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'''simple docstring''' import bza import gzip import lzma import os import shutil import struct import tarfile import warnings import zipfile from abc import ABC, abstractmethod from pathlib import Path from typing import Dict, List, Optional, Type, Union from .. import config...
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'''simple docstring''' import logging from pathlib import Path import numpy as np import pytorch_lightning as pl import torch from pytorch_lightning.callbacks import EarlyStopping, ModelCheckpoint from pytorch_lightning.utilities import rank_zero_only from utils_rag import save_json def lowerCamelCase ( l...
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'''simple docstring''' import os import sys import unittest lowercase : Dict = os.path.abspath(os.path.dirname(os.path.dirname(os.path.dirname(__file__)))) sys.path.append(os.path.join(git_repo_path, "utils")) import check_dummies # noqa: E402 from check_dummies import create_dummy_files, ...
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'''simple docstring''' def lowerCamelCase ( ): """simple docstring""" return 1 def lowerCamelCase ( lowerCAmelCase : int ): """simple docstring""" return 0 if x < 0 else two_pence(x - 2 ) + one_pence() def lowerCamelCase ( lowerCAmelCase : int ): """s...
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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 lowerCamelCase_ ( UpperCAmelCase_ ): '''simpl...
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'''simple docstring''' from ..utils import DummyObject, requires_backends class _lowerCamelCase ( metaclass=lowercase__ ): '''simple docstring''' A_ : Optional[Any] = ["""flax""", """transformers"""] def __init__( self : Union[str, Any] , *_A : ...
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"""simple docstring""" import json import pathlib import unittest import numpy as np from transformers.testing_utils import require_torch, require_vision, slow from transformers.utils import is_torch_available, is_vision_available from ...test_image_processing_common import ImageProcessingSavingTestMixin, prepar...
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'''simple docstring''' from typing import List, Union from ..utils import ( add_end_docstrings, is_tf_available, is_torch_available, is_vision_available, logging, requires_backends, ) from .base import PIPELINE_INIT_ARGS, Pipeline if is_vision_available(): from PIL import Image ...
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"""simple docstring""" import numpy as np def lowercase ( lowerCAmelCase__ : np.ndarray , lowerCAmelCase__ : float ) -> np.ndarray: return np.where(vector > 0 , lowerCAmelCase__ , (alpha * (np.exp(lowerCAmelCase__ ) - 1)) ) if __name__ == "...
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'''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, AutoMode...
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"""simple docstring""" import re import time from typing import Optional import IPython.display as disp from ..trainer_callback import TrainerCallback from ..trainer_utils import IntervalStrategy, has_length def UpperCAmelCase__ ( SCREAMING_SNAKE_CASE : Any ): '''simple ...
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'''simple docstring''' import torch from diffusers import DDPMScheduler from .test_schedulers import SchedulerCommonTest class _lowerCamelCase ( lowercase__ ): '''simple docstring''' A_ : Dict = (DDPMScheduler,) def __lowerCAmelCase ( self : Any ...
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'''simple docstring''' from collections import OrderedDict from ...utils import logging from .auto_factory import _BaseAutoModelClass, _LazyAutoMapping, auto_class_update from .configuration_auto import CONFIG_MAPPING_NAMES lowerCamelCase : Any = logging.get_logger(__name__) lowerCamelCase : D...
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'''simple docstring''' import random import unittest import torch from diffusers import IFInpaintingPipeline from diffusers.utils import floats_tensor from diffusers.utils.import_utils import is_xformers_available from diffusers.utils.testing_utils import skip_mps, torch_device from ..pipeline_params import ( ...
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# 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.pipeline_flax_controlnet import FlaxStableDiffusionControlNetPipeline # noqa: F401 ...
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'''simple docstring''' import unittest from transformers import DebertaConfig, is_torch_available from transformers.testing_utils import require_sentencepiece, require_tokenizers, require_torch, slow, torch_device from ...test_configuration_common import ConfigTester from ...test_modeling_common import ModelTeste...
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from __future__ import annotations import unittest from transformers import BlenderbotSmallConfig, BlenderbotSmallTokenizer, is_tf_available from transformers.testing_utils import require_tf, require_tokenizers, slow from transformers.utils import cached_property from ...test_configuration_common import ConfigTe...
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'''simple docstring''' class _lowerCamelCase : # Public class to implement a graph '''simple docstring''' def __init__( self : List[Any] , _A : int , _A : int , _A : list[list[bool]] ) -> None: __magic_name__ : Tuple = row __...
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import warnings from collections import OrderedDict from typing import Any, Mapping, Optional from ... import PreTrainedTokenizer from ...configuration_utils import PretrainedConfig from ...onnx import OnnxConfig, OnnxConfigWithPast, OnnxSeqaSeqConfigWithPast from ...onnx.utils import compute_effective_axis_dime...
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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, is_vision_available, ) lowerCAmelCase :Tuple = {'''processing_layoutxlm''': ['''L...
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import unittest from parameterized import parameterized from transformers import OpenLlamaConfig, is_torch_available, set_seed from transformers.testing_utils import require_torch, torch_device from ...generation.test_utils import GenerationTesterMixin from ...test_configuration_common import Confi...
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'''simple docstring''' from __future__ import annotations from math import ceil, floor, sqrt def lowerCamelCase ( lowerCAmelCase : int = 200_0000 ): """simple docstring""" __magic_name__ : list[int] = [0] __magic_name__ : int for idx in range(1 , ceil(sqrt...
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from typing import TYPE_CHECKING from ...utils import ( OptionalDependencyNotAvailable, _LazyModule, is_tokenizers_available, is_torch_available, is_vision_available, ) __lowerCamelCase : Dict = { """configuration_perceiver""": ["""PERCEIVER_PRETRAINED_CONFIG_ARCHIVE_MAP...
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'''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, ) lowerCAmelCase :str = {'''configuration...
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'''simple docstring''' def lowercase__ ( __lowercase : int , __lowercase : int ) -> int: """simple docstring""" while a != 0: __UpperCamelCase , __UpperCamelCase = b % a, a return b def lowercase__ ( __lowerca...
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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, get_resize_output_image_size, normalize, rescale, resize, to_channel...
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"""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/LICENS...
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'''simple docstring''' from __future__ import annotations from math import pi # Define the Reduced Planck Constant ℏ (H bar), speed of light C, value of # Pi and the function lowerCAmelCase :Tuple = 1.0_5_4_5_7_1_8_1_7E-3_4 # unit of ℏ : J * s lowerCAmelCase :Union[str, Any] = 3E8 # unit ...
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'''simple docstring''' import argparse import os import torch from transformers import FlavaConfig, FlavaForPreTraining from transformers.models.flava.convert_dalle_to_flava_codebook import convert_dalle_checkpoint def __snake_case ( UpperCAmelCase_ : Dict ): # encoder....
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'''simple docstring''' import os from itertools import chain from random import randrange, shuffle import pytest from .sola import PokerHand lowerCAmelCase :Tuple = ( '''4S 3H 2C 7S 5H''', '''9D 8H 2C 6S 7H''', '''2D 6D 9D TH 7D''', '''TC 8C 2S JH 6C''', '''JH 8S TH AH QH''', '...
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'''simple docstring''' import os import unittest from transformers import BatchEncoding from transformers.models.bert.tokenization_bert import ( BasicTokenizer, WordpieceTokenizer, _is_control, _is_punctuation, _is_whitespace, ) from transformers.models.prophetnet.tokenization_prophetnet impo...
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'''simple docstring''' from typing import TYPE_CHECKING from ...utils import ( OptionalDependencyNotAvailable, _LazyModule, is_flax_available, is_tf_available, is_torch_available, ) lowerCAmelCase :Union[str, Any] = { '''configuration_vision_encoder_decoder''': ['''VisionEncode...
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"""simple docstring""" def _lowerCamelCase ( _UpperCamelCase , _UpperCamelCase , _UpperCamelCase ): '''simple docstring''' def update_area_of_max_square(_UpperCamelCase , _UpperCamelCase ) -> int: # BASE CASE if row >= rows or col >= cols: return 0 __lower...
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'''simple docstring''' from collections import UserDict from typing import List, Union from ..utils import ( add_end_docstrings, is_tf_available, is_torch_available, is_vision_available, logging, requires_backends, ) from .base import PIPELINE_INIT_ARGS, Pipeline if is_vision_available():...
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'''simple docstring''' lowercase_ = [ """Audio""", """Array2D""", """Array3D""", """Array4D""", """Array5D""", """ClassLabel""", """Features""", """Sequence""", """Value""", """Image""", """Translation""", """TranslationVariableLanguages""", ] from .audio impor...
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'''simple docstring''' import json import os import re import shutil import tempfile import unittest from typing import Tuple from transformers import AddedToken, BatchEncoding, ByTaTokenizer from transformers.utils import cached_property, is_tf_available, is_torch_available from ...test_tokenization_common impor...
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from typing import Callable, List, Optional, Tuple, Union import torch from transformers import CLIPTextModel, CLIPTokenizer from ...configuration_utils import ConfigMixin, register_to_config from ...models import ModelMixin, TransformeraDModel, VQModel from ...schedulers import VQDiffusionScheduler from .....
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'''simple docstring''' import unittest from transformers import is_torch_available from transformers.testing_utils import require_torch if is_torch_available(): import torch from transformers.generation import DisjunctiveConstraint @require_torch class _lowerCamelCase ( unittest.TestCas...
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"""simple docstring""" from math import log from scipy.constants import Boltzmann, physical_constants snake_case__ : Optional[Any] = 300 # TEMPERATURE (unit = K) def _snake_case ( _snake_case : float , _snake_case : float , _snake_case : float , ): if ...
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'''simple docstring''' import re import tempfile from pathlib import Path import pytest import yaml from datasets.utils.readme import ReadMe # @pytest.fixture # def example_yaml_structure(): lowerCAmelCase :List[str] = yaml.safe_load( '''\ name: "" allow_empty: false allow_empty_text: true subse...
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"""simple docstring""" from itertools import product def __a ( __lowerCamelCase, __lowerCamelCase ): UpperCAmelCase_ : Dict = sides_number UpperCAmelCase_ : Optional[Any] = max_face_number * dice_number UpperCAmelCase_ : Optional[Any] = ...
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'''simple docstring''' from __future__ import annotations import os import tempfile import unittest from transformers import ConvBertConfig, is_tf_available from transformers.testing_utils import require_tf, slow from ...test_configuration_common import ConfigTester from ...test_modeling_tf_common import TFModel...
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# 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 # # Unless required by a...
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'''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 requ...
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'''simple docstring''' from abc import ABC, abstractmethod from typing import Optional, Union from .. import Dataset, DatasetDict, Features, IterableDataset, IterableDatasetDict, NamedSplit from ..utils.typing import NestedDataStructureLike, PathLike class __SCREAMING_SNAKE_CASE (lowerCamelCase_ ...
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'''simple docstring''' import logging from pathlib import Path import numpy as np import pytorch_lightning as pl import torch from pytorch_lightning.callbacks import EarlyStopping, ModelCheckpoint from pytorch_lightning.utilities import rank_zero_only from utils_rag import save_json def lowerCamelCase ( l...
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"""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 ...
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'''simple docstring''' def lowerCamelCase ( ): """simple docstring""" return 1 def lowerCamelCase ( lowerCAmelCase : int ): """simple docstring""" return 0 if x < 0 else two_pence(x - 2 ) + one_pence() def lowerCamelCase ( lowerCAmelCase : int ): """s...
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def lowerCAmelCase_ ( __A ) -> bool: '''simple docstring''' return credit_card_number.startswith(("34", "35", "37", "4", "5", "6") ) def lowerCAmelCase_ ( __A ) -> bool: '''simple docstring''' UpperCAm...
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'''simple docstring''' from ..utils import DummyObject, requires_backends class _lowerCamelCase ( metaclass=lowercase__ ): '''simple docstring''' A_ : Optional[Any] = ["""flax""", """transformers"""] def __init__( self : Union[str, Any] , *_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_class from . import is_sagemaker_available if is_sagemaker_available(): from sagemaker import Session, TrainingJobAnalytics from sagemaker...
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'''simple docstring''' from typing import List, Union from ..utils import ( add_end_docstrings, is_tf_available, is_torch_available, is_vision_available, logging, requires_backends, ) from .base import PIPELINE_INIT_ARGS, Pipeline if is_vision_available(): from PIL import Image ...
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'''simple docstring''' import requests def __lowerCAmelCase ( UpperCamelCase__ , UpperCamelCase__ ) -> None: __lowerCamelCase = {'''Content-Type''': '''application/json'''} __lowerCamelCase = requests.post(UpperCamelCase__ , json={'''text''': message_body} , headers=UpperCa...
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'''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, AutoMode...
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import io import math from typing import Dict, Optional, Union import numpy as np from huggingface_hub import hf_hub_download from ...image_processing_utils import BaseImageProcessor, BatchFeature from ...image_transforms import convert_to_rgb, normalize, to_channel_dimension_format, to_pil_image from ...image_util...
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'''simple docstring''' import torch from diffusers import DDPMScheduler from .test_schedulers import SchedulerCommonTest class _lowerCamelCase ( lowercase__ ): '''simple docstring''' A_ : Dict = (DDPMScheduler,) def __lowerCAmelCase ( self : Any ...
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"""simple docstring""" from typing import TYPE_CHECKING from ....utils import _LazyModule __UpperCamelCase = {'''tokenization_tapex''': ['''TapexTokenizer''']} if TYPE_CHECKING: from .tokenization_tapex import TapexTokenizer else: import sys __UpperCamelCase = _LazyModule(__nam...
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'''simple docstring''' import random import unittest import torch from diffusers import IFInpaintingPipeline from diffusers.utils import floats_tensor from diffusers.utils.import_utils import is_xformers_available from diffusers.utils.testing_utils import skip_mps, torch_device from ..pipeline_params import ( ...
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'''simple docstring''' # This script creates a super tiny model that is useful inside tests, when we just want to test that # the machinery works, without needing to the check the quality of the outcomes. # # This version creates a tiny vocab first, and then a tiny model - so the outcome is ...
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'''simple docstring''' import unittest from transformers import DebertaConfig, is_torch_available from transformers.testing_utils import require_sentencepiece, require_tokenizers, require_torch, slow, torch_device from ...test_configuration_common import ConfigTester from ...test_modeling_common import ModelTeste...
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import warnings from typing import List, Optional, Union from ...processing_utils import ProcessorMixin from ...tokenization_utils_base import BatchEncoding, PaddingStrategy, PreTokenizedInput, TextInput, TruncationStrategy from ...utils import TensorType class __A ( a ): ...
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'''simple docstring''' class _lowerCamelCase : # Public class to implement a graph '''simple docstring''' def __init__( self : List[Any] , _A : int , _A : int , _A : list[list[bool]] ) -> None: __magic_name__ : Tuple = row __...
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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 lowerCAmelCase__ = '''sshleife...
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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, is_vision_available, ) lowerCAmelCase :Tuple = {'''processing_layoutxlm''': ['''L...
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import tempfile import unittest import numpy as np from diffusers import ( DDIMScheduler, DPMSolverMultistepScheduler, EulerAncestralDiscreteScheduler, EulerDiscreteScheduler, LMSDiscreteScheduler, OnnxStableDiffusionPipeline, PNDMScheduler, ) from diffusers.utils.testing...
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'''simple docstring''' from __future__ import annotations from math import ceil, floor, sqrt def lowerCamelCase ( lowerCAmelCase : int = 200_0000 ): """simple docstring""" __magic_name__ : list[int] = [0] __magic_name__ : int for idx in range(1 , ceil(sqrt...
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"""simple docstring""" import os import re import shutil import sys import tempfile import unittest import black _lowercase = os.path.abspath(os.path.dirname(os.path.dirname(os.path.dirname(__file__)))) sys.path.append(os.path.join(git_repo_path, '''utils''')) import check_copies # noqa: E402 # Th...
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'''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, ) lowerCAmelCase :str = {'''configuration...
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'''simple docstring''' import random import timeit from functools import wraps from typing import Callable, Optional from ..configuration_utils import PretrainedConfig from ..models.auto.modeling_tf_auto import TF_MODEL_MAPPING, TF_MODEL_WITH_LM_HEAD_MAPPING from ..utils import is_pyanvml_available, is_tf_ava...
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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, get_resize_output_image_size, normalize, rescale, resize, to_channel...
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import re import tempfile from pathlib import Path import pytest import yaml from datasets.utils.readme import ReadMe # @pytest.fixture # def example_yaml_structure(): a_ = yaml.safe_load( '\\nname: ""\nallow_empty: false\nallow_empty_text: true\nsubsections:\n - name: "Dataset Card for X" # First-lev...
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'''simple docstring''' from __future__ import annotations from math import pi # Define the Reduced Planck Constant ℏ (H bar), speed of light C, value of # Pi and the function lowerCAmelCase :Tuple = 1.0_5_4_5_7_1_8_1_7E-3_4 # unit of ℏ : J * s lowerCAmelCase :Union[str, Any] = 3E8 # unit ...
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"""simple docstring""" def a_ ( _lowerCAmelCase : int , _lowerCAmelCase : int ): '''simple docstring''' return abs(_lowerCAmelCase ) if a == 0 else greatest_common_divisor(b % a , _lowerCAmelCase ) def a_ ( _lowerCAmelCase : int , _lowerCAmelC...
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'''simple docstring''' import os from itertools import chain from random import randrange, shuffle import pytest from .sola import PokerHand lowerCAmelCase :Tuple = ( '''4S 3H 2C 7S 5H''', '''9D 8H 2C 6S 7H''', '''2D 6D 9D TH 7D''', '''TC 8C 2S JH 6C''', '''JH 8S TH AH QH''', '...
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"""simple docstring""" import numpy as np import torch from torch.nn import CrossEntropyLoss from transformers import AutoModelForCausalLM, AutoTokenizer import datasets from datasets import logging snake_case_ = """\ """ snake_case_ = """ Perplexity (PPL) is one...
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'''simple docstring''' from typing import TYPE_CHECKING from ...utils import ( OptionalDependencyNotAvailable, _LazyModule, is_flax_available, is_tf_available, is_torch_available, ) lowerCAmelCase :Union[str, Any] = { '''configuration_vision_encoder_decoder''': ['''VisionEncode...
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'''simple docstring''' import logging import os import sys from dataclasses import dataclass, field from typing import Optional import numpy as np import torch from datasets import load_dataset from torchvision.transforms import Compose, Lambda, Normalize, RandomHorizontalFlip, RandomResizedCrop, ToTensor ...
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'''simple docstring''' from collections import UserDict from typing import List, Union from ..utils import ( add_end_docstrings, is_tf_available, is_torch_available, is_vision_available, logging, requires_backends, ) from .base import PIPELINE_INIT_ARGS, Pipeline if is_vision_available():...
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'''simple docstring''' import warnings from typing import List, Optional, Tuple, Union import numpy as np import PIL import torch from ...models import UNetaDModel from ...schedulers import RePaintScheduler from ...utils import PIL_INTERPOLATION, logging, randn_tensor from ..pipeline_utils import DiffusionP...
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'''simple docstring''' import json import os import re import shutil import tempfile import unittest from typing import Tuple from transformers import AddedToken, BatchEncoding, ByTaTokenizer from transformers.utils import cached_property, is_tf_available, is_torch_available from ...test_tokenization_common impor...
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"""simple docstring""" def _A ( lowercase , lowercase ): """simple docstring""" assert x is not None assert y is not None a =len(lowercase ) a =len(lowercase ) # declaring the array for storing the dp values a =[[0] * ...
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'''simple docstring''' import unittest from transformers import is_torch_available from transformers.testing_utils import require_torch if is_torch_available(): import torch from transformers.generation import DisjunctiveConstraint @require_torch class _lowerCamelCase ( unittest.TestCas...
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from typing import List, Optional, Union import numpy as np import PIL import torch from PIL import Image from ...models import UNetaDConditionModel, VQModel from ...pipelines import DiffusionPipeline from ...pipelines.pipeline_utils import ImagePipelineOutput from ...schedulers import DDPMScheduler from ...utils...
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'''simple docstring''' import re import tempfile from pathlib import Path import pytest import yaml from datasets.utils.readme import ReadMe # @pytest.fixture # def example_yaml_structure(): lowerCAmelCase :List[str] = yaml.safe_load( '''\ name: "" allow_empty: false allow_empty_text: true subse...
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'''simple docstring''' import os import jsonlines import numpy as np from tqdm import tqdm snake_case_ : Optional[Any] = 2048 snake_case_ : Union[str, Any] = 4096 snake_case_ : int = 42 snake_case_ : Any = os.environ.pop('PROCESS_TRAIN', 'false') snake_case_ : Dict = ...
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'''simple docstring''' from __future__ import annotations import os import tempfile import unittest from transformers import ConvBertConfig, is_tf_available from transformers.testing_utils import require_tf, slow from ...test_configuration_common import ConfigTester from ...test_modeling_tf_common import TFModel...
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"""simple docstring""" import tempfile import unittest import numpy as np from huggingface_hub import HfFolder, delete_repo from requests.exceptions import HTTPError from transformers import BertConfig, is_flax_available from transformers.testing_utils import TOKEN, USER, is_staging_test, requi...
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'''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 requ...
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'''simple docstring''' import argparse import torch from transformers import ( SpeechTaConfig, SpeechTaFeatureExtractor, SpeechTaForSpeechToSpeech, SpeechTaForSpeechToText, SpeechTaForTextToSpeech, SpeechTaProcessor, SpeechTaTokenizer, logging, ) from transformers.tokenizatio...
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'''simple docstring''' import logging from pathlib import Path import numpy as np import pytorch_lightning as pl import torch from pytorch_lightning.callbacks import EarlyStopping, ModelCheckpoint from pytorch_lightning.utilities import rank_zero_only from utils_rag import save_json def lowerCamelCase ( l...
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"""simple docstring""" from __future__ import annotations import unittest from transformers import is_tf_available, is_torch_available from transformers.testing_utils import DUMMY_UNKNOWN_IDENTIFIER, SMALL_MODEL_IDENTIFIER, is_pt_tf_cross_test, slow if is_tf_available(): from transformers import ( ...
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'''simple docstring''' def lowerCamelCase ( ): """simple docstring""" return 1 def lowerCamelCase ( lowerCAmelCase : int ): """simple docstring""" return 0 if x < 0 else two_pence(x - 2 ) + one_pence() def lowerCamelCase ( lowerCAmelCase : int ): """s...
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import requests UpperCamelCase = '''https://newsapi.org/v1/articles?source=bbc-news&sortBy=top&apiKey=''' def lowercase_ ( _lowerCamelCase : str): # fetching a list of articles in json format lowercase__ : Union[str, Any] = requests.get(_NEWS_API + bbc_news_...
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'''simple docstring''' from ..utils import DummyObject, requires_backends class _lowerCamelCase ( metaclass=lowercase__ ): '''simple docstring''' A_ : Optional[Any] = ["""flax""", """transformers"""] def __init__( self : Union[str, Any] , *_A : ...
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import collections import inspect import unittest from typing import Dict, List, Tuple from transformers import MaskFormerSwinConfig from transformers.testing_utils import require_torch, require_torch_multi_gpu, torch_device from transformers.utils import is_torch_available from ...test_backbone_common imp...
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'''simple docstring''' from typing import List, Union from ..utils import ( add_end_docstrings, is_tf_available, is_torch_available, is_vision_available, logging, requires_backends, ) from .base import PIPELINE_INIT_ARGS, Pipeline if is_vision_available(): from PIL import Image ...
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'''simple docstring''' import json import os from pathlib import Path from shutil import copyfile from typing import Any, Dict, List, Optional, Tuple, Union import sentencepiece from ...tokenization_utils import BatchEncoding, PreTrainedTokenizer from ...utils import logging __lowerCAmelCase = loggin...
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'''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, AutoMode...
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import argparse from diffusers.pipelines.stable_diffusion.convert_from_ckpt import download_controlnet_from_original_ckpt if __name__ == "__main__": __A = argparse.ArgumentParser() parser.add_argument( "--checkpoint_path", default=None, type=str, required=True, help="...
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'''simple docstring''' import torch from diffusers import DDPMScheduler from .test_schedulers import SchedulerCommonTest class _lowerCamelCase ( lowercase__ ): '''simple docstring''' A_ : Dict = (DDPMScheduler,) def __lowerCAmelCase ( self : Any ...
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"""simple docstring""" import sys from typing import Tuple import numpy as np import torch from PIL import Image from torch import nn from transformers.image_utils import PILImageResampling from utils import img_tensorize class lowerCAmelCase__ : '''simple docstring''' de...
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'''simple docstring''' import random import unittest import torch from diffusers import IFInpaintingPipeline from diffusers.utils import floats_tensor from diffusers.utils.import_utils import is_xformers_available from diffusers.utils.testing_utils import skip_mps, torch_device from ..pipeline_params import ( ...
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import datasets import faiss import numpy as np import streamlit as st import torch from elasticsearch import Elasticsearch from elia_utils import ( embed_questions_for_retrieval, make_qa_sas_model, qa_sas_generate, query_es_index, query_qa_dense_index, ) import transformers from transformers ...
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'''simple docstring''' import unittest from transformers import DebertaConfig, is_torch_available from transformers.testing_utils import require_sentencepiece, require_tokenizers, require_torch, slow, torch_device from ...test_configuration_common import ConfigTester from ...test_modeling_common import ModelTeste...
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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/license...
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'''simple docstring''' class _lowerCamelCase : # Public class to implement a graph '''simple docstring''' def __init__( self : List[Any] , _A : int , _A : int , _A : list[list[bool]] ) -> None: __magic_name__ : Tuple = row __...
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from copy import deepcopy from typing import Optional, Union import numpy as np from ...processing_utils import ProcessorMixin from ...tokenization_utils_base import BatchEncoding from ...utils import TensorType, is_tf_available, is_torch_available if is_torch_available(): import torch if is_tf_available()...
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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, is_vision_available, ) lowerCAmelCase :Tuple = {'''processing_layoutxlm''': ['''L...
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import functools def _A ( SCREAMING_SNAKE_CASE : list[int] , SCREAMING_SNAKE_CASE : list[int] ): """simple docstring""" if not isinstance(SCREAMING_SNAKE_CASE , SCREAMING_SNAKE_CASE ) or not all(isinstance(SCREAMING_SNAKE_CASE ...
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'''simple docstring''' from __future__ import annotations from math import ceil, floor, sqrt def lowerCamelCase ( lowerCAmelCase : int = 200_0000 ): """simple docstring""" __magic_name__ : list[int] = [0] __magic_name__ : int for idx in range(1 , ceil(sqrt...
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"""simple docstring""" import argparse import torch from huggingface_hub import hf_hub_download from transformers import AutoTokenizer, RobertaPreLayerNormConfig, RobertaPreLayerNormForMaskedLM from transformers.utils import logging logging.set_verbosity_info() lowercase__ ...
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'''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, ) lowerCAmelCase :str = {'''configuration...
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'''simple docstring''' import argparse import logging import sys from unittest.mock import patch import run_glue_deebert from transformers.testing_utils import TestCasePlus, get_gpu_count, require_torch_non_multi_gpu, slow logging.basicConfig(level=logging.DEBUG) __snake_case = logging.getLogger...
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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, get_resize_output_image_size, normalize, rescale, resize, to_channel...
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"""simple docstring""" from __future__ import annotations def a_ ( lowerCamelCase , lowerCamelCase ): if b == 0: return (1, 0) ((UpperCAmelCase__) , (UpperCAmelCase__)) = extended_euclid(lowerCamelCase , a % b ) UpperCAmelCase__ ...
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'''simple docstring''' from __future__ import annotations from math import pi # Define the Reduced Planck Constant ℏ (H bar), speed of light C, value of # Pi and the function lowerCAmelCase :Tuple = 1.0_5_4_5_7_1_8_1_7E-3_4 # unit of ℏ : J * s lowerCAmelCase :Union[str, Any] = 3E8 # unit ...
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import argparse import collections import json import os import re import string import sys import numpy as np lowercase : Union[str, Any] = re.compile(r"""\b(a|an|the)\b""", re.UNICODE) lowercase : Union[str, Any] = None def A_ ( ) -> Dict: a__ : Dict...
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'''simple docstring''' import os from itertools import chain from random import randrange, shuffle import pytest from .sola import PokerHand lowerCAmelCase :Tuple = ( '''4S 3H 2C 7S 5H''', '''9D 8H 2C 6S 7H''', '''2D 6D 9D TH 7D''', '''TC 8C 2S JH 6C''', '''JH 8S TH AH QH''', '...
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"""simple docstring""" from ...configuration_utils import PretrainedConfig from ...utils import logging __magic_name__ = logging.get_logger(__name__) __magic_name__ = { "facebook/dpr-ctx_encoder-single-nq-base": ( "https://huggingface.co/facebook/dpr-ctx_encoder-single-nq-base/resol...
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'''simple docstring''' from typing import TYPE_CHECKING from ...utils import ( OptionalDependencyNotAvailable, _LazyModule, is_flax_available, is_tf_available, is_torch_available, ) lowerCAmelCase :Union[str, Any] = { '''configuration_vision_encoder_decoder''': ['''VisionEncode...
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import argparse import glob import logging import os import sys import time from collections import defaultdict from pathlib import Path from typing import Dict, List, Tuple import numpy as np import pytorch_lightning as pl import torch from callbacks import SeqaSeqLoggingCallback, get_checkpoint_callback, get_early_...
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'''simple docstring''' from collections import UserDict from typing import List, Union from ..utils import ( add_end_docstrings, is_tf_available, is_torch_available, is_vision_available, logging, requires_backends, ) from .base import PIPELINE_INIT_ARGS, Pipeline if is_vision_available():...
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"""simple docstring""" from math import sqrt import numpy as np from sympy import symbols # Coefficient # Speed of light (m/s) SCREAMING_SNAKE_CASE : str = 2_9979_2458 # Symbols SCREAMING_SNAKE_CASE , SCREAMING_SNAKE_CASE , SCREAMING_SNAKE_CASE , SCREAMING_SNAKE_CASE : Dict ...
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'''simple docstring''' import json import os import re import shutil import tempfile import unittest from typing import Tuple from transformers import AddedToken, BatchEncoding, ByTaTokenizer from transformers.utils import cached_property, is_tf_available, is_torch_available from ...test_tokenization_common impor...
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import numpy as np import torch from imwatermark import WatermarkEncoder # Copied from https://github.com/Stability-AI/generative-models/blob/613af104c6b85184091d42d374fef420eddb356d/scripts/demo/streamlit_helpers.py#L66 A__ : List[str] = 0b10_11_00_11_11_10_11_00_10_01_00_00_01_11_10_11_10_11_00_01_...
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'''simple docstring''' import unittest from transformers import is_torch_available from transformers.testing_utils import require_torch if is_torch_available(): import torch from transformers.generation import DisjunctiveConstraint @require_torch class _lowerCamelCase ( unittest.TestCas...
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'''simple docstring''' import inspect from typing import List, Optional, Tuple, Union import numpy as np import PIL import torch import torch.utils.checkpoint from ...models import UNetaDModel, VQModel from ...schedulers import ( DDIMScheduler, DPMSolverMultistepScheduler, EulerAncestralDiscreteSc...
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'''simple docstring''' import re import tempfile from pathlib import Path import pytest import yaml from datasets.utils.readme import ReadMe # @pytest.fixture # def example_yaml_structure(): lowerCAmelCase :List[str] = yaml.safe_load( '''\ name: "" allow_empty: false allow_empty_text: true subse...
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"""simple docstring""" # tests directory-specific settings - this file is run automatically # by pytest before any tests are run import sys import warnings from os.path import abspath, dirname, join # allow having multiple repository checkouts and not needing to remember to rerun # 'pip...
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'''simple docstring''' from __future__ import annotations import os import tempfile import unittest from transformers import ConvBertConfig, is_tf_available from transformers.testing_utils import require_tf, slow from ...test_configuration_common import ConfigTester from ...test_modeling_tf_common import TFModel...
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"""simple docstring""" from typing import TYPE_CHECKING from ...utils import _LazyModule __UpperCamelCase : Optional[Any] = {'''tokenization_bertweet''': ['''BertweetTokenizer''']} if TYPE_CHECKING: from .tokenization_bertweet import BertweetTokenizer else: import sys ...
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'''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 requ...
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import warnings from ...processing_utils import ProcessorMixin from ...tokenization_utils_base import BatchEncoding class snake_case__ (_UpperCamelCase ): """simple docstring""" SCREAMING_SNAKE_CASE_ : int = ["""image_processor""", """tokenizer"""] SCREAMING_S...
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'''simple docstring''' import logging from pathlib import Path import numpy as np import pytorch_lightning as pl import torch from pytorch_lightning.callbacks import EarlyStopping, ModelCheckpoint from pytorch_lightning.utilities import rank_zero_only from utils_rag import save_json def lowerCamelCase ( l...
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"""simple docstring""" # Lint as: python3 import os import re import urllib.parse from pathlib import Path from typing import Callable, List, Optional, Union from zipfile import ZipFile from ..utils.file_utils import cached_path, hf_github_url from ..utils.logging import get_logger from ..utils.version impor...
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'''simple docstring''' def lowerCamelCase ( ): """simple docstring""" return 1 def lowerCamelCase ( lowerCAmelCase : int ): """simple docstring""" return 0 if x < 0 else two_pence(x - 2 ) + one_pence() def lowerCamelCase ( lowerCAmelCase : int ): """s...
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"""simple docstring""" from __future__ import annotations import unittest from transformers import is_tf_available from transformers.testing_utils import require_sentencepiece, require_tf, require_tokenizers, slow if is_tf_available(): import numpy as np import tensorflow as tf from transform...
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'''simple docstring''' from ..utils import DummyObject, requires_backends class _lowerCamelCase ( metaclass=lowercase__ ): '''simple docstring''' A_ : Optional[Any] = ["""flax""", """transformers"""] def __init__( self : Union[str, Any] , *_A : ...
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"""simple docstring""" import unittest from transformers import DebertaConfig, is_torch_available from transformers.testing_utils import require_sentencepiece, require_tokenizers, require_torch, slow, torch_device from ...test_configuration_common import ConfigTester from ...test_modeling_common import ModelTes...
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'''simple docstring''' from typing import List, Union from ..utils import ( add_end_docstrings, is_tf_available, is_torch_available, is_vision_available, logging, requires_backends, ) from .base import PIPELINE_INIT_ARGS, Pipeline if is_vision_available(): from PIL import Image ...
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"""simple docstring""" class lowerCAmelCase__ : '''simple docstring''' def __init__( self : Optional[int] , lowercase_ : list): '''simple docstring''' SCREAMING_SNAKE_CASE_ : Tuple = set_counts SCREAMING_SN...
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'''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, AutoMode...
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import dataclasses import re from dataclasses import dataclass from functools import total_ordering from typing import Optional, Union lowercase__ : Union[str, Any] = re.compile(R"^(?P<major>\d+)" R"\.(?P<minor>\d+)" R"\.(?P<patch>\d+)$") @total_ordering @dataclass class UpperCAmel...
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'''simple docstring''' import torch from diffusers import DDPMScheduler from .test_schedulers import SchedulerCommonTest class _lowerCamelCase ( lowercase__ ): '''simple docstring''' A_ : Dict = (DDPMScheduler,) def __lowerCAmelCase ( self : Any ...
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def lowerCamelCase__ ( a__ : Optional[int] , a__ : Union[str, Any] , a__ : int , a__ : Any , a__ : Dict , a__ : List[str] ) -> Optional[Any]: if index == r: for j in range(a__ ): print(...
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'''simple docstring''' import random import unittest import torch from diffusers import IFInpaintingPipeline from diffusers.utils import floats_tensor from diffusers.utils.import_utils import is_xformers_available from diffusers.utils.testing_utils import skip_mps, torch_device from ..pipeline_params import ( ...
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'''simple docstring''' from typing import TYPE_CHECKING from ...utils import ( OptionalDependencyNotAvailable, _LazyModule, is_flax_available, is_tf_available, is_tokenizers_available, is_torch_available, ) lowercase__ : List[Any] = { '''configuration_electra''': ['...
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'''simple docstring''' import unittest from transformers import DebertaConfig, is_torch_available from transformers.testing_utils import require_sentencepiece, require_tokenizers, require_torch, slow, torch_device from ...test_configuration_common import ConfigTester from ...test_modeling_common import ModelTeste...
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import os def __lowerCamelCase ( ): """simple docstring""" a :int = os.path.join(os.path.dirname(UpperCAmelCase_ ) , '''num.txt''' ) with open(UpperCAmelCase_ ) as file_hand: return str(sum(int(UpperCAmelCase_ ) for line in file_h...
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'''simple docstring''' class _lowerCamelCase : # Public class to implement a graph '''simple docstring''' def __init__( self : List[Any] , _A : int , _A : int , _A : list[list[bool]] ) -> None: __magic_name__ : Tuple = row __...
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'''simple docstring''' import argparse import struct import unittest class lowercase__ : def __init__( self : int ,lowerCamelCase__ : bytes ): '''simple docstring''' _UpperCamelCase : Dict = data # Initialize hash values _UpperCamelCase...
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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, is_vision_available, ) lowerCAmelCase :Tuple = {'''processing_layoutxlm''': ['''L...
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import argparse import json import os import time import zipfile from get_ci_error_statistics import download_artifact, get_artifacts_links from transformers import logging __lowerCAmelCase : Optional[int] = logging.get_logger(__name__) def UpperCAmelCase_ ( __lowerCAmelCase ...
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'''simple docstring''' from __future__ import annotations from math import ceil, floor, sqrt def lowerCamelCase ( lowerCAmelCase : int = 200_0000 ): """simple docstring""" __magic_name__ : list[int] = [0] __magic_name__ : int for idx in range(1 , ceil(sqrt...
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'''simple docstring''' from ...processing_utils import ProcessorMixin class lowerCAmelCase_ ( lowercase__ ): __lowerCamelCase : Union[str, Any] = """SpeechT5FeatureExtractor""" __lowerCamelCase : Tuple = """SpeechT5Tokenizer""" def __init__( self...
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'''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, ) lowerCAmelCase :str = {'''configuration...
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import unittest from transformers import is_tf_available from transformers.testing_utils import require_tf if is_tf_available(): import tensorflow as tf from tensorflow.python.eager import context from tensorflow.python.framework import ops from transformers import GradientAccumulator, create_opti...
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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, get_resize_output_image_size, normalize, rescale, resize, to_channel...
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import copy from ...configuration_utils import PretrainedConfig from ...utils import logging from ..bit import BitConfig A : int = logging.get_logger(__name__) A : Dict = { '''Intel/dpt-large''': '''https://huggingface.co/Intel/dpt-large/resolve/main/config.json''', # See all DPT models at ht...
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'''simple docstring''' from __future__ import annotations from math import pi # Define the Reduced Planck Constant ℏ (H bar), speed of light C, value of # Pi and the function lowerCAmelCase :Tuple = 1.0_5_4_5_7_1_8_1_7E-3_4 # unit of ℏ : J * s lowerCAmelCase :Union[str, Any] = 3E8 # unit ...
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"""simple docstring""" from __future__ import annotations import unittest from transformers import AutoTokenizer, MBartConfig, is_tf_available from transformers.testing_utils import require_sentencepiece, require_tf, require_tokenizers, slow from transformers.utils import cached_property from ...test_configura...
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'''simple docstring''' import os from itertools import chain from random import randrange, shuffle import pytest from .sola import PokerHand lowerCAmelCase :Tuple = ( '''4S 3H 2C 7S 5H''', '''9D 8H 2C 6S 7H''', '''2D 6D 9D TH 7D''', '''TC 8C 2S JH 6C''', '''JH 8S TH AH QH''', '...
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"""simple docstring""" from __future__ import annotations import collections import tempfile import unittest import numpy as np from transformers.testing_utils import require_tf, require_vision, slow from transformers.utils import is_tf_available, is_vision_available from ...test_modeling_tf_common imp...
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'''simple docstring''' from typing import TYPE_CHECKING from ...utils import ( OptionalDependencyNotAvailable, _LazyModule, is_flax_available, is_tf_available, is_torch_available, ) lowerCAmelCase :Union[str, Any] = { '''configuration_vision_encoder_decoder''': ['''VisionEncode...
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def lowerCamelCase__ ( _A , _A ): '''simple docstring''' return int((input_a, input_a).count(1 ) != 0 ) def lowerCamelCase__ ( ): '''simple docstring''' assert or_gate(0 , 0 ) == 0 assert or_gate...
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'''simple docstring''' from collections import UserDict from typing import List, Union from ..utils import ( add_end_docstrings, is_tf_available, is_torch_available, is_vision_available, logging, requires_backends, ) from .base import PIPELINE_INIT_ARGS, Pipeline if is_vision_available():...
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from typing import TYPE_CHECKING from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available _A = { '''configuration_time_series_transformer''': [ '''TIME_SERIES_TRANSFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''TimeSeriesTransformerConfig''', ], } try: ...
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'''simple docstring''' import json import os import re import shutil import tempfile import unittest from typing import Tuple from transformers import AddedToken, BatchEncoding, ByTaTokenizer from transformers.utils import cached_property, is_tf_available, is_torch_available from ...test_tokenization_common impor...
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'''simple docstring''' class __lowerCAmelCase : """simple docstring""" def __init__( self : Optional[int] , lowerCAmelCase__ : int ) -> None: '''simple docstring''' _UpperCamelCase = size _UpperCam...
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'''simple docstring''' import unittest from transformers import is_torch_available from transformers.testing_utils import require_torch if is_torch_available(): import torch from transformers.generation import DisjunctiveConstraint @require_torch class _lowerCamelCase ( unittest.TestCas...
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def __lowerCamelCase ( UpperCAmelCase_ : Dict ): """simple docstring""" a :int = len(UpperCAmelCase_ ) while cur > 1: # Find the maximum number in arr a :int = arr.index(max(arr[0:cur] ) ) ...
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'''simple docstring''' import re import tempfile from pathlib import Path import pytest import yaml from datasets.utils.readme import ReadMe # @pytest.fixture # def example_yaml_structure(): lowerCAmelCase :List[str] = yaml.safe_load( '''\ name: "" allow_empty: false allow_empty_text: true subse...
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'''simple docstring''' from typing import TYPE_CHECKING from ...utils import ( OptionalDependencyNotAvailable, _LazyModule, is_torch_available, ) snake_case_ : Tuple = { '''configuration_falcon''': ['''FALCON_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''FalconConfig'''], } try: if not is_t...
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'''simple docstring''' from __future__ import annotations import os import tempfile import unittest from transformers import ConvBertConfig, is_tf_available from transformers.testing_utils import require_tf, slow from ...test_configuration_common import ConfigTester from ...test_modeling_tf_common import TFModel...
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import os def UpperCAmelCase_ ( ) -> Any: __lowercase : Any = os.path.dirname(os.path.realpath(__lowerCAmelCase ) ) __lowercase : str = os.path.join(__lowerCAmelCase , '''triangle.txt''' ) with open(__lowerCAmelCase ) as f: __lowercase ...
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'''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 requ...
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'''simple docstring''' from __future__ import annotations from sys import maxsize from typing import Generic, TypeVar _SCREAMING_SNAKE_CASE = TypeVar("T") def __a(SCREAMING_SNAKE_CASE_ : int ): '''simple docstring''' return (position - 1) // 2 def __a(SCREAMING_S...
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'''simple docstring''' import logging from pathlib import Path import numpy as np import pytorch_lightning as pl import torch from pytorch_lightning.callbacks import EarlyStopping, ModelCheckpoint from pytorch_lightning.utilities import rank_zero_only from utils_rag import save_json def lowerCamelCase ( l...
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import os from typing import Dict, List, Union import tensorflow as tf from keras_nlp.tokenizers import BytePairTokenizer from tensorflow_text import pad_model_inputs from .tokenization_gpta import GPTaTokenizer class _A ( tf.keras.layers.Layer): def __init__( self , _SCREAMING_SNAKE_CAS...
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'''simple docstring''' def lowerCamelCase ( ): """simple docstring""" return 1 def lowerCamelCase ( lowerCAmelCase : int ): """simple docstring""" return 0 if x < 0 else two_pence(x - 2 ) + one_pence() def lowerCamelCase ( lowerCAmelCase : int ): """s...
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import logging import os from typing import List, Tuple import numpy as np import psutil import torch import torch.distributed as dist from transformers import RagRetriever A : List[Any] = logging.getLogger(__name__) class __A( lowercase__ ): def __init__( self , _snake_case , ...
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'''simple docstring''' from ..utils import DummyObject, requires_backends class _lowerCamelCase ( metaclass=lowercase__ ): '''simple docstring''' A_ : Optional[Any] = ["""flax""", """transformers"""] def __init__( self : Union[str, Any] , *_A : ...
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"""simple docstring""" from typing import TYPE_CHECKING from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available __magic_name__ = { '''configuration_blip_2''': [ '''BLIP_2_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''Blip2Config''', '''Blip2QFormerConfig'...
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'''simple docstring''' from typing import List, Union from ..utils import ( add_end_docstrings, is_tf_available, is_torch_available, is_vision_available, logging, requires_backends, ) from .base import PIPELINE_INIT_ARGS, Pipeline if is_vision_available(): from PIL import Image ...
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"""simple docstring""" import argparse from pathlib import Path from transformers import AutoConfig, AutoTokenizer, RagConfig, RagSequenceForGeneration, RagTokenForGeneration def _A (__a , __a , __a , __a , __a = None , __a = None , __a = None , ) -> ...
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'''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, AutoMode...
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from typing import TYPE_CHECKING from ...utils import ( OptionalDependencyNotAvailable, _LazyModule, is_sentencepiece_available, is_tokenizers_available, is_torch_available, is_vision_available, ) lowercase__ : Tuple = {'''processing_layoutxlm''': ['''Layou...
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'''simple docstring''' import torch from diffusers import DDPMScheduler from .test_schedulers import SchedulerCommonTest class _lowerCamelCase ( lowercase__ ): '''simple docstring''' A_ : Dict = (DDPMScheduler,) def __lowerCAmelCase ( self : Any ...
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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 ModelTesterMixin, ids_tensor from ....
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'''simple docstring''' import random import unittest import torch from diffusers import IFInpaintingPipeline from diffusers.utils import floats_tensor from diffusers.utils.import_utils import is_xformers_available from diffusers.utils.testing_utils import skip_mps, torch_device from ..pipeline_params import ( ...
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'''simple docstring''' from __future__ import annotations import inspect import unittest from transformers import ViTConfig from transformers.testing_utils import require_tf, require_vision, slow from transformers.utils import cached_property, is_tf_available, is_vision_available from ...test_configuration_co...
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'''simple docstring''' import unittest from transformers import DebertaConfig, is_torch_available from transformers.testing_utils import require_sentencepiece, require_tokenizers, require_torch, slow, torch_device from ...test_configuration_common import ConfigTester from ...test_modeling_common import ModelTeste...
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import unittest from transformers.models.xlm_prophetnet.tokenization_xlm_prophetnet import SPIECE_UNDERLINE, XLMProphetNetTokenizer from transformers.testing_utils import get_tests_dir, require_sentencepiece, slow from transformers.utils import cached_property from ...test_tokenization_common import TokenizerTeste...
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'''simple docstring''' class _lowerCamelCase : # Public class to implement a graph '''simple docstring''' def __init__( self : List[Any] , _A : int , _A : int , _A : list[list[bool]] ) -> None: __magic_name__ : Tuple = row __...
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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 FlaxSchedulerMixin ...
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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, is_vision_available, ) lowerCAmelCase :Tuple = {'''processing_layoutxlm''': ['''L...
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import inspect import unittest from huggingface_hub import hf_hub_download from transformers import ConvNextConfig, UperNetConfig from transformers.testing_utils import require_torch, require_torch_multi_gpu, require_vision, slow, torch_device from transformers.utils import is_torch_available, is_vision_avai...
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'''simple docstring''' from __future__ import annotations from math import ceil, floor, sqrt def lowerCamelCase ( lowerCAmelCase : int = 200_0000 ): """simple docstring""" __magic_name__ : list[int] = [0] __magic_name__ : int for idx in range(1 , ceil(sqrt...
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'''simple docstring''' from argparse import ArgumentParser from datasets.commands.convert import ConvertCommand from datasets.commands.dummy_data import DummyDataCommand from datasets.commands.env import EnvironmentCommand from datasets.commands.run_beam import RunBeamCommand from datasets.commands.test import...
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'''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, ) lowerCAmelCase :str = {'''configuration...
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