python_code stringlengths 0 992k | repo_name stringlengths 8 46 | file_path stringlengths 5 162 |
|---|---|---|
from vlmo.datasets import WikibkDataset
from .datamodule_base import BaseDataModule
class WikibkDataModule(BaseDataModule):
def __init__(self, *args, **kwargs):
super().__init__(*args, **kwargs)
@property
def dataset_cls(self):
return WikibkDataset
@property
def dataset_name(self... | EXA-1-master | exa/models/unilm-master/vlmo/vlmo/datamodules/wikibk_datamodule.py |
from vlmo.datasets import CocoCaptionKarpathyDataset
from .datamodule_base import BaseDataModule
class CocoCaptionKarpathyDataModule(BaseDataModule):
def __init__(self, *args, **kwargs):
super().__init__(*args, **kwargs)
@property
def dataset_cls(self):
return CocoCaptionKarpathyDataset
... | EXA-1-master | exa/models/unilm-master/vlmo/vlmo/datamodules/coco_caption_karpathy_datamodule.py |
from vlmo.datasets import F30KCaptionKarpathyDataset
from .datamodule_base import BaseDataModule
class F30KCaptionKarpathyDataModule(BaseDataModule):
def __init__(self, *args, **kwargs):
super().__init__(*args, **kwargs)
@property
def dataset_cls(self):
return F30KCaptionKarpathyDataset
... | EXA-1-master | exa/models/unilm-master/vlmo/vlmo/datamodules/f30k_caption_karpathy_datamodule.py |
import json
import pandas as pd
import pyarrow as pa
import os
from tqdm import tqdm
from collections import defaultdict
def process(root, iden, row):
texts = [r["sentence"] for r in row]
labels = [r["label"] for r in row]
split = iden.split("-")[0]
if iden.startswith("train"):
directory = ... | EXA-1-master | exa/models/unilm-master/vlmo/vlmo/utils/write_nlvr2.py |
import json
import pandas as pd
import pyarrow as pa
import gc
import random
import os
from tqdm import tqdm
from glob import glob
def path2rest(line):
return [
"None",
[line],
"wikibk",
"train",
]
def make_arrow(root, dataset_root):
for index in range(0, 50):
fi... | EXA-1-master | exa/models/unilm-master/vlmo/vlmo/utils/write_wikibk.py |
import json
import pandas as pd
import pyarrow as pa
import random
import os
from tqdm import tqdm
from glob import glob
from collections import defaultdict
def path2rest(path, iid2captions):
name = path.split("/")[-1]
iid = int(name[:-4])
with open(path, "rb") as fp:
binary = fp.read()
cdi... | EXA-1-master | exa/models/unilm-master/vlmo/vlmo/utils/write_vg.py |
import json
import pandas as pd
import pyarrow as pa
import random
import os
from tqdm import tqdm
from glob import glob
from collections import defaultdict
def path2rest(path, iid2captions, iid2split):
name = path.split("/")[-1]
with open(path, "rb") as fp:
binary = fp.read()
captions = iid2ca... | EXA-1-master | exa/models/unilm-master/vlmo/vlmo/utils/write_f30k_karpathy.py |
import json
import os
import pandas as pd
import pyarrow as pa
import random
from tqdm import tqdm
from glob import glob
from collections import defaultdict
def path2rest(path, iid2captions, iid2split):
name = path.split("/")[-1]
with open(path, "rb") as fp:
binary = fp.read()
captions = iid2capt... | EXA-1-master | exa/models/unilm-master/vlmo/vlmo/utils/write_coco_karpathy.py |
import json
import pandas as pd
import pyarrow as pa
import gc
import random
import os
from tqdm import tqdm
from glob import glob
def path2rest(path, iid2captions):
split, _, name = path.split("/")[-3:]
split = split.split("_")[-1]
iid = name
with open(path, "rb") as fp:
binary = fp.read()
... | EXA-1-master | exa/models/unilm-master/vlmo/vlmo/utils/write_conceptual_caption.py |
import json
import pandas as pd
import pyarrow as pa
import random
import os
from tqdm import tqdm
from glob import glob
from collections import defaultdict, Counter
from .glossary import normalize_word
def get_score(occurences):
if occurences == 0:
return 0.0
elif occurences == 1:
return 0.3... | EXA-1-master | exa/models/unilm-master/vlmo/vlmo/utils/write_vqa.py |
import json
import pandas as pd
import pyarrow as pa
import gc
import random
import os
from tqdm import tqdm
from glob import glob
def path2rest(path, iid2captions):
split, _, name = path.split("/")[-3:]
split = split.split("_")[-1]
iid = name
with open(path, "rb") as fp:
binary = fp.read()
... | EXA-1-master | exa/models/unilm-master/vlmo/vlmo/utils/write_sbu.py |
import re
contractions = {
"aint": "ain't",
"arent": "aren't",
"cant": "can't",
"couldve": "could've",
"couldnt": "couldn't",
"couldn'tve": "couldn't've",
"couldnt've": "couldn't've",
"didnt": "didn't",
"doesnt": "doesn't",
"dont": "don't",
"hadnt": "hadn't",
"hadnt've":... | EXA-1-master | exa/models/unilm-master/vlmo/vlmo/utils/glossary.py |
from .utils import (
inception_normalize,
MinMaxResize,
)
from torchvision import transforms
from .randaug import RandAugment
def pixelbert_transform(size=800):
longer = int((1333 / 800) * size)
return transforms.Compose(
[
MinMaxResize(shorter=size, longer=longer),
tra... | EXA-1-master | exa/models/unilm-master/vlmo/vlmo/transforms/pixelbert.py |
from .pixelbert import (
pixelbert_transform,
pixelbert_transform_randaug,
)
from .square_transform import (
square_transform,
square_transform_randaug,
)
_transforms = {
"pixelbert": pixelbert_transform,
"pixelbert_randaug": pixelbert_transform_randaug,
"square_transform": square_transform... | EXA-1-master | exa/models/unilm-master/vlmo/vlmo/transforms/__init__.py |
# code in this file is adpated from rpmcruz/autoaugment
# https://github.com/rpmcruz/autoaugment/blob/master/transformations.py
import random
import PIL, PIL.ImageOps, PIL.ImageEnhance, PIL.ImageDraw
import numpy as np
import torch
from PIL import Image
def ShearX(img, v): # [-0.3, 0.3]
assert -0.3 <= v <= 0.3
... | EXA-1-master | exa/models/unilm-master/vlmo/vlmo/transforms/randaug.py |
from torchvision import transforms
from PIL import Image
class MinMaxResize:
def __init__(self, shorter=800, longer=1333):
self.min = shorter
self.max = longer
def __call__(self, x):
w, h = x.size
scale = self.min / min(w, h)
if h < w:
newh, neww = self.min... | EXA-1-master | exa/models/unilm-master/vlmo/vlmo/transforms/utils.py |
import cv2
import numpy as np
## aug functions
def identity_func(img):
return img
def autocontrast_func(img, cutoff=0):
'''
same output as PIL.ImageOps.autocontrast
'''
n_bins = 256
def tune_channel(ch):
n = ch.size
cut = cutoff * n // 100
if cut == 0:
... | EXA-1-master | exa/models/unilm-master/vlmo/vlmo/transforms/randaugment.py |
# code in this file is adpated from the ALBEF repo (https://github.com/salesforce/ALBEF)
from .utils import (
inception_normalize,
)
from torchvision import transforms
from .randaugment import RandomAugment
from PIL import Image
def square_transform(size=224):
return transforms.Compose(
[
... | EXA-1-master | exa/models/unilm-master/vlmo/vlmo/transforms/square_transform.py |
from .vlmo_module import VLMo
| EXA-1-master | exa/models/unilm-master/vlmo/vlmo/modules/__init__.py |
import os
import torch
import torch.nn as nn
import torch.nn.functional as F
import pytorch_lightning as pl
import numpy as np
import vlmo.modules.multiway_transformer
from transformers.models.bert.modeling_bert import BertConfig, BertEmbeddings
from vlmo.modules import heads, objectives, vlmo_utils
from pytorch_light... | EXA-1-master | exa/models/unilm-master/vlmo/vlmo/modules/vlmo_module.py |
import torch
import random
import json
from transformers.optimization import AdamW
from transformers import (
get_polynomial_decay_schedule_with_warmup,
get_cosine_schedule_with_warmup,
)
from vlmo.modules.dist_utils import all_gather
from vlmo.modules.objectives import compute_irtr_recall, compute_irtr_recall... | EXA-1-master | exa/models/unilm-master/vlmo/vlmo/modules/vlmo_utils.py |
import torch
import torch.nn as nn
import torch.nn.functional as F
import os
import glob
import json
import tqdm
import functools
import torch.distributed as dist
from torch.utils.data.distributed import DistributedSampler
from einops import rearrange
from pytorch_lightning.utilities.distributed import rank_zero_info
... | EXA-1-master | exa/models/unilm-master/vlmo/vlmo/modules/objectives.py |
""" Vision Transformer (ViT) in PyTorch
A PyTorch implement of Vision Transformers as described in
'An Image Is Worth 16 x 16 Words: Transformers for Image Recognition at Scale' - https://arxiv.org/abs/2010.11929
The official jax code is released and available at https://github.com/google-research/vision_transformer
... | EXA-1-master | exa/models/unilm-master/vlmo/vlmo/modules/multiway_transformer.py |
# Copyright (c) Facebook, Inc. and its affiliates. All Rights Reserved
"""
This file contains primitives for multi-gpu communication.
This is useful when doing distributed training.
"""
import functools
import logging
import numpy as np
import pickle
import torch
import torch.distributed as dist
import torch
_LOCAL_... | EXA-1-master | exa/models/unilm-master/vlmo/vlmo/modules/dist_utils.py |
import torch
import torch.nn as nn
import torch.nn.functional as F
from transformers.models.bert.modeling_bert import BertPredictionHeadTransform
class Pooler(nn.Module):
def __init__(self, hidden_size):
super().__init__()
self.dense = nn.Linear(hidden_size, hidden_size)
self.activation =... | EXA-1-master | exa/models/unilm-master/vlmo/vlmo/modules/heads.py |
EXA-1-master | exa/models/unilm-master/vlmo/vlmo/gadgets/__init__.py | |
import torch
from torchmetrics import Metric
class Accuracy(Metric):
def __init__(self, dist_sync_on_step=False):
super().__init__(dist_sync_on_step=dist_sync_on_step)
self.add_state("correct", default=torch.tensor(0.0), dist_reduce_fx="sum")
self.add_state("total", default=torch.tensor(0.... | EXA-1-master | exa/models/unilm-master/vlmo/vlmo/gadgets/my_metrics.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... | EXA-1-master | exa/models/unilm-master/minilm/examples/run_xnli.py |
# --------------------------------------------------------
# WavLM: Large-Scale Self-Supervised Pre-training for Full Stack Speech Processing (https://arxiv.org/abs/2110.13900.pdf)
# Github source: https://github.com/microsoft/unilm/tree/master/wavlm
# Copyright (c) 2021 Microsoft
# Licensed under The MIT License [se... | EXA-1-master | exa/models/unilm-master/wavlm/modules.py |
# --------------------------------------------------------
# WavLM: Large-Scale Self-Supervised Pre-training for Full Stack Speech Processing (https://arxiv.org/abs/2110.13900.pdf)
# Github source: https://github.com/microsoft/unilm/tree/master/wavlm
# Copyright (c) 2021 Microsoft
# Licensed under The MIT License [se... | EXA-1-master | exa/models/unilm-master/wavlm/WavLM.py |
import argparse
import os
import torch
from fairseq.data import (FairseqDataset, PrependTokenDataset,
TokenBlockDataset, TruncateDataset, data_utils, StripTokenDataset, ConcatDataset)
from fairseq.data.indexed_dataset import make_builder
from tqdm import tqdm
from transformers import AutoToke... | EXA-1-master | exa/models/unilm-master/infoxlm/tools/para2bin.py |
import argparse
import os
import torch
from fairseq.data import (FairseqDataset, PrependTokenDataset,
TokenBlockDataset, TruncateDataset, data_utils, StripTokenDataset, ConcatDataset, PrependTokenDataset, AppendTokenDataset)
from fairseq.data.indexed_dataset import make_builder
from tqdm impo... | EXA-1-master | exa/models/unilm-master/infoxlm/tools/para2bin4xlco.py |
import argparse
import os
import torch
from fairseq.data import (FairseqDataset, PrependTokenDataset,
TokenBlockDataset, TruncateDataset, data_utils)
from fairseq.data.indexed_dataset import make_builder
from tqdm import tqdm
from transformers import AutoTokenizer
class IndexDataset(Fairseq... | EXA-1-master | exa/models/unilm-master/infoxlm/tools/txt2bin.py |
#!/usr/bin/env python3
# Copyright (c) Facebook, Inc. and its affiliates.
#
# This source code is licensed under the MIT license found in the
# LICENSE file in the root directory of this source tree.
"""
Data pre-processing: build vocabularies and binarize training data.
"""
from collections import Counter
from iterto... | EXA-1-master | exa/models/unilm-master/infoxlm/fairseq/preprocess.py |
#!/usr/bin/env python3 -u
# Copyright (c) Facebook, Inc. and its affiliates.
#
# This source code is licensed under the MIT license found in the
# LICENSE file in the root directory of this source tree.
"""
Translate pre-processed data with a trained model.
"""
import torch
from fairseq import bleu, checkpoint_utils,... | EXA-1-master | exa/models/unilm-master/infoxlm/fairseq/generate.py |
#!/usr/bin/env python3 -u
#!/usr/bin/env python3 -u
# Copyright (c) Facebook, Inc. and its affiliates.
#
# This source code is licensed under the MIT license found in the
# LICENSE file in the root directory of this source tree.
import torch
from fairseq import checkpoint_utils, options, progress_bar, utils
def mai... | EXA-1-master | exa/models/unilm-master/infoxlm/fairseq/validate.py |
#!/usr/bin/env python3
# Copyright (c) Facebook, Inc. and its affiliates.
#
# This source code is licensed under the MIT license found in the
# LICENSE file in the root directory of this source tree.
import os
from setuptools import setup, find_packages, Extension
import sys
if sys.version_info < (3, 5):
sys.exi... | EXA-1-master | exa/models/unilm-master/infoxlm/fairseq/setup.py |
#!/usr/bin/env python3 -u
# Copyright (c) Facebook, Inc. and its affiliates.
#
# This source code is licensed under the MIT license found in the
# LICENSE file in the root directory of this source tree.
"""
Translate raw text with a trained model. Batches data on-the-fly.
"""
from collections import namedtuple
import ... | EXA-1-master | exa/models/unilm-master/infoxlm/fairseq/interactive.py |
#!/usr/bin/env python3 -u
# Copyright (c) Facebook, Inc. and its affiliates.
#
# This source code is licensed under the MIT license found in the
# LICENSE file in the root directory of this source tree.
"""
Train a new model on one or across multiple GPUs.
"""
import collections
import math
import random
import numpy... | EXA-1-master | exa/models/unilm-master/infoxlm/fairseq/train.py |
# Copyright (c) Facebook, Inc. and its affiliates.
#
# This source code is licensed under the MIT license found in the
# LICENSE file in the root directory of this source tree.
import functools
from fairseq.hub_utils import BPEHubInterface as bpe # noqa
from fairseq.hub_utils import TokenizerHubInterface as tokenize... | EXA-1-master | exa/models/unilm-master/infoxlm/fairseq/hubconf.py |
#!/usr/bin/env python3 -u
# Copyright (c) Facebook, Inc. and its affiliates.
#
# This source code is licensed under the MIT license found in the
# LICENSE file in the root directory of this source tree.
"""
Evaluate the perplexity of a trained language model.
"""
import numpy as np
import torch
from fairseq import c... | EXA-1-master | exa/models/unilm-master/infoxlm/fairseq/eval_lm.py |
#!/usr/bin/env python3
# Copyright (c) Facebook, Inc. and its affiliates.
#
# This source code is licensed under the MIT license found in the
# LICENSE file in the root directory of this source tree.
"""
BLEU scoring of generated translations against reference translations.
"""
import argparse
import os
import sys
fr... | EXA-1-master | exa/models/unilm-master/infoxlm/fairseq/score.py |
# Copyright (c) Facebook, Inc. and its affiliates.
#
# This source code is licensed under the MIT license found in the
# LICENSE file in the root directory of this source tree.
import tempfile
import unittest
import torch
from fairseq.data import Dictionary
class TestDictionary(unittest.TestCase):
def test_fi... | EXA-1-master | exa/models/unilm-master/infoxlm/fairseq/tests/test_dictionary.py |
# Copyright (c) Facebook, Inc. and its affiliates.
#
# This source code is licensed under the MIT license found in the
# LICENSE file in the root directory of this source tree.
import argparse
from multiprocessing import Manager
import random
import unittest
import torch
import torch.nn as nn
from fairseq import dis... | EXA-1-master | exa/models/unilm-master/infoxlm/fairseq/tests/test_bmuf.py |
# Copyright (c) Facebook, Inc. and its affiliates.
#
# This source code is licensed under the MIT license found in the
# LICENSE file in the root directory of this source tree.
import unittest
import torch
from fairseq import utils
class TestUtils(unittest.TestCase):
def test_convert_padding_direction(self):
... | EXA-1-master | exa/models/unilm-master/infoxlm/fairseq/tests/test_utils.py |
# Copyright (c) Facebook, Inc. and its affiliates.
#
# This source code is licensed under the MIT license found in the
# LICENSE file in the root directory of this source tree.
import unittest
from fairseq.data import iterators
class TestIterators(unittest.TestCase):
def test_counting_iterator(self):
x... | EXA-1-master | exa/models/unilm-master/infoxlm/fairseq/tests/test_iterators.py |
# Copyright (c) Facebook, Inc. and its affiliates.
#
# This source code is licensed under the MIT license found in the
# LICENSE file in the root directory of this source tree.
import unittest
from typing import Dict, List
import tests.utils as test_utils
import torch
from fairseq import utils
from fairseq.data impor... | EXA-1-master | exa/models/unilm-master/infoxlm/fairseq/tests/test_noising.py |
# Copyright (c) Facebook, Inc. and its affiliates.
#
# This source code is licensed under the MIT license found in the
# LICENSE file in the root directory of this source tree.
import torch
import unittest
from fairseq.modules.sparse_multihead_attention import SparseMultiheadAttention
class TestSparseMultiheadAttent... | EXA-1-master | exa/models/unilm-master/infoxlm/fairseq/tests/test_sparse_multihead_attention.py |
# Copyright (c) Facebook, Inc. and its affiliates.
#
# This source code is licensed under the MIT license found in the
# LICENSE file in the root directory of this source tree.
import contextlib
from io import StringIO
import unittest
from unittest.mock import MagicMock, patch
import torch
from fairseq import data, ... | EXA-1-master | exa/models/unilm-master/infoxlm/fairseq/tests/test_train.py |
# Copyright (c) Facebook, Inc. and its affiliates.
#
# This source code is licensed under the MIT license found in the
# LICENSE file in the root directory of this source tree.
import argparse
import unittest
import torch
from fairseq.sequence_scorer import SequenceScorer
import tests.utils as test_utils
class Te... | EXA-1-master | exa/models/unilm-master/infoxlm/fairseq/tests/test_sequence_scorer.py |
# Copyright (c) Facebook, Inc. and its affiliates.
#
# This source code is licensed under the MIT license found in the
# LICENSE file in the root directory of this source tree.
import torch
import unittest
from fairseq.modules.multihead_attention import MultiheadAttention
class TestMultiheadAttention(unittest.TestCa... | EXA-1-master | exa/models/unilm-master/infoxlm/fairseq/tests/test_multihead_attention.py |
# Copyright (c) Facebook, Inc. and its affiliates.
#
# This source code is licensed under the MIT license found in the
# LICENSE file in the root directory of this source tree.
import collections
import unittest
import numpy as np
from fairseq.data import ListDataset, ResamplingDataset
class TestResamplingDataset(... | EXA-1-master | exa/models/unilm-master/infoxlm/fairseq/tests/test_resampling_dataset.py |
EXA-1-master | exa/models/unilm-master/infoxlm/fairseq/tests/__init__.py | |
# Copyright (c) Facebook, Inc. and its affiliates.
#
# This source code is licensed under the MIT license found in the
# LICENSE file in the root directory of this source tree.
import unittest
import torch
from fairseq.data import (
BacktranslationDataset,
LanguagePairDataset,
TransformEosDataset,
)
from... | EXA-1-master | exa/models/unilm-master/infoxlm/fairseq/tests/test_backtranslation_dataset.py |
# Copyright (c) Facebook, Inc. and its affiliates.
#
# This source code is licensed under the MIT license found in the
# LICENSE file in the root directory of this source tree.
import contextlib
from io import StringIO
import os
import random
import sys
import tempfile
import unittest
import torch
from fairseq impor... | EXA-1-master | exa/models/unilm-master/infoxlm/fairseq/tests/test_binaries.py |
# Copyright (c) Facebook, Inc. and its affiliates.
#
# This source code is licensed under the MIT license found in the
# LICENSE file in the root directory of this source tree.
import argparse
import copy
import unittest
import torch
from fairseq.criterions.cross_entropy import CrossEntropyCriterion
from fairseq.cri... | EXA-1-master | exa/models/unilm-master/infoxlm/fairseq/tests/test_label_smoothing.py |
# Copyright (c) Facebook, Inc. and its affiliates.
#
# This source code is licensed under the MIT license found in the
# LICENSE file in the root directory of this source tree.
import argparse
import torch
from fairseq import utils
from fairseq.data import Dictionary
from fairseq.data.language_pair_dataset import col... | EXA-1-master | exa/models/unilm-master/infoxlm/fairseq/tests/utils.py |
# Copyright (c) Facebook, Inc. and its affiliates.
#
# This source code is licensed under the MIT license found in the
# LICENSE file in the root directory of this source tree.
import torch
import unittest
from fairseq.modules import ConvTBC
import torch.nn as nn
class TestConvTBC(unittest.TestCase):
def test_c... | EXA-1-master | exa/models/unilm-master/infoxlm/fairseq/tests/test_convtbc.py |
# Copyright (c) Facebook, Inc. and its affiliates.
#
# This source code is licensed under the MIT license found in the
# LICENSE file in the root directory of this source tree.
import argparse
import unittest
import torch
from fairseq.optim.adam import FairseqAdam
from fairseq.optim.fp16_optimizer import MemoryEffic... | EXA-1-master | exa/models/unilm-master/infoxlm/fairseq/tests/test_memory_efficient_fp16.py |
# Copyright (c) Facebook, Inc. and its affiliates.
#
# This source code is licensed under the MIT license found in the
# LICENSE file in the root directory of this source tree.
import unittest
import torch
from fairseq.data import TokenBlockDataset
import tests.utils as test_utils
class TestTokenBlockDataset(unit... | EXA-1-master | exa/models/unilm-master/infoxlm/fairseq/tests/test_token_block_dataset.py |
# Copyright (c) Facebook, Inc. and its affiliates.
#
# This source code is licensed under the MIT license found in the
# LICENSE file in the root directory of this source tree.
import argparse
import unittest
import torch
from fairseq.sequence_generator import SequenceGenerator
import tests.utils as test_utils
cl... | EXA-1-master | exa/models/unilm-master/infoxlm/fairseq/tests/test_sequence_generator.py |
# Copyright (c) Facebook, Inc. and its affiliates.
#
# This source code is licensed under the MIT license found in the
# LICENSE file in the root directory of this source tree.
import unittest
import torch
from fairseq.data import LanguagePairDataset, TokenBlockDataset
from fairseq.data.concat_dataset import ConcatDa... | EXA-1-master | exa/models/unilm-master/infoxlm/fairseq/tests/test_concat_dataset.py |
# Copyright (c) Facebook, Inc. and its affiliates.
#
# This source code is licensed under the MIT license found in the
# LICENSE file in the root directory of this source tree.
import contextlib
from io import StringIO
import json
import os
import tempfile
import unittest
from . import test_binaries
class TestRepro... | EXA-1-master | exa/models/unilm-master/infoxlm/fairseq/tests/test_reproducibility.py |
# Copyright (c) Facebook, Inc. and its affiliates.
#
# This source code is licensed under the MIT license found in the
# LICENSE file in the root directory of this source tree.
import torch
import unittest
from fairseq.data import Dictionary
from fairseq.modules import CharacterTokenEmbedder
class TestCharacterToke... | EXA-1-master | exa/models/unilm-master/infoxlm/fairseq/tests/test_character_token_embedder.py |
# Copyright (c) Facebook, Inc. and its affiliates.
#
# This source code is licensed under the MIT license found in the
# LICENSE file in the root directory of this source tree.
import collections
import os
import tempfile
import unittest
import shutil
import numpy as np
import torch
from torch import nn
from script... | EXA-1-master | exa/models/unilm-master/infoxlm/fairseq/tests/test_average_checkpoints.py |
# Copyright (c) Facebook, Inc. and its affiliates.
#
# This source code is licensed under the MIT license found in the
# LICENSE file in the root directory of this source tree.
import unittest
from collections import OrderedDict
import numpy as np
import torch
from fairseq.data import LanguagePairDataset, TokenBlockD... | EXA-1-master | exa/models/unilm-master/infoxlm/fairseq/tests/test_multi_corpus_sampled_dataset.py |
#!/usr/bin/env python3
import argparse
import os
import unittest
from inspect import currentframe, getframeinfo
import numpy as np
import torch
from fairseq.data import data_utils as fairseq_data_utils
from fairseq.data.dictionary import Dictionary
from fairseq.models import (
BaseFairseqModel,
FairseqDecoder... | EXA-1-master | exa/models/unilm-master/infoxlm/fairseq/tests/speech_recognition/asr_test_base.py |
#!/usr/bin/env python3
# Copyright (c) Facebook, Inc. and its affiliates.
#
# This source code is licensed under the MIT license found in the
# LICENSE file in the root directory of this source tree.
import unittest
import numpy as np
import torch
from examples.speech_recognition.data.collaters import Seq2SeqCollater... | EXA-1-master | exa/models/unilm-master/infoxlm/fairseq/tests/speech_recognition/test_collaters.py |
#!/usr/bin/env python3
# Copyright (c) Facebook, Inc. and its affiliates.
#
# This source code is licensed under the MIT license found in the
# LICENSE file in the root directory of this source tree.
from examples.speech_recognition.criterions.cross_entropy_acc import CrossEntropyWithAccCriterion
from .asr_test_base i... | EXA-1-master | exa/models/unilm-master/infoxlm/fairseq/tests/speech_recognition/test_cross_entropy.py |
#!/usr/bin/env python3
# import models/encoder/decoder to be tested
from examples.speech_recognition.models.vggtransformer import (
TransformerDecoder,
VGGTransformerEncoder,
VGGTransformerModel,
vggtransformer_1,
vggtransformer_2,
vggtransformer_base,
)
# import base test class
from .asr_test... | EXA-1-master | exa/models/unilm-master/infoxlm/fairseq/tests/speech_recognition/test_vggtransformer.py |
EXA-1-master | exa/models/unilm-master/infoxlm/fairseq/tests/speech_recognition/__init__.py | |
# Copyright (c) Facebook, Inc. and its affiliates.
#
# This source code is licensed under the MIT license found in the
# LICENSE file in the root directory of this source tree.
"""
A modified version of the legacy DistributedDataParallel module that uses c10d
communication primitives. This version is simpler than the ... | EXA-1-master | exa/models/unilm-master/infoxlm/fairseq/fairseq/legacy_distributed_data_parallel.py |
# Copyright (c) Facebook, Inc. and its affiliates.
#
# This source code is licensed under the MIT license found in the
# LICENSE file in the root directory of this source tree.
import argparse
import torch
import sys
from fairseq import utils
from fairseq.data.indexed_dataset import get_available_dataset_impl
def ... | EXA-1-master | exa/models/unilm-master/infoxlm/fairseq/fairseq/options.py |
# Copyright (c) Facebook, Inc. and its affiliates.
#
# This source code is licensed under the MIT license found in the
# LICENSE file in the root directory of this source tree.
from collections import namedtuple
import torch
from fairseq import utils
DecoderOut = namedtuple('IterativeRefinementDecoderOut', [
'... | EXA-1-master | exa/models/unilm-master/infoxlm/fairseq/fairseq/iterative_refinement_generator.py |
# Copyright (c) Facebook, Inc. and its affiliates.
#
# This source code is licensed under the MIT license found in the
# LICENSE file in the root directory of this source tree.
import time
class AverageMeter(object):
"""Computes and stores the average and current value"""
def __init__(self):
self.res... | EXA-1-master | exa/models/unilm-master/infoxlm/fairseq/fairseq/meters.py |
# Copyright (c) Facebook, Inc. and its affiliates.
#
# This source code is licensed under the MIT license found in the
# LICENSE file in the root directory of this source tree.
import argparse
REGISTRIES = {}
def setup_registry(
registry_name: str,
base_class=None,
default=None,
):
assert registry_... | EXA-1-master | exa/models/unilm-master/infoxlm/fairseq/fairseq/registry.py |
# Copyright (c) Facebook, Inc. and its affiliates.
#
# This source code is licensed under the MIT license found in the
# LICENSE file in the root directory of this source tree.
import ctypes
import math
import torch
try:
from fairseq import libbleu
except ImportError as e:
import sys
sys.stderr.write('ERR... | EXA-1-master | exa/models/unilm-master/infoxlm/fairseq/fairseq/bleu.py |
# Copyright (c) Facebook, Inc. and its affiliates.
#
# This source code is licensed under the MIT license found in the
# LICENSE file in the root directory of this source tree.
__all__ = ['pdb']
__version__ = '0.9.0'
import fairseq.criterions # noqa
import fairseq.models # noqa
import fairseq.modules # noqa
import... | EXA-1-master | exa/models/unilm-master/infoxlm/fairseq/fairseq/__init__.py |
# Copyright (c) Facebook, Inc. and its affiliates.
#
# This source code is licensed under the MIT license found in the
# LICENSE file in the root directory of this source tree.
import math
import torch
from fairseq import search, utils
from fairseq.data import data_utils
from fairseq.models import FairseqIncremental... | EXA-1-master | exa/models/unilm-master/infoxlm/fairseq/fairseq/sequence_generator.py |
# Copyright (c) Facebook, Inc. and its affiliates.
#
# This source code is licensed under the MIT license found in the
# LICENSE file in the root directory of this source tree.
import multiprocessing
import os
import pdb
import sys
__all__ = ['set_trace']
_stdin = [None]
_stdin_lock = multiprocessing.Lock()
try:
... | EXA-1-master | exa/models/unilm-master/infoxlm/fairseq/fairseq/pdb.py |
# Copyright (c) Facebook, Inc. and its affiliates.
#
# This source code is licensed under the MIT license found in the
# LICENSE file in the root directory of this source tree.
import re
SPACE_NORMALIZER = re.compile(r"\s+")
def tokenize_line(line):
line = SPACE_NORMALIZER.sub(" ", line)
line = line.strip()... | EXA-1-master | exa/models/unilm-master/infoxlm/fairseq/fairseq/tokenizer.py |
#!/usr/bin/env python3 -u
# Copyright (c) Facebook, Inc. and its affiliates.
#
# This source code is licensed under the MIT license found in the
# LICENSE file in the root directory of this source tree.
import argparse
import copy
import os
import torch
from torch import nn
from fairseq import utils
from fairseq.dat... | EXA-1-master | exa/models/unilm-master/infoxlm/fairseq/fairseq/hub_utils.py |
# Copyright (c) Facebook, Inc. and its affiliates.
#
# This source code is licensed under the MIT license found in the
# LICENSE file in the root directory of this source tree.
import torch
import sys
from fairseq import utils
class SequenceScorer(object):
"""Scores the target for a given source sentence."""
... | EXA-1-master | exa/models/unilm-master/infoxlm/fairseq/fairseq/sequence_scorer.py |
# Copyright (c) Facebook, Inc. and its affiliates.
#
# This source code is licensed under the MIT license found in the
# LICENSE file in the root directory of this source tree.
from collections import defaultdict
import contextlib
import copy
import importlib.util
import math
import os
import sys
from typing import Ca... | EXA-1-master | exa/models/unilm-master/infoxlm/fairseq/fairseq/utils.py |
# Copyright (c) Facebook, Inc. and its affiliates.
#
# This source code is licensed under the MIT license found in the
# LICENSE file in the root directory of this source tree.
import collections
import logging
import os
import re
import shutil
import traceback
from collections import OrderedDict
from typing import Un... | EXA-1-master | exa/models/unilm-master/infoxlm/fairseq/fairseq/checkpoint_utils.py |
# Copyright (c) Facebook, Inc. and its affiliates.
#
# This source code is licensed under the MIT license found in the
# LICENSE file in the root directory of this source tree.
import os
import pickle
import socket
import subprocess
import warnings
import torch
import torch.distributed as dist
from fairseq import ut... | EXA-1-master | exa/models/unilm-master/infoxlm/fairseq/fairseq/distributed_utils.py |
# Copyright (c) Facebook, Inc. and its affiliates.
#
# This source code is licensed under the MIT license found in the
# LICENSE file in the root directory of this source tree.
"""
Utilities for working with the local dataset cache.
This file is adapted from `AllenNLP <https://github.com/allenai/allennlp>`_.
and `hugg... | EXA-1-master | exa/models/unilm-master/infoxlm/fairseq/fairseq/file_utils.py |
# Copyright (c) Facebook, Inc. and its affiliates.
#
# This source code is licensed under the MIT license found in the
# LICENSE file in the root directory of this source tree.
import math
import torch
class Search(object):
def __init__(self, tgt_dict):
self.pad = tgt_dict.pad()
self.unk = tgt_... | EXA-1-master | exa/models/unilm-master/infoxlm/fairseq/fairseq/search.py |
# Copyright (c) Facebook, Inc. and its affiliates.
#
# This source code is licensed under the MIT license found in the
# LICENSE file in the root directory of this source tree.
"""
Wrapper around various loggers and progress bars (e.g., tqdm).
"""
from collections import OrderedDict
import json
from numbers import Nu... | EXA-1-master | exa/models/unilm-master/infoxlm/fairseq/fairseq/progress_bar.py |
# Copyright (c) Facebook, Inc. and its affiliates.
#
# This source code is licensed under the MIT license found in the
# LICENSE file in the root directory of this source tree.
"""
Train a network across multiple GPUs.
"""
import contextlib
import math
import os
import sys
from collections import OrderedDict
from ite... | EXA-1-master | exa/models/unilm-master/infoxlm/fairseq/fairseq/trainer.py |
# Copyright (c) Facebook, Inc. and its affiliates.
#
# This source code is licensed under the MIT license found in the
# LICENSE file in the root directory of this source tree.
from collections import Counter
import os
from fairseq.tokenizer import tokenize_line
def safe_readline(f):
pos = f.tell()
while Tr... | EXA-1-master | exa/models/unilm-master/infoxlm/fairseq/fairseq/binarizer.py |
# Copyright (c) Facebook, Inc. and its affiliates.
#
# This source code is licensed under the MIT license found in the
# LICENSE file in the root directory of this source tree.
import numpy as np
import torch
from fairseq import tokenizer
from fairseq.data import (
data_utils,
FairseqDataset,
iterators,
... | EXA-1-master | exa/models/unilm-master/infoxlm/fairseq/fairseq/tasks/fairseq_task.py |
# Copyright (c) Facebook, Inc. and its affiliates.
#
# This source code is licensed under the MIT license found in the
# LICENSE file in the root directory of this source tree.
import os
from fairseq.data import (
data_utils,
Dictionary,
AppendTokenDataset,
DenoisingDataset,
PrependTokenDataset,
... | EXA-1-master | exa/models/unilm-master/infoxlm/fairseq/fairseq/tasks/denoising.py |
# Copyright (c) Facebook, Inc. and its affiliates.
#
# This source code is licensed under the MIT license found in the
# LICENSE file in the root directory of this source tree.
from collections import OrderedDict
import os
import torch
from fairseq import options, utils
from fairseq.data import (
Dictionary,
... | EXA-1-master | exa/models/unilm-master/infoxlm/fairseq/fairseq/tasks/multilingual_translation.py |
# Copyright (c) Facebook, Inc. and its affiliates.
#
# This source code is licensed under the MIT license found in the
# LICENSE file in the root directory of this source tree.
import torch
from fairseq.utils import new_arange
from fairseq.tasks import register_task
from fairseq.tasks.translation import TranslationTa... | EXA-1-master | exa/models/unilm-master/infoxlm/fairseq/fairseq/tasks/translation_lev.py |
# Copyright (c) Facebook, Inc. and its affiliates.
#
# This source code is licensed under the MIT license found in the
# LICENSE file in the root directory of this source tree.
import os
import torch
from fairseq import utils
from fairseq.data import (
data_utils,
Dictionary,
MonolingualDataset,
Toke... | EXA-1-master | exa/models/unilm-master/infoxlm/fairseq/fairseq/tasks/language_modeling.py |
# Copyright (c) Facebook, Inc. and its affiliates.
#
# This source code is licensed under the MIT license found in the
# LICENSE file in the root directory of this source tree.
import itertools
import numpy as np
import os
from fairseq import tokenizer
from fairseq.data import (
ConcatDataset,
indexed_dataset... | EXA-1-master | exa/models/unilm-master/infoxlm/fairseq/fairseq/tasks/legacy_masked_lm.py |
# Copyright (c) Facebook, Inc. and its affiliates.
#
# This source code is licensed under the MIT license found in the
# LICENSE file in the root directory of this source tree.
import argparse
import importlib
import os
from .fairseq_task import FairseqTask
TASK_REGISTRY = {}
TASK_CLASS_NAMES = set()
def setup_tas... | EXA-1-master | exa/models/unilm-master/infoxlm/fairseq/fairseq/tasks/__init__.py |
# Copyright (c) Facebook, Inc. and its affiliates.
#
# This source code is licensed under the MIT license found in the
# LICENSE file in the root directory of this source tree.
import os
from fairseq.data import FileAudioDataset
from . import FairseqTask, register_task
@register_task('audio_pretraining')
class Audi... | EXA-1-master | exa/models/unilm-master/infoxlm/fairseq/fairseq/tasks/audio_pretraining.py |
# Copyright (c) Facebook, Inc. and its affiliates.
#
# This source code is licensed under the MIT license found in the
# LICENSE file in the root directory of this source tree.
import itertools
import os
from fairseq import options, utils
from fairseq.data import (
AppendTokenDataset,
ConcatDataset,
data_... | EXA-1-master | exa/models/unilm-master/infoxlm/fairseq/fairseq/tasks/translation.py |
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