repo stringlengths 2 99 | file stringlengths 13 225 | code stringlengths 0 18.3M | file_length int64 0 18.3M | avg_line_length float64 0 1.36M | max_line_length int64 0 4.26M | extension_type stringclasses 1
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VLC-BERT | VLC-BERT-master/external/pytorch_pretrained_bert/optimization_openai.py | # coding=utf-8
# Copyright 2018 The Open AI Team Authors and The HugginFace 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
#
# U... | 5,661 | 39.156028 | 116 | py |
VLC-BERT | VLC-BERT-master/external/pytorch_pretrained_bert/__main__.py | # coding: utf8
def main():
import sys
if (len(sys.argv) != 4 and len(sys.argv) != 5) or sys.argv[1] not in [
"convert_tf_checkpoint_to_pytorch",
"convert_openai_checkpoint",
"convert_transfo_xl_checkpoint",
"convert_gpt2_checkpoint",
]:
print(
"Should be used ... | 4,393 | 51.309524 | 145 | py |
VLC-BERT | VLC-BERT-master/external/pytorch_pretrained_bert/convert_gpt2_checkpoint_to_pytorch.py | # coding=utf-8
# Copyright 2018 The HugginFace 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 ... | 3,046 | 40.739726 | 111 | py |
VLC-BERT | VLC-BERT-master/external/pytorch_pretrained_bert/convert_openai_checkpoint_to_pytorch.py | # coding=utf-8
# Copyright 2018 The HugginFace 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 ... | 3,141 | 42.041096 | 118 | py |
VLC-BERT | VLC-BERT-master/external/pytorch_pretrained_bert/tokenization.py | # coding=utf-8
# Copyright 2018 The Google AI Language Team Authors and The HugginFace 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/LICENS... | 14,453 | 37.854839 | 133 | py |
VLC-BERT | VLC-BERT-master/external/pytorch_pretrained_bert/modeling.py | # coding=utf-8
# Copyright 2018 The Google AI Language Team Authors and The HugginFace 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... | 60,198 | 48.18219 | 139 | py |
VLC-BERT | VLC-BERT-master/external/pytorch_pretrained_bert/modeling_gpt2.py | # coding=utf-8
# Copyright 2018 The OpenAI Team Authors and HugginFace 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 ... | 29,887 | 42.632117 | 146 | py |
VLC-BERT | VLC-BERT-master/external/pytorch_pretrained_bert/modeling_openai.py | # coding=utf-8
# Copyright 2018 The OpenAI Team Authors and HugginFace 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 ... | 37,647 | 45.421702 | 152 | py |
VLC-BERT | VLC-BERT-master/external/pytorch_pretrained_bert/convert_transfo_xl_checkpoint_to_pytorch.py | # coding=utf-8
# Copyright 2018 The HugginFace 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 ... | 5,642 | 47.230769 | 121 | py |
VLC-BERT | VLC-BERT-master/external/pytorch_pretrained_bert/file_utils.py | """
Utilities for working with the local dataset cache.
This file is adapted from the AllenNLP library at https://github.com/allenai/allennlp
Copyright by the AllenNLP authors.
"""
from __future__ import (absolute_import, division, print_function, unicode_literals)
import json
import logging
import os
import shutil
im... | 8,280 | 32.124 | 112 | py |
VLC-BERT | VLC-BERT-master/external/pytorch_pretrained_bert/convert_tf_checkpoint_to_pytorch.py | # coding=utf-8
# Copyright 2018 The HugginFace 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 ... | 2,538 | 39.301587 | 109 | py |
VLC-BERT | VLC-BERT-master/external/pytorch_pretrained_bert/__init__.py | __version__ = "0.6.0"
from .tokenization import BertTokenizer, BasicTokenizer, WordpieceTokenizer
from .tokenization_openai import OpenAIGPTTokenizer
from .tokenization_transfo_xl import (TransfoXLTokenizer, TransfoXLCorpus)
from .tokenization_gpt2 import GPT2Tokenizer
from .modeling import (BertConfig, BertModel, Ber... | 1,286 | 50.48 | 88 | py |
VLC-BERT | VLC-BERT-master/external/pytorch_pretrained_bert/tokenization_gpt2.py | # coding=utf-8
# Copyright 2018 The Open AI Team Authors and The HugginFace 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
#
# U... | 8,544 | 40.280193 | 114 | py |
VLC-BERT | VLC-BERT-master/external/pytorch_pretrained_bert/modeling_transfo_xl.py | # coding=utf-8
# Copyright 2018 Google AI, Google Brain and Carnegie Mellon University Authors and the HugginFace 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 Licen... | 58,702 | 41.476845 | 131 | py |
VLC-BERT | VLC-BERT-master/external/pytorch_pretrained_bert/tokenization_transfo_xl.py | # coding=utf-8
# Copyright 2018 Google AI, Google Brain and Carnegie Mellon University Authors and the HugginFace 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 Licen... | 24,851 | 35.927192 | 109 | py |
VLC-BERT | VLC-BERT-master/external/pytorch_pretrained_bert/tokenization_openai.py | # coding=utf-8
# Copyright 2018 The Open AI Team Authors and The HugginFace 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
#
# U... | 11,338 | 41.950758 | 129 | py |
VLC-BERT | VLC-BERT-master/external/pytorch_pretrained_bert/modeling_transfo_xl_utilities.py | # coding=utf-8
# Copyright 2018 Google AI, Google Brain and Carnegie Mellon University Authors and the HugginFace 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 Licen... | 16,113 | 38.985112 | 132 | py |
VLC-BERT | VLC-BERT-master/common/lr_scheduler.py | # Copyright (c) Facebook, Inc. and its affiliates. All Rights Reserved.
from bisect import bisect_right
import torch
# FIXME ideally this would be achieved with a CombinedLRScheduler,
# separating MultiStepLR with WarmupLR
# but the current LRScheduler design doesn't allow it
class WarmupMultiStepLR(torch.optim.lr_s... | 1,810 | 33.169811 | 80 | py |
VLC-BERT | VLC-BERT-master/common/fast_rcnn.py | import torch
import torch.nn as nn
import torch.nn.functional as F
import torch.utils.model_zoo as model_zoo
from common.backbone.resnet.resnet import *
from common.backbone.resnet.resnet import Bottleneck, BasicBlock
from common.backbone.resnet.resnet import model_urls
from common.lib.roi_pooling.roi_pool import ROI... | 10,223 | 49.117647 | 155 | py |
VLC-BERT | VLC-BERT-master/common/visual_linguistic_bert.py | import torch
import torch.nn as nn
from easydict import EasyDict as edict
from external.pytorch_pretrained_bert.modeling import BertLayerNorm, BertEncoder, BertPooler, ACT2FN, BertOnlyMLMHead
from common.commonsense_fusion import SimpleFusionLayer
# todo: add this to config
NUM_SPECIAL_WORDS = 1000
class BaseModel(n... | 28,112 | 49.56295 | 128 | py |
VLC-BERT | VLC-BERT-master/common/commonsense_fusion.py | import torch.nn as nn
def init_weights(m):
if isinstance(m, nn.Linear):
nn.init.xavier_uniform_(m.weight)
nn.init.uniform_(m.bias)
def prepare_mask(key_mask, query_mask):
len_k = key_mask.size(1)
len_q = query_mask.size(1)
padding_mask1 = query_mask.unsqueeze(1).expand(-1, len_k, -1)... | 2,409 | 35.515152 | 169 | py |
VLC-BERT | VLC-BERT-master/common/module.py | from collections import namedtuple
from typing import Dict
import torch
import torch.nn as nn
import torch.nn.functional as F
class Module(nn.Module):
def __init__(self, config):
super(Module, self).__init__()
self.config = config
def init_weight(self):
raise NotImplementedError()
... | 1,786 | 26.921875 | 65 | py |
VLC-BERT | VLC-BERT-master/common/__init__.py | 0 | 0 | 0 | py | |
VLC-BERT | VLC-BERT-master/common/trainer.py | import os
import time
from collections import namedtuple
import torch
try:
from apex import amp
from apex.amp import _amp_state
except ImportError:
pass
#raise ImportError("Please install apex from https://www.github.com/nvidia/apex if you want to use fp16.")
# Parameter to pass to batch_end_callback
... | 7,611 | 37.251256 | 122 | py |
VLC-BERT | VLC-BERT-master/common/backbone/__init__.py | from .resnet import resnet18, resnet34, resnet50, resnet101, resnet152
| 71 | 35 | 70 | py |
VLC-BERT | VLC-BERT-master/common/backbone/resnet/resnet.py | """
Modified from torchvision, but exposes features from different stages
"""
import torch.nn as nn
import torch.utils.model_zoo as model_zoo
import torch
import warnings
__all__ = ['ResNet', 'resnet18', 'resnet34', 'resnet50', 'resnet101',
'resnet152']
model_urls = {
'resnet18': 'https://download.pyt... | 17,247 | 40.461538 | 135 | py |
VLC-BERT | VLC-BERT-master/common/backbone/resnet/__init__.py | from .resnet import *
| 22 | 10.5 | 21 | py |
VLC-BERT | VLC-BERT-master/common/callbacks/epoch_end_callbacks/checkpoint.py | import torch
class Checkpoint(object):
def __init__(self, prefix, frequent):
super(Checkpoint, self).__init__()
self.prefix = prefix
self.frequent = frequent
def __call__(self, epoch_num, net, optimizer, writer, validation_monitor=None):
checkpoint_dict = dict()
check... | 1,212 | 36.90625 | 83 | py |
VLC-BERT | VLC-BERT-master/common/callbacks/epoch_end_callbacks/validation_monitor.py | import logging
import shutil
class ValidationMonitor(object):
def __init__(self, val_func, val_loader, metrics, host_metric_name='Acc', label_index_in_batch=-1):
super(ValidationMonitor, self).__init__()
self.val_func = val_func
self.val_loader = val_loader
self.metrics = metrics
... | 2,031 | 38.076923 | 124 | py |
VLC-BERT | VLC-BERT-master/common/callbacks/epoch_end_callbacks/__init__.py | 0 | 0 | 0 | py | |
VLC-BERT | VLC-BERT-master/common/callbacks/batch_end_callbacks/speedometer.py | # --------------------------------------------------------
# Deformable Convolutional Networks
# Copyright (c) 2016 by Contributors
# Copyright (c) 2017 Microsoft
# Licensed under The Apache-2.0 License [see LICENSE for details]
# Modified by Yuwen Xiong
# Modified by Dazhi Cheng
# -------------------------------------... | 4,461 | 42.320388 | 146 | py |
VLC-BERT | VLC-BERT-master/common/callbacks/batch_end_callbacks/__init__.py | 0 | 0 | 0 | py | |
VLC-BERT | VLC-BERT-master/common/nlp/misc.py | import torch
import random
def get_align_matrix(aligned_ids, sparse=False, device=None, dtype=torch.float32):
"""
Get aligned matrix for feature alignment in sentence embedding
:param aligned_ids: list, aligned_ids[k] means original index of k-th token
:param sparse: whether to return sparse matrix
... | 2,726 | 30.344828 | 104 | py |
VLC-BERT | VLC-BERT-master/common/nlp/time_distributed.py | """
A wrapper that unrolls the second (time) dimension of a tensor
into the first (batch) dimension, applies some other ``Module``,
and then rolls the time dimension back up.
"""
import torch
class TimeDistributed(torch.nn.Module):
"""
Given an input shaped like ``(batch_size, time_steps, [rest])`` and a ``M... | 2,245 | 42.192308 | 99 | py |
VLC-BERT | VLC-BERT-master/common/nlp/encoder_base.py | from typing import Tuple, Union, Optional, Callable
import torch
from torch.nn.utils.rnn import pack_padded_sequence, PackedSequence
# We have two types here for the state, because storing the state in something
# which is Iterable (like a tuple, below), is helpful for internal manipulation
# - however, the states are... | 18,404 | 52.502907 | 109 | py |
VLC-BERT | VLC-BERT-master/common/nlp/bert_encoder_wrapper.py | import torch
import torch.nn as nn
from external.pytorch_pretrained_bert.modeling import BertEncoder, BertLayerNorm
class BertEncoderWrapper(nn.Module):
def __init__(self, bert_config, input_size, output_all_encoded_layers=False):
super(BertEncoderWrapper, self).__init__()
self.bert_config = bert_... | 3,207 | 49.125 | 112 | py |
VLC-BERT | VLC-BERT-master/common/nlp/__init__.py | 0 | 0 | 0 | py | |
VLC-BERT | VLC-BERT-master/common/nlp/input_variational_dropout.py | import torch
class InputVariationalDropout(torch.nn.Dropout):
"""
Apply the dropout technique in Gal and Ghahramani, "Dropout as a Bayesian Approximation:
Representing Model Uncertainty in Deep Learning" (https://arxiv.org/abs/1506.02142) to a
3D tensor.
This module accepts a 3D tensor of shape ``... | 1,324 | 37.970588 | 98 | py |
VLC-BERT | VLC-BERT-master/common/nlp/roberta/tokenization_roberta.py | # coding=utf-8
# Copyright 2018 The Open AI 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/LICENSE-2.0
#
# ... | 8,303 | 40.313433 | 118 | py |
VLC-BERT | VLC-BERT-master/common/nlp/roberta/utils.py | from __future__ import (absolute_import, division, print_function,
unicode_literals)
import sys
import os
try:
from functools import lru_cache
except ImportError:
# Just a dummy decorator to get the checks to run on python2
# because honestly I don't want to support a byte-level un... | 40,379 | 45.736111 | 380 | py |
VLC-BERT | VLC-BERT-master/common/nlp/roberta/__init__.py | from .tokenization_roberta import RobertaTokenizer
| 51 | 25 | 50 | py |
VLC-BERT | VLC-BERT-master/common/nlp/roberta/modeling_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... | 17,448 | 53.021672 | 134 | py |
VLC-BERT | VLC-BERT-master/common/nlp/bert/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... | 8,653 | 45.031915 | 130 | py |
VLC-BERT | VLC-BERT-master/common/nlp/bert/__init__.py | 0 | 0 | 0 | py | |
VLC-BERT | VLC-BERT-master/common/metrics/eval_metric.py | import torch
import torch.distributed as distributed
class EvalMetric(object):
"""Base class for all evaluation metrics.
.. note::
This is a base class that provides common metric interfaces.
One should not use this class directly, but instead create new metric
classes that extend it.
... | 2,371 | 33.376812 | 80 | py |
VLC-BERT | VLC-BERT-master/common/metrics/vqa_metrics.py | import torch
from .eval_metric import EvalMetric
class LossLogger(EvalMetric):
def __init__(self, output_name, display_name=None,
allreduce=False, num_replicas=1):
self.output_name = output_name
if display_name is None:
display_name = output_name
super(LossLogg... | 1,174 | 31.638889 | 90 | py |
VLC-BERT | VLC-BERT-master/common/metrics/refcoco_metrics.py | import torch
from .eval_metric import EvalMetric
class LossLogger(EvalMetric):
def __init__(self, output_name, display_name=None,
allreduce=False, num_replicas=1):
self.output_name = output_name
if display_name is None:
display_name = output_name
super(LossLogg... | 2,715 | 33.379747 | 98 | py |
VLC-BERT | VLC-BERT-master/common/metrics/pretrain_metrics.py | import torch
from .eval_metric import EvalMetric
class LossLogger(EvalMetric):
def __init__(self, output_name, display_name=None,
allreduce=False, num_replicas=1):
self.output_name = output_name
if display_name is None:
display_name = output_name
super(LossLogg... | 3,263 | 35.266667 | 112 | py |
VLC-BERT | VLC-BERT-master/common/metrics/__init__.py | 0 | 0 | 0 | py | |
VLC-BERT | VLC-BERT-master/common/metrics/composite_eval_metric.py | import numpy as np
from .eval_metric import EvalMetric
import torch
class CompositeEvalMetric(EvalMetric):
"""Manages multiple evaluation metrics.
Args:
metrics (list of EvalMetric): List of child metrics.
name (str): Name of this metric instance for display.
"""
def __init__(self, met... | 2,153 | 29.771429 | 80 | py |
VLC-BERT | VLC-BERT-master/common/metrics/vcr_metrics.py | import torch
from .eval_metric import EvalMetric
class LossLogger(EvalMetric):
def __init__(self, output_name, display_name=None,
allreduce=False, num_replicas=1):
self.output_name = output_name
if display_name is None:
display_name = output_name
super(LossLogg... | 2,953 | 35.02439 | 90 | py |
VLC-BERT | VLC-BERT-master/common/utils/multi_task_dataloader.py | from functools import reduce
import operator
from typing import List
from torch.utils.data import DataLoader
import sys
INT_MAX = sys.maxsize
def prod(iterable):
if len(list(iterable)) > 0:
return reduce(operator.mul, iterable)
else:
return 1
class MultiTaskDataLoader(object):
"""
M... | 1,619 | 26.931034 | 102 | py |
VLC-BERT | VLC-BERT-master/common/utils/build_attn_annot_okvqa.py | import json
import random
import numpy as np
from external.pytorch_pretrained_bert import BertTokenizer
import string
from nltk.corpus import stopwords
#nltk.download('stopwords')
DATASET = 'okvqa'
EXP_NAME = 'semqo'
MAX_COMMONSENSE_LEN = 5
RANDOM_SEED = 12345
random.seed(RANDOM_SEED)
tokenizer = BertTokenizer.from_p... | 4,128 | 28.705036 | 113 | py |
VLC-BERT | VLC-BERT-master/common/utils/misc.py | import os
import numpy as np
import torch
import torch.nn.functional as F
import logging
def block_digonal_matrix(*blocks):
"""
Construct block diagonal matrix
:param blocks: blocks of block diagonal matrix
:param device
:param dtype
:return: block diagonal matrix
"""
assert len(blocks... | 5,958 | 36.71519 | 124 | py |
VLC-BERT | VLC-BERT-master/common/utils/flatten.py | import torch
class Flattener(torch.nn.Module):
def __init__(self):
"""
Flattens last 3 dimensions to make it only batch size, -1
"""
super(Flattener, self).__init__()
def forward(self, x):
return x.view(x.size(0), -1)
| 269 | 19.769231 | 65 | py |
VLC-BERT | VLC-BERT-master/common/utils/bbox.py | import torch
def nonlinear_transform(ex_rois, gt_rois):
"""
compute bounding box regression targets from ex_rois to gt_rois
:param ex_rois: [k, 4] ([x1, y1, x2, y2])
:param gt_rois: [k, 4] (corresponding gt_boxes [x1, y1, x2, y2] )
:return: bbox_targets: [k, 4]
"""
assert ex_rois.shape[0] ... | 3,289 | 33.631579 | 113 | py |
VLC-BERT | VLC-BERT-master/common/utils/create_logger.py | # --------------------------------------------------------
# Deformable Convolutional Networks
# Copyright (c) 2017 Microsoft
# Licensed under The Apache-2.0 License [see LICENSE for details]
# Written by Bin Xiao
# --------------------------------------------------------
import os
import logging
import time
import er... | 1,639 | 31.156863 | 89 | py |
VLC-BERT | VLC-BERT-master/common/utils/load.py | import torch
import os
def smart_load_model_state_dict(model, state_dict):
parsed_state_dict = {}
for k, v in state_dict.items():
if k not in model.state_dict():
if k.startswith('module.'):
k = k[len('module.'):]
else:
k = 'module.' + k
i... | 4,708 | 47.546392 | 104 | py |
VLC-BERT | VLC-BERT-master/common/utils/__init__.py | 0 | 0 | 0 | py | |
VLC-BERT | VLC-BERT-master/common/utils/build_sbert_emb.py | from sentence_transformers import SentenceTransformer
import json
import pickle5 as pickle
import os
from tqdm import tqdm
DATASET = 'aokvqa'
EXP_NAME = 'semqo'
MAX_COMMONSENSE_LEN = 5
BASE_SAVE_PATH = 'data/coco'
USE_QUESTION = True
def filename(exp_name):
return (exp_name[:-1]+ "." + exp_name[-1]).lower()
def... | 5,182 | 40.464 | 123 | py |
VLC-BERT | VLC-BERT-master/common/utils/zipreader.py | import zipfile
import os
import io
import time
from PIL import Image
class ZipReader(object):
zip_bank = dict()
def __init__(self):
super(ZipReader, self).__init__()
@staticmethod
def get_zipfile(path):
zip_bank = ZipReader.zip_bank
if path in zip_bank:
return zip... | 2,772 | 31.244186 | 121 | py |
VLC-BERT | VLC-BERT-master/common/utils/masked_softmax.py | import torch
def masked_softmax(vector: torch.Tensor, mask: torch.Tensor, dim: int = -1) -> torch.Tensor:
"""
``torch.nn.functional.softmax(vector)`` does not work if some elements of ``vector`` should be
masked. This performs a softmax on just the non-masked portions of ``vector``. Passing
``None``... | 1,533 | 50.133333 | 111 | py |
VLC-BERT | VLC-BERT-master/common/utils/pad_sequence.py | import torch
def pad_sequence(sequence, lengths):
"""
:param sequence: [\sum b, .....] sequence
:param lengths: [b1, b2, b3...] that sum to \sum b
:return: [len(lengths), maxlen(b), .....] tensor
"""
output = sequence.new_zeros(len(lengths), max(lengths), *sequence.shape[1:])
start = 0
... | 480 | 25.722222 | 80 | py |
VLC-BERT | VLC-BERT-master/common/utils/build_attn_annot_aokvqa.py | import json
import random
import numpy as np
from external.pytorch_pretrained_bert import BertTokenizer
import string
from nltk.corpus import stopwords
#nltk.download('stopwords')
DATASET = 'aokvqa'
EXP_NAME = 'semqo'
MAX_COMMONSENSE_LEN = 5
RANDOM_SEED = 12345
random.seed(RANDOM_SEED)
tokenizer = BertTokenizer.from_... | 3,554 | 28.139344 | 115 | py |
VLC-BERT | VLC-BERT-master/common/utils/clip_pad.py | import torch
def clip_pad_images(tensor, pad_shape, pad=0):
"""
Clip clip_pad_images of the pad area.
:param tensor: [c, H, W]
:param pad_shape: [h, w]
:return: [c, h, w]
"""
if not isinstance(tensor, torch.Tensor):
tensor = torch.as_tensor(tensor)
H, W = tensor.shape[1:]
h... | 1,738 | 28.982759 | 93 | py |
VLC-BERT | VLC-BERT-master/common/utils/mask.py | from skimage.draw import polygon
import torch
def generate_instance_mask(seg_polys, box, mask_size=(14, 14), dtype=torch.float32, copy=True):
"""
Generate instance mask from polygon
:param seg_poly: torch.Tensor, (N, 2), (x, y) coordinate of N vertices of segmented foreground polygon
:param box: array... | 1,282 | 33.675676 | 106 | py |
VLC-BERT | VLC-BERT-master/common/lib/roi_pooling/roi_pool.py | # Copyright (c) Facebook, Inc. and its affiliates. All Rights Reserved.
import torch
from torch import nn
from torch.autograd import Function
from torch.autograd.function import once_differentiable
from torch.nn.modules.utils import _pair
from . import C_ROIPooling
class _ROIPool(Function):
@staticmethod
def... | 2,174 | 28.794521 | 90 | py |
VLC-BERT | VLC-BERT-master/common/lib/roi_pooling/roi_align.py | # Copyright (c) Facebook, Inc. and its affiliates. All Rights Reserved.
import torch
from torch import nn
from torch.autograd import Function
from torch.autograd.function import once_differentiable
from torch.nn.modules.utils import _pair
from . import C_ROIPooling
class _ROIAlign(Function):
@staticmethod
de... | 2,468 | 30.253165 | 98 | py |
VLC-BERT | VLC-BERT-master/common/lib/roi_pooling/setup.py | # Copyright (c) Facebook, Inc. and its affiliates. All Rights Reserved.
#!/usr/bin/env python
import glob
import os
import torch
from setuptools import find_packages
from setuptools import setup
from torch.utils.cpp_extension import CUDA_HOME
from torch.utils.cpp_extension import CppExtension
from torch.utils.cpp_ext... | 1,799 | 26.272727 | 73 | py |
VLC-BERT | VLC-BERT-master/common/lib/roi_pooling/__init__.py | from .roi_align import ROIAlign
from .roi_pool import ROIPool | 61 | 30 | 31 | py |
VLC-BERT | VLC-BERT-master/common/lib/roi_pooling/debug.py | import torch
from roi_pool import ROIPool
from roi_align import ROIAlign
align = ROIAlign(output_size=(3, 3), spatial_scale=1.0, sampling_ratio=1)
pool = ROIPool(output_size=(3, 3), spatial_scale=1.0)
device = torch.device("cuda:0")
feature = torch.arange(81*2*3).view((2,3,9,9)).float().to(device)
rois = torch.Tenso... | 463 | 24.777778 | 73 | py |
VLC-BERT | VLC-BERT-master/viz/_init_paths.py | import os
import sys
this_dir = os.path.abspath(os.path.dirname(__file__))
def add_path(path):
if path not in sys.path:
sys.path.insert(0, path)
root_path = os.path.join(this_dir, '../')
add_path(root_path)
| 224 | 15.071429 | 53 | py |
VLC-BERT | VLC-BERT-master/viz/bertviz/model_view.py | # coding=utf-8
# Copyright 2018 The Tensor2Tensor 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... | 2,180 | 33.078125 | 102 | py |
VLC-BERT | VLC-BERT-master/viz/bertviz/__init__.py | 0 | 0 | 0 | py | |
VLC-BERT | VLC-BERT-master/viz/bertviz/attention.py | import torch
from collections import defaultdict
def get_attention(model, model_type, tokenizer, sentence_a, sentence_b=None, include_queries_and_keys=False):
"""Compute representation of attention to pass to the d3 visualization
Args:
model: pytorch-transformers model
model_type: type of mo... | 8,283 | 43.778378 | 185 | py |
VLC-BERT | VLC-BERT-master/scripts/launch.py | r"""
`torch.distributed.launch` is a module that spawns up multiple distributed
training processes on each of the training nodes.
The utility can be used for single-node distributed training, in which one or
more processes per node will be spawned. The utility can be used for either
CPU training or GPU training. If the... | 9,500 | 46.268657 | 95 | py |
VLC-BERT | VLC-BERT-master/okvqa/test.py | import _init_paths
import os
import argparse
from copy import deepcopy
from okvqa.function.config import config, update_config
from okvqa.function.test import test_net
def parse_args():
parser = argparse.ArgumentParser('Get Test Result of OK-VQA Network')
parser.add_argument('--cfg', type=str, help='path to ... | 1,531 | 32.304348 | 108 | py |
VLC-BERT | VLC-BERT-master/okvqa/_init_paths.py | import os
import sys
this_dir = os.path.abspath(os.path.dirname(__file__))
def add_path(path):
if path not in sys.path:
sys.path.insert(0, path)
root_path = os.path.join(this_dir, '../')
add_path(root_path)
| 224 | 15.071429 | 53 | py |
VLC-BERT | VLC-BERT-master/okvqa/train_end2end.py | import _init_paths
import os
import argparse
import torch
import subprocess
import json
from okvqa.function.config import config, update_config
from okvqa.function.train import train_net
from okvqa.function.test import test_net
from external.PythonEvaluationTools.okvqa_vqaEval import run_eval
def parse_args():
p... | 3,058 | 33.370787 | 113 | py |
VLC-BERT | VLC-BERT-master/okvqa/function/val.py | from collections import namedtuple
import torch
from common.trainer import to_cuda
@torch.no_grad()
def do_validation(net, val_loader, metrics, label_index_in_batch):
net.eval()
metrics.reset()
for nbatch, batch in enumerate(val_loader):
batch = to_cuda(batch)
label = batch[label_index_in_... | 528 | 26.842105 | 95 | py |
VLC-BERT | VLC-BERT-master/okvqa/function/test.py | import os
import pprint
import shutil
import json
from tqdm import tqdm, trange
import numpy as np
import torch
import torch.nn.functional as F
from common.utils.load import smart_load_model_state_dict
from common.trainer import to_cuda
from common.utils.create_logger import create_logger
from okvqa.data.build import... | 3,523 | 40.458824 | 162 | py |
VLC-BERT | VLC-BERT-master/okvqa/function/config.py | from easydict import EasyDict as edict
import yaml
_C = edict()
config = _C
# ------------------------------------------------------------------------------------- #
# Common options
# ------------------------------------------------------------------------------------- #
_C.RNG_SEED = -1
_C.OUTPUT_PATH = ''
_C.MODUL... | 7,737 | 36.201923 | 108 | py |
VLC-BERT | VLC-BERT-master/okvqa/function/__init__.py | 0 | 0 | 0 | py | |
VLC-BERT | VLC-BERT-master/okvqa/function/train.py | import os
import pprint
import shutil
import inspect
from tensorboardX import SummaryWriter
import numpy as np
import torch
import torch.nn
import torch.optim as optim
import torch.distributed as distributed
from torch.nn.parallel import DistributedDataParallel as DDP
from common.utils.create_logger import create_log... | 17,597 | 51.219585 | 147 | py |
VLC-BERT | VLC-BERT-master/okvqa/modules/resnet_vlbert_for_okvqa.py | import os
import torch
import torch.nn as nn
import torch.nn.functional as F
from external.pytorch_pretrained_bert import BertTokenizer
from external.pytorch_pretrained_bert.modeling import BertPredictionHeadTransform
from common.module import Module
from common.fast_rcnn import FastRCNN
from common.visual_linguistic_b... | 22,549 | 50.601831 | 156 | py |
VLC-BERT | VLC-BERT-master/okvqa/modules/__init__.py | from .resnet_vlbert_for_okvqa import ResNetVLBERT
| 52 | 12.25 | 49 | py |
VLC-BERT | VLC-BERT-master/okvqa/data/__init__.py | 0 | 0 | 0 | py | |
VLC-BERT | VLC-BERT-master/okvqa/data/collate_batch.py | import torch
from common.utils.clip_pad import *
class BatchCollator(object):
def __init__(self, dataset, append_ind=False):
self.dataset = dataset
self.test_mode = self.dataset.test_mode
self.data_names = self.dataset.data_names
self.append_ind = append_ind
def __call__(self,... | 2,295 | 37.266667 | 115 | py |
VLC-BERT | VLC-BERT-master/okvqa/data/build.py | import torch.utils.data
from .datasets import *
from . import samplers
from .transforms.build import build_transforms
from .collate_batch import BatchCollator
import pprint
DATASET_CATALOGS = {'okvqa': OKVQA}
def build_dataset(dataset_name, *args, **kwargs):
assert dataset_name in DATASET_CATALOGS, "dataset not... | 4,750 | 44.247619 | 106 | py |
VLC-BERT | VLC-BERT-master/okvqa/data/datasets/okvqa.py | import os
import json
import _pickle as cPickle
from PIL import Image
import re
import base64
import numpy as np
import csv
import sys
import time
import logging
import pickle5 as pickle
import torch
from torch.utils.data import Dataset
from external.pytorch_pretrained_bert import BertTokenizer
from common.utils.zipr... | 22,450 | 42.935421 | 171 | py |
VLC-BERT | VLC-BERT-master/okvqa/data/datasets/__init__.py | from .okvqa import OKVQA
| 26 | 8 | 24 | py |
VLC-BERT | VLC-BERT-master/okvqa/data/samplers/grouped_batch_sampler.py | # Copyright (c) Facebook, Inc. and its affiliates. All Rights Reserved.
import itertools
import torch
from torch.utils.data.sampler import BatchSampler
from torch.utils.data.sampler import Sampler
class GroupedBatchSampler(BatchSampler):
"""
Wraps another sampler to yield a mini-batch of indices.
It enfo... | 4,846 | 40.42735 | 88 | py |
VLC-BERT | VLC-BERT-master/okvqa/data/samplers/distributed.py | # Copyright (c) Facebook, Inc. and its affiliates. All Rights Reserved.
# Code is copy-pasted exactly as in torch.utils.data.distributed.
# FIXME remove this once c10d fixes the bug it has
import math
import torch
import torch.distributed as dist
from torch.utils.data.sampler import Sampler
class DistributedSampler(S... | 2,568 | 37.924242 | 86 | py |
VLC-BERT | VLC-BERT-master/okvqa/data/samplers/__init__.py | from .distributed import DistributedSampler
from .grouped_batch_sampler import GroupedBatchSampler
| 100 | 24.25 | 54 | py |
VLC-BERT | VLC-BERT-master/okvqa/data/transforms/__init__.py | from .transforms import Compose
from .transforms import Resize
from .transforms import RandomHorizontalFlip
from .transforms import ToTensor
from .transforms import Normalize
from .build import build_transforms
| 212 | 25.625 | 44 | py |
VLC-BERT | VLC-BERT-master/okvqa/data/transforms/build.py | from . import transforms as T
def build_transforms(cfg, mode='train'):
assert mode in ['train', 'test', 'val']
min_size = cfg.SCALES[0]
max_size = cfg.SCALES[1]
assert min_size <= max_size
if mode == 'train':
flip_prob = cfg.TRAIN.FLIP_PROB
elif mode == 'test':
flip_prob = cfg... | 1,034 | 23.069767 | 85 | py |
VLC-BERT | VLC-BERT-master/okvqa/data/transforms/transforms.py | import random
import numpy as np
import torch
import torchvision
from torchvision.transforms import functional as F
class Compose(object):
def __init__(self, transforms):
self.transforms = transforms
def __call__(self, image, boxes, masks, im_info, flipped):
for t in self.transforms:
... | 4,104 | 30.821705 | 97 | py |
VLC-BERT | VLC-BERT-master/data/conceptual-captions/utils/gen_val_image_json.py | captions = []
urls = []
with open('Validation_GCC-1.1.0-Validation.tsv') as fp:
for cnt, line in enumerate(fp):
s = line.split('\t')
captions.append(s[0].split(' '))
urls.append(s[1][:-1])
valids = set([])
with open('val_valid.txt') as fp:
for cnt, line in enumerate(fp):
... | 1,047 | 32.806452 | 121 | py |
VLC-BERT | VLC-BERT-master/data/conceptual-captions/utils/gen_train_image_json.py | captions = []
urls = []
with open('Train_GCC-training.tsv') as fp:
for cnt, line in enumerate(fp):
s = line.split('\t')
captions.append(s[0].split(' '))
urls.append(s[1][:-1])
valids = set([])
with open('train_valid.txt') as fp:
for cnt, line in enumerate(fp):
valids.ad... | 1,059 | 32.125 | 125 | py |
VLC-BERT | VLC-BERT-master/data/conceptual-captions/utils/gen_train4download.py | import os
captions = []
urls = []
with open('Train_GCC-training.tsv') as fp:
for cnt, line in enumerate(fp):
s = line.split('\t')
captions.append(s[0].split(' '))
urls.append(s[1][:-1])
with open('train4download.txt', 'w') as fp:
for cnt, url in enumerate(urls):
fp.wri... | 454 | 25.764706 | 72 | py |
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