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"""simple docstring""" from unittest.mock import patch import pyspark from datasets.packaged_modules.spark.spark import ( Spark, SparkExamplesIterable, _generate_iterable_examples, ) from ..utils import ( require_dill_gt_0_3_2, require_not_windows, ) def lowerCAmelCase_...
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"""simple docstring""" import argparse import logging from collections import namedtuple import torch from model_bertabs import BertAbsSummarizer from models.model_builder import AbsSummarizer # The authors' implementation from transformers import BertTokenizer logging.basicConfig(level=logging...
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"""simple docstring""" from collections import OrderedDict from typing import Mapping from ...configuration_utils import PretrainedConfig from ...onnx import OnnxConfig from ...utils import logging UpperCAmelCase__ =logging.get_logger(__name__) UpperCAmelCase__ ={ "facebook/data2vec-...
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"""simple docstring""" def lowerCAmelCase_ ( UpperCamelCase__ : int ): """simple docstring""" assert ( isinstance(UpperCamelCase__ , UpperCamelCase__ ) and number_of_steps > 0 ), f'''number_of_steps needs to be positive integer, your input {number_of_s...
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"""simple docstring""" from __future__ import annotations from collections.abc import Iterator from typing import Any class lowerCamelCase__ : def __init__( self : Optional[int] , A_ : Any ): '''simple docstring''' __lowe...
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"""simple docstring""" import unittest from transformers import BarthezTokenizer, BarthezTokenizerFast, BatchEncoding from transformers.testing_utils import require_sentencepiece, require_tokenizers, require_torch, slow from ...test_tokenization_common import TokenizerTesterMixin @require_tok...
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"""simple docstring""" import os def lowerCAmelCase_ ( ): """simple docstring""" with open(os.path.dirname(UpperCamelCase__ ) + """/p022_names.txt""" ) as file: __lowercase = str(file.readlines()[0] ) __lowercase = names.replace("""\"""" ...
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"""simple docstring""" import gc import random import unittest import torch from diffusers import ( IFImgaImgPipeline, IFImgaImgSuperResolutionPipeline, IFInpaintingPipeline, IFInpaintingSuperResolutionPipeline, IFPipeline, IFSuperResolutionPipeline, ) from diffusers.mod...
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"""simple docstring""" import unittest from transformers.testing_utils import CaptureStdout from transformers.tools.python_interpreter import evaluate def lowerCAmelCase_ ( UpperCamelCase__ : Optional[Any] ): """simple docstring""" return x + 2 c...
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"""simple docstring""" class lowerCamelCase__ : def __init__( self : Optional[Any] , A_ : Dict , A_ : str , A_ : Any ): '''simple docstring''' __lowercase = None __lowercase = ...
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"""simple docstring""" import string import numpy def lowerCAmelCase_ ( UpperCamelCase__ : int , UpperCamelCase__ : int ): """simple docstring""" return b if a == 0 else greatest_common_divisor(b % a , UpperCamelCase__ ) class lo...
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"""simple docstring""" from pathlib import Path import cva import numpy as np from matplotlib import pyplot as plt def lowerCAmelCase_ ( UpperCamelCase__ : np.ndarray , UpperCamelCase__ : np.ndarray , UpperCamelCase__ : np.ndarray , UpperCamelCase__ : int...
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"""simple docstring""" def lowerCAmelCase_ ( UpperCamelCase__ : str , UpperCamelCase__ : str ): """simple docstring""" __lowercase = len(UpperCamelCase__ ) __lowercase = [] for i in range(len(UpperCamelCase__ ) - pat_len + 1 ...
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"""simple docstring""" from PIL import Image def lowerCAmelCase_ ( UpperCamelCase__ : Image , UpperCamelCase__ : int ): """simple docstring""" __lowercase = (259 * (level + 255)) / (255 * (259 - level)) def contrast(UpperCamelCase__ ...
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"""simple docstring""" import argparse import json from tqdm import tqdm def lowerCAmelCase_ ( ): """simple docstring""" __lowercase = argparse.ArgumentParser() # Required parameters parser.add_argument( """--src_path""" , type=UpperCamelCa...
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"""simple docstring""" import os import re import shutil import sys import tempfile import unittest import black UpperCAmelCase__ =os.path.abspath(os.path.dirname(os.path.dirname(os.path.dirname(__file__)))) sys.path.append(os.path.join(git_repo_path, "utils")) import check_copies # noqa:...
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"""simple docstring""" import argparse import random import joblib import numpy as np import torch from igf.igf import ( SecondaryLearner, collect_objective_set, compute_perplexity, generate_datasets, load_gpta, recopy_gpta, set_seed, train_secondary_learner, ) ...
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"""simple docstring""" from typing import Optional import torch import torch.utils.checkpoint from torch import Tensor, nn from torch.nn import BCEWithLogitsLoss, CrossEntropyLoss, MSELoss from ...activations import ACTaFN from ...file_utils import add_code_sample_docstrings, add_start_docstrings, ad...
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"""simple docstring""" 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 ( BnbQu...
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"""simple docstring""" from __future__ import annotations def lowerCAmelCase_ ( UpperCamelCase__ : list[float] , UpperCamelCase__ : Any ): """simple docstring""" print(f'''Vertex\tShortest Distance from vertex {src}''' ) for i, d in enumerate(Upp...
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"""simple docstring""" 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 from ...utils.backbone_utils import BackboneConfigMixin, get_aligned_outp...
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"""simple docstring""" import os import time import warnings from dataclasses import dataclass, field from enum import Enum from typing import List, Optional, Union import torch from filelock import FileLock from torch.utils.data import Dataset from ...tokenization_utils_base import PreTrainedToke...
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"""simple docstring""" from typing import TYPE_CHECKING from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tf_available, is_torch_available UpperCAmelCase__ ={ "configuration_groupvit": [ "GROUPVIT_PRETRAINED_CONFIG_ARCHIVE_MAP", "GroupViTConfig", "...
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"""simple docstring""" from collections import OrderedDict from typing import Any, List, Mapping, Optional from ... import PreTrainedTokenizer, TensorType, is_torch_available from ...configuration_utils import PretrainedConfig from ...onnx import OnnxConfigWithPast, PatchingSpec from ...utils import log...
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"""simple docstring""" 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_...
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"""simple docstring""" import pytest import requests from datasets.utils.file_utils import http_head from .utils import OfflineSimulationMode, RequestWouldHangIndefinitelyError, offline @pytest.mark.integration def lowerCAmelCase_ ( ): """simple docstring""" wit...
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"""simple docstring""" import inspect import unittest import warnings from transformers import DeiTConfig from transformers.models.auto import get_values from transformers.testing_utils import ( require_accelerate, require_torch, require_torch_gpu, require_vision, slow, tor...
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"""simple docstring""" def lowerCAmelCase_ ( UpperCamelCase__ : list , UpperCamelCase__ : int , UpperCamelCase__ : int = 0 , UpperCamelCase__ : int = 0 ): """simple docstring""" __lowercase = right or len(UpperCamelCase__ ...
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"""simple docstring""" from typing import TYPE_CHECKING from ...utils import ( OptionalDependencyNotAvailable, _LazyModule, is_torch_available, ) UpperCAmelCase__ ={ "configuration_mega": ["MEGA_PRETRAINED_CONFIG_ARCHIVE_MAP", "MegaConfig", "MegaOnnxConfig"], } try: ...
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"""simple docstring""" import json import os from pathlib import Path from shutil import copyfile from typing import Any, Dict, List, Optional, Tuple, Union import sentencepiece from ...tokenization_utils import BatchEncoding, PreTrainedTokenizer from ...utils import logging UpperCAmelCase__ ...
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"""simple docstring""" from __future__ import annotations def lowerCAmelCase_ ( UpperCamelCase__ : list[float] ): """simple docstring""" if len(UpperCamelCase__ ) < 2: raise ValueError("""Monogons and Digons are not polygons in the Euclidean space""" ) ...
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"""simple docstring""" import copy from typing import TYPE_CHECKING, Any, Mapping, Optional, OrderedDict from packaging import version from ...configuration_utils import PretrainedConfig from ...onnx import OnnxConfig from ...utils import logging from ..auto.configuration_auto import AutoConfig ...
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"""simple docstring""" import inspect import unittest from transformers import MobileNetVaConfig from transformers.testing_utils import require_torch, require_vision, slow, torch_device from transformers.utils import cached_property, is_torch_available, is_vision_available from ...test_configuration_c...
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"""simple docstring""" import time from dataclasses import dataclass from multiprocessing import Pool from unittest import TestCase from unittest.mock import patch import multiprocess import numpy as np import pytest from datasets.utils.py_utils import ( NestedDataStructure, asdict, ...
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"""simple docstring""" import math from typing import Dict, Iterable, List, Optional, Tuple, Union import numpy as np from ...image_processing_utils import BaseImageProcessor, BatchFeature, get_size_dict from ...image_transforms import normalize, rescale, resize, to_channel_dimension_format from ...im...
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"""simple docstring""" from typing import Optional from urllib.parse import quote import huggingface_hub as hfh from packaging import version def lowerCAmelCase_ ( UpperCamelCase__ : str , UpperCamelCase__ : str , UpperCamelCase__ : Optional[str] = None ): ...
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"""simple docstring""" import argparse import shlex import runhouse as rh if __name__ == "__main__": # Refer to https://runhouse-docs.readthedocs-hosted.com/en/latest/api/python/cluster.html#hardware-setup for cloud access # setup instructions, if using on-demand hardware # I...
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"""simple docstring""" def lowerCAmelCase_ ( UpperCamelCase__ : Union[str, Any] , UpperCamelCase__ : Union[str, Any] , UpperCamelCase__ : int ): """simple docstring""" if n == 0: return 1 elif n % 2 == 1: return (binary_exponentiation...
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"""simple docstring""" from __future__ import annotations import unittest from transformers import BlenderbotSmallConfig, BlenderbotSmallTokenizer, is_tf_available from transformers.testing_utils import require_tf, require_tokenizers, slow from transformers.utils import cached_property from ...test_...
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"""simple docstring""" 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...
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"""simple docstring""" 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__) UpperCAmelCase__ ={ "microsoft/focaln...
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"""simple docstring""" import unittest import numpy as np from transformers.testing_utils import require_flax, require_tf, require_torch from transformers.utils import ( expand_dims, flatten_dict, is_flax_available, is_tf_available, is_torch_available, reshape, squeeze...
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"""simple docstring""" def lowerCAmelCase_ ( UpperCamelCase__ : str ): """simple docstring""" if not all(x.isalpha() for x in string ): raise ValueError("""String must only contain alphabetic characters.""" ) __lowercase = sorted(string.lower() ...
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"""simple docstring""" def lowerCAmelCase_ ( UpperCamelCase__ : int , UpperCamelCase__ : int ): """simple docstring""" return x if y == 0 else greatest_common_divisor(UpperCamelCase__ , x % y ) def lowerCAmelCase_ ( UpperCamelCase__ ...
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"""simple docstring""" UpperCAmelCase__ =[sum(int(c, 10) ** 2 for c in i.__str__()) for i in range(10_0000)] def lowerCAmelCase_ ( UpperCamelCase__ : int ): """simple docstring""" __lowercase = 0 while number: # Increased Speed Slightly by ch...
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"""simple docstring""" import argparse import logging from collections import namedtuple import torch from model_bertabs import BertAbsSummarizer from models.model_builder import AbsSummarizer # The authors' implementation from transformers import BertTokenizer logging.basicConfig(level=logging...
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"""simple docstring""" import warnings from collections import OrderedDict from typing import Any, Mapping, Optional from ... import PreTrainedTokenizer from ...configuration_utils import PretrainedConfig from ...onnx import OnnxConfig, OnnxConfigWithPast, OnnxSeqaSeqConfigWithPast from ...onnx.utils i...
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"""simple docstring""" def lowerCAmelCase_ ( UpperCamelCase__ : int ): """simple docstring""" assert ( isinstance(UpperCamelCase__ , UpperCamelCase__ ) and number_of_steps > 0 ), f'''number_of_steps needs to be positive integer, your input {number_of_s...
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"""simple docstring""" from typing import TYPE_CHECKING from ...utils import ( OptionalDependencyNotAvailable, _LazyModule, is_tokenizers_available, is_torch_available, is_vision_available, ) UpperCAmelCase__ ={ "configuration_layoutlmv2": ["LAYOUTLMV2_PRETRAINED_CONF...
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"""simple docstring""" import unittest from transformers import BarthezTokenizer, BarthezTokenizerFast, BatchEncoding from transformers.testing_utils import require_sentencepiece, require_tokenizers, require_torch, slow from ...test_tokenization_common import TokenizerTesterMixin @require_tok...
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"""simple docstring""" def lowerCAmelCase_ ( UpperCamelCase__ : int ): """simple docstring""" assert ( isinstance(UpperCamelCase__ , UpperCamelCase__ ) and number_of_steps > 0 ), f'''number_of_steps needs to be positive integer, your input {number_of_s...
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"""simple docstring""" import gc import random import unittest import torch from diffusers import ( IFImgaImgPipeline, IFImgaImgSuperResolutionPipeline, IFInpaintingPipeline, IFInpaintingSuperResolutionPipeline, IFPipeline, IFSuperResolutionPipeline, ) from diffusers.mod...
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"""simple docstring""" import argparse import logging import sys from unittest.mock import patch import run_glue_deebert from transformers.testing_utils import TestCasePlus, get_gpu_count, require_torch_non_multi_gpu, slow logging.basicConfig(level=logging.DEBUG) UpperCAmelCase__ =logging....
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"""simple docstring""" class lowerCamelCase__ : def __init__( self : Optional[Any] , A_ : Dict , A_ : str , A_ : Any ): '''simple docstring''' __lowercase = None __lowercase = ...
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"""simple docstring""" import darl # noqa import gym import tqdm from diffusers.experimental import ValueGuidedRLPipeline UpperCAmelCase__ ={ "n_samples": 64, "horizon": 32, "num_inference_steps": 20, "n_guide_steps": 2, # can set to 0 for faster sampling, does not use value n...
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"""simple docstring""" from pathlib import Path import cva import numpy as np from matplotlib import pyplot as plt def lowerCAmelCase_ ( UpperCamelCase__ : np.ndarray , UpperCamelCase__ : np.ndarray , UpperCamelCase__ : np.ndarray , UpperCamelCase__ : int...
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"""simple docstring""" def lowerCAmelCase_ ( UpperCamelCase__ : list[int] , UpperCamelCase__ : int ): """simple docstring""" __lowercase = len(UpperCamelCase__ ) __lowercase = [[False] * (required_sum + 1) for _ in range(arr_len + ...
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"""simple docstring""" from PIL import Image def lowerCAmelCase_ ( UpperCamelCase__ : Image , UpperCamelCase__ : int ): """simple docstring""" __lowercase = (259 * (level + 255)) / (255 * (259 - level)) def contrast(UpperCamelCase__ ...
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"""simple docstring""" # coding=utf-8 # Copyright 2023 The HuggingFace Inc. team. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENS...
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"""simple docstring""" import os import re import shutil import sys import tempfile import unittest import black UpperCAmelCase__ =os.path.abspath(os.path.dirname(os.path.dirname(os.path.dirname(__file__)))) sys.path.append(os.path.join(git_repo_path, "utils")) import check_copies # noqa:...
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"""simple docstring""" from typing import Callable, Optional, Union from ...configuration_utils import PretrainedConfig from ...utils import logging UpperCAmelCase__ =logging.get_logger(__name__) UpperCAmelCase__ ={ "microsoft/xprophetnet-large-wiki100-cased": ( "https://huggi...
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"""simple docstring""" from typing import Optional import torch import torch.utils.checkpoint from torch import Tensor, nn from torch.nn import BCEWithLogitsLoss, CrossEntropyLoss, MSELoss from ...activations import ACTaFN from ...file_utils import add_code_sample_docstrings, add_start_docstrings, ad...
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"""simple docstring""" import unittest import numpy as np import timeout_decorator # noqa from transformers import BlenderbotConfig, is_flax_available from transformers.testing_utils import jax_device, require_flax, slow from ...generation.test_flax_utils import FlaxGenerationTesterMixin from ...t...
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"""simple docstring""" from __future__ import annotations def lowerCAmelCase_ ( UpperCamelCase__ : list[float] , UpperCamelCase__ : Any ): """simple docstring""" print(f'''Vertex\tShortest Distance from vertex {src}''' ) for i, d in enumerate(Upp...
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"""simple docstring""" import os import warnings from typing import List, Optional from ...tokenization_utils_base import BatchEncoding from ...utils import logging from .configuration_rag import RagConfig UpperCAmelCase__ =logging.get_logger(__name__) class lowerCamelCase__ : ...
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"""simple docstring""" import os import time import warnings from dataclasses import dataclass, field from enum import Enum from typing import List, Optional, Union import torch from filelock import FileLock from torch.utils.data import Dataset from ...tokenization_utils_base import PreTrainedToke...
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"""simple docstring""" import unittest import numpy as np from transformers.testing_utils import require_flax, require_tf, require_torch from transformers.utils import ( expand_dims, flatten_dict, is_flax_available, is_tf_available, is_torch_available, reshape, squeeze...
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"""simple docstring""" from collections import OrderedDict from typing import Any, List, Mapping, Optional from ... import PreTrainedTokenizer, TensorType, is_torch_available from ...configuration_utils import PretrainedConfig from ...onnx import OnnxConfigWithPast, PatchingSpec from ...utils import log...
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"""simple docstring""" def lowerCAmelCase_ ( UpperCamelCase__ : int ): """simple docstring""" if not isinstance(UpperCamelCase__ , UpperCamelCase__ ) or number < 0: raise ValueError("""Input must be a non-negative integer""" ) __lowercase = ...
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"""simple docstring""" import pytest import requests from datasets.utils.file_utils import http_head from .utils import OfflineSimulationMode, RequestWouldHangIndefinitelyError, offline @pytest.mark.integration def lowerCAmelCase_ ( ): """simple docstring""" wit...
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"""simple docstring""" import json from typing import List, Optional, Tuple from tokenizers import normalizers from tokenizers.pre_tokenizers import BertPreTokenizer, PreTokenizer from ...tokenization_utils_fast import PreTrainedTokenizerFast from ...utils import logging from .tokenization_roformer i...
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"""simple docstring""" def lowerCAmelCase_ ( UpperCamelCase__ : list , UpperCamelCase__ : int , UpperCamelCase__ : int = 0 , UpperCamelCase__ : int = 0 ): """simple docstring""" __lowercase = right or len(UpperCamelCase__ ...
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"""simple docstring""" import re import warnings from contextlib import contextmanager from ...processing_utils import ProcessorMixin class lowerCamelCase__ ( _a ): a : Optional[int] = ["""image_processor""", """tokenizer"""] a : Optional[Any] =...
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"""simple docstring""" import json import os from pathlib import Path from shutil import copyfile from typing import Any, Dict, List, Optional, Tuple, Union import sentencepiece from ...tokenization_utils import BatchEncoding, PreTrainedTokenizer from ...utils import logging UpperCAmelCase__ ...
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"""simple docstring""" from __future__ import annotations def lowerCAmelCase_ ( UpperCamelCase__ : list[int] , UpperCamelCase__ : int ): """simple docstring""" __lowercase = 0 __lowercase = len(UpperCamelCase__ ) - 1 while...
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"""simple docstring""" import copy from typing import TYPE_CHECKING, Any, Mapping, Optional, OrderedDict from packaging import version from ...configuration_utils import PretrainedConfig from ...onnx import OnnxConfig from ...utils import logging from ..auto.configuration_auto import AutoConfig ...
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"""simple docstring""" import time from dataclasses import dataclass from multiprocessing import Pool from unittest import TestCase from unittest.mock import patch import multiprocess import numpy as np import pytest from datasets.utils.py_utils import ( NestedDataStructure, asdict, ...
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"""simple docstring""" import time from dataclasses import dataclass from multiprocessing import Pool from unittest import TestCase from unittest.mock import patch import multiprocess import numpy as np import pytest from datasets.utils.py_utils import ( NestedDataStructure, asdict, ...
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"""simple docstring""" def lowerCAmelCase_ ( UpperCamelCase__ : list , UpperCamelCase__ : int = 0 ): """simple docstring""" __lowercase = length or len(UpperCamelCase__ ) __lowercase = False for i in range(length - 1 ): if l...
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"""simple docstring""" from typing import Optional from urllib.parse import quote import huggingface_hub as hfh from packaging import version def lowerCAmelCase_ ( UpperCamelCase__ : str , UpperCamelCase__ : str , UpperCamelCase__ : Optional[str] = None ): ...
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"""simple docstring""" import os import time import pytest from datasets.utils.filelock import FileLock, Timeout def lowerCAmelCase_ ( UpperCamelCase__ : Dict ): """simple docstring""" __lowercase = FileLock(str(tmpdir / """foo.lock""" ) ) ...
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"""simple docstring""" def lowerCAmelCase_ ( UpperCamelCase__ : Union[str, Any] , UpperCamelCase__ : Union[str, Any] , UpperCamelCase__ : int ): """simple docstring""" if n == 0: return 1 elif n % 2 == 1: return (binary_exponentiation...
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"""simple docstring""" import comet # From: unbabel-comet import torch import datasets UpperCAmelCase__ =datasets.logging.get_logger(__name__) UpperCAmelCase__ ="\\n@inproceedings{rei-EtAl:2020:WMT,\n author = {Rei, Ricardo and Stewart, Craig and Farinha, Ana C and Lavie, Alon},...
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"""simple docstring""" 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...
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"""simple docstring""" from __future__ import annotations def lowerCAmelCase_ ( UpperCamelCase__ : list[int | float] , UpperCamelCase__ : int , UpperCamelCase__ : int ): """simple docstring""" if len(UpperCamelCase__ ) == 0: raise Val...
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"""simple docstring""" import unittest import numpy as np from transformers.testing_utils import require_flax, require_tf, require_torch from transformers.utils import ( expand_dims, flatten_dict, is_flax_available, is_tf_available, is_torch_available, reshape, squeeze...
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"""simple docstring""" import fire from torch.utils.data import DataLoader from tqdm import tqdm from transformers import AutoTokenizer from utils import SeqaSeqDataset, pickle_save def lowerCAmelCase_ ( UpperCamelCase__ : Dict , UpperCamelCase__ : Optional[int] , UpperCa...
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"""simple docstring""" def lowerCAmelCase_ ( UpperCamelCase__ : int , UpperCamelCase__ : int ): """simple docstring""" return x if y == 0 else greatest_common_divisor(UpperCamelCase__ , x % y ) def lowerCAmelCase_ ( UpperCamelCase__ ...
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"""simple docstring""" import logging from dataclasses import dataclass, field from typing import Optional from seqaseq_trainer import arg_to_scheduler from transformers import TrainingArguments UpperCAmelCase__ =logging.getLogger(__name__) @dataclass class lowerCamelCase__ ( ...
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"""simple docstring""" import argparse import logging from collections import namedtuple import torch from model_bertabs import BertAbsSummarizer from models.model_builder import AbsSummarizer # The authors' implementation from transformers import BertTokenizer logging.basicConfig(level=logging...
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"""simple docstring""" from typing import TYPE_CHECKING from ...utils import ( OptionalDependencyNotAvailable, _LazyModule, is_sentencepiece_available, is_tokenizers_available, is_torch_available, ) UpperCAmelCase__ ={} try: if not is_sentencepiece_available(): ...
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"""simple docstring""" def lowerCAmelCase_ ( UpperCamelCase__ : int ): """simple docstring""" assert ( isinstance(UpperCamelCase__ , UpperCamelCase__ ) and number_of_steps > 0 ), f'''number_of_steps needs to be positive integer, your input {number_of_s...
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"""simple docstring""" # Lint as: python3 # pylint: enable=line-too-long # pylint: disable=g-import-not-at-top,g-bad-import-order,wrong-import-position UpperCAmelCase__ ="2.13.1" import platform import pyarrow from packaging import version if version.parse(platform.python_version()) < vers...
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"""simple docstring""" import unittest from transformers import BarthezTokenizer, BarthezTokenizerFast, BatchEncoding from transformers.testing_utils import require_sentencepiece, require_tokenizers, require_torch, slow from ...test_tokenization_common import TokenizerTesterMixin @require_tok...
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"""simple docstring""" import argparse import collections import numpy as np import torch from flax import traverse_util from tax import checkpoints from transformers import MTaConfig, UMTaEncoderModel, UMTaForConditionalGeneration from transformers.utils import logging logging.set_verbosity_in...
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"""simple docstring""" import gc import random import unittest import torch from diffusers import ( IFImgaImgPipeline, IFImgaImgSuperResolutionPipeline, IFInpaintingPipeline, IFInpaintingSuperResolutionPipeline, IFPipeline, IFSuperResolutionPipeline, ) from diffusers.mod...
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"""simple docstring""" import baseaa import io import json import os from copy import deepcopy from ..optimizer import AcceleratedOptimizer from ..scheduler import AcceleratedScheduler class lowerCamelCase__ : def __init__( self : Any , A_ : int ): ...
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"""simple docstring""" class lowerCamelCase__ : def __init__( self : Optional[Any] , A_ : Dict , A_ : str , A_ : Any ): '''simple docstring''' __lowercase = None __lowercase = ...
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"""simple docstring""" import argparse import csv import logging import os import random import numpy as np import torch from torch.utils.data import DataLoader, RandomSampler, SequentialSampler, TensorDataset from tqdm import tqdm, trange from transformers import ( CONFIG_NAME, WEIGHTS_...
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"""simple docstring""" from pathlib import Path import cva import numpy as np from matplotlib import pyplot as plt def lowerCAmelCase_ ( UpperCamelCase__ : np.ndarray , UpperCamelCase__ : np.ndarray , UpperCamelCase__ : np.ndarray , UpperCamelCase__ : int...
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"""simple docstring""" from typing import TYPE_CHECKING from ..utils import _LazyModule UpperCAmelCase__ ={ "config": [ "EXTERNAL_DATA_FORMAT_SIZE_LIMIT", "OnnxConfig", "OnnxConfigWithPast", "OnnxSeq2SeqConfigWithPast", "PatchingSpec", ], ...
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"""simple docstring""" from PIL import Image def lowerCAmelCase_ ( UpperCamelCase__ : Image , UpperCamelCase__ : int ): """simple docstring""" __lowercase = (259 * (level + 255)) / (255 * (259 - level)) def contrast(UpperCamelCase__ ...
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"""simple docstring""" from typing import Any import numpy as np def lowerCAmelCase_ ( UpperCamelCase__ : np.ndarray ): """simple docstring""" return np.array_equal(UpperCamelCase__ , matrix.conjugate().T ) def lowerCAmelCase_ ( UpperCamelCa...
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"""simple docstring""" import os import re import shutil import sys import tempfile import unittest import black UpperCAmelCase__ =os.path.abspath(os.path.dirname(os.path.dirname(os.path.dirname(__file__)))) sys.path.append(os.path.join(git_repo_path, "utils")) import check_copies # noqa:...
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"""simple docstring""" UpperCAmelCase__ ="Tobias Carryer" from time import time class lowerCamelCase__ : def __init__( self : List[Any] , A_ : Union[str, Any] , A_ : str , A_ : List[Any] , A_ : int=i...
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"""simple docstring""" from typing import Optional import torch import torch.utils.checkpoint from torch import Tensor, nn from torch.nn import BCEWithLogitsLoss, CrossEntropyLoss, MSELoss from ...activations import ACTaFN from ...file_utils import add_code_sample_docstrings, add_start_docstrings, ad...
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"""simple docstring""" def lowerCAmelCase_ ( UpperCamelCase__ : int , UpperCamelCase__ : int ): """simple docstring""" if a < 0 or b < 0: raise ValueError("""the value of both inputs must be positive""" ) __lowercase = str(bin(UpperCame...
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"""simple docstring""" from __future__ import annotations def lowerCAmelCase_ ( UpperCamelCase__ : list[float] , UpperCamelCase__ : Any ): """simple docstring""" print(f'''Vertex\tShortest Distance from vertex {src}''' ) for i, d in enumerate(Upp...
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"""simple docstring""" import unittest from transformers import ( MODEL_FOR_SEQUENCE_CLASSIFICATION_MAPPING, TF_MODEL_FOR_SEQUENCE_CLASSIFICATION_MAPPING, TextClassificationPipeline, pipeline, ) from transformers.testing_utils import is_pipeline_test, nested_simplify, require_tf, requi...
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"""simple docstring""" import os import time import warnings from dataclasses import dataclass, field from enum import Enum from typing import List, Optional, Union import torch from filelock import FileLock from torch.utils.data import Dataset from ...tokenization_utils_base import PreTrainedToke...
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"""simple docstring""" from __future__ import annotations def lowerCAmelCase_ ( UpperCamelCase__ : list , UpperCamelCase__ : int | None = None , UpperCamelCase__ : int | None = None ): """simple docstring""" if start is None: __lowercas...
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"""simple docstring""" from collections import OrderedDict from typing import Any, List, Mapping, Optional from ... import PreTrainedTokenizer, TensorType, is_torch_available from ...configuration_utils import PretrainedConfig from ...onnx import OnnxConfigWithPast, PatchingSpec from ...utils import log...
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"""simple docstring""" import unittest import numpy as np from transformers import BertConfig, is_flax_available from transformers.testing_utils import require_flax, slow from ...test_modeling_flax_common import FlaxModelTesterMixin, floats_tensor, ids_tensor, random_attention_mask if is_flax_av...
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"""simple docstring""" import pytest import requests from datasets.utils.file_utils import http_head from .utils import OfflineSimulationMode, RequestWouldHangIndefinitelyError, offline @pytest.mark.integration def lowerCAmelCase_ ( ): """simple docstring""" wit...
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"""simple docstring""" import functools import operator from ...configuration_utils import PretrainedConfig from ...utils import logging UpperCAmelCase__ =logging.get_logger(__name__) UpperCAmelCase__ ={ "microsoft/unispeech-large-1500h-cv": ( "https://huggingface.co/microsof...
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"""simple docstring""" def lowerCAmelCase_ ( UpperCamelCase__ : list , UpperCamelCase__ : int , UpperCamelCase__ : int = 0 , UpperCamelCase__ : int = 0 ): """simple docstring""" __lowercase = right or len(UpperCamelCase__ ...
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"""simple docstring""" import time import warnings from abc import ABC from copy import deepcopy from typing import Optional import torch from ..utils import add_start_docstrings, logging UpperCAmelCase__ =logging.get_logger(__name__) UpperCAmelCase__ =R"\n Args:\n input_i...
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"""simple docstring""" import json import os from pathlib import Path from shutil import copyfile from typing import Any, Dict, List, Optional, Tuple, Union import sentencepiece from ...tokenization_utils import BatchEncoding, PreTrainedTokenizer from ...utils import logging UpperCAmelCase__ ...
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"""simple docstring""" UpperCAmelCase__ =0 # The first color of the flag. UpperCAmelCase__ =1 # The second color of the flag. UpperCAmelCase__ =2 # The third color of the flag. UpperCAmelCase__ =(red, white, blue) def lowerCAmelCase_ ( UpperCamelCase__ : list ): ...
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"""simple docstring""" import copy from typing import TYPE_CHECKING, Any, Mapping, Optional, OrderedDict from packaging import version from ...configuration_utils import PretrainedConfig from ...onnx import OnnxConfig from ...utils import logging from ..auto.configuration_auto import AutoConfig ...
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"""simple docstring""" import itertools import random import unittest import numpy as np from transformers import BatchFeature, SpeechTaFeatureExtractor from transformers.testing_utils import require_torch from transformers.utils.import_utils import is_torch_available from ...test_sequence_feature...
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"""simple docstring""" import time from dataclasses import dataclass from multiprocessing import Pool from unittest import TestCase from unittest.mock import patch import multiprocess import numpy as np import pytest from datasets.utils.py_utils import ( NestedDataStructure, asdict, ...
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"""simple docstring""" import numpy as np def lowerCAmelCase_ ( UpperCamelCase__ : np.array ): """simple docstring""" return (2 / (1 + np.exp(-2 * vector ))) - 1 if __name__ == "__main__": import doctest doctest.testmod()
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"""simple docstring""" from typing import Optional from urllib.parse import quote import huggingface_hub as hfh from packaging import version def lowerCAmelCase_ ( UpperCamelCase__ : str , UpperCamelCase__ : str , UpperCamelCase__ : Optional[str] = None ): ...
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"""simple docstring""" from __future__ import annotations from math import pi # Define the Reduced Planck Constant ℏ (H bar), speed of light C, value of # Pi and the function UpperCAmelCase__ =1.0_54_57_18_17e-34 # unit of ℏ : J * s UpperCAmelCase__ =3e8 # unit of c : m * s^-1 def low...
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"""simple docstring""" def lowerCAmelCase_ ( UpperCamelCase__ : Union[str, Any] , UpperCamelCase__ : Union[str, Any] , UpperCamelCase__ : int ): """simple docstring""" if n == 0: return 1 elif n % 2 == 1: return (binary_exponentiation...
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"""simple docstring""" from numpy import exp, pi, sqrt def lowerCAmelCase_ ( UpperCamelCase__ : Dict , UpperCamelCase__ : float = 0.0 , UpperCamelCase__ : float = 1.0 ): """simple docstring""" return 1 / sqrt(2 * pi * sigma**2 ) * exp(-(...
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"""simple docstring""" 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...
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"""simple docstring""" from ...processing_utils import ProcessorMixin class lowerCamelCase__ ( _a ): a : Optional[int] = """SpeechT5FeatureExtractor""" a : Tuple = """SpeechT5Tokenizer""" def __init__( self : Union[str, Any] , ...
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"""simple docstring""" import unittest import numpy as np from transformers.testing_utils import require_flax, require_tf, require_torch from transformers.utils import ( expand_dims, flatten_dict, is_flax_available, is_tf_available, is_torch_available, reshape, squeeze...
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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, VisionEncoderDecoderModel...
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"""simple docstring""" def lowerCAmelCase_ ( UpperCamelCase__ : int , UpperCamelCase__ : int ): """simple docstring""" return x if y == 0 else greatest_common_divisor(UpperCamelCase__ , x % y ) def lowerCAmelCase_ ( UpperCamelCase__ ...
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"""simple docstring""" import argparse from collections import defaultdict import yaml UpperCAmelCase__ ="docs/source/en/_toctree.yml" def lowerCAmelCase_ ( UpperCamelCase__ : List[Any] ): """simple docstring""" __lowercase = defaultdict(...
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"""simple docstring""" import argparse import logging from collections import namedtuple import torch from model_bertabs import BertAbsSummarizer from models.model_builder import AbsSummarizer # The authors' implementation from transformers import BertTokenizer logging.basicConfig(level=logging...
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"""simple docstring""" from ...configuration_utils import PretrainedConfig from ...utils import logging UpperCAmelCase__ =logging.get_logger(__name__) UpperCAmelCase__ ={ "uclanlp/visualbert-vqa": "https://huggingface.co/uclanlp/visualbert-vqa/resolve/main/config.json", "uclanlp/visu...
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"""simple docstring""" def lowerCAmelCase_ ( UpperCamelCase__ : int ): """simple docstring""" assert ( isinstance(UpperCamelCase__ , UpperCamelCase__ ) and number_of_steps > 0 ), f'''number_of_steps needs to be positive integer, your input {number_of_s...
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"""simple docstring""" # Copyright 2023 The HuggingFace Team. All rights reserved. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENS...
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"""simple docstring""" import unittest from transformers import BarthezTokenizer, BarthezTokenizerFast, BatchEncoding from transformers.testing_utils import require_sentencepiece, require_tokenizers, require_torch, slow from ...test_tokenization_common import TokenizerTesterMixin @require_tok...
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"""simple docstring""" from typing import TYPE_CHECKING from ...utils import ( OptionalDependencyNotAvailable, _LazyModule, is_tf_available, is_torch_available, is_vision_available, ) UpperCAmelCase__ ={ "configuration_efficientformer": [ "EFFICIENTFORMER_PRE...
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"""simple docstring""" import gc import random import unittest import torch from diffusers import ( IFImgaImgPipeline, IFImgaImgSuperResolutionPipeline, IFInpaintingPipeline, IFInpaintingSuperResolutionPipeline, IFPipeline, IFSuperResolutionPipeline, ) from diffusers.mod...
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"""simple docstring""" from typing import Optional from urllib.parse import quote import huggingface_hub as hfh from packaging import version def lowerCAmelCase_ ( UpperCamelCase__ : str , UpperCamelCase__ : str , UpperCamelCase__ : Optional[str] = None ): ...
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"""simple docstring""" class lowerCamelCase__ : def __init__( self : Optional[Any] , A_ : Dict , A_ : str , A_ : Any ): '''simple docstring''' __lowercase = None __lowercase = ...
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"""simple docstring""" from collections import OrderedDict from typing import Any, List, Mapping, Optional from ... import PreTrainedTokenizer, TensorType, is_torch_available from ...configuration_utils import PretrainedConfig from ...onnx import OnnxConfigWithPast, PatchingSpec from ...utils import log...
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"""simple docstring""" from pathlib import Path import cva import numpy as np from matplotlib import pyplot as plt def lowerCAmelCase_ ( UpperCamelCase__ : np.ndarray , UpperCamelCase__ : np.ndarray , UpperCamelCase__ : np.ndarray , UpperCamelCase__ : int...
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"""simple docstring""" import inspect import re from hashlib import shaaaa from typing import Dict, List from .arrow import arrow from .audiofolder import audiofolder from .csv import csv from .imagefolder import imagefolder from .json import json from .pandas import pandas from .parquet import par...
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"""simple docstring""" from PIL import Image def lowerCAmelCase_ ( UpperCamelCase__ : Image , UpperCamelCase__ : int ): """simple docstring""" __lowercase = (259 * (level + 255)) / (255 * (259 - level)) def contrast(UpperCamelCase__ ...
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"""simple docstring""" 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_...
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"""simple docstring""" import os import re import shutil import sys import tempfile import unittest import black UpperCAmelCase__ =os.path.abspath(os.path.dirname(os.path.dirname(os.path.dirname(__file__)))) sys.path.append(os.path.join(git_repo_path, "utils")) import check_copies # noqa:...
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"""simple docstring""" import argparse from tax import checkpoints from transformers import AutoConfig, FlaxAutoModelForSeqaSeqLM def lowerCAmelCase_ ( UpperCamelCase__ : Any , UpperCamelCase__ : Optional[int] , UpperCamelCase__ : str ): """simple d...
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"""simple docstring""" from typing import Optional import torch import torch.utils.checkpoint from torch import Tensor, nn from torch.nn import BCEWithLogitsLoss, CrossEntropyLoss, MSELoss from ...activations import ACTaFN from ...file_utils import add_code_sample_docstrings, add_start_docstrings, ad...
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"""simple docstring""" from typing import Tuple, Union from ...modeling_outputs import BackboneOutput from ...modeling_utils import PreTrainedModel from ...utils import is_timm_available, is_torch_available, requires_backends from ...utils.backbone_utils import BackboneMixin from .configuration_timm_bac...
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"""simple docstring""" from __future__ import annotations def lowerCAmelCase_ ( UpperCamelCase__ : list[float] , UpperCamelCase__ : Any ): """simple docstring""" print(f'''Vertex\tShortest Distance from vertex {src}''' ) for i, d in enumerate(Upp...
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"""simple docstring""" import logging import os import sys from dataclasses import dataclass, field from typing import Optional import torch from datasets import load_dataset from torchvision.transforms import Compose, Lambda, Normalize, RandomHorizontalFlip, RandomResizedCrop, ToTensor from torchvis...
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"""simple docstring""" import os import time import warnings from dataclasses import dataclass, field from enum import Enum from typing import List, Optional, Union import torch from filelock import FileLock from torch.utils.data import Dataset from ...tokenization_utils_base import PreTrainedToke...
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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_common import C...
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"""simple docstring""" from collections import OrderedDict from typing import Any, List, Mapping, Optional from ... import PreTrainedTokenizer, TensorType, is_torch_available from ...configuration_utils import PretrainedConfig from ...onnx import OnnxConfigWithPast, PatchingSpec from ...utils import log...
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"""simple docstring""" from maths.prime_factors import prime_factors def lowerCAmelCase_ ( UpperCamelCase__ : int ): """simple docstring""" if not isinstance(UpperCamelCase__ , UpperCamelCase__ ): __lowercase = f'''Input value of [number={num...
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"""simple docstring""" import pytest import requests from datasets.utils.file_utils import http_head from .utils import OfflineSimulationMode, RequestWouldHangIndefinitelyError, offline @pytest.mark.integration def lowerCAmelCase_ ( ): """simple docstring""" wit...
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"""simple docstring""" from typing import TYPE_CHECKING from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available UpperCAmelCase__ ={ "configuration_pegasus_x": ["PEGASUS_X_PRETRAINED_CONFIG_ARCHIVE_MAP", "PegasusXConfig"], } try: if not is_torch_availabl...
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"""simple docstring""" def lowerCAmelCase_ ( UpperCamelCase__ : list , UpperCamelCase__ : int , UpperCamelCase__ : int = 0 , UpperCamelCase__ : int = 0 ): """simple docstring""" __lowercase = right or len(UpperCamelCase__ ...
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"""simple docstring""" from ...configuration_utils import PretrainedConfig from ...utils import logging UpperCAmelCase__ =logging.get_logger(__name__) UpperCAmelCase__ ={ "caidas/swin2sr-classicalsr-x2-64": ( "https://huggingface.co/caidas/swin2sr-classicalsr-x2-64/resolve/main/c...
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"""simple docstring""" import json import os from pathlib import Path from shutil import copyfile from typing import Any, Dict, List, Optional, Tuple, Union import sentencepiece from ...tokenization_utils import BatchEncoding, PreTrainedTokenizer from ...utils import logging UpperCAmelCase__ ...
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"""simple docstring""" import numpy as np def lowerCAmelCase_ ( UpperCamelCase__ : np.array ): """simple docstring""" return 1 / (1 + np.exp(-vector )) if __name__ == "__main__": import doctest doctest.testmod()
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"""simple docstring""" import copy from typing import TYPE_CHECKING, Any, Mapping, Optional, OrderedDict from packaging import version from ...configuration_utils import PretrainedConfig from ...onnx import OnnxConfig from ...utils import logging from ..auto.configuration_auto import AutoConfig ...
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"""simple docstring""" def lowerCAmelCase_ ( UpperCamelCase__ : list[int] ): """simple docstring""" if not nums: # Makes sure that the list is not empty raise ValueError("""List is empty""" ) __lowercase = sum(UpperCamelCase__ ) / len(UpperCame...
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"""simple docstring""" import time from dataclasses import dataclass from multiprocessing import Pool from unittest import TestCase from unittest.mock import patch import multiprocess import numpy as np import pytest from datasets.utils.py_utils import ( NestedDataStructure, asdict, ...
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"""simple docstring""" from collections import OrderedDict from typing import TYPE_CHECKING, Any, Mapping, Optional from ...configuration_utils import PretrainedConfig from ...onnx import OnnxConfig from ...utils import logging if TYPE_CHECKING: from ... import FeatureExtractionMixin, Tensor...
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"""simple docstring""" from typing import Optional from urllib.parse import quote import huggingface_hub as hfh from packaging import version def lowerCAmelCase_ ( UpperCamelCase__ : str , UpperCamelCase__ : str , UpperCamelCase__ : Optional[str] = None ): ...
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"""simple docstring""" import asyncio import os import re import sys import tempfile import unittest from contextlib import contextmanager from copy import deepcopy from distutils.util import strtobool from enum import Enum from importlib.util import find_spec from pathlib import Path from unittest...
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"""simple docstring""" def lowerCAmelCase_ ( UpperCamelCase__ : Union[str, Any] , UpperCamelCase__ : Union[str, Any] , UpperCamelCase__ : int ): """simple docstring""" if n == 0: return 1 elif n % 2 == 1: return (binary_exponentiation...
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"""simple docstring""" from typing import TYPE_CHECKING from ...utils import ( OptionalDependencyNotAvailable, _LazyModule, is_tf_available, is_torch_available, is_vision_available, ) UpperCAmelCase__ ={ "configuration_convnext": ["CONVNEXT_PRETRAINED_CONFIG_ARCHIVE_M...
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"""simple docstring""" 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...
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"""simple docstring""" import logging import os from .state import PartialState class lowerCamelCase__ ( logging.LoggerAdapter ): @staticmethod def SCREAMING_SNAKE_CASE_ ( A_ : Dict ): '''simple docstring''' __lowercase ...
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"""simple docstring""" import unittest import numpy as np from transformers.testing_utils import require_flax, require_tf, require_torch from transformers.utils import ( expand_dims, flatten_dict, is_flax_available, is_tf_available, is_torch_available, reshape, squeeze...
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"""simple docstring""" import unittest from transformers import BarthezTokenizer, BarthezTokenizerFast, BatchEncoding from transformers.testing_utils import require_sentencepiece, require_tokenizers, require_torch, slow from ...test_tokenization_common import TokenizerTesterMixin @require_tok...
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"""simple docstring""" def lowerCAmelCase_ ( UpperCamelCase__ : int , UpperCamelCase__ : int ): """simple docstring""" return x if y == 0 else greatest_common_divisor(UpperCamelCase__ , x % y ) def lowerCAmelCase_ ( UpperCamelCase__ ...
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"""simple docstring""" import os from tempfile import TemporaryDirectory from unittest import TestCase import pytest from absl.testing import parameterized from datasets import config from datasets.arrow_reader import HF_GCP_BASE_URL from datasets.builder import DatasetBuilder from datasets.dataset...
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"""simple docstring""" import argparse import logging from collections import namedtuple import torch from model_bertabs import BertAbsSummarizer from models.model_builder import AbsSummarizer # The authors' implementation from transformers import BertTokenizer logging.basicConfig(level=logging...
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"""simple docstring""" def lowerCAmelCase_ ( UpperCamelCase__ : str , UpperCamelCase__ : str = " " ): """simple docstring""" __lowercase = [] __lowercase = 0 for index, char in enumerate(UpperCamelCase__ ): if char == separa...
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"""simple docstring""" def lowerCAmelCase_ ( UpperCamelCase__ : int ): """simple docstring""" assert ( isinstance(UpperCamelCase__ , UpperCamelCase__ ) and number_of_steps > 0 ), f'''number_of_steps needs to be positive integer, your input {number_of_s...
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"""simple docstring""" import qiskit def lowerCAmelCase_ ( UpperCamelCase__ : int = 2 ): """simple docstring""" __lowercase = qubits # Using Aer's simulator __lowercase = qiskit.Aer.get_backend("""aer_simulator""" ) # Creating a ...
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"""simple docstring""" import unittest from transformers import BarthezTokenizer, BarthezTokenizerFast, BatchEncoding from transformers.testing_utils import require_sentencepiece, require_tokenizers, require_torch, slow from ...test_tokenization_common import TokenizerTesterMixin @require_tok...
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"""simple docstring""" import importlib import sys from argparse import REMAINDER, ArgumentParser from pathlib import Path import torch_xla.distributed.xla_multiprocessing as xmp def lowerCAmelCase_ ( ): """simple docstring""" __lowercase = ArgumentParse...
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"""simple docstring""" import gc import random import unittest import torch from diffusers import ( IFImgaImgPipeline, IFImgaImgSuperResolutionPipeline, IFInpaintingPipeline, IFInpaintingSuperResolutionPipeline, IFPipeline, IFSuperResolutionPipeline, ) from diffusers.mod...
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"""simple docstring""" UpperCAmelCase__ =6_5521 def lowerCAmelCase_ ( UpperCamelCase__ : str ): """simple docstring""" __lowercase = 1 __lowercase = 0 for plain_chr in plain_text: __lowercase = (a + ord(UpperCamelCase__ ...
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"""simple docstring""" class lowerCamelCase__ : def __init__( self : Optional[Any] , A_ : Dict , A_ : str , A_ : Any ): '''simple docstring''' __lowercase = None __lowercase = ...
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"""simple docstring""" from itertools import product def lowerCAmelCase_ ( UpperCamelCase__ : int , UpperCamelCase__ : int ): """simple docstring""" __lowercase = sides_number __lowercase = max_face_number * dice_number __lowe...
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"""simple docstring""" from pathlib import Path import cva import numpy as np from matplotlib import pyplot as plt def lowerCAmelCase_ ( UpperCamelCase__ : np.ndarray , UpperCamelCase__ : np.ndarray , UpperCamelCase__ : np.ndarray , UpperCamelCase__ : int...
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"""simple docstring""" import argparse import os import re import tensorflow as tf import torch from transformers import BertConfig, BertModel from transformers.utils import logging logging.set_verbosity_info() UpperCAmelCase__ =logging.get_logger(__name__) def lowerCAmelCase_ ( ...
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"""simple docstring""" from PIL import Image def lowerCAmelCase_ ( UpperCamelCase__ : Image , UpperCamelCase__ : int ): """simple docstring""" __lowercase = (259 * (level + 255)) / (255 * (259 - level)) def contrast(UpperCamelCase__ ...
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"""simple docstring""" import flax.linen as nn import jax import jax.numpy as jnp class lowerCamelCase__ ( nn.Module ): a : int a : jnp.dtype = jnp.floataa def SCREAMING_SNAKE_CASE_ ( self : List[Any] ): '''simpl...
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"""simple docstring""" import os import re import shutil import sys import tempfile import unittest import black UpperCAmelCase__ =os.path.abspath(os.path.dirname(os.path.dirname(os.path.dirname(__file__)))) sys.path.append(os.path.join(git_repo_path, "utils")) import check_copies # noqa:...
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"""simple docstring""" from arguments import InitializationArguments from transformers import AutoConfig, AutoModelForCausalLM, AutoTokenizer, HfArgumentParser # Configuration UpperCAmelCase__ =HfArgumentParser(InitializationArguments) UpperCAmelCase__ =parser.parse_args() # Load codeparro...
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"""simple docstring""" from typing import Optional import torch import torch.utils.checkpoint from torch import Tensor, nn from torch.nn import BCEWithLogitsLoss, CrossEntropyLoss, MSELoss from ...activations import ACTaFN from ...file_utils import add_code_sample_docstrings, add_start_docstrings, ad...
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"""simple docstring""" # Author: OMKAR PATHAK, Nwachukwu Chidiebere # Use a Python dictionary to construct the graph. from __future__ import annotations from pprint import pformat from typing import Generic, TypeVar UpperCAmelCase__ =TypeVar("T") class lowerCamelCase__ ( Generic[...
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"""simple docstring""" from __future__ import annotations def lowerCAmelCase_ ( UpperCamelCase__ : list[float] , UpperCamelCase__ : Any ): """simple docstring""" print(f'''Vertex\tShortest Distance from vertex {src}''' ) for i, d in enumerate(Upp...
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"""simple docstring""" from __future__ import annotations def lowerCAmelCase_ ( UpperCamelCase__ : list[float] , UpperCamelCase__ : list[float] ): """simple docstring""" __lowercase = sorted(numsa + numsa ) __lowercase , __lowercase...
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"""simple docstring""" import os import time import warnings from dataclasses import dataclass, field from enum import Enum from typing import List, Optional, Union import torch from filelock import FileLock from torch.utils.data import Dataset from ...tokenization_utils_base import PreTrainedToke...
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"""simple docstring""" from __future__ import annotations UpperCAmelCase__ =8.9_88e9 # units = N * m^s * C^-2 def lowerCAmelCase_ ( UpperCamelCase__ : float , UpperCamelCase__ : float , UpperCamelCase__ : float , UpperCamelCase__ : float ): ...
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"""simple docstring""" from collections import OrderedDict from typing import Any, List, Mapping, Optional from ... import PreTrainedTokenizer, TensorType, is_torch_available from ...configuration_utils import PretrainedConfig from ...onnx import OnnxConfigWithPast, PatchingSpec from ...utils import log...
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