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 |
|---|---|---|---|---|
"""simple docstring"""
# Copyright 2021 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
#
# ... | 64 | """simple docstring"""
import importlib
import json
import os
from collections import OrderedDict
from typing import Dict, Optional, Union
# Build the list of all image processors
from ...configuration_utils import PretrainedConfig
from ...dynamic_module_utils import get_class_from_dynamic_module, resolve_trust_r... | 64 | 1 |
"""simple docstring"""
def lowercase_ ( _lowerCamelCase: int , _lowerCamelCase: float , _lowerCamelCase: float ) -> float:
'''simple docstring'''
return round(float(moles / volume ) * nfactor )
def lowercase_ ( _lowerCamelCase: float , _lowerCamelCase: float... | 64 | """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, normalize, rescale, resize, to_channel_dimension_format
from ...image_utils import (
IMAG... | 64 | 1 |
"""simple docstring"""
from __future__ import annotations
def lowercase_ ( _lowerCamelCase: list[int] , _lowerCamelCase: int ) -> list[list[int]]:
'''simple docstring'''
__lowerCamelCase : list[list[int]] = []
__lowerCamelCase : list[int] ... | 64 | """simple docstring"""
from ...configuration_utils import PretrainedConfig
from ...utils import logging
__A = logging.get_logger(__name__)
__A = {
'''uclanlp/visualbert-vqa''': '''https://huggingface.co/uclanlp/visualbert-vqa/resolve/main/config.json''',
'''uclanlp/visualbert-vqa-pre''': '''... | 64 | 1 |
"""simple docstring"""
__A = {
'''Pillow''': '''Pillow<10.0.0''',
'''accelerate''': '''accelerate>=0.20.3''',
'''av''': '''av==9.2.0''',
'''beautifulsoup4''': '''beautifulsoup4''',
'''black''': '''black~=23.1''',
'''codecarbon''': '''codecarbon==1.2.0''',
'''cookiecutter''': '''co... | 64 | """simple docstring"""
from ...configuration_utils import PretrainedConfig
class _snake_case ( a__ ):
snake_case__ = "bert-generation"
def __init__( self : Optional[int] , UpperCAmelCase : Dict=50358 , UpperCAmelCase : int=1024 , U... | 64 | 1 |
"""simple docstring"""
def lowercase_ ( _lowerCamelCase: int = 100 ) -> int:
'''simple docstring'''
__lowerCamelCase : Optional[Any] = set()
__lowerCamelCase : Union[str, Any] = 0
__lowerCamelCase : Optional[Any] ... | 64 | """simple docstring"""
import unittest
import numpy as np
from diffusers import OnnxStableDiffusionInpaintPipelineLegacy
from diffusers.utils.testing_utils import (
is_onnx_available,
load_image,
load_numpy,
nightly,
require_onnxruntime,
require_torch_gpu,
)
if is_onnx_available():
... | 64 | 1 |
"""simple docstring"""
import copy
from typing import Any, Dict, List, Optional, Union
import numpy as np
from ...audio_utils import mel_filter_bank, spectrogram, window_function
from ...feature_extraction_sequence_utils import SequenceFeatureExtractor
from ...feature_extraction_utils import BatchFeature
from ..... | 64 | """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. ... | 64 | 1 |
"""simple docstring"""
import warnings
from typing import Any, Dict, 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 imp... | 64 | """simple docstring"""
import gc
import unittest
import numpy as np
import torch
from diffusers import AutoencoderKL, DDIMScheduler, DiTPipeline, DPMSolverMultistepScheduler, TransformeraDModel
from diffusers.utils import is_xformers_available, load_numpy, slow, torch_device
from diffusers.utils.testing_utils im... | 64 | 1 |
"""simple docstring"""
import cmath
import math
def lowercase_ ( _lowerCamelCase: float , _lowerCamelCase: float , _lowerCamelCase: float , _lowerCamelCase: float ) -> complex:
'''simple docstring'''
__lowerCamelCase : Dict = math.radians(_lowerCa... | 64 | """simple docstring"""
def lowercase_ ( _lowerCamelCase: int ) -> int:
'''simple docstring'''
if not isinstance(_lowerCamelCase , _lowerCamelCase ):
raise TypeError("Input value must be an 'int' type" )
__lowerCamelCase : Dict = 0
... | 64 | 1 |
"""simple docstring"""
def lowercase_ ( _lowerCamelCase: int ) -> int:
'''simple docstring'''
if a < 0:
raise ValueError("Input value must be a positive integer" )
elif isinstance(_lowerCamelCase , _lowerCamelCase ):
raise TypeError("Input value m... | 64 | """simple docstring"""
import argparse
import json
import requests
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from transformers import ViTImageProcessor, ViTMSNConfig, ViTMSNModel
from transformers.image_utils import IMAGENET_DEFAULT_MEAN, IMAGENET_DEFAULT_STD
torch.set_grad... | 64 | 1 |
"""simple docstring"""
import json
from typing import Iterator, List, Union
from tokenizers import AddedToken, Regex, Tokenizer, decoders, normalizers, pre_tokenizers, trainers
from tokenizers.implementations.base_tokenizer import BaseTokenizer
from tokenizers.models import Unigram
from tokenizers.processors impo... | 64 | """simple docstring"""
from typing import Any
import numpy as np
def lowercase_ ( _lowerCamelCase: np.ndarray ) -> bool:
'''simple docstring'''
return np.array_equal(_lowerCamelCase , matrix.conjugate().T )
def lowercase_ ( _lowerCamelCase: np.ndarray , _lowerCa... | 64 | 1 |
"""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. ... | 64 | """simple docstring"""
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tf_available, is_torch_available
__A = {
'''configuration_xlm''': ['''XLM_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''XLMConfig''', '''XLMOnnxConfig'''],
'''tokenization_xlm''': ['... | 64 | 1 |
"""simple docstring"""
def lowercase_ ( _lowerCamelCase: int = 1000 ) -> int:
'''simple docstring'''
__lowerCamelCase : int = -1
__lowerCamelCase : int = 0
for a in range(1 , n // 3 ):
# Solving the two equatio... | 64 | """simple docstring"""
from ...configuration_utils import PretrainedConfig
from ...utils import logging
__A = logging.get_logger(__name__)
__A = {
'''RWKV/rwkv-4-169m-pile''': '''https://huggingface.co/RWKV/rwkv-4-169m-pile/resolve/main/config.json''',
'''RWKV/rwkv-4-430m-pile''': '''https:/... | 64 | 1 |
"""simple docstring"""
from ...configuration_utils import PretrainedConfig
from ...utils import logging
__A = logging.get_logger(__name__)
__A = {
'''facebook/s2t-wav2vec2-large-en-de''': (
'''https://huggingface.co/facebook/s2t-wav2vec2-large-en-de/resolve/main/config.json'''
),
... | 64 | """simple docstring"""
import requests
__A = '''YOUR API KEY'''
def lowercase_ ( _lowerCamelCase: str , _lowerCamelCase: str = giphy_api_key ) -> list:
'''simple docstring'''
__lowerCamelCase : Dict = "+".join(query.split() )
__lowerCamelCase ... | 64 | 1 |
"""simple docstring"""
import argparse
import os
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_task_guides.py
__A = '''src/transformers'''
__A = '''docs/source/e... | 64 | """simple docstring"""
import copy
from ...configuration_utils import PretrainedConfig
from ...utils import logging
from ..auto import CONFIG_MAPPING
__A = logging.get_logger(__name__)
__A = {
'''ut/deta''': '''https://huggingface.co/ut/deta/resolve/main/config.json''',
}
class _snake_case ... | 64 | 1 |
"""simple docstring"""
def lowercase_ ( _lowerCamelCase: int = 4000000 ) -> int:
'''simple docstring'''
__lowerCamelCase : Tuple = [0, 1]
__lowerCamelCase : Union[str, Any] = 0
while fib[i] <= n:
fib.append(fib[i] ... | 64 | """simple docstring"""
def lowercase_ ( _lowerCamelCase: int = 4000000 ) -> int:
'''simple docstring'''
__lowerCamelCase : Tuple = [0, 1]
__lowerCamelCase : Union[str, Any] = 0
while fib[i] <= n:
fib.append(fib[i] ... | 64 | 1 |
"""simple docstring"""
from dataclasses import dataclass, field
from typing import Tuple
from ..utils import cached_property, is_torch_available, is_torch_tpu_available, logging, requires_backends
from .benchmark_args_utils import BenchmarkArguments
if is_torch_available():
import torch
if is_torch_tpu_ava... | 64 | """simple docstring"""
def lowercase_ ( _lowerCamelCase: int = 100 ) -> int:
'''simple docstring'''
__lowerCamelCase : Optional[Any] = set()
__lowerCamelCase : Union[str, Any] = 0
__lowerCamelCase : Optional[Any] ... | 64 | 1 |
"""simple docstring"""
import argparse
import json
import requests
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from transformers import ViTImageProcessor, ViTMSNConfig, ViTMSNModel
from transformers.image_utils import IMAGENET_DEFAULT_MEAN, IMAGENET_DEFAULT_STD
torch.set_grad... | 64 | """simple docstring"""
from __future__ import annotations
from collections.abc import Sequence
from typing import Literal
def lowercase_ ( _lowerCamelCase: str , _lowerCamelCase: str ) -> str | Literal[False]:
'''simple docstring'''
__lowerCamelCase : Optional[int] ... | 64 | 1 |
"""simple docstring"""
import unittest
from dataclasses import dataclass
import pytest
from accelerate.commands.config.config_args import SageMakerConfig
from accelerate.utils import ComputeEnvironment
from accelerate.utils.launch import _convert_nargs_to_dict
@dataclass
class _snake_case ( a__ ):
... | 64 | """simple docstring"""
import os
import zipfile
import requests
from get_ci_error_statistics import download_artifact, get_artifacts_links
def lowercase_ ( _lowerCamelCase: str , _lowerCamelCase: Optional[int]=7 ) -> int:
'''simple docstring'''
__lowerCamelCase : List[st... | 64 | 1 |
"""simple docstring"""
from collections.abc import Sequence
from queue import Queue
class _snake_case :
def __init__( self : str , UpperCAmelCase : Optional[Any] , UpperCAmelCase : Any , UpperCAmelCase : Optional[int] , UpperCAmelCase : Dict... | 64 | """simple docstring"""
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 Optiona... | 64 | 1 |
"""simple docstring"""
import os
import zipfile
import requests
from get_ci_error_statistics import download_artifact, get_artifacts_links
def lowercase_ ( _lowerCamelCase: str , _lowerCamelCase: Optional[int]=7 ) -> int:
'''simple docstring'''
__lowerCamelCase : List[st... | 64 | """simple docstring"""
from io import BytesIO
from typing import List, Union
import requests
from ..utils import add_end_docstrings, is_decord_available, is_torch_available, logging, requires_backends
from .base import PIPELINE_INIT_ARGS, Pipeline
if is_decord_available():
import numpy as np
from decor... | 64 | 1 |
"""simple docstring"""
import os
from typing import Dict, List, Tuple, TypeVar, Union
__A = TypeVar('''T''')
__A = Union[List[T], Tuple[T, ...]]
__A = Union[T, List[T], Dict[str, T]]
__A = Union[str, bytes, os.PathLike] | 64 | """simple docstring"""
from typing import List, Optional, Tuple, Union
import torch
from ...schedulers import DDIMScheduler
from ...utils import randn_tensor
from ..pipeline_utils import DiffusionPipeline, ImagePipelineOutput
class _snake_case ( a__ ):
def __init__( self : Option... | 64 | 1 |
"""simple docstring"""
import os
import time
import warnings
from dataclasses import dataclass, field
from enum import Enum
from typing import List, Optional, Union
import torch
from filelock import FileLock
from torch.utils.data import Dataset
from ...tokenization_utils_base import PreTrainedTokenizerBase
from ... | 64 | """simple docstring"""
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
__A = logging.get_logger(__name__)
__A = {
'''google/efficie... | 64 | 1 |
"""simple docstring"""
import gc
import unittest
import torch
from parameterized import parameterized
from diffusers import AutoencoderKL
from diffusers.utils import floats_tensor, load_hf_numpy, require_torch_gpu, slow, torch_all_close, torch_device
from diffusers.utils.import_utils import is_xformers_available... | 64 | """simple docstring"""
import importlib
import json
import os
from collections import OrderedDict
from typing import Dict, Optional, Union
# Build the list of all image processors
from ...configuration_utils import PretrainedConfig
from ...dynamic_module_utils import get_class_from_dynamic_module, resolve_trust_r... | 64 | 1 |
"""simple docstring"""
import os
import time
from dataclasses import dataclass, field
from enum import Enum
from typing import Dict, List, Optional, Union
import torch
from filelock import FileLock
from torch.utils.data import Dataset
from ...models.auto.modeling_auto import MODEL_FOR_QUESTION_ANSWERING_MAPPING
... | 64 | """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, normalize, rescale, resize, to_channel_dimension_format
from ...image_utils import (
IMAG... | 64 | 1 |
"""simple docstring"""
from ...utils import (
OptionalDependencyNotAvailable,
is_flax_available,
is_torch_available,
is_transformers_available,
)
try:
if not (is_transformers_available() and is_torch_available()):
raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvai... | 64 | """simple docstring"""
from ...configuration_utils import PretrainedConfig
from ...utils import logging
__A = logging.get_logger(__name__)
__A = {
'''uclanlp/visualbert-vqa''': '''https://huggingface.co/uclanlp/visualbert-vqa/resolve/main/config.json''',
'''uclanlp/visualbert-vqa-pre''': '''... | 64 | 1 |
"""simple docstring"""
def lowercase_ ( _lowerCamelCase: int = 1000 ) -> int:
'''simple docstring'''
return sum(e for e in range(3 , _lowerCamelCase ) if e % 3 == 0 or e % 5 == 0 )
if __name__ == "__main__":
print(F"""{solution() = }""") | 64 | """simple docstring"""
from ...configuration_utils import PretrainedConfig
class _snake_case ( a__ ):
snake_case__ = "bert-generation"
def __init__( self : Optional[int] , UpperCAmelCase : Dict=50358 , UpperCAmelCase : int=1024 , U... | 64 | 1 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tf_available, is_torch_available
__A = {
'''configuration_xlm''': ['''XLM_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''XLMConfig''', '''XLMOnnxConfig'''],
'''tokenization_xlm''': ['... | 64 | """simple docstring"""
import unittest
import numpy as np
from diffusers import OnnxStableDiffusionInpaintPipelineLegacy
from diffusers.utils.testing_utils import (
is_onnx_available,
load_image,
load_numpy,
nightly,
require_onnxruntime,
require_torch_gpu,
)
if is_onnx_available():
... | 64 | 1 |
"""simple docstring"""
from __future__ import annotations
from itertools import permutations
from random import randint
from timeit import repeat
def lowercase_ ( ) -> tuple[list[int], int]:
'''simple docstring'''
__lowerCamelCase : int = [randint(-1000 , 10... | 64 | """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. ... | 64 | 1 |
"""simple docstring"""
from __future__ import annotations
import numpy as np
def lowercase_ ( _lowerCamelCase: np.ndarray ) -> tuple[np.ndarray, np.ndarray]:
'''simple docstring'''
__lowerCamelCase , __lowerCamelCase : Any = np.shape(_lowerCamelCase )
... | 64 | """simple docstring"""
import gc
import unittest
import numpy as np
import torch
from diffusers import AutoencoderKL, DDIMScheduler, DiTPipeline, DPMSolverMultistepScheduler, TransformeraDModel
from diffusers.utils import is_xformers_available, load_numpy, slow, torch_device
from diffusers.utils.testing_utils im... | 64 | 1 |
"""simple docstring"""
import argparse
import glob
import logging
import os
import time
from argparse import Namespace
import numpy as np
import torch
from lightning_base import BaseTransformer, add_generic_args, generic_train
from torch.utils.data import DataLoader, TensorDataset
from transformers import glue_c... | 64 | """simple docstring"""
def lowercase_ ( _lowerCamelCase: int ) -> int:
'''simple docstring'''
if not isinstance(_lowerCamelCase , _lowerCamelCase ):
raise TypeError("Input value must be an 'int' type" )
__lowerCamelCase : Dict = 0
... | 64 | 1 |
"""simple docstring"""
from __future__ import annotations
def lowercase_ ( _lowerCamelCase: list[float] ) -> float:
'''simple docstring'''
__lowerCamelCase : List[str] = 0.00
__lowerCamelCase : Dict = 0
for resistor in resisto... | 64 | """simple docstring"""
import argparse
import json
import requests
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from transformers import ViTImageProcessor, ViTMSNConfig, ViTMSNModel
from transformers.image_utils import IMAGENET_DEFAULT_MEAN, IMAGENET_DEFAULT_STD
torch.set_grad... | 64 | 1 |
"""simple docstring"""
from ...configuration_utils import PretrainedConfig
from ...utils import logging
__A = logging.get_logger(__name__)
__A = {
'''MIT/ast-finetuned-audioset-10-10-0.4593''': (
'''https://huggingface.co/MIT/ast-finetuned-audioset-10-10-0.4593/resolve/main/config.json''... | 64 | """simple docstring"""
from typing import Any
import numpy as np
def lowercase_ ( _lowerCamelCase: np.ndarray ) -> bool:
'''simple docstring'''
return np.array_equal(_lowerCamelCase , matrix.conjugate().T )
def lowercase_ ( _lowerCamelCase: np.ndarray , _lowerCa... | 64 | 1 |
"""simple docstring"""
import unittest
import numpy as np
import timeout_decorator # noqa
from transformers import BlenderbotConfig, is_flax_available
from transformers.testing_utils import jax_device, require_flax, slow
from ...generation.test_flax_utils import FlaxGenerationTesterMixin
from ...test_modeling_... | 64 | """simple docstring"""
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tf_available, is_torch_available
__A = {
'''configuration_xlm''': ['''XLM_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''XLMConfig''', '''XLMOnnxConfig'''],
'''tokenization_xlm''': ['... | 64 | 1 |
"""simple docstring"""
from __future__ import annotations
def lowercase_ ( _lowerCamelCase: list[int] , _lowerCamelCase: int ) -> list[int]:
'''simple docstring'''
__lowerCamelCase : Optional[Any] = 0
__lowerCamelCase : List[str] = ... | 64 | """simple docstring"""
from ...configuration_utils import PretrainedConfig
from ...utils import logging
__A = logging.get_logger(__name__)
__A = {
'''RWKV/rwkv-4-169m-pile''': '''https://huggingface.co/RWKV/rwkv-4-169m-pile/resolve/main/config.json''',
'''RWKV/rwkv-4-430m-pile''': '''https:/... | 64 | 1 |
"""simple docstring"""
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
__A = logging.get_logger(__name__)
__A = {
'''google/efficie... | 64 | """simple docstring"""
import requests
__A = '''YOUR API KEY'''
def lowercase_ ( _lowerCamelCase: str , _lowerCamelCase: str = giphy_api_key ) -> list:
'''simple docstring'''
__lowerCamelCase : Dict = "+".join(query.split() )
__lowerCamelCase ... | 64 | 1 |
"""simple docstring"""
from __future__ import annotations
from collections.abc import Sequence
from typing import Literal
def lowercase_ ( _lowerCamelCase: str , _lowerCamelCase: str ) -> str | Literal[False]:
'''simple docstring'''
__lowerCamelCase : Optional[int] ... | 64 | """simple docstring"""
import copy
from ...configuration_utils import PretrainedConfig
from ...utils import logging
from ..auto import CONFIG_MAPPING
__A = logging.get_logger(__name__)
__A = {
'''ut/deta''': '''https://huggingface.co/ut/deta/resolve/main/config.json''',
}
class _snake_case ... | 64 | 1 |
"""simple docstring"""
# NOTE: This file is deprecated and will be removed in a future version.
# It only exists so that temporarely `from diffusers.pipelines import DiffusionPipeline` works
from ...utils import deprecate
from ..controlnet.multicontrolnet import MultiControlNetModel # noqa: F401
from ..controlnet... | 64 | """simple docstring"""
def lowercase_ ( _lowerCamelCase: int = 4000000 ) -> int:
'''simple docstring'''
__lowerCamelCase : Tuple = [0, 1]
__lowerCamelCase : Union[str, Any] = 0
while fib[i] <= n:
fib.append(fib[i] ... | 64 | 1 |
"""simple docstring"""
import os
import tempfile
from functools import partial
from unittest import TestCase
from unittest.mock import patch
import numpy as np
import pytest
from datasets.arrow_dataset import Dataset
from datasets.search import ElasticSearchIndex, FaissIndex, MissingIndex
from .utils import req... | 64 | """simple docstring"""
def lowercase_ ( _lowerCamelCase: int = 100 ) -> int:
'''simple docstring'''
__lowerCamelCase : Optional[Any] = set()
__lowerCamelCase : Union[str, Any] = 0
__lowerCamelCase : Optional[Any] ... | 64 | 1 |
"""simple docstring"""
from typing import List, Optional, Tuple, Union
import PIL
import torch
from torchvision import transforms
from diffusers.pipeline_utils import DiffusionPipeline, ImagePipelineOutput
from diffusers.schedulers import DDIMScheduler
from diffusers.utils import randn_tensor
__A = trans... | 64 | """simple docstring"""
from __future__ import annotations
from collections.abc import Sequence
from typing import Literal
def lowercase_ ( _lowerCamelCase: str , _lowerCamelCase: str ) -> str | Literal[False]:
'''simple docstring'''
__lowerCamelCase : Optional[int] ... | 64 | 1 |
"""simple docstring"""
import torch
from diffusers import DDIMParallelScheduler
from .test_schedulers import SchedulerCommonTest
class _snake_case ( a__ ):
snake_case__ = (DDIMParallelScheduler,)
snake_case__ = (("eta", 0.0), ("num_inference_steps", 50))
... | 64 | """simple docstring"""
import os
import zipfile
import requests
from get_ci_error_statistics import download_artifact, get_artifacts_links
def lowercase_ ( _lowerCamelCase: str , _lowerCamelCase: Optional[int]=7 ) -> int:
'''simple docstring'''
__lowerCamelCase : List[st... | 64 | 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/data2vec-vi... | 64 | """simple docstring"""
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 Optiona... | 64 | 1 |
"""simple docstring"""
import argparse
import json
from collections import OrderedDict
from pathlib import Path
import requests
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from transformers import (
SegformerConfig,
SegformerForImageClassification,
SegformerForSeman... | 64 | """simple docstring"""
from io import BytesIO
from typing import List, Union
import requests
from ..utils import add_end_docstrings, is_decord_available, is_torch_available, logging, requires_backends
from .base import PIPELINE_INIT_ARGS, Pipeline
if is_decord_available():
import numpy as np
from decor... | 64 | 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
#
# ... | 64 | """simple docstring"""
from typing import List, Optional, Tuple, Union
import torch
from ...schedulers import DDIMScheduler
from ...utils import randn_tensor
from ..pipeline_utils import DiffusionPipeline, ImagePipelineOutput
class _snake_case ( a__ ):
def __init__( self : Option... | 64 | 1 |
"""simple docstring"""
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 GPTaToke... | 64 | """simple docstring"""
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
__A = logging.get_logger(__name__)
__A = {
'''google/efficie... | 64 | 1 |
"""simple docstring"""
import inspect
import os
import unittest
from dataclasses import dataclass
import torch
from accelerate import Accelerator, DistributedDataParallelKwargs, GradScalerKwargs
from accelerate.state import AcceleratorState
from accelerate.test_utils import execute_subprocess_async, require_cuda... | 64 | """simple docstring"""
import importlib
import json
import os
from collections import OrderedDict
from typing import Dict, Optional, Union
# Build the list of all image processors
from ...configuration_utils import PretrainedConfig
from ...dynamic_module_utils import get_class_from_dynamic_module, resolve_trust_r... | 64 | 1 |
"""simple docstring"""
from dataclasses import dataclass
from typing import List, Optional, Union
import numpy as np
import PIL
from PIL import Image
from ...utils import (
BaseOutput,
OptionalDependencyNotAvailable,
is_flax_available,
is_k_diffusion_available,
is_k_diffusion_version,
is_... | 64 | """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, normalize, rescale, resize, to_channel_dimension_format
from ...image_utils import (
IMAG... | 64 | 1 |
"""simple docstring"""
from __future__ import annotations
def lowercase_ ( _lowerCamelCase: list[int] , _lowerCamelCase: int ) -> int:
'''simple docstring'''
if len(_lowerCamelCase ) < k or k < 0:
raise ValueError("Invalid Input" )
__lowerCamelCase : ... | 64 | """simple docstring"""
from ...configuration_utils import PretrainedConfig
from ...utils import logging
__A = logging.get_logger(__name__)
__A = {
'''uclanlp/visualbert-vqa''': '''https://huggingface.co/uclanlp/visualbert-vqa/resolve/main/config.json''',
'''uclanlp/visualbert-vqa-pre''': '''... | 64 | 1 |
"""simple docstring"""
import inspect
import os
import unittest
import torch
import accelerate
from accelerate import Accelerator
from accelerate.test_utils import execute_subprocess_async, require_multi_gpu
from accelerate.utils import patch_environment
class _snake_case ( unittest.TestCase ):
... | 64 | """simple docstring"""
from ...configuration_utils import PretrainedConfig
class _snake_case ( a__ ):
snake_case__ = "bert-generation"
def __init__( self : Optional[int] , UpperCAmelCase : Dict=50358 , UpperCAmelCase : int=1024 , U... | 64 | 1 |
"""simple docstring"""
import argparse
from collections import OrderedDict
from pathlib import Path
import torch
from transformers import (
VisualBertConfig,
VisualBertForMultipleChoice,
VisualBertForPreTraining,
VisualBertForQuestionAnswering,
VisualBertForVisualReasoning,
)
from transformer... | 64 | """simple docstring"""
import unittest
import numpy as np
from diffusers import OnnxStableDiffusionInpaintPipelineLegacy
from diffusers.utils.testing_utils import (
is_onnx_available,
load_image,
load_numpy,
nightly,
require_onnxruntime,
require_torch_gpu,
)
if is_onnx_available():
... | 64 | 1 |
"""simple docstring"""
import logging
import torch
from accelerate import Accelerator
from arguments import EvaluationArguments
from datasets import load_dataset
from torch.utils.data import IterableDataset
from torch.utils.data.dataloader import DataLoader
from transformers import AutoModelForCausalLM, AutoToke... | 64 | """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. ... | 64 | 1 |
"""simple docstring"""
import importlib
import os
from dataclasses import dataclass
from enum import Enum
from typing import Any, Dict, Optional, Union
import torch
from ..utils import BaseOutput
__A = '''scheduler_config.json'''
class _snake_case ( a__ ):
snake_case__ = ... | 64 | """simple docstring"""
import gc
import unittest
import numpy as np
import torch
from diffusers import AutoencoderKL, DDIMScheduler, DiTPipeline, DPMSolverMultistepScheduler, TransformeraDModel
from diffusers.utils import is_xformers_available, load_numpy, slow, torch_device
from diffusers.utils.testing_utils im... | 64 | 1 |
"""simple docstring"""
import json
import os
import re
import shutil
import tempfile
import unittest
from typing import Tuple
from transformers import AddedToken, BatchEncoding, PerceiverTokenizer
from transformers.utils import cached_property, is_tf_available, is_torch_available
from ...test_tokenization_common... | 64 | """simple docstring"""
def lowercase_ ( _lowerCamelCase: int ) -> int:
'''simple docstring'''
if not isinstance(_lowerCamelCase , _lowerCamelCase ):
raise TypeError("Input value must be an 'int' type" )
__lowerCamelCase : Dict = 0
... | 64 | 1 |
"""simple docstring"""
import shutil
import tempfile
import unittest
from transformers import SPIECE_UNDERLINE, BatchEncoding, MBartaaTokenizer, MBartaaTokenizerFast, is_torch_available
from transformers.testing_utils import (
get_tests_dir,
nested_simplify,
require_sentencepiece,
require_tokenize... | 64 | """simple docstring"""
import argparse
import json
import requests
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from transformers import ViTImageProcessor, ViTMSNConfig, ViTMSNModel
from transformers.image_utils import IMAGENET_DEFAULT_MEAN, IMAGENET_DEFAULT_STD
torch.set_grad... | 64 | 1 |
"""simple docstring"""
def lowercase_ ( _lowerCamelCase: list ) -> list:
'''simple docstring'''
if len(_lowerCamelCase ) <= 1:
return [tuple(_lowerCamelCase )]
__lowerCamelCase : Union[str, Any] = []
def generate(_lowerCamelCase: int... | 64 | """simple docstring"""
from typing import Any
import numpy as np
def lowercase_ ( _lowerCamelCase: np.ndarray ) -> bool:
'''simple docstring'''
return np.array_equal(_lowerCamelCase , matrix.conjugate().T )
def lowercase_ ( _lowerCamelCase: np.ndarray , _lowerCa... | 64 | 1 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available, is_vision_available
__A = {
'''configuration_poolformer''': [
'''POOLFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP''',
'''PoolFormerConfig''',
''... | 64 | """simple docstring"""
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tf_available, is_torch_available
__A = {
'''configuration_xlm''': ['''XLM_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''XLMConfig''', '''XLMOnnxConfig'''],
'''tokenization_xlm''': ['... | 64 | 1 |
"""simple docstring"""
from ...configuration_utils import PretrainedConfig
from ...utils import logging
__A = logging.get_logger(__name__)
__A = {
'''uclanlp/visualbert-vqa''': '''https://huggingface.co/uclanlp/visualbert-vqa/resolve/main/config.json''',
'''uclanlp/visualbert-vqa-pre''': '''... | 64 | """simple docstring"""
from ...configuration_utils import PretrainedConfig
from ...utils import logging
__A = logging.get_logger(__name__)
__A = {
'''RWKV/rwkv-4-169m-pile''': '''https://huggingface.co/RWKV/rwkv-4-169m-pile/resolve/main/config.json''',
'''RWKV/rwkv-4-430m-pile''': '''https:/... | 64 | 1 |
"""simple docstring"""
import json
import unittest
import numpy as np
from huggingface_hub import hf_hub_download
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 ImageProcessin... | 64 | """simple docstring"""
import requests
__A = '''YOUR API KEY'''
def lowercase_ ( _lowerCamelCase: str , _lowerCamelCase: str = giphy_api_key ) -> list:
'''simple docstring'''
__lowerCamelCase : Dict = "+".join(query.split() )
__lowerCamelCase ... | 64 | 1 |
"""simple docstring"""
from ..utils import (
OptionalDependencyNotAvailable,
is_flax_available,
is_scipy_available,
is_torch_available,
is_torchsde_available,
)
try:
if not is_torch_available():
raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
from... | 64 | """simple docstring"""
import copy
from ...configuration_utils import PretrainedConfig
from ...utils import logging
from ..auto import CONFIG_MAPPING
__A = logging.get_logger(__name__)
__A = {
'''ut/deta''': '''https://huggingface.co/ut/deta/resolve/main/config.json''',
}
class _snake_case ... | 64 | 1 |
"""simple docstring"""
import json
import os
from dataclasses import dataclass
from functools import partial
from typing import Callable
import flax.linen as nn
import jax
import jax.numpy as jnp
import joblib
import optax
import wandb
from flax import jax_utils, struct, traverse_util
from flax.serialization impo... | 64 | """simple docstring"""
def lowercase_ ( _lowerCamelCase: int = 4000000 ) -> int:
'''simple docstring'''
__lowerCamelCase : Tuple = [0, 1]
__lowerCamelCase : Union[str, Any] = 0
while fib[i] <= n:
fib.append(fib[i] ... | 64 | 1 |
"""simple docstring"""
import contextlib
from multiprocessing import Pool, RLock
from tqdm.auto import tqdm
from ..utils import experimental, logging
__A = logging.get_logger(__name__)
class _snake_case :
snake_case__ = None
@experimental
def lowercase_ ( _lowerCamel... | 64 | """simple docstring"""
def lowercase_ ( _lowerCamelCase: int = 100 ) -> int:
'''simple docstring'''
__lowerCamelCase : Optional[Any] = set()
__lowerCamelCase : Union[str, Any] = 0
__lowerCamelCase : Optional[Any] ... | 64 | 1 |
"""simple docstring"""
from queue import Queue
from typing import TYPE_CHECKING, Optional
if TYPE_CHECKING:
from ..models.auto import AutoTokenizer
class _snake_case :
def lowerCamelCase__ ( self : Optional[int] , UpperCAmelCase : List[str] ):
ra... | 64 | """simple docstring"""
from __future__ import annotations
from collections.abc import Sequence
from typing import Literal
def lowercase_ ( _lowerCamelCase: str , _lowerCamelCase: str ) -> str | Literal[False]:
'''simple docstring'''
__lowerCamelCase : Optional[int] ... | 64 | 1 |
"""simple docstring"""
def lowercase_ ( _lowerCamelCase: list[int] , _lowerCamelCase: list[int] ) -> tuple[float, float]:
'''simple docstring'''
if not len(_lowerCamelCase ) == len(_lowerCamelCase ) == 3:
raise ValueError("Please enter a valid equation." )
if ... | 64 | """simple docstring"""
import os
import zipfile
import requests
from get_ci_error_statistics import download_artifact, get_artifacts_links
def lowercase_ ( _lowerCamelCase: str , _lowerCamelCase: Optional[int]=7 ) -> int:
'''simple docstring'''
__lowerCamelCase : List[st... | 64 | 1 |
"""simple docstring"""
# using dfs for finding eulerian path traversal
def lowercase_ ( _lowerCamelCase: Dict , _lowerCamelCase: Optional[Any] , _lowerCamelCase: List[Any] , _lowerCamelCase: List[Any]=None ) -> Dict:
'''simple docstring'''
__lowerCamelCase : Lis... | 64 | """simple docstring"""
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 Optiona... | 64 | 1 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_sentencepiece_available,
is_tf_available,
is_tokenizers_available,
is_torch_available,
)
__A = {'''configuration_xglm''': ['''XGLM_P... | 64 | """simple docstring"""
from io import BytesIO
from typing import List, Union
import requests
from ..utils import add_end_docstrings, is_decord_available, is_torch_available, logging, requires_backends
from .base import PIPELINE_INIT_ARGS, Pipeline
if is_decord_available():
import numpy as np
from decor... | 64 | 1 |
"""simple docstring"""
import json
import os
import tempfile
import transformers
import datasets
from utils import generate_example_dataset, get_duration
__A = 500000
__A, __A = os.path.split(__file__)
__A = os.path.join(RESULTS_BASEPATH, '''results''', RESULTS_FILENAME.replace('''.py''... | 64 | """simple docstring"""
from typing import List, Optional, Tuple, Union
import torch
from ...schedulers import DDIMScheduler
from ...utils import randn_tensor
from ..pipeline_utils import DiffusionPipeline, ImagePipelineOutput
class _snake_case ( a__ ):
def __init__( self : Option... | 64 | 1 |
"""simple docstring"""
import warnings
from ..trainer import Trainer
from ..utils import logging
__A = logging.get_logger(__name__)
class _snake_case ( a__ ):
def __init__( self : Tuple , UpperCAmelCase : List[str]=None , **UpperCAmelCase : List[Any... | 64 | """simple docstring"""
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
__A = logging.get_logger(__name__)
__A = {
'''google/efficie... | 64 | 1 |
"""simple docstring"""
def lowercase_ ( _lowerCamelCase: str , _lowerCamelCase: list[str] ) -> str:
'''simple docstring'''
__lowerCamelCase : Tuple = ""
for word_or_phrase in separated:
if not isinstance(_lowerCamelCase , _lowerCamelC... | 64 | """simple docstring"""
import importlib
import json
import os
from collections import OrderedDict
from typing import Dict, Optional, Union
# Build the list of all image processors
from ...configuration_utils import PretrainedConfig
from ...dynamic_module_utils import get_class_from_dynamic_module, resolve_trust_r... | 64 | 1 |
"""simple docstring"""
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,
AutoMod... | 64 | """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, normalize, rescale, resize, to_channel_dimension_format
from ...image_utils import (
IMAG... | 64 | 1 |
"""simple docstring"""
from string import ascii_lowercase, ascii_uppercase
def lowercase_ ( _lowerCamelCase: str ) -> str:
'''simple docstring'''
if not sentence:
return ""
__lowerCamelCase : List[str] = dict(zip(_lowerCamelCase , _lower... | 64 | """simple docstring"""
from ...configuration_utils import PretrainedConfig
from ...utils import logging
__A = logging.get_logger(__name__)
__A = {
'''uclanlp/visualbert-vqa''': '''https://huggingface.co/uclanlp/visualbert-vqa/resolve/main/config.json''',
'''uclanlp/visualbert-vqa-pre''': '''... | 64 | 1 |
"""simple docstring"""
import gc
import unittest
from diffusers import FlaxDPMSolverMultistepScheduler, FlaxStableDiffusionPipeline
from diffusers.utils import is_flax_available, slow
from diffusers.utils.testing_utils import require_flax
if is_flax_available():
import jax
import jax.numpy as jnp
fr... | 64 | """simple docstring"""
from ...configuration_utils import PretrainedConfig
class _snake_case ( a__ ):
snake_case__ = "bert-generation"
def __init__( self : Optional[int] , UpperCAmelCase : Dict=50358 , UpperCAmelCase : int=1024 , U... | 64 | 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 YolosConfig, YolosForObjectDetection, YolosImageProcessor
from transformers.utils import logging
logging.set_verbos... | 64 | """simple docstring"""
import unittest
import numpy as np
from diffusers import OnnxStableDiffusionInpaintPipelineLegacy
from diffusers.utils.testing_utils import (
is_onnx_available,
load_image,
load_numpy,
nightly,
require_onnxruntime,
require_torch_gpu,
)
if is_onnx_available():
... | 64 | 1 |
"""simple docstring"""
from ...configuration_utils import PretrainedConfig
from ...utils import logging
__A = logging.get_logger(__name__)
__A = {
'''weiweishi/roc-bert-base-zh''': '''https://huggingface.co/weiweishi/roc-bert-base-zh/resolve/main/config.json''',
}
class _snake_case ( a_... | 64 | """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. ... | 64 | 1 |
"""simple docstring"""
from pathlib import Path
import fire
def lowercase_ ( _lowerCamelCase: str , _lowerCamelCase: str , _lowerCamelCase: int ) -> str:
'''simple docstring'''
__lowerCamelCase : List[Any] = Path(_lowerCamelCase )
__lowerCamelC... | 64 | """simple docstring"""
import gc
import unittest
import numpy as np
import torch
from diffusers import AutoencoderKL, DDIMScheduler, DiTPipeline, DPMSolverMultistepScheduler, TransformeraDModel
from diffusers.utils import is_xformers_available, load_numpy, slow, torch_device
from diffusers.utils.testing_utils im... | 64 | 1 |
"""simple docstring"""
import json
from typing import TYPE_CHECKING, List, Optional, Tuple
from tokenizers import pre_tokenizers
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import logging
if TYPE_CHECKING:
from transformers.pipelines.conversational import Conversation
__A... | 64 | """simple docstring"""
def lowercase_ ( _lowerCamelCase: int ) -> int:
'''simple docstring'''
if not isinstance(_lowerCamelCase , _lowerCamelCase ):
raise TypeError("Input value must be an 'int' type" )
__lowerCamelCase : Dict = 0
... | 64 | 1 |
"""simple docstring"""
import csv
import tweepy
# Twitter API credentials
__A = ''''''
__A = ''''''
__A = ''''''
__A = ''''''
def lowercase_ ( _lowerCamelCase: str ) -> None:
'''simple docstring'''
__lowerCamelCase : str = tweepy.OAuthH... | 64 | """simple docstring"""
import argparse
import json
import requests
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from transformers import ViTImageProcessor, ViTMSNConfig, ViTMSNModel
from transformers.image_utils import IMAGENET_DEFAULT_MEAN, IMAGENET_DEFAULT_STD
torch.set_grad... | 64 | 1 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_sentencepiece_available,
is_tokenizers_available,
is_torch_available,
)
__A = {
'''configuration_llama''': ['''LLAMA_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''L... | 64 | """simple docstring"""
from typing import Any
import numpy as np
def lowercase_ ( _lowerCamelCase: np.ndarray ) -> bool:
'''simple docstring'''
return np.array_equal(_lowerCamelCase , matrix.conjugate().T )
def lowercase_ ( _lowerCamelCase: np.ndarray , _lowerCa... | 64 | 1 |
"""simple docstring"""
from dataclasses import dataclass, field
from typing import ClassVar, Dict
from ..features import Features, Value
from .base import TaskTemplate
@dataclass(frozen=a__ )
class _snake_case ( a__ ):
snake_case__ = field(default="language-modeling" , meta... | 64 | """simple docstring"""
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tf_available, is_torch_available
__A = {
'''configuration_xlm''': ['''XLM_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''XLMConfig''', '''XLMOnnxConfig'''],
'''tokenization_xlm''': ['... | 64 | 1 |
"""simple docstring"""
def lowercase_ ( _lowerCamelCase: int ) -> bool:
'''simple docstring'''
if not isinstance(_lowerCamelCase , _lowerCamelCase ):
__lowerCamelCase : Dict = F"""Input value of [number={number}] must be an integer"""
... | 64 | """simple docstring"""
from ...configuration_utils import PretrainedConfig
from ...utils import logging
__A = logging.get_logger(__name__)
__A = {
'''RWKV/rwkv-4-169m-pile''': '''https://huggingface.co/RWKV/rwkv-4-169m-pile/resolve/main/config.json''',
'''RWKV/rwkv-4-430m-pile''': '''https:/... | 64 | 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... | 64 | """simple docstring"""
import requests
__A = '''YOUR API KEY'''
def lowercase_ ( _lowerCamelCase: str , _lowerCamelCase: str = giphy_api_key ) -> list:
'''simple docstring'''
__lowerCamelCase : Dict = "+".join(query.split() )
__lowerCamelCase ... | 64 | 1 |
"""simple docstring"""
def lowercase_ ( _lowerCamelCase: list[list] ) -> list[list]:
'''simple docstring'''
__lowerCamelCase : Optional[int] = current_set.copy()
for row_index, row in enumerate(_lowerCamelCase ):
__lowerCamelCase : int ... | 64 | """simple docstring"""
import copy
from ...configuration_utils import PretrainedConfig
from ...utils import logging
from ..auto import CONFIG_MAPPING
__A = logging.get_logger(__name__)
__A = {
'''ut/deta''': '''https://huggingface.co/ut/deta/resolve/main/config.json''',
}
class _snake_case ... | 64 | 1 |
"""simple docstring"""
from unittest.mock import patch
import pyspark
from datasets.packaged_modules.spark.spark import (
Spark,
SparkExamplesIterable,
_generate_iterable_examples,
)
from ..utils import (
require_dill_gt_0_3_2,
require_not_windows,
)
def lowercase_ ( _lowerCamelC... | 64 | """simple docstring"""
def lowercase_ ( _lowerCamelCase: int = 4000000 ) -> int:
'''simple docstring'''
__lowerCamelCase : Tuple = [0, 1]
__lowerCamelCase : Union[str, Any] = 0
while fib[i] <= n:
fib.append(fib[i] ... | 64 | 1 |
"""simple docstring"""
from typing import Optional
from torch import nn
from .transformer_ad import TransformeraDModel, TransformeraDModelOutput
class _snake_case ( nn.Module ):
def __init__( self : Optional[int] , UpperCAmelCase : int = 16 , UpperCAmelCase : ... | 64 | """simple docstring"""
def lowercase_ ( _lowerCamelCase: int = 100 ) -> int:
'''simple docstring'''
__lowerCamelCase : Optional[Any] = set()
__lowerCamelCase : Union[str, Any] = 0
__lowerCamelCase : Optional[Any] ... | 64 | 1 |
"""simple docstring"""
import unittest
from transformers import GPTNeoXJapaneseConfig, is_torch_available
from transformers.models.gpt_neox_japanese.tokenization_gpt_neox_japanese import GPTNeoXJapaneseTokenizer
from transformers.testing_utils import require_torch, slow, torch_device
from ...test_configuration_c... | 64 | """simple docstring"""
from __future__ import annotations
from collections.abc import Sequence
from typing import Literal
def lowercase_ ( _lowerCamelCase: str , _lowerCamelCase: str ) -> str | Literal[False]:
'''simple docstring'''
__lowerCamelCase : Optional[int] ... | 64 | 1 |
"""simple docstring"""
from __future__ import annotations
import string
from itertools import cycle, product
from pathlib import Path
__A = (
string.ascii_letters + string.digits + string.punctuation + string.whitespace
)
__A = [ord(letter) for letter in string.ascii_lowercase]
__A = {ord(c... | 64 | """simple docstring"""
import os
import zipfile
import requests
from get_ci_error_statistics import download_artifact, get_artifacts_links
def lowercase_ ( _lowerCamelCase: str , _lowerCamelCase: Optional[int]=7 ) -> int:
'''simple docstring'''
__lowerCamelCase : List[st... | 64 | 1 |
"""simple docstring"""
import baseaa
def lowercase_ ( _lowerCamelCase: str ) -> bytes:
'''simple docstring'''
return baseaa.baaencode(string.encode("utf-8" ) )
def lowercase_ ( _lowerCamelCase: bytes ) -> str:
'''simple docstring'''
return baseaa.baadec... | 64 | """simple docstring"""
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 Optiona... | 64 | 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... | 64 | """simple docstring"""
from io import BytesIO
from typing import List, Union
import requests
from ..utils import add_end_docstrings, is_decord_available, is_torch_available, logging, requires_backends
from .base import PIPELINE_INIT_ARGS, Pipeline
if is_decord_available():
import numpy as np
from decor... | 64 | 1 |
"""simple docstring"""
import argparse
from collections import OrderedDict
from pathlib import Path
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from torchvision.transforms import functional as F
from transformers import DetrImageProcessor, TableTransformerConfig, TableTransform... | 64 | """simple docstring"""
from typing import List, Optional, Tuple, Union
import torch
from ...schedulers import DDIMScheduler
from ...utils import randn_tensor
from ..pipeline_utils import DiffusionPipeline, ImagePipelineOutput
class _snake_case ( a__ ):
def __init__( self : Option... | 64 | 1 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import _LazyModule
__A = {'''processing_wav2vec2_with_lm''': ['''Wav2Vec2ProcessorWithLM''']}
if TYPE_CHECKING:
from .processing_wavaveca_with_lm import WavaVecaProcessorWithLM
else:
import sys
__A = _LazyModule(__n... | 64 | """simple docstring"""
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
__A = logging.get_logger(__name__)
__A = {
'''google/efficie... | 64 | 1 |
"""simple docstring"""
import argparse
import torch
from transformers import (
WavaVecaConfig,
WavaVecaFeatureExtractor,
WavaVecaForAudioFrameClassification,
WavaVecaForSequenceClassification,
WavaVecaForXVector,
logging,
)
logging.set_verbosity_info()
__A = logging.get_logger(__n... | 64 | """simple docstring"""
import importlib
import json
import os
from collections import OrderedDict
from typing import Dict, Optional, Union
# Build the list of all image processors
from ...configuration_utils import PretrainedConfig
from ...dynamic_module_utils import get_class_from_dynamic_module, resolve_trust_r... | 64 | 1 |
"""simple docstring"""
from ...configuration_utils import PretrainedConfig
from ...utils import logging
__A = logging.get_logger(__name__)
__A = {
'''facebook/xglm-564M''': '''https://huggingface.co/facebook/xglm-564M/resolve/main/config.json''',
# See all XGLM models at https://huggingface.... | 64 | """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, normalize, rescale, resize, to_channel_dimension_format
from ...image_utils import (
IMAG... | 64 | 1 |
"""simple docstring"""
import numpy as np
from cva import destroyAllWindows, imread, imshow, waitKey
class _snake_case :
def __init__( self : List[str] , UpperCAmelCase : int , UpperCAmelCase : int , UpperCAmelCase : int ):
if dst_widt... | 64 | """simple docstring"""
from ...configuration_utils import PretrainedConfig
from ...utils import logging
__A = logging.get_logger(__name__)
__A = {
'''uclanlp/visualbert-vqa''': '''https://huggingface.co/uclanlp/visualbert-vqa/resolve/main/config.json''',
'''uclanlp/visualbert-vqa-pre''': '''... | 64 | 1 |
"""simple docstring"""
def lowercase_ ( _lowerCamelCase: str , _lowerCamelCase: str ) -> bool:
'''simple docstring'''
__lowerCamelCase : str = len(_lowerCamelCase )
__lowerCamelCase : Tuple = len(_lowerCamelCase )
__lowerCa... | 64 | """simple docstring"""
from ...configuration_utils import PretrainedConfig
class _snake_case ( a__ ):
snake_case__ = "bert-generation"
def __init__( self : Optional[int] , UpperCAmelCase : Dict=50358 , UpperCAmelCase : int=1024 , U... | 64 | 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
#
# ... | 64 | """simple docstring"""
import unittest
import numpy as np
from diffusers import OnnxStableDiffusionInpaintPipelineLegacy
from diffusers.utils.testing_utils import (
is_onnx_available,
load_image,
load_numpy,
nightly,
require_onnxruntime,
require_torch_gpu,
)
if is_onnx_available():
... | 64 | 1 |
"""simple docstring"""
import os
from tempfile import TemporaryDirectory
from unittest import TestCase
import pytest
from absl.testing import parameterized
from datasets import config
from datasets.arrow_reader import HF_GCP_BASE_URL
from datasets.builder import DatasetBuilder
from datasets.dataset_dict import I... | 64 | """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. ... | 64 | 1 |
"""simple docstring"""
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 .to... | 64 | """simple docstring"""
import gc
import unittest
import numpy as np
import torch
from diffusers import AutoencoderKL, DDIMScheduler, DiTPipeline, DPMSolverMultistepScheduler, TransformeraDModel
from diffusers.utils import is_xformers_available, load_numpy, slow, torch_device
from diffusers.utils.testing_utils im... | 64 | 1 |
"""simple docstring"""
import pickle
import shutil
import tempfile
import unittest
from transformers import SPIECE_UNDERLINE, XLMRobertaTokenizer, XLMRobertaTokenizerFast
from transformers.testing_utils import get_tests_dir, require_sentencepiece, require_tokenizers, slow
from transformers.utils import cached_pro... | 64 | """simple docstring"""
def lowercase_ ( _lowerCamelCase: int ) -> int:
'''simple docstring'''
if not isinstance(_lowerCamelCase , _lowerCamelCase ):
raise TypeError("Input value must be an 'int' type" )
__lowerCamelCase : Dict = 0
... | 64 | 1 |
"""simple docstring"""
from typing import Optional, Union
import numpy as np
from ...image_processing_utils import BaseImageProcessor, BatchFeature
from ...image_transforms import get_image_size, pad, rescale, to_channel_dimension_format
from ...image_utils import ChannelDimension, ImageInput, make_list_of_image... | 64 | """simple docstring"""
import argparse
import json
import requests
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from transformers import ViTImageProcessor, ViTMSNConfig, ViTMSNModel
from transformers.image_utils import IMAGENET_DEFAULT_MEAN, IMAGENET_DEFAULT_STD
torch.set_grad... | 64 | 1 |
"""simple docstring"""
import re
import warnings
from contextlib import contextmanager
from ...processing_utils import ProcessorMixin
class _snake_case ( a__ ):
snake_case__ = ["image_processor", "tokenizer"]
snake_case__ = "AutoImageProcessor"
snake_case_... | 64 | """simple docstring"""
from typing import Any
import numpy as np
def lowercase_ ( _lowerCamelCase: np.ndarray ) -> bool:
'''simple docstring'''
return np.array_equal(_lowerCamelCase , matrix.conjugate().T )
def lowercase_ ( _lowerCamelCase: np.ndarray , _lowerCa... | 64 | 1 |
"""simple docstring"""
from math import factorial
__A = {str(d): factorial(d) for d in range(10)}
def lowercase_ ( _lowerCamelCase: int ) -> int:
'''simple docstring'''
return sum(DIGIT_FACTORIAL[d] for d in str(_lowerCamelCase ) )
def lowercase_ ( ) -> int:
... | 64 | """simple docstring"""
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tf_available, is_torch_available
__A = {
'''configuration_xlm''': ['''XLM_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''XLMConfig''', '''XLMOnnxConfig'''],
'''tokenization_xlm''': ['... | 64 | 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''',
... | 64 | """simple docstring"""
from ...configuration_utils import PretrainedConfig
from ...utils import logging
__A = logging.get_logger(__name__)
__A = {
'''RWKV/rwkv-4-169m-pile''': '''https://huggingface.co/RWKV/rwkv-4-169m-pile/resolve/main/config.json''',
'''RWKV/rwkv-4-430m-pile''': '''https:/... | 64 | 1 |
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