code stringlengths 86 54.5k | code_codestyle int64 0 371 | style_context stringlengths 87 49.2k | style_context_codestyle int64 0 349 | label int64 0 1 |
|---|---|---|---|---|
import gc
import unittest
import numpy as np
import torch
from transformers import CLIPTextConfig, CLIPTextModel, CLIPTokenizer
from diffusers import AutoencoderKL, DDIMScheduler, LDMTextToImagePipeline, UNetaDConditionModel
from diffusers.utils.testing_utils import (
enable_full_determinism,
load_nump... | 36 |
import json
import os
import unittest
from transformers import DebertaTokenizer, DebertaTokenizerFast
from transformers.models.deberta.tokenization_deberta import VOCAB_FILES_NAMES
from transformers.testing_utils import slow
from ...test_tokenization_common import TokenizerTesterMixin
class UpperCAme... | 36 | 1 |
from argparse import ArgumentParser
from ..pipelines import Pipeline, PipelineDataFormat, get_supported_tasks, pipeline
from ..utils import logging
from . import BaseTransformersCLICommand
lowercase : Tuple = logging.get_logger(__name__) # pylint: disable=invalid-name
def lowe... | 36 |
import os
import tempfile
import unittest
from pathlib import Path
from transformers import AutoConfig, is_tf_available
from transformers.testing_utils import require_tf
if is_tf_available():
import tensorflow as tf
from transformers import TensorFlowBenchmark, TensorFlowBenchmarkArguments
... | 36 | 1 |
import pytest
from datasets.utils.sharding import _distribute_shards, _number_of_shards_in_gen_kwargs, _split_gen_kwargs
@pytest.mark.parametrize(
"kwargs, expected" , [
({"num_shards": 0, "max_num_jobs": 1}, []),
({"num_shards": 10, "max_num_jobs": 1}, [range(10 )]),
({"nu... | 36 |
import argparse
import copy
def lowerCAmelCase__ ( _a : List[Any] ):
snake_case_ : List[Any] = {}
with open(_a ) as f:
for line in f:
if line.split()[0] not in dict_of_neighbours:
snake_case_ : int = []
_list.append([line.spl... | 36 | 1 |
from __future__ import annotations
from math import pi
from typing import Protocol
import matplotlib.pyplot as plt
import numpy as np
class UpperCAmelCase_ ( SCREAMING_SNAKE_CASE__ ):
'''simple docstring'''
def _lowerCAmelCase ( self , _SCREAMING_SNAKE_CASE ) -> ... | 36 |
from typing import TYPE_CHECKING
from ...file_utils import _LazyModule, is_tokenizers_available, is_torch_available
from ...utils import OptionalDependencyNotAvailable
lowercase : Any = {'''configuration_gpt_neox''': ['''GPT_NEOX_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''GPTNeoXConfig''']}
... | 36 | 1 |
import argparse
import torch
from transformers import LxmertConfig, LxmertForPreTraining, load_tf_weights_in_lxmert
from transformers.utils import logging
logging.set_verbosity_info()
def lowerCAmelCase__ ( _a : int , _a : str , _a : List[Any] ):
# Initialise... | 36 |
def lowerCAmelCase__ ( _a : float , _a : float ):
if density <= 0:
raise ValueError("Impossible fluid density" )
if bulk_modulus <= 0:
raise ValueError("Impossible bulk modulus" )
return (bulk_modulus / density) ** 0.5
if __name__ == "__main__":
... | 36 | 1 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_flax_available, is_torch_available
lowercase : Tuple = {'''configuration_speech_encoder_decoder''': ['''SpeechEncoderDecoderConfig''']}
try:
if not is_torch_available():
... | 36 |
def lowerCAmelCase__ ( _a : int = 50 ):
snake_case_ : Union[str, Any] = [1] * (length + 1)
for row_length in range(3 , length + 1 ):
for block_length in range(3 , row_length + 1 ):
for block_start in range(row_length - block_length ):
... | 36 | 1 |
import os
from shutil import copyfile
from typing import List, Optional, Tuple
from ...tokenization_utils import AddedToken
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import is_sentencepiece_available, logging
if is_sentencepiece_available():
from .tokenization_fnet im... | 36 |
import json
from typing import TYPE_CHECKING, List, Optional, Tuple
from tokenizers import pre_tokenizers
from ...tokenization_utils_base import BatchEncoding
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import logging
from .tokenization_gpta import GPTaTokenizer
if TYPE_CHECK... | 36 | 1 |
import os
import unittest
from transformers import FunnelTokenizer, FunnelTokenizerFast
from transformers.models.funnel.tokenization_funnel import VOCAB_FILES_NAMES
from transformers.testing_utils import require_tokenizers
from ...test_tokenization_common import TokenizerTesterMixin
@require_tokenizers
cla... | 36 |
import datasets
from .evaluate import evaluate
lowercase : Dict = '''\
@article{hendrycks2021cuad,
title={CUAD: An Expert-Annotated NLP Dataset for Legal Contract Review},
author={Dan Hendrycks and Collin Burns and Anya Chen and Spencer Ball},
journal={arXiv preprint ... | 36 | 1 |
from typing import TYPE_CHECKING
from ....utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
lowercase : List[str] = {
'''configuration_trajectory_transformer''': [
'''TRAJECTORY_TRANSFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP''',
'''TrajectoryTr... | 36 |
from ...utils import (
OptionalDependencyNotAvailable,
is_torch_available,
is_transformers_available,
is_transformers_version,
)
try:
if not (is_transformers_available() and is_torch_available() and is_transformers_version('''>=''', '''4.25.0''')):
raise OptionalDependencyN... | 36 | 1 |
import unittest
from transformers import GPTSwaTokenizer
from transformers.testing_utils import get_tests_dir, require_sentencepiece, require_tokenizers, slow
from ...test_tokenization_common import TokenizerTesterMixin
lowercase : List[Any] = get_tests_dir('''fixtures/test_sentencepi... | 36 |
def lowerCAmelCase__ ( _a : dict ):
snake_case_ : List[Any] = set()
# edges = list of graph's edges
snake_case_ : int = get_edges(_a )
# While there are still elements in edges list, take an arbitrary edge
# (from_node, to_node) and add his extre... | 36 | 1 |
import logging
import os
from typing import List, TextIO, Union
from conllu import parse_incr
from utils_ner import InputExample, Split, TokenClassificationTask
lowercase : Any = logging.getLogger(__name__)
class UpperCAmelCase_ ( SCREAMING_SNAKE_CASE__ ):
'''simp... | 36 |
import numpy as np
def lowerCAmelCase__ ( _a : np.array ):
return (2 / (1 + np.exp(-2 * vector ))) - 1
if __name__ == "__main__":
import doctest
doctest.testmod()
| 36 | 1 |
def lowerCAmelCase__ ( _a : int ):
if n == 1 or not isinstance(_a , _a ):
return 0
elif n == 2:
return 1
else:
snake_case_ : Any = [0, 1]
for i in range(2 , n + 1 ):
sequence.append(sequence[i - 1] + sequence[i - 2] )
r... | 36 |
import os
import time
import pytest
from datasets.utils.filelock import FileLock, Timeout
def lowerCAmelCase__ ( _a : str ):
snake_case_ : str = FileLock(str(tmpdir / "foo.lock" ) )
snake_case_ : Optional[Any] = FileLock(str(tmpdir / "foo.lock" ... | 36 | 1 |
import importlib
import shutil
import threading
import warnings
from typing import List
import fsspec
import fsspec.asyn
from . import compression
from .hffilesystem import HfFileSystem
lowercase : Union[str, Any] = importlib.util.find_spec('''s3fs''') is not None
if _has_safs:
... | 36 |
from __future__ import annotations
def lowerCAmelCase__ ( _a : str , _a : str ):
snake_case_ : Optional[Any] = get_failure_array(_a )
# 2) Step through text searching for pattern
snake_case_ , snake_case_ : Dict = 0, 0 # index into te... | 36 | 1 |
def lowerCAmelCase__ ( _a : int = 50 ):
snake_case_ : Union[str, Any] = [[0] * 3 for _ in range(length + 1 )]
for row_length in range(length + 1 ):
for tile_length in range(2 , 5 ):
for tile_start in range(row_length - tile_length + 1 )... | 36 |
import importlib
import sys
from argparse import REMAINDER, ArgumentParser
from pathlib import Path
import torch_xla.distributed.xla_multiprocessing as xmp
def lowerCAmelCase__ ( ):
snake_case_ : str = ArgumentParser(
description=(
"PyTorch TPU distributed training l... | 36 | 1 |
import os
from pickle import UnpicklingError
from typing import Dict, Tuple
import jax
import jax.numpy as jnp
import numpy as np
from flax.serialization import from_bytes
from flax.traverse_util import flatten_dict, unflatten_dict
import transformers
from .utils import logging
lowercase : Any ... | 36 |
import argparse
import os
import re
# All paths are set with the intent you should run this script from the root of the repo with the command
# python utils/check_dummies.py
lowercase : Optional[Any] = '''src/diffusers'''
# Matches is_xxx_available()
lowercase : Any ... | 36 | 1 |
import json
import os
import shutil
import tempfile
from unittest import TestCase
from transformers import BartTokenizer, BartTokenizerFast, DPRQuestionEncoderTokenizer, DPRQuestionEncoderTokenizerFast
from transformers.models.bart.configuration_bart import BartConfig
from transformers.models.bert.tokenization_... | 36 |
lowercase : Optional[int] = {
'''Pillow''': '''Pillow''',
'''accelerate''': '''accelerate>=0.11.0''',
'''compel''': '''compel==0.1.8''',
'''black''': '''black~=23.1''',
'''datasets''': '''datasets''',
'''filelock''': '''filelock''',
'''flax''': '''flax>=0.4.1''... | 36 | 1 |
import torch
from torch import nn
from ...configuration_utils import ConfigMixin, register_to_config
from ...models import ModelMixin
class UpperCAmelCase_ ( SCREAMING_SNAKE_CASE__ , SCREAMING_SNAKE_CASE__ ):
'''simple docstring'''
@register_to_config
def __init__( s... | 36 |
from ...processing_utils import ProcessorMixin
from ...tokenization_utils_base import BatchEncoding
class UpperCAmelCase_ ( SCREAMING_SNAKE_CASE__ ):
'''simple docstring'''
A : Tuple = ['image_processor', 'tokenizer']
A : Tuple = 'AutoIm... | 36 | 1 |
from __future__ import annotations
import bisect
def lowerCAmelCase__ ( _a : list[int] , _a : int , _a : int = 0 , _a : int = -1 ):
if hi < 0:
snake_case_ : str = len(_a )
while lo < hi:
snake_case_ : Union[str, An... | 36 |
import os
import unittest
from transformers import MobileBertTokenizer, MobileBertTokenizerFast
from transformers.models.bert.tokenization_bert import (
VOCAB_FILES_NAMES,
BasicTokenizer,
WordpieceTokenizer,
_is_control,
_is_punctuation,
_is_whitespace,
)
from transformers.testing_utils ... | 36 | 1 |
def lowerCAmelCase__ ( _a : Optional[Any] , _a : List[Any] , _a : List[Any] , _a : Any ):
if height >= 1:
move_tower(height - 1 , _a , _a , _a )
move_disk(_a , _a )
move_tower(height - 1 , _a , _a , _a ... | 36 |
import unittest
import numpy as np
from transformers import BertConfig, is_flax_available
from transformers.testing_utils import require_flax, slow
from ...test_modeling_flax_common import FlaxModelTesterMixin, floats_tensor, ids_tensor, random_attention_mask
if is_flax_available():
from transformers... | 36 | 1 |
import math
def lowerCAmelCase__ ( _a : int ):
snake_case_ : str = [True] * n
snake_case_ : List[Any] = False
snake_case_ : int = False
snake_case_ : Union[str, Any] = True
for i in range(3 , int(n**0.5 + 1 ) , ... | 36 |
import copy
from collections import OrderedDict
from typing import Mapping
from packaging import version
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
from ..auto import CONFIG_MAPPING
lowercase : List[Any] = logging.ge... | 36 | 1 |
import json
import os
import tempfile
from unittest.mock import patch
import torch
from torch.utils.data import DataLoader, TensorDataset
from accelerate import DistributedType, infer_auto_device_map, init_empty_weights
from accelerate.accelerator import Accelerator
from accelerate.state import GradientState, ... | 36 |
from typing import Dict, List, Optional, Union
import numpy as np
from ...image_processing_utils import BaseImageProcessor, BatchFeature, get_size_dict
from ...image_transforms import center_crop, normalize, rescale, resize, to_channel_dimension_format
from ...image_utils import (
IMAGENET_STANDARD_MEAN,
... | 36 | 1 |
import os
import zipfile
import requests
from get_ci_error_statistics import download_artifact, get_artifacts_links
def lowerCAmelCase__ ( _a : int , _a : int=7 ):
snake_case_ : Any = None
if token is not None:
snake_case_ : Optional[int] = ... | 36 |
import shutil
import tempfile
import unittest
from unittest.mock import patch
from transformers import (
DefaultFlowCallback,
IntervalStrategy,
PrinterCallback,
ProgressCallback,
Trainer,
TrainerCallback,
TrainingArguments,
is_torch_available,
)
from transformers.testing_utils im... | 36 | 1 |
import unittest
from pathlib import Path
from tempfile import TemporaryDirectory
from transformers import AutoConfig, TFGPTaLMHeadModel, is_keras_nlp_available, is_tf_available
from transformers.models.gpta.tokenization_gpta import GPTaTokenizer
from transformers.testing_utils import require_keras_nlp, require_... | 36 |
import json
import os
import unittest
from transformers import DebertaTokenizer, DebertaTokenizerFast
from transformers.models.deberta.tokenization_deberta import VOCAB_FILES_NAMES
from transformers.testing_utils import slow
from ...test_tokenization_common import TokenizerTesterMixin
class UpperCAme... | 36 | 1 |
from collections import OrderedDict
from typing import List, Mapping
from packaging import version
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
lowercase : int = logging.get_logger(__name__)
lowercase : List... | 36 |
import os
import tempfile
import unittest
from pathlib import Path
from transformers import AutoConfig, is_tf_available
from transformers.testing_utils import require_tf
if is_tf_available():
import tensorflow as tf
from transformers import TensorFlowBenchmark, TensorFlowBenchmarkArguments
... | 36 | 1 |
import secrets
from random import shuffle
from string import ascii_letters, ascii_lowercase, ascii_uppercase, digits, punctuation
def lowerCAmelCase__ ( _a : int = 8 ):
snake_case_ : Any = ascii_letters + digits + punctuation
return "".join(secrets.choice(_a ) for ... | 36 |
import argparse
import copy
def lowerCAmelCase__ ( _a : List[Any] ):
snake_case_ : List[Any] = {}
with open(_a ) as f:
for line in f:
if line.split()[0] not in dict_of_neighbours:
snake_case_ : int = []
_list.append([line.spl... | 36 | 1 |
import gc
import unittest
from diffusers import FlaxStableDiffusionInpaintPipeline
from diffusers.utils import is_flax_available, load_image, slow
from diffusers.utils.testing_utils import require_flax
if is_flax_available():
import jax
import jax.numpy as jnp
from flax.jax_utils import r... | 36 |
from typing import TYPE_CHECKING
from ...file_utils import _LazyModule, is_tokenizers_available, is_torch_available
from ...utils import OptionalDependencyNotAvailable
lowercase : Any = {'''configuration_gpt_neox''': ['''GPT_NEOX_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''GPTNeoXConfig''']}
... | 36 | 1 |
import math
import random
from typing import Any
from .hill_climbing import SearchProblem
def lowerCAmelCase__ ( _a : List[Any] , _a : bool = True , _a : float = math.inf , _a : float = -math.inf , _a : float = math.inf , _a : float = -... | 36 |
def lowerCAmelCase__ ( _a : float , _a : float ):
if density <= 0:
raise ValueError("Impossible fluid density" )
if bulk_modulus <= 0:
raise ValueError("Impossible bulk modulus" )
return (bulk_modulus / density) ** 0.5
if __name__ == "__main__":
... | 36 | 1 |
from typing import Dict, List, Optional, Union
import numpy as np
from ...image_processing_utils import BaseImageProcessor, BatchFeature, get_size_dict
from ...image_transforms import center_crop, normalize, rescale, resize, to_channel_dimension_format
from ...image_utils import (
IMAGENET_STANDARD_MEAN,
... | 36 |
def lowerCAmelCase__ ( _a : int = 50 ):
snake_case_ : Union[str, Any] = [1] * (length + 1)
for row_length in range(3 , length + 1 ):
for block_length in range(3 , row_length + 1 ):
for block_start in range(row_length - block_length ):
... | 36 | 1 |
from ...utils import (
OptionalDependencyNotAvailable,
is_torch_available,
is_transformers_available,
is_transformers_version,
)
try:
if not (is_transformers_available() and is_torch_available() and is_transformers_version('''>=''', '''4.25.0''')):
raise OptionalDependencyN... | 36 |
import json
from typing import TYPE_CHECKING, List, Optional, Tuple
from tokenizers import pre_tokenizers
from ...tokenization_utils_base import BatchEncoding
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import logging
from .tokenization_gpta import GPTaTokenizer
if TYPE_CHECK... | 36 | 1 |
import math
from collections.abc import Iterator
from itertools import takewhile
def lowerCAmelCase__ ( _a : int ):
if 1 < number < 4:
# 2 and 3 are primes
return True
elif number < 2 or number % 2 == 0 or number % 3 == 0:
# Negatives, 0, 1, all even numbers, all multip... | 36 |
import datasets
from .evaluate import evaluate
lowercase : Dict = '''\
@article{hendrycks2021cuad,
title={CUAD: An Expert-Annotated NLP Dataset for Legal Contract Review},
author={Dan Hendrycks and Collin Burns and Anya Chen and Spencer Ball},
journal={arXiv preprint ... | 36 | 1 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_torch_available,
is_vision_available,
)
lowercase : Optional[int] = {'''configuration_beit''': ['''BEIT_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''Be... | 36 |
from ...utils import (
OptionalDependencyNotAvailable,
is_torch_available,
is_transformers_available,
is_transformers_version,
)
try:
if not (is_transformers_available() and is_torch_available() and is_transformers_version('''>=''', '''4.25.0''')):
raise OptionalDependencyN... | 36 | 1 |
import functools
import logging
import os
import sys
import threading
from logging import (
CRITICAL, # NOQA
DEBUG, # NOQA
ERROR, # NOQA
FATAL, # NOQA
INFO, # NOQA
NOTSET, # NOQA
WARN, # NOQA
WARNING, # NOQA
)
from typing import Optional
import huggingface_hub.utils as hf... | 36 |
def lowerCAmelCase__ ( _a : dict ):
snake_case_ : List[Any] = set()
# edges = list of graph's edges
snake_case_ : int = get_edges(_a )
# While there are still elements in edges list, take an arbitrary edge
# (from_node, to_node) and add his extre... | 36 | 1 |
from typing import List, Optional, Union
import numpy as np
from ....audio_utils import mel_filter_bank, optimal_fft_length, spectrogram, window_function
from ....feature_extraction_sequence_utils import SequenceFeatureExtractor
from ....feature_extraction_utils import BatchFeature
from ....file_utils import P... | 36 |
import numpy as np
def lowerCAmelCase__ ( _a : np.array ):
return (2 / (1 + np.exp(-2 * vector ))) - 1
if __name__ == "__main__":
import doctest
doctest.testmod()
| 36 | 1 |
from ...utils import (
OptionalDependencyNotAvailable,
is_torch_available,
is_transformers_available,
is_transformers_version,
)
try:
if not (is_transformers_available() and is_torch_available() and is_transformers_version('''>=''', '''4.25.0''')):
raise OptionalDependencyN... | 36 |
import os
import time
import pytest
from datasets.utils.filelock import FileLock, Timeout
def lowerCAmelCase__ ( _a : str ):
snake_case_ : str = FileLock(str(tmpdir / "foo.lock" ) )
snake_case_ : Optional[Any] = FileLock(str(tmpdir / "foo.lock" ... | 36 | 1 |
from __future__ import annotations
import os
import tempfile
import unittest
import numpy as np
from huggingface_hub import hf_hub_download
from transformers import is_tensorflow_text_available, is_tf_available
from transformers.testing_utils import require_tensorflow_text, require_tf, slow
from ..test_model... | 36 |
from __future__ import annotations
def lowerCAmelCase__ ( _a : str , _a : str ):
snake_case_ : Optional[Any] = get_failure_array(_a )
# 2) Step through text searching for pattern
snake_case_ , snake_case_ : Dict = 0, 0 # index into te... | 36 | 1 |
import json
import pathlib
import unittest
import numpy as np
from transformers.testing_utils import require_torch, require_vision, slow
from transformers.utils import is_torch_available, is_vision_available
from ...test_image_processing_common import ImageProcessingSavingTestMixin, prepare_image_inputs
if ... | 36 |
import importlib
import sys
from argparse import REMAINDER, ArgumentParser
from pathlib import Path
import torch_xla.distributed.xla_multiprocessing as xmp
def lowerCAmelCase__ ( ):
snake_case_ : str = ArgumentParser(
description=(
"PyTorch TPU distributed training l... | 36 | 1 |
# Copyright 2023 The HuggingFace Team. 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 ap... | 36 |
import argparse
import os
import re
# All paths are set with the intent you should run this script from the root of the repo with the command
# python utils/check_dummies.py
lowercase : Optional[Any] = '''src/diffusers'''
# Matches is_xxx_available()
lowercase : Any ... | 36 | 1 |
def lowerCAmelCase__ ( _a : int , _a : Dict ):
return (pointa[0] - pointa[0]) ** 2 + (pointa[1] - pointa[1]) ** 2
def lowerCAmelCase__ ( _a : Dict , _a : List[str]=0 ):
return sorted(_a , key=lambda _a : x[column] )
def ... | 36 |
lowercase : Optional[int] = {
'''Pillow''': '''Pillow''',
'''accelerate''': '''accelerate>=0.11.0''',
'''compel''': '''compel==0.1.8''',
'''black''': '''black~=23.1''',
'''datasets''': '''datasets''',
'''filelock''': '''filelock''',
'''flax''': '''flax>=0.4.1''... | 36 | 1 |
lowercase : Union[str, Any] = 0 # The first color of the flag.
lowercase : int = 1 # The second color of the flag.
lowercase : int = 2 # The third color of the flag.
lowercase : Tuple = (red, white, blue)
def ... | 36 |
from ...processing_utils import ProcessorMixin
from ...tokenization_utils_base import BatchEncoding
class UpperCAmelCase_ ( SCREAMING_SNAKE_CASE__ ):
'''simple docstring'''
A : Tuple = ['image_processor', 'tokenizer']
A : Tuple = 'AutoIm... | 36 | 1 |
from collections import OrderedDict
from typing import Mapping
from packaging import version
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
lowercase : str = logging.get_logger(__name__)
lowercase : Optional[A... | 36 |
import os
import unittest
from transformers import MobileBertTokenizer, MobileBertTokenizerFast
from transformers.models.bert.tokenization_bert import (
VOCAB_FILES_NAMES,
BasicTokenizer,
WordpieceTokenizer,
_is_control,
_is_punctuation,
_is_whitespace,
)
from transformers.testing_utils ... | 36 | 1 |
from __future__ import annotations
def lowerCAmelCase__ ( _a : list , _a : int | None = None , _a : int | None = None ):
if start is None:
snake_case_ : Dict = 0
if end is None:
snake_case_ : Tuple = len(_a ) - 1
if st... | 36 |
import unittest
import numpy as np
from transformers import BertConfig, is_flax_available
from transformers.testing_utils import require_flax, slow
from ...test_modeling_flax_common import FlaxModelTesterMixin, floats_tensor, ids_tensor, random_attention_mask
if is_flax_available():
from transformers... | 36 | 1 |
import unittest
from transformers import DebertaConfig, is_torch_available
from transformers.testing_utils import require_sentencepiece, require_tokenizers, require_torch, slow, torch_device
from ...test_configuration_common import ConfigTester
from ...test_modeling_common import ModelTesterMixin, ids_tensor
f... | 36 |
import copy
from collections import OrderedDict
from typing import Mapping
from packaging import version
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
from ..auto import CONFIG_MAPPING
lowercase : List[Any] = logging.ge... | 36 | 1 |
import shutil
import tempfile
import unittest
import numpy as np
import pytest
from transformers.testing_utils import require_vision
from transformers.utils import is_vision_available
if is_vision_available():
from PIL import Image
from transformers import (
AutoProcessor,
... | 36 |
from typing import Dict, List, Optional, Union
import numpy as np
from ...image_processing_utils import BaseImageProcessor, BatchFeature, get_size_dict
from ...image_transforms import center_crop, normalize, rescale, resize, to_channel_dimension_format
from ...image_utils import (
IMAGENET_STANDARD_MEAN,
... | 36 | 1 |
from ...processing_utils import ProcessorMixin
from ...tokenization_utils_base import BatchEncoding
class UpperCAmelCase_ ( SCREAMING_SNAKE_CASE__ ):
'''simple docstring'''
A : Tuple = ['image_processor', 'tokenizer']
A : Tuple = 'AutoIm... | 36 |
import shutil
import tempfile
import unittest
from unittest.mock import patch
from transformers import (
DefaultFlowCallback,
IntervalStrategy,
PrinterCallback,
ProgressCallback,
Trainer,
TrainerCallback,
TrainingArguments,
is_torch_available,
)
from transformers.testing_utils im... | 36 | 1 |
import math
from datetime import datetime, timedelta
def lowerCAmelCase__ ( _a : int ):
snake_case_ : Union[str, Any] = year % 19
snake_case_ : List[str] = year % 4
snake_case_ : str = year % 7
snake_case_ : Optional[Any] = mat... | 36 |
import json
import os
import unittest
from transformers import DebertaTokenizer, DebertaTokenizerFast
from transformers.models.deberta.tokenization_deberta import VOCAB_FILES_NAMES
from transformers.testing_utils import slow
from ...test_tokenization_common import TokenizerTesterMixin
class UpperCAme... | 36 | 1 |
import argparse
import json
import os
from collections import OrderedDict
import torch
from transformers import LukeConfig, LukeForMaskedLM, MLukeTokenizer, XLMRobertaTokenizer
from transformers.tokenization_utils_base import AddedToken
@torch.no_grad()
def lowerCAmelCase__ ( _a : List[str... | 36 |
import os
import tempfile
import unittest
from pathlib import Path
from transformers import AutoConfig, is_tf_available
from transformers.testing_utils import require_tf
if is_tf_available():
import tensorflow as tf
from transformers import TensorFlowBenchmark, TensorFlowBenchmarkArguments
... | 36 | 1 |
import cva
import numpy as np
class UpperCAmelCase_ :
'''simple docstring'''
def __init__( self , _SCREAMING_SNAKE_CASE , _SCREAMING_SNAKE_CASE ) -> int:
if k in (0.04, 0.06):
snake_case_ : Optional[int] = k
snake_case_ :... | 36 |
import argparse
import copy
def lowerCAmelCase__ ( _a : List[Any] ):
snake_case_ : List[Any] = {}
with open(_a ) as f:
for line in f:
if line.split()[0] not in dict_of_neighbours:
snake_case_ : int = []
_list.append([line.spl... | 36 | 1 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
lowercase : str = {
'''configuration_nllb_moe''': [
'''NLLB_MOE_PRETRAINED_CONFIG_ARCHIVE_MAP''',
'''NllbMoeConfig''',
]
}
try:
if not i... | 36 |
from typing import TYPE_CHECKING
from ...file_utils import _LazyModule, is_tokenizers_available, is_torch_available
from ...utils import OptionalDependencyNotAvailable
lowercase : Any = {'''configuration_gpt_neox''': ['''GPT_NEOX_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''GPTNeoXConfig''']}
... | 36 | 1 |
import argparse
import json
import subprocess
def lowerCAmelCase__ ( _a : Optional[Any] , _a : Optional[Any] ):
snake_case_ : int = []
snake_case_ : Optional[int] = (
F'''curl -H "Accept: application/vnd.github+json" -H "Authorization: Bea... | 36 |
def lowerCAmelCase__ ( _a : float , _a : float ):
if density <= 0:
raise ValueError("Impossible fluid density" )
if bulk_modulus <= 0:
raise ValueError("Impossible bulk modulus" )
return (bulk_modulus / density) ** 0.5
if __name__ == "__main__":
... | 36 | 1 |
import fire
from torch.utils.data import DataLoader
from tqdm import tqdm
from transformers import AutoTokenizer
from utils import SeqaSeqDataset, pickle_save
def lowerCAmelCase__ ( _a : List[str] , _a : str , _a : Dict=10_24 , _a : str=10_24 , _a : ... | 36 |
def lowerCAmelCase__ ( _a : int = 50 ):
snake_case_ : Union[str, Any] = [1] * (length + 1)
for row_length in range(3 , length + 1 ):
for block_length in range(3 , row_length + 1 ):
for block_start in range(row_length - block_length ):
... | 36 | 1 |
from typing import Optional
import torch
import torch.utils.checkpoint
from torch import Tensor, nn
from torch.nn import BCEWithLogitsLoss, CrossEntropyLoss, MSELoss
from ...activations import ACTaFN
from ...modeling_outputs import (
BackboneOutput,
BaseModelOutputWithNoAttention,
BaseModelOutputWi... | 36 |
import json
from typing import TYPE_CHECKING, List, Optional, Tuple
from tokenizers import pre_tokenizers
from ...tokenization_utils_base import BatchEncoding
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import logging
from .tokenization_gpta import GPTaTokenizer
if TYPE_CHECK... | 36 | 1 |
import argparse
import logging
import os
from pathlib import Path
from typing import Any, Dict
import pytorch_lightning as pl
from pytorch_lightning.utilities import rank_zero_info
from transformers import (
AdamW,
AutoConfig,
AutoModel,
AutoModelForPreTraining,
AutoModelForQuestionAnswerin... | 36 |
import datasets
from .evaluate import evaluate
lowercase : Dict = '''\
@article{hendrycks2021cuad,
title={CUAD: An Expert-Annotated NLP Dataset for Legal Contract Review},
author={Dan Hendrycks and Collin Burns and Anya Chen and Spencer Ball},
journal={arXiv preprint ... | 36 | 1 |
from collections import OrderedDict
from typing import Mapping
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
lowercase : str = logging.get_logger(__name__)
lowercase : Optional[Any] = {
'''ca... | 36 |
from ...utils import (
OptionalDependencyNotAvailable,
is_torch_available,
is_transformers_available,
is_transformers_version,
)
try:
if not (is_transformers_available() and is_torch_available() and is_transformers_version('''>=''', '''4.25.0''')):
raise OptionalDependencyN... | 36 | 1 |
from typing import TYPE_CHECKING
from ...utils import _LazyModule
lowercase : int = {'''tokenization_wav2vec2_phoneme''': ['''Wav2Vec2PhonemeCTCTokenizer''']}
if TYPE_CHECKING:
from .tokenization_wavaveca_phoneme import WavaVecaPhonemeCTCTokenizer
else:
import sys
... | 36 |
def lowerCAmelCase__ ( _a : dict ):
snake_case_ : List[Any] = set()
# edges = list of graph's edges
snake_case_ : int = get_edges(_a )
# While there are still elements in edges list, take an arbitrary edge
# (from_node, to_node) and add his extre... | 36 | 1 |
import inspect
import tempfile
from collections import OrderedDict, UserDict
from collections.abc import MutableMapping
from contextlib import ExitStack, contextmanager
from dataclasses import fields
from enum import Enum
from typing import Any, ContextManager, List, Tuple
import numpy as np
from .import_utils... | 36 |
import numpy as np
def lowerCAmelCase__ ( _a : np.array ):
return (2 / (1 + np.exp(-2 * vector ))) - 1
if __name__ == "__main__":
import doctest
doctest.testmod()
| 36 | 1 |
import warnings
from typing import List, Optional, Union
from ...processing_utils import ProcessorMixin
from ...tokenization_utils_base import BatchEncoding, PaddingStrategy, PreTokenizedInput, TextInput, TruncationStrategy
from ...utils import TensorType
class UpperCAmelCase_ ( SCREAMING_SNAKE_CASE... | 36 |
import os
import time
import pytest
from datasets.utils.filelock import FileLock, Timeout
def lowerCAmelCase__ ( _a : str ):
snake_case_ : str = FileLock(str(tmpdir / "foo.lock" ) )
snake_case_ : Optional[Any] = FileLock(str(tmpdir / "foo.lock" ... | 36 | 1 |
import argparse
import json
from typing import List
from ltp import LTP
from transformers import BertTokenizer
def lowerCAmelCase__ ( _a : Optional[int] ):
# This defines a "chinese character" as anything in the CJK Unicode block:
# https://en.wikipedia.org/wiki/CJK_Unified_Ideo... | 36 |
from __future__ import annotations
def lowerCAmelCase__ ( _a : str , _a : str ):
snake_case_ : Optional[Any] = get_failure_array(_a )
# 2) Step through text searching for pattern
snake_case_ , snake_case_ : Dict = 0, 0 # index into te... | 36 | 1 |
# Copyright (c) 2021-, 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.apache.org/licenses/LICENSE-2.0
#
# Unless required ... | 36 |
import importlib
import sys
from argparse import REMAINDER, ArgumentParser
from pathlib import Path
import torch_xla.distributed.xla_multiprocessing as xmp
def lowerCAmelCase__ ( ):
snake_case_ : str = ArgumentParser(
description=(
"PyTorch TPU distributed training l... | 36 | 1 |
import gc
import random
import unittest
import numpy as np
import torch
from PIL import Image
from transformers import CLIPTextConfig, CLIPTextModel, CLIPTokenizer
from diffusers import AutoencoderKL, PNDMScheduler, StableDiffusionInpaintPipeline, UNetaDConditionModel
from diffusers.utils import floats_tensor,... | 36 |
import argparse
import os
import re
# All paths are set with the intent you should run this script from the root of the repo with the command
# python utils/check_dummies.py
lowercase : Optional[Any] = '''src/diffusers'''
# Matches is_xxx_available()
lowercase : Any ... | 36 | 1 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
lowercase : Union[str, Any] = logging.get_logger(__name__)
class UpperCAmelCase_ ( SCREAMING_SNAKE_CASE_ ):
'''simple docstring'''
A : Union[str, Any] = 't... | 350 |
lowercase : Optional[int] = {
'''Pillow''': '''Pillow''',
'''accelerate''': '''accelerate>=0.11.0''',
'''compel''': '''compel==0.1.8''',
'''black''': '''black~=23.1''',
'''datasets''': '''datasets''',
'''filelock''': '''filelock''',
'''flax''': '''flax>=0.4.1''... | 36 | 0 |
from datetime import datetime as dt
import os
from github import Github
lowercase : Optional[Any] = [
'''good first issue''',
'''good second issue''',
'''good difficult issue''',
'''feature request''',
'''new model''',
'''wip''',
]
def lowerCAmelCase__ ... | 351 |
from ...processing_utils import ProcessorMixin
from ...tokenization_utils_base import BatchEncoding
class UpperCAmelCase_ ( SCREAMING_SNAKE_CASE__ ):
'''simple docstring'''
A : Tuple = ['image_processor', 'tokenizer']
A : Tuple = 'AutoIm... | 36 | 0 |
from typing import Dict
from .base import GenericTensor, Pipeline
class UpperCAmelCase_ ( _UpperCAmelCase ):
'''simple docstring'''
def _lowerCAmelCase ( self , _SCREAMING_SNAKE_CASE=None , _SCREAMING_SNAKE_CASE=None , _SCREAMING_SNAKE_CASE=None , ... | 352 |
import os
import unittest
from transformers import MobileBertTokenizer, MobileBertTokenizerFast
from transformers.models.bert.tokenization_bert import (
VOCAB_FILES_NAMES,
BasicTokenizer,
WordpieceTokenizer,
_is_control,
_is_punctuation,
_is_whitespace,
)
from transformers.testing_utils ... | 36 | 0 |
from ..utils import DummyObject, requires_backends
class UpperCAmelCase_ ( metaclass=A__ ):
'''simple docstring'''
A : Union[str, Any] = ['transformers', 'torch', 'note_seq']
def __init__( self , *_SCREAMING_SNAKE_CASE , **_SCREAMING_SNAKE_C... | 353 |
import unittest
import numpy as np
from transformers import BertConfig, is_flax_available
from transformers.testing_utils import require_flax, slow
from ...test_modeling_flax_common import FlaxModelTesterMixin, floats_tensor, ids_tensor, random_attention_mask
if is_flax_available():
from transformers... | 36 | 0 |
import argparse
import pickle
import numpy as np
import torch
from torch import nn
from transformers import ReformerConfig, ReformerModelWithLMHead
from transformers.utils import logging
logging.set_verbosity_info()
def lowerCAmelCase__ ( _a : Union[str, Any] , _a : Dict ,... | 354 |
import copy
from collections import OrderedDict
from typing import Mapping
from packaging import version
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
from ..auto import CONFIG_MAPPING
lowercase : List[Any] = logging.ge... | 36 | 0 |
from typing import TYPE_CHECKING
# rely on isort to merge the imports
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available, is_vision_available
lowercase : Union[str, Any] = {
'''configuration_efficientnet''': [
'''EFFICIENTNET_PRETRAINED_CO... | 355 |
from typing import Dict, List, Optional, Union
import numpy as np
from ...image_processing_utils import BaseImageProcessor, BatchFeature, get_size_dict
from ...image_transforms import center_crop, normalize, rescale, resize, to_channel_dimension_format
from ...image_utils import (
IMAGENET_STANDARD_MEAN,
... | 36 | 0 |
from unittest import TestCase
from datasets import Dataset
from minhash_deduplication import deduplicate_dataset, make_duplicate_clusters
def lowerCAmelCase__ ( ):
snake_case_ : Optional[Any] = {
"repo_name": ["test_repo1", "test_repo2", "test_repo3"],
"path": ["test_1.p... | 356 |
import shutil
import tempfile
import unittest
from unittest.mock import patch
from transformers import (
DefaultFlowCallback,
IntervalStrategy,
PrinterCallback,
ProgressCallback,
Trainer,
TrainerCallback,
TrainingArguments,
is_torch_available,
)
from transformers.testing_utils im... | 36 | 0 |
import sys
def lowerCAmelCase__ ( _a : int ):
snake_case_ : int = len(__A )
snake_case_ : int = [[0 for x in range(__A )] for x in range(__A )]
snake_case_ : Dict = [[0 for x in range(__A )] for x in range(__A )]
f... | 357 |
import json
import os
import unittest
from transformers import DebertaTokenizer, DebertaTokenizerFast
from transformers.models.deberta.tokenization_deberta import VOCAB_FILES_NAMES
from transformers.testing_utils import slow
from ...test_tokenization_common import TokenizerTesterMixin
class UpperCAme... | 36 | 0 |
def lowerCAmelCase__ ( _a : int = 2_00 ):
snake_case_ : Dict = [1, 2, 5, 10, 20, 50, 1_00, 2_00]
snake_case_ : Optional[Any] = [0] * (pence + 1)
snake_case_ : Optional[int] = 1 # base case: 1 way to make 0 pence
for coin in coins:
for ... | 358 |
import os
import tempfile
import unittest
from pathlib import Path
from transformers import AutoConfig, is_tf_available
from transformers.testing_utils import require_tf
if is_tf_available():
import tensorflow as tf
from transformers import TensorFlowBenchmark, TensorFlowBenchmarkArguments
... | 36 | 0 |
"""simple docstring"""
import numpy as np
from scipy.spatial.distance import cdist
from sklearn.metrics import fa_score
import datasets
lowercase : Tuple = """\
@inproceedings{kakwani2020indicnlpsuite,
title={{IndicNLPSuite: Monolingual Corpora, Evaluation Benchmarks and Pr... | 359 |
import argparse
import copy
def lowerCAmelCase__ ( _a : List[Any] ):
snake_case_ : List[Any] = {}
with open(_a ) as f:
for line in f:
if line.split()[0] not in dict_of_neighbours:
snake_case_ : int = []
_list.append([line.spl... | 36 | 0 |
from pathlib import Path
from typing import List
from transformers import is_torch_available, is_vision_available
from transformers.testing_utils import get_tests_dir, is_tool_test
from transformers.tools.agent_types import AGENT_TYPE_MAPPING, AgentAudio, AgentImage, AgentText
if is_torch_available():
import... | 360 |
from typing import TYPE_CHECKING
from ...file_utils import _LazyModule, is_tokenizers_available, is_torch_available
from ...utils import OptionalDependencyNotAvailable
lowercase : Any = {'''configuration_gpt_neox''': ['''GPT_NEOX_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''GPTNeoXConfig''']}
... | 36 | 0 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_torch_available,
)
lowercase : int = {
'''configuration_mega''': ['''MEGA_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''MegaConfig''', '''MegaOnnxConfig'''],
}
try:
if... | 361 |
def lowerCAmelCase__ ( _a : float , _a : float ):
if density <= 0:
raise ValueError("Impossible fluid density" )
if bulk_modulus <= 0:
raise ValueError("Impossible bulk modulus" )
return (bulk_modulus / density) ** 0.5
if __name__ == "__main__":
... | 36 | 0 |
import json
import os
import unittest
from transformers import CLIPTokenizer, CLIPTokenizerFast
from transformers.models.clip.tokenization_clip import VOCAB_FILES_NAMES
from transformers.testing_utils import require_ftfy, require_tokenizers
from ...test_tokenization_common import TokenizerTesterMixin
@requ... | 362 |
def lowerCAmelCase__ ( _a : int = 50 ):
snake_case_ : Union[str, Any] = [1] * (length + 1)
for row_length in range(3 , length + 1 ):
for block_length in range(3 , row_length + 1 ):
for block_start in range(row_length - block_length ):
... | 36 | 0 |
import random
import unittest
import torch
from diffusers import IFInpaintingSuperResolutionPipeline
from diffusers.utils import floats_tensor
from diffusers.utils.import_utils import is_xformers_available
from diffusers.utils.testing_utils import skip_mps, torch_device
from ..pipeline_params import (
TEX... | 363 |
import json
from typing import TYPE_CHECKING, List, Optional, Tuple
from tokenizers import pre_tokenizers
from ...tokenization_utils_base import BatchEncoding
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import logging
from .tokenization_gpta import GPTaTokenizer
if TYPE_CHECK... | 36 | 0 |
import json
import os
import tempfile
import transformers
import datasets
from utils import generate_example_dataset, get_duration
lowercase : Union[str, Any] = 50_00_00
lowercase ,lowercase : Union[str, Any] = os.path.split(__file__)
lowercase : ... | 364 |
import datasets
from .evaluate import evaluate
lowercase : Dict = '''\
@article{hendrycks2021cuad,
title={CUAD: An Expert-Annotated NLP Dataset for Legal Contract Review},
author={Dan Hendrycks and Collin Burns and Anya Chen and Spencer Ball},
journal={arXiv preprint ... | 36 | 0 |
import argparse
import os
import shutil
import torch
from emmental.modules import MagnitudeBinarizer, ThresholdBinarizer, TopKBinarizer
def lowerCAmelCase__ ( _a : List[str] ):
snake_case_ : List[Any] = args.pruning_method
snake_case_ : Tuple = args.thresh... | 365 |
from ...utils import (
OptionalDependencyNotAvailable,
is_torch_available,
is_transformers_available,
is_transformers_version,
)
try:
if not (is_transformers_available() and is_torch_available() and is_transformers_version('''>=''', '''4.25.0''')):
raise OptionalDependencyN... | 36 | 0 |
from functools import lru_cache
def lowerCAmelCase__ ( _a : int ):
snake_case_ : Tuple = 2
snake_case_ : int = set()
while i * i <= n:
if n % i:
i += 1
else:
n //= i
factors.add(lowerCAmelCase__ )
if n > 1:
factors.add... | 366 |
def lowerCAmelCase__ ( _a : dict ):
snake_case_ : List[Any] = set()
# edges = list of graph's edges
snake_case_ : int = get_edges(_a )
# While there are still elements in edges list, take an arbitrary edge
# (from_node, to_node) and add his extre... | 36 | 0 |
import functools
import gc
import inspect
import torch
from .imports import is_npu_available, is_xpu_available
def lowerCAmelCase__ ( *_a : str ):
if not isinstance(a_ , a_ ):
snake_case_ : Optional[int] = list(a_ )
for i in range(len(a_ ) ... | 367 |
import numpy as np
def lowerCAmelCase__ ( _a : np.array ):
return (2 / (1 + np.exp(-2 * vector ))) - 1
if __name__ == "__main__":
import doctest
doctest.testmod()
| 36 | 0 |
from operator import delitem, getitem, setitem
import pytest
from data_structures.hashing.hash_map import HashMap
def lowerCAmelCase__ ( _a : Optional[Any] ):
return getitem, k
def lowerCAmelCase__ ( _a : str , _a : int ):
return seti... | 368 |
import os
import time
import pytest
from datasets.utils.filelock import FileLock, Timeout
def lowerCAmelCase__ ( _a : str ):
snake_case_ : str = FileLock(str(tmpdir / "foo.lock" ) )
snake_case_ : Optional[Any] = FileLock(str(tmpdir / "foo.lock" ... | 36 | 0 |
import os
import re
from shutil import copyfile
from typing import Any, Dict, List, Optional, Tuple
import sentencepiece as spm
from ...tokenization_utils import AddedToken, PreTrainedTokenizer
from ...utils import logging
lowercase : str = logging.get_logger(__name__)
lowercase ... | 369 |
from __future__ import annotations
def lowerCAmelCase__ ( _a : str , _a : str ):
snake_case_ : Optional[Any] = get_failure_array(_a )
# 2) Step through text searching for pattern
snake_case_ , snake_case_ : Dict = 0, 0 # index into te... | 36 | 0 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
lowercase : Optional[int] = logging.get_logger(__name__)
lowercase : Tuple = {
'''microsoft/trocr-base-handwritten''': (
'''https://huggingface.co/microsoft/trocr-base-h... | 370 |
import importlib
import sys
from argparse import REMAINDER, ArgumentParser
from pathlib import Path
import torch_xla.distributed.xla_multiprocessing as xmp
def lowerCAmelCase__ ( ):
snake_case_ : str = ArgumentParser(
description=(
"PyTorch TPU distributed training l... | 36 | 0 |
import collections
import tempfile
import unittest
import numpy as np
from transformers.testing_utils import (
is_pt_flax_cross_test,
require_flax,
require_torch,
require_vision,
slow,
torch_device,
)
from transformers.utils import is_flax_available, is_torch_available, is_vision_availa... | 371 |
import argparse
import os
import re
# All paths are set with the intent you should run this script from the root of the repo with the command
# python utils/check_dummies.py
lowercase : Optional[Any] = '''src/diffusers'''
# Matches is_xxx_available()
lowercase : Any ... | 36 | 0 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tf_available,
is_tokenizers_available,
is_torch_available,
is_vision_available,
)
lowercase : List[str] = {
'''configuration_owlvit... | 350 |
lowercase : Optional[int] = {
'''Pillow''': '''Pillow''',
'''accelerate''': '''accelerate>=0.11.0''',
'''compel''': '''compel==0.1.8''',
'''black''': '''black~=23.1''',
'''datasets''': '''datasets''',
'''filelock''': '''filelock''',
'''flax''': '''flax>=0.4.1''... | 36 | 0 |
import os
from shutil import copyfile
from typing import List, Optional, Tuple
from ...tokenization_utils import AddedToken
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import is_sentencepiece_available, logging
if is_sentencepiece_available():
from .tokenization_camembe... | 351 |
from ...processing_utils import ProcessorMixin
from ...tokenization_utils_base import BatchEncoding
class UpperCAmelCase_ ( SCREAMING_SNAKE_CASE__ ):
'''simple docstring'''
A : Tuple = ['image_processor', 'tokenizer']
A : Tuple = 'AutoIm... | 36 | 0 |
import os
import random
import sys
from . import cryptomath_module as cryptoMath # noqa: N812
from . import rabin_miller as rabinMiller # noqa: N812
def lowerCAmelCase__ ( ):
print("Making key files..." )
make_key_files("rsa" , 10_24 )
print("Key files generation successful."... | 352 |
import os
import unittest
from transformers import MobileBertTokenizer, MobileBertTokenizerFast
from transformers.models.bert.tokenization_bert import (
VOCAB_FILES_NAMES,
BasicTokenizer,
WordpieceTokenizer,
_is_control,
_is_punctuation,
_is_whitespace,
)
from transformers.testing_utils ... | 36 | 0 |
import gc
import random
import unittest
import torch
from diffusers import (
IFImgaImgPipeline,
IFImgaImgSuperResolutionPipeline,
IFInpaintingPipeline,
IFInpaintingSuperResolutionPipeline,
IFPipeline,
IFSuperResolutionPipeline,
)
from diffusers.models.attention_processor import AttnAddedKVPro... | 353 |
import unittest
import numpy as np
from transformers import BertConfig, is_flax_available
from transformers.testing_utils import require_flax, slow
from ...test_modeling_flax_common import FlaxModelTesterMixin, floats_tensor, ids_tensor, random_attention_mask
if is_flax_available():
from transformers... | 36 | 0 |
import unittest
import numpy as np
from transformers.testing_utils import require_torch, require_vision
from transformers.utils import is_torch_available, is_vision_available
from ...test_image_processing_common import ImageProcessingSavingTestMixin, prepare_image_inputs
if is_torch_available():
import ... | 354 |
import copy
from collections import OrderedDict
from typing import Mapping
from packaging import version
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
from ..auto import CONFIG_MAPPING
lowercase : List[Any] = logging.ge... | 36 | 0 |
def lowerCAmelCase__ ( _a : int ):
snake_case_ : Optional[Any] = [], []
while len(snake_case_ ) > 1:
snake_case_ : Optional[Any] = min(snake_case_ ), max(snake_case_ )
start.append(snake_case_ )
end.append(snake_case_ )
... | 355 |
from typing import Dict, List, Optional, Union
import numpy as np
from ...image_processing_utils import BaseImageProcessor, BatchFeature, get_size_dict
from ...image_transforms import center_crop, normalize, rescale, resize, to_channel_dimension_format
from ...image_utils import (
IMAGENET_STANDARD_MEAN,
... | 36 | 0 |
from copy import deepcopy
from typing import Optional, Union
import numpy as np
from ...processing_utils import ProcessorMixin
from ...tokenization_utils_base import BatchEncoding
from ...utils import TensorType, is_tf_available, is_torch_available
if is_torch_available():
import torch
if is_tf_avail... | 356 |
import shutil
import tempfile
import unittest
from unittest.mock import patch
from transformers import (
DefaultFlowCallback,
IntervalStrategy,
PrinterCallback,
ProgressCallback,
Trainer,
TrainerCallback,
TrainingArguments,
is_torch_available,
)
from transformers.testing_utils im... | 36 | 0 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
lowercase : Union[str, Any] = logging.get_logger(__name__)
lowercase : List[Any] = {
'''studio-ousia/luke-base''': '''https://huggingface.co/studio-ousia/luke-base/resolve/main/... | 357 |
import json
import os
import unittest
from transformers import DebertaTokenizer, DebertaTokenizerFast
from transformers.models.deberta.tokenization_deberta import VOCAB_FILES_NAMES
from transformers.testing_utils import slow
from ...test_tokenization_common import TokenizerTesterMixin
class UpperCAme... | 36 | 0 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tf_available,
is_tokenizers_available,
is_torch_available,
)
lowercase : Dict = {
'''configuration_whisper''': ['''WHISPER_PRETRAINED_C... | 358 |
import os
import tempfile
import unittest
from pathlib import Path
from transformers import AutoConfig, is_tf_available
from transformers.testing_utils import require_tf
if is_tf_available():
import tensorflow as tf
from transformers import TensorFlowBenchmark, TensorFlowBenchmarkArguments
... | 36 | 0 |
"""simple docstring"""
import unittest
import numpy as np
import timeout_decorator # noqa
from transformers import BlenderbotSmallConfig, is_flax_available
from transformers.testing_utils import require_flax, slow
from ...generation.test_flax_utils import FlaxGenerationTesterMixin
from ...test_modeling_f... | 359 |
import argparse
import copy
def lowerCAmelCase__ ( _a : List[Any] ):
snake_case_ : List[Any] = {}
with open(_a ) as f:
for line in f:
if line.split()[0] not in dict_of_neighbours:
snake_case_ : int = []
_list.append([line.spl... | 36 | 0 |
import io
import json
import fsspec
import pytest
from datasets import Dataset, DatasetDict, Features, NamedSplit, Value
from datasets.io.json import JsonDatasetReader, JsonDatasetWriter
from ..utils import assert_arrow_memory_doesnt_increase, assert_arrow_memory_increases
def lowerCAmelCase__ ( ... | 360 |
from typing import TYPE_CHECKING
from ...file_utils import _LazyModule, is_tokenizers_available, is_torch_available
from ...utils import OptionalDependencyNotAvailable
lowercase : Any = {'''configuration_gpt_neox''': ['''GPT_NEOX_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''GPTNeoXConfig''']}
... | 36 | 0 |
import argparse
from transformers import (
TapasConfig,
TapasForMaskedLM,
TapasForQuestionAnswering,
TapasForSequenceClassification,
TapasModel,
TapasTokenizer,
load_tf_weights_in_tapas,
)
from transformers.utils import logging
logging.set_verbosity_info()
def lowerCAmelCas... | 361 |
def lowerCAmelCase__ ( _a : float , _a : float ):
if density <= 0:
raise ValueError("Impossible fluid density" )
if bulk_modulus <= 0:
raise ValueError("Impossible bulk modulus" )
return (bulk_modulus / density) ** 0.5
if __name__ == "__main__":
... | 36 | 0 |
def lowerCAmelCase__ ( _a : Optional[int] ):
if number < 0:
raise ValueError("number must not be negative" )
return number & (number - 1) == 0
if __name__ == "__main__":
import doctest
doctest.testmod()
| 362 |
def lowerCAmelCase__ ( _a : int = 50 ):
snake_case_ : Union[str, Any] = [1] * (length + 1)
for row_length in range(3 , length + 1 ):
for block_length in range(3 , row_length + 1 ):
for block_start in range(row_length - block_length ):
... | 36 | 0 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
lowercase : Tuple = logging.get_logger(__name__)
lowercase : Any = {
'''EleutherAI/gpt-neox-20b''': '''https://huggingface.co/EleutherAI/gpt-neox-20b/resolve/main/config.json'''... | 363 |
import json
from typing import TYPE_CHECKING, List, Optional, Tuple
from tokenizers import pre_tokenizers
from ...tokenization_utils_base import BatchEncoding
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import logging
from .tokenization_gpta import GPTaTokenizer
if TYPE_CHECK... | 36 | 0 |
import json
import os
import subprocess
import unittest
from ast import literal_eval
import pytest
from parameterized import parameterized, parameterized_class
from . import is_sagemaker_available
if is_sagemaker_available():
from sagemaker import Session, TrainingJobAnalytics
from sagemaker.hu... | 364 |
import datasets
from .evaluate import evaluate
lowercase : Dict = '''\
@article{hendrycks2021cuad,
title={CUAD: An Expert-Annotated NLP Dataset for Legal Contract Review},
author={Dan Hendrycks and Collin Burns and Anya Chen and Spencer Ball},
journal={arXiv preprint ... | 36 | 0 |
import unittest
from transformers import AlbertConfig, is_torch_available
from transformers.models.auto import get_values
from transformers.testing_utils import require_torch, slow, torch_device
from ...test_configuration_common import ConfigTester
from ...test_modeling_common import ModelTesterMixin, ids_tens... | 365 |
from ...utils import (
OptionalDependencyNotAvailable,
is_torch_available,
is_transformers_available,
is_transformers_version,
)
try:
if not (is_transformers_available() and is_torch_available() and is_transformers_version('''>=''', '''4.25.0''')):
raise OptionalDependencyN... | 36 | 0 |
import gc
import math
import unittest
import torch
from diffusers import UNetaDModel
from diffusers.utils import floats_tensor, logging, slow, torch_all_close, torch_device
from diffusers.utils.testing_utils import enable_full_determinism
from .test_modeling_common import ModelTesterMixin, UNetTesterMixin
l... | 366 |
def lowerCAmelCase__ ( _a : dict ):
snake_case_ : List[Any] = set()
# edges = list of graph's edges
snake_case_ : int = get_edges(_a )
# While there are still elements in edges list, take an arbitrary edge
# (from_node, to_node) and add his extre... | 36 | 0 |
import argparse
from copy import deepcopy
import numpy as np
from datasets import ClassLabel, DatasetDict, load_dataset
from evaluate import load
from transformers import (
AutoModelForSequenceClassification,
AutoTokenizer,
DataCollatorWithPadding,
Trainer,
TrainerCallback,
TrainingArgu... | 367 |
import numpy as np
def lowerCAmelCase__ ( _a : np.array ):
return (2 / (1 + np.exp(-2 * vector ))) - 1
if __name__ == "__main__":
import doctest
doctest.testmod()
| 36 | 0 |
def lowerCAmelCase__ ( _a : int = 10_00 ):
snake_case_ : Dict = -1
snake_case_ : str = 0
for a in range(1 , n // 3 ):
# Solving the two equations a**2+b**2=c**2 and a+b+c=N eliminating c
snake_case_ : List[Any] = (n * n - 2 * ... | 368 |
import os
import time
import pytest
from datasets.utils.filelock import FileLock, Timeout
def lowerCAmelCase__ ( _a : str ):
snake_case_ : str = FileLock(str(tmpdir / "foo.lock" ) )
snake_case_ : Optional[Any] = FileLock(str(tmpdir / "foo.lock" ... | 36 | 0 |
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