code stringlengths 81 54k | code_codestyle int64 0 721 | style_context stringlengths 91 41.9k | style_context_codestyle int64 0 699 | label int64 0 1 |
|---|---|---|---|---|
"""simple docstring"""
import baseaa
import io
import json
import os
from copy import deepcopy
from ..optimizer import AcceleratedOptimizer
from ..scheduler import AcceleratedScheduler
class __lowercase :
"""simple docstring"""
def __init__(self , lowercase__ ):
... | 48 |
"""simple docstring"""
import copy
from dataclasses import dataclass, field
from typing import ClassVar, Dict
from ..features import Audio, Features, Value
from .base import TaskTemplate
@dataclass(frozen=_UpperCAmelCase)
class __lowercase ( _UpperCAmelCase):
"""simple docstring"""
... | 48 | 1 |
"""simple docstring"""
from __future__ import annotations
import math
import random
from collections.abc import Collection
from typing import overload
class __lowercase :
"""simple docstring"""
def __init__(self , lowercase__ = None ):
if components is N... | 48 |
"""simple docstring"""
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,
get_resize_output_image_size,
normalize,
rescale,
resize,
to_channe... | 48 | 1 |
"""simple docstring"""
# Copyright 2023 The HuggingFace Inc. 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... | 48 |
"""simple docstring"""
import os
from shutil import copyfile
from typing import List, Optional, Tuple
from tokenizers import processors
from ...tokenization_utils import AddedToken, BatchEncoding
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import is_sentencepiece_available, loggi... | 48 | 1 |
"""simple docstring"""
def SCREAMING_SNAKE_CASE__ ( SCREAMING_SNAKE_CASE__ : int = 5_0 ):
"""simple docstring"""
snake_case_ : Optional[Any] = [[0] * 3 for _ in range(length + 1 )]
for row_length in range(length + 1 ):
for tile_length in range(2 ... | 48 |
"""simple docstring"""
import argparse
import hashlib # hashlib is only used inside the Test class
import struct
class __lowercase :
"""simple docstring"""
def __init__(self , lowercase__ ):
snake_case_ : Union[str, Any] = data
s... | 48 | 1 |
"""simple docstring"""
import copy
import random
from transformers import CLIPTokenizer
class __lowercase ( _UpperCAmelCase):
"""simple docstring"""
def __init__(self , *lowercase__ , **lowercase__ ):
super().__init__(*lowercase__ , **lowercase... | 48 |
"""simple docstring"""
from manim import *
class __lowercase ( _UpperCAmelCase):
"""simple docstring"""
def __UpperCamelCase (self ):
snake_case_ : Union[str, Any] = Rectangle(height=0.5 , width=0.5 )
snake_c... | 48 | 1 |
"""simple docstring"""
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_ava... | 48 |
"""simple docstring"""
from random import randint
from tempfile import TemporaryFile
import numpy as np
def SCREAMING_SNAKE_CASE__ ( SCREAMING_SNAKE_CASE__ : List[Any] , SCREAMING_SNAKE_CASE__ : Dict , SCREAMING_SNAKE_CASE__ : Optional[int] ):
"""simple docstring"""
... | 48 | 1 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available, is_vision_available
a_ = {
'''configuration_conditional_detr''': [
'''CONDITIONAL_DETR_PRETRAINED_CONFIG_ARCHIVE_MAP''',
'''ConditionalDetrCo... | 48 |
"""simple docstring"""
import random
def SCREAMING_SNAKE_CASE__ ( SCREAMING_SNAKE_CASE__ : int , SCREAMING_SNAKE_CASE__ : float , SCREAMING_SNAKE_CASE__ : bool = False ):
"""simple docstring"""
snake_case_ : dict = {i: [] for i in range(SCREAMING... | 48 | 1 |
"""simple docstring"""
from ..utils import DummyObject, requires_backends
class __lowercase ( metaclass=_UpperCAmelCase):
"""simple docstring"""
_A : Tuple = ["""onnx"""]
def __init__(self , *lowercase__ , **lowercase__ ):
... | 48 |
"""simple docstring"""
from ...configuration_utils import PretrainedConfig
from ...utils import logging
a_ = logging.get_logger(__name__)
a_ = {
'''facebook/dpr-ctx_encoder-single-nq-base''': (
'''https://huggingface.co/facebook/dpr-ctx_encoder-single-nq-base/resolve/main/config.js... | 48 | 1 |
"""simple docstring"""
import random
def SCREAMING_SNAKE_CASE__ ( SCREAMING_SNAKE_CASE__ : int ):
"""simple docstring"""
snake_case_ : Union[str, Any] = num - 1
snake_case_ : List[str] = 0
while s % 2 == 0:
snake_case_ : ... | 48 |
"""simple docstring"""
import json
import multiprocessing as mp
import re
from collections import defaultdict
from functools import partial
from typing import Dict, List, Optional, Set, Tuple, Type
from datasets import Dataset
from datasketch import MinHash, MinHashLSH
from dpu_utils.utils.iterators import Thread... | 48 | 1 |
"""simple docstring"""
import warnings
from ...processing_utils import ProcessorMixin
from ...tokenization_utils_base import BatchEncoding
class __lowercase ( _UpperCAmelCase):
"""simple docstring"""
_A : Union[str, Any] = ["""image_processor""", ""... | 48 |
"""simple docstring"""
import argparse
import logging
import pickle
from collections import Counter
logging.basicConfig(
format='''%(asctime)s - %(levelname)s - %(name)s - %(message)s''', datefmt='''%m/%d/%Y %H:%M:%S''', level=logging.INFO
)
a_ = logging.getLogger(__name__)
if __name__ == "__main__... | 48 | 1 |
"""simple docstring"""
import sys
from .dependency_versions_table import deps
from .utils.versions import require_version, require_version_core
# define which module versions we always want to check at run time
# (usually the ones defined in `install_requires` in setup.py)
#
# order specific notes:
# - tqdm mus... | 48 |
"""simple docstring"""
import pytest
from datasets import Dataset, DatasetDict, Features, NamedSplit, Value
from datasets.io.text import TextDatasetReader
from ..utils import assert_arrow_memory_doesnt_increase, assert_arrow_memory_increases
def SCREAMING_SNAKE_CASE__ ( SCREAMING_SNAKE_CASE__... | 48 | 1 |
"""simple docstring"""
import argparse
import shutil
from pathlib import Path
from tqdm import tqdm
from transformers import AutoTokenizer
def SCREAMING_SNAKE_CASE__ ( SCREAMING_SNAKE_CASE__ : Any , SCREAMING_SNAKE_CASE__ : Dict , SCREAMING_SNAKE_CASE__ : Optional[Any] , ... | 48 |
"""simple docstring"""
from copy import deepcopy
class __lowercase :
"""simple docstring"""
def __init__(self , lowercase__ = None , lowercase__ = None ):
if arr is None and size is not None:
snake_case_ : str = size
... | 48 | 1 |
"""simple docstring"""
import logging
import os
from typing import List, TextIO, Union
from conllu import parse_incr
from utils_ner import InputExample, Split, TokenClassificationTask
a_ = logging.getLogger(__name__)
class __lowercase ( _UpperCAmelCase):
"""simple docstri... | 48 |
"""simple docstring"""
def SCREAMING_SNAKE_CASE__ ( SCREAMING_SNAKE_CASE__ : list ):
"""simple docstring"""
snake_case_ : Optional[int] = len(SCREAMING_SNAKE_CASE__ )
for i in range(1 , SCREAMING_SNAKE_CASE__ ):
snake_case_ : Tuple ... | 48 | 1 |
"""simple docstring"""
import inspect
import os
import re
from transformers.configuration_utils import PretrainedConfig
from transformers.utils import direct_transformers_import
# All paths are set with the intent you should run this script from the root of the repo with the command
# python utils/check_config_... | 48 |
"""simple docstring"""
import warnings
from ...processing_utils import ProcessorMixin
from ...tokenization_utils_base import BatchEncoding
class __lowercase ( _UpperCAmelCase):
"""simple docstring"""
_A : Union[str, Any] = ["""image_processor""", ""... | 48 | 1 |
"""simple docstring"""
import json
from typing import List, Optional, Tuple
from tokenizers import pre_tokenizers, processors
from ...tokenization_utils_base import AddedToken, BatchEncoding
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import logging
from .tokenization_bart import... | 48 |
"""simple docstring"""
import argparse
import copy
def SCREAMING_SNAKE_CASE__ ( SCREAMING_SNAKE_CASE__ : Any ):
"""simple docstring"""
snake_case_ : List[Any] = {}
with open(SCREAMING_SNAKE_CASE__ ) as f:
for line in f:
if line... | 48 | 1 |
"""simple docstring"""
import logging
import numpy as np
import pytest
from scipy.linalg import eigh
logging.basicConfig(level=logging.INFO, format='''%(message)s''')
def SCREAMING_SNAKE_CASE__ ( SCREAMING_SNAKE_CASE__ : np.ndarray ):
"""simple docstring"""
return input_a... | 48 |
"""simple docstring"""
import copy
from ...configuration_utils import PretrainedConfig
from ...utils import add_start_docstrings
a_ = r'''
[`RagConfig`] stores the configuration of a *RagModel*. Configuration objects inherit from [`PretrainedConfig`] and
can be used to control the model outputs... | 48 | 1 |
"""simple docstring"""
from typing import Dict
import numpy as np
from ..utils import add_end_docstrings, is_tf_available, is_torch_available, logging
from .base import PIPELINE_INIT_ARGS, GenericTensor, Pipeline, PipelineException
if is_tf_available():
import tensorflow as tf
from ..tf_utils import sta... | 48 |
"""simple docstring"""
import copy
from ...configuration_utils import PretrainedConfig
from ...utils import logging
from ..auto.configuration_auto import CONFIG_MAPPING
a_ = logging.get_logger(__name__)
class __lowercase ( _UpperCAmelCase):
"""simple docstring"""
... | 48 | 1 |
"""simple docstring"""
from typing import Any, Dict, List, Optional, Tuple, Union
import torch
from torch import nn
from torch.utils.data import DistributedSampler, RandomSampler
from transformers import PreTrainedModel, Trainer, logging
from transformers.integrations import is_fairscale_available
from transform... | 48 |
"""simple docstring"""
import logging
import os
from typing import List, TextIO, Union
from conllu import parse_incr
from utils_ner import InputExample, Split, TokenClassificationTask
a_ = logging.getLogger(__name__)
class __lowercase ( _UpperCAmelCase):
"""simple docstri... | 48 | 1 |
"""simple docstring"""
import unittest
from transformers import is_torch_available
from transformers.testing_utils import require_sentencepiece, require_tokenizers, require_torch, slow
if is_torch_available():
import torch
from transformers import XLMRobertaModel
@require_sentencepiece
@require_to... | 48 |
"""simple docstring"""
import random
def SCREAMING_SNAKE_CASE__ ( SCREAMING_SNAKE_CASE__ : int ):
"""simple docstring"""
snake_case_ : Union[str, Any] = num - 1
snake_case_ : List[str] = 0
while s % 2 == 0:
snake_case_ : ... | 48 | 1 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
a_ = {
'''configuration_git''': ['''GIT_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''GitConfig''', '''GitVisionConfig'''],
'''processing_git''': ['''GitProcessor'... | 48 |
"""simple docstring"""
from collections import OrderedDict
from typing import TYPE_CHECKING, Any, Mapping, Optional, Union
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
if TYPE_CHECKING:
from ... import FeatureExtractionMixin, PreTrainedTokeni... | 48 | 1 |
"""simple docstring"""
from typing import Callable, List, Optional, Tuple, Union
import torch
from transformers import CLIPTextModel, CLIPTokenizer
from ...configuration_utils import ConfigMixin, register_to_config
from ...models import ModelMixin, TransformeraDModel, VQModel
from ...schedulers import VQDiffusio... | 48 |
"""simple docstring"""
def SCREAMING_SNAKE_CASE__ ( SCREAMING_SNAKE_CASE__ : int , SCREAMING_SNAKE_CASE__ : int ):
"""simple docstring"""
return numa ^ numa < 0
if __name__ == "__main__":
import doctest
doctest.testmod()
| 48 | 1 |
"""simple docstring"""
# Lint as: python3
import dataclasses
import re
from dataclasses import dataclass
from functools import total_ordering
from typing import Optional, Union
a_ = re.compile(r'''^(?P<major>\d+)''' r'''\.(?P<minor>\d+)''' r'''\.(?P<patch>\d+)$''')
@total_ordering
@dataclass
clas... | 48 |
"""simple docstring"""
import tempfile
import unittest
from pathlib import Path
from shutil import copyfile
from transformers import BatchEncoding, MarianTokenizer
from transformers.testing_utils import get_tests_dir, require_sentencepiece, slow
from transformers.utils import is_sentencepiece_available, is_tf_ava... | 48 | 1 |
"""simple docstring"""
import argparse
import copy
def SCREAMING_SNAKE_CASE__ ( SCREAMING_SNAKE_CASE__ : Any ):
"""simple docstring"""
snake_case_ : List[Any] = {}
with open(SCREAMING_SNAKE_CASE__ ) as f:
for line in f:
if line... | 48 |
"""simple docstring"""
import copy
from dataclasses import dataclass, field
from typing import ClassVar, Dict
from ..features import Audio, Features, Value
from .base import TaskTemplate
@dataclass(frozen=_UpperCAmelCase)
class __lowercase ( _UpperCAmelCase):
"""simple docstring"""
... | 48 | 1 |
"""simple docstring"""
import argparse
from transformers import BigBirdConfig, BigBirdForPreTraining, BigBirdForQuestionAnswering, load_tf_weights_in_big_bird
from transformers.utils import logging
logging.set_verbosity_info()
def SCREAMING_SNAKE_CASE__ ( SCREAMING_SNAKE_CASE__ : List[str] ... | 48 |
"""simple docstring"""
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,
get_resize_output_image_size,
normalize,
rescale,
resize,
to_channe... | 48 | 1 |
"""simple docstring"""
import logging
import os
import quant_trainer
import torch
from torch.utils.data import DataLoader
from transformers import Trainer, is_torch_tpu_available
from transformers.trainer_utils import PredictionOutput
a_ = logging.getLogger(__name__)
if is_torch_tpu_available(check_d... | 48 |
"""simple docstring"""
import os
from shutil import copyfile
from typing import List, Optional, Tuple
from tokenizers import processors
from ...tokenization_utils import AddedToken, BatchEncoding
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import is_sentencepiece_available, loggi... | 48 | 1 |
"""simple docstring"""
from typing import Dict, Optional, Union
import numpy as np
from ...image_processing_utils import BaseImageProcessor, BatchFeature, get_size_dict
from ...image_transforms import flip_channel_order, resize, to_channel_dimension_format, to_pil_image
from ...image_utils import (
ChannelDi... | 48 |
"""simple docstring"""
import argparse
import hashlib # hashlib is only used inside the Test class
import struct
class __lowercase :
"""simple docstring"""
def __init__(self , lowercase__ ):
snake_case_ : Union[str, Any] = data
s... | 48 | 1 |
"""simple docstring"""
import argparse
from transformers import CLIPImageProcessor, CLIPVisionModelWithProjection
from diffusers import UnCLIPImageVariationPipeline, UnCLIPPipeline
if __name__ == "__main__":
a_ = argparse.ArgumentParser()
parser.add_argument('''--dump_path''', default=None, typ... | 48 |
"""simple docstring"""
from manim import *
class __lowercase ( _UpperCAmelCase):
"""simple docstring"""
def __UpperCamelCase (self ):
snake_case_ : Union[str, Any] = Rectangle(height=0.5 , width=0.5 )
snake_c... | 48 | 1 |
"""simple docstring"""
from ...configuration_utils import PretrainedConfig
from ...utils import logging
a_ = logging.get_logger(__name__)
a_ = {
'''microsoft/trocr-base-handwritten''': (
'''https://huggingface.co/microsoft/trocr-base-handwritten/resolve/main/config.json'''
),
... | 48 |
"""simple docstring"""
from random import randint
from tempfile import TemporaryFile
import numpy as np
def SCREAMING_SNAKE_CASE__ ( SCREAMING_SNAKE_CASE__ : List[Any] , SCREAMING_SNAKE_CASE__ : Dict , SCREAMING_SNAKE_CASE__ : Optional[int] ):
"""simple docstring"""
... | 48 | 1 |
"""simple docstring"""
import os
# All paths are set with the intent you should run this script from the root of the repo with the command
# python utils/check_doctest_list.py
a_ = '''.'''
if __name__ == "__main__":
a_ = os.path.join(REPO_PATH, '''utils/documentation_tests.txt''')
a_ ... | 48 |
"""simple docstring"""
import random
def SCREAMING_SNAKE_CASE__ ( SCREAMING_SNAKE_CASE__ : int , SCREAMING_SNAKE_CASE__ : float , SCREAMING_SNAKE_CASE__ : bool = False ):
"""simple docstring"""
snake_case_ : dict = {i: [] for i in range(SCREAMING... | 48 | 1 |
"""simple docstring"""
from __future__ import annotations
import unittest
from transformers import BlenderbotConfig, BlenderbotTokenizer, is_tf_available
from transformers.testing_utils import require_tf, require_tokenizers, slow
from transformers.utils import cached_property
from ...test_configuration_common i... | 48 |
"""simple docstring"""
from ...configuration_utils import PretrainedConfig
from ...utils import logging
a_ = logging.get_logger(__name__)
a_ = {
'''facebook/dpr-ctx_encoder-single-nq-base''': (
'''https://huggingface.co/facebook/dpr-ctx_encoder-single-nq-base/resolve/main/config.js... | 48 | 1 |
"""simple docstring"""
from ...configuration_utils import PretrainedConfig
from ...utils import logging
a_ = logging.get_logger(__name__)
a_ = {
'''facebook/dpr-ctx_encoder-single-nq-base''': (
'''https://huggingface.co/facebook/dpr-ctx_encoder-single-nq-base/resolve/main/config.js... | 48 |
"""simple docstring"""
import json
import multiprocessing as mp
import re
from collections import defaultdict
from functools import partial
from typing import Dict, List, Optional, Set, Tuple, Type
from datasets import Dataset
from datasketch import MinHash, MinHashLSH
from dpu_utils.utils.iterators import Thread... | 48 | 1 |
"""simple docstring"""
from typing import List, Optional, Union
from ...image_utils import ImageInput
from ...processing_utils import ProcessorMixin
from ...tokenization_utils_base import BatchEncoding, PaddingStrategy, PreTokenizedInput, TextInput, TruncationStrategy
from ...utils import TensorType
class ... | 48 |
"""simple docstring"""
import argparse
import logging
import pickle
from collections import Counter
logging.basicConfig(
format='''%(asctime)s - %(levelname)s - %(name)s - %(message)s''', datefmt='''%m/%d/%Y %H:%M:%S''', level=logging.INFO
)
a_ = logging.getLogger(__name__)
if __name__ == "__main__... | 48 | 1 |
"""simple docstring"""
import random
import unittest
import torch
from diffusers import IFInpaintingPipeline
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 (
... | 48 |
"""simple docstring"""
import pytest
from datasets import Dataset, DatasetDict, Features, NamedSplit, Value
from datasets.io.text import TextDatasetReader
from ..utils import assert_arrow_memory_doesnt_increase, assert_arrow_memory_increases
def SCREAMING_SNAKE_CASE__ ( SCREAMING_SNAKE_CASE__... | 48 | 1 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
a_ = {
'''configuration_time_series_transformer''': [
'''TIME_SERIES_TRANSFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP''',
'''TimeSeriesTransformerCon... | 48 |
"""simple docstring"""
from copy import deepcopy
class __lowercase :
"""simple docstring"""
def __init__(self , lowercase__ = None , lowercase__ = None ):
if arr is None and size is not None:
snake_case_ : str = size
... | 48 | 1 |
"""simple docstring"""
def SCREAMING_SNAKE_CASE__ ( SCREAMING_SNAKE_CASE__ : int ):
"""simple docstring"""
snake_case_ : Tuple = int(SCREAMING_SNAKE_CASE__ )
if decimal in (0, 1): # Exit cases for the recursion
return str(SCREAMING_SNAKE_CASE__ )
... | 48 |
"""simple docstring"""
def SCREAMING_SNAKE_CASE__ ( SCREAMING_SNAKE_CASE__ : list ):
"""simple docstring"""
snake_case_ : Optional[int] = len(SCREAMING_SNAKE_CASE__ )
for i in range(1 , SCREAMING_SNAKE_CASE__ ):
snake_case_ : Tuple ... | 48 | 1 |
"""simple docstring"""
import random
import unittest
import numpy as np
import transformers
from transformers import is_flax_available, is_torch_available
from transformers.testing_utils import is_pt_flax_cross_test, require_flax
if is_flax_available():
import os
import jax.numpy as jnp
from jax impo... | 48 |
"""simple docstring"""
import warnings
from ...processing_utils import ProcessorMixin
from ...tokenization_utils_base import BatchEncoding
class __lowercase ( _UpperCAmelCase):
"""simple docstring"""
_A : Union[str, Any] = ["""image_processor""", ""... | 48 | 1 |
"""simple docstring"""
import argparse
import json
import numpy
import torch
from transformers.models.xlm.tokenization_xlm import VOCAB_FILES_NAMES
from transformers.utils import CONFIG_NAME, WEIGHTS_NAME, logging
logging.set_verbosity_info()
def SCREAMING_SNAKE_CASE__ ( SCREAMING_SNAKE_CAS... | 48 |
"""simple docstring"""
import argparse
import copy
def SCREAMING_SNAKE_CASE__ ( SCREAMING_SNAKE_CASE__ : Any ):
"""simple docstring"""
snake_case_ : List[Any] = {}
with open(SCREAMING_SNAKE_CASE__ ) as f:
for line in f:
if line... | 48 | 1 |
"""simple docstring"""
import argparse
import math
import traceback
import dateutil.parser as date_parser
import requests
def SCREAMING_SNAKE_CASE__ ( SCREAMING_SNAKE_CASE__ : str ):
"""simple docstring"""
snake_case_ : Optional[Any] = {}
snake_case_ ... | 48 |
"""simple docstring"""
import copy
from ...configuration_utils import PretrainedConfig
from ...utils import add_start_docstrings
a_ = r'''
[`RagConfig`] stores the configuration of a *RagModel*. Configuration objects inherit from [`PretrainedConfig`] and
can be used to control the model outputs... | 48 | 1 |
"""simple docstring"""
import os
import random
import sys
from . import cryptomath_module as cryptomath
from . import rabin_miller
a_ = 3
def SCREAMING_SNAKE_CASE__ ( SCREAMING_SNAKE_CASE__ : int ):
"""simple docstring"""
print("""Generating primitive root of p""... | 48 |
"""simple docstring"""
import copy
from ...configuration_utils import PretrainedConfig
from ...utils import logging
from ..auto.configuration_auto import CONFIG_MAPPING
a_ = logging.get_logger(__name__)
class __lowercase ( _UpperCAmelCase):
"""simple docstring"""
... | 48 | 1 |
"""simple docstring"""
import tempfile
import unittest
from pathlib import Path
from shutil import copyfile
from transformers import BatchEncoding, MarianTokenizer
from transformers.testing_utils import get_tests_dir, require_sentencepiece, slow
from transformers.utils import is_sentencepiece_available, is_tf_ava... | 48 |
"""simple docstring"""
import logging
import os
from typing import List, TextIO, Union
from conllu import parse_incr
from utils_ner import InputExample, Split, TokenClassificationTask
a_ = logging.getLogger(__name__)
class __lowercase ( _UpperCAmelCase):
"""simple docstri... | 48 | 1 |
"""simple docstring"""
# Copyright 2023 The HuggingFace Inc. 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... | 48 |
"""simple docstring"""
import random
def SCREAMING_SNAKE_CASE__ ( SCREAMING_SNAKE_CASE__ : int ):
"""simple docstring"""
snake_case_ : Union[str, Any] = num - 1
snake_case_ : List[str] = 0
while s % 2 == 0:
snake_case_ : ... | 48 | 1 |
"""simple docstring"""
from random import randint
from tempfile import TemporaryFile
import numpy as np
def SCREAMING_SNAKE_CASE__ ( SCREAMING_SNAKE_CASE__ : List[Any] , SCREAMING_SNAKE_CASE__ : Dict , SCREAMING_SNAKE_CASE__ : Optional[int] ):
"""simple docstring"""
... | 48 |
"""simple docstring"""
from collections import OrderedDict
from typing import TYPE_CHECKING, Any, Mapping, Optional, Union
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
if TYPE_CHECKING:
from ... import FeatureExtractionMixin, PreTrainedTokeni... | 48 | 1 |
"""simple docstring"""
from ...utils import is_torch_available, is_transformers_available
if is_transformers_available() and is_torch_available():
from .pipeline_vq_diffusion import LearnedClassifierFreeSamplingEmbeddings, VQDiffusionPipeline
| 48 |
"""simple docstring"""
def SCREAMING_SNAKE_CASE__ ( SCREAMING_SNAKE_CASE__ : int , SCREAMING_SNAKE_CASE__ : int ):
"""simple docstring"""
return numa ^ numa < 0
if __name__ == "__main__":
import doctest
doctest.testmod()
| 48 | 1 |
"""simple docstring"""
import colorsys
from PIL import Image # type: ignore
def SCREAMING_SNAKE_CASE__ ( SCREAMING_SNAKE_CASE__ : float , SCREAMING_SNAKE_CASE__ : float , SCREAMING_SNAKE_CASE__ : int ):
"""simple docstring"""
snake_case_ : str = ... | 48 |
"""simple docstring"""
import tempfile
import unittest
from pathlib import Path
from shutil import copyfile
from transformers import BatchEncoding, MarianTokenizer
from transformers.testing_utils import get_tests_dir, require_sentencepiece, slow
from transformers.utils import is_sentencepiece_available, is_tf_ava... | 48 | 1 |
"""simple docstring"""
from manim import *
class __lowercase ( _UpperCAmelCase):
"""simple docstring"""
def __UpperCamelCase (self ):
snake_case_ : Union[str, Any] = Rectangle(height=0.5 , width=0.5 )
snake_c... | 48 |
"""simple docstring"""
import copy
from dataclasses import dataclass, field
from typing import ClassVar, Dict
from ..features import Audio, Features, Value
from .base import TaskTemplate
@dataclass(frozen=_UpperCAmelCase)
class __lowercase ( _UpperCAmelCase):
"""simple docstring"""
... | 48 | 1 |
"""simple docstring"""
import heapq
import sys
import numpy as np
a_ = tuple[int, int]
class __lowercase :
"""simple docstring"""
def __init__(self ):
snake_case_ : Union[str, Any] = []
snake_case_ : List[str] = ... | 48 |
"""simple docstring"""
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,
get_resize_output_image_size,
normalize,
rescale,
resize,
to_channe... | 48 | 1 |
"""simple docstring"""
def SCREAMING_SNAKE_CASE__ ( SCREAMING_SNAKE_CASE__ : int , SCREAMING_SNAKE_CASE__ : int ):
"""simple docstring"""
return numa ^ numa < 0
if __name__ == "__main__":
import doctest
doctest.testmod()
| 48 |
"""simple docstring"""
import os
from shutil import copyfile
from typing import List, Optional, Tuple
from tokenizers import processors
from ...tokenization_utils import AddedToken, BatchEncoding
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import is_sentencepiece_available, loggi... | 48 | 1 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_sentencepiece_available,
is_tf_available,
is_tokenizers_available,
is_torch_available,
)
a_ = {
'''configuration_rembert''': ['''REMBERT_PRETRAINED_... | 48 |
"""simple docstring"""
import argparse
import hashlib # hashlib is only used inside the Test class
import struct
class __lowercase :
"""simple docstring"""
def __init__(self , lowercase__ ):
snake_case_ : Union[str, Any] = data
s... | 48 | 1 |
"""simple docstring"""
from __future__ import annotations
import math
def SCREAMING_SNAKE_CASE__ ( SCREAMING_SNAKE_CASE__ : int ):
"""simple docstring"""
if num <= 0:
snake_case_ : Tuple = f'{num}: Invalid input, please enter a positive integer.'
... | 48 |
"""simple docstring"""
from manim import *
class __lowercase ( _UpperCAmelCase):
"""simple docstring"""
def __UpperCamelCase (self ):
snake_case_ : Union[str, Any] = Rectangle(height=0.5 , width=0.5 )
snake_c... | 48 | 1 |
"""simple docstring"""
import copy
from dataclasses import dataclass, field
from typing import ClassVar, Dict
from ..features import Audio, Features, Value
from .base import TaskTemplate
@dataclass(frozen=_UpperCAmelCase)
class __lowercase ( _UpperCAmelCase):
"""simple docstring"""
... | 48 |
"""simple docstring"""
from random import randint
from tempfile import TemporaryFile
import numpy as np
def SCREAMING_SNAKE_CASE__ ( SCREAMING_SNAKE_CASE__ : List[Any] , SCREAMING_SNAKE_CASE__ : Dict , SCREAMING_SNAKE_CASE__ : Optional[int] ):
"""simple docstring"""
... | 48 | 1 |
"""simple docstring"""
from . import __version__
# Backward compatibility imports, to make sure all those objects can be found in file_utils
from .utils import (
CLOUDFRONT_DISTRIB_PREFIX,
CONFIG_NAME,
DISABLE_TELEMETRY,
DUMMY_INPUTS,
DUMMY_MASK,
ENV_VARS_TRUE_AND_AUTO_VALUES,
ENV_VARS... | 48 |
"""simple docstring"""
import random
def SCREAMING_SNAKE_CASE__ ( SCREAMING_SNAKE_CASE__ : int , SCREAMING_SNAKE_CASE__ : float , SCREAMING_SNAKE_CASE__ : bool = False ):
"""simple docstring"""
snake_case_ : dict = {i: [] for i in range(SCREAMING... | 48 | 1 |
"""simple docstring"""
# Imports
import numpy as np
class __lowercase :
"""simple docstring"""
def __init__(self , lowercase__=None , lowercase__=None , lowercase__=None , lowercase__=None , lowercase__=None ):
self.set_matricies(red=lowercase... | 48 |
"""simple docstring"""
from ...configuration_utils import PretrainedConfig
from ...utils import logging
a_ = logging.get_logger(__name__)
a_ = {
'''facebook/dpr-ctx_encoder-single-nq-base''': (
'''https://huggingface.co/facebook/dpr-ctx_encoder-single-nq-base/resolve/main/config.js... | 48 | 1 |
"""simple docstring"""
import argparse
import os
import re
import numpy as np
import PIL
import torch
from timm import create_model
from torch.optim.lr_scheduler import OneCycleLR
from torch.utils.data import DataLoader, Dataset
from torchvision.transforms import Compose, RandomResizedCrop, Resize, ToTensor
from... | 48 |
"""simple docstring"""
import json
import multiprocessing as mp
import re
from collections import defaultdict
from functools import partial
from typing import Dict, List, Optional, Set, Tuple, Type
from datasets import Dataset
from datasketch import MinHash, MinHashLSH
from dpu_utils.utils.iterators import Thread... | 48 | 1 |
"""simple docstring"""
import unittest
import numpy as np
from transformers.testing_utils import require_pytesseract, require_torch
from transformers.utils import is_pytesseract_available, is_torch_available
from ...test_image_processing_common import ImageProcessingSavingTestMixin, prepare_image_inputs
if is... | 48 |
"""simple docstring"""
import argparse
import logging
import pickle
from collections import Counter
logging.basicConfig(
format='''%(asctime)s - %(levelname)s - %(name)s - %(message)s''', datefmt='''%m/%d/%Y %H:%M:%S''', level=logging.INFO
)
a_ = logging.getLogger(__name__)
if __name__ == "__main__... | 48 | 1 |
"""simple docstring"""
import os
from shutil import copyfile
from typing import List, Optional, Tuple
from tokenizers import processors
from ...tokenization_utils import AddedToken, BatchEncoding
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import is_sentencepiece_available, loggi... | 48 |
"""simple docstring"""
import pytest
from datasets import Dataset, DatasetDict, Features, NamedSplit, Value
from datasets.io.text import TextDatasetReader
from ..utils import assert_arrow_memory_doesnt_increase, assert_arrow_memory_increases
def SCREAMING_SNAKE_CASE__ ( SCREAMING_SNAKE_CASE__... | 48 | 1 |
"""simple docstring"""
import os
import re
import shutil
import sys
import tempfile
import unittest
import black
a_ = os.path.abspath(os.path.dirname(os.path.dirname(os.path.dirname(__file__))))
sys.path.append(os.path.join(git_repo_path, '''utils'''))
import check_copies # noqa: E402
# This is the... | 48 |
"""simple docstring"""
from copy import deepcopy
class __lowercase :
"""simple docstring"""
def __init__(self , lowercase__ = None , lowercase__ = None ):
if arr is None and size is not None:
snake_case_ : str = size
... | 48 | 1 |
"""simple docstring"""
from typing import Dict, List, Optional, Tuple, Union
import numpy as np
from ...image_processing_utils import BaseImageProcessor, BatchFeature, get_size_dict
from ...image_transforms import (
center_crop,
flip_channel_order,
get_resize_output_image_size,
rescale,
resiz... | 48 |
"""simple docstring"""
def SCREAMING_SNAKE_CASE__ ( SCREAMING_SNAKE_CASE__ : list ):
"""simple docstring"""
snake_case_ : Optional[int] = len(SCREAMING_SNAKE_CASE__ )
for i in range(1 , SCREAMING_SNAKE_CASE__ ):
snake_case_ : Tuple ... | 48 | 1 |
"""simple docstring"""
import os
import unittest
from transformers.models.cpmant.tokenization_cpmant import VOCAB_FILES_NAMES, CpmAntTokenizer
from transformers.testing_utils import require_jieba, tooslow
from ...test_tokenization_common import TokenizerTesterMixin
@require_jieba
class __lowercase ... | 48 |
"""simple docstring"""
import warnings
from ...processing_utils import ProcessorMixin
from ...tokenization_utils_base import BatchEncoding
class __lowercase ( _UpperCAmelCase):
"""simple docstring"""
_A : Union[str, Any] = ["""image_processor""", ""... | 48 | 1 |
"""simple docstring"""
from ...processing_utils import ProcessorMixin
class __lowercase ( _UpperCAmelCase):
"""simple docstring"""
_A : Union[str, Any] = ["""image_processor""", """feature_extractor"""]
_A : List[str] = """... | 48 |
"""simple docstring"""
import argparse
import copy
def SCREAMING_SNAKE_CASE__ ( SCREAMING_SNAKE_CASE__ : Any ):
"""simple docstring"""
snake_case_ : List[Any] = {}
with open(SCREAMING_SNAKE_CASE__ ) as f:
for line in f:
if line... | 48 | 1 |
"""simple docstring"""
import importlib.util
import os
import platform
from argparse import ArgumentParser
import huggingface_hub
from .. import __version__ as version
from ..utils import (
is_accelerate_available,
is_flax_available,
is_safetensors_available,
is_tf_available,
is_torch_availab... | 48 |
"""simple docstring"""
import copy
from ...configuration_utils import PretrainedConfig
from ...utils import add_start_docstrings
a_ = r'''
[`RagConfig`] stores the configuration of a *RagModel*. Configuration objects inherit from [`PretrainedConfig`] and
can be used to control the model outputs... | 48 | 1 |
"""simple docstring"""
import unittest
from parameterized import parameterized
from transformers import OpenLlamaConfig, is_torch_available, set_seed
from transformers.testing_utils import require_torch, torch_device
from ...generation.test_utils import GenerationTesterMixin
from ...test_configuration_common im... | 48 |
"""simple docstring"""
import copy
from ...configuration_utils import PretrainedConfig
from ...utils import logging
from ..auto.configuration_auto import CONFIG_MAPPING
a_ = logging.get_logger(__name__)
class __lowercase ( _UpperCAmelCase):
"""simple docstring"""
... | 48 | 1 |
"""simple docstring"""
from copy import deepcopy
class __lowercase :
"""simple docstring"""
def __init__(self , lowercase__ = None , lowercase__ = None ):
if arr is None and size is not None:
snake_case_ : str = size
... | 48 |
"""simple docstring"""
import logging
import os
from typing import List, TextIO, Union
from conllu import parse_incr
from utils_ner import InputExample, Split, TokenClassificationTask
a_ = logging.getLogger(__name__)
class __lowercase ( _UpperCAmelCase):
"""simple docstri... | 48 | 1 |
"""simple docstring"""
from __future__ import annotations
import unittest
from transformers import BlenderbotSmallConfig, BlenderbotSmallTokenizer, is_tf_available
from transformers.testing_utils import require_tf, require_tokenizers, slow
from transformers.utils import cached_property
from ...test_configuratio... | 48 |
"""simple docstring"""
import random
def SCREAMING_SNAKE_CASE__ ( SCREAMING_SNAKE_CASE__ : int ):
"""simple docstring"""
snake_case_ : Union[str, Any] = num - 1
snake_case_ : List[str] = 0
while s % 2 == 0:
snake_case_ : ... | 48 | 1 |
"""simple docstring"""
def SCREAMING_SNAKE_CASE__ ( SCREAMING_SNAKE_CASE__ : str , SCREAMING_SNAKE_CASE__ : int ):
"""simple docstring"""
snake_case_ : str = word.split()
def justify(SCREAMING_SNAKE_CASE__ : list , SCREAMING_SNAKE_CASE__ : int ... | 48 |
"""simple docstring"""
from collections import OrderedDict
from typing import TYPE_CHECKING, Any, Mapping, Optional, Union
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
if TYPE_CHECKING:
from ... import FeatureExtractionMixin, PreTrainedTokeni... | 48 | 1 |
"""simple docstring"""
import json
from typing import List, Optional, Tuple
from tokenizers import pre_tokenizers, processors
from ...tokenization_utils_base import AddedToken, BatchEncoding
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import logging
from .tokenization_roberta imp... | 48 |
"""simple docstring"""
def SCREAMING_SNAKE_CASE__ ( SCREAMING_SNAKE_CASE__ : int , SCREAMING_SNAKE_CASE__ : int ):
"""simple docstring"""
return numa ^ numa < 0
if __name__ == "__main__":
import doctest
doctest.testmod()
| 48 | 1 |
"""simple docstring"""
from __future__ import annotations
import unittest
from transformers import AutoTokenizer, PegasusConfig, is_tf_available
from transformers.testing_utils import require_sentencepiece, require_tf, require_tokenizers, slow
from transformers.utils import cached_property
from ...test_configur... | 48 |
"""simple docstring"""
import tempfile
import unittest
from pathlib import Path
from shutil import copyfile
from transformers import BatchEncoding, MarianTokenizer
from transformers.testing_utils import get_tests_dir, require_sentencepiece, slow
from transformers.utils import is_sentencepiece_available, is_tf_ava... | 48 | 1 |
"""simple docstring"""
import shutil
import tempfile
import unittest
from transformers import ClapFeatureExtractor, ClapProcessor, RobertaTokenizer, RobertaTokenizerFast
from transformers.testing_utils import require_sentencepiece, require_torchaudio
from .test_feature_extraction_clap import floats_list
@... | 48 |
"""simple docstring"""
import copy
from dataclasses import dataclass, field
from typing import ClassVar, Dict
from ..features import Audio, Features, Value
from .base import TaskTemplate
@dataclass(frozen=_UpperCAmelCase)
class __lowercase ( _UpperCAmelCase):
"""simple docstring"""
... | 48 | 1 |
"""simple docstring"""
from math import atan, cos, radians, sin, tan
from .haversine_distance import haversine_distance
a_ = 6_3_7_8_1_3_7.0
a_ = 6_3_5_6_7_5_2.3_1_4_2_4_5
a_ = 6378137
def SCREAMING_SNAKE_CASE__ ( SCREAMING_SNAKE_CASE__ : float , SCREAMING_SN... | 48 |
"""simple docstring"""
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,
get_resize_output_image_size,
normalize,
rescale,
resize,
to_channe... | 48 | 1 |
"""simple docstring"""
from __future__ import annotations
def SCREAMING_SNAKE_CASE__ ( SCREAMING_SNAKE_CASE__ : str , SCREAMING_SNAKE_CASE__ : list[str] | None = None ):
"""simple docstring"""
snake_case_ : List[Any] = word_bank or []
# create a ta... | 48 |
"""simple docstring"""
import os
from shutil import copyfile
from typing import List, Optional, Tuple
from tokenizers import processors
from ...tokenization_utils import AddedToken, BatchEncoding
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import is_sentencepiece_available, loggi... | 48 | 1 |
"""simple docstring"""
from dataclasses import dataclass, field
from typing import ClassVar, Dict
from ..features import Features, Sequence, Value
from .base import TaskTemplate
@dataclass(frozen=_UpperCAmelCase)
class __lowercase ( _UpperCAmelCase):
"""simple docstring"""
... | 48 |
"""simple docstring"""
import argparse
import hashlib # hashlib is only used inside the Test class
import struct
class __lowercase :
"""simple docstring"""
def __init__(self , lowercase__ ):
snake_case_ : Union[str, Any] = data
s... | 48 | 1 |
"""simple docstring"""
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
a_ = logging.get_logger(__name__)
a_ = {
'''facebook/data2ve... | 48 |
"""simple docstring"""
from manim import *
class __lowercase ( _UpperCAmelCase):
"""simple docstring"""
def __UpperCamelCase (self ):
snake_case_ : Union[str, Any] = Rectangle(height=0.5 , width=0.5 )
snake_c... | 48 | 1 |
"""simple docstring"""
import argparse
import json
from pathlib import Path
import requests
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from transformers import BeitConfig, BeitForImageClassification, BeitForMaskedImageModeling, BeitImageProcessor
from transformers.image_utils ... | 48 |
"""simple docstring"""
from random import randint
from tempfile import TemporaryFile
import numpy as np
def SCREAMING_SNAKE_CASE__ ( SCREAMING_SNAKE_CASE__ : List[Any] , SCREAMING_SNAKE_CASE__ : Dict , SCREAMING_SNAKE_CASE__ : Optional[int] ):
"""simple docstring"""
... | 48 | 1 |
"""simple docstring"""
from __future__ import annotations
def SCREAMING_SNAKE_CASE__ ( SCREAMING_SNAKE_CASE__ : list[int | str] ):
"""simple docstring"""
create_state_space_tree(SCREAMING_SNAKE_CASE__ , [] , 0 , [0 for i in range(len(SCREAMING_SNAKE_CASE__... | 48 |
"""simple docstring"""
import random
def SCREAMING_SNAKE_CASE__ ( SCREAMING_SNAKE_CASE__ : int , SCREAMING_SNAKE_CASE__ : float , SCREAMING_SNAKE_CASE__ : bool = False ):
"""simple docstring"""
snake_case_ : dict = {i: [] for i in range(SCREAMING... | 48 | 1 |
"""simple docstring"""
from __future__ import annotations
from collections import Counter
from random import random
class __lowercase :
"""simple docstring"""
def __init__(self ):
snake_case_ : Tuple = {}
def __UpperCamelCas... | 48 |
"""simple docstring"""
from ...configuration_utils import PretrainedConfig
from ...utils import logging
a_ = logging.get_logger(__name__)
a_ = {
'''facebook/dpr-ctx_encoder-single-nq-base''': (
'''https://huggingface.co/facebook/dpr-ctx_encoder-single-nq-base/resolve/main/config.js... | 48 | 1 |
"""simple docstring"""
import argparse
import json
from pathlib import Path
import requests
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from transformers import DetrConfig, DetrForObjectDetection, DetrForSegmentation, DetrImageProcessor, ResNetConfig
from transformers.utils imp... | 48 |
"""simple docstring"""
import json
import multiprocessing as mp
import re
from collections import defaultdict
from functools import partial
from typing import Dict, List, Optional, Set, Tuple, Type
from datasets import Dataset
from datasketch import MinHash, MinHashLSH
from dpu_utils.utils.iterators import Thread... | 48 | 1 |
"""simple docstring"""
import argparse
import torch
from huggingface_hub import hf_hub_download
from transformers import AutoTokenizer, RobertaPreLayerNormConfig, RobertaPreLayerNormForMaskedLM
from transformers.utils import logging
logging.set_verbosity_info()
a_ = logging.get_logger(__name__)
... | 48 |
"""simple docstring"""
import argparse
import logging
import pickle
from collections import Counter
logging.basicConfig(
format='''%(asctime)s - %(levelname)s - %(name)s - %(message)s''', datefmt='''%m/%d/%Y %H:%M:%S''', level=logging.INFO
)
a_ = logging.getLogger(__name__)
if __name__ == "__main__... | 48 | 1 |
"""simple docstring"""
from typing import Mapping
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxSeqaSeqConfigWithPast
from ...utils import logging
a_ = logging.get_logger(__name__)
a_ = {
'''google/umt5-small''': '''https://huggingface.co/google/umt5-small/re... | 48 |
"""simple docstring"""
import pytest
from datasets import Dataset, DatasetDict, Features, NamedSplit, Value
from datasets.io.text import TextDatasetReader
from ..utils import assert_arrow_memory_doesnt_increase, assert_arrow_memory_increases
def SCREAMING_SNAKE_CASE__ ( SCREAMING_SNAKE_CASE__... | 48 | 1 |
"""simple docstring"""
# tests directory-specific settings - this file is run automatically
# by pytest before any tests are run
import doctest
import sys
import warnings
from os.path import abspath, dirname, join
import _pytest
from transformers.testing_utils import HfDoctestModule, HfDocTestParser
# allow h... | 48 |
"""simple docstring"""
from copy import deepcopy
class __lowercase :
"""simple docstring"""
def __init__(self , lowercase__ = None , lowercase__ = None ):
if arr is None and size is not None:
snake_case_ : str = size
... | 48 | 1 |
"""simple docstring"""
from typing import Callable, Optional, Union
from ...configuration_utils import PretrainedConfig
from ...utils import logging
a_ = logging.get_logger(__name__)
a_ = {
'''microsoft/xprophetnet-large-wiki100-cased''': (
'''https://huggingface.co/microsoft/xpro... | 48 |
"""simple docstring"""
def SCREAMING_SNAKE_CASE__ ( SCREAMING_SNAKE_CASE__ : list ):
"""simple docstring"""
snake_case_ : Optional[int] = len(SCREAMING_SNAKE_CASE__ )
for i in range(1 , SCREAMING_SNAKE_CASE__ ):
snake_case_ : Tuple ... | 48 | 1 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_speech_available, is_torch_available
a_ = {
'''configuration_audio_spectrogram_transformer''': [
'''AUDIO_SPECTROGRAM_TRANSFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP''',
... | 48 |
"""simple docstring"""
import warnings
from ...processing_utils import ProcessorMixin
from ...tokenization_utils_base import BatchEncoding
class __lowercase ( _UpperCAmelCase):
"""simple docstring"""
_A : Union[str, Any] = ["""image_processor""", ""... | 48 | 1 |
"""simple docstring"""
import tempfile
import unittest
import numpy as np
from diffusers import (
DDIMScheduler,
DPMSolverMultistepScheduler,
EulerAncestralDiscreteScheduler,
EulerDiscreteScheduler,
LMSDiscreteScheduler,
OnnxStableDiffusionPipeline,
PNDMScheduler,
)
from diffusers.uti... | 48 |
"""simple docstring"""
import argparse
import copy
def SCREAMING_SNAKE_CASE__ ( SCREAMING_SNAKE_CASE__ : Any ):
"""simple docstring"""
snake_case_ : List[Any] = {}
with open(SCREAMING_SNAKE_CASE__ ) as f:
for line in f:
if line... | 48 | 1 |
"""simple docstring"""
import json
import os
from typing import Optional, Tuple
from ...tokenization_utils import PreTrainedTokenizer
from ...utils import logging
a_ = logging.get_logger(__name__)
a_ = {'''vocab_file''': '''vocab.json'''}
a_ = {
'''vocab_file''': {
'''mg... | 48 |
"""simple docstring"""
import copy
from ...configuration_utils import PretrainedConfig
from ...utils import add_start_docstrings
a_ = r'''
[`RagConfig`] stores the configuration of a *RagModel*. Configuration objects inherit from [`PretrainedConfig`] and
can be used to control the model outputs... | 48 | 1 |
"""simple docstring"""
import unittest
from transformers import (
MODEL_FOR_SEQUENCE_CLASSIFICATION_MAPPING,
TF_MODEL_FOR_SEQUENCE_CLASSIFICATION_MAPPING,
TextClassificationPipeline,
pipeline,
)
from transformers.testing_utils import is_pipeline_test, nested_simplify, require_tf, require_torch, sl... | 48 |
"""simple docstring"""
import copy
from ...configuration_utils import PretrainedConfig
from ...utils import logging
from ..auto.configuration_auto import CONFIG_MAPPING
a_ = logging.get_logger(__name__)
class __lowercase ( _UpperCAmelCase):
"""simple docstring"""
... | 48 | 1 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
a_ = {
'''configuration_jukebox''': [
'''JUKEBOX_PRETRAINED_CONFIG_ARCHIVE_MAP''',
'''JukeboxConfig''',
'''JukeboxPriorConfig''',
... | 48 |
"""simple docstring"""
import logging
import os
from typing import List, TextIO, Union
from conllu import parse_incr
from utils_ner import InputExample, Split, TokenClassificationTask
a_ = logging.getLogger(__name__)
class __lowercase ( _UpperCAmelCase):
"""simple docstri... | 48 | 1 |
"""simple docstring"""
import argparse
import logging
import pickle
from collections import Counter
logging.basicConfig(
format='''%(asctime)s - %(levelname)s - %(name)s - %(message)s''', datefmt='''%m/%d/%Y %H:%M:%S''', level=logging.INFO
)
a_ = logging.getLogger(__name__)
if __name__ == "__main__... | 48 |
"""simple docstring"""
import random
def SCREAMING_SNAKE_CASE__ ( SCREAMING_SNAKE_CASE__ : int ):
"""simple docstring"""
snake_case_ : Union[str, Any] = num - 1
snake_case_ : List[str] = 0
while s % 2 == 0:
snake_case_ : ... | 48 | 1 |
"""simple docstring"""
import logging
import os
from dataclasses import dataclass, field
from typing import Dict, Optional
import numpy as np
from utils_multiple_choice import MultipleChoiceDataset, Split, processors
import transformers
from transformers import (
AutoConfig,
AutoModelForMultipleChoice,
... | 48 |
"""simple docstring"""
from collections import OrderedDict
from typing import TYPE_CHECKING, Any, Mapping, Optional, Union
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
if TYPE_CHECKING:
from ... import FeatureExtractionMixin, PreTrainedTokeni... | 48 | 1 |
"""simple docstring"""
a_ = 65521
def SCREAMING_SNAKE_CASE__ ( SCREAMING_SNAKE_CASE__ : str ):
"""simple docstring"""
snake_case_ : List[Any] = 1
snake_case_ : Tuple = 0
for plain_chr in plain_text:
snake_case_ : ... | 48 |
"""simple docstring"""
def SCREAMING_SNAKE_CASE__ ( SCREAMING_SNAKE_CASE__ : int , SCREAMING_SNAKE_CASE__ : int ):
"""simple docstring"""
return numa ^ numa < 0
if __name__ == "__main__":
import doctest
doctest.testmod()
| 48 | 1 |
"""simple docstring"""
import doctest
import glob
import importlib
import inspect
import os
import re
from contextlib import contextmanager
from functools import wraps
from unittest.mock import patch
import numpy as np
import pytest
from absl.testing import parameterized
import datasets
from datasets import load... | 48 |
"""simple docstring"""
import tempfile
import unittest
from pathlib import Path
from shutil import copyfile
from transformers import BatchEncoding, MarianTokenizer
from transformers.testing_utils import get_tests_dir, require_sentencepiece, slow
from transformers.utils import is_sentencepiece_available, is_tf_ava... | 48 | 1 |
"""simple docstring"""
from __future__ import annotations
def SCREAMING_SNAKE_CASE__ ( SCREAMING_SNAKE_CASE__ : int ):
"""simple docstring"""
snake_case_ : Optional[Any] = 2
snake_case_ : Optional[Any] = []
while i * i <= n:
i... | 48 |
"""simple docstring"""
import copy
from dataclasses import dataclass, field
from typing import ClassVar, Dict
from ..features import Audio, Features, Value
from .base import TaskTemplate
@dataclass(frozen=_UpperCAmelCase)
class __lowercase ( _UpperCAmelCase):
"""simple docstring"""
... | 48 | 1 |
"""simple docstring"""
import json
import multiprocessing as mp
import re
from collections import defaultdict
from functools import partial
from typing import Dict, List, Optional, Set, Tuple, Type
from datasets import Dataset
from datasketch import MinHash, MinHashLSH
from dpu_utils.utils.iterators import Thread... | 48 |
"""simple docstring"""
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,
get_resize_output_image_size,
normalize,
rescale,
resize,
to_channe... | 48 | 1 |
"""simple docstring"""
import re
from filelock import FileLock
try:
import nltk
a_ = True
except (ImportError, ModuleNotFoundError):
a_ = False
if NLTK_AVAILABLE:
with FileLock('''.lock''') as lock:
nltk.download('''punkt''', quiet=True)
def SCREAMING_SNAKE_CA... | 48 |
"""simple docstring"""
import os
from shutil import copyfile
from typing import List, Optional, Tuple
from tokenizers import processors
from ...tokenization_utils import AddedToken, BatchEncoding
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import is_sentencepiece_available, loggi... | 48 | 1 |
"""simple docstring"""
import re
import string
import numpy as np
import datasets
a_ = '''
Returns the rate at which the input predicted strings exactly match their references, ignoring any strings input as part of the regexes_to_ignore list.
'''
a_ = '''
Args:
predictions: List of predi... | 48 |
"""simple docstring"""
import argparse
import hashlib # hashlib is only used inside the Test class
import struct
class __lowercase :
"""simple docstring"""
def __init__(self , lowercase__ ):
snake_case_ : Union[str, Any] = data
s... | 48 | 1 |
"""simple docstring"""
from __future__ import annotations
def SCREAMING_SNAKE_CASE__ ( SCREAMING_SNAKE_CASE__ : int | float | str , SCREAMING_SNAKE_CASE__ : int | float | str ):
"""simple docstring"""
if nth_term == "":
return [""]
snake_case_ : L... | 48 |
"""simple docstring"""
from manim import *
class __lowercase ( _UpperCAmelCase):
"""simple docstring"""
def __UpperCamelCase (self ):
snake_case_ : Union[str, Any] = Rectangle(height=0.5 , width=0.5 )
snake_c... | 48 | 1 |
"""simple docstring"""
# 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
#
# ... | 48 |
"""simple docstring"""
from random import randint
from tempfile import TemporaryFile
import numpy as np
def SCREAMING_SNAKE_CASE__ ( SCREAMING_SNAKE_CASE__ : List[Any] , SCREAMING_SNAKE_CASE__ : Dict , SCREAMING_SNAKE_CASE__ : Optional[int] ):
"""simple docstring"""
... | 48 | 1 |
"""simple docstring"""
import os
from shutil import copyfile
from typing import Any, Dict, List, Optional, Tuple
import sentencepiece as spm
from ...tokenization_utils import AddedToken, BatchEncoding, PreTrainedTokenizer
from ...utils import logging
a_ = logging.get_logger(__name__)
a_ = ''... | 48 |
"""simple docstring"""
import random
def SCREAMING_SNAKE_CASE__ ( SCREAMING_SNAKE_CASE__ : int , SCREAMING_SNAKE_CASE__ : float , SCREAMING_SNAKE_CASE__ : bool = False ):
"""simple docstring"""
snake_case_ : dict = {i: [] for i in range(SCREAMING... | 48 | 1 |
"""simple docstring"""
import unittest
import torch
from torch import nn
from accelerate.test_utils import require_cuda
from accelerate.utils.memory import find_executable_batch_size, release_memory
def SCREAMING_SNAKE_CASE__ ( ):
"""simple docstring"""
raise RuntimeError(""... | 48 |
"""simple docstring"""
from ...configuration_utils import PretrainedConfig
from ...utils import logging
a_ = logging.get_logger(__name__)
a_ = {
'''facebook/dpr-ctx_encoder-single-nq-base''': (
'''https://huggingface.co/facebook/dpr-ctx_encoder-single-nq-base/resolve/main/config.js... | 48 | 1 |
"""simple docstring"""
import copy
from ...configuration_utils import PretrainedConfig
from ...utils import logging
from ..auto.configuration_auto import CONFIG_MAPPING
a_ = logging.get_logger(__name__)
class __lowercase ( _UpperCAmelCase):
"""simple docstring"""
... | 48 |
"""simple docstring"""
import json
import multiprocessing as mp
import re
from collections import defaultdict
from functools import partial
from typing import Dict, List, Optional, Set, Tuple, Type
from datasets import Dataset
from datasketch import MinHash, MinHashLSH
from dpu_utils.utils.iterators import Thread... | 48 | 1 |
"""simple docstring"""
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 Tokenizer... | 48 |
"""simple docstring"""
import argparse
import logging
import pickle
from collections import Counter
logging.basicConfig(
format='''%(asctime)s - %(levelname)s - %(name)s - %(message)s''', datefmt='''%m/%d/%Y %H:%M:%S''', level=logging.INFO
)
a_ = logging.getLogger(__name__)
if __name__ == "__main__... | 48 | 1 |
"""simple docstring"""
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
... | 48 |
"""simple docstring"""
import pytest
from datasets import Dataset, DatasetDict, Features, NamedSplit, Value
from datasets.io.text import TextDatasetReader
from ..utils import assert_arrow_memory_doesnt_increase, assert_arrow_memory_increases
def SCREAMING_SNAKE_CASE__ ( SCREAMING_SNAKE_CASE__... | 48 | 1 |
"""simple docstring"""
from ...configuration_utils import PretrainedConfig
from ...utils import logging
a_ = logging.get_logger(__name__)
a_ = {}
class __lowercase ( _UpperCAmelCase):
"""simple docstring"""
_A : Tuple = """llama"... | 48 |
"""simple docstring"""
from copy import deepcopy
class __lowercase :
"""simple docstring"""
def __init__(self , lowercase__ = None , lowercase__ = None ):
if arr is None and size is not None:
snake_case_ : str = size
... | 48 | 1 |
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