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import unittest import numpy as np import requests from transformers.testing_utils import require_torch, require_vision from transformers.utils import is_torch_available, is_vision_available from ...test_image_processing_common import ImageProcessingSavingTestMixin, prepare_image_inputs if is_torch_available()...
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import unittest from transformers import BigBirdTokenizer, BigBirdTokenizerFast from transformers.testing_utils import get_tests_dir, require_sentencepiece, require_tokenizers, require_torch, slow from transformers.utils import cached_property from ...test_tokenization_common import TokenizerTesterMixin UpperCa...
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from typing import Dict import numpy as np import torch from . import residue_constants as rc from .tensor_utils import tensor_tree_map, tree_map def A ( __UpperCAmelCase ) -> str: '''simple docstring''' UpperCAmelCase_ = [] UpperCAmelCase_ ...
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from __future__ import annotations import string from itertools import cycle, product from pathlib import Path UpperCamelCase_ = ( string.ascii_letters + string.digits + string.punctuation + string.whitespace ) UpperCamelCase_ = [ord(letter) for letter in string.ascii_lowercase] UpperCam...
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import unittest from transformers import ( MODEL_FOR_CAUSAL_LM_MAPPING, TF_MODEL_FOR_CAUSAL_LM_MAPPING, TextGenerationPipeline, logging, pipeline, ) from transformers.testing_utils import ( CaptureLogger, is_pipeline_test, require_accelerate, require_tf, require_torch, r...
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import pytest UpperCamelCase_ = "__dummy_dataset1__" UpperCamelCase_ = "\nimport json\nimport os\n\nimport datasets\n\n\nREPO_URL = \"https://huggingface.co/datasets/albertvillanova/tests-raw-jsonl/resolve/main/\"\nURLS = {\"train\": REPO_URL + \"wikiann-bn-train.jsonl\", \"validation\": RE...
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from __future__ import annotations UpperCamelCase_ = [] def A ( __UpperCAmelCase , __UpperCAmelCase , __UpperCAmelCase ) -> bool: '''simple docstring''' for i in range(len(lowerCAmelCase__ ) ): if board[row][i] == 1: ...
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from ...configuration_utils import PretrainedConfig from ...utils import logging UpperCamelCase_ = logging.get_logger(__name__) UpperCamelCase_ = { "s-JoL/Open-Llama-V1": "https://huggingface.co/s-JoL/Open-Llama-V1/blob/main/config.json", } class a_ ( _snake_case ): ...
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import inspect import unittest from transformers import RegNetConfig from transformers.file_utils import cached_property, is_torch_available, is_vision_available from transformers.testing_utils import require_torch, require_vision, slow, torch_device from ...test_configuration_common import ConfigTester from .....
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import tempfile import torch from diffusers import ( DEISMultistepScheduler, DPMSolverMultistepScheduler, DPMSolverSinglestepScheduler, UniPCMultistepScheduler, ) from .test_schedulers import SchedulerCommonTest class a_ ( _snake_case ): UpperCamelCase__ : Optiona...
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from typing import Dict, List from nltk.translate import gleu_score import datasets from datasets import MetricInfo UpperCamelCase_ = "\\n@misc{wu2016googles,\n title={Google\'s Neural Machine Translation System: Bridging the Gap between Human and Machine Translation},\n author={Yonghui Wu ...
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import inspect import unittest import torch import torch.nn as nn from accelerate.hooks import ( AlignDevicesHook, ModelHook, SequentialHook, add_hook_to_module, attach_align_device_hook, remove_hook_from_module, remove_hook_from_submodules, ) from accelerate.test_utils import require_...
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from __future__ import annotations from typing import Any def A ( __UpperCAmelCase ) -> Dict: '''simple docstring''' if not postfix_notation: return 0 UpperCAmelCase_ = {'''+''', '''-''', '''*''', '''/'''} UpperCAmelCase_ ...
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import shutil import tempfile import unittest import numpy as np import pytest from transformers.testing_utils import require_vision from transformers.utils import is_vision_available if is_vision_available(): from PIL import Image from transformers import ( AutoProcessor, B...
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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 AutoImageProcessor, ViTImageProcessor from transformers.testing_utils import TOKEN, USER, get_tests_...
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from collections import OrderedDict from typing import Mapping from packaging import version from ...configuration_utils import PretrainedConfig from ...onnx import OnnxConfig from ...utils import logging UpperCamelCase_ = logging.get_logger(__name__) UpperCamelCase_ = { "facebook/lev...
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import tempfile import unittest from pathlib import Path from shutil import copyfile from transformers import BatchEncoding, MarianTokenizer from transformers.testing_utils import get_tests_dir, require_sentencepiece, slow from transformers.utils import is_sentencepiece_available, is_tf_available, is_torch_availab...
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import os import sys import tempfile import torch from .state import AcceleratorState from .utils import PrecisionType, PrepareForLaunch, is_mps_available, patch_environment def A ( __UpperCAmelCase , __UpperCAmelCase=() , __UpperCAmelCase=None , __UpperCAmelCase="no" , __...
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import os # All paths are set with the intent you should run this script from the root of the repo with the command # python utils/check_doctest_list.py UpperCamelCase_ = "." if __name__ == "__main__": UpperCamelCase_ = os.path.join(REPO_PATH, "utils/documentation_tests.txt") ...
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import math import os import re import sys import unittest from pathlib import Path from typing import Tuple from unittest.mock import patch from parameterized import parameterized from transformers.testing_utils import ( CaptureStderr, ExtendSysPath, TestCasePlus, execute_subprocess_async, ge...
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_lowerCAmelCase = { "km/h": 1.0, "m/s": 3.6, "mph": 1.60_93_44, "knot": 1.8_52, } _lowerCAmelCase = { "km/h": 1.0, "m/s": 0.2_77_77_77_78, "mph": 0.6_21_37_11_92, "knot": 0.5_39_95_68_03, } def A ( __UpperCAmelCase , __UpperCAmelCase ...
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import functools def A ( __UpperCAmelCase , __UpperCAmelCase ) -> int: '''simple docstring''' UpperCAmelCase_ = len(__UpperCAmelCase ) UpperCAmelCase_ = len(__UpperCAmelCase ) @functools.cache def min_distance(_...
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import string import numpy def A ( __UpperCAmelCase , __UpperCAmelCase ) -> int: '''simple docstring''' return b if a == 0 else greatest_common_divisor(b % a , __lowerCamelCase ) class a_ : UpperCamelCase__ : Any =string.asc...
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import os import unicodedata from shutil import copyfile from typing import Any, Dict, List, Optional, Tuple import sentencepiece as spm from ...tokenization_utils import AddedToken, PreTrainedTokenizer from ...utils import SPIECE_UNDERLINE, logging UpperCamelCase_ = logging.get_logger(__name__) Upp...
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import os def A ( __UpperCAmelCase = "input.txt" ) -> int: '''simple docstring''' with open(os.path.join(os.path.dirname(_snake_case ) , _snake_case ) ) as input_file: UpperCAmelCase_ = [ [int(_snake_case ) fo...
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from ...configuration_utils import PretrainedConfig from ...utils import logging from ...utils.backbone_utils import BackboneConfigMixin, get_aligned_output_features_output_indices UpperCamelCase_ = logging.get_logger(__name__) class a_ ( _snake_case , _snake_case ): UpperCam...
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import unittest from transformers import AlbertConfig, is_torch_available from transformers.models.auto import get_values from transformers.testing_utils import require_torch, slow, torch_device from ...test_configuration_common import ConfigTester from ...test_modeling_common import ModelTesterMixin, ids_tensor,...
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import os from argparse import ArgumentParser, Namespace from ..data import SingleSentenceClassificationProcessor as Processor from ..pipelines import TextClassificationPipeline from ..utils import is_tf_available, is_torch_available, logging from . import BaseTransformersCLICommand if not is_tf_available() and ...
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class a_ : """simple docstring""" def __init__( self :Optional[Any] , _lowercase :int , _lowercase :str=None , _lowercase :Union[str, Any]=None) -> str: UpperCAmelCase_ = data UpperCAmelCase_ ...
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import unittest from typing import Dict, List, Optional, Union import numpy as np from transformers.testing_utils import require_torch, require_vision from transformers.utils import is_torch_available, is_vision_available from ...test_image_processing_common import ImageProcessingSavingTestMixin, prepare_image_i...
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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 import WavaVecaPhonemeCTCTokenizerOutput from t...
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def A ( __UpperCAmelCase = 100_0000 ) -> int: '''simple docstring''' UpperCAmelCase_ = [i - 1 for i in range(limit + 1 )] for i in range(2 , limit + 1 ): if phi[i] == i - 1: for j in range(2 * i , limit + 1 ...
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import json import pathlib import unittest import numpy as np from transformers.testing_utils import require_torch, require_vision, slow from transformers.utils import is_torch_available, is_vision_available from ...test_image_processing_common import ImageProcessingSavingTestMixin, prepare_image_inputs if i...
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import tempfile import torch from diffusers import PNDMScheduler from .test_schedulers import SchedulerCommonTest class a_ ( _snake_case ): UpperCamelCase__ : List[Any] =(PNDMScheduler,) UpperCamelCase__ : Optional[Any] =(("num_inference_steps", 50),) ...
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import argparse import intel_extension_for_pytorch as ipex import torch from diffusers import DPMSolverMultistepScheduler, StableDiffusionPipeline UpperCamelCase_ = argparse.ArgumentParser("Stable Diffusion script with intel optimization", add_help=False) parser.add_argument("--dpm", action="store_tr...
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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 ..table import array_cast from ..ut...
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def A ( __UpperCAmelCase = 100_0000 ) -> Any: '''simple docstring''' UpperCAmelCase_ = set(range(3 , lowerCamelCase__ , 2 ) ) primes.add(2 ) for p in range(3 , lowerCamelCase__ , 2 ): if p not in primes...
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from ..utils import DummyObject, requires_backends class a_ ( metaclass=_snake_case ): UpperCamelCase__ : Any =["torch", "scipy"] def __init__( self :List[str] , *_lowercase :List[str] , **_lowercase :Union[str, Any]) -> List[Any]: ...
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import argparse import os import jax as jnp import numpy as onp import torch import torch.nn as nn from music_spectrogram_diffusion import inference from tax import checkpoints from diffusers import DDPMScheduler, OnnxRuntimeModel, SpectrogramDiffusionPipeline from diffusers.pipelines.spectrogram_diffusion import...
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from typing import Dict import numpy as np import torch from . import residue_constants as rc from .tensor_utils import tensor_tree_map, tree_map def A ( __UpperCAmelCase ) -> Dict[str, torch.Tensor]: '''simple docstring''' UpperCAmelCase_ = [] UpperC...
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import argparse import os import gluonnlp as nlp import mxnet as mx import numpy as np import torch from gluonnlp.base import get_home_dir from gluonnlp.model.bert import BERTEncoder from gluonnlp.model.utils import _load_vocab from gluonnlp.vocab import Vocab from packaging import version from torch import nn fr...
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# Copyright 2023 The HuggingFace Inc. team. All rights reserved. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by ...
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from collections.abc import Callable def A ( __UpperCAmelCase , __UpperCAmelCase , __UpperCAmelCase ) -> List[str]: '''simple docstring''' UpperCAmelCase_ = a UpperCAmelCase_ = b if function(__UpperCAmelCase ) == 0: ...
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from typing import TYPE_CHECKING from ...utils import ( OptionalDependencyNotAvailable, _LazyModule, is_flax_available, is_tf_available, is_tokenizers_available, is_torch_available, ) UpperCamelCase_ = {"configuration_opt": ["OPT_PRETRAINED_CONFIG_ARCHIVE_MAP", "OPTConfig"]} t...
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import csv from collections import defaultdict from dataclasses import dataclass, field from typing import List, Optional import matplotlib.pyplot as plt import numpy as np from matplotlib.ticker import ScalarFormatter from transformers import HfArgumentParser def A ( __UpperCAmelCase=None ...
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import unittest from transformers import BigBirdTokenizer, BigBirdTokenizerFast from transformers.testing_utils import get_tests_dir, require_sentencepiece, require_tokenizers, require_torch, slow from transformers.utils import cached_property from ...test_tokenization_common import TokenizerTesterMixin UpperCa...
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import json from typing import List, Optional, Tuple from tokenizers import normalizers from ...tokenization_utils_fast import PreTrainedTokenizerFast from .tokenization_lxmert import LxmertTokenizer UpperCamelCase_ = {"vocab_file": "vocab.txt", "tokenizer_file": "tokenizer.json"} UpperCamelCase_ ...
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from __future__ import annotations import string from itertools import cycle, product from pathlib import Path UpperCamelCase_ = ( string.ascii_letters + string.digits + string.punctuation + string.whitespace ) UpperCamelCase_ = [ord(letter) for letter in string.ascii_lowercase] UpperCam...
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from collections import defaultdict def A ( __UpperCAmelCase ) -> int: '''simple docstring''' UpperCAmelCase_ = 1 UpperCAmelCase_ = True for v in tree[start]: if v not in visited: ret += dfs(_UpperCAmel...
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import pytest UpperCamelCase_ = "__dummy_dataset1__" UpperCamelCase_ = "\nimport json\nimport os\n\nimport datasets\n\n\nREPO_URL = \"https://huggingface.co/datasets/albertvillanova/tests-raw-jsonl/resolve/main/\"\nURLS = {\"train\": REPO_URL + \"wikiann-bn-train.jsonl\", \"validation\": RE...
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import argparse import os from pathlib import Path from typing import Dict import tensorflow as tf import torch from tqdm import tqdm from transformers import PegasusConfig, PegasusForConditionalGeneration, PegasusTokenizer from transformers.models.pegasus.configuration_pegasus import DEFAULTS, task_specific_para...
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from ...configuration_utils import PretrainedConfig from ...utils import logging UpperCamelCase_ = logging.get_logger(__name__) UpperCamelCase_ = { "s-JoL/Open-Llama-V1": "https://huggingface.co/s-JoL/Open-Llama-V1/blob/main/config.json", } class a_ ( _snake_case ): ...
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from .constants import ( MODEL_NAME, OPTIMIZER_NAME, RNG_STATE_NAME, SAFE_WEIGHTS_INDEX_NAME, SAFE_WEIGHTS_NAME, SCALER_NAME, SCHEDULER_NAME, TORCH_LAUNCH_PARAMS, WEIGHTS_INDEX_NAME, WEIGHTS_NAME, ) from .dataclasses import ( BnbQuantizationConfig, ComputeEnvironmen...
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import tempfile import torch from diffusers import ( DEISMultistepScheduler, DPMSolverMultistepScheduler, DPMSolverSinglestepScheduler, UniPCMultistepScheduler, ) from .test_schedulers import SchedulerCommonTest class a_ ( _snake_case ): UpperCamelCase__ : Optiona...
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def A ( __UpperCAmelCase , __UpperCAmelCase , __UpperCAmelCase , __UpperCAmelCase ) -> Optional[Any]: '''simple docstring''' if height >= 1: move_tower(height - 1 , __lowerCAmelCase , __lowerCAmelCase , __lowerCAmelCase ) ...
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import inspect import unittest import torch import torch.nn as nn from accelerate.hooks import ( AlignDevicesHook, ModelHook, SequentialHook, add_hook_to_module, attach_align_device_hook, remove_hook_from_module, remove_hook_from_submodules, ) from accelerate.test_utils import require_...
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def A ( __UpperCAmelCase ) -> Optional[Any]: '''simple docstring''' UpperCAmelCase_ = False while is_sorted is False: # Until all the indices are traversed keep looping UpperCAmelCase_ = True for i in range(0 , l...
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import shutil import tempfile import unittest import numpy as np import pytest from transformers.testing_utils import require_vision from transformers.utils import is_vision_available if is_vision_available(): from PIL import Image from transformers import ( AutoProcessor, B...
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import math from ...configuration_utils import PretrainedConfig from ...utils import logging UpperCamelCase_ = logging.get_logger(__name__) UpperCamelCase_ = { 'facebook/data2vec-base-960h': 'https://huggingface.co/facebook/data2vec-audio-base-960h/resolve/main/config.json', # See ...
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from collections import OrderedDict from typing import Mapping from packaging import version from ...configuration_utils import PretrainedConfig from ...onnx import OnnxConfig from ...utils import logging UpperCamelCase_ = logging.get_logger(__name__) UpperCamelCase_ = { "facebook/lev...
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import json from typing import List, Optional, Tuple from tokenizers import normalizers from ...tokenization_utils_fast import PreTrainedTokenizerFast from .tokenization_lxmert import LxmertTokenizer UpperCamelCase_ = {"vocab_file": "vocab.txt", "tokenizer_file": "tokenizer.json"} UpperCamelCase_ = ...
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import os import sys import tempfile import torch from .state import AcceleratorState from .utils import PrecisionType, PrepareForLaunch, is_mps_available, patch_environment def A ( __UpperCAmelCase , __UpperCAmelCase=() , __UpperCAmelCase=None , __UpperCAmelCase="no" , __...
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from . import __version__ # Backward compatibility imports, to make sure all those objects can be found in file_utils from .utils import ( CLOUDFRONT_DISTRIB_PREFIX, CONFIG_NAME, DISABLE_TELEMETRY, DUMMY_INPUTS, DUMMY_MASK, ENV_VARS_TRUE_AND_AUTO_VALUES, ENV_VARS_TRUE_VALUES, FEATUR...
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import math import os import re import sys import unittest from pathlib import Path from typing import Tuple from unittest.mock import patch from parameterized import parameterized from transformers.testing_utils import ( CaptureStderr, ExtendSysPath, TestCasePlus, execute_subprocess_async, ge...
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import json import pathlib import unittest import numpy as np from transformers.testing_utils import require_torch, require_vision, slow from transformers.utils import is_torch_available, is_vision_available from ...test_image_processing_common import ImageProcessingSavingTestMixin, prepare_image_inputs if is_...
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import functools def A ( __UpperCAmelCase , __UpperCAmelCase ) -> int: '''simple docstring''' UpperCAmelCase_ = len(__UpperCAmelCase ) UpperCAmelCase_ = len(__UpperCAmelCase ) @functools.cache def min_distance(_...
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from __future__ import annotations def A ( __UpperCAmelCase , __UpperCAmelCase , __UpperCAmelCase ) -> tuple[float, list[float]]: '''simple docstring''' UpperCAmelCase_ = list(range(len(__UpperCAmelCase ) ) ) UpperCAmelCase_ ...
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import os import unicodedata from shutil import copyfile from typing import Any, Dict, List, Optional, Tuple import sentencepiece as spm from ...tokenization_utils import AddedToken, PreTrainedTokenizer from ...utils import SPIECE_UNDERLINE, logging UpperCamelCase_ = logging.get_logger(__name__) Upp...
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import gc import unittest import numpy as np import torch from transformers import CLIPTextConfig, CLIPTextModel, CLIPTokenizer from diffusers import ( AutoencoderKL, DDIMScheduler, EulerAncestralDiscreteScheduler, LMSDiscreteScheduler, PNDMScheduler, StableDiffusionPanoramaPipeline, U...
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from ...configuration_utils import PretrainedConfig from ...utils import logging from ...utils.backbone_utils import BackboneConfigMixin, get_aligned_output_features_output_indices UpperCamelCase_ = logging.get_logger(__name__) class a_ ( _snake_case , _snake_case ): UpperCam...
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def A ( __UpperCAmelCase ) -> int: '''simple docstring''' if not isinstance(_lowerCamelCase , _lowerCamelCase ): raise TypeError('''Input value must be an \'int\' type''' ) UpperCAmelCase_ = 0 while number: position += ...
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import os from argparse import ArgumentParser, Namespace from ..data import SingleSentenceClassificationProcessor as Processor from ..pipelines import TextClassificationPipeline from ..utils import is_tf_available, is_torch_available, logging from . import BaseTransformersCLICommand if not is_tf_available() and ...
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import json import os import re import sys import urllib.request import requests from bsa import BeautifulSoup UpperCamelCase_ = { "User-Agent": "Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36" " (KHTML, like Gecko) Chrome/70.0.3538.102 Safari/537.36 Edge/18.19582" } def ...
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import unittest from typing import Dict, List, Optional, Union import numpy as np from transformers.testing_utils import require_torch, require_vision from transformers.utils import is_torch_available, is_vision_available from ...test_image_processing_common import ImageProcessingSavingTestMixin, prepare_image_i...
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from __future__ import annotations import inspect import unittest import numpy as np from transformers import ResNetConfig from transformers.testing_utils import require_tf, require_vision, slow from transformers.utils import cached_property, is_tf_available, is_vision_available from ...test_configuration_common...
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def A ( __UpperCAmelCase = 100_0000 ) -> int: '''simple docstring''' UpperCAmelCase_ = [i - 1 for i in range(limit + 1 )] for i in range(2 , limit + 1 ): if phi[i] == i - 1: for j in range(2 * i , limit + 1 ...
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def A ( ) -> int: '''simple docstring''' return [ a * b * (1000 - a - b) for a in range(1 , 999 ) for b in range(_SCREAMING_SNAKE_CASE , 999 ) if (a * a + b * b == (1000 - a - b) ** 2) ][0] if __name__ == "__main__"...
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import tempfile import torch from diffusers import PNDMScheduler from .test_schedulers import SchedulerCommonTest class a_ ( _snake_case ): UpperCamelCase__ : List[Any] =(PNDMScheduler,) UpperCamelCase__ : Optional[Any] =(("num_inference_steps", 50),) ...
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import os from typing import Dict, List, Tuple, TypeVar, Union UpperCamelCase_ = TypeVar("T") UpperCamelCase_ = Union[List[T], Tuple[T, ...]] UpperCamelCase_ = Union[T, List[T], Dict[str, T]] UpperCamelCase_ = Union[str, bytes, os.PathLike]
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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 ..table import array_cast from ..ut...
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from functools import reduce UpperCamelCase_ = ( '73167176531330624919225119674426574742355349194934' '96983520312774506326239578318016984801869478851843' '85861560789112949495459501737958331952853208805511' '12540698747158523863050715693290963295227443043557' '6689664895044524452316...
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from ..utils import DummyObject, requires_backends class a_ ( metaclass=_snake_case ): UpperCamelCase__ : Any =["torch", "scipy"] def __init__( self :List[str] , *_lowercase :List[str] , **_lowercase :Union[str, Any]) -> List[Any]: ...
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import os import unittest from huggingface_hub.utils import are_progress_bars_disabled import transformers.models.bart.tokenization_bart from transformers import logging from transformers.testing_utils import CaptureLogger, mockenv, mockenv_context from transformers.utils.logging import disable_progress_bar, enab...
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from typing import Dict import numpy as np import torch from . import residue_constants as rc from .tensor_utils import tensor_tree_map, tree_map def A ( __UpperCAmelCase ) -> Dict[str, torch.Tensor]: '''simple docstring''' UpperCAmelCase_ = [] UpperC...
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from datasets.utils.patching import _PatchedModuleObj, patch_submodule from . import _test_patching def A ( ) -> Any: '''simple docstring''' import os as original_os from os import path as original_path from os import rename as original_rename from os.path im...
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# Copyright 2023 The HuggingFace Inc. team. All rights reserved. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by ...
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import os import posixpath import uuid from dataclasses import dataclass from typing import TYPE_CHECKING, Iterable, List, Optional, Tuple, Union import numpy as np import pyarrow as pa import datasets from datasets.arrow_writer import ArrowWriter, ParquetWriter from datasets.config import MAX_SHARD_SIZE from dat...
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from typing import TYPE_CHECKING from ...utils import ( OptionalDependencyNotAvailable, _LazyModule, is_flax_available, is_tf_available, is_tokenizers_available, is_torch_available, ) UpperCamelCase_ = {"configuration_opt": ["OPT_PRETRAINED_CONFIG_ARCHIVE_MAP", "OPTConfig"]} t...
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from __future__ import annotations import time UpperCamelCase_ = list[tuple[int, int]] UpperCamelCase_ = [ [0, 0, 0, 0, 0, 0, 0], [0, 1, 0, 0, 0, 0, 0], # 0 are free path whereas 1's are obstacles [0, 0, 0, 0, 0, 0, 0], [0, 0, 1, 0, 0, 0, 0], [1, 0, 1, 0, 0, 0, 0], ...
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import unittest from transformers import BigBirdTokenizer, BigBirdTokenizerFast from transformers.testing_utils import get_tests_dir, require_sentencepiece, require_tokenizers, require_torch, slow from transformers.utils import cached_property from ...test_tokenization_common import TokenizerTesterMixin UpperCa...
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from typing import TYPE_CHECKING # rely on isort to merge the imports from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tokenizers_available, is_torch_available UpperCamelCase_ = {'''configuration_mra''': ['''MRA_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''MraConfig''']} try: if ...
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from __future__ import annotations import string from itertools import cycle, product from pathlib import Path UpperCamelCase_ = ( string.ascii_letters + string.digits + string.punctuation + string.whitespace ) UpperCamelCase_ = [ord(letter) for letter in string.ascii_lowercase] UpperCam...
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import numpy as np from PIL import Image def A ( __UpperCAmelCase , __UpperCAmelCase , __UpperCAmelCase ) -> Union[str, Any]: '''simple docstring''' UpperCAmelCase_ = np.array(_lowercase ) if arr.shape[0] != arr.shape[1]: rai...
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import pytest UpperCamelCase_ = "__dummy_dataset1__" UpperCamelCase_ = "\nimport json\nimport os\n\nimport datasets\n\n\nREPO_URL = \"https://huggingface.co/datasets/albertvillanova/tests-raw-jsonl/resolve/main/\"\nURLS = {\"train\": REPO_URL + \"wikiann-bn-train.jsonl\", \"validation\": RE...
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from datetime import datetime as dt import os from github import Github UpperCamelCase_ = [ "good first issue", "good second issue", "good difficult issue", "feature request", "new model", "wip", ] def A ( ) -> Tuple: '''simple docstring''' ...
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from ...configuration_utils import PretrainedConfig from ...utils import logging UpperCamelCase_ = logging.get_logger(__name__) UpperCamelCase_ = { "s-JoL/Open-Llama-V1": "https://huggingface.co/s-JoL/Open-Llama-V1/blob/main/config.json", } class a_ ( _snake_case ): ...
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import unittest from parameterized import parameterized from transformers import LlamaConfig, is_torch_available, set_seed from transformers.testing_utils import require_torch, slow, torch_device from ...generation.test_utils import GenerationTesterMixin from ...test_configuration_common import ConfigTester fr...
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import tempfile import torch from diffusers import ( DEISMultistepScheduler, DPMSolverMultistepScheduler, DPMSolverSinglestepScheduler, UniPCMultistepScheduler, ) from .test_schedulers import SchedulerCommonTest class a_ ( _snake_case ): UpperCamelCase__ : Optiona...
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from PIL import Image def A ( __UpperCAmelCase , __UpperCAmelCase ) -> Image: '''simple docstring''' UpperCAmelCase_ = (259 * (level + 255)) / (255 * (259 - level)) def contrast(__UpperCAmelCase ) -> int: return int(128 + factor *...
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import inspect import unittest import torch import torch.nn as nn from accelerate.hooks import ( AlignDevicesHook, ModelHook, SequentialHook, add_hook_to_module, attach_align_device_hook, remove_hook_from_module, remove_hook_from_submodules, ) from accelerate.test_utils import require_...
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from ...configuration_utils import PretrainedConfig from ...utils import logging UpperCamelCase_ = logging.get_logger(__name__) UpperCamelCase_ = { '''facebook/timesformer''': '''https://huggingface.co/facebook/timesformer/resolve/main/config.json''', } class a_ ( a__ ...
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import shutil import tempfile import unittest import numpy as np import pytest from transformers.testing_utils import require_vision from transformers.utils import is_vision_available if is_vision_available(): from PIL import Image from transformers import ( AutoProcessor, B...
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from math import factorial UpperCamelCase_ = {str(digit): factorial(digit) for digit in range(10)} def A ( __UpperCAmelCase ) -> int: '''simple docstring''' if not isinstance(__UpperCAmelCase , __UpperCAmelCase ): raise TypeError('''Paramet...
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from collections import OrderedDict from typing import Mapping from packaging import version from ...configuration_utils import PretrainedConfig from ...onnx import OnnxConfig from ...utils import logging UpperCamelCase_ = logging.get_logger(__name__) UpperCamelCase_ = { "facebook/lev...
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def A ( __UpperCAmelCase = 100_0000 ) -> int: '''simple docstring''' UpperCAmelCase_ = set(range(3 , snake_case__ , 2 ) ) primes.add(2 ) for p in range(3 , snake_case__ , 2 ): if p not in primes: ...
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import os import sys import tempfile import torch from .state import AcceleratorState from .utils import PrecisionType, PrepareForLaunch, is_mps_available, patch_environment def A ( __UpperCAmelCase , __UpperCAmelCase=() , __UpperCAmelCase=None , __UpperCAmelCase="no" , __...
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import os from typing import Any, Callable, Dict, List, Optional, Tuple, Union import torch from torch import nn from ...models.controlnet import ControlNetModel, ControlNetOutput from ...models.modeling_utils import ModelMixin from ...utils import logging UpperCamelCase_ = logging.get_logger(__name_...
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import math import os import re import sys import unittest from pathlib import Path from typing import Tuple from unittest.mock import patch from parameterized import parameterized from transformers.testing_utils import ( CaptureStderr, ExtendSysPath, TestCasePlus, execute_subprocess_async, ge...
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from .constants import ( MODEL_NAME, OPTIMIZER_NAME, RNG_STATE_NAME, SAFE_WEIGHTS_INDEX_NAME, SAFE_WEIGHTS_NAME, SCALER_NAME, SCHEDULER_NAME, TORCH_LAUNCH_PARAMS, WEIGHTS_INDEX_NAME, WEIGHTS_NAME, ) from .dataclasses import ( BnbQuantizationConfig, ComputeEnvironment,...
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import functools def A ( __UpperCAmelCase , __UpperCAmelCase ) -> int: '''simple docstring''' UpperCAmelCase_ = len(__UpperCAmelCase ) UpperCAmelCase_ = len(__UpperCAmelCase ) @functools.cache def min_distance(_...
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import contextlib import csv import json import os import sqlitea import tarfile import textwrap import zipfile import pyarrow as pa import pyarrow.parquet as pq import pytest import datasets import datasets.config @pytest.fixture(scope='''session''' ) def A ( ) -> List[str]: '''simp...
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import os import unicodedata from shutil import copyfile from typing import Any, Dict, List, Optional, Tuple import sentencepiece as spm from ...tokenization_utils import AddedToken, PreTrainedTokenizer from ...utils import SPIECE_UNDERLINE, logging UpperCamelCase_ = logging.get_logger(__name__) Upp...
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import itertools import json import os import unittest from transformers import AddedToken, LongformerTokenizer, LongformerTokenizerFast from transformers.models.longformer.tokenization_longformer import VOCAB_FILES_NAMES from transformers.testing_utils import require_tokenizers, slow from ...test_tokenization_co...
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from ...configuration_utils import PretrainedConfig from ...utils import logging from ...utils.backbone_utils import BackboneConfigMixin, get_aligned_output_features_output_indices UpperCamelCase_ = logging.get_logger(__name__) class a_ ( _snake_case , _snake_case ): UpperCam...
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import functools from typing import Any def A ( __UpperCAmelCase , __UpperCAmelCase ) -> Tuple: '''simple docstring''' if not isinstance(snake_case_ , snake_case_ ) or len(snake_case_ ) == 0: raise ValueError('''the string should be not empty string'...
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import os from argparse import ArgumentParser, Namespace from ..data import SingleSentenceClassificationProcessor as Processor from ..pipelines import TextClassificationPipeline from ..utils import is_tf_available, is_torch_available, logging from . import BaseTransformersCLICommand if not is_tf_available() and ...
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import inspect from typing import Callable, List, Optional, Union import torch from transformers import CLIPImageProcessor, CLIPTextModel, CLIPTokenizer from diffusers import DiffusionPipeline from diffusers.models import AutoencoderKL, UNetaDConditionModel from diffusers.pipelines.stable_diffusion import StableD...
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import unittest from typing import Dict, List, Optional, Union import numpy as np from transformers.testing_utils import require_torch, require_vision from transformers.utils import is_torch_available, is_vision_available from ...test_image_processing_common import ImageProcessingSavingTestMixin, prepare_image_i...
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def A ( __UpperCAmelCase , __UpperCAmelCase = False ) -> Optional[Any]: '''simple docstring''' if not isinstance(__a , __a ): UpperCAmelCase_ = f"Expected string as input, found {type(__a )}" raise ValueError(__a ) ...
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def A ( __UpperCAmelCase = 100_0000 ) -> int: '''simple docstring''' UpperCAmelCase_ = [i - 1 for i in range(limit + 1 )] for i in range(2 , limit + 1 ): if phi[i] == i - 1: for j in range(2 * i , limit + 1 ...
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def A ( __UpperCAmelCase = 10**12 ) -> Union[str, Any]: '''simple docstring''' UpperCAmelCase_ = 1 UpperCAmelCase_ = 0 UpperCAmelCase_ = 1 UpperCAmelCase_ = 1 while numerator <= 2 * min_total -...
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import tempfile import torch from diffusers import PNDMScheduler from .test_schedulers import SchedulerCommonTest class a_ ( _snake_case ): UpperCamelCase__ : List[Any] =(PNDMScheduler,) UpperCamelCase__ : Optional[Any] =(("num_inference_steps", 50),) ...
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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 transformers.utils import logging logging.set_verbos...
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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 ..table import array_cast from ..ut...
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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_sentencepiece_available, logging if is_sentencepiece...
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from ..utils import DummyObject, requires_backends class a_ ( metaclass=_snake_case ): UpperCamelCase__ : Any =["torch", "scipy"] def __init__( self :List[str] , *_lowercase :List[str] , **_lowercase :Union[str, Any]) -> List[Any]: ...
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from typing import TYPE_CHECKING from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available, is_vision_available UpperCamelCase_ = { "configuration_poolformer": [ "POOLFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP", "PoolFormerConfig", "PoolFormerOnnxConfig...
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from typing import Dict import numpy as np import torch from . import residue_constants as rc from .tensor_utils import tensor_tree_map, tree_map def A ( __UpperCAmelCase ) -> Dict[str, torch.Tensor]: '''simple docstring''' UpperCAmelCase_ = [] UpperC...
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import argparse from collections import defaultdict import yaml UpperCamelCase_ = "docs/source/en/_toctree.yml" def A ( __UpperCAmelCase ) -> str: '''simple docstring''' UpperCAmelCase_ = defaultdict(__UpperCAmelCase ) UpperCAmelCase_ ...
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# Copyright 2023 The HuggingFace Inc. team. All rights reserved. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by ...
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from typing import TYPE_CHECKING from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available UpperCamelCase_ = { 'configuration_bigbird_pegasus': [ 'BIGBIRD_PEGASUS_PRETRAINED_CONFIG_ARCHIVE_MAP', 'BigBirdPegasusConfig', 'BigBirdPegasusOnnxConfig', ...
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from typing import TYPE_CHECKING from ...utils import ( OptionalDependencyNotAvailable, _LazyModule, is_flax_available, is_tf_available, is_tokenizers_available, is_torch_available, ) UpperCamelCase_ = {"configuration_opt": ["OPT_PRETRAINED_CONFIG_ARCHIVE_MAP", "OPTConfig"]} t...
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import re import subprocess import sys UpperCamelCase_ = subprocess.check_output("git merge-base main HEAD".split()).decode("utf-8") UpperCamelCase_ = subprocess.check_output(f"git diff --name-only {fork_point_sha}".split()).decode("utf-8").split() UpperCamelCase_ = "|".join(sys....
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import unittest from transformers import BigBirdTokenizer, BigBirdTokenizerFast from transformers.testing_utils import get_tests_dir, require_sentencepiece, require_tokenizers, require_torch, slow from transformers.utils import cached_property from ...test_tokenization_common import TokenizerTesterMixin UpperCa...
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from PIL import Image def A ( __UpperCAmelCase ) -> Dict: '''simple docstring''' UpperCAmelCase_ = image.size UpperCAmelCase_ = 0 UpperCAmelCase_ = image.load() for i in range(_A ): for j in ra...
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from __future__ import annotations import string from itertools import cycle, product from pathlib import Path UpperCamelCase_ = ( string.ascii_letters + string.digits + string.punctuation + string.whitespace ) UpperCamelCase_ = [ord(letter) for letter in string.ascii_lowercase] UpperCam...
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import argparse from transformers import CLIPImageProcessor, CLIPVisionModelWithProjection from diffusers import UnCLIPImageVariationPipeline, UnCLIPPipeline if __name__ == "__main__": UpperCamelCase_ = argparse.ArgumentParser() parser.add_argument("--dump_path", default=None, type=str, re...
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import pytest UpperCamelCase_ = "__dummy_dataset1__" UpperCamelCase_ = "\nimport json\nimport os\n\nimport datasets\n\n\nREPO_URL = \"https://huggingface.co/datasets/albertvillanova/tests-raw-jsonl/resolve/main/\"\nURLS = {\"train\": REPO_URL + \"wikiann-bn-train.jsonl\", \"validation\": RE...
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def A ( __UpperCAmelCase ) -> bool: '''simple docstring''' return str(__UpperCAmelCase ) == str(__UpperCAmelCase )[::-1] def A ( __UpperCAmelCase ) -> int: '''simple docstring''' return int(__UpperCAmelCase ) + int(str(__UpperC...
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from ...configuration_utils import PretrainedConfig from ...utils import logging UpperCamelCase_ = logging.get_logger(__name__) UpperCamelCase_ = { "s-JoL/Open-Llama-V1": "https://huggingface.co/s-JoL/Open-Llama-V1/blob/main/config.json", } class a_ ( _snake_case ): ...
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from typing import TYPE_CHECKING from ...utils import ( OptionalDependencyNotAvailable, _LazyModule, is_flax_available, is_tf_available, is_tokenizers_available, is_torch_available, ) UpperCamelCase_ = { "configuration_electra": ["ELECTRA_PRETRAINED_CONFIG_ARCHIVE_MAP", "...
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import tempfile import torch from diffusers import ( DEISMultistepScheduler, DPMSolverMultistepScheduler, DPMSolverSinglestepScheduler, UniPCMultistepScheduler, ) from .test_schedulers import SchedulerCommonTest class a_ ( _snake_case ): UpperCamelCase__ : Optiona...
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import requests from bsa import BeautifulSoup def A ( __UpperCAmelCase = "AAPL" ) -> str: '''simple docstring''' UpperCAmelCase_ = f"https://in.finance.yahoo.com/quote/{symbol}?s={symbol}" UpperCAmelCase_ = BeautifulSoup(requests.get(__sn...
362
import inspect import unittest import torch import torch.nn as nn from accelerate.hooks import ( AlignDevicesHook, ModelHook, SequentialHook, add_hook_to_module, attach_align_device_hook, remove_hook_from_module, remove_hook_from_submodules, ) from accelerate.test_utils import require_...
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import requests UpperCamelCase_ = "" # <-- Put your OpenWeatherMap appid here! UpperCamelCase_ = "https://api.openweathermap.org/data/2.5/" def A ( __UpperCAmelCase = "Chicago" , __UpperCAmelCase = APPID ) -> dict: '''simple docstring''' retu...
363
import shutil import tempfile import unittest import numpy as np import pytest from transformers.testing_utils import require_vision from transformers.utils import is_vision_available if is_vision_available(): from PIL import Image from transformers import ( AutoProcessor, B...
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def A ( __UpperCAmelCase ) -> Any: '''simple docstring''' UpperCAmelCase_ = [0] * len(SCREAMING_SNAKE_CASE_ ) UpperCAmelCase_ = [] UpperCAmelCase_ = [1] * len(SCREAMING_SNAKE_CASE_ ) for values in graph.values...
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from collections import OrderedDict from typing import Mapping from packaging import version from ...configuration_utils import PretrainedConfig from ...onnx import OnnxConfig from ...utils import logging UpperCamelCase_ = logging.get_logger(__name__) UpperCamelCase_ = { "facebook/lev...
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def A ( __UpperCAmelCase ) -> int: '''simple docstring''' if n == 1 or not isinstance(snake_case__ , snake_case__ ): return 0 elif n == 2: return 1 else: UpperCAmelCase_ = [0, 1] for i in range(2 ...
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import os import sys import tempfile import torch from .state import AcceleratorState from .utils import PrecisionType, PrepareForLaunch, is_mps_available, patch_environment def A ( __UpperCAmelCase , __UpperCAmelCase=() , __UpperCAmelCase=None , __UpperCAmelCase="no" , __...
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def A ( __UpperCAmelCase ) -> int: '''simple docstring''' if not grid or not grid[0]: raise TypeError('''The grid does not contain the appropriate information''' ) for cell_n in range(1 , len(grid[0] ) ): grid[0][cell_n] += grid[0][...
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import math import os import re import sys import unittest from pathlib import Path from typing import Tuple from unittest.mock import patch from parameterized import parameterized from transformers.testing_utils import ( CaptureStderr, ExtendSysPath, TestCasePlus, execute_subprocess_async, ge...
344
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from typing import TYPE_CHECKING from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available, is_vision_available _lowerCAmelCase = {"configuration_yolos": ["YOLOS_PRETRAINED_CONFIG_ARCHIVE_MAP", "YolosConfig", "YolosOnnxConfig"]} try: if not is_vision_available(): ...
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import functools def A ( __UpperCAmelCase , __UpperCAmelCase ) -> int: '''simple docstring''' UpperCAmelCase_ = len(__UpperCAmelCase ) UpperCAmelCase_ = len(__UpperCAmelCase ) @functools.cache def min_distance(_...
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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_ = { 'camembert-base': 'https://huggingface.co/ca...
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import os import unicodedata from shutil import copyfile from typing import Any, Dict, List, Optional, Tuple import sentencepiece as spm from ...tokenization_utils import AddedToken, PreTrainedTokenizer from ...utils import SPIECE_UNDERLINE, logging UpperCamelCase_ = logging.get_logger(__name__) Upp...
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import inspect import unittest from transformers import RegNetConfig from transformers.file_utils import cached_property, is_torch_available, is_vision_available from transformers.testing_utils import require_torch, require_vision, slow, torch_device from ...test_configuration_common import ConfigTester from ...t...
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from ...configuration_utils import PretrainedConfig from ...utils import logging from ...utils.backbone_utils import BackboneConfigMixin, get_aligned_output_features_output_indices UpperCamelCase_ = logging.get_logger(__name__) class a_ ( _snake_case , _snake_case ): UpperCam...
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import sys def A ( __UpperCAmelCase ) -> str: '''simple docstring''' UpperCAmelCase_ = len(__SCREAMING_SNAKE_CASE ) UpperCAmelCase_ = [[0 for x in range(__SCREAMING_SNAKE_CASE )] for x in range(__SCREAMING_SNAKE_CASE )] ...
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import os from argparse import ArgumentParser, Namespace from ..data import SingleSentenceClassificationProcessor as Processor from ..pipelines import TextClassificationPipeline from ..utils import is_tf_available, is_torch_available, logging from . import BaseTransformersCLICommand if not is_tf_available() and ...
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UpperCamelCase_ = range(2, 20 + 1) UpperCamelCase_ = [10**k for k in range(ks[-1] + 1)] UpperCamelCase_ = {} def A ( __UpperCAmelCase , __UpperCAmelCase , __UpperCAmelCase , __UpperCAmelCase ) -> List[Any]: '''simple docstring''' ...
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import unittest from typing import Dict, List, Optional, Union import numpy as np from transformers.testing_utils import require_torch, require_vision from transformers.utils import is_torch_available, is_vision_available from ...test_image_processing_common import ImageProcessingSavingTestMixin, prepare_image_i...
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from sklearn.metrics import recall_score import datasets UpperCamelCase_ = "\nRecall is the fraction of the positive examples that were correctly labeled by the model as positive. It can be computed with the equation:\nRecall = TP / (TP + FN)\nWhere TP is the true positives and FN is the false negative...
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def A ( __UpperCAmelCase = 100_0000 ) -> int: '''simple docstring''' UpperCAmelCase_ = [i - 1 for i in range(limit + 1 )] for i in range(2 , limit + 1 ): if phi[i] == i - 1: for j in range(2 * i , limit + 1 ...
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from __future__ import annotations from fractions import Fraction def A ( __UpperCAmelCase , __UpperCAmelCase ) -> bool: '''simple docstring''' return ( num != den and num % 10 == den // 10 and (num // 10) / (den % 10) == num / den ) def ...
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import tempfile import torch from diffusers import PNDMScheduler from .test_schedulers import SchedulerCommonTest class a_ ( _snake_case ): UpperCamelCase__ : List[Any] =(PNDMScheduler,) UpperCamelCase__ : Optional[Any] =(("num_inference_steps", 50),) ...
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import importlib import inspect import json import os import re import shutil import sys from pathlib import Path from typing import Dict, Optional, Union from urllib import request from huggingface_hub import HfFolder, cached_download, hf_hub_download, model_info from packaging import version from .. import __ve...
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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 ..table import array_cast from ..ut...
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import unittest from accelerate import debug_launcher from accelerate.test_utils import require_cpu, test_ops, test_script @require_cpu class a_ ( unittest.TestCase ): def __a ( self :Optional[Any]) -> Union[str, Any]: debug_launcher(test_script.main) def...
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from ..utils import DummyObject, requires_backends class a_ ( metaclass=_snake_case ): UpperCamelCase__ : Any =["torch", "scipy"] def __init__( self :List[str] , *_lowercase :List[str] , **_lowercase :Union[str, Any]) -> List[Any]: ...
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import math def A ( __UpperCAmelCase ) -> bool: '''simple docstring''' return math.sqrt(__UpperCAmelCase ) * math.sqrt(__UpperCAmelCase ) == num def A ( __UpperCAmelCase ) -> bool: '''simple docstring''' UpperCAmelCase_ ...
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from typing import Dict import numpy as np import torch from . import residue_constants as rc from .tensor_utils import tensor_tree_map, tree_map def A ( __UpperCAmelCase ) -> Dict[str, torch.Tensor]: '''simple docstring''' UpperCAmelCase_ = [] UpperC...
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import os from pathlib import Path def A ( ) -> List[str]: '''simple docstring''' from torch.utils.cpp_extension import load UpperCAmelCase_ = Path(__UpperCAmelCase ).resolve().parent.parent.parent / '''kernels''' / '''deformable_detr''' UpperCAm...
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# Copyright 2023 The HuggingFace Inc. team. All rights reserved. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by ...
344
0
import copy import json import os import tempfile from transformers import is_torch_available from .test_configuration_utils import config_common_kwargs class a_ ( _snake_case ): def __init__( self :int , _lowercase :Dict , _lowercase :List[str]=None ...
356
from typing import TYPE_CHECKING from ...utils import ( OptionalDependencyNotAvailable, _LazyModule, is_flax_available, is_tf_available, is_tokenizers_available, is_torch_available, ) UpperCamelCase_ = {"configuration_opt": ["OPT_PRETRAINED_CONFIG_ARCHIVE_MAP", "OPTConfig"]} t...
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import copy import os from typing import Union from ...configuration_utils import PretrainedConfig from ...utils import logging UpperCamelCase_ = logging.get_logger(__name__) UpperCamelCase_ = { "microsoft/git-base": "https://huggingface.co/microsoft/git-base/resolve/main/config.json",...
357
import unittest from transformers import BigBirdTokenizer, BigBirdTokenizerFast from transformers.testing_utils import get_tests_dir, require_sentencepiece, require_tokenizers, require_torch, slow from transformers.utils import cached_property from ...test_tokenization_common import TokenizerTesterMixin UpperCa...
344
0
import gc import random import tempfile import unittest import numpy as np import torch from PIL import Image from transformers import CLIPTextConfig, CLIPTextModel, CLIPTokenizer from diffusers import ( AutoencoderKL, DDIMInverseScheduler, DDIMScheduler, DPMSolverMultistepInverseScheduler, ...
358
from __future__ import annotations import string from itertools import cycle, product from pathlib import Path UpperCamelCase_ = ( string.ascii_letters + string.digits + string.punctuation + string.whitespace ) UpperCamelCase_ = [ord(letter) for letter in string.ascii_lowercase] UpperCam...
344
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class a_ : def __init__( self :str) -> List[Any]: UpperCAmelCase_ = 0 UpperCAmelCase_ = 0 UpperCAmelCase_ = {} def __a ( self :Tuple , _lowercase :Tuple) -> Optional[int]: ...
359
import pytest UpperCamelCase_ = "__dummy_dataset1__" UpperCamelCase_ = "\nimport json\nimport os\n\nimport datasets\n\n\nREPO_URL = \"https://huggingface.co/datasets/albertvillanova/tests-raw-jsonl/resolve/main/\"\nURLS = {\"train\": REPO_URL + \"wikiann-bn-train.jsonl\", \"validation\": RE...
344
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def A ( __UpperCAmelCase = 100_0000 ) -> int: '''simple docstring''' UpperCAmelCase_ = [i - 1 for i in range(limit + 1 )] for i in range(2 , limit + 1 ): if phi[i] == i - 1: for j in range(2 * i , limit + 1 ...
360
from ...configuration_utils import PretrainedConfig from ...utils import logging UpperCamelCase_ = logging.get_logger(__name__) UpperCamelCase_ = { "s-JoL/Open-Llama-V1": "https://huggingface.co/s-JoL/Open-Llama-V1/blob/main/config.json", } class a_ ( _snake_case ): ...
344
0
import argparse import os import re UpperCamelCase_ = "src/transformers/models/auto" # re pattern that matches mapping introductions: # SUPER_MODEL_MAPPING_NAMES = OrderedDict or SUPER_MODEL_MAPPING = OrderedDict UpperCamelCase_ = re.compile(r"[A-Z_]+_MAPPING(\s+|_[A-Z_]+\s+)=\s+Order...
361
import tempfile import torch from diffusers import ( DEISMultistepScheduler, DPMSolverMultistepScheduler, DPMSolverSinglestepScheduler, UniPCMultistepScheduler, ) from .test_schedulers import SchedulerCommonTest class a_ ( _snake_case ): UpperCamelCase__ : Optiona...
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0
# Copyright 2023 The HuggingFace Inc. team. All rights reserved. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by ...
362
import inspect import unittest import torch import torch.nn as nn from accelerate.hooks import ( AlignDevicesHook, ModelHook, SequentialHook, add_hook_to_module, attach_align_device_hook, remove_hook_from_module, remove_hook_from_submodules, ) from accelerate.test_utils import require_...
344
0
import re def A ( __UpperCAmelCase ) -> list: '''simple docstring''' return [char.split() for char in re.split(r'''[^ a-z A-Z 0-9 \s]''' , str_ )] def A ( __UpperCAmelCase ) -> str: '''simple docstring''' UpperCAmelCase_...
363
import shutil import tempfile import unittest import numpy as np import pytest from transformers.testing_utils import require_vision from transformers.utils import is_vision_available if is_vision_available(): from PIL import Image from transformers import ( AutoProcessor, B...
344
0
from collections import OrderedDict from typing import Any, Mapping, Optional from ... import PreTrainedTokenizer from ...configuration_utils import PretrainedConfig from ...file_utils import TensorType, is_torch_available from ...onnx import OnnxConfig, OnnxConfigWithPast, OnnxSeqaSeqConfigWithPast from ...onnx.u...
364
from collections import OrderedDict from typing import Mapping from packaging import version from ...configuration_utils import PretrainedConfig from ...onnx import OnnxConfig from ...utils import logging UpperCamelCase_ = logging.get_logger(__name__) UpperCamelCase_ = { "facebook/lev...
344
0
import torch from diffusers import DDPMParallelScheduler from .test_schedulers import SchedulerCommonTest class a_ ( _snake_case ): UpperCamelCase__ : Tuple =(DDPMParallelScheduler,) def __a ( self :Tuple , **_lowercase :str) -> Union[str, Any...
365
import os import sys import tempfile import torch from .state import AcceleratorState from .utils import PrecisionType, PrepareForLaunch, is_mps_available, patch_environment def A ( __UpperCAmelCase , __UpperCAmelCase=() , __UpperCAmelCase=None , __UpperCAmelCase="no" , __...
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from ...configuration_utils import PretrainedConfig from ...utils import logging UpperCamelCase_ = logging.get_logger(__name__) UpperCamelCase_ = { "google/vivit-b-16x2-kinetics400": ( "https://huggingface.co/google/vivit-b-16x2-kinetics400/resolve/main/config.json" ), #...
366
import math import os import re import sys import unittest from pathlib import Path from typing import Tuple from unittest.mock import patch from parameterized import parameterized from transformers.testing_utils import ( CaptureStderr, ExtendSysPath, TestCasePlus, execute_subprocess_async, ge...
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import os def A ( __UpperCAmelCase = "input.txt" ) -> int: '''simple docstring''' with open(os.path.join(os.path.dirname(__UpperCAmelCase ) , __UpperCAmelCase ) ) as input_file: UpperCAmelCase_ = [ [int(__UpperCAm...
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import functools def A ( __UpperCAmelCase , __UpperCAmelCase ) -> int: '''simple docstring''' UpperCAmelCase_ = len(__UpperCAmelCase ) UpperCAmelCase_ = len(__UpperCAmelCase ) @functools.cache def min_distance(_...
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import unittest from transformers import BigBirdTokenizer, BigBirdTokenizerFast from transformers.testing_utils import get_tests_dir, require_sentencepiece, require_tokenizers, require_torch, slow from transformers.utils import cached_property from ...test_tokenization_common import TokenizerTesterMixin UpperCa...
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import os import unicodedata from shutil import copyfile from typing import Any, Dict, List, Optional, Tuple import sentencepiece as spm from ...tokenization_utils import AddedToken, PreTrainedTokenizer from ...utils import SPIECE_UNDERLINE, logging UpperCamelCase_ = logging.get_logger(__name__) Upp...
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