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
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robust_trust_region | robust_trust_region-main/pytorch-deeplab_v3_plus/dataloaders/utils.py | import numpy as np
import torch
def decode_seg_map_sequence(label_masks, dataset='pascal'):
rgb_masks = []
for label_mask in label_masks:
rgb_mask = decode_segmap(label_mask, dataset)
rgb_masks.append(rgb_mask)
rgb_masks = torch.from_numpy(np.array(rgb_masks).transpose([0, 3, 1, 2]))
re... | 3,959 | 33.137931 | 84 | py |
robust_trust_region | robust_trust_region-main/pytorch-deeplab_v3_plus/dataloaders/__init__.py | from torch.utils.data import DataLoader, dataset
from dataloaders.datasets import combine_dbs, indexed_dataset
import numpy as np
def make_data_loader(args, proposal_generator=None, **kwargs):
def wrap_dataset(set):
if 'single_image_training' in args and args.single_image_training is not None:
if ar... | 2,887 | 44.84127 | 113 | py |
robust_trust_region | robust_trust_region-main/pytorch-deeplab_v3_plus/dataloaders/datasets/cityscapes.py | import os
import numpy as np
import scipy.misc as m
from PIL import Image
from torch.utils import data
from mypath import Path
from torchvision import transforms
from dataloaders import custom_transforms as tr
class CityscapesSegmentation(data.Dataset):
NUM_CLASSES = 19
def __init__(self, args, root=Path.db_r... | 5,370 | 35.537415 | 103 | py |
robust_trust_region | robust_trust_region-main/pytorch-deeplab_v3_plus/dataloaders/datasets/pascal.py | from __future__ import print_function, division
import os
from PIL import Image
import numpy as np
import torch
from torch.utils.data import Dataset
from mypath import Path
from torchvision import transforms
from dataloaders import custom_transforms as tr
class VOCSegmentation(Dataset):
"""
PascalVoc dataset
... | 7,403 | 33.598131 | 105 | py |
robust_trust_region | robust_trust_region-main/pytorch-deeplab_v3_plus/dataloaders/datasets/sbd.py | from __future__ import print_function, division
import os
import numpy as np
import scipy.io
import torch.utils.data as data
from PIL import Image
from mypath import Path
from torchvision import transforms
from dataloaders import custom_transforms as tr
class SBDSegmentation(data.Dataset):
NUM_CLASSES = 21
... | 4,081 | 30.643411 | 106 | py |
robust_trust_region | robust_trust_region-main/pytorch-deeplab_v3_plus/dataloaders/datasets/indexed_dataset.py | import torch.utils.data.dataset
class IndexedDataset(torch.utils.data.dataset.Dataset):
def __init__(self, base):
self.base = base
def __getitem__(self, index):
sample = self.base[index]
sample["index"] = index
return sample
def __len__(self):
return len(self.base)... | 321 | 22 | 55 | py |
robust_trust_region | robust_trust_region-main/pytorch-deeplab_v3_plus/dataloaders/datasets/combine_dbs.py | import torch.utils.data as data
class CombineDBs(data.Dataset):
NUM_CLASSES = 21
def __init__(self, dataloaders, excluded=None):
self.dataloaders = dataloaders
self.excluded = excluded
self.im_ids = []
# Combine object lists
for dl in dataloaders:
for elem ... | 3,310 | 32.11 | 96 | py |
robust_trust_region | robust_trust_region-main/pytorch-deeplab_v3_plus/dataloaders/datasets/coco.py | import numpy as np
import torch
from torch.utils.data import Dataset
from mypath import Path
from tqdm import trange
import os
from pycocotools.coco import COCO
from pycocotools import mask
from torchvision import transforms
from dataloaders import custom_transforms as tr
from PIL import Image, ImageFile
ImageFile.LOAD... | 5,636 | 34.012422 | 96 | py |
robust_trust_region | robust_trust_region-main/pytorch-deeplab_v3_plus/utils/log_lin_softmax.py | import torch
from torch.autograd import Function
from torch.autograd import Variable
import torch.nn.functional as F
class LogLinSoftmax(Function):
# computes log(a + b * s_ijkl) where s_ijkl is softmax of the input
@staticmethod
def forward(ctx, a, b, logits, dim):
ctx.dim, ctx.a, ctx.b = dim, a... | 2,569 | 31.948718 | 88 | py |
robust_trust_region | robust_trust_region-main/pytorch-deeplab_v3_plus/utils/proposal_generator.py | import multiprocessing as mp
import tempfile, shutil, os
import io, pickle
import torch
import torch.nn.functional as F
import gzip
class AlphaBasedProposalGenerator(object):
def __init__(self, alpha_expansion, eps=0):
self.alpha_expansion = alpha_expansion
self.model = None
self.eps = eps... | 3,035 | 27.373832 | 84 | py |
robust_trust_region | robust_trust_region-main/pytorch-deeplab_v3_plus/utils/saver.py | import os
import shutil
import torch
from collections import OrderedDict
import glob
class Saver(object):
def __init__(self, args):
self.args = args
self.directory = os.path.join('run', args.dataset + args.train_dataset_suffix, args.checkname)
self.runs = sorted(glob.glob(os.path.join(self... | 2,581 | 39.34375 | 109 | py |
robust_trust_region | robust_trust_region-main/pytorch-deeplab_v3_plus/utils/vis.py | import torch
def get_edges(seg_map):
edges = torch.zeros_like(seg_map) == 1
edges[..., :-1, :] |= seg_map[..., :-1, :] != seg_map[..., 1:, :]
edges[..., :, :-1] |= seg_map[..., :, :-1] != seg_map[..., :, 1:]
edges[..., 1:, :] |= seg_map[..., :-1, :] != seg_map[..., 1:, :]
edges[..., :, 1:] |= seg... | 378 | 36.9 | 69 | py |
robust_trust_region | robust_trust_region-main/pytorch-deeplab_v3_plus/utils/loss.py | import torch
import torch.nn as nn
import torch.nn.functional as F
class SegmentationLosses(object):
def __init__(self, weight=None, reduction_mode='mean', batch_average=True, ignore_index=255, cuda=False):
self.ignore_index = ignore_index
self.weight = weight
self.reduction_mode = reductio... | 3,977 | 33.894737 | 109 | py |
robust_trust_region | robust_trust_region-main/pytorch-deeplab_v3_plus/utils/summaries.py | import os
import torch
import numpy as np
import scipy.ndimage
from torchvision.utils import make_grid
from tensorboardX import SummaryWriter
from dataloaders.utils import decode_seg_map_sequence
from utils import vis
class TensorboardSummary(object):
def __init__(self, directory):
self.directory = directo... | 1,691 | 42.384615 | 108 | py |
robust_trust_region | robust_trust_region-main/pytorch-deeplab_v3_plus/modeling/aspp.py | import math
import torch
import torch.nn as nn
import torch.nn.functional as F
from modeling.sync_batchnorm.batchnorm import SynchronizedBatchNorm2d
class _ASPPModule(nn.Module):
def __init__(self, inplanes, planes, kernel_size, padding, dilation, BatchNorm):
super(_ASPPModule, self).__init__()
sel... | 3,602 | 36.926316 | 116 | py |
robust_trust_region | robust_trust_region-main/pytorch-deeplab_v3_plus/modeling/decoder.py | import math
import torch
import torch.nn as nn
import torch.nn.functional as F
from modeling.sync_batchnorm.batchnorm import SynchronizedBatchNorm2d
class Decoder(nn.Module):
def __init__(self, num_classes, backbone, BatchNorm, skip=False):
super(Decoder, self).__init__()
if backbone == 'resnet' or... | 3,606 | 34.019417 | 104 | py |
robust_trust_region | robust_trust_region-main/pytorch-deeplab_v3_plus/modeling/deeplab.py | import torch
import torch.nn as nn
import torch.nn.functional as F
from modeling.sync_batchnorm.batchnorm import SynchronizedBatchNorm2d
from modeling.aspp import build_aspp
from modeling.decoder import build_decoder
from modeling.backbone import build_backbone
def freeze_batchnorm(self):
for m in self.modules():... | 2,898 | 30.857143 | 93 | py |
robust_trust_region | robust_trust_region-main/pytorch-deeplab_v3_plus/modeling/backbone/resnet.py | import math
import torch.nn as nn
import torch.utils.model_zoo as model_zoo
from modeling.sync_batchnorm.batchnorm import SynchronizedBatchNorm2d
class Bottleneck(nn.Module):
expansion = 4
def __init__(self, inplanes, planes, stride=1, dilation=1, downsample=None, BatchNorm=None):
super(Bottleneck, se... | 6,222 | 37.41358 | 130 | py |
robust_trust_region | robust_trust_region-main/pytorch-deeplab_v3_plus/modeling/backbone/drn.py | import torch.nn as nn
import math
import torch.utils.model_zoo as model_zoo
from modeling.sync_batchnorm.batchnorm import SynchronizedBatchNorm2d
webroot = 'https://tigress-web.princeton.edu/~fy/drn/models/'
model_urls = {
'resnet50': 'https://download.pytorch.org/models/resnet50-19c8e357.pth',
'drn-c-26': we... | 14,649 | 35.352357 | 100 | py |
robust_trust_region | robust_trust_region-main/pytorch-deeplab_v3_plus/modeling/backbone/xception.py | import math
import torch
import torch.nn as nn
import torch.nn.functional as F
import torch.utils.model_zoo as model_zoo
from modeling.sync_batchnorm.batchnorm import SynchronizedBatchNorm2d
def fixed_padding(inputs, kernel_size, dilation):
kernel_size_effective = kernel_size + (kernel_size - 1) * (dilation - 1)
... | 11,553 | 39.118056 | 116 | py |
robust_trust_region | robust_trust_region-main/pytorch-deeplab_v3_plus/modeling/backbone/mobilenet.py | import torch
import torch.nn.functional as F
import torch.nn as nn
import math
from modeling.sync_batchnorm.batchnorm import SynchronizedBatchNorm2d
import torch.utils.model_zoo as model_zoo
def conv_bn(inp, oup, stride, BatchNorm):
return nn.Sequential(
nn.Conv2d(inp, oup, 3, stride, 1, bias=False),
... | 5,390 | 34.467105 | 110 | py |
robust_trust_region | robust_trust_region-main/pytorch-deeplab_v3_plus/modeling/sync_batchnorm/replicate.py | # -*- coding: utf-8 -*-
# File : replicate.py
# Author : Jiayuan Mao
# Email : maojiayuan@gmail.com
# Date : 27/01/2018
#
# This file is part of Synchronized-BatchNorm-PyTorch.
# https://github.com/vacancy/Synchronized-BatchNorm-PyTorch
# Distributed under MIT License.
import functools
from torch.nn.parallel.dat... | 3,218 | 35.579545 | 115 | py |
robust_trust_region | robust_trust_region-main/pytorch-deeplab_v3_plus/modeling/sync_batchnorm/unittest.py | # -*- coding: utf-8 -*-
# File : unittest.py
# Author : Jiayuan Mao
# Email : maojiayuan@gmail.com
# Date : 27/01/2018
#
# This file is part of Synchronized-BatchNorm-PyTorch.
# https://github.com/vacancy/Synchronized-BatchNorm-PyTorch
# Distributed under MIT License.
import unittest
import numpy as np
from torc... | 834 | 26.833333 | 157 | py |
robust_trust_region | robust_trust_region-main/pytorch-deeplab_v3_plus/modeling/sync_batchnorm/batchnorm.py | # -*- coding: utf-8 -*-
# File : batchnorm.py
# Author : Jiayuan Mao
# Email : maojiayuan@gmail.com
# Date : 27/01/2018
#
# This file is part of Synchronized-BatchNorm-PyTorch.
# https://github.com/vacancy/Synchronized-BatchNorm-PyTorch
# Distributed under MIT License.
import collections
import torch
import torc... | 12,932 | 44.861702 | 116 | py |
robust_trust_region | robust_trust_region-main/pytorch-deeplab_v3_plus/doc/deeplab_resnet.py | import math
import torch
import torch.nn as nn
import torch.nn.functional as F
import torch.utils.model_zoo as model_zoo
from modeling.sync_batchnorm.batchnorm import SynchronizedBatchNorm2d
BatchNorm2d = SynchronizedBatchNorm2d
class Bottleneck(nn.Module):
expansion = 4
def __init__(self, inplanes, planes, ... | 11,247 | 34.594937 | 111 | py |
robust_trust_region | robust_trust_region-main/pytorch-deeplab_v3_plus/doc/deeplab_xception.py | import math
import torch
import torch.nn as nn
import torch.nn.functional as F
import torch.utils.model_zoo as model_zoo
from modeling.sync_batchnorm.batchnorm import SynchronizedBatchNorm2d
BatchNorm2d = SynchronizedBatchNorm2d
class SeparableConv2d(nn.Module):
def __init__(self, inplanes, planes, kernel_size=3,... | 16,199 | 37.117647 | 127 | py |
fat-albert | fat-albert-master/abmn/src/core/model.py | import re
import tensorflow as tf
initializer = "xavier"
def _activation_summary(x):
tensor_name = re.sub('%s_[0-9]*/', x.op.name)
tf.compat.v1.summary.histogram(tensor_name + '/activations', x)
tf.compat.v1.summary.scalar(tensor_name + '/sparsity',
tf.nn.zero_fraction(x))
# Dropou... | 10,768 | 38.16 | 127 | py |
fat-albert | fat-albert-master/bert/setup.py | """
Simple check list from AllenNLP repo: https://github.com/allenai/allennlp/blob/master/setup.py
To create the package for pypi.
1. Change the version in __init__.py, setup.py as well as docs/source/conf.py.
2. Commit these changes with the message: "Release: VERSION"
3. Add a tag in git to mark the release: "git... | 2,923 | 39.054795 | 183 | py |
fat-albert | fat-albert-master/bert/hubconf.py | from transformers import (
AutoTokenizer, AutoConfig, AutoModel, AutoModelWithLMHead, AutoModelForSequenceClassification, AutoModelForQuestionAnswering
)
from transformers.file_utils import add_start_docstrings
dependencies = ['torch', 'tqdm', 'boto3', 'requests', 'regex', 'sentencepiece', 'sacremoses']
@add_star... | 6,489 | 56.433628 | 189 | py |
fat-albert | fat-albert-master/bert/examples/run_lm_finetuning.py | # coding=utf-8
# Copyright 2018 The Google AI Language Team Authors and The HuggingFace Inc. team.
# Copyright (c) 2018, NVIDIA CORPORATION. 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 cop... | 28,924 | 50.929982 | 165 | py |
fat-albert | fat-albert-master/bert/examples/run_squad.py | # coding=utf-8
# Copyright 2018 The Google AI Language Team Authors and The HuggingFace Inc. team.
# Copyright (c) 2018, NVIDIA CORPORATION. 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 cop... | 31,780 | 54.175347 | 151 | py |
fat-albert | fat-albert-master/bert/examples/run_glue.py | # coding=utf-8
# Copyright 2018 The Google AI Language Team Authors and The HuggingFace Inc. team.
# Copyright (c) 2018, NVIDIA CORPORATION. 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 cop... | 28,343 | 52.278195 | 158 | py |
fat-albert | fat-albert-master/bert/examples/benchmarks.py | # coding=utf-8
# Copyright 2018 The HuggingFace Inc. team.
# Copyright (c) 2018, NVIDIA CORPORATION. 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.a... | 23,631 | 48.439331 | 138 | py |
fat-albert | fat-albert-master/bert/examples/run_summarization_finetuning.py | # coding=utf-8
# Copyright 2019 The HuggingFace Inc. team.
# Copyright (c) 2019 The HuggingFace 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.a... | 15,727 | 30.902637 | 120 | py |
fat-albert | fat-albert-master/bert/examples/run_bertology.py | #!/usr/bin/env python3
# Copyright 2018 CMU and The HuggingFace Inc. 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 requir... | 18,901 | 51.798883 | 177 | py |
fat-albert | fat-albert-master/bert/examples/utils_summarization_test.py | # coding=utf-8
# Copyright 2019 HuggingFace Inc.
#
# 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 ag... | 5,178 | 36.80292 | 98 | py |
fat-albert | fat-albert-master/bert/examples/run_generation.py | #!/usr/bin/env python3
# coding=utf-8
# Copyright 2018 Google AI, Google Brain and Carnegie Mellon University Authors and the HuggingFace Inc. team.
# Copyright (c) 2018, NVIDIA CORPORATION. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in c... | 13,112 | 49.241379 | 167 | py |
fat-albert | fat-albert-master/bert/examples/run_ner.py | # coding=utf-8
# Copyright 2018 The Google AI Language Team Authors and The HuggingFace Inc. team.
# Copyright (c) 2018, NVIDIA CORPORATION. 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 cop... | 28,788 | 53.013133 | 184 | py |
fat-albert | fat-albert-master/bert/examples/utils_summarization.py | from collections import deque
import os
import torch
from torch.utils.data import Dataset
# ------------
# Data loading
# ------------
class CNNDailyMailDataset(Dataset):
""" Abstracts the dataset used to train seq2seq models.
CNN/Daily News:
The CNN/Daily News raw datasets are downloaded from [1]. T... | 6,022 | 31.556757 | 88 | py |
fat-albert | fat-albert-master/bert/examples/run_tf_glue.py | import os
import tensorflow as tf
import tensorflow_datasets
from transformers import BertTokenizer, TFBertForSequenceClassification, BertConfig, glue_convert_examples_to_features, BertForSequenceClassification, glue_processors
# script parameters
BATCH_SIZE = 32
EVAL_BATCH_SIZE = BATCH_SIZE * 2
USE_XLA = False
USE_AM... | 3,978 | 41.329787 | 166 | py |
fat-albert | fat-albert-master/bert/examples/run_multiple_choice.py | # coding=utf-8
# Copyright 2018 The Google AI Language Team Authors and The HuggingFace Inc. team.
# Copyright (c) 2018, NVIDIA CORPORATION. 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 cop... | 29,481 | 50.722807 | 168 | py |
fat-albert | fat-albert-master/bert/examples/run_xnli.py | # coding=utf-8
# Copyright 2018 The Google AI Language Team Authors and The HuggingFace Inc. team.
# Copyright (c) 2018, NVIDIA CORPORATION. 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 cop... | 27,117 | 51.554264 | 151 | py |
fat-albert | fat-albert-master/bert/examples/contrib/run_transfo_xl.py | # coding=utf-8
# Copyright 2018 Google AI, Google Brain and Carnegie Mellon University Authors and the HuggingFace Inc. team.
# Copyright (c) 2018, NVIDIA CORPORATION. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the Lice... | 6,742 | 42.785714 | 111 | py |
fat-albert | fat-albert-master/bert/examples/contrib/run_swag.py | # coding=utf-8
# Copyright 2018 The Google AI Language Team Authors and The HuggingFace Inc. team.
# Copyright (c) 2018, NVIDIA CORPORATION. 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 cop... | 31,683 | 45.731563 | 154 | py |
fat-albert | fat-albert-master/bert/examples/contrib/run_movieqa.bak.py | # coding=utf-8
# Copyright 2018 The Google AI Language Team Authors and The HuggingFace Inc. team.
# Copyright (c) 2018, NVIDIA CORPORATION. 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 cop... | 32,036 | 45.701166 | 154 | py |
fat-albert | fat-albert-master/bert/examples/contrib/run_openai_gpt.py | # coding=utf-8
# Copyright 2018 Google AI, Google Brain and Carnegie Mellon University Authors and the HuggingFace Inc. team.
# Copyright (c) 2018, NVIDIA CORPORATION. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the Lice... | 14,471 | 48.731959 | 132 | py |
fat-albert | fat-albert-master/bert/examples/contrib/run_movieqa.py | # coding=utf-8
# Copyright 2018 The Google AI Language Team Authors and The HuggingFace Inc. team.
# Copyright (c) 2018, NVIDIA CORPORATION. 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 cop... | 35,214 | 45.274639 | 154 | py |
fat-albert | fat-albert-master/bert/examples/contrib/run_camembert.py | from pathlib import Path
import tarfile
import urllib.request
import torch
from transformers.tokenization_camembert import CamembertTokenizer
from transformers.modeling_camembert import CamembertForMaskedLM
def fill_mask(masked_input, model, tokenizer, topk=5):
# Adapted from https://github.com/pytorch/fairseq/... | 2,015 | 40.142857 | 114 | py |
fat-albert | fat-albert-master/bert/examples/distillation/grouped_batch_sampler.py | # coding=utf-8
# Copyright 2019-present, the HuggingFace Inc. team and Facebook, Inc.
#
# 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... | 4,368 | 40.216981 | 125 | py |
fat-albert | fat-albert-master/bert/examples/distillation/utils.py | # coding=utf-8
# Copyright 2019-present, the HuggingFace Inc. team and Facebook, Inc.
#
# 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... | 4,308 | 32.146154 | 104 | py |
fat-albert | fat-albert-master/bert/examples/distillation/lm_seqs_dataset.py | # coding=utf-8
# Copyright 2019-present, the HuggingFace Inc. team and Facebook, Inc.
#
# 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... | 5,453 | 34.881579 | 111 | py |
fat-albert | fat-albert-master/bert/examples/distillation/run_squad_w_distillation.py | # coding=utf-8
# Copyright 2018 The Google AI Language Team Authors and The HuggingFace Inc. team.
# Copyright (c) 2018, NVIDIA CORPORATION. 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 cop... | 33,733 | 55.129784 | 151 | py |
fat-albert | fat-albert-master/bert/examples/distillation/train.py | # coding=utf-8
# Copyright 2019-present, the HuggingFace Inc. 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 a... | 13,598 | 45.731959 | 135 | py |
fat-albert | fat-albert-master/bert/examples/distillation/distiller.py | # coding=utf-8
# Copyright 2019-present, the HuggingFace Inc. team and Facebook, Inc.
#
# 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... | 25,933 | 46.848708 | 163 | py |
fat-albert | fat-albert-master/bert/examples/distillation/scripts/extract.py | # coding=utf-8
# Copyright 2019-present, the HuggingFace Inc. 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 a... | 4,326 | 47.077778 | 158 | py |
fat-albert | fat-albert-master/bert/examples/distillation/scripts/extract_distilbert.py | # coding=utf-8
# Copyright 2019-present, the HuggingFace Inc. 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 a... | 4,255 | 50.277108 | 158 | py |
fat-albert | fat-albert-master/bert/templates/adding_a_new_model/modeling_xxx.py | # coding=utf-8
# Copyright 2018 XXX Authors
#
# 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 ... | 34,579 | 51.473445 | 151 | py |
fat-albert | fat-albert-master/bert/templates/adding_a_new_model/convert_xxx_original_tf_checkpoint_to_pytorch.py | # coding=utf-8
# Copyright 2018 The HuggingFace Inc. 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 applicable... | 2,565 | 37.878788 | 100 | py |
fat-albert | fat-albert-master/bert/templates/adding_a_new_model/modeling_tf_xxx.py | # coding=utf-8
# Copyright 2018 The Google AI Language Team Authors and The HuggingFace Inc. team.
# Copyright (c) 2018, NVIDIA CORPORATION. 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 cop... | 27,575 | 53.605941 | 193 | py |
fat-albert | fat-albert-master/bert/templates/adding_a_new_model/tests/modeling_xxx_test.py | # coding=utf-8
# Copyright 2018 XXX Authors.
#
# 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... | 11,628 | 44.425781 | 160 | py |
fat-albert | fat-albert-master/bert/templates/adding_a_new_example_script/run_xxx.py | # coding=utf-8
# Copyright 2018 XXX. 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
#
# Unless required by applicable... | 30,654 | 53.741071 | 151 | py |
fat-albert | fat-albert-master/bert/datasets/SWAG/pytorch_misc.py | """
Miscellaneous functions that might be useful for pytorch
"""
import h5py
import numpy as np
import torch
from torch.autograd import Variable
import os
import dill as pkl
from itertools import tee
from torch import nn
import time
def optimistic_restore(network, state_dict):
mismatch = False
own_state = net... | 15,621 | 29.216634 | 118 | py |
fat-albert | fat-albert-master/bert/datasets/SWAG/swag_baselines/unarylstm/lstm_swag.py | from typing import Dict, List, TextIO, Optional
from overrides import overrides
import torch
from torch.nn.modules import Linear, Dropout
import torch.nn.functional as F
from allennlp.common import Params
from allennlp.common.checks import check_dimensions_match
from allennlp.data import Vocabulary
from allennlp.modu... | 6,737 | 45.791667 | 97 | py |
fat-albert | fat-albert-master/bert/datasets/SWAG/swag_baselines/esim/esim_swag.py | # TODO: projection dropout with ELMO
# l2 reg with ELMO
# multiple ELMO layers
# doc
from typing import Dict, Optional
import torch
from torch.autograd import Variable
from allennlp.common import Params
from allennlp.common.checks import check_dimensions_match
from allennlp.data import Vocabulary
from allennlp... | 13,868 | 45.69697 | 156 | py |
fat-albert | fat-albert-master/bert/datasets/SWAG/swag_baselines/decomposable_attention/decomposable_attention_swag.py | from typing import Dict, Optional
import torch
from allennlp.common import Params
from allennlp.common.checks import check_dimensions_match
from allennlp.data import Vocabulary
from allennlp.models.model import Model
from allennlp.modules import FeedForward, MatrixAttention
from allennlp.modules import Seq2SeqEncoder... | 13,628 | 50.430189 | 164 | py |
fat-albert | fat-albert-master/bert/datasets/SWAG/create_swag/generate_candidates/rebalance_dataset_mlp.py | """
The big idea will be to add in the worst scoring one. But we want to use a MULTILAYER PERCEPTRON.
Also not using word features for now
"""
import matplotlib as mpl
mpl.use('Agg')
import seaborn as sns
import matplotlib.pyplot as plt
from allennlp.data import Vocabulary
from torch.nn import functional as F
from t... | 10,256 | 39.066406 | 138 | py |
fat-albert | fat-albert-master/bert/datasets/SWAG/create_swag/generate_candidates/classifiers.py | """
The big idea will be to add in the worst scoring one. But we want to use a MULTILAYER PERCEPTRON.
Also not using word features for now
"""
import torch
from allennlp.common import Params
from allennlp.modules.augmented_lstm import AugmentedLstm
from allennlp.modules.seq2seq_encoders.pytorch_seq2seq_wrapper import... | 15,626 | 43.019718 | 151 | py |
fat-albert | fat-albert-master/bert/datasets/SWAG/create_swag/generate_candidates/sample_candidates.py | import pickle as pkl
from argparse import ArgumentParser
from copy import deepcopy
from time import time
import numpy as np
import pandas as pd
import torch
from allennlp.commands.predict import Predictor
from allennlp.data import Vocabulary
from allennlp.models.archival import load_archive
from tqdm import tqdm
from... | 8,718 | 40.918269 | 119 | py |
fat-albert | fat-albert-master/bert/datasets/SWAG/create_swag/generate_candidates/rebalance_dataset_ensemble.py | """
The big idea will be to add in the worst scoring one. But we want to use a MULTILAYER PERCEPTRON.
Also not using word features for now
"""
import pickle as pkl
from argparse import ArgumentParser
from copy import deepcopy
import numpy as np
import pandas as pd
import spacy
import torch
from allennlp.data import ... | 13,160 | 44.539792 | 122 | py |
fat-albert | fat-albert-master/bert/datasets/SWAG/create_swag/lm/pretrain_lm.py | import os
import pandas as pd
import torch
from allennlp.data import Instance
from allennlp.data import Token
from allennlp.data import Vocabulary
from allennlp.data.dataset import Batch
from allennlp.data.fields import TextField
from allennlp.data.token_indexers import SingleIdTokenIndexer
from allennlp.data.token_in... | 4,759 | 40.391304 | 118 | py |
fat-albert | fat-albert-master/bert/datasets/SWAG/create_swag/lm/train_lm.py | import os
from argparse import ArgumentParser
import numpy as np
import pandas as pd
import torch
from torch import optim
from torch.optim.lr_scheduler import StepLR
from tqdm import tqdm
from create_swag.lm.config import NUM_FOLDS
from create_swag.lm.load_data import load_lm_data, RawPassages
from create_swag.lm.sim... | 3,709 | 41.159091 | 104 | py |
fat-albert | fat-albert-master/bert/datasets/SWAG/create_swag/lm/simple_bilm.py | """
A wrapper around ai2s elmo LM to allow for an lm objective...
"""
from typing import Optional, Tuple
from typing import Union, List, Dict
import numpy as np
import torch
from allennlp.common.checks import ConfigurationError
from allennlp.data import Token, Vocabulary, Instance
from allennlp.data.dataset import Ba... | 16,902 | 48.568915 | 117 | py |
fat-albert | fat-albert-master/bert/datasets/SWAG/create_swag/lm/load_data.py | # First make the vocabulary, etc.
import os
import pickle as pkl
import random
import simplejson as json
from allennlp.common.util import get_spacy_model
from allennlp.data import Instance
from allennlp.data import Token
from allennlp.data import Vocabulary
from allennlp.data.dataset import Batch
from allennlp.data.f... | 6,285 | 40.629139 | 118 | py |
fat-albert | fat-albert-master/bert/transformers/modeling_encoder_decoder.py | # coding=utf-8
# Copyright 2018 The HuggingFace Inc. 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 applicable... | 15,827 | 49.893891 | 472 | py |
fat-albert | fat-albert-master/bert/transformers/modeling_tf_albert.py | # coding=utf-8
# Copyright 2018 The OpenAI Team Authors and HuggingFace Inc. team.
# Copyright (c) 2018, NVIDIA CORPORATION. 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... | 39,735 | 48.732165 | 193 | py |
fat-albert | fat-albert-master/bert/transformers/optimization.py | # coding=utf-8
# Copyright 2018 The Google AI Language Team Authors and The HuggingFace Inc. 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/LICEN... | 7,658 | 44.052941 | 134 | py |
fat-albert | fat-albert-master/bert/transformers/__main__.py | # coding: utf8
def main():
import sys
if (len(sys.argv) < 4 or len(sys.argv) > 6) or sys.argv[1] not in ["bert", "gpt", "transfo_xl", "gpt2", "xlnet", "xlm"]:
print(
"This command line utility let you convert original (author released) model checkpoint to pytorch.\n"
"It should be used a... | 7,085 | 53.507692 | 135 | py |
fat-albert | fat-albert-master/bert/transformers/configuration_utils.py | # coding=utf-8
# Copyright 2018 The Google AI Language Team Authors and The HuggingFace Inc. team.
# Copyright (c) 2018, NVIDIA CORPORATION. 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 cop... | 11,152 | 51.116822 | 296 | py |
fat-albert | fat-albert-master/bert/transformers/modeling_tf_pytorch_utils.py | # coding=utf-8
# Copyright 2018 The Google AI Language Team Authors and The HuggingFace Inc. team.
# Copyright (c) 2018, NVIDIA CORPORATION. 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 cop... | 12,465 | 41.546075 | 166 | py |
fat-albert | fat-albert-master/bert/transformers/modeling_distilbert.py | # coding=utf-8
# Copyright 2019-present, the HuggingFace Inc. team, The Google AI Language Team and Facebook, Inc.
#
# 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.or... | 39,603 | 49.839538 | 201 | py |
fat-albert | fat-albert-master/bert/transformers/modeling_tf_gpt2.py | # coding=utf-8
# Copyright 2018 The OpenAI Team Authors and HuggingFace Inc. team.
# Copyright (c) 2018, NVIDIA CORPORATION. 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... | 32,228 | 49.834385 | 193 | py |
fat-albert | fat-albert-master/bert/transformers/modeling_tf_transfo_xl.py | # coding=utf-8
# Copyright 2018 Google AI, Google Brain and Carnegie Mellon University Authors and the HuggingFace Inc. team.
# Copyright (c) 2018, NVIDIA CORPORATION. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the Lice... | 36,425 | 45.820051 | 193 | py |
fat-albert | fat-albert-master/bert/transformers/modeling_tf_auto.py | # coding=utf-8
# Copyright 2018 The HuggingFace Inc. 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 applicable... | 37,420 | 70.687739 | 472 | py |
fat-albert | fat-albert-master/bert/transformers/modeling_utils.py | # coding=utf-8
# Copyright 2018 The Google AI Language Team Authors and The HuggingFace Inc. team.
# Copyright (c) 2018, NVIDIA CORPORATION. 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 cop... | 45,511 | 51.798144 | 472 | py |
fat-albert | fat-albert-master/bert/transformers/modeling_tf_openai.py | # coding=utf-8
# Copyright 2018 The OpenAI Team Authors and HuggingFace Inc. team.
# Copyright (c) 2018, NVIDIA CORPORATION. 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... | 30,118 | 49.535235 | 193 | py |
fat-albert | fat-albert-master/bert/transformers/modeling_bert.py | # coding=utf-8
# Copyright 2018 The Google AI Language Team Authors and The HuggingFace Inc. team.
# Copyright (c) 2018, NVIDIA CORPORATION. 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 cop... | 68,217 | 52.212168 | 187 | py |
fat-albert | fat-albert-master/bert/transformers/modeling_gpt2.py | # coding=utf-8
# Copyright 2018 The OpenAI Team Authors and HuggingFace Inc. team.
# Copyright (c) 2018, NVIDIA CORPORATION. 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... | 34,421 | 49.920118 | 148 | py |
fat-albert | fat-albert-master/bert/transformers/convert_albert_original_tf_checkpoint_to_pytorch.py | # coding=utf-8
# Copyright 2018 The HuggingFace Inc. 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 applicable... | 2,597 | 37.776119 | 103 | py |
fat-albert | fat-albert-master/bert/transformers/modeling_openai.py | # coding=utf-8
# Copyright 2018 The OpenAI Team Authors and HuggingFace Inc. team.
# Copyright (c) 2018, NVIDIA CORPORATION. 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... | 31,203 | 48.687898 | 148 | py |
fat-albert | fat-albert-master/bert/transformers/convert_gpt2_original_tf_checkpoint_to_pytorch.py | # coding=utf-8
# Copyright 2018 The HuggingFace Inc. 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 applicable... | 3,074 | 39.460526 | 111 | py |
fat-albert | fat-albert-master/bert/transformers/modeling_tf_roberta.py | # coding=utf-8
# Copyright 2018 The Google AI Language Team Authors and The HuggingFace Inc. team.
# Copyright (c) 2018, NVIDIA CORPORATION. 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 cop... | 22,329 | 51.789598 | 193 | py |
fat-albert | fat-albert-master/bert/transformers/convert_roberta_original_pytorch_checkpoint_to_pytorch.py | # coding=utf-8
# Copyright 2018 The HuggingFace Inc. 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 applicable... | 8,486 | 45.889503 | 188 | py |
fat-albert | fat-albert-master/bert/transformers/tokenization_bert.py | # coding=utf-8
# Copyright 2018 The Google AI Language Team Authors and The HuggingFace Inc. 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/LICEN... | 22,451 | 43.636183 | 183 | py |
fat-albert | fat-albert-master/bert/transformers/convert_transfo_xl_original_tf_checkpoint_to_pytorch.py | # coding=utf-8
# Copyright 2018 The HuggingFace Inc. 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 applicable... | 5,518 | 45.771186 | 121 | py |
fat-albert | fat-albert-master/bert/transformers/configuration_ctrl.py | # coding=utf-8
# Copyright 2018 Salesforce and HuggingFace Inc. team.
# Copyright (c) 2018, NVIDIA CORPORATION. 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
#
# htt... | 5,775 | 39.111111 | 120 | py |
fat-albert | fat-albert-master/bert/transformers/modeling_tf_transfo_xl_utilities.py | # coding=utf-8
# Copyright 2018 Google AI, Google Brain and Carnegie Mellon University Authors and the HuggingFace Inc. team.
# Copyright (c) 2018, NVIDIA CORPORATION. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the Lice... | 8,325 | 46.306818 | 110 | py |
fat-albert | fat-albert-master/bert/transformers/modeling_tf_xlnet.py | # coding=utf-8
# Copyright 2018 Google AI, Google Brain and Carnegie Mellon University Authors and the HuggingFace Inc. team.
# Copyright (c) 2018, NVIDIA CORPORATION. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the Lice... | 57,790 | 50.92363 | 193 | py |
fat-albert | fat-albert-master/bert/transformers/convert_openai_original_tf_checkpoint_to_pytorch.py | # coding=utf-8
# Copyright 2018 The HuggingFace Inc. 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 applicable... | 3,161 | 40.605263 | 118 | py |
fat-albert | fat-albert-master/bert/transformers/modeling_camembert.py | # coding=utf-8
# Copyright 2019 Inria, Facebook AI Research and the HuggingFace Inc. team.
# Copyright (c) 2018, NVIDIA CORPORATION. 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... | 17,760 | 59.411565 | 217 | py |
fat-albert | fat-albert-master/bert/transformers/convert_xlm_original_pytorch_checkpoint_to_pytorch.py | # coding=utf-8
# Copyright 2018 The HuggingFace Inc. 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 applicable... | 3,235 | 37.52381 | 117 | py |
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