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'''simple docstring''' from __future__ import annotations import unittest from transformers import XGLMConfig, XGLMTokenizer, is_tf_available from transformers.testing_utils import require_tf, slow from ...test_configuration_common import ConfigTester from ...test_modeling_tf_common im...
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'''simple docstring''' from dataclasses import asdict, dataclass from typing import Optional from ...configuration_utils import PretrainedConfig from ...utils import logging __lowerCamelCase : Dict = logging.get_logger(__name__) # TODO Update this __lowerCamelCase : ...
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'''simple docstring''' import os from shutil import copyfile from typing import List, Optional, Tuple from ...tokenization_utils import AddedToken from ...tokenization_utils_fast import PreTrainedTokenizerFast from ...utils import is_sentencepiece_available, logging if is_sentencepiec...
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'''simple docstring''' from typing import TYPE_CHECKING from ...utils import ( OptionalDependencyNotAvailable, _LazyModule, is_tf_available, is_tokenizers_available, is_torch_available, ) __lowerCamelCase : Any = { '''configuration_longformer...
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'''simple docstring''' from collections import deque from .hash_table import HashTable class A_ (a_ ): """simple docstring""" def __init__( self :List[str] , *lowerCAmelCase__ :Optional[Any] , **lowerCAmelCase__ ...
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'''simple docstring''' import inspect import tempfile import unittest from huggingface_hub import hf_hub_download from transformers import is_torch_available from transformers.testing_utils import is_flaky, require_torch, slow, torch_device from ...test_configuration_common import Con...
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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 A_ : """simple docstring""" ...
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'''simple docstring''' import itertools import json import os import unittest from transformers import AddedToken, RobertaTokenizer, RobertaTokenizerFast from transformers.models.roberta.tokenization_roberta import VOCAB_FILES_NAMES from transformers.testing_utils import require_tokenizer...
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'''simple docstring''' import copy import unittest from transformers.models.auto import get_values from transformers.testing_utils import require_torch, slow, torch_device from transformers.utils import cached_property, is_torch_available, is_vision_available from ...test_configuration_c...
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'''simple docstring''' import math def __UpperCAmelCase ( __magic_name__ )-> bool: """simple docstring""" snake_case_ : Optional[int] = math.loga(math.sqrt(4 * positive_integer + 1 ) / 2 + 1 / 2 ) return exponent == int(__mag...
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'''simple docstring''' def __UpperCAmelCase ( )-> str: """simple docstring""" snake_case_ : str = [] snake_case_ : List[Any] = 1 while len(__magic_name__ ) < 1E6: constant.append(str(__magic_name__ ) )...
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'''simple docstring''' import argparse import json from dataclasses import dataclass, field from functools import partial from pathlib import Path from typing import List import timm import torch import torch.nn as nn from huggingface_hub import hf_hub_download from torch import Tenso...
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'''simple docstring''' from ...configuration_utils import PretrainedConfig from ...utils import logging __lowerCamelCase : Dict = logging.get_logger(__name__) __lowerCamelCase : str = { '''RWKV/rwkv-4-169m-pile''': '''https://huggingface.co/RWKV/rwkv-...
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'''simple docstring''' from ...configuration_utils import PretrainedConfig from ...utils import logging __lowerCamelCase : List[Any] = logging.get_logger(__name__) __lowerCamelCase : Dict = { '''weiweishi/roc-bert-base-zh''': '''https://huggingface.co...
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'''simple docstring''' import inspect import os import unittest import torch import accelerate from accelerate import debug_launcher from accelerate.test_utils import ( execute_subprocess_async, require_cpu, require_huggingface_suite, require_multi_gpu, require_...
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'''simple docstring''' def __UpperCAmelCase ( __magic_name__ ,__magic_name__ ,__magic_name__ )-> int: """simple docstring""" def update_area_of_max_square(__magic_name__ ,__magic_name__ ) -> int: # BASE CASE if row >= rows or col >= col...
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'''simple docstring''' from string import ascii_uppercase __lowerCamelCase : Optional[Any] = {char: i for i, char in enumerate(ascii_uppercase)} __lowerCamelCase : List[str] = dict(enumerate(ascii_uppercase)) def __UpperCAmelCase ( __magic_name...
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'''simple docstring''' import os import zipfile import requests from get_ci_error_statistics import download_artifact, get_artifacts_links def __UpperCAmelCase ( __magic_name__ ,__magic_name__=7 )-> Tuple: """simple docstring""" snake_case_ : ...
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'''simple docstring''' import logging import os import sys from dataclasses import dataclass, field from typing import Optional from seqaseq_trainer import SeqaSeqTrainer from seqaseq_training_args import SeqaSeqTrainingArguments import transformers from transformers import ( Aut...
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'''simple docstring''' from string import ascii_uppercase __lowerCamelCase : Optional[Any] = {char: i for i, char in enumerate(ascii_uppercase)} __lowerCamelCase : List[str] = dict(enumerate(ascii_uppercase)) def __UpperCAmelCase ( __magic_name...
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'''simple docstring''' import unittest from transformers import AlbertTokenizer, AlbertTokenizerFast from transformers.testing_utils import get_tests_dir, require_sentencepiece, require_tokenizers, slow from ...test_tokenization_common import TokenizerTesterMixin __lowerCamelCase : ...
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'''simple docstring''' import argparse import os import numpy as np import tensorflow as tf import torch from transformers import BertModel def __UpperCAmelCase ( __magic_name__ ,__magic_name__ ,__magic_name__ )-> Dict: """simple docstring""" ...
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'''simple docstring''' import warnings from ...utils import logging from .image_processing_clip import CLIPImageProcessor __lowerCamelCase : Optional[Any] = logging.get_logger(__name__) class A_ (a_ ): """simple docstring""" ...
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'''simple docstring''' from collections import deque from .hash_table import HashTable class A_ (a_ ): """simple docstring""" def __init__( self :List[str] , *lowerCAmelCase__ :Optional[Any] , **lowerCAmelCase__ ...
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'''simple docstring''' from dataclasses import dataclass, field from typing import Tuple from ..utils import cached_property, is_torch_available, is_torch_tpu_available, logging, requires_backends from .benchmark_args_utils import BenchmarkArguments if is_torch_available(): import to...
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'''simple docstring''' from collections.abc import Iterator, MutableMapping from dataclasses import dataclass from typing import Generic, TypeVar __lowerCamelCase : Dict = TypeVar('''KEY''') __lowerCamelCase : int = TypeVar('''VAL''') @dataclas...
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'''simple docstring''' from ....configuration_utils import PretrainedConfig from ....utils import logging __lowerCamelCase : Tuple = logging.get_logger(__name__) __lowerCamelCase : Dict = { '''Visual-Attention-Network/van-base''': ( '''https:...
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'''simple docstring''' from ...configuration_utils import PretrainedConfig from ...utils import logging __lowerCamelCase : str = logging.get_logger(__name__) __lowerCamelCase : Tuple = { '''bigcode/gpt_bigcode-santacoder''': '''https://huggingface.co/...
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'''simple docstring''' import gc import random import unittest import numpy as np import torch from PIL import Image from transformers import CLIPTextConfig, CLIPTextModel, CLIPTokenizer from diffusers import ( AutoencoderKL, DDIMScheduler, EulerAncestralDiscreteSchedule...
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'''simple docstring''' import json import logging import os import socket import git import numpy as np import torch logging.basicConfig( format='''%(asctime)s - %(levelname)s - %(name)s - PID: %(process)d - %(message)s''', datefmt='''%m/%d/%Y %H:%M:%S''', level=loggi...
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'''simple docstring''' def __UpperCAmelCase ( __magic_name__ ,__magic_name__ ,__magic_name__ ,__magic_name__ )-> Dict: """simple docstring""" if height >= 1: move_tower(height - 1 ,__magic_name__ ,__magic_name__ ,__magic_name__ ) mov...
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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 ImageProce...
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'''simple docstring''' import json import os from typing import Dict, List, Optional, Tuple import regex as re from ...tokenization_utils import PreTrainedTokenizer from ...utils import logging __lowerCamelCase : Dict = logging.get_logger(__name__) __lowerCamelC...
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'''simple docstring''' def __UpperCAmelCase ( __magic_name__ ,__magic_name__ )-> str: """simple docstring""" if not isinstance(__magic_name__ ,__magic_name__ ): raise ValueError("iterations must be defined as integers" ) if not isinstanc...
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'''simple docstring''' from typing import TYPE_CHECKING from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available __lowerCamelCase : Union[str, Any] = { '''configuration_git''': ['''GIT_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''GitConfig''', '''G...
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'''simple docstring''' import argparse import os # New Code # import evaluate import torch from datasets import load_dataset from torch.optim import AdamW from torch.utils.data import DataLoader from transformers import AutoModelForSequenceClassification, AutoTokenizer, get_linear_sched...
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'''simple docstring''' import logging import sys from dataclasses import dataclass, field from typing import Any, Dict, List, Optional, Union import librosa import torch from datasets import DatasetDict, load_dataset from packaging import version from torch import nn from transformer...
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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....
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'''simple docstring''' import json from typing import Dict, List, Optional, Tuple, Union from tokenizers import pre_tokenizers, processors from ...tokenization_utils_base import AddedToken, BatchEncoding, EncodedInput from ...tokenization_utils_fast import PreTrainedTokenizerFast from .....
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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, is_vision_available, ) __lowerCamelCase : Any = {'''configurat...
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'''simple docstring''' from dataclasses import dataclass, field from typing import Tuple from ..utils import cached_property, is_tf_available, logging, requires_backends from .benchmark_args_utils import BenchmarkArguments if is_tf_available(): import tensorflow as tf __lowerCam...
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'''simple docstring''' import copy import unittest from transformers.models.auto import get_values from transformers.testing_utils import require_torch, slow, torch_device from transformers.utils import cached_property, is_torch_available, is_vision_available from ...test_configuration_c...
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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 __lowerCamelCase : List[str] = { '''configuration_informer''': [ '''INFORMER_PRE...
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'''simple docstring''' import pytest from datasets.parallel import ParallelBackendConfig, parallel_backend from datasets.utils.py_utils import map_nested from .utils import require_dill_gt_0_3_2, require_joblibspark, require_not_windows def __UpperCAmelCase ( __magic_name_...
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'''simple docstring''' def __UpperCAmelCase ( __magic_name__ ,__magic_name__ ,__magic_name__ )-> list: """simple docstring""" snake_case_ : Optional[Any] = len(__magic_name__ ) snake_case_ : Tuple = [[0] * n for i i...
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'''simple docstring''' from dataclasses import asdict, dataclass from typing import Optional from ...configuration_utils import PretrainedConfig from ...utils import logging __lowerCamelCase : Dict = logging.get_logger(__name__) # TODO Update this __lowerCamelCase : ...
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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 :...
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'''simple docstring''' from typing import TYPE_CHECKING from ...utils import ( OptionalDependencyNotAvailable, _LazyModule, is_tf_available, is_tokenizers_available, is_torch_available, ) __lowerCamelCase : Any = { '''configuration_longformer...
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'''simple docstring''' import unittest from transformers import GPTNeoXJapaneseConfig, is_torch_available from transformers.models.gpt_neox_japanese.tokenization_gpt_neox_japanese import GPTNeoXJapaneseTokenizer from transformers.testing_utils import require_torch, slow, torch_device from...
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'''simple docstring''' import inspect import tempfile import unittest from huggingface_hub import hf_hub_download from transformers import is_torch_available from transformers.testing_utils import is_flaky, require_torch, slow, torch_device from ...test_configuration_common import Con...
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'''simple docstring''' from transformers import HfArgumentParser, TensorFlowBenchmark, TensorFlowBenchmarkArguments def __UpperCAmelCase ( )-> Any: """simple docstring""" snake_case_ : Optional[Any] = HfArgumentParser(__magic_name__ ) ...
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'''simple docstring''' import itertools import json import os import unittest from transformers import AddedToken, RobertaTokenizer, RobertaTokenizerFast from transformers.models.roberta.tokenization_roberta import VOCAB_FILES_NAMES from transformers.testing_utils import require_tokenizer...
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'''simple docstring''' __lowerCamelCase : Optional[int] = '''ABCDEFGHIJKLMNOPQRSTUVWXYZabcdefghijklmnopqrstuvwxyz0123456789+/''' def __UpperCAmelCase ( __magic_name__ )-> bytes: """simple docstring""" if not isinstance(__magic_name__ ,_...
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'''simple docstring''' import math def __UpperCAmelCase ( __magic_name__ )-> bool: """simple docstring""" snake_case_ : Optional[int] = math.loga(math.sqrt(4 * positive_integer + 1 ) / 2 + 1 / 2 ) return exponent == int(__mag...
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'''simple docstring''' import importlib import shutil import threading import warnings from typing import List import fsspec import fsspec.asyn from . import compression from .hffilesystem import HfFileSystem __lowerCamelCase : Tuple = importlib.util.find_spec('''...
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'''simple docstring''' import argparse import json from dataclasses import dataclass, field from functools import partial from pathlib import Path from typing import List import timm import torch import torch.nn as nn from huggingface_hub import hf_hub_download from torch import Tenso...
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'''simple docstring''' import os from shutil import copyfile from typing import List, Optional, Tuple from tokenizers import processors from ...tokenization_utils import AddedToken, BatchEncoding from ...tokenization_utils_fast import PreTrainedTokenizerFast from ...utils import is_sent...
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'''simple docstring''' from ...configuration_utils import PretrainedConfig from ...utils import logging __lowerCamelCase : List[Any] = logging.get_logger(__name__) __lowerCamelCase : Dict = { '''weiweishi/roc-bert-base-zh''': '''https://huggingface.co...
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'''simple docstring''' import os from shutil import copyfile from typing import Any, Dict, List, Optional, Tuple import sentencepiece as spm from ...tokenization_utils import PreTrainedTokenizer from ...utils import logging __lowerCamelCase : Any = logging.get_logger...
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'''simple docstring''' def __UpperCAmelCase ( __magic_name__ ,__magic_name__ ,__magic_name__ )-> int: """simple docstring""" def update_area_of_max_square(__magic_name__ ,__magic_name__ ) -> int: # BASE CASE if row >= rows or col >= col...
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'''simple docstring''' import argparse import math import traceback import dateutil.parser as date_parser import requests def __UpperCAmelCase ( __magic_name__ )-> List[str]: """simple docstring""" snake_case_ : List[str] = {} ...
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'''simple docstring''' import os import zipfile import requests from get_ci_error_statistics import download_artifact, get_artifacts_links def __UpperCAmelCase ( __magic_name__ ,__magic_name__=7 )-> Tuple: """simple docstring""" snake_case_ : ...
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'''simple docstring''' import gc import random import unittest import numpy as np import torch from PIL import Image from transformers import XLMRobertaTokenizerFast from diffusers import DDIMScheduler, KandinskyInpaintPipeline, KandinskyPriorPipeline, UNetaDConditionModel, VQModel fr...
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'''simple docstring''' from string import ascii_uppercase __lowerCamelCase : Optional[Any] = {char: i for i, char in enumerate(ascii_uppercase)} __lowerCamelCase : List[str] = dict(enumerate(ascii_uppercase)) def __UpperCAmelCase ( __magic_name...
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'''simple docstring''' import json import os import shutil import tempfile import unittest import numpy as np import pytest from transformers import CLIPTokenizer, CLIPTokenizerFast from transformers.models.clip.tokenization_clip import VOCAB_FILES_NAMES from transformers.testing_uti...
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'''simple docstring''' import argparse import os import numpy as np import tensorflow as tf import torch from transformers import BertModel def __UpperCAmelCase ( __magic_name__ ,__magic_name__ ,__magic_name__ )-> Dict: """simple docstring""" ...
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'''simple docstring''' from typing import TYPE_CHECKING from ..utils import _LazyModule __lowerCamelCase : Tuple = { '''config''': [ '''EXTERNAL_DATA_FORMAT_SIZE_LIMIT''', '''OnnxConfig''', '''OnnxConfigWithPast''', '''OnnxSeq2SeqCo...
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'''simple docstring''' from collections import deque from .hash_table import HashTable class A_ (a_ ): """simple docstring""" def __init__( self :List[str] , *lowerCAmelCase__ :Optional[Any] , **lowerCAmelCase__ ...
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'''simple docstring''' import requests from bsa import BeautifulSoup def __UpperCAmelCase ( __magic_name__ = "https://www.worldometers.info/coronavirus" )-> dict: """simple docstring""" snake_case_ : List[Any] = BeautifulSoup(requests.g...
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'''simple docstring''' from collections.abc import Iterator, MutableMapping from dataclasses import dataclass from typing import Generic, TypeVar __lowerCamelCase : Dict = TypeVar('''KEY''') __lowerCamelCase : int = TypeVar('''VAL''') @dataclas...
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'''simple docstring''' import numpy as np __lowerCamelCase : Dict = [ ['''a''', '''b''', '''c''', '''d''', '''e'''], ['''f''', '''g''', '''h''', '''i''', '''k'''], ['''l''', '''m''', '''n''', '''o''', '''p'''], ['''q''', '''r''', '''s''', '''t''', '''u'''], ...
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'''simple docstring''' from ...configuration_utils import PretrainedConfig from ...utils import logging __lowerCamelCase : str = logging.get_logger(__name__) __lowerCamelCase : Tuple = { '''bigcode/gpt_bigcode-santacoder''': '''https://huggingface.co/...
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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, ) __lowerCamelCase : ...
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'''simple docstring''' import json import logging import os import socket import git import numpy as np import torch logging.basicConfig( format='''%(asctime)s - %(levelname)s - %(name)s - PID: %(process)d - %(message)s''', datefmt='''%m/%d/%Y %H:%M:%S''', level=loggi...
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'''simple docstring''' from ... import PretrainedConfig __lowerCamelCase : Any = { '''sijunhe/nezha-cn-base''': '''https://huggingface.co/sijunhe/nezha-cn-base/resolve/main/config.json''', } class A_ (a_ ): """simple docstring""" ...
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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 ImageProce...
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'''simple docstring''' import inspect import tempfile import unittest from huggingface_hub import hf_hub_download from transformers import is_torch_available from transformers.testing_utils import is_flaky, require_torch, slow, torch_device from ...test_configuration_common import Con...
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'''simple docstring''' def __UpperCAmelCase ( __magic_name__ ,__magic_name__ )-> str: """simple docstring""" if not isinstance(__magic_name__ ,__magic_name__ ): raise ValueError("iterations must be defined as integers" ) if not isinstanc...
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'''simple docstring''' import argparse import os import numpy as np import tensorflow as tf import torch from transformers import BertModel def __UpperCAmelCase ( __magic_name__ ,__magic_name__ ,__magic_name__ )-> Dict: """simple docstring""" ...
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'''simple docstring''' import argparse import os # New Code # import evaluate import torch from datasets import load_dataset from torch.optim import AdamW from torch.utils.data import DataLoader from transformers import AutoModelForSequenceClassification, AutoTokenizer, get_linear_sched...
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import json import os import re import shutil import tempfile import unittest from typing import Tuple from transformers import AddedToken, BatchEncoding, PerceiverTokenizer from transformers.utils import cached_property, is_tf_available, is_torch_available from ...test_tokenization_common import TokenizerTest...
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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....
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__snake_case = [4, 1, 7, 4, 2, 6, 4, 1, 5, 3, 7, 5] __snake_case = [3, 7, 7, 4, 2, 6, 4, 1, 5, 3, 7, 5] __snake_case = { 0: '''Sunday''', 1: '''Monday''', 2: '''Tuesday''', 3: '''Wednesday''', 4: '''Thursday''', 5: '''Friday''', 6: '''...
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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, is_vision_available, ) __lowerCamelCase : Any = {'''configurat...
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import os def SCREAMING_SNAKE_CASE_ ( _snake_case :int ) -> List[Any]: _A = len(grid[0] ) _A = len(_snake_case ) _A = 0 _A = 0 _A = 0 # Check vertically, horizontally, diagonally at the same time (only wor...
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'''simple docstring''' import copy import unittest from transformers.models.auto import get_values from transformers.testing_utils import require_torch, slow, torch_device from transformers.utils import cached_property, is_torch_available, is_vision_available from ...test_configuration_c...
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'''simple docstring''' lowerCAmelCase : dict[str, float] = { "joule": 1.0, "kilojoule": 10_00, "megajoule": 1_00_00_00, "gigajoule": 10_00_00_00_00, "wattsecond": 1.0, "watthour": 36_00, "kilowatthour": 3_60_00_00, "newtonmeter": 1.0, "calorie_nutr": 41_8...
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'''simple docstring''' import pytest from datasets.parallel import ParallelBackendConfig, parallel_backend from datasets.utils.py_utils import map_nested from .utils import require_dill_gt_0_3_2, require_joblibspark, require_not_windows def __UpperCAmelCase ( __magic_name_...
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"""simple docstring""" import gc import importlib.metadata import tempfile import unittest from packaging import version from transformers import ( AutoModel, AutoModelForCausalLM, AutoModelForSeqaSeqLM, AutoModelForSequenceClassification, AutoTokenizer, BitsAndBytesConfig, pipeline,...
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'''simple docstring''' from dataclasses import asdict, dataclass from typing import Optional from ...configuration_utils import PretrainedConfig from ...utils import logging __lowerCamelCase : Dict = logging.get_logger(__name__) # TODO Update this __lowerCamelCase : ...
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'''simple docstring''' import sys import tempfile import unittest import unittest.mock as mock from pathlib import Path from huggingface_hub import HfFolder, delete_repo from requests.exceptions import HTTPError from transformers import AutoFeatureExtractor, WavaVecaFeatureExtractor from transformers.testing_util...
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'''simple docstring''' from typing import TYPE_CHECKING from ...utils import ( OptionalDependencyNotAvailable, _LazyModule, is_tf_available, is_tokenizers_available, is_torch_available, ) __lowerCamelCase : Any = { '''configuration_longformer...
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from ..utils import DummyObject, requires_backends class UpperCamelCase_ ( metaclass=UpperCamelCase__ ): lowerCamelCase_ = ["flax"] def __init__( self :Dict , *__A :List[str] , **__A :Dict ) -> Union[str, Any]: """simple do...
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'''simple docstring''' import inspect import tempfile import unittest from huggingface_hub import hf_hub_download from transformers import is_torch_available from transformers.testing_utils import is_flaky, require_torch, slow, torch_device from ...test_configuration_common import Con...
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"""simple docstring""" def _snake_case ( _snake_case : list ) -> list: '''simple docstring''' for i in range(len(_snake_case ) - 1 , 0 , -1 ): _A = False for j in range(_snake_case , 0 , -1 ): ...
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'''simple docstring''' import itertools import json import os import unittest from transformers import AddedToken, RobertaTokenizer, RobertaTokenizerFast from transformers.models.roberta.tokenization_roberta import VOCAB_FILES_NAMES from transformers.testing_utils import require_tokenizer...
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'''simple docstring''' def _lowerCAmelCase ( __snake_case : float ) -> float: if edge <= 0 or not isinstance(__snake_case , __snake_case ): raise ValueError('Length must be a positive.' ) return 3 * ((25 + 10 * (5 ** (1 / 2))) ** (1 / 2))...
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'''simple docstring''' import math def __UpperCAmelCase ( __magic_name__ )-> bool: """simple docstring""" snake_case_ : Optional[int] = math.loga(math.sqrt(4 * positive_integer + 1 ) / 2 + 1 / 2 ) return exponent == int(__mag...
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import os import numpy import onnx def A ( __UpperCamelCase , __UpperCamelCase ) -> int: A__ = a.name A__ = b.name A__ = '' A__ = '' A__ = a == b A__ = name_a A__ = name_b return res def A ( __UpperCamelCa...
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'''simple docstring''' import argparse import json from dataclasses import dataclass, field from functools import partial from pathlib import Path from typing import List import timm import torch import torch.nn as nn from huggingface_hub import hf_hub_download from torch import Tenso...
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import math def _snake_case ( __snake_case = 100 ): _UpperCamelCase = sum(i * i for i in range(1 , n + 1 ) ) _UpperCamelCase = int(math.pow(sum(range(1 , n + 1 ) ) , 2 ) ) return square_of_sum - sum_of_squares if __name__ == ...
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'''simple docstring''' from ...configuration_utils import PretrainedConfig from ...utils import logging __lowerCamelCase : List[Any] = logging.get_logger(__name__) __lowerCamelCase : Dict = { '''weiweishi/roc-bert-base-zh''': '''https://huggingface.co...
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'''simple docstring''' import copy from ...configuration_utils import PretrainedConfig from ...utils import logging from ..auto.configuration_auto import CONFIG_MAPPING lowercase_ = logging.get_logger(__name__) class __A ( A ): '''simple docstring''' __lowerCamelCase ...
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'''simple docstring''' def __UpperCAmelCase ( __magic_name__ ,__magic_name__ ,__magic_name__ )-> int: """simple docstring""" def update_area_of_max_square(__magic_name__ ,__magic_name__ ) -> int: # BASE CASE if row >= rows or col >= col...
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from ...processing_utils import ProcessorMixin from ...tokenization_utils_base import BatchEncoding class _snake_case ( UpperCAmelCase_ ): __lowerCAmelCase : List[str] = 'ClapFeatureExtractor' __lowerCAmelCase : Tuple = ('RobertaTokenizer', 'RobertaTokenizerFast') def __...
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'''simple docstring''' import os import zipfile import requests from get_ci_error_statistics import download_artifact, get_artifacts_links def __UpperCAmelCase ( __magic_name__ ,__magic_name__=7 )-> Tuple: """simple docstring""" snake_case_ : ...
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'''simple docstring''' 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_b...
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'''simple docstring''' from string import ascii_uppercase __lowerCamelCase : Optional[Any] = {char: i for i, char in enumerate(ascii_uppercase)} __lowerCamelCase : List[str] = dict(enumerate(ascii_uppercase)) def __UpperCAmelCase ( __magic_name...
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import os import tempfile import unittest from pathlib import Path from transformers import AutoConfig, is_torch_available from transformers.testing_utils import require_torch, torch_device if is_torch_available(): from transformers import PyTorchBenchmark, PyTorchBenchmarkArguments @require_torc...
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'''simple docstring''' import argparse import os import numpy as np import tensorflow as tf import torch from transformers import BertModel def __UpperCAmelCase ( __magic_name__ ,__magic_name__ ,__magic_name__ )-> Dict: """simple docstring""" ...
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import requests A : str = 'https://newsapi.org/v1/articles?source=bbc-news&sortBy=top&apiKey=' def UpperCamelCase ( __magic_name__ : str ) -> None: """simple docstring""" lowercase__ = requests.get(_NEWS_API + bbc_news_api_key ).json() #...
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'''simple docstring''' from collections import deque from .hash_table import HashTable class A_ (a_ ): """simple docstring""" def __init__( self :List[str] , *lowerCAmelCase__ :Optional[Any] , **lowerCAmelCase__ ...
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import argparse from collections import OrderedDict from pathlib import Path import torch from huggingface_hub import hf_hub_download from PIL import Image from torchvision.transforms import functional as F from transformers import DetrImageProcessor, TableTransformerConfig, TableTransformerForObjectDete...
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'''simple docstring''' from collections.abc import Iterator, MutableMapping from dataclasses import dataclass from typing import Generic, TypeVar __lowerCamelCase : Dict = TypeVar('''KEY''') __lowerCamelCase : int = TypeVar('''VAL''') @dataclas...
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from __future__ import annotations import pandas as pd def __SCREAMING_SNAKE_CASE ( a__ : list[int] ,a__ : list[int] ,a__ : int ) -> list[int]: __A : List[str] = [0] * no_of_processes __A : Dict = [0] * no_of_processes # Copy the burst time into remai...
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'''simple docstring''' from ...configuration_utils import PretrainedConfig from ...utils import logging __lowerCamelCase : str = logging.get_logger(__name__) __lowerCamelCase : Tuple = { '''bigcode/gpt_bigcode-santacoder''': '''https://huggingface.co/...
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'''simple docstring''' from __future__ import annotations def __a(SCREAMING_SNAKE_CASE_ : list[int | float] , SCREAMING_SNAKE_CASE_ : int , SCREAMING_SNAKE_CASE_ : int ): '''simple docstring''' if len(SCREAMING_SNAKE_CASE_ ) == 0: raise Val...
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'''simple docstring''' import json import logging import os import socket import git import numpy as np import torch logging.basicConfig( format='''%(asctime)s - %(levelname)s - %(name)s - PID: %(process)d - %(message)s''', datefmt='''%m/%d/%Y %H:%M:%S''', level=loggi...
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"""simple docstring""" _a = """ # Transformers installation ! pip install transformers datasets # To install from source instead of the last release, comment the command above and uncomment the following one. # ! pip install git+https://github.com/huggingface/transformers.git """ _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 ImageProce...
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import argparse import json import os import torch from transformers import LukeConfig, LukeModel, LukeTokenizer, RobertaTokenizer from transformers.tokenization_utils_base import AddedToken @torch.no_grad() def _lowercase( __a : Union[str, Any] , __a : Union[str, Any] , _...
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'''simple docstring''' def __UpperCAmelCase ( __magic_name__ ,__magic_name__ )-> str: """simple docstring""" if not isinstance(__magic_name__ ,__magic_name__ ): raise ValueError("iterations must be defined as integers" ) if not isinstanc...
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import json import os import tempfile import transformers import datasets from utils import generate_example_dataset, get_duration UpperCAmelCase_ : List[str] = 500000 UpperCAmelCase_ , UpperCAmelCase_ : List[Any] = os.path.split(__file__) UpperCAmelCase_ :...
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'''simple docstring''' import argparse import os # New Code # import evaluate import torch from datasets import load_dataset from torch.optim import AdamW from torch.utils.data import DataLoader from transformers import AutoModelForSequenceClassification, AutoTokenizer, get_linear_sched...
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'''simple docstring''' import argparse import torch from datasets import load_dataset from donut import DonutModel from transformers import ( DonutImageProcessor, DonutProcessor, DonutSwinConfig, DonutSwinModel, MBartConfig, MBartForCausalLM, VisionEncoderDecode...
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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....
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import os import re import warnings from shutil import copyfile from typing import List, Optional, Tuple from ...tokenization_utils_fast import PreTrainedTokenizerFast from ...utils import is_sentencepiece_available, logging if is_sentencepiece_available(): from .tokenization_ta import TaTo...
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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, is_vision_available, ) __lowerCamelCase : Any = {'''configurat...
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'''simple docstring''' import math from numpy import inf from scipy.integrate import quad def _UpperCamelCase (_lowerCamelCase : float )-> float: '''simple docstring''' if num <= 0: raise ValueError('''math domain error''' ) return quad(_lowerCame...
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'''simple docstring''' import copy import unittest from transformers.models.auto import get_values from transformers.testing_utils import require_torch, slow, torch_device from transformers.utils import cached_property, is_torch_available, is_vision_available from ...test_configuration_c...
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# DISCLAIMER: This file is strongly influenced by https://github.com/ermongroup/ddim from dataclasses import dataclass from typing import Optional, Tuple, Union import flax import jax import jax.numpy as jnp from ..configuration_utils import ConfigMixin, register_to_config from .scheduling_utils_flax import ( ...
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'''simple docstring''' import pytest from datasets.parallel import ParallelBackendConfig, parallel_backend from datasets.utils.py_utils import map_nested from .utils import require_dill_gt_0_3_2, require_joblibspark, require_not_windows def __UpperCAmelCase ( __magic_name_...
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'''simple docstring''' def _a ( _lowerCamelCase ) -> int: """simple docstring""" return 1 if digit in (0, 1) else (digit * factorial(digit - 1 )) def _a ( _lowerCamelCase ) -> bool: """simple docstring""" _...
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'''simple docstring''' from dataclasses import asdict, dataclass from typing import Optional from ...configuration_utils import PretrainedConfig from ...utils import logging __lowerCamelCase : Dict = logging.get_logger(__name__) # TODO Update this __lowerCamelCase : ...
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from typing import TYPE_CHECKING from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available, is_vision_available __A : List[str] = { "configuration_conditional_detr": [ "CONDITIONAL_DETR_PRETRAINED_CONFIG_ARCHIVE_MAP", "ConditionalDe...
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'''simple docstring''' from typing import TYPE_CHECKING from ...utils import ( OptionalDependencyNotAvailable, _LazyModule, is_tf_available, is_tokenizers_available, is_torch_available, ) __lowerCamelCase : Any = { '''configuration_longformer...
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'''simple docstring''' from math import cos, sin, sqrt, tau from audio_filters.iir_filter import IIRFilter def lowercase__( __UpperCamelCase: int ,__UpperCamelCase: int ,__UpperCamelCase: float = 1 / sqrt(2 ) ): """simple docstring""" ...
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'''simple docstring''' import inspect import tempfile import unittest from huggingface_hub import hf_hub_download from transformers import is_torch_available from transformers.testing_utils import is_flaky, require_torch, slow, torch_device from ...test_configuration_common import Con...
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"""simple docstring""" import unittest import numpy as np import torch from diffusers import VersatileDiffusionImageVariationPipeline from diffusers.utils.testing_utils import load_image, require_torch_gpu, slow, torch_device A_ = False class __lowerCamelCase ( unittest.TestCase ): pass...
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'''simple docstring''' import itertools import json import os import unittest from transformers import AddedToken, RobertaTokenizer, RobertaTokenizerFast from transformers.models.roberta.tokenization_roberta import VOCAB_FILES_NAMES from transformers.testing_utils import require_tokenizer...
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from typing import TYPE_CHECKING from ...utils import ( OptionalDependencyNotAvailable, _LazyModule, is_sentencepiece_available, is_speech_available, is_torch_available, ) __a = { 'configuration_trocr': ['TROCR_PRETRAINED_CONFIG_ARCHIVE_MAP', 'TrOCRConfig'], 'processin...
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'''simple docstring''' import math def __UpperCAmelCase ( __magic_name__ )-> bool: """simple docstring""" snake_case_ : Optional[int] = math.loga(math.sqrt(4 * positive_integer + 1 ) / 2 + 1 / 2 ) return exponent == int(__mag...
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import numpy as np import torch from torch.utils.data import DataLoader from accelerate.utils.dataclasses import DistributedType class lowerCamelCase_ : '''simple docstring''' def __init__( self : Any , _lowerCAmelCase : Optional[int]=2 , _lowerCAme...
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'''simple docstring''' import argparse import json from dataclasses import dataclass, field from functools import partial from pathlib import Path from typing import List import timm import torch import torch.nn as nn from huggingface_hub import hf_hub_download from torch import Tenso...
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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_ = { "bert-base-uncased": "https://huggingface.co...
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'''simple docstring''' from ...configuration_utils import PretrainedConfig from ...utils import logging __lowerCamelCase : List[Any] = logging.get_logger(__name__) __lowerCamelCase : Dict = { '''weiweishi/roc-bert-base-zh''': '''https://huggingface.co...
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print((lambda quine: quine % quine)("""print((lambda quine: quine %% quine)(%r))"""))
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'''simple docstring''' def __UpperCAmelCase ( __magic_name__ ,__magic_name__ ,__magic_name__ )-> int: """simple docstring""" def update_area_of_max_square(__magic_name__ ,__magic_name__ ) -> int: # BASE CASE if row >= rows or col >= col...
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"""simple docstring""" import argparse from tax import checkpoints from transformers import AutoConfig, FlaxAutoModelForSeqaSeqLM def __snake_case ( _lowercase ,_lowercase ,_lowercase ): """simple docstring""" UpperCamelCase = AutoConfig.from_pretrained(_l...
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'''simple docstring''' import os import zipfile import requests from get_ci_error_statistics import download_artifact, get_artifacts_links def __UpperCAmelCase ( __magic_name__ ,__magic_name__=7 )-> Tuple: """simple docstring""" snake_case_ : ...
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import os from typing import BinaryIO, Optional, Union import numpy as np import pyarrow.parquet as pq from .. import Audio, Dataset, Features, Image, NamedSplit, Value, config from ..features.features import FeatureType, _visit from ..formatting import query_table from ..packaged_modules import _PACKAGED_DATASETS...
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'''simple docstring''' from string import ascii_uppercase __lowerCamelCase : Optional[Any] = {char: i for i, char in enumerate(ascii_uppercase)} __lowerCamelCase : List[str] = dict(enumerate(ascii_uppercase)) def __UpperCAmelCase ( __magic_name...
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from math import pi def lowercase ( __A : int , __A : int ) -> float: '''simple docstring''' return 2 * pi * radius * (angle / 360) if __name__ == "__main__": print(arc_length(90, 10))
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'''simple docstring''' import argparse import os import numpy as np import tensorflow as tf import torch from transformers import BertModel def __UpperCAmelCase ( __magic_name__ ,__magic_name__ ,__magic_name__ )-> Dict: """simple docstring""" ...
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import argparse import collections import json import os import re import string import sys import numpy as np UpperCamelCase : List[str] = re.compile(r"""\b(a|an|the)\b""", re.UNICODE) UpperCamelCase : Union[str, Any] = None def UpperCamelCase_ ( ) -> List[str]...
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'''simple docstring''' from collections import deque from .hash_table import HashTable class A_ (a_ ): """simple docstring""" def __init__( self :List[str] , *lowerCAmelCase__ :Optional[Any] , **lowerCAmelCase__ ...
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'''simple docstring''' import os from dataclasses import dataclass, field from io import BytesIO from typing import TYPE_CHECKING, Any, ClassVar, Dict, Optional, Union import numpy as np import pyarrow as pa from .. import config from ..download.streaming_download_manager import xopen, xsplitext from ..ta...
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'''simple docstring''' from collections.abc import Iterator, MutableMapping from dataclasses import dataclass from typing import Generic, TypeVar __lowerCamelCase : Dict = TypeVar('''KEY''') __lowerCamelCase : int = TypeVar('''VAL''') @dataclas...
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def __SCREAMING_SNAKE_CASE (SCREAMING_SNAKE_CASE__ ): if not numbers: return 0 if not isinstance(SCREAMING_SNAKE_CASE__ , (list, tuple) ) or not all( isinstance(SCREAMING_SNAKE_CASE__ , SCREAMING_SNAKE_CASE__ ) for number in numbers ): ...
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'''simple docstring''' from ...configuration_utils import PretrainedConfig from ...utils import logging __lowerCamelCase : str = logging.get_logger(__name__) __lowerCamelCase : Tuple = { '''bigcode/gpt_bigcode-santacoder''': '''https://huggingface.co/...
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from scipy.stats import pearsonr, spearmanr from sklearn.metrics import fa_score, matthews_corrcoef import datasets __UpperCAmelCase = '''\ @inproceedings{wang2019glue, title={{GLUE}: A Multi-Task Benchmark and Analysis Platform for Natural Language Understanding}, author={Wang, Alex and Singh, Amanpre...
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'''simple docstring''' import json import logging import os import socket import git import numpy as np import torch logging.basicConfig( format='''%(asctime)s - %(levelname)s - %(name)s - PID: %(process)d - %(message)s''', datefmt='''%m/%d/%Y %H:%M:%S''', level=loggi...
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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 import image from tran...
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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 ImageProce...
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'''simple docstring''' import logging import os from .state import PartialState class UpperCAmelCase ( logging.LoggerAdapter ): '''simple docstring''' @staticmethod def UpperCamelCase( SCREAMING_SNAKE_CASE_ ) -> List[Any]: '''simple docstring''' lower...
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'''simple docstring''' def __UpperCAmelCase ( __magic_name__ ,__magic_name__ )-> str: """simple docstring""" if not isinstance(__magic_name__ ,__magic_name__ ): raise ValueError("iterations must be defined as integers" ) if not isinstanc...
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import argparse from tax import checkpoints from transformers import AutoConfig, FlaxAutoModelForSeqaSeqLM def _a ( SCREAMING_SNAKE_CASE , SCREAMING_SNAKE_CASE , SCREAMING_SNAKE_CASE ): """simple docstring""" lowercase__ = AutoConfig.from_pretrained(SCREAMING_SNA...
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'''simple docstring''' import argparse import os # New Code # import evaluate import torch from datasets import load_dataset from torch.optim import AdamW from torch.utils.data import DataLoader from transformers import AutoModelForSequenceClassification, AutoTokenizer, get_linear_sched...
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'''simple docstring''' import asyncio import os import shutil import subprocess import sys import tempfile import unittest from distutils.util import strtobool from functools import partial from pathlib import Path from typing import List, Union from unittest import mock import torch from ..state import Accele...
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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....
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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 ( SwiftFormerConfig, SwiftFormerForImageClassification, ViTImageProcessor, ) from transformers.utils import logging logging....
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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, is_vision_available, ) __lowerCamelCase : Any = {'''configurat...
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"""simple docstring""" from ..utils import DummyObject, requires_backends class A_ ( metaclass=_a ): lowerCAmelCase__ = ['transformers', 'torch', 'note_seq'] def __init__( self: Union[str, Any] ,*__lowerCAmelCase: List[str] ,**__lowerCAmelCase: L...
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'''simple docstring''' import copy import unittest from transformers.models.auto import get_values from transformers.testing_utils import require_torch, slow, torch_device from transformers.utils import cached_property, is_torch_available, is_vision_available from ...test_configuration_c...
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from collections import OrderedDict from typing import Mapping from ...configuration_utils import PretrainedConfig from ...onnx import OnnxConfig from ...utils import logging SCREAMING_SNAKE_CASE__ = logging.get_logger(__name__) SCREAMING_SNAKE_CASE__ = { '''roberta-...
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'''simple docstring''' import pytest from datasets.parallel import ParallelBackendConfig, parallel_backend from datasets.utils.py_utils import map_nested from .utils import require_dill_gt_0_3_2, require_joblibspark, require_not_windows def __UpperCAmelCase ( __magic_name_...
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'''simple docstring''' import warnings from ...utils import logging from .image_processing_owlvit import OwlViTImageProcessor UpperCAmelCase__ : int = logging.get_logger(__name__) class A ( SCREAMING_SNAKE_CASE__ ): def __init__( self : Any , *__magic_name_...
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'''simple docstring''' from dataclasses import asdict, dataclass from typing import Optional from ...configuration_utils import PretrainedConfig from ...utils import logging __lowerCamelCase : Dict = logging.get_logger(__name__) # TODO Update this __lowerCamelCase : ...
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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 imp...
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'''simple docstring''' from typing import TYPE_CHECKING from ...utils import ( OptionalDependencyNotAvailable, _LazyModule, is_tf_available, is_tokenizers_available, is_torch_available, ) __lowerCamelCase : Any = { '''configuration_longformer...
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'''simple docstring''' import json from typing import List, Optional, Tuple from tokenizers import normalizers from ...tokenization_utils_fast import PreTrainedTokenizerFast from .tokenization_electra import ElectraTokenizer UpperCamelCase : Union[str, Any] = {'vocab_file': 'vocab.txt', '...
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'''simple docstring''' import inspect import tempfile import unittest from huggingface_hub import hf_hub_download from transformers import is_torch_available from transformers.testing_utils import is_flaky, require_torch, slow, torch_device from ...test_configuration_common import Con...
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'''simple docstring''' from pathlib import Path import fire def __snake_case ( SCREAMING_SNAKE_CASE_ : str , SCREAMING_SNAKE_CASE_ : str , SCREAMING_SNAKE_CASE_ : int ) -> int: """simple docstring""" UpperCAmelCase = Path(SCREAMING_SNAKE_CASE_ ) UpperCAm...
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'''simple docstring''' import itertools import json import os import unittest from transformers import AddedToken, RobertaTokenizer, RobertaTokenizerFast from transformers.models.roberta.tokenization_roberta import VOCAB_FILES_NAMES from transformers.testing_utils import require_tokenizer...
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"""simple docstring""" import argparse import math import os import torch from neural_compressor.utils.pytorch import load from PIL import Image from transformers import CLIPTextModel, CLIPTokenizer from diffusers import AutoencoderKL, StableDiffusionPipeline, UNetaDConditionModel ...
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'''simple docstring''' import math def __UpperCAmelCase ( __magic_name__ )-> bool: """simple docstring""" snake_case_ : Optional[int] = math.loga(math.sqrt(4 * positive_integer + 1 ) / 2 + 1 / 2 ) return exponent == int(__mag...
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import pytest from datasets import Dataset, DatasetDict, Features, NamedSplit, Value from datasets.io.text import TextDatasetReader from ..utils import assert_arrow_memory_doesnt_increase, assert_arrow_memory_increases def a_ ( lowerCAmelCase_ : Optional[Any], lowerCAmelCase_ : Optio...
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'''simple docstring''' import argparse import json from dataclasses import dataclass, field from functools import partial from pathlib import Path from typing import List import timm import torch import torch.nn as nn from huggingface_hub import hf_hub_download from torch import Tenso...
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from __future__ import annotations from typing import Any def a__ ( lowercase__ ): '''simple docstring''' if not postfix_notation: return 0 UpperCAmelCase_ ={"+", "-", "*", "/"} UpperCAmelCase_ =[] for token ...
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'''simple docstring''' from ...configuration_utils import PretrainedConfig from ...utils import logging __lowerCamelCase : List[Any] = logging.get_logger(__name__) __lowerCamelCase : Dict = { '''weiweishi/roc-bert-base-zh''': '''https://huggingface.co...
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import pytest import datasets # Import fixture modules as plugins SCREAMING_SNAKE_CASE :str = ['tests.fixtures.files', 'tests.fixtures.hub', 'tests.fixtures.fsspec'] def UpperCAmelCase ( a_ , a_ ) -> Optional[Any]: """simple docstring""" for item in i...
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'''simple docstring''' def __UpperCAmelCase ( __magic_name__ ,__magic_name__ ,__magic_name__ )-> int: """simple docstring""" def update_area_of_max_square(__magic_name__ ,__magic_name__ ) -> int: # BASE CASE if row >= rows or col >= col...
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'''simple docstring''' import os import zipfile import pytest from datasets.utils.extract import ( BzipaExtractor, Extractor, GzipExtractor, LzaExtractor, SevenZipExtractor, TarExtractor, XzExtractor, ZipExtractor, ZstdExtractor, ) from .utils import require_lza, require_py...
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'''simple docstring''' import os import zipfile import requests from get_ci_error_statistics import download_artifact, get_artifacts_links def __UpperCAmelCase ( __magic_name__ ,__magic_name__=7 )-> Tuple: """simple docstring""" snake_case_ : ...
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from typing import TYPE_CHECKING from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tokenizers_available, is_torch_available A_ : Tuple = { 'configuration_graphormer': ['GRAPHORMER_PRETRAINED_CONFIG_ARCHIVE_MAP', 'GraphormerConfig'], } try: i...
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'''simple docstring''' from string import ascii_uppercase __lowerCamelCase : Optional[Any] = {char: i for i, char in enumerate(ascii_uppercase)} __lowerCamelCase : List[str] = dict(enumerate(ascii_uppercase)) def __UpperCAmelCase ( __magic_name...
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"""simple docstring""" import argparse import torch from transformers import OpenAIGPTConfig, OpenAIGPTModel, load_tf_weights_in_openai_gpt from transformers.utils import CONFIG_NAME, WEIGHTS_NAME, logging logging.set_verbosity_info() def __lowerCAmelCase ( __UpperCamelCase :...
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'''simple docstring''' import argparse import os import numpy as np import tensorflow as tf import torch from transformers import BertModel def __UpperCAmelCase ( __magic_name__ ,__magic_name__ ,__magic_name__ )-> Dict: """simple docstring""" ...
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import os from pathlib import Path from unittest.mock import patch import pytest import zstandard as zstd from datasets.download.download_config import DownloadConfig from datasets.utils.file_utils import ( OfflineModeIsEnabled, cached_path, fsspec_get, fsspec_head, ftp_get, ftp_head, ...
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'''simple docstring''' from collections import deque from .hash_table import HashTable class A_ (a_ ): """simple docstring""" def __init__( self :List[str] , *lowerCAmelCase__ :Optional[Any] , **lowerCAmelCase__ ...
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