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'''simple docstring''' import random from typing import Any def a__ ( lowerCAmelCase__ ) -> list[Any]: for _ in range(len(lowerCAmelCase__ ) ): UpperCAmelCase__ : int = random.randint(0 , len(lowerCAmelCase__ ) - 1 ) UpperCAmelCas...
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'''simple docstring''' from ..utils import DummyObject, requires_backends class lowerCamelCase_ ( metaclass=__a ): lowerCAmelCase__ = ['torch', 'torchsde'] def __init__( self : Tuple , *_A : Any , **_A : Optional[Any] ...
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'''simple docstring''' import math def a__ ( ) -> None: UpperCAmelCase__ : List[str] = input('''Enter message: ''' ) UpperCAmelCase__ : Any = int(input(F"""Enter key [2-{len(lowerCAmelCase__ ) - 1}]: """ ) ) UpperCAmelCase__ ...
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'''simple docstring''' from ...configuration_utils import PretrainedConfig from ...utils import logging UpperCamelCase__ = logging.get_logger(__name__) UpperCamelCase__ = {'''ctrl''': '''https://huggingface.co/ctrl/resolve/main/config.json'''} class lowerCamelCase_ ( ...
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'''simple docstring''' from typing import TYPE_CHECKING from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tokenizers_available, is_torch_available UpperCamelCase__ = { '''configuration_nezha''': ['''NEZHA_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''NezhaConfig'''], } try: ...
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'''simple docstring''' import json import os import subprocess import unittest from ast import literal_eval import pytest from parameterized import parameterized, parameterized_class from . import is_sagemaker_available if is_sagemaker_available(): from sagemaker import Session, TrainingJobAna...
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'''simple docstring''' from typing import TYPE_CHECKING from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available, is_vision_available UpperCamelCase__ = { '''configuration_conditional_detr''': [ '''CONDITIONAL_DETR_PRETRAINED_CONFIG_ARCHIVE_MAP''', ...
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'''simple docstring''' import math_equivalence # From: git+https://github.com/hendrycks/math.git import datasets UpperCamelCase__ = '''\ @article{hendrycksmath2021, title={Measuring Mathematical Problem Solving With the MATH Dataset}, author={Dan Hendrycks and Collin Burns and Saura...
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'''simple docstring''' from typing import TYPE_CHECKING # rely on isort to merge the imports from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available UpperCamelCase__ = { '''configuration_informer''': [ '''INFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP''', ...
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'''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_b...
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'''simple docstring''' from itertools import product def a__ ( lowerCAmelCase__ , lowerCAmelCase__ ) -> list[int]: UpperCAmelCase__ : Optional[Any] = sides_number UpperCAmelCase__ : Optional[Any] = max_face_number * dice_number ...
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'''simple docstring''' import random from typing import Any def a__ ( lowerCAmelCase__ ) -> list[Any]: for _ in range(len(lowerCAmelCase__ ) ): UpperCAmelCase__ : int = random.randint(0 , len(lowerCAmelCase__ ) - 1 ) UpperCAmelCas...
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'''simple docstring''' from typing import TYPE_CHECKING from ...utils import ( OptionalDependencyNotAvailable, _LazyModule, is_sentencepiece_available, is_speech_available, is_torch_available, ) UpperCamelCase__ = { '''configuration_trocr''': ['''TROCR_PRETRAINED_C...
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'''simple docstring''' import math def a__ ( lowerCAmelCase__ ) -> list[int]: UpperCAmelCase__ : List[Any] = [] UpperCAmelCase__ : Dict = 2 UpperCAmelCase__ : Optional[Any] = int(math.sqrt(lowerCAmelCase__ )...
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'''simple docstring''' from multiprocessing import Lock, Pipe, Process # lock used to ensure that two processes do not access a pipe at the same time UpperCamelCase__ = Lock() def a__ ( lowerCAmelCase__ , lowerCAmelCase__ , lowerCAmelCase__ , lowerCAmelCase__ , ...
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'''simple docstring''' import gc import random import unittest import numpy as np import torch from PIL import Image from transformers import CLIPTextConfig, CLIPTextModel, CLIPTokenizer from diffusers import AutoencoderKL, PNDMScheduler, StableDiffusionInpaintPipeline, UNetaDConditionModel from diff...
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'''simple docstring''' import math import tensorflow as tf from packaging import version def a__ ( lowerCAmelCase__ ) -> Optional[int]: UpperCAmelCase__ : Union[str, Any] = tf.convert_to_tensor(lowerCAmelCase__ ) UpperCAmelCase__ : Tuple ...
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'''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 ...tes...
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'''simple docstring''' def a__ ( lowerCAmelCase__ = 1_00_00_00 ) -> int: UpperCAmelCase__ : str = 1 UpperCAmelCase__ : int = 1 UpperCAmelCase__ : int = {1: 1} for inputa in range(2 , lowerCAmelCase__ ): ...
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'''simple docstring''' import os import tempfile from functools import partial from unittest import TestCase from unittest.mock import patch import datasets import datasets.config from .utils import require_beam class lowerCamelCase_ ( datasets.BeamBasedBuilder ): ...
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'''simple docstring''' import gc import unittest import numpy as np import torch from torch.backends.cuda import sdp_kernel from diffusers import ( CMStochasticIterativeScheduler, ConsistencyModelPipeline, UNetaDModel, ) from diffusers.utils import randn_tensor, slow, torch_device from...
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'''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-...
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'''simple docstring''' import gc import unittest import numpy as np import torch from diffusers import StableDiffusionKDiffusionPipeline from diffusers.utils import slow, torch_device from diffusers.utils.testing_utils import enable_full_determinism, require_torch_gpu enable_full_determinism() ...
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'''simple docstring''' import argparse import torch from transformers import GPTaConfig, GPTaModel, load_tf_weights_in_gpta from transformers.utils import CONFIG_NAME, WEIGHTS_NAME, logging logging.set_verbosity_info() def a__ ( lowerCAmelCase__ , lowerCAmelCase__ , lowerC...
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'''simple docstring''' import os import sys UpperCamelCase__ = os.path.join(os.path.dirname(__file__), '''src''') sys.path.append(SRC_DIR) from transformers import ( AutoConfig, AutoModel, AutoModelForCausalLM, AutoModelForMaskedLM, AutoModelForQuestionAnswering, ...
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'''simple docstring''' from __future__ import annotations import copy import inspect import unittest import numpy as np from transformers import is_tf_available, is_vision_available from transformers.models.auto import get_values from transformers.testing_utils import require_tf, slow from transfor...
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'''simple docstring''' import warnings from transformers import AutoTokenizer from transformers.utils import is_torch_available from transformers.utils.generic import ExplicitEnum from ...processing_utils import ProcessorMixin if is_torch_available(): import torch class lowerCamelCa...
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'''simple docstring''' import webbrowser from sys import argv from urllib.parse import parse_qs, quote import requests from bsa import BeautifulSoup from fake_useragent import UserAgent if __name__ == "__main__": UpperCamelCase__ = '''%20'''.join(argv[1:]) if len(argv) > 1 else quote(str(in...
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'''simple docstring''' import warnings from ...utils import logging from .image_processing_flava import FlavaImageProcessor UpperCamelCase__ = logging.get_logger(__name__) class lowerCamelCase_ ( __a ): def __init__( self : Union[str, Any] ,...
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'''simple docstring''' from pathlib import Path import cva import numpy as np from matplotlib import pyplot as plt def a__ ( lowerCAmelCase__ , lowerCAmelCase__ , lowerCAmelCase__ , lowerCAmelCase__ , lowerCAmelCase__ ) -> np.ndarray: UpperCAmelCase__ ...
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'''simple docstring''' import json import os from typing import Optional import numpy as np from ...feature_extraction_utils import BatchFeature from ...processing_utils import ProcessorMixin from ...utils import logging from ...utils.hub import get_file_from_repo from ..auto import AutoTokenizer ...
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'''simple docstring''' from datetime import datetime as dt import os from github import Github UpperCamelCase__ = [ '''good first issue''', '''good second issue''', '''good difficult issue''', '''feature request''', '''new model''', '''wip''', ] def ...
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'''simple docstring''' import argparse import json from pathlib import Path import torch import torchaudio from datasets import load_dataset from huggingface_hub import hf_hub_download from transformers import ASTConfig, ASTFeatureExtractor, ASTForAudioClassification from transformers.utils import lo...
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'''simple docstring''' from typing import List, Optional, Tuple, Union import torch from ...utils import logging, randn_tensor from ..pipeline_utils import AudioPipelineOutput, DiffusionPipeline UpperCamelCase__ = logging.get_logger(__name__) # pylint: disable=invalid-name class ...
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'''simple docstring''' from typing import TYPE_CHECKING from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available UpperCamelCase__ = { '''configuration_timesformer''': ['''TIMESFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''TimesformerConfig'''], } try: if not...
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'''simple docstring''' from math import factorial def a__ ( lowerCAmelCase__ , lowerCAmelCase__ , lowerCAmelCase__ ) -> float: if successes > trials: raise ValueError('''successes must be lower or equal to trials''' ) if trials < 0 or successes < 0: ...
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'''simple docstring''' import argparse from argparse import Namespace import torch from torch import nn from transformers import XGLMConfig, XGLMForCausalLM def a__ ( lowerCAmelCase__ ) -> Any: UpperCAmelCase__ : Union[str, Any] = [ '''decod...
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'''simple docstring''' from typing import Dict, Iterable, 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, ...
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'''simple docstring''' from math import loga def a__ ( lowerCAmelCase__ ) -> int: if a < 0: raise ValueError('''Input value must be a positive integer''' ) elif isinstance(lowerCAmelCase__ , lowerCAmelCase__ ): raise TypeError('''Input value must b...
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'''simple docstring''' import math def a__ ( ) -> None: UpperCAmelCase__ : List[str] = input('''Enter message: ''' ) UpperCAmelCase__ : Any = int(input(F"""Enter key [2-{len(lowerCAmelCase__ ) - 1}]: """ ) ) UpperCAmelCase__ ...
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'''simple docstring''' from typing import TYPE_CHECKING from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available UpperCamelCase__ = { '''configuration_megatron_bert''': ['''MEGATRON_BERT_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''MegatronBertConfig'''], } try: i...
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'''simple docstring''' class lowerCamelCase_ : def __init__( self : str , _A : Union[str, Any] , _A : Optional[int] ): '''simple docstring''' UpperCAmelCase__ : Optional[Any] = name ...
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'''simple docstring''' UpperCamelCase__ = frozenset( [ '''prompt''', '''height''', '''width''', '''guidance_scale''', '''negative_prompt''', '''prompt_embeds''', '''negative_prompt_embeds''', '''cross_attention_kwargs''', ...
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'''simple docstring''' import inspect import re 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_docstrings.py UpperCamelCase__ = '''src/transformers'...
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'''simple docstring''' import inspect import unittest import numpy as np from transformers import BeitConfig from transformers.testing_utils import require_flax, require_vision, slow from transformers.utils import cached_property, is_flax_available, is_vision_available from ...test_configuration_comm...
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'''simple docstring''' from ..utils import DummyObject, requires_backends class lowerCamelCase_ ( metaclass=__a ): lowerCAmelCase__ = ['torch', 'torchsde'] def __init__( self : Tuple , *_A : Any , **_A : Optional[Any] ...
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'''simple docstring''' def a__ ( lowerCAmelCase__ = 10_00 ) -> int: UpperCAmelCase__ , UpperCAmelCase__ : Optional[int] = 1, 1 UpperCAmelCase__ : Dict = 2 while True: UpperCAmelCase__ : Optional[int] = 0 ...
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'''simple docstring''' from ...configuration_utils import PretrainedConfig from ...utils import logging UpperCamelCase__ = logging.get_logger(__name__) UpperCamelCase__ = {'''ctrl''': '''https://huggingface.co/ctrl/resolve/main/config.json'''} class lowerCamelCase_ ( ...
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'''simple docstring''' import argparse import os import transformers from .convert_slow_tokenizer import SLOW_TO_FAST_CONVERTERS from .utils import logging logging.set_verbosity_info() UpperCamelCase__ = logging.get_logger(__name__) UpperCamelCase__ = {name: getattr(transfo...
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'''simple docstring''' import json import os import subprocess import unittest from ast import literal_eval import pytest from parameterized import parameterized, parameterized_class from . import is_sagemaker_available if is_sagemaker_available(): from sagemaker import Session, TrainingJobAna...
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'''simple docstring''' from ...configuration_utils import PretrainedConfig from ...utils import logging UpperCamelCase__ = logging.get_logger(__name__) UpperCamelCase__ = {'''ctrl''': '''https://huggingface.co/ctrl/resolve/main/config.json'''} class lowerCamelCase_ ( ...
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'''simple docstring''' import math_equivalence # From: git+https://github.com/hendrycks/math.git import datasets UpperCamelCase__ = '''\ @article{hendrycksmath2021, title={Measuring Mathematical Problem Solving With the MATH Dataset}, author={Dan Hendrycks and Collin Burns and Saura...
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'''simple docstring''' import copy from ...configuration_utils import PretrainedConfig from ...utils import logging from ..auto import CONFIG_MAPPING UpperCamelCase__ = logging.get_logger(__name__) UpperCamelCase__ = { '''ut/deta''': '''https://huggingface.co/ut/deta/resolve/m...
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'''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_b...
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'''simple docstring''' import json import os import shutil import tempfile import unittest import numpy as np import pytest from transformers import BertTokenizer, BertTokenizerFast from transformers.models.bert.tokenization_bert import VOCAB_FILES_NAMES from transformers.testing_utils import requir...
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'''simple docstring''' import random from typing import Any def a__ ( lowerCAmelCase__ ) -> list[Any]: for _ in range(len(lowerCAmelCase__ ) ): UpperCAmelCase__ : int = random.randint(0 , len(lowerCAmelCase__ ) - 1 ) UpperCAmelCas...
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'''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, convert_to_rgb, get_resize_output_image_size, normalize, re...
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'''simple docstring''' import math def a__ ( lowerCAmelCase__ ) -> list[int]: UpperCAmelCase__ : List[Any] = [] UpperCAmelCase__ : Dict = 2 UpperCAmelCase__ : Optional[Any] = int(math.sqrt(lowerCAmelCase__ )...
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'''simple docstring''' import argparse import os import re UpperCamelCase__ = '''src/diffusers''' # Pattern that looks at the indentation in a line. UpperCamelCase__ = re.compile(R'''^(\s*)\S''') # Pattern that matches `"key":" and puts `key` in group 0. UpperCamelCase__ =...
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'''simple docstring''' import gc import random import unittest import numpy as np import torch from PIL import Image from transformers import CLIPTextConfig, CLIPTextModel, CLIPTokenizer from diffusers import AutoencoderKL, PNDMScheduler, StableDiffusionInpaintPipeline, UNetaDConditionModel from diff...
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'''simple docstring''' from math import factorial def a__ ( lowerCAmelCase__ , lowerCAmelCase__ , lowerCAmelCase__ ) -> float: if successes > trials: raise ValueError('''successes must be lower or equal to trials''' ) if trials < 0 or successes < 0: ...
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'''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 ...tes...
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'''simple docstring''' import os from pathlib import Path def a__ ( ) -> Union[str, Any]: from torch.utils.cpp_extension import load UpperCAmelCase__ : List[str] = Path(lowerCAmelCase__ ).resolve().parent.parent.parent / '''kernels''' / '''deformable...
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'''simple docstring''' import os import tempfile from functools import partial from unittest import TestCase from unittest.mock import patch import datasets import datasets.config from .utils import require_beam class lowerCamelCase_ ( datasets.BeamBasedBuilder ): ...
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'''simple docstring''' import importlib import torch import yaml from omegaconf import OmegaConf from taming.models.vqgan import VQModel def a__ ( lowerCAmelCase__ , lowerCAmelCase__=False ) -> List[str]: UpperCAmelCase__ : str = OmegaConf.load(lo...
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'''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-...
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'''simple docstring''' # Lint as: python3 import sys from collections.abc import Mapping from typing import TYPE_CHECKING import numpy as np import pyarrow as pa from .. import config from ..utils.py_utils import map_nested from .formatting import TensorFormatter if TYPE_CHECKING: import torc...
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'''simple docstring''' import argparse import torch from transformers import GPTaConfig, GPTaModel, load_tf_weights_in_gpta from transformers.utils import CONFIG_NAME, WEIGHTS_NAME, logging logging.set_verbosity_info() def a__ ( lowerCAmelCase__ , lowerCAmelCase__ , lowerC...
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'''simple docstring''' import argparse import collections import os import re 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_table.py UpperCamelCase__ = ...
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'''simple docstring''' from __future__ import annotations import copy import inspect import unittest import numpy as np from transformers import is_tf_available, is_vision_available from transformers.models.auto import get_values from transformers.testing_utils import require_tf, slow from transfor...
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'''simple docstring''' from typing import Dict, List, Optional, Union import numpy as np from transformers.utils import is_vision_available from transformers.utils.generic import TensorType from ...image_processing_utils import BaseImageProcessor, BatchFeature, get_size_dict from ...image_transforms i...
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'''simple docstring''' import webbrowser from sys import argv from urllib.parse import parse_qs, quote import requests from bsa import BeautifulSoup from fake_useragent import UserAgent if __name__ == "__main__": UpperCamelCase__ = '''%20'''.join(argv[1:]) if len(argv) > 1 else quote(str(in...
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'''simple docstring''' from ..utils import DummyObject, requires_backends class lowerCamelCase_ ( metaclass=__a ): lowerCAmelCase__ = ['torch', 'torchsde'] def __init__( self : Tuple , *_A : Any , **_A : Optional[Any] ...
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'''simple docstring''' from pathlib import Path import cva import numpy as np from matplotlib import pyplot as plt def a__ ( lowerCAmelCase__ , lowerCAmelCase__ , lowerCAmelCase__ , lowerCAmelCase__ , lowerCAmelCase__ ) -> np.ndarray: UpperCAmelCase__ ...
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'''simple docstring''' import pytest from datasets import inspect_metric, list_metrics, load_metric @pytest.fixture def a__ ( lowerCAmelCase__ ) -> int: monkeypatch.setattr('''datasets.utils.deprecation_utils._emitted_deprecation_warnings''' , set() ) @pyte...
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'''simple docstring''' from datetime import datetime as dt import os from github import Github UpperCamelCase__ = [ '''good first issue''', '''good second issue''', '''good difficult issue''', '''feature request''', '''new model''', '''wip''', ] def ...
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'''simple docstring''' from collections import OrderedDict from typing import Mapping from ...configuration_utils import PretrainedConfig from ...onnx import OnnxConfig UpperCamelCase__ = { '''albert-base-v1''': '''https://huggingface.co/albert-base-v1/resolve/main/config.json''', ''...
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'''simple docstring''' from typing import List, Optional, Tuple, Union import torch from ...utils import logging, randn_tensor from ..pipeline_utils import AudioPipelineOutput, DiffusionPipeline UpperCamelCase__ = logging.get_logger(__name__) # pylint: disable=invalid-name class ...
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'''simple docstring''' from __future__ import annotations UpperCamelCase__ = { '''A''': ['''B''', '''C''', '''E'''], '''B''': ['''A''', '''D''', '''E'''], '''C''': ['''A''', '''F''', '''G'''], '''D''': ['''B'''], '''E''': ['''A''', '''B''', '''D'''], '''F''': ['''C'''], ...
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'''simple docstring''' from math import factorial def a__ ( lowerCAmelCase__ , lowerCAmelCase__ , lowerCAmelCase__ ) -> float: if successes > trials: raise ValueError('''successes must be lower or equal to trials''' ) if trials < 0 or successes < 0: ...
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'''simple docstring''' import os from dataclasses import dataclass, field from io import BytesIO from typing import TYPE_CHECKING, Any, ClassVar, Dict, Optional, Union import numpy as np import pyarrow as pa from .. import config from ..download.streaming_download_manager import xopen, xsplitext from...
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'''simple docstring''' from typing import Dict, Iterable, 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, ...
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'''simple docstring''' import unittest from transformers import JukeboxTokenizer from transformers.testing_utils import require_torch class lowerCamelCase_ ( unittest.TestCase ): lowerCAmelCase__ = JukeboxTokenizer lowerCAmelCase__ = { 'artist': 'Zac B...
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'''simple docstring''' import math def a__ ( ) -> None: UpperCAmelCase__ : List[str] = input('''Enter message: ''' ) UpperCAmelCase__ : Any = int(input(F"""Enter key [2-{len(lowerCAmelCase__ ) - 1}]: """ ) ) UpperCAmelCase__ ...
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'''simple docstring''' from binascii import hexlify from hashlib import shaaaa from os import urandom # RFC 3526 - More Modular Exponential (MODP) Diffie-Hellman groups for # Internet Key Exchange (IKE) https://tools.ietf.org/html/rfc3526 UpperCamelCase__ = { # 1536-bit 5: { ...
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'''simple docstring''' class lowerCamelCase_ : def __init__( self : str , _A : Union[str, Any] , _A : Optional[int] ): '''simple docstring''' UpperCAmelCase__ : Optional[Any] = name ...
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'''simple docstring''' import numpy as np import torch from torch.utils.data import DataLoader from accelerate.utils.dataclasses import DistributedType class lowerCamelCase_ : def __init__( self : Dict , _A : str=2 , _A : Tuple=3 ,...
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'''simple docstring''' import inspect import re 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_docstrings.py UpperCamelCase__ = '''src/transformers'...
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'''simple docstring''' import numpy as np from nltk.translate import meteor_score import datasets from datasets.config import importlib_metadata, version UpperCamelCase__ = version.parse(importlib_metadata.version('''nltk''')) if NLTK_VERSION >= version.Version('''3.6.4'''): from nltk impo...
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'''simple docstring''' from ..utils import DummyObject, requires_backends class lowerCamelCase_ ( metaclass=__a ): lowerCAmelCase__ = ['torch', 'torchsde'] def __init__( self : Tuple , *_A : Any , **_A : Optional[Any] ...
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'''simple docstring''' from typing import TYPE_CHECKING from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available, is_vision_available UpperCamelCase__ = { '''configuration_mobilenet_v2''': [ '''MOBILENET_V2_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''M...
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'''simple docstring''' from ...configuration_utils import PretrainedConfig from ...utils import logging UpperCamelCase__ = logging.get_logger(__name__) UpperCamelCase__ = {'''ctrl''': '''https://huggingface.co/ctrl/resolve/main/config.json'''} class lowerCamelCase_ ( ...
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'''simple docstring''' from typing import TYPE_CHECKING from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available UpperCamelCase__ = { '''configuration_bigbird_pegasus''': [ '''BIGBIRD_PEGASUS_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''BigBirdPegasusCo...
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'''simple docstring''' import json import os import subprocess import unittest from ast import literal_eval import pytest from parameterized import parameterized, parameterized_class from . import is_sagemaker_available if is_sagemaker_available(): from sagemaker import Session, TrainingJobAna...
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'''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 UpperCamelCase__ = '''src/transformers''' U...
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'''simple docstring''' import math_equivalence # From: git+https://github.com/hendrycks/math.git import datasets UpperCamelCase__ = '''\ @article{hendrycksmath2021, title={Measuring Mathematical Problem Solving With the MATH Dataset}, author={Dan Hendrycks and Collin Burns and Saura...
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'''simple docstring''' from typing import Optional import torch import torch.utils.checkpoint from torch import Tensor, nn from torch.nn import BCEWithLogitsLoss, CrossEntropyLoss, MSELoss from ...activations import ACTaFN from ...file_utils import add_code_sample_docstrings, add_start_docstrings, add_...
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'''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_b...
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'''simple docstring''' import gc import unittest import numpy as np import torch from transformers import CLIPTextConfig, CLIPTextModel, CLIPTokenizer from diffusers import ( AutoencoderKL, DDIMScheduler, EulerAncestralDiscreteScheduler, LMSDiscreteScheduler, PNDMScheduler, ...
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'''simple docstring''' import random from typing import Any def a__ ( lowerCAmelCase__ ) -> list[Any]: for _ in range(len(lowerCAmelCase__ ) ): UpperCAmelCase__ : int = random.randint(0 , len(lowerCAmelCase__ ) - 1 ) UpperCAmelCas...
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'''simple docstring''' import argparse import os import gluonnlp as nlp import mxnet as mx import numpy as np import torch from gluonnlp.base import get_home_dir from gluonnlp.model.bert import BERTEncoder from gluonnlp.model.utils import _load_vocab from gluonnlp.vocab import Vocab from packaging im...
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'''simple docstring''' import math def a__ ( lowerCAmelCase__ ) -> list[int]: UpperCAmelCase__ : List[Any] = [] UpperCAmelCase__ : Dict = 2 UpperCAmelCase__ : Optional[Any] = int(math.sqrt(lowerCAmelCase__ )...
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'''simple docstring''' # Imports import numpy as np class lowerCamelCase_ : def __init__( self : Dict , _A : int=None , _A : Any=None , _A : List[str]=None , _A : Optional[int]=None , _A : Optio...
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'''simple docstring''' import gc import random import unittest import numpy as np import torch from PIL import Image from transformers import CLIPTextConfig, CLIPTextModel, CLIPTokenizer from diffusers import AutoencoderKL, PNDMScheduler, StableDiffusionInpaintPipeline, UNetaDConditionModel from diff...
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'''simple docstring''' import tempfile import unittest from make_student import create_student_by_copying_alternating_layers from transformers import AutoConfig from transformers.file_utils import cached_property from transformers.testing_utils import require_torch UpperCamelCase__ = '''ss...
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'''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 ...tes...
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'''simple docstring''' from __future__ import annotations UpperCamelCase__ = [-1_0, -5, 0, 5, 5.1, 1_1, 1_3, 2_1, 3, 4, -2_1, -1_0, -5, -1, 0] UpperCamelCase__ = [-5, 0, 5, 5.1, 1_1, 1_3, 2_1, -1, 4, -1, -1_0, -5, -1, 0, -1] def a__ ( lowerCAmelCase__ ) -> list...
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'''simple docstring''' import os import tempfile from functools import partial from unittest import TestCase from unittest.mock import patch import datasets import datasets.config from .utils import require_beam class lowerCamelCase_ ( datasets.BeamBasedBuilder ): ...
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'''simple docstring''' from __future__ import annotations import time UpperCamelCase__ = list[tuple[int, int]] UpperCamelCase__ = [ [0, 0, 0, 0, 0, 0, 0], [0, 1, 0, 0, 0, 0, 0], # 0 are free path whereas 1's are obstacles [0, 0, 0, 0, 0, 0, 0], [0, 0, 1, 0, 0, 0, 0...
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'''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-...
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'''simple docstring''' def a__ ( lowerCAmelCase__ ) -> list: if n_term == "": return [] UpperCAmelCase__ : list = [] for temp in range(int(lowerCAmelCase__ ) ): series.append(F"""1/{temp + 1}""" if series else '''1''' ) return series...
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'''simple docstring''' import argparse import torch from transformers import GPTaConfig, GPTaModel, load_tf_weights_in_gpta from transformers.utils import CONFIG_NAME, WEIGHTS_NAME, logging logging.set_verbosity_info() def a__ ( lowerCAmelCase__ , lowerCAmelCase__ , lowerC...
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'''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 ...tes...
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'''simple docstring''' from __future__ import annotations import copy import inspect import unittest import numpy as np from transformers import is_tf_available, is_vision_available from transformers.models.auto import get_values from transformers.testing_utils import require_tf, slow from transfor...
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'''simple docstring''' import argparse import json import pickle from pathlib import Path import requests import torch from huggingface_hub import hf_hub_download from PIL import Image from transformers import MaskFormerConfig, MaskFormerForInstanceSegmentation, MaskFormerImageProcessor, SwinConfig ...
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'''simple docstring''' import webbrowser from sys import argv from urllib.parse import parse_qs, quote import requests from bsa import BeautifulSoup from fake_useragent import UserAgent if __name__ == "__main__": UpperCamelCase__ = '''%20'''.join(argv[1:]) if len(argv) > 1 else quote(str(in...
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'''simple docstring''' from scipy.stats import spearmanr import datasets UpperCamelCase__ = ''' The Spearman rank-order correlation coefficient is a measure of the relationship between two datasets. Like other correlation coefficients, this one varies between -1 and +1 with 0 implying no correla...
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'''simple docstring''' from pathlib import Path import cva import numpy as np from matplotlib import pyplot as plt def a__ ( lowerCAmelCase__ , lowerCAmelCase__ , lowerCAmelCase__ , lowerCAmelCase__ , lowerCAmelCase__ ) -> np.ndarray: UpperCAmelCase__ ...
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'''simple docstring''' import unittest from transformers import is_torch_available from transformers.testing_utils import require_torch, slow, torch_device from ...generation.test_utils import GenerationTesterMixin from ...test_configuration_common import ConfigTester from ...test_modeling_common import...
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'''simple docstring''' from datetime import datetime as dt import os from github import Github UpperCamelCase__ = [ '''good first issue''', '''good second issue''', '''good difficult issue''', '''feature request''', '''new model''', '''wip''', ] def ...
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'''simple docstring''' import unittest from transformers import EsmConfig, is_torch_available from transformers.testing_utils import TestCasePlus, require_torch, slow, torch_device from ...test_configuration_common import ConfigTester from ...test_modeling_common import ModelTesterMixin, ids_tensor, rand...
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'''simple docstring''' from typing import List, Optional, Tuple, Union import torch from ...utils import logging, randn_tensor from ..pipeline_utils import AudioPipelineOutput, DiffusionPipeline UpperCamelCase__ = logging.get_logger(__name__) # pylint: disable=invalid-name class ...
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'''simple docstring''' from __future__ import annotations import unittest import numpy as np from transformers import BlipTextConfig from transformers.testing_utils import require_tf, slow from transformers.utils import is_tf_available from ...test_configuration_common import ConfigTester from ......
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'''simple docstring''' from math import factorial def a__ ( lowerCAmelCase__ , lowerCAmelCase__ , lowerCAmelCase__ ) -> float: if successes > trials: raise ValueError('''successes must be lower or equal to trials''' ) if trials < 0 or successes < 0: ...
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'''simple docstring''' import json import sys def a__ ( lowerCAmelCase__ , lowerCAmelCase__ ) -> List[str]: with open(lowerCAmelCase__ , encoding='''utf-8''' ) as f: UpperCAmelCase__ : Union[str, Any] = json.load(lowerCAmelCase__ ) ...
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'''simple docstring''' from typing import Dict, Iterable, 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, ...
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'''simple docstring''' from typing import TYPE_CHECKING from ...utils import ( OptionalDependencyNotAvailable, _LazyModule, is_sentencepiece_available, is_tokenizers_available, is_torch_available, ) UpperCamelCase__ = {'''configuration_plbart''': ['''PLBART_PRETRAINED_C...
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'''simple docstring''' import math def a__ ( ) -> None: UpperCAmelCase__ : List[str] = input('''Enter message: ''' ) UpperCAmelCase__ : Any = int(input(F"""Enter key [2-{len(lowerCAmelCase__ ) - 1}]: """ ) ) UpperCAmelCase__ ...
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'''simple docstring''' from dataclasses import dataclass from typing import Optional, Tuple, Union import flax import jax.numpy as jnp from jax import random from ..configuration_utils import ConfigMixin, register_to_config from ..utils import BaseOutput from .scheduling_utils_flax import FlaxSchedule...
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'''simple docstring''' class lowerCamelCase_ : def __init__( self : str , _A : Union[str, Any] , _A : Optional[int] ): '''simple docstring''' UpperCAmelCase__ : Optional[Any] = name ...
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'''simple docstring''' import json import os import shutil import warnings from argparse import ArgumentParser, Namespace from pathlib import Path from typing import List from ..utils import logging from . import BaseTransformersCLICommand try: from cookiecutter.main import cookiecutter Up...
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'''simple docstring''' import inspect import re 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_docstrings.py UpperCamelCase__ = '''src/transformers'...
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'''simple docstring''' import os from datetime import datetime as dt from github import Github UpperCamelCase__ = [ '''good first issue''', '''good second issue''', '''good difficult issue''', '''enhancement''', '''new pipeline/model''', '''new scheduler''', '...
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'''simple docstring''' from ..utils import DummyObject, requires_backends class lowerCamelCase_ ( metaclass=__a ): lowerCAmelCase__ = ['torch', 'torchsde'] def __init__( self : Tuple , *_A : Any , **_A : Optional[Any] ...
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'''simple docstring''' import argparse import torch from transformers import BlenderbotConfig, BlenderbotForConditionalGeneration from transformers.utils import logging logging.set_verbosity_info() UpperCamelCase__ = logging.get_logger(__name__) UpperCamelCase__ = [ ['''att...
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'''simple docstring''' from ...configuration_utils import PretrainedConfig from ...utils import logging UpperCamelCase__ = logging.get_logger(__name__) UpperCamelCase__ = {'''ctrl''': '''https://huggingface.co/ctrl/resolve/main/config.json'''} class lowerCamelCase_ ( ...
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'''simple docstring''' import argparse import re import torch from CLAP import create_model from transformers import AutoFeatureExtractor, ClapConfig, ClapModel UpperCamelCase__ = { '''text_branch''': '''text_model''', '''audio_branch''': '''audio_model.audio_encoder''', '''a...
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'''simple docstring''' import json import os import subprocess import unittest from ast import literal_eval import pytest from parameterized import parameterized, parameterized_class from . import is_sagemaker_available if is_sagemaker_available(): from sagemaker import Session, TrainingJobAna...
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'''simple docstring''' from random import randint, random def a__ ( lowerCAmelCase__ , lowerCAmelCase__ , lowerCAmelCase__ , lowerCAmelCase__ = False , lowerCAmelCase__ = False , lowerCAmelCase__ = 5 , ) -> list: UpperCAmelCase__ : List[str...
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'''simple docstring''' import math_equivalence # From: git+https://github.com/hendrycks/math.git import datasets UpperCamelCase__ = '''\ @article{hendrycksmath2021, title={Measuring Mathematical Problem Solving With the MATH Dataset}, author={Dan Hendrycks and Collin Burns and Saura...
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'''simple docstring''' import string def a__ ( lowerCAmelCase__ ) -> None: for key in range(len(string.ascii_uppercase ) ): UpperCAmelCase__ : Tuple = '''''' for symbol in message: if symbol in string.ascii_uppercase: ...
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'''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_b...
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'''simple docstring''' import torch from diffusers import DDPMScheduler from .test_schedulers import SchedulerCommonTest class lowerCamelCase_ ( __a ): lowerCAmelCase__ = (DDPMScheduler,) def lowercase_ ( self : Optional[int] , **_A ...
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'''simple docstring''' import random from typing import Any def a__ ( lowerCAmelCase__ ) -> list[Any]: for _ in range(len(lowerCAmelCase__ ) ): UpperCAmelCase__ : int = random.randint(0 , len(lowerCAmelCase__ ) - 1 ) UpperCAmelCas...
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'''simple docstring''' def a__ ( lowerCAmelCase__ , lowerCAmelCase__ , lowerCAmelCase__ ) -> float: return round(float(moles / volume ) * nfactor ) def a__ ( lowerCAmelCase__ , lowerCAmelCase__ , lowerCAmelCase__ ) -> float: return ...
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'''simple docstring''' import math def a__ ( lowerCAmelCase__ ) -> list[int]: UpperCAmelCase__ : List[Any] = [] UpperCAmelCase__ : Dict = 2 UpperCAmelCase__ : Optional[Any] = int(math.sqrt(lowerCAmelCase__ )...
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'''simple docstring''' UpperCamelCase__ = 9.80_665 def a__ ( lowerCAmelCase__ , lowerCAmelCase__ , lowerCAmelCase__ = g ) -> float: if fluid_density <= 0: raise ValueError('''Impossible fluid density''' ) if volume < 0: raise ValueEr...
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'''simple docstring''' import gc import random import unittest import numpy as np import torch from PIL import Image from transformers import CLIPTextConfig, CLIPTextModel, CLIPTokenizer from diffusers import AutoencoderKL, PNDMScheduler, StableDiffusionInpaintPipeline, UNetaDConditionModel from diff...
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'''simple docstring''' from typing import List, Optional, Union import numpy as np import PIL.Image from ...image_processing_utils import BaseImageProcessor, BatchFeature from ...image_transforms import rescale, resize, to_channel_dimension_format from ...image_utils import ( ChannelDimension, ...
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'''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 ...tes...
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'''simple docstring''' from collections import defaultdict def a__ ( lowerCAmelCase__ , lowerCAmelCase__ ) -> bool: UpperCAmelCase__ : Optional[Any] = first_str.lower().strip() UpperCAmelCase__ : Optional[Any] = second_str.lower...
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'''simple docstring''' import os import tempfile from functools import partial from unittest import TestCase from unittest.mock import patch import datasets import datasets.config from .utils import require_beam class lowerCamelCase_ ( datasets.BeamBasedBuilder ): ...
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'''simple docstring''' import warnings from ...utils import logging from .image_processing_segformer import SegformerImageProcessor UpperCamelCase__ = logging.get_logger(__name__) class lowerCamelCase_ ( __a ): def __init__( self : int , *_...
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'''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-...
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'''simple docstring''' from typing import List, Optional, Union import numpy as np import torch import torchaudio.compliance.kaldi as ta_kaldi from ...feature_extraction_sequence_utils import SequenceFeatureExtractor from ...feature_extraction_utils import BatchFeature from ...utils import PaddingStrat...
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'''simple docstring''' import argparse import torch from transformers import GPTaConfig, GPTaModel, load_tf_weights_in_gpta from transformers.utils import CONFIG_NAME, WEIGHTS_NAME, logging logging.set_verbosity_info() def a__ ( lowerCAmelCase__ , lowerCAmelCase__ , lowerC...
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'''simple docstring''' import pytest import datasets.config from datasets.utils.info_utils import is_small_dataset @pytest.mark.parametrize('''dataset_size''' , [None, 4_00 * 2**20, 6_00 * 2**20] ) @pytest.mark.parametrize('''input_in_memory_max_size''' , ['''default''', 0, 1_00 * 2**2...
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'''simple docstring''' from __future__ import annotations import copy import inspect import unittest import numpy as np from transformers import is_tf_available, is_vision_available from transformers.models.auto import get_values from transformers.testing_utils import require_tf, slow from transfor...
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'''simple docstring''' import inspect import unittest from transformers import YolosConfig from transformers.testing_utils import require_torch, require_vision, slow, torch_device from transformers.utils import cached_property, is_torch_available, is_vision_available from ...test_configuration_common im...
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'''simple docstring''' import webbrowser from sys import argv from urllib.parse import parse_qs, quote import requests from bsa import BeautifulSoup from fake_useragent import UserAgent if __name__ == "__main__": UpperCamelCase__ = '''%20'''.join(argv[1:]) if len(argv) > 1 else quote(str(in...
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'''simple docstring''' def a__ ( lowerCAmelCase__ ) -> list: if len(lowerCAmelCase__ ) <= 1: return [tuple(lowerCAmelCase__ )] UpperCAmelCase__ : int = [] def generate(lowerCAmelCase__ , lowerCAmelCase__ ): UpperCAmelCase__ ...
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'''simple docstring''' from pathlib import Path import cva import numpy as np from matplotlib import pyplot as plt def a__ ( lowerCAmelCase__ , lowerCAmelCase__ , lowerCAmelCase__ , lowerCAmelCase__ , lowerCAmelCase__ ) -> np.ndarray: UpperCAmelCase__ ...
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'''simple docstring''' import multiprocessing from typing import TYPE_CHECKING, Optional, Union from .. import Dataset, Features, config from ..formatting import query_table from ..packaged_modules.sql.sql import Sql from ..utils import logging from .abc import AbstractDatasetInputStream if TYPE_CHE...
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'''simple docstring''' from datetime import datetime as dt import os from github import Github UpperCamelCase__ = [ '''good first issue''', '''good second issue''', '''good difficult issue''', '''feature request''', '''new model''', '''wip''', ] def ...
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'''simple docstring''' import math_equivalence # From: git+https://github.com/hendrycks/math.git import datasets UpperCamelCase__ = '''\ @article{hendrycksmath2021, title={Measuring Mathematical Problem Solving With the MATH Dataset}, author={Dan Hendrycks and Collin Burns and Saura...
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'''simple docstring''' from typing import List, Optional, Tuple, Union import torch from ...utils import logging, randn_tensor from ..pipeline_utils import AudioPipelineOutput, DiffusionPipeline UpperCamelCase__ = logging.get_logger(__name__) # pylint: disable=invalid-name class ...
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'''simple docstring''' import warnings from ...processing_utils import ProcessorMixin from ...tokenization_utils_base import BatchEncoding class lowerCamelCase_ ( __a ): lowerCAmelCase__ = ['image_processor', 'tokenizer'] lowerCAmelCase__ = 'ViTImageProcessor' ...
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'''simple docstring''' from math import factorial def a__ ( lowerCAmelCase__ , lowerCAmelCase__ , lowerCAmelCase__ ) -> float: if successes > trials: raise ValueError('''successes must be lower or equal to trials''' ) if trials < 0 or successes < 0: ...
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'''simple docstring''' import warnings from diffusers import StableDiffusionInpaintPipeline as StableDiffusionInpaintPipeline # noqa F401 warnings.warn( '''The `inpainting.py` script is outdated. Please use directly `from diffusers import''' ''' StableDiffusionInpaintPipeline` instead.''' )
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'''simple docstring''' from typing import Dict, Iterable, 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, ...
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'''simple docstring''' from .imports import is_tqdm_available if is_tqdm_available(): from tqdm.auto import tqdm as _tqdm from ..state import PartialState def a__ ( lowerCAmelCase__ = True , *lowerCAmelCase__ , **lowerCAmelCase__ ) -> int: if not is_tqdm_av...
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'''simple docstring''' import math def a__ ( ) -> None: UpperCAmelCase__ : List[str] = input('''Enter message: ''' ) UpperCAmelCase__ : Any = int(input(F"""Enter key [2-{len(lowerCAmelCase__ ) - 1}]: """ ) ) UpperCAmelCase__ ...
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'''simple docstring''' from typing import TYPE_CHECKING from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available UpperCamelCase__ = {'''configuration_sew''': ['''SEW_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''SEWConfig''']} try: if not is_torch_available(): raise...
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'''simple docstring''' class lowerCamelCase_ : def __init__( self : str , _A : Union[str, Any] , _A : Optional[int] ): '''simple docstring''' UpperCAmelCase__ : Optional[Any] = name ...
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'''simple docstring''' import argparse import json import os import torch from torch import nn from transformers import NllbMoeConfig, NllbMoeModel from transformers.modeling_utils import dtype_byte_size from transformers.utils import WEIGHTS_INDEX_NAME, WEIGHTS_NAME def a__ ( lowerC...
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'''simple docstring''' import inspect import re 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_docstrings.py UpperCamelCase__ = '''src/transformers'...
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'''simple docstring''' from typing import Dict, Iterable, Optional, Union import numpy as np from ...image_processing_utils import BaseImageProcessor, BatchFeature, get_size_dict from ...image_transforms import normalize, rescale, resize, to_channel_dimension_format, to_pil_image from ...image_utils impo...
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'''simple docstring''' from ..utils import DummyObject, requires_backends class lowerCamelCase_ ( metaclass=__a ): lowerCAmelCase__ = ['torch', 'torchsde'] def __init__( self : Tuple , *_A : Any , **_A : Optional[Any] ...
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'''simple docstring''' import os import unittest from transformers import LayoutLMTokenizer, LayoutLMTokenizerFast from transformers.models.layoutlm.tokenization_layoutlm import VOCAB_FILES_NAMES from transformers.testing_utils import require_tokenizers from ...test_tokenization_common import TokenizerT...
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'''simple docstring''' from ...configuration_utils import PretrainedConfig from ...utils import logging UpperCamelCase__ = logging.get_logger(__name__) UpperCamelCase__ = {'''ctrl''': '''https://huggingface.co/ctrl/resolve/main/config.json'''} class lowerCamelCase_ ( ...
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'''simple docstring''' from torch import nn def a__ ( lowerCAmelCase__ ) -> List[Any]: if act_fn in ["swish", "silu"]: return nn.SiLU() elif act_fn == "mish": return nn.Mish() elif act_fn == "gelu": return nn.GELU() else: raise...
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'''simple docstring''' import json import os import subprocess import unittest from ast import literal_eval import pytest from parameterized import parameterized, parameterized_class from . import is_sagemaker_available if is_sagemaker_available(): from sagemaker import Session, TrainingJobAna...
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'''simple docstring''' import gc import random import unittest import numpy as np import torch from PIL import Image from transformers import CLIPTextConfig, CLIPTextModel, CLIPTokenizer from diffusers import AutoencoderKL, PNDMScheduler, StableDiffusionInpaintPipeline, UNetaDConditionModel from diff...
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'''simple docstring''' import math_equivalence # From: git+https://github.com/hendrycks/math.git import datasets UpperCamelCase__ = '''\ @article{hendrycksmath2021, title={Measuring Mathematical Problem Solving With the MATH Dataset}, author={Dan Hendrycks and Collin Burns and Saura...
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'''simple docstring''' from datetime import datetime import requests def a__ ( lowerCAmelCase__ ) -> bytes: UpperCAmelCase__ : Any = '''https://downloadgram.net/wp-json/wppress/video-downloader/video?url=''' UpperCAmelCase__ : str = ...
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'''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_b...
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'''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-...
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'''simple docstring''' import random from typing import Any def a__ ( lowerCAmelCase__ ) -> list[Any]: for _ in range(len(lowerCAmelCase__ ) ): UpperCAmelCase__ : int = random.randint(0 , len(lowerCAmelCase__ ) - 1 ) UpperCAmelCas...
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'''simple docstring''' import inspect import re 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_docstrings.py UpperCamelCase__ = '''src/transformers'...
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'''simple docstring''' import math def a__ ( lowerCAmelCase__ ) -> list[int]: UpperCAmelCase__ : List[Any] = [] UpperCAmelCase__ : Dict = 2 UpperCAmelCase__ : Optional[Any] = int(math.sqrt(lowerCAmelCase__ )...
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'''simple docstring''' import unittest import numpy as np import torch from diffusers import ScoreSdeVePipeline, ScoreSdeVeScheduler, UNetaDModel from diffusers.utils.testing_utils import enable_full_determinism, require_torch, slow, torch_device enable_full_determinism() class lowerCa...
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'''simple docstring''' import gc import random import unittest import numpy as np import torch from PIL import Image from transformers import CLIPTextConfig, CLIPTextModel, CLIPTokenizer from diffusers import AutoencoderKL, PNDMScheduler, StableDiffusionInpaintPipeline, UNetaDConditionModel from diff...
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'''simple docstring''' def a__ ( lowerCAmelCase__ = 10_00 ) -> int: return sum(2 * a * ((a - 1) // 2) for a in range(3 , n + 1 ) ) if __name__ == "__main__": print(solution())
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'''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 ...tes...
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'''simple docstring''' # coding=utf-8 # Copyright 2020 The HuggingFace Inc. team. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-...
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'''simple docstring''' import os import tempfile from functools import partial from unittest import TestCase from unittest.mock import patch import datasets import datasets.config from .utils import require_beam class lowerCamelCase_ ( datasets.BeamBasedBuilder ): ...
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'''simple docstring''' from __future__ import annotations def a__ ( lowerCAmelCase__ , lowerCAmelCase__ ) -> tuple[int, int]: if b == 0: return (1, 0) ((UpperCAmelCase__) , (UpperCAmelCase__)) : List[str] = extended_euclid(lowerCAmelCase...
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'''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-...
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'''simple docstring''' import argparse import torch from transformers import LxmertConfig, LxmertForPreTraining, load_tf_weights_in_lxmert from transformers.utils import logging logging.set_verbosity_info() def a__ ( lowerCAmelCase__ , lowerCAmelCase__ , lowerCAmelCase__ ...
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'''simple docstring''' import argparse import torch from transformers import GPTaConfig, GPTaModel, load_tf_weights_in_gpta from transformers.utils import CONFIG_NAME, WEIGHTS_NAME, logging logging.set_verbosity_info() def a__ ( lowerCAmelCase__ , lowerCAmelCase__ , lowerC...
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