from .fcos import CustomFCOS
def build_model(cfg):
'''
Wrapper around detectron's build_model() to do the backbone (or the whole model) initialization ... | 2,246 | 50.068182 | 124 | py |
robust_object_detection | robust_object_detection-main/src/models/adet/layers/deform_conv.py | import torch
from torch import nn
from detectron2.layers import Conv2d
class _NewEmptyTensorOp(torch.autograd.Function):
@staticmethod
def forward(ctx, x, new_shape):
ctx.shape = x.shape
return x.new_empty(new_shape)
@staticmethod
def backward(ctx, grad):
shape = ctx.shape
... | 3,988 | 33.094017 | 104 | py |
robust_object_detection | robust_object_detection-main/src/models/adet/layers/iou_loss.py | import torch
from torch import nn
class IOULoss(nn.Module):
"""
Intersetion Over Union (IoU) loss which supports three
different IoU computations:
* IoU
* Linear IoU
* gIoU
"""
def __init__(self, loc_loss_type='iou'):
super(IOULoss, self).__init__()
self.loc_loss_type =... | 830 | 25.806452 | 58 | py |
robust_object_detection | robust_object_detection-main/src/models/adet/layers/naive_group_norm.py | import torch
from torch.nn import Module, Parameter
from torch.nn import init
class NaiveGroupNorm(Module):
r"""NaiveGroupNorm implements Group Normalization with the high-level matrix operations in PyTorch.
It is a temporary solution to export GN by ONNX before the official GN can be exported by ONNX.
Th... | 2,976 | 41.528571 | 103 | py |
robust_object_detection | robust_object_detection-main/src/models/adet/utils/comm.py | import torch
import torch.nn.functional as F
import torch.distributed as dist
from detectron2.utils.comm import get_world_size
def reduce_sum(tensor):
world_size = get_world_size()
if world_size < 2:
return tensor
tensor = tensor.clone()
dist.all_reduce(tensor, op=dist.ReduceOp.SUM)
retur... | 2,879 | 26.961165 | 68 | py |
robust_object_detection | robust_object_detection-main/src/models/adet/modeling/one_stage_detector.py | import logging
from torch import nn
from detectron2.modeling.meta_arch.build import META_ARCH_REGISTRY
from detectron2.modeling import ProposalNetwork, GeneralizedRCNN
from detectron2.utils.events import get_event_storage
from detectron2.utils.logger import log_first_n
from detectron2.modeling.postprocessing import de... | 7,381 | 39.56044 | 100 | py |
robust_object_detection | robust_object_detection-main/src/models/adet/modeling/backbone/lpf.py | import torch
import torch.nn.parallel
import numpy as np
import torch.nn as nn
import torch.nn.functional as F
class Downsample(nn.Module):
def __init__(self, pad_type='reflect', filt_size=3, stride=2, channels=None, pad_off=0):
super(Downsample, self).__init__()
self.filt_size = filt_size
... | 4,207 | 35.912281 | 143 | py |
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