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"""simple docstring""" import unittest from diffusers.models.unet_ad_blocks import * # noqa F403 from diffusers.utils import torch_device from .test_unet_blocks_common import UNetBlockTesterMixin class _UpperCamelCase ( __lowercase ,unittest.TestCase ): '''simple docstring''' __...
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'''simple docstring''' import gc import unittest import numpy as np import torch from diffusers import StableDiffusionKDiffusionPipeline from diffusers.utils import slow, torch_device from diffusers.utils.testing_utils import enable_full_determinism, require_torch_gpu enable_full_determini...
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import argparse import os import evaluate import torch from datasets import load_dataset from torch.optim import AdamW from torch.utils.data import DataLoader from transformers import AutoModelForSequenceClassification, AutoTokenizer, get_linear_schedule_with_warmup, set_seed from accelerate import Accelerator...
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'''simple docstring''' # Copyright (c) 2021-, NVIDIA CORPORATION. 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/lice...
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import json import os import unittest from transformers import BatchEncoding, LEDTokenizer, LEDTokenizerFast from transformers.models.led.tokenization_led import VOCAB_FILES_NAMES from transformers.testing_utils import require_tokenizers, require_torch from transformers.utils import cached_property from .....
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'''simple docstring''' from __future__ import annotations from typing import Any class UpperCAmelCase_ : def __init__( self : Optional[int] , UpperCAmelCase__ : int , UpperCAmelCase__ : int , UpperCAmelCase__ : ...
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import inspect import unittest from transformers import ViTConfig from transformers.testing_utils import ( require_accelerate, require_torch, require_torch_gpu, require_vision, slow, torch_device, ) from transformers.utils import cached_property, is_torch_available, is_v...
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'''simple docstring''' class UpperCAmelCase_ : def __init__( self : List[str] , UpperCAmelCase__ : list[int] ) -> None: lowerCAmelCase = len(UpperCAmelCase__ ) lowerCAmelCase = [0] * len_array if len_a...
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"""simple docstring""" import unittest from .lib import ( Matrix, Vector, axpy, square_zero_matrix, unit_basis_vector, zero_vector, ) class UpperCAmelCase (unittest.TestCase ): """simple docstring""" def _snake_case ( self ): lowercase__: Union[s...
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'''simple docstring''' def a_ ( lowerCamelCase : Optional[Any] ): return [ { 0: [1, 2], 1: [0, 2], 2: [0, 1, 3, 5], 3: [2, 4], 4: [3], 5: [2, 6, 8], 6: [5, 7], 7: [6, 8], 8:...
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"""simple docstring""" from __future__ import annotations from typing import Any def a__ ( __SCREAMING_SNAKE_CASE ) -> Optional[Any]: if not postfix_notation: return 0 __lowerCAmelCase: Optional[int] = {"+", "-", "*", "/"} __lowerCAmelCase: Tuple...
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'''simple docstring''' import argparse from collections import OrderedDict from pathlib import Path import requests import torch from PIL import Image from transformers import GLPNConfig, GLPNForDepthEstimation, GLPNImageProcessor from transformers.utils import logging logging.set_verbosi...
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"""simple docstring""" from abc import ABC, abstractmethod from argparse import ArgumentParser class _UpperCAmelCase ( __lowercase ): @staticmethod @abstractmethod def a ( _lowercase : ArgumentParser ): raise NotImplementedError() @abstractmethod def ...
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'''simple docstring''' import unittest from transformers import is_torch_available from transformers.testing_utils import require_sentencepiece, require_tokenizers, require_torch, slow if is_torch_available(): import torch from transformers import XLMRobertaModel @require_se...
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"""simple docstring""" from itertools import product from cva import COLOR_BGR2GRAY, cvtColor, imread, imshow, waitKey from numpy import dot, exp, mgrid, pi, ravel, square, uinta, zeros def lowercase ( _SCREAMING_SNAKE_CASE : List[str] , _SCREAMING_SNAKE_CASE ...
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'''simple docstring''' import multiprocessing import time from arguments import PretokenizationArguments from datasets import load_dataset from transformers import AutoTokenizer, HfArgumentParser def a_ ( lowerCamelCase : Dict ): lowerCAmelCase = {} lowerCAmel...
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from typing import TYPE_CHECKING from ...utils import ( OptionalDependencyNotAvailable, _LazyModule, is_sentencepiece_available, is_tf_available, is_tokenizers_available, is_torch_available, ) a ={ """configuration_rembert""": ["""REMBERT_PRETRAINED_CONFIG_ARCHIVE_MAP"""...
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'''simple docstring''' import logging from dataclasses import dataclass, field from pathlib import Path from typing import Optional, Union from .generation.configuration_utils import GenerationConfig from .training_args import TrainingArguments from .utils import add_start_docstrings __snake...
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from typing import List import numpy as np def __lowerCamelCase ( lowerCamelCase__ : dict ): '''simple docstring''' lowerCamelCase = {key: len(lowerCamelCase__ ) for key, value in gen_kwargs.items() if isinstance(lowerCamelCase__ , lowerCamelCase__ )} if len(set(...
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'''simple docstring''' import argparse import torch from transformers import ( EncodecConfig, EncodecFeatureExtractor, EncodecModel, logging, ) # checkpoints downloaded from: # https://dl.fbaipublicfiles.com/encodec/v0/encodec_24khz-d7cc33bc.th # https://huggingface.co/f...
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"""simple docstring""" import math from dataclasses import dataclass from typing import List, Optional, Tuple, Union import numpy as np import torch from diffusers.configuration_utils import ConfigMixin, register_to_config from diffusers.schedulers.scheduling_utils import SchedulerMixin from dif...
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'''simple docstring''' import warnings from ...utils import logging from .image_processing_flava import FlavaImageProcessor __snake_case =logging.get_logger(__name__) class UpperCAmelCase_ ( __lowercase ): def __init__( self : Dict , *Upper...
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"""simple docstring""" import json import os import shutil import tempfile import unittest import numpy as np import pytest from transformers import CLIPTokenizer, CLIPTokenizerFast from transformers.models.clip.tokenization_clip import VOCAB_FILES_NAMES from transformers.testing_utils import require_vision from...
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'''simple docstring''' from typing import List, Optional from tokenizers import ByteLevelBPETokenizer from ...tokenization_utils_fast import PreTrainedTokenizerFast from ...utils import logging from .tokenization_blenderbot_small import BlenderbotSmallTokenizer __snake_case =logging...
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def _a ( UpperCamelCase_ : Dict ) -> Any: """simple docstring""" lowerCAmelCase__ = len(UpperCamelCase_ ) while cur > 1: # Find the maximum number in arr lowerCAmelCase__ = arr.index(max(arr[0:cur] ) ...
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'''simple docstring''' from ...configuration_utils import PretrainedConfig from ...utils import logging __snake_case =logging.get_logger(__name__) __snake_case ={ """facebook/s2t-wav2vec2-large-en-de""": ( """https://huggingface.co/facebook/s2t-wav2vec2-large-en-d...
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import logging import torch from torch import nn from torch.nn import CrossEntropyLoss, MSELoss from transformers.file_utils import add_start_docstrings, add_start_docstrings_to_model_forward from transformers.models.bert.modeling_bert import ( BERT_INPUTS_DOCSTRING, BERT_START_DOCSTRING, Bert...
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'''simple docstring''' from __future__ import annotations from bisect import bisect_left from functools import total_ordering from heapq import merge @total_ordering class UpperCAmelCase_ ( __lowercase ): def __lt__( self : Optional[int] , UpperCAmelCa...
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import inspect import os import unittest import torch import accelerate from accelerate import Accelerator from accelerate.test_utils import execute_subprocess_async, require_multi_gpu from accelerate.utils import patch_environment class lowercase__ ( unittest.TestCase )...
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'''simple docstring''' import datasets from .nmt_bleu import compute_bleu # From: https://github.com/tensorflow/nmt/blob/master/nmt/scripts/bleu.py __snake_case ="""\ @INPROCEEDINGS{Papineni02bleu:a, author = {Kishore Papineni and Salim Roukos and Todd Ward and Wei-jing Zhu}, ti...
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"""simple docstring""" from ...configuration_utils import PretrainedConfig from ...utils import logging __A = logging.get_logger(__name__) __A = { "facebook/dpr-ctx_encoder-single-nq-base": ( "https://huggingface.co/facebook/dpr-ctx_encoder-single-nq-base/resolve/main/config.json" ), ...
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'''simple docstring''' from sklearn.metrics import fa_score, matthews_corrcoef import datasets from .record_evaluation import evaluate as evaluate_record __snake_case ="""\ @article{wang2019superglue, title={SuperGLUE: A Stickier Benchmark for General-Purpose Language Understanding ...
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"""simple docstring""" from typing import TYPE_CHECKING from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available __A = { "configuration_git": ["GIT_PRETRAINED_CONFIG_ARCHIVE_MAP", "GitConfig", "GitVisionConfig"], "processing_git": ["GitProcessor"], } ...
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'''simple docstring''' print((lambda quine: quine % quine)("""print((lambda quine: quine %% quine)(%r))"""))
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"""simple docstring""" import unittest 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_inputs ...
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'''simple docstring''' import os __snake_case ={"""I""": 1, """V""": 5, """X""": 10, """L""": 50, """C""": 100, """D""": 500, """M""": 1_000} def a_ ( lowerCamelCase : str ): lowerCAmelCase = 0 lowerCAmelCase = 0 while index < len(lowerCamelCas...
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"""simple docstring""" import argparse import torch from ...utils import logging from . import AlbertConfig, AlbertForPreTraining, load_tf_weights_in_albert logging.set_verbosity_info() def lowercase ( _SCREAMING_SNAKE_CASE : Tuple , _SCREAMING_SNAKE_CASE ...
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'''simple docstring''' import itertools import random import unittest import numpy as np from transformers import ASTFeatureExtractor from transformers.testing_utils import require_torch, require_torchaudio from transformers.utils.import_utils import is_torch_available from ...test_sequence_...
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import warnings from .generation import TFGenerationMixin class A_ ( __lowercase ): # warning at import time warnings.warn( '''Importing `TFGenerationMixin` from `src/transformers/generation_tf_utils.py` is deprecated and will ''' '''be remove...
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'''simple docstring''' import pickle import unittest import torch from accelerate import Accelerator from accelerate.state import AcceleratorState from accelerate.test_utils import require_cpu @require_cpu class UpperCAmelCase_ ( unittest.TestCase ): def __Upp...
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import unittest from queue import Empty from threading import Thread from transformers import AutoTokenizer, TextIteratorStreamer, TextStreamer, is_torch_available from transformers.testing_utils import CaptureStdout, require_torch, torch_device from ..test_modeling_common import ids_tensor if is_torch_available...
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'''simple docstring''' import json from typing import TYPE_CHECKING, List, Optional, Tuple from tokenizers import pre_tokenizers, processors from ...tokenization_utils_base import AddedToken, BatchEncoding from ...tokenization_utils_fast import PreTrainedTokenizerFast from ...utils import loggin...
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"""simple docstring""" import copy import tempfile import unittest from huggingface_hub import HfFolder, delete_repo from parameterized import parameterized from requests.exceptions import HTTPError from transformers import AutoConfig, GenerationConfig from transformers.testing_utils import TOKE...
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'''simple docstring''' from __future__ import annotations from statistics import mean def a_ ( lowerCamelCase : list[int] , lowerCamelCase : list[int] , lowerCamelCase : int ): lowerCAmelCase = [0] * no_of_processes lowerCAmelCase = [0] * no_of_proces...
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"""simple docstring""" import json import os import unittest from transformers import DebertaTokenizer, DebertaTokenizerFast from transformers.models.deberta.tokenization_deberta import VOCAB_FILES_NAMES from transformers.testing_utils import slow from ...test_tokenization_common import TokenizerTesterMixin clas...
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'''simple docstring''' import gc import unittest import numpy as np import torch from diffusers import StableDiffusionKDiffusionPipeline from diffusers.utils import slow, torch_device from diffusers.utils.testing_utils import enable_full_determinism, require_torch_gpu enable_full_determini...
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import os def _a ( ) -> Dict: """simple docstring""" lowerCAmelCase__ = os.path.join(os.path.dirname(UpperCamelCase_ ) , "num.txt" ) with open(UpperCamelCase_ ) as file_hand: return str(sum(int(UpperCamelCase_ ) fo...
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'''simple docstring''' # Copyright (c) 2021-, NVIDIA CORPORATION. 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/lice...
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from collections import Counter import numpy as np from sklearn import datasets from sklearn.model_selection import train_test_split __lowerCAmelCase : Dict = datasets.load_iris() __lowerCAmelCase : Union[str, Any] = np.array(data['data']) __lowerCAmelCase : int ...
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'''simple docstring''' from __future__ import annotations from typing import Any class UpperCAmelCase_ : def __init__( self : Optional[int] , UpperCAmelCase__ : int , UpperCAmelCase__ : int , UpperCAmelCase__ : ...
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import argparse import requests import torch from PIL import Image from transformers import SwinConfig, SwinForMaskedImageModeling, ViTImageProcessor def lowerCAmelCase_ ( __UpperCAmelCase: Optional[int] ) -> List[Any]: UpperCamelCase__ : Any = ...
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'''simple docstring''' class UpperCAmelCase_ : def __init__( self : List[str] , UpperCAmelCase__ : list[int] ) -> None: lowerCAmelCase = len(UpperCAmelCase__ ) lowerCAmelCase = [0] * len_array if len_a...
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"""simple docstring""" import argparse import torch from transformers import ( EncodecConfig, EncodecFeatureExtractor, EncodecModel, logging, ) # checkpoints downloaded from: # https://dl.fbaipublicfiles.com/encodec/v0/encodec_24khz-d7cc33bc.th # https://huggingface.co/facebook/musicgen-small/...
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'''simple docstring''' def a_ ( lowerCamelCase : Optional[Any] ): return [ { 0: [1, 2], 1: [0, 2], 2: [0, 1, 3, 5], 3: [2, 4], 4: [3], 5: [2, 6, 8], 6: [5, 7], 7: [6, 8], 8:...
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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 ..auto import CONFIG_MAPPING __A = logging.get_logger...
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'''simple docstring''' import argparse from collections import OrderedDict from pathlib import Path import requests import torch from PIL import Image from transformers import GLPNConfig, GLPNForDepthEstimation, GLPNImageProcessor from transformers.utils import logging logging.set_verbosi...
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"""simple docstring""" from typing import TYPE_CHECKING from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available _lowercase : str = { 'configuration_lilt': ['LILT_PRETRAINED_CONFIG_ARCHIVE_MAP', 'LiltConfig'], } try: if not is_torch_available()...
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'''simple docstring''' import unittest from transformers import is_torch_available from transformers.testing_utils import require_sentencepiece, require_tokenizers, require_torch, slow if is_torch_available(): import torch from transformers import XLMRobertaModel @require_se...
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"""simple docstring""" import unittest from transformers import AlbertTokenizer, AlbertTokenizerFast from transformers.testing_utils import get_tests_dir, require_sentencepiece, require_tokenizers, slow from ...test_tokenization_common import TokenizerTesterMixin __A : Optional[Any] ...
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'''simple docstring''' import multiprocessing import time from arguments import PretokenizationArguments from datasets import load_dataset from transformers import AutoTokenizer, HfArgumentParser def a_ ( lowerCamelCase : Dict ): lowerCAmelCase = {} lowerCAmel...
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import argparse import json import pickle from pathlib import Path import requests import torch from huggingface_hub import hf_hub_download from PIL import Image from transformers import MaskFormerConfig, MaskFormerForInstanceSegmentation, MaskFormerImageProcessor, SwinConfig from transformers.utils im...
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'''simple docstring''' import logging from dataclasses import dataclass, field from pathlib import Path from typing import Optional, Union from .generation.configuration_utils import GenerationConfig from .training_args import TrainingArguments from .utils import add_start_docstrings __snake...
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import os import unittest from tempfile import TemporaryDirectory import torch import torch.nn as nn from accelerate.utils import ( OffloadedWeightsLoader, extract_submodules_state_dict, load_offloaded_weight, offload_state_dict, offload_weight, ) class __lowercase ( nn.Module ...
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'''simple docstring''' import argparse import torch from transformers import ( EncodecConfig, EncodecFeatureExtractor, EncodecModel, logging, ) # checkpoints downloaded from: # https://dl.fbaipublicfiles.com/encodec/v0/encodec_24khz-d7cc33bc.th # https://huggingface.co/f...
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"""simple docstring""" import argparse import struct import unittest class lowerCamelCase__ : def __init__( self , SCREAMING_SNAKE_CASE ): """simple docstring""" snake_case : Optional[int] = data # Initialize hash values sn...
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'''simple docstring''' import warnings from ...utils import logging from .image_processing_flava import FlavaImageProcessor __snake_case =logging.get_logger(__name__) class UpperCAmelCase_ ( __lowercase ): def __init__( self : Dict , *Upper...
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"""simple docstring""" import argparse import evaluate import torch from datasets import load_dataset from torch.optim import AdamW from torch.utils.data import DataLoader from transformers import AutoModelForSequenceClassification, AutoTokenizer, get_linear_schedule_with_warmup, set_seed from accelerate import ...
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'''simple docstring''' from typing import List, Optional from tokenizers import ByteLevelBPETokenizer from ...tokenization_utils_fast import PreTrainedTokenizerFast from ...utils import logging from .tokenization_blenderbot_small import BlenderbotSmallTokenizer __snake_case =logging...
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def _a ( UpperCamelCase_ : Optional[Any] ) -> Optional[Any]: """simple docstring""" return [ { 0: [1, 2], 1: [0, 2], 2: [0, 1, 3, 5], 3: [2, 4], 4: [3], 5: [2, 6, 8], ...
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'''simple docstring''' from ...configuration_utils import PretrainedConfig from ...utils import logging __snake_case =logging.get_logger(__name__) __snake_case ={ """facebook/s2t-wav2vec2-large-en-de""": ( """https://huggingface.co/facebook/s2t-wav2vec2-large-en-d...
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def a__ ( A_ ): '''simple docstring''' if len(A_ ) <= 1: return lst __magic_name__ = 1 while i < len(A_ ): if lst[i - 1] <= lst[i]: i += 1 else: __magic_name__ , __magic_name__ = lst[i], lst[i - ...
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'''simple docstring''' from __future__ import annotations from bisect import bisect_left from functools import total_ordering from heapq import merge @total_ordering class UpperCAmelCase_ ( __lowercase ): def __lt__( self : Optional[int] , UpperCAmelCa...
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import json from typing import List, Optional, Tuple from tokenizers import normalizers from ...tokenization_utils_fast import PreTrainedTokenizerFast from ...utils import logging from .tokenization_mobilebert import MobileBertTokenizer UpperCAmelCase_ = logging.get_logger(__name__)...
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'''simple docstring''' import datasets from .nmt_bleu import compute_bleu # From: https://github.com/tensorflow/nmt/blob/master/nmt/scripts/bleu.py __snake_case ="""\ @INPROCEEDINGS{Papineni02bleu:a, author = {Kishore Papineni and Salim Roukos and Todd Ward and Wei-jing Zhu}, ti...
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"""simple docstring""" from ..utils import DummyObject, requires_backends class UpperCAmelCase (metaclass=__lowercase ): """simple docstring""" _UpperCAmelCase :Any = ['''keras_nlp'''] def __init__( self , *_UpperCAmelCase , **_UpperCAmelCase ): ...
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'''simple docstring''' from sklearn.metrics import fa_score, matthews_corrcoef import datasets from .record_evaluation import evaluate as evaluate_record __snake_case ="""\ @article{wang2019superglue, title={SuperGLUE: A Stickier Benchmark for General-Purpose Language Understanding ...
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"""simple docstring""" from __future__ import annotations from typing import Any class snake_case : def __init__( self : Optional[int] , UpperCamelCase__ : int , UpperCamelCase__ : int , UpperCamelCase__ : float = 0)-> None: ...
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'''simple docstring''' print((lambda quine: quine % quine)("""print((lambda quine: quine %% quine)(%r))"""))
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"""simple docstring""" def lowercase__ ( snake_case_ :str , snake_case_ :str ): def get_matched_characters(snake_case_ :str , snake_case_ :str ) -> str: __UpperCAmelCase = [] __UpperCAmelCase = min(len(_stra ) , len(_s...
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'''simple docstring''' import os __snake_case ={"""I""": 1, """V""": 5, """X""": 10, """L""": 50, """C""": 100, """D""": 500, """M""": 1_000} def a_ ( lowerCamelCase : str ): lowerCAmelCase = 0 lowerCAmelCase = 0 while index < len(lowerCamelCas...
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"""simple docstring""" import copy from ...configuration_utils import PretrainedConfig from ...utils import logging from ..bit import BitConfig __A : Any = logging.get_logger(__name__) __A : List[Any] = { "Intel/dpt-large": "https://huggingface.co/Intel...
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'''simple docstring''' import itertools import random import unittest import numpy as np from transformers import ASTFeatureExtractor from transformers.testing_utils import require_torch, require_torchaudio from transformers.utils.import_utils import is_torch_available from ...test_sequence_...
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import random import timeit from functools import wraps from typing import Callable, Optional from ..configuration_utils import PretrainedConfig from ..models.auto.modeling_tf_auto import TF_MODEL_MAPPING, TF_MODEL_WITH_LM_HEAD_MAPPING from ..utils import is_pyanvml_available, is_tf_available, logging from...
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'''simple docstring''' import pickle import unittest import torch from accelerate import Accelerator from accelerate.state import AcceleratorState from accelerate.test_utils import require_cpu @require_cpu class UpperCAmelCase_ ( unittest.TestCase ): def __Upp...
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import argparse import os from pathlib import Path import torch from bark.generation import _load_model as _bark_load_model from huggingface_hub import hf_hub_download from transformers import EncodecConfig, EncodecModel, set_seed from transformers.models.bark.configuration_bark import ( BarkCoarseConfig, ...
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'''simple docstring''' import json from typing import TYPE_CHECKING, List, Optional, Tuple from tokenizers import pre_tokenizers, processors from ...tokenization_utils_base import AddedToken, BatchEncoding from ...tokenization_utils_fast import PreTrainedTokenizerFast from ...utils import loggin...
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"""simple docstring""" from collections.abc import Callable import numpy as np def UpperCamelCase__ ( lowercase__ : Callable , lowercase__ : float , lowercase__ : float , lowercase__ : float , lowercase__ : float ): snake_case ...
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'''simple docstring''' from __future__ import annotations from statistics import mean def a_ ( lowerCamelCase : list[int] , lowerCamelCase : list[int] , lowerCamelCase : int ): lowerCAmelCase = [0] * no_of_processes lowerCAmelCase = [0] * no_of_proces...
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"""simple docstring""" from sklearn.metrics import fa_score, matthews_corrcoef import datasets from .record_evaluation import evaluate as evaluate_record A : Tuple = "\\n@article{wang2019superglue,\n title={SuperGLUE: A Stickier Benchmark for General-Purpose Language Understanding Systems},\n a...
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'''simple docstring''' import gc import unittest import numpy as np import torch from diffusers import StableDiffusionKDiffusionPipeline from diffusers.utils import slow, torch_device from diffusers.utils.testing_utils import enable_full_determinism, require_torch_gpu enable_full_determini...
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import multiprocessing import time from arguments import PretokenizationArguments from datasets import load_dataset from transformers import AutoTokenizer, HfArgumentParser def _a ( UpperCamelCase_ : Dict ) -> Dict: """simple docstring""" lowerCAmelCase__ ...
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'''simple docstring''' # Copyright (c) 2021-, NVIDIA CORPORATION. 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/lice...
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def a__ ( A_ ): '''simple docstring''' __magic_name__ = n ** (1 / 3) return (val * val * val) == n if __name__ == "__main__": print(perfect_cube(27)) print(perfect_cube(4))
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'''simple docstring''' from __future__ import annotations from typing import Any class UpperCAmelCase_ : def __init__( self : Optional[int] , UpperCAmelCase__ : int , UpperCAmelCase__ : int , UpperCAmelCase__ : ...
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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 PreTrainedTokenizer from ...utils import logging UpperCAmelCase_ = logging.get_logger(__name...
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'''simple docstring''' class UpperCAmelCase_ : def __init__( self : List[str] , UpperCAmelCase__ : list[int] ) -> None: lowerCAmelCase = len(UpperCAmelCase__ ) lowerCAmelCase = [0] * len_array if len_a...
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"""simple docstring""" import heapq def SCREAMING_SNAKE_CASE__ ( __UpperCAmelCase ) -> Union[str, Any]: lowercase__: str = [] # for each node and his adjacency list add them and the rank of the node to queue # using heapq module the queue will be filled like a Priority Queue # hea...
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'''simple docstring''' def a_ ( lowerCamelCase : Optional[Any] ): return [ { 0: [1, 2], 1: [0, 2], 2: [0, 1, 3, 5], 3: [2, 4], 4: [3], 5: [2, 6, 8], 6: [5, 7], 7: [6, 8], 8:...
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"""simple docstring""" import os # noqa: this is just for tests import os as renamed_os # noqa: this is just for tests from os import path # noqa: this is just for tests from os import path as renamed_path # noqa: this is just for tests from os.path import join # noqa: this is just for tests from os....
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'''simple docstring''' import argparse from collections import OrderedDict from pathlib import Path import requests import torch from PIL import Image from transformers import GLPNConfig, GLPNForDepthEstimation, GLPNImageProcessor from transformers.utils import logging logging.set_verbosi...
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"""simple docstring""" import inspect import unittest from transformers import BitConfig 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_backbone_common imp...
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'''simple docstring''' import unittest from transformers import is_torch_available from transformers.testing_utils import require_sentencepiece, require_tokenizers, require_torch, slow if is_torch_available(): import torch from transformers import XLMRobertaModel @require_se...
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"""simple docstring""" import itertools import random import unittest import numpy as np from transformers import ASTFeatureExtractor from transformers.testing_utils import require_torch, require_torchaudio from transformers.utils.import_utils import is_torch_available from ...test_sequence_fe...
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'''simple docstring''' import multiprocessing import time from arguments import PretokenizationArguments from datasets import load_dataset from transformers import AutoTokenizer, HfArgumentParser def a_ ( lowerCamelCase : Dict ): lowerCAmelCase = {} lowerCAmel...
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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_dict import IterableDataset...
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'''simple docstring''' import logging from dataclasses import dataclass, field from pathlib import Path from typing import Optional, Union from .generation.configuration_utils import GenerationConfig from .training_args import TrainingArguments from .utils import add_start_docstrings __snake...
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import unittest from transformers import AutoTokenizer, FalconConfig, is_torch_available from transformers.testing_utils import require_torch, slow, torch_device from ...generation.test_utils import GenerationTesterMixin from ...test_configuration_common import ConfigTester from ...test_modeling_common import Mode...
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'''simple docstring''' import argparse import torch from transformers import ( EncodecConfig, EncodecFeatureExtractor, EncodecModel, logging, ) # checkpoints downloaded from: # https://dl.fbaipublicfiles.com/encodec/v0/encodec_24khz-d7cc33bc.th # https://huggingface.co/f...
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"""simple docstring""" import argparse import torch from safetensors.torch import load_file from diffusers import StableDiffusionPipeline def UpperCamelCase__ ( lowercase__ : Union[str, Any] , lowercase__ : Tuple , lowercase__ : Optional[Any] , low...
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'''simple docstring''' import warnings from ...utils import logging from .image_processing_flava import FlavaImageProcessor __snake_case =logging.get_logger(__name__) class UpperCAmelCase_ ( __lowercase ): def __init__( self : Dict , *Upper...
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"""simple docstring""" from __future__ import annotations from collections.abc import MutableSequence class _UpperCamelCase : '''simple docstring''' def __init__( self , __a , __a ): if len(UpperCAmelCase__ ) != degree + 1: raise ValueError( ...
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'''simple docstring''' from typing import List, Optional from tokenizers import ByteLevelBPETokenizer from ...tokenization_utils_fast import PreTrainedTokenizerFast from ...utils import logging from .tokenization_blenderbot_small import BlenderbotSmallTokenizer __snake_case =logging...
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import logging import os from .state import PartialState class lowercase__ ( logging.LoggerAdapter ): @staticmethod def UpperCAmelCase ( __UpperCAmelCase )-> Optional[int]: '''simple docstring''' lowerCAmelCase__ = PartialState() retu...
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'''simple docstring''' from ...configuration_utils import PretrainedConfig from ...utils import logging __snake_case =logging.get_logger(__name__) __snake_case ={ """facebook/s2t-wav2vec2-large-en-de""": ( """https://huggingface.co/facebook/s2t-wav2vec2-large-en-d...
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import argparse import json import os import re import torch from transformers import BloomConfig, BloomModel from transformers.file_utils import CONFIG_NAME, WEIGHTS_NAME from transformers.utils import logging logging.set_verbosity_info() __lowerCAmelCase : List[str] = [ 'wo...
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'''simple docstring''' from __future__ import annotations from bisect import bisect_left from functools import total_ordering from heapq import merge @total_ordering class UpperCAmelCase_ ( __lowercase ): def __lt__( self : Optional[int] , UpperCAmelCa...
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import importlib import math import os from dataclasses import dataclass from enum import Enum from typing import Any, Dict, Optional, Tuple, Union import flax import jax.numpy as jnp from ..utils import BaseOutput UpperCAmelCase_ = 'scheduler_config.json' class ...
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'''simple docstring''' import datasets from .nmt_bleu import compute_bleu # From: https://github.com/tensorflow/nmt/blob/master/nmt/scripts/bleu.py __snake_case ="""\ @INPROCEEDINGS{Papineni02bleu:a, author = {Kishore Papineni and Salim Roukos and Todd Ward and Wei-jing Zhu}, ti...
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"""simple docstring""" from __future__ import annotations def SCREAMING_SNAKE_CASE__ ( __UpperCAmelCase , __UpperCAmelCase ) -> Union[str, Any]: lowercase__: List[Any] = 0 lowercase__: Union[str, Any] = len(__UpperCAmelCase ) - 1 while i < j: if nums[i] + nu...
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'''simple docstring''' from sklearn.metrics import fa_score, matthews_corrcoef import datasets from .record_evaluation import evaluate as evaluate_record __snake_case ="""\ @article{wang2019superglue, title={SuperGLUE: A Stickier Benchmark for General-Purpose Language Understanding ...
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"""simple docstring""" from ...configuration_utils import PretrainedConfig from ...utils import logging __A = logging.get_logger(__name__) __A = { "microsoft/biogpt": "https://huggingface.co/microsoft/biogpt/resolve/main/config.json", # See all BioGPT models at https://hu...
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'''simple docstring''' print((lambda quine: quine % quine)("""print((lambda quine: quine %% quine)(%r))"""))
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"""simple docstring""" import logging import sys from dataclasses import dataclass, field from typing import Any, Dict, List, Optional, Union import librosa import torch from datasets import DatasetDict, load_dataset from packaging import version from torch import nn from transformers import (...
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'''simple docstring''' import os __snake_case ={"""I""": 1, """V""": 5, """X""": 10, """L""": 50, """C""": 100, """D""": 500, """M""": 1_000} def a_ ( lowerCamelCase : str ): lowerCAmelCase = 0 lowerCAmelCase = 0 while index < len(lowerCamelCas...
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"""simple docstring""" import copy from typing import Dict, Optional from ...configuration_utils import PretrainedConfig from ...utils import logging from ..auto import CONFIG_MAPPING from ..detr import DetrConfig from ..swin import SwinConfig __A : Tuple = { "facebook/m...
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'''simple docstring''' import itertools import random import unittest import numpy as np from transformers import ASTFeatureExtractor from transformers.testing_utils import require_torch, require_torchaudio from transformers.utils.import_utils import is_torch_available from ...test_sequence_...
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def SCREAMING_SNAKE_CASE__ ( lowerCamelCase__ , lowerCamelCase__ , lowerCamelCase__ , lowerCamelCase__ ) -> Tuple: __lowerCamelCase , __lowerCamelCase : Dict = len(lowerCamelCase__ ), len(grid[0] ) if ( min(lowerCamelCase__ , lowerCamelCase__ ) < 0 or ro...
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'''simple docstring''' import pickle import unittest import torch from accelerate import Accelerator from accelerate.state import AcceleratorState from accelerate.test_utils import require_cpu @require_cpu class UpperCAmelCase_ ( unittest.TestCase ): def __Upp...
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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 from ...utils.backbone_utils import BackboneConfigMixin, get_aligned_output_features_output_indices UpperCAm...
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'''simple docstring''' import json from typing import TYPE_CHECKING, List, Optional, Tuple from tokenizers import pre_tokenizers, processors from ...tokenization_utils_base import AddedToken, BatchEncoding from ...tokenization_utils_fast import PreTrainedTokenizerFast from ...utils import loggin...
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"""simple docstring""" __A = {str(digit): digit**5 for digit in range(10)} def UpperCamelCase__ ( lowercase__ : int ): return sum(DIGITS_FIFTH_POWER[digit] for digit in str(lowercase__ ) ) def UpperCamelCase__ ( ): return sum( ...
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'''simple docstring''' from __future__ import annotations from statistics import mean def a_ ( lowerCamelCase : list[int] , lowerCamelCase : list[int] , lowerCamelCase : int ): lowerCAmelCase = [0] * no_of_processes lowerCAmelCase = [0] * no_of_proces...
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"""simple docstring""" from graphs.minimum_spanning_tree_kruskal import kruskal def _lowerCamelCase ( ): '''simple docstring''' __lowerCAmelCase = 9 __lowerCAmelCase = [ [0, 1, 4], [0, 7, 8], [1, 2, 8], [7, 8, 7], [7, 6, 1], [2, 8, 2], ...
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'''simple docstring''' import gc import unittest import numpy as np import torch from diffusers import StableDiffusionKDiffusionPipeline from diffusers.utils import slow, torch_device from diffusers.utils.testing_utils import enable_full_determinism, require_torch_gpu enable_full_determini...
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import sys import warnings from os.path import abspath, dirname, join # allow having multiple repository checkouts and not needing to remember to rerun # 'pip install -e .[dev]' when switching between checkouts and running tests. a_ = abspath(join(dirname(dirname(__file__)), '''src''')) sys.path.insert...
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'''simple docstring''' # Copyright (c) 2021-, NVIDIA CORPORATION. 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/lice...
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from math import factorial def a__ ( A_ = 100 ): '''simple docstring''' return sum(int(A_ ) for x in str(factorial(A_ ) ) ) if __name__ == "__main__": print(solution(int(input('Enter the Number: ').strip())))
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'''simple docstring''' from __future__ import annotations from typing import Any class UpperCAmelCase_ : def __init__( self : Optional[int] , UpperCAmelCase__ : int , UpperCAmelCase__ : int , UpperCAmelCase__ : ...
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import datasets from .nmt_bleu import compute_bleu # From: https://github.com/tensorflow/nmt/blob/master/nmt/scripts/bleu.py UpperCAmelCase_ = '\\n@INPROCEEDINGS{Papineni02bleu:a,\n author = {Kishore Papineni and Salim Roukos and Todd Ward and Wei-jing Zhu},\n title = {BLEU: a Meth...
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'''simple docstring''' class UpperCAmelCase_ : def __init__( self : List[str] , UpperCAmelCase__ : list[int] ) -> None: lowerCAmelCase = len(UpperCAmelCase__ ) lowerCAmelCase = [0] * len_array if len_a...
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"""simple docstring""" from ...configuration_utils import PretrainedConfig from ...utils import logging __A = logging.get_logger(__name__) __A = { "facebook/s2t-wav2vec2-large-en-de": ( "https://huggingface.co/facebook/s2t-wav2vec2-large-en-de/resolve/main/config.json" ), # See al...
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'''simple docstring''' def a_ ( lowerCamelCase : Optional[Any] ): return [ { 0: [1, 2], 1: [0, 2], 2: [0, 1, 3, 5], 3: [2, 4], 4: [3], 5: [2, 6, 8], 6: [5, 7], 7: [6, 8], 8:...
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"""simple docstring""" class snake_case : def __init__( self : List[str] , UpperCamelCase__ : Optional[int])-> str: '''simple docstring''' __lowerCAmelCase: Tuple = arr.split(",") def lowercase_ ( self : ...
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'''simple docstring''' import argparse from collections import OrderedDict from pathlib import Path import requests import torch from PIL import Image from transformers import GLPNConfig, GLPNForDepthEstimation, GLPNImageProcessor from transformers.utils import logging logging.set_verbosi...
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"""simple docstring""" import warnings from ...utils import logging from .image_processing_imagegpt import ImageGPTImageProcessor _lowercase : Tuple = logging.get_logger(__name__) class _UpperCAmelCase ( __lowercase ): def __init__( self : List[Any] ...
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'''simple docstring''' import unittest from transformers import is_torch_available from transformers.testing_utils import require_sentencepiece, require_tokenizers, require_torch, slow if is_torch_available(): import torch from transformers import XLMRobertaModel @require_se...
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"""simple docstring""" from __future__ import annotations from bisect import bisect_left from functools import total_ordering from heapq import merge @total_ordering class _a ( __lowercase): """simple docstring""" def __lt__( self : Optional[int] , __UpperCamelC...
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'''simple docstring''' import multiprocessing import time from arguments import PretokenizationArguments from datasets import load_dataset from transformers import AutoTokenizer, HfArgumentParser def a_ ( lowerCamelCase : Dict ): lowerCAmelCase = {} lowerCAmel...
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import fire from torch.utils.data import DataLoader from tqdm import tqdm from transformers import AutoTokenizer from utils import SeqaSeqDataset, pickle_save def SCREAMING_SNAKE_CASE__ ( lowerCamelCase__ , lowerCamelCase__ , lowerCamelCase__=1_0_2_4 , lowerCamelCase__=1_0_2_4 , lowerCa...
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'''simple docstring''' import logging from dataclasses import dataclass, field from pathlib import Path from typing import Optional, Union from .generation.configuration_utils import GenerationConfig from .training_args import TrainingArguments from .utils import add_start_docstrings __snake...
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import re from ..utils import cached_file # docstyle-ignore UpperCAmelCase : Any = "\nHuman: <<task>>\n\nAssistant: " UpperCAmelCase : Union[str, Any] = "huggingface-tools/default-prompts" UpperCAmelCase : str = {"chat": "chat_prompt_template.txt", "run": "run_prompt_template...
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'''simple docstring''' import argparse import torch from transformers import ( EncodecConfig, EncodecFeatureExtractor, EncodecModel, logging, ) # checkpoints downloaded from: # https://dl.fbaipublicfiles.com/encodec/v0/encodec_24khz-d7cc33bc.th # https://huggingface.co/f...
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"""simple docstring""" from decimal import Decimal, getcontext from math import ceil, factorial def UpperCamelCase__ ( lowercase__ : int ): if not isinstance(lowercase__ , lowercase__ ): raise TypeError("Undefined for non-integers" ) elif precision...
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'''simple docstring''' import warnings from ...utils import logging from .image_processing_flava import FlavaImageProcessor __snake_case =logging.get_logger(__name__) class UpperCAmelCase_ ( __lowercase ): def __init__( self : Dict , *Upper...
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"""simple docstring""" import inspect import unittest from math import floor from transformers import CvtConfig 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_config...
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'''simple docstring''' from typing import List, Optional from tokenizers import ByteLevelBPETokenizer from ...tokenization_utils_fast import PreTrainedTokenizerFast from ...utils import logging from .tokenization_blenderbot_small import BlenderbotSmallTokenizer __snake_case =logging...
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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.INFO) a_ = logging.getLogge...
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'''simple docstring''' from ...configuration_utils import PretrainedConfig from ...utils import logging __snake_case =logging.get_logger(__name__) __snake_case ={ """facebook/s2t-wav2vec2-large-en-de""": ( """https://huggingface.co/facebook/s2t-wav2vec2-large-en-d...
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import unittest from datasets import load_dataset from transformers.pipelines import pipeline from transformers.testing_utils import is_pipeline_test, nested_simplify, require_torch, slow @is_pipeline_test @require_torch class UpperCAmelCase_ ( unittest.TestCase ): '''simple docs...
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'''simple docstring''' from __future__ import annotations from bisect import bisect_left from functools import total_ordering from heapq import merge @total_ordering class UpperCAmelCase_ ( __lowercase ): def __lt__( self : Optional[int] , UpperCAmelCa...
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import unittest import numpy as np from transformers.testing_utils import require_pytesseract, require_torch from transformers.utils import is_pytesseract_available, is_torch_available from ...test_image_processing_common import ImageProcessingSavingTestMixin, prepare_image_inputs if is_torch...
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'''simple docstring''' import datasets from .nmt_bleu import compute_bleu # From: https://github.com/tensorflow/nmt/blob/master/nmt/scripts/bleu.py __snake_case ="""\ @INPROCEEDINGS{Papineni02bleu:a, author = {Kishore Papineni and Salim Roukos and Todd Ward and Wei-jing Zhu}, ti...
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"""simple docstring""" import unittest from transformers import EsmConfig, is_torch_available from transformers.testing_utils import TestCasePlus, require_torch, slow, torch_device from ...test_configuration_common import ConfigTester from ...test_modeling_common import ModelTesterMixin, ids_tensor, random_atte...
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'''simple docstring''' from sklearn.metrics import fa_score, matthews_corrcoef import datasets from .record_evaluation import evaluate as evaluate_record __snake_case ="""\ @article{wang2019superglue, title={SuperGLUE: A Stickier Benchmark for General-Purpose Language Understanding ...
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"""simple docstring""" import json from typing import TYPE_CHECKING, List, Optional, Tuple from tokenizers import pre_tokenizers, processors from ...tokenization_utils_base import AddedToken, BatchEncoding from ...tokenization_utils_fast import PreTrainedTokenizerFast from ...utils import logging fro...
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'''simple docstring''' print((lambda quine: quine % quine)("""print((lambda quine: quine %% quine)(%r))"""))
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"""simple docstring""" from typing import Mapping from ...configuration_utils import PretrainedConfig from ...onnx import OnnxSeqaSeqConfigWithPast from ...utils import logging _lowercase : List[str] = logging.get_logger(__name__) _lowercase : Union[str, Any] = { ...
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'''simple docstring''' import os __snake_case ={"""I""": 1, """V""": 5, """X""": 10, """L""": 50, """C""": 100, """D""": 500, """M""": 1_000} def a_ ( lowerCamelCase : str ): lowerCAmelCase = 0 lowerCAmelCase = 0 while index < len(lowerCamelCas...
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"""simple docstring""" import itertools import random import unittest import numpy as np from transformers import WAV_2_VEC_2_PRETRAINED_MODEL_ARCHIVE_LIST, WavaVecaConfig, WavaVecaFeatureExtractor from transformers.testing_utils import require_torch, slow from ...test_sequence_feature_extracti...
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'''simple docstring''' import itertools import random import unittest import numpy as np from transformers import ASTFeatureExtractor from transformers.testing_utils import require_torch, require_torchaudio from transformers.utils.import_utils import is_torch_available from ...test_sequence_...
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import inspect import jax import jax.lax as lax import jax.numpy as jnp from ..utils import add_start_docstrings from ..utils.logging import get_logger a =get_logger(__name__) a =r""" Args: input_ids (`jnp.ndarray` of shape `(batch_size, sequence_length)`): Indices of in...
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'''simple docstring''' import pickle import unittest import torch from accelerate import Accelerator from accelerate.state import AcceleratorState from accelerate.test_utils import require_cpu @require_cpu class UpperCAmelCase_ ( unittest.TestCase ): def __Upp...
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import argparse from collections import defaultdict import yaml UpperCAmelCase : Any = "docs/source/en/_toctree.yml" def __lowerCamelCase ( lowerCamelCase__ : Any ): '''simple docstring''' lowerCamelCase = defaultdict(lowerCamelCase__ ) for doc in model_...
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'''simple docstring''' import json from typing import TYPE_CHECKING, List, Optional, Tuple from tokenizers import pre_tokenizers, processors from ...tokenization_utils_base import AddedToken, BatchEncoding from ...tokenization_utils_fast import PreTrainedTokenizerFast from ...utils import loggin...
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"""simple docstring""" def UpperCamelCase__ ( lowercase__ : int = 1000 ): snake_case , snake_case : Tuple = 1, 1 snake_case : Optional[int] = 2 while True: snake_case : Optional[int] = 0 snake_case : List[Any] = fa + fa ...
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'''simple docstring''' from __future__ import annotations from statistics import mean def a_ ( lowerCamelCase : list[int] , lowerCamelCase : list[int] , lowerCamelCase : int ): lowerCAmelCase = [0] * no_of_processes lowerCAmelCase = [0] * no_of_proces...
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"""simple docstring""" import argparse import json import os import sys import tempfile import unittest from argparse import Namespace from dataclasses import dataclass, field from enum import Enum from pathlib import Path from typing import List, Literal, Optional import yaml from transformers import HfArgument...
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'''simple docstring''' import gc import unittest import numpy as np import torch from diffusers import StableDiffusionKDiffusionPipeline from diffusers.utils import slow, torch_device from diffusers.utils.testing_utils import enable_full_determinism, require_torch_gpu enable_full_determini...
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import gc import unittest import numpy as np import torch from diffusers import StableDiffusionKDiffusionPipeline from diffusers.utils import slow, torch_device from diffusers.utils.testing_utils import enable_full_determinism, require_torch_gpu enable_full_determinism() @slow @require_torch_gpu class l...
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'''simple docstring''' # Copyright (c) 2021-, NVIDIA CORPORATION. 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/lice...
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def a__ ( A_, A_, A_, A_ ): '''simple docstring''' if height >= 1: move_tower(height - 1, A_, A_, A_ ) move_disk(A_, A_ ) move_tower(height - 1, A_, A_, A_ ) def a__ ( A_, A_ ): ...
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'''simple docstring''' from __future__ import annotations from typing import Any class UpperCAmelCase_ : def __init__( self : Optional[int] , UpperCAmelCase__ : int , UpperCAmelCase__ : int , UpperCAmelCase__ : ...
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import unicodedata from dataclasses import dataclass from typing import Optional, Union import numpy as np from transformers.data.data_collator import DataCollatorMixin from transformers.file_utils import PaddingStrategy from transformers.tokenization_utils_base import PreTrainedTokenizerBase ...
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'''simple docstring''' class UpperCAmelCase_ : def __init__( self : List[str] , UpperCAmelCase__ : list[int] ) -> None: lowerCAmelCase = len(UpperCAmelCase__ ) lowerCAmelCase = [0] * len_array if len_a...
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"""simple docstring""" import argparse import os import re import zipfile import torch from transformers import AutoTokenizer, GPTaConfig def SCREAMING_SNAKE_CASE__ ( __UpperCAmelCase , __UpperCAmelCase , __UpperCAmelCase=0 ) -> List[Any]: # Format the message. if name is None: ...
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'''simple docstring''' def a_ ( lowerCamelCase : Optional[Any] ): return [ { 0: [1, 2], 1: [0, 2], 2: [0, 1, 3, 5], 3: [2, 4], 4: [3], 5: [2, 6, 8], 6: [5, 7], 7: [6, 8], 8:...
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"""simple docstring""" import json import os import unittest from transformers.models.roc_bert.tokenization_roc_bert import ( VOCAB_FILES_NAMES, RoCBertBasicTokenizer, RoCBertTokenizer, RoCBertWordpieceTokenizer, _is_control, _is_punctuation, _is_whitespace, ) from tra...
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'''simple docstring''' import argparse from collections import OrderedDict from pathlib import Path import requests import torch from PIL import Image from transformers import GLPNConfig, GLPNForDepthEstimation, GLPNImageProcessor from transformers.utils import logging logging.set_verbosi...
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"""simple docstring""" import numpy as np def lowercase__ ( snake_case_ :np.ndarray , snake_case_ :float ): return np.where(vector > 0 , snake_case_ , (alpha * (np.exp(snake_case_ ) - 1)) ) if __name__ == "__main__": import doctest ...
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'''simple docstring''' import unittest from transformers import is_torch_available from transformers.testing_utils import require_sentencepiece, require_tokenizers, require_torch, slow if is_torch_available(): import torch from transformers import XLMRobertaModel @require_se...
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"""simple docstring""" import inspect import unittest import numpy as np from transformers import BeitConfig from transformers.testing_utils import require_flax, require_vision, slow from transformers.utils import cached_property, is_flax_available, is_vision_available from ...test_configuratio...
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'''simple docstring''' import multiprocessing import time from arguments import PretokenizationArguments from datasets import load_dataset from transformers import AutoTokenizer, HfArgumentParser def a_ ( lowerCamelCase : Dict ): lowerCAmelCase = {} lowerCAmel...
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import warnings from ...utils import logging from .image_processing_flava import FlavaImageProcessor a =logging.get_logger(__name__) class A_ ( __lowercase ): def __init__( self : Dict ,*SCREAMING_SNAKE_CASE__ : Dict ,**SCREAMING_SNAKE_CASE__ : List[str]...
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'''simple docstring''' import logging from dataclasses import dataclass, field from pathlib import Path from typing import Optional, Union from .generation.configuration_utils import GenerationConfig from .training_args import TrainingArguments from .utils import add_start_docstrings __snake...
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from typing import TYPE_CHECKING from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tf_available, is_torch_available UpperCAmelCase : List[str] = { "configuration_xlm": ["XLM_PRETRAINED_CONFIG_ARCHIVE_MAP", "XLMConfig", "XLMOnnxConfig"], "tokenization_xlm": ["XLMTokenizer"], ...
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'''simple docstring''' import argparse import torch from transformers import ( EncodecConfig, EncodecFeatureExtractor, EncodecModel, logging, ) # checkpoints downloaded from: # https://dl.fbaipublicfiles.com/encodec/v0/encodec_24khz-d7cc33bc.th # https://huggingface.co/f...
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"""simple docstring""" import argparse import json from pathlib import Path import requests import timm import torch from huggingface_hub import hf_hub_download from PIL import Image from transformers import DeiTConfig, DeiTForImageClassificationWithTeacher, DeiTImageProcessor from transformer...
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'''simple docstring''' import warnings from ...utils import logging from .image_processing_flava import FlavaImageProcessor __snake_case =logging.get_logger(__name__) class UpperCAmelCase_ ( __lowercase ): def __init__( self : Dict , *Upper...
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"""simple docstring""" import gc import unittest import numpy as np import torch from transformers import CLIPTextConfig, CLIPTextModel, CLIPTokenizer from diffusers import ( AutoencoderKL, DDIMScheduler, StableDiffusionAttendAndExcitePipeline, UNetaDConditionModel, ) from diffusers.utils import ...
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'''simple docstring''' from typing import List, Optional from tokenizers import ByteLevelBPETokenizer from ...tokenization_utils_fast import PreTrainedTokenizerFast from ...utils import logging from .tokenization_blenderbot_small import BlenderbotSmallTokenizer __snake_case =logging...
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