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'''simple docstring''' def SCREAMING_SNAKE_CASE( ) -> list[list[int]]: return [list(range(1_0_0_0 - i , -1_0_0_0 - i , -1 ) ) for i in range(1_0_0_0 )] UpperCamelCase = generate_large_matrix() UpperCamelCase = ( [[4, 3, ...
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'''simple docstring''' import warnings from ...utils import logging from .image_processing_beit import BeitImageProcessor UpperCamelCase = logging.get_logger(__name__) class lowerCAmelCase_ ( UpperCAmelCase_ ): '''simple docstring''' def __...
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'''simple docstring''' import argparse import torch from ...utils import logging from . import AlbertConfig, AlbertForPreTraining, load_tf_weights_in_albert logging.set_verbosity_info() def SCREAMING_SNAKE_CASE( __lowercase , __lowercase , __lowercase ) -...
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'''simple docstring''' import os import pytest from transformers.dynamic_module_utils import get_imports UpperCamelCase = ''' import os ''' UpperCamelCase = ''' def foo(): import os return False ''' UpperCamelCase = ''' def foo(): def bar(): ...
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'''simple docstring''' import argparse import requests import torch from PIL import Image from transformers import SwinConfig, SwinForMaskedImageModeling, ViTImageProcessor def SCREAMING_SNAKE_CASE( __lowercase ) -> Optional[Any]: A: Any = SwinConfig(imag...
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'''simple docstring''' import argparse import json from pathlib import Path import requests import torch from huggingface_hub import hf_hub_download from PIL import Image from transformers import ( BertTokenizer, ViltConfig, ViltForImageAndTextRetrieval, ViltForImagesAndTex...
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'''simple docstring''' import inspect import unittest from datasets import load_dataset from packaging import version from transformers import BeitConfig from transformers.models.auto import get_values from transformers.testing_utils import require_torch, require_torch_multi_gpu, require_vision...
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'''simple docstring''' import argparse import json import os import numpy as np import PIL import requests import tensorflow.keras.applications.efficientnet as efficientnet import torch from huggingface_hub import hf_hub_download from PIL import Image from tensorflow.keras.preprocessing impor...
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'''simple docstring''' from dataclasses import dataclass from typing import Dict, Optional, Union import torch import torch.nn.functional as F from torch import nn from ..configuration_utils import ConfigMixin, register_to_config from ..utils import BaseOutput from .attention import BasicTrans...
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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_focalnet''': ['''FOCALNET_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''FocalNetCon...
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'''simple docstring''' import unittest from transformers import is_torch_available from transformers.testing_utils import require_sentencepiece, require_tokenizers, require_torch, slow if is_torch_available(): import torch from transformers import XLMRobertaModel @requ...
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'''simple docstring''' from typing import Any, Dict, List, Union from ..utils import add_end_docstrings, is_torch_available, is_vision_available, logging, requires_backends from .base import PIPELINE_INIT_ARGS, Pipeline if is_vision_available(): from ..image_utils import load_image if...
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'''simple docstring''' import os try: from .build_directory_md import good_file_paths except ImportError: from build_directory_md import good_file_paths # type: ignore UpperCamelCase = list(good_file_paths()) assert filepaths, "good_file_paths() failed!" UpperCamelCase ...
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'''simple docstring''' from collections import OrderedDict from typing import Mapping from ...configuration_utils import PretrainedConfig from ...onnx import OnnxConfig from ...utils import logging UpperCamelCase = logging.get_logger(__name__) UpperCamelCase = { '''Yi...
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'''simple docstring''' import inspect import os import re from transformers.configuration_utils import PretrainedConfig from transformers.utils import direct_transformers_import # All paths are set with the intent you should run this script from the root of the repo with the command # python ...
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'''simple docstring''' from __future__ import annotations def SCREAMING_SNAKE_CASE( __lowercase ) -> bool: if len(__lowercase ) < 2: raise ValueError('''Monogons and Digons are not polygons in the Euclidean space''' ) if any(i <= 0 for i in nums ): ...
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'''simple docstring''' import os # Precomputes a list of the 100 first triangular numbers UpperCamelCase = [int(0.5 * n * (n + 1)) for n in range(1, 101)] def SCREAMING_SNAKE_CASE( ) -> Union[str, Any]: A: List[str] = os.path.dirname(os.path.realpath(__l...
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'''simple docstring''' # tests directory-specific settings - this file is run automatically # by pytest before any tests are run import doctest import sys import warnings from os.path import abspath, dirname, join import _pytest from transformers.testing_utils import HfDoctestModule, HfDocTe...
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'''simple docstring''' from argparse import ArgumentParser from .add_new_model import AddNewModelCommand from .add_new_model_like import AddNewModelLikeCommand from .convert import ConvertCommand from .download import DownloadCommand from .env import EnvironmentCommand from .lfs import LfsCommand...
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'''simple docstring''' import heapq import sys import numpy as np UpperCamelCase = tuple[int, int] class lowerCAmelCase_ : '''simple docstring''' def __init__( self : List[Any] ) -> str: '''simple ...
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'''simple docstring''' import math from datetime import datetime, timedelta def SCREAMING_SNAKE_CASE( __lowercase ) -> datetime: A: Optional[Any] = year % 1_9 A: str = year % 4 A: int = year % 7 A: int = ...
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'''simple docstring''' def SCREAMING_SNAKE_CASE( __lowercase = 1 , __lowercase = 1_0_0_0 ) -> int: A: Any = 1 A: Optional[Any] = 0 for divide_by_number in range(__lowercase , digit + 1 ): A: li...
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'''simple docstring''' import os import time import numpy as np import onnxruntime as ort UpperCamelCase = '''1''' UpperCamelCase = '''0''' UpperCamelCase = '''1''' UpperCamelCase = ort.SessionOptions() UpperCamelCase = ort.GraphOptimizationLev...
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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, ) UpperCamelCase = { '''configuration_vision_encoder_decoder''': ['''VisionEn...
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'''simple docstring''' from queue import PriorityQueue from typing import Any import numpy as np def SCREAMING_SNAKE_CASE( __lowercase , __lowercase , __lowercase , __lowercase , __lowercase , __lowercase , __lowercase , ...
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'''simple docstring''' import fire from utils import calculate_rouge, save_json def SCREAMING_SNAKE_CASE( __lowercase , __lowercase , __lowercase=None , **__lowercase ) -> Any: A: Any = [x.strip() for x in open(__lowercase ...
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'''simple docstring''' from ..utils import DummyObject, requires_backends class lowerCAmelCase_ ( metaclass=UpperCAmelCase_ ): '''simple docstring''' UpperCamelCase_ : Optional[int] = ["""keras_nlp"""] def __init__( self ...
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'''simple docstring''' def SCREAMING_SNAKE_CASE( __lowercase , __lowercase = 0 ) -> list: A: Dict = length or len(__lowercase ) A: Dict = False for i in range(length - 1 ): if list_data[i] > list_data[i + 1]...
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'''simple docstring''' from collections import OrderedDict from typing import TYPE_CHECKING, Any, Mapping, Optional, Union from ...configuration_utils import PretrainedConfig from ...onnx import OnnxConfig, OnnxSeqaSeqConfigWithPast from ...utils import logging if TYPE_CHECKING: from ......
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'''simple docstring''' import argparse from collections import OrderedDict from pathlib import Path import torch from transformers import ( VisualBertConfig, VisualBertForMultipleChoice, VisualBertForPreTraining, VisualBertForQuestionAnswering, VisualBertForVisualReasonin...
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'''simple docstring''' import os import sys import unittest UpperCamelCase = os.path.abspath(os.path.dirname(os.path.dirname(os.path.dirname(__file__)))) sys.path.append(os.path.join(git_repo_path, '''utils''')) import get_test_info # noqa: E402 from get_test_info import ( # noqa: ...
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'''simple docstring''' from itertools import permutations def SCREAMING_SNAKE_CASE( __lowercase ) -> bool: if num[3] % 2 != 0: return False if (num[2] + num[3] + num[4]) % 3 != 0: return False if num[5] % 5 != 0: return False ...
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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...
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'''simple docstring''' import json import os from functools import lru_cache from typing import List, Optional, Tuple import regex as re from ...tokenization_utils import AddedToken, PreTrainedTokenizer from ...utils import logging UpperCamelCase = logging.get_logger(__name__) ...
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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 SCREAMING_SNAKE_CASE( __lowercase ) -> str: # encod...
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'''simple docstring''' def SCREAMING_SNAKE_CASE( __lowercase ) -> int: if not isinstance(__lowercase , __lowercase ): raise TypeError('''only integers accepted as input''' ) else: A: str = str(abs(__lowercase ) ...
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'''simple docstring''' import json import os import unittest from transformers.models.gptsan_japanese.tokenization_gptsan_japanese import ( VOCAB_FILES_NAMES, GPTSanJapaneseTokenizer, ) from transformers.testing_utils import require_tokenizers, slow from ...test_tokenization_common im...
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'''simple docstring''' from __future__ import annotations import math def SCREAMING_SNAKE_CASE( __lowercase , __lowercase ) -> list: if len(__lowercase ) != 2 or len(a[0] ) != 2 or len(__lowercase ) != 2 or len(b[0] ) != 2: raise Excepti...
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'''simple docstring''' from typing import TYPE_CHECKING from ...utils import ( OptionalDependencyNotAvailable, _LazyModule, is_torch_available, ) UpperCamelCase = { '''configuration_swiftformer''': [ '''SWIFTFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP''', ...
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'''simple docstring''' from dataclasses import dataclass from typing import Optional, Tuple, Union import numpy as np import torch from ..configuration_utils import ConfigMixin, register_to_config from ..utils import BaseOutput, randn_tensor from .scheduling_utils import SchedulerMixin ...
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'''simple docstring''' import pyarrow.parquet as pq import pytest from datasets import Audio, Dataset, DatasetDict, Features, NamedSplit, Sequence, Value, config from datasets.features.image import Image from datasets.io.parquet import ParquetDatasetReader, ParquetDatasetWriter, get_writer_batch_si...
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'''simple docstring''' import json import logging import math import os import sys from dataclasses import dataclass, field from typing import Optional from datasets import Dataset, load_dataset import transformers from transformers import ( CONFIG_MAPPING, MODEL_FOR_MASKED_LM_MAPP...
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'''simple docstring''' from __future__ import annotations import matplotlib.pyplot as plt # type: ignore import numpy # initial triangle of Koch snowflake UpperCamelCase = numpy.array([0, 0]) UpperCamelCase = numpy.array([0.5, 0.8_66_02_54]) UpperCamelCase = numpy.ar...
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'''simple docstring''' import json import os import unittest from typing import Tuple from transformers import WavaVecaPhonemeCTCTokenizer from transformers.models.wavaveca.tokenization_wavaveca import VOCAB_FILES_NAMES from transformers.models.wavaveca_phoneme.tokenization_wavaveca_phoneme impor...
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'''simple docstring''' import argparse import os import torch from transformers.utils import WEIGHTS_NAME UpperCamelCase = ['''small''', '''medium''', '''large'''] UpperCamelCase = '''lm_head.decoder.weight''' UpperCamelCase = '''lm_head.weight''' def SCREAMIN...
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'''simple docstring''' import warnings from ...utils import logging from .image_processing_beit import BeitImageProcessor UpperCamelCase = logging.get_logger(__name__) class lowerCAmelCase_ ( UpperCAmelCase_ ): '''simple docstring''' def __...
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'''simple docstring''' from manim import * class lowerCAmelCase_ ( UpperCAmelCase_ ): '''simple docstring''' def _snake_case ( self : int ) -> Union[str, Any]: '''simple docstring''' A: ...
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'''simple docstring''' import os import pytest from transformers.dynamic_module_utils import get_imports UpperCamelCase = ''' import os ''' UpperCamelCase = ''' def foo(): import os return False ''' UpperCamelCase = ''' def foo(): def bar(): ...
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'''simple docstring''' from __future__ import annotations import time from math import sqrt # 1 for manhattan, 0 for euclidean UpperCamelCase = 0 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...
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'''simple docstring''' import argparse import json from pathlib import Path import requests import torch from huggingface_hub import hf_hub_download from PIL import Image from transformers import ( BertTokenizer, ViltConfig, ViltForImageAndTextRetrieval, ViltForImagesAndTex...
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'''simple docstring''' from ...utils import ( OptionalDependencyNotAvailable, is_torch_available, is_transformers_available, is_transformers_version, ) try: if not (is_transformers_available() and is_torch_available()): raise OptionalDependencyNotAvailable() ex...
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'''simple docstring''' import argparse import json import os import numpy as np import PIL import requests import tensorflow.keras.applications.efficientnet as efficientnet import torch from huggingface_hub import hf_hub_download from PIL import Image from tensorflow.keras.preprocessing impor...
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'''simple docstring''' import baseaa import io import json import os from copy import deepcopy from ..optimizer import AcceleratedOptimizer from ..scheduler import AcceleratedScheduler class lowerCAmelCase_ : '''simple docstring''' def __init__( self ...
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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_focalnet''': ['''FOCALNET_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''FocalNetCon...
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'''simple docstring''' import argparse from pathlib import Path from transformers import AutoConfig, AutoTokenizer, RagConfig, RagSequenceForGeneration, RagTokenForGeneration def SCREAMING_SNAKE_CASE( __lowercase , __lowercase , __lowercase , __lowercase , ...
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'''simple docstring''' from typing import Any, Dict, List, Union from ..utils import add_end_docstrings, is_torch_available, is_vision_available, logging, requires_backends from .base import PIPELINE_INIT_ARGS, Pipeline if is_vision_available(): from ..image_utils import load_image if...
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'''simple docstring''' from collections.abc import Iterator, MutableMapping from dataclasses import dataclass from typing import Generic, TypeVar UpperCamelCase = TypeVar('''KEY''') UpperCamelCase = TypeVar('''VAL''') @dataclass(frozen=UpperCAmelCase_ , slots=Upper...
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'''simple docstring''' from collections import OrderedDict from typing import Mapping from ...configuration_utils import PretrainedConfig from ...onnx import OnnxConfig from ...utils import logging UpperCamelCase = logging.get_logger(__name__) UpperCamelCase = { '''Yi...
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'''simple docstring''' import numpy as np from cva import COLOR_BGR2GRAY, cvtColor, imread from numpy import array, uinta from PIL import Image from digital_image_processing import change_contrast as cc from digital_image_processing import convert_to_negative as cn from digital_image_processing i...
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'''simple docstring''' from __future__ import annotations def SCREAMING_SNAKE_CASE( __lowercase ) -> bool: if len(__lowercase ) < 2: raise ValueError('''Monogons and Digons are not polygons in the Euclidean space''' ) if any(i <= 0 for i in nums ): ...
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'''simple docstring''' import math def SCREAMING_SNAKE_CASE( __lowercase ) -> list: A: int = [True] * n A: List[str] = False A: List[str] = False A: List[Any] = True for i in range(3 , ...
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'''simple docstring''' # tests directory-specific settings - this file is run automatically # by pytest before any tests are run import doctest import sys import warnings from os.path import abspath, dirname, join import _pytest from transformers.testing_utils import HfDoctestModule, HfDocTe...
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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/...
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'''simple docstring''' import heapq import sys import numpy as np UpperCamelCase = tuple[int, int] class lowerCAmelCase_ : '''simple docstring''' def __init__( self : List[Any] ) -> str: '''simple ...
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'''simple docstring''' import itertools import json import linecache import os import pickle import re import socket import string from collections import Counter from logging import getLogger from pathlib import Path from typing import Callable, Dict, Iterable, List import git import torc...
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'''simple docstring''' def SCREAMING_SNAKE_CASE( __lowercase = 1 , __lowercase = 1_0_0_0 ) -> int: A: Any = 1 A: Optional[Any] = 0 for divide_by_number in range(__lowercase , digit + 1 ): A: li...
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'''simple docstring''' import inspect import os import sys import unittest import accelerate from accelerate.test_utils import execute_subprocess_async, require_tpu class lowerCAmelCase_ ( unittest.TestCase ): '''simple docstring''' def _snake_case ...
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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, ) UpperCamelCase = { '''configuration_vision_encoder_decoder''': ['''VisionEn...
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'''simple docstring''' # limitations under the License. # 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 .pipelines import DiffusionPipeline, ImagePipelineOutput # noqa: F40...
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'''simple docstring''' import fire from utils import calculate_rouge, save_json def SCREAMING_SNAKE_CASE( __lowercase , __lowercase , __lowercase=None , **__lowercase ) -> Any: A: Any = [x.strip() for x in open(__lowercase ...
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'''simple docstring''' from typing import Any, Dict, Optional import torch import torch.nn.functional as F from torch import nn from ..utils import maybe_allow_in_graph from .activations import get_activation from .attention_processor import Attention from .embeddings import CombinedTimestepLa...
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'''simple docstring''' def SCREAMING_SNAKE_CASE( __lowercase , __lowercase = 0 ) -> list: A: Dict = length or len(__lowercase ) A: Dict = False for i in range(length - 1 ): if list_data[i] > list_data[i + 1]...
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'''simple docstring''' import argparse import os import shutil import torch from emmental.modules import MagnitudeBinarizer, ThresholdBinarizer, TopKBinarizer def SCREAMING_SNAKE_CASE( __lowercase ) -> Tuple: A: List[Any] = args.pruning_method A: ...
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'''simple docstring''' import argparse from collections import OrderedDict from pathlib import Path import torch from transformers import ( VisualBertConfig, VisualBertForMultipleChoice, VisualBertForPreTraining, VisualBertForQuestionAnswering, VisualBertForVisualReasonin...
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'''simple docstring''' import warnings from ...utils import logging from .image_processing_beit import BeitImageProcessor UpperCamelCase = logging.get_logger(__name__) class lowerCAmelCase_ ( UpperCAmelCase_ ): '''simple docstring''' def __...
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'''simple docstring''' from itertools import permutations def SCREAMING_SNAKE_CASE( __lowercase ) -> bool: if num[3] % 2 != 0: return False if (num[2] + num[3] + num[4]) % 3 != 0: return False if num[5] % 5 != 0: return False ...
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'''simple docstring''' from collections import OrderedDict from typing import Mapping from ...configuration_utils import PretrainedConfig from ...onnx import OnnxConfig from ...utils import logging UpperCamelCase = logging.get_logger(__name__) UpperCamelCase = { '''Yi...
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'''simple docstring''' import json import os from functools import lru_cache from typing import List, Optional, Tuple import regex as re from ...tokenization_utils import AddedToken, PreTrainedTokenizer from ...utils import logging UpperCamelCase = logging.get_logger(__name__) ...
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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''' def SCREAMING_SNAKE_CASE( __lowercase ) -> int: if not isinstance(__lowercase , __lowercase ): raise TypeError('''only integers accepted as input''' ) else: A: str = str(abs(__lowercase ) ...
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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, is_vision_available, ) UpperCamelCase = { ...
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'''simple docstring''' from __future__ import annotations import math def SCREAMING_SNAKE_CASE( __lowercase , __lowercase ) -> list: if len(__lowercase ) != 2 or len(a[0] ) != 2 or len(__lowercase ) != 2 or len(b[0] ) != 2: raise Excepti...
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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_tok...
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'''simple docstring''' from dataclasses import dataclass from typing import Optional, Tuple, Union import numpy as np import torch from ..configuration_utils import ConfigMixin, register_to_config from ..utils import BaseOutput, randn_tensor from .scheduling_utils import SchedulerMixin ...
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'''simple docstring''' import argparse import json from pathlib import Path import requests import torch from huggingface_hub import hf_hub_download from PIL import Image from transformers import ( BertTokenizer, ViltConfig, ViltForImageAndTextRetrieval, ViltForImagesAndTex...
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'''simple docstring''' import json import logging import math import os import sys from dataclasses import dataclass, field from typing import Optional from datasets import Dataset, load_dataset import transformers from transformers import ( CONFIG_MAPPING, MODEL_FOR_MASKED_LM_MAPP...
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'''simple docstring''' import argparse import shutil from pathlib import Path from tqdm import tqdm from transformers import AutoTokenizer def SCREAMING_SNAKE_CASE( __lowercase , __lowercase , __lowercase , __lowercase=1_0_2_4 ) -> Optional[in...
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'''simple docstring''' import json import os import unittest from typing import Tuple from transformers import WavaVecaPhonemeCTCTokenizer from transformers.models.wavaveca.tokenization_wavaveca import VOCAB_FILES_NAMES from transformers.models.wavaveca_phoneme.tokenization_wavaveca_phoneme impor...
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'''simple docstring''' import shutil import tempfile import unittest from transformers import SPIECE_UNDERLINE, BatchEncoding, MBartTokenizer, MBartTokenizerFast, is_torch_available from transformers.testing_utils import ( get_tests_dir, nested_simplify, require_sentencepiece, r...
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'''simple docstring''' import warnings from ...utils import logging from .image_processing_beit import BeitImageProcessor UpperCamelCase = logging.get_logger(__name__) class lowerCAmelCase_ ( UpperCAmelCase_ ): '''simple docstring''' def __...
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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,...
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'''simple docstring''' import os import pytest from transformers.dynamic_module_utils import get_imports UpperCamelCase = ''' import os ''' UpperCamelCase = ''' def foo(): import os return False ''' UpperCamelCase = ''' def foo(): def bar(): ...
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'''simple docstring''' import copy from typing import Dict, List, Optional from ...configuration_utils import PretrainedConfig from ...utils import logging from ..auto import CONFIG_MAPPING UpperCamelCase = { '''facebook/mask2former-swin-small-coco-instance''': ( '''http...
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'''simple docstring''' import argparse import json from pathlib import Path import requests import torch from huggingface_hub import hf_hub_download from PIL import Image from transformers import ( BertTokenizer, ViltConfig, ViltForImageAndTextRetrieval, ViltForImagesAndTex...
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'''simple docstring''' from .glue import GlueDataset, GlueDataTrainingArguments from .language_modeling import ( LineByLineTextDataset, LineByLineWithRefDataset, LineByLineWithSOPTextDataset, TextDataset, TextDatasetForNextSentencePrediction, ) from .squad import SquadDataset,...
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'''simple docstring''' import argparse import json import os import numpy as np import PIL import requests import tensorflow.keras.applications.efficientnet as efficientnet import torch from huggingface_hub import hf_hub_download from PIL import Image from tensorflow.keras.preprocessing impor...
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'''simple docstring''' import fire from utils import calculate_rouge, save_json def SCREAMING_SNAKE_CASE( __lowercase , __lowercase , __lowercase=None , **__lowercase ) -> Any: A: Any = [x.strip() for x in open(__lowercase ...
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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_focalnet''': ['''FOCALNET_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''FocalNetCon...
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'''simple docstring''' from typing import List, Optional, Union import numpy as np import tensorflow as tf from .utils import logging UpperCamelCase = logging.get_logger(__name__) def SCREAMING_SNAKE_CASE( __lowercase ) -> List[int]: if isinstance(__lowerca...
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'''simple docstring''' from typing import Any, Dict, List, Union from ..utils import add_end_docstrings, is_torch_available, is_vision_available, logging, requires_backends from .base import PIPELINE_INIT_ARGS, Pipeline if is_vision_available(): from ..image_utils import load_image if...
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'''simple docstring''' import secrets from random import shuffle from string import ascii_letters, ascii_lowercase, ascii_uppercase, digits, punctuation def SCREAMING_SNAKE_CASE( __lowercase = 8 ) -> str: A: Optional[int] = ascii_letters + digits + punctuation ...
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'''simple docstring''' from collections import OrderedDict from typing import Mapping from ...configuration_utils import PretrainedConfig from ...onnx import OnnxConfig from ...utils import logging UpperCamelCase = logging.get_logger(__name__) UpperCamelCase = { '''Yi...
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'''simple docstring''' def SCREAMING_SNAKE_CASE( __lowercase , __lowercase ) -> str: if not isinstance(__lowercase , __lowercase ): raise ValueError('''iterations must be defined as integers''' ) if not isinstance(__lowercase ,...
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'''simple docstring''' from __future__ import annotations def SCREAMING_SNAKE_CASE( __lowercase ) -> bool: if len(__lowercase ) < 2: raise ValueError('''Monogons and Digons are not polygons in the Euclidean space''' ) if any(i <= 0 for i in nums ): ...
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'''simple docstring''' import os import pytest from transformers.dynamic_module_utils import get_imports UpperCamelCase = ''' import os ''' UpperCamelCase = ''' def foo(): import os return False ''' UpperCamelCase = ''' def foo(): def bar(): ...
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'''simple docstring''' # tests directory-specific settings - this file is run automatically # by pytest before any tests are run import doctest import sys import warnings from os.path import abspath, dirname, join import _pytest from transformers.testing_utils import HfDoctestModule, HfDocTe...
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'''simple docstring''' import argparse from pathlib import Path import fairseq import torch from fairseq.models.xmod import XMODModel as FairseqXmodModel from packaging import version from transformers import XmodConfig, XmodForMaskedLM, XmodForSequenceClassification from transformers.utils im...
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'''simple docstring''' import heapq import sys import numpy as np UpperCamelCase = tuple[int, int] class lowerCAmelCase_ : '''simple docstring''' def __init__( self : List[Any] ) -> str: '''simple ...
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'''simple docstring''' from collections import OrderedDict from typing import Any, List, Mapping, Optional from ... import PreTrainedTokenizer, TensorType, is_torch_available from ...configuration_utils import PretrainedConfig from ...onnx import OnnxConfigWithPast, PatchingSpec from ...utils impo...
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'''simple docstring''' def SCREAMING_SNAKE_CASE( __lowercase = 1 , __lowercase = 1_0_0_0 ) -> int: A: Any = 1 A: Optional[Any] = 0 for divide_by_number in range(__lowercase , digit + 1 ): A: li...
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'''simple docstring''' from typing import TYPE_CHECKING from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available UpperCamelCase = { '''configuration_clipseg''': [ '''CLIPSEG_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''CLIPSegConfig''', ...
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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, ) UpperCamelCase = { '''configuration_vision_encoder_decoder''': ['''VisionEn...
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'''simple docstring''' from __future__ import annotations def SCREAMING_SNAKE_CASE( __lowercase , __lowercase , __lowercase , __lowercase , __lowercase , ) -> None: A: Any = len(__lowercase ) # If row...
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'''simple docstring''' import fire from utils import calculate_rouge, save_json def SCREAMING_SNAKE_CASE( __lowercase , __lowercase , __lowercase=None , **__lowercase ) -> Any: A: Any = [x.strip() for x in open(__lowercase ...
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'''simple docstring''' from __future__ import annotations import copy import tempfile import unittest from transformers import CONFIG_MAPPING, AutoConfig, BertConfig, GPTaConfig, TaConfig, TapasConfig, is_tf_available from transformers.testing_utils import ( DUMMY_UNKNOWN_IDENTIFIER, S...
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'''simple docstring''' def SCREAMING_SNAKE_CASE( __lowercase , __lowercase = 0 ) -> list: A: Dict = length or len(__lowercase ) A: Dict = False for i in range(length - 1 ): if list_data[i] > list_data[i + 1]...
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'''simple docstring''' import warnings from contextlib import contextmanager from ...processing_utils import ProcessorMixin from .feature_extraction_wavaveca import WavaVecaFeatureExtractor from .tokenization_wavaveca import WavaVecaCTCTokenizer class lowerCAmelCase_ ( UpperCA...
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'''simple docstring''' import argparse from collections import OrderedDict from pathlib import Path import torch from transformers import ( VisualBertConfig, VisualBertForMultipleChoice, VisualBertForPreTraining, VisualBertForQuestionAnswering, VisualBertForVisualReasonin...
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'''simple docstring''' import inspect import os import unittest import torch import accelerate from accelerate import Accelerator from accelerate.test_utils import execute_subprocess_async, require_multi_gpu from accelerate.utils import patch_environment class lowerCAmelCase_ ...
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'''simple docstring''' from itertools import permutations def SCREAMING_SNAKE_CASE( __lowercase ) -> bool: if num[3] % 2 != 0: return False if (num[2] + num[3] + num[4]) % 3 != 0: return False if num[5] % 5 != 0: return False ...
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'''simple docstring''' # coding=utf-8 # Copyright 2023 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/...
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'''simple docstring''' import json import os from functools import lru_cache from typing import List, Optional, Tuple import regex as re from ...tokenization_utils import AddedToken, PreTrainedTokenizer from ...utils import logging UpperCamelCase = logging.get_logger(__name__) ...
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'''simple docstring''' import pickle import numpy as np from matplotlib import pyplot as plt class lowerCAmelCase_ : '''simple docstring''' def __init__( self : int , SCREAMING_SNAKE_CASE_ : List[str] , SCREAMING_SNAKE_CASE_ : ...
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'''simple docstring''' def SCREAMING_SNAKE_CASE( __lowercase ) -> int: if not isinstance(__lowercase , __lowercase ): raise TypeError('''only integers accepted as input''' ) else: A: str = str(abs(__lowercase ) ...
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'''simple docstring''' def SCREAMING_SNAKE_CASE( __lowercase ) -> int: assert ( isinstance(__lowercase , __lowercase ) and number_of_steps > 0 ), F"""number_of_steps needs to be positive integer, your input {number_of_steps}""" if number_of_s...
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'''simple docstring''' from __future__ import annotations import math def SCREAMING_SNAKE_CASE( __lowercase , __lowercase ) -> list: if len(__lowercase ) != 2 or len(a[0] ) != 2 or len(__lowercase ) != 2 or len(b[0] ) != 2: raise Excepti...
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'''simple docstring''' class lowerCAmelCase_ : '''simple docstring''' def __init__( self : int , SCREAMING_SNAKE_CASE_ : list ) -> None: '''simple docstring''' A: Any = set_counts ...
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'''simple docstring''' from dataclasses import dataclass from typing import Optional, Tuple, Union import numpy as np import torch from ..configuration_utils import ConfigMixin, register_to_config from ..utils import BaseOutput, randn_tensor from .scheduling_utils import SchedulerMixin ...
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'''simple docstring''' from typing import TYPE_CHECKING from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available UpperCamelCase = { '''configuration_upernet''': ['''UperNetConfig'''], } try: if not is_torch_available(): raise Optional...
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'''simple docstring''' import json import logging import math import os import sys from dataclasses import dataclass, field from typing import Optional from datasets import Dataset, load_dataset import transformers from transformers import ( CONFIG_MAPPING, MODEL_FOR_MASKED_LM_MAPP...
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'''simple docstring''' from ..utils import DummyObject, requires_backends class lowerCAmelCase_ ( metaclass=UpperCAmelCase_ ): '''simple docstring''' UpperCamelCase_ : Optional[Any] = ["""torch"""] def __init__( self ...
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'''simple docstring''' import json import os import unittest from typing import Tuple from transformers import WavaVecaPhonemeCTCTokenizer from transformers.models.wavaveca.tokenization_wavaveca import VOCAB_FILES_NAMES from transformers.models.wavaveca_phoneme.tokenization_wavaveca_phoneme impor...
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'''simple docstring''' def SCREAMING_SNAKE_CASE( __lowercase , __lowercase ) -> Union[str, Any]: print('''\nThe shortest path matrix using Floyd Warshall algorithm\n''' ) for i in range(__lowercase ): for j in range(__lowercase ): ...
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'''simple docstring''' import warnings from ...utils import logging from .image_processing_beit import BeitImageProcessor UpperCamelCase = logging.get_logger(__name__) class lowerCAmelCase_ ( UpperCAmelCase_ ): '''simple docstring''' def __...
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'''simple docstring''' import gc import tempfile import unittest import numpy as np import torch from diffusers import VersatileDiffusionPipeline from diffusers.utils.testing_utils import load_image, nightly, require_torch_gpu, torch_device UpperCamelCase = False clas...
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'''simple docstring''' import os import pytest from transformers.dynamic_module_utils import get_imports UpperCamelCase = ''' import os ''' UpperCamelCase = ''' def foo(): import os return False ''' UpperCamelCase = ''' def foo(): def bar(): ...
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'''simple docstring''' import datasets UpperCamelCase = '''\ @InProceedings{conneau2018xnli, author = "Conneau, Alexis and Rinott, Ruty and Lample, Guillaume and Williams, Adina and Bowman, Samuel R. and ...
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'''simple docstring''' import argparse import json from pathlib import Path import requests import torch from huggingface_hub import hf_hub_download from PIL import Image from transformers import ( BertTokenizer, ViltConfig, ViltForImageAndTextRetrieval, ViltForImagesAndTex...
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'''simple docstring''' import unittest from datasets import load_dataset from transformers.pipelines import pipeline from transformers.testing_utils import is_pipeline_test, nested_simplify, require_torch, slow @is_pipeline_test @require_torch class lowerCAmelCase_ ( unitte...
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'''simple docstring''' import argparse import json import os import numpy as np import PIL import requests import tensorflow.keras.applications.efficientnet as efficientnet import torch from huggingface_hub import hf_hub_download from PIL import Image from tensorflow.keras.preprocessing impor...
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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, ) UpperCamelCase = { '''configuration_vision_encoder_decoder''': ['''VisionEn...
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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_focalnet''': ['''FOCALNET_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''FocalNetCon...
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'''simple docstring''' import os import re import shutil from argparse import ArgumentParser, Namespace from datasets.commands import BaseDatasetsCLICommand from datasets.utils.logging import get_logger UpperCamelCase = '''<<<<<<< This should probably be modified because it mentions:...
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'''simple docstring''' from typing import Any, Dict, List, Union from ..utils import add_end_docstrings, is_torch_available, is_vision_available, logging, requires_backends from .base import PIPELINE_INIT_ARGS, Pipeline if is_vision_available(): from ..image_utils import load_image if...
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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, AutoModelForP...
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'''simple docstring''' from collections import OrderedDict from typing import Mapping from ...configuration_utils import PretrainedConfig from ...onnx import OnnxConfig from ...utils import logging UpperCamelCase = logging.get_logger(__name__) UpperCamelCase = { '''Yi...
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'''simple docstring''' import torch from torch import nn from ...configuration_utils import ConfigMixin, register_to_config from ...models import ModelMixin class lowerCAmelCase_ ( UpperCAmelCase_ , UpperCAmelCase_ ): '''simple docstring''' @register...
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'''simple docstring''' from __future__ import annotations def SCREAMING_SNAKE_CASE( __lowercase ) -> bool: if len(__lowercase ) < 2: raise ValueError('''Monogons and Digons are not polygons in the Euclidean space''' ) if any(i <= 0 for i in nums ): ...
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'''simple docstring''' from typing import TYPE_CHECKING from ...utils import ( OptionalDependencyNotAvailable, _LazyModule, is_torch_available, ) UpperCamelCase = { '''configuration_encodec''': [ '''ENCODEC_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''Encod...
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'''simple docstring''' # tests directory-specific settings - this file is run automatically # by pytest before any tests are run import doctest import sys import warnings from os.path import abspath, dirname, join import _pytest from transformers.testing_utils import HfDoctestModule, HfDocTe...
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'''simple docstring''' import argparse import json from pathlib import Path import requests import torch from huggingface_hub import hf_hub_download from PIL import Image from transformers import ViTConfig, ViTForImageClassification, ViTImageProcessor, ViTModel from transformers.utils import ...
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'''simple docstring''' import heapq import sys import numpy as np UpperCamelCase = tuple[int, int] class lowerCAmelCase_ : '''simple docstring''' def __init__( self : List[Any] ) -> str: '''simple ...
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'''simple docstring''' import os import random import sys from . import cryptomath_module as cryptomath from . import rabin_miller UpperCamelCase = 3 def SCREAMING_SNAKE_CASE( __lowercase ) -> int: print('''Generating primitive root of p''' ) while T...
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'''simple docstring''' def SCREAMING_SNAKE_CASE( __lowercase = 1 , __lowercase = 1_0_0_0 ) -> int: A: Any = 1 A: Optional[Any] = 0 for divide_by_number in range(__lowercase , digit + 1 ): A: li...
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'''simple docstring''' import inspect import tempfile from collections import OrderedDict, UserDict from collections.abc import MutableMapping from contextlib import ExitStack, contextmanager from dataclasses import fields from enum import Enum from typing import Any, ContextManager, List, Tuple ...
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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, ) UpperCamelCase = { '''configuration_vision_encoder_decoder''': ['''VisionEn...
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'''simple docstring''' import os from collections.abc import Iterator def SCREAMING_SNAKE_CASE( __lowercase = "." ) -> Iterator[str]: for dir_path, dir_names, filenames in os.walk(__lowercase ): A: Tuple = [d for d in dir_names if d != '''scripts'...
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'''simple docstring''' import fire from utils import calculate_rouge, save_json def SCREAMING_SNAKE_CASE( __lowercase , __lowercase , __lowercase=None , **__lowercase ) -> Any: A: Any = [x.strip() for x in open(__lowercase ...
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'''simple docstring''' import time import unittest from transformers import is_torch_available from transformers.testing_utils import require_torch, torch_device from ..test_modeling_common import ids_tensor if is_torch_available(): import torch from transformers.generation imp...
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'''simple docstring''' def SCREAMING_SNAKE_CASE( __lowercase , __lowercase = 0 ) -> list: A: Dict = length or len(__lowercase ) A: Dict = False for i in range(length - 1 ): if list_data[i] > list_data[i + 1]...
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'''simple docstring''' from typing import TYPE_CHECKING from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available UpperCamelCase = {'''configuration_vit_msn''': ['''VIT_MSN_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''ViTMSNConfig''']} try: if not is_torch_ava...
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'''simple docstring''' import argparse from collections import OrderedDict from pathlib import Path import torch from transformers import ( VisualBertConfig, VisualBertForMultipleChoice, VisualBertForPreTraining, VisualBertForQuestionAnswering, VisualBertForVisualReasonin...
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'''simple docstring''' def SCREAMING_SNAKE_CASE( __lowercase , __lowercase ) -> int: return int((input_a, input_a).count(1 ) != 0 ) def SCREAMING_SNAKE_CASE( ) -> None: assert or_gate(0 , 0 ) == 0 assert or_gate(0 ...
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'''simple docstring''' from itertools import permutations def SCREAMING_SNAKE_CASE( __lowercase ) -> bool: if num[3] % 2 != 0: return False if (num[2] + num[3] + num[4]) % 3 != 0: return False if num[5] % 5 != 0: return False ...
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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, ) UpperCamelCase = { '''configuration_blenderbo...
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'''simple docstring''' import json import os from functools import lru_cache from typing import List, Optional, Tuple import regex as re from ...tokenization_utils import AddedToken, PreTrainedTokenizer from ...utils import logging UpperCamelCase = logging.get_logger(__name__) ...
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'''simple docstring''' from ...processing_utils import ProcessorMixin from ...tokenization_utils_base import BatchEncoding class lowerCAmelCase_ ( UpperCAmelCase_ ): '''simple docstring''' UpperCamelCase_ : Union[str, Any] = """ClapFea...
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'''simple docstring''' def SCREAMING_SNAKE_CASE( __lowercase ) -> int: if not isinstance(__lowercase , __lowercase ): raise TypeError('''only integers accepted as input''' ) else: A: str = str(abs(__lowercase ) ...
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'''simple docstring''' import json import os import shutil import tempfile from unittest import TestCase from transformers import BartTokenizer, BartTokenizerFast, DPRQuestionEncoderTokenizer, DPRQuestionEncoderTokenizerFast from transformers.models.bart.configuration_bart import BartConfig from...
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'''simple docstring''' from __future__ import annotations import math def SCREAMING_SNAKE_CASE( __lowercase , __lowercase ) -> list: if len(__lowercase ) != 2 or len(a[0] ) != 2 or len(__lowercase ) != 2 or len(b[0] ) != 2: raise Excepti...
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'''simple docstring''' import copy from dataclasses import dataclass, field from typing import ClassVar, Dict from ..features import ClassLabel, Features, Value from .base import TaskTemplate @dataclass(frozen=UpperCAmelCase_ ) class lowerCAmelCase_ ( UpperCAmelCase_ ):...
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'''simple docstring''' from dataclasses import dataclass from typing import Optional, Tuple, Union import numpy as np import torch from ..configuration_utils import ConfigMixin, register_to_config from ..utils import BaseOutput, randn_tensor from .scheduling_utils import SchedulerMixin ...
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'''simple docstring''' # We ignore warnings about stepping the scheduler since we step it ourselves during gradient accumulation import warnings from .state import AcceleratorState, GradientState warnings.filterwarnings('''ignore''', category=UserWarning, module='''torch.optim.lr_scheduler''')...
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'''simple docstring''' import json import logging import math import os import sys from dataclasses import dataclass, field from typing import Optional from datasets import Dataset, load_dataset import transformers from transformers import ( CONFIG_MAPPING, MODEL_FOR_MASKED_LM_MAPP...
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'''simple docstring''' import argparse import pathlib import fairseq import torch from fairseq.models.roberta import RobertaModel as FairseqRobertaModel from fairseq.modules import TransformerSentenceEncoderLayer from packaging import version from transformers import XLMRobertaConfig, XLMRober...
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'''simple docstring''' import json import os import unittest from typing import Tuple from transformers import WavaVecaPhonemeCTCTokenizer from transformers.models.wavaveca.tokenization_wavaveca import VOCAB_FILES_NAMES from transformers.models.wavaveca_phoneme.tokenization_wavaveca_phoneme impor...
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'''simple docstring''' from __future__ import annotations import numpy as np from numpy import floataa from numpy.typing import NDArray def SCREAMING_SNAKE_CASE( __lowercase , __lowercase , __lowercase , __lowercase , ) -> list[float]: ...
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'''simple docstring''' import warnings from ...utils import logging from .image_processing_beit import BeitImageProcessor UpperCamelCase = logging.get_logger(__name__) class lowerCAmelCase_ ( UpperCAmelCase_ ): '''simple docstring''' def __...
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'''simple docstring''' import os import textwrap import pyarrow as pa import pytest from datasets import ClassLabel, Features, Image from datasets.packaged_modules.csv.csv import Csv from ..utils import require_pil @pytest.fixture def SCREAMING_SNAKE_CASE( __lowercase ) -> ...
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'''simple docstring''' import os import pytest from transformers.dynamic_module_utils import get_imports UpperCamelCase = ''' import os ''' UpperCamelCase = ''' def foo(): import os return False ''' UpperCamelCase = ''' def foo(): def bar(): ...
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'''simple docstring''' import math import unittest def SCREAMING_SNAKE_CASE( __lowercase ) -> bool: assert isinstance(__lowercase , __lowercase ) and ( number >= 0 ), "'number' must been an int and positive" if 1 < number < 4: ...
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'''simple docstring''' import argparse import json from pathlib import Path import requests import torch from huggingface_hub import hf_hub_download from PIL import Image from transformers import ( BertTokenizer, ViltConfig, ViltForImageAndTextRetrieval, ViltForImagesAndTex...
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'''simple docstring''' from typing import List, Optional, Union import torch from transformers import ( XLMRobertaTokenizer, ) from ...models import UNetaDConditionModel, VQModel from ...pipelines import DiffusionPipeline from ...pipelines.pipeline_utils import ImagePipelineOutput from .....
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'''simple docstring''' import argparse import json import os import numpy as np import PIL import requests import tensorflow.keras.applications.efficientnet as efficientnet import torch from huggingface_hub import hf_hub_download from PIL import Image from tensorflow.keras.preprocessing impor...
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'''simple docstring''' import unittest from transformers import load_tool from .test_tools_common import ToolTesterMixin UpperCamelCase = ''' Hugging Face was founded in 2016 by French entrepreneurs Clément Delangue, Julien Chaumond, and Thomas Wolf originally as a company that develo...
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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_focalnet''': ['''FOCALNET_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''FocalNetCon...
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'''simple docstring''' def SCREAMING_SNAKE_CASE( __lowercase ) -> str: A: Optional[Any] = 0 # if input_string is "aba" than new_input_string become "a|b|a" A: Tuple = '''''' A: Optional[Any] = '''''' # appe...
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'''simple docstring''' from typing import Any, Dict, List, Union from ..utils import add_end_docstrings, is_torch_available, is_vision_available, logging, requires_backends from .base import PIPELINE_INIT_ARGS, Pipeline if is_vision_available(): from ..image_utils import load_image if...
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'''simple docstring''' from itertools import permutations def SCREAMING_SNAKE_CASE( __lowercase ) -> bool: if num[3] % 2 != 0: return False if (num[2] + num[3] + num[4]) % 3 != 0: return False if num[5] % 5 != 0: return False ...
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'''simple docstring''' from collections import OrderedDict from typing import Mapping from ...configuration_utils import PretrainedConfig from ...onnx import OnnxConfig from ...utils import logging UpperCamelCase = logging.get_logger(__name__) UpperCamelCase = { '''Yi...
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'''simple docstring''' import argparse import os import sys from unittest.mock import patch import pytorch_lightning as pl import timeout_decorator import torch from distillation import SummarizationDistiller, distill_main from finetune import SummarizationModule, main from transformers impo...
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'''simple docstring''' from __future__ import annotations def SCREAMING_SNAKE_CASE( __lowercase ) -> bool: if len(__lowercase ) < 2: raise ValueError('''Monogons and Digons are not polygons in the Euclidean space''' ) if any(i <= 0 for i in nums ): ...
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'''simple docstring''' import json import os import unittest from transformers.models.roc_bert.tokenization_roc_bert import ( VOCAB_FILES_NAMES, RoCBertBasicTokenizer, RoCBertTokenizer, RoCBertWordpieceTokenizer, _is_control, _is_punctuation, _is_whitespace, ) fr...
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'''simple docstring''' # tests directory-specific settings - this file is run automatically # by pytest before any tests are run import doctest import sys import warnings from os.path import abspath, dirname, join import _pytest from transformers.testing_utils import HfDoctestModule, HfDocTe...
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'''simple docstring''' import argparse import json from pathlib import Path import requests import timm import torch from huggingface_hub import hf_hub_download from PIL import Image from transformers import DeiTConfig, DeiTForImageClassificationWithTeacher, DeiTImageProcessor from transform...
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'''simple docstring''' import heapq import sys import numpy as np UpperCamelCase = tuple[int, int] class lowerCAmelCase_ : '''simple docstring''' def __init__( self : List[Any] ) -> str: '''simple ...
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'''simple docstring''' import logging import os from dataclasses import dataclass from typing import List, Optional, Union import tqdm from filelock import FileLock from transformers import ( BartTokenizer, BartTokenizerFast, DataProcessor, PreTrainedTokenizer, RobertaT...
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'''simple docstring''' def SCREAMING_SNAKE_CASE( __lowercase = 1 , __lowercase = 1_0_0_0 ) -> int: A: Any = 1 A: Optional[Any] = 0 for divide_by_number in range(__lowercase , digit + 1 ): A: li...
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'''simple docstring''' def SCREAMING_SNAKE_CASE( __lowercase , __lowercase , __lowercase ) -> int: def count_of_possible_combinations(__lowercase ) -> int: if target < 0: return 0 if target == 0: r...
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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, ) UpperCamelCase = { '''configuration_vision_encoder_decoder''': ['''VisionEn...
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