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lowerCamelCase : dict[tuple[int, int, int], int] = {} def snake_case_ ( lowerCAmelCase_ : int , lowerCAmelCase_ : int , lowerCAmelCase_ : int ): # if we are absent twice, or late 3 consecutive days, # no further prize strings are possib...
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from __future__ import annotations import math lowerCamelCase : List[Any] = '''2020.9.26''' lowerCamelCase : str = '''xcodz-dot, cclaus, dhruvmanila''' def snake_case_ ( lowerCAmelCase_ : float , lowerCAmelCase_ : float , lowerCAmelCas...
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lowerCamelCase : Optional[Any] = '''ABCDEFGHIJKLMNOPQRSTUVWXYZ''' def snake_case_ ( ): __lowercase : List[str] = input("""Enter message: """ ) __lowercase : int = input("""Enter key [alphanumeric]: """ ) __lowercase : ...
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from itertools import permutations def snake_case_ ( lowerCAmelCase_ : tuple ): if num[3] % 2 != 0: return False if (num[2] + num[3] + num[4]) % 3 != 0: return False if num[5] % 5 != 0: return False __lowercase : ...
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from functools import reduce lowerCamelCase : List[str] = ( '''73167176531330624919225119674426574742355349194934''' '''96983520312774506326239578318016984801869478851843''' '''85861560789112949495459501737958331952853208805511''' '''1254069874715852386305071569329096329522...
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import os from shutil import copyfile from typing import Any, Dict, List, Optional, Tuple import sentencepiece as spm from ...tokenization_utils import PreTrainedTokenizer from ...utils import logging lowerCamelCase : int = '''▁''' lowerCamelCase : Optional[int] = ...
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import inspect import unittest from transformers import ViTHybridConfig from transformers.testing_utils import require_accelerate, require_torch, require_vision, 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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lowerCamelCase : Optional[Any] = '''ABCDEFGHIJKLMNOPQRSTUVWXYZ''' def snake_case_ ( ): __lowercase : List[str] = input("""Enter message: """ ) __lowercase : int = input("""Enter key [alphanumeric]: """ ) __lowercase : ...
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def snake_case_ ( lowerCAmelCase_ : str ): assert column_title.isupper() __lowercase : Union[str, Any] = 0 __lowercase : str = len(lowerCAmelCase_ ) - 1 __lowercase : List[str] = 0 while index >= 0: ...
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import secrets from random import shuffle from string import ascii_letters, ascii_lowercase, ascii_uppercase, digits, punctuation def snake_case_ ( lowerCAmelCase_ : int = 8 ): __lowercase : str = ascii_letters + digits + punctuation return "".join(secrets.choice(l...
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# coding=utf-8 # Copyright 2020 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/LICENSE-2.0 # # Unless required by app...
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import argparse import json from pathlib import Path import torch import torchaudio from datasets import load_dataset from huggingface_hub import hf_hub_download from transformers import ASTConfig, ASTFeatureExtractor, ASTForAudioClassification from transformers.utils import logging logging.set_verbosity_inf...
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import unittest from transformers import CamembertTokenizer, CamembertTokenizerFast from transformers.testing_utils import get_tests_dir, require_sentencepiece, require_tokenizers, slow from transformers.utils import is_torch_available from ...test_tokenization_common import TokenizerTesterMixin lowerCamelCa...
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from ...configuration_utils import PretrainedConfig from ...utils import logging lowerCamelCase : Optional[Any] = logging.get_logger(__name__) lowerCamelCase : List[str] = { '''google/canine-s''': '''https://huggingface.co/google/canine-s/resolve/main/config.jso...
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from collections import namedtuple import requests from lxml import html # type: ignore lowerCamelCase : Any = namedtuple('''covid_data''', '''cases deaths recovered''') def snake_case_ ( lowerCAmelCase_ : str = "https://www.worldometers.info/coronavirus/" ): _...
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import random import unittest import numpy as np from diffusers import ( DPMSolverMultistepScheduler, EulerAncestralDiscreteScheduler, EulerDiscreteScheduler, LMSDiscreteScheduler, OnnxStableDiffusionImgaImgPipeline, PNDMScheduler, ) from diffusers.utils import floats_tensor from diffus...
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# Copyright 2023 The HuggingFace Inc. team. All rights reserved. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required ...
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import math class lowerCAmelCase : '''simple docstring''' def __init__( self : Tuple , __a : int=0 ) -> Optional[Any]: # a graph with Node 0,1,...,N-1 """simple docstring""" __lowercase : Any = n __lowercase : ...
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import os def snake_case_ ( ): __lowercase : Union[str, Any] = os.path.dirname(os.path.realpath(lowerCAmelCase_ ) ) __lowercase : List[str] = os.path.join(lowerCAmelCase_ , """triangle.txt""" ) with open(lowerCAmelCase_ ) as f: ...
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lowerCamelCase : Dict = '''0.21.0''' from .accelerator import Accelerator from .big_modeling import ( cpu_offload, cpu_offload_with_hook, disk_offload, dispatch_model, init_empty_weights, init_on_device, load_checkpoint_and_dispatch, ) from .data_loader import s...
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import inspect import re from transformers.utils import direct_transformers_import # All paths are set with the intent you should run this script from the root of the repo with the command # python utils/check_config_docstrings.py lowerCamelCase : int = '''src/transformers''' # This is...
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from maths.prime_check import is_prime def snake_case_ ( lowerCAmelCase_ : int ): if not isinstance(lowerCAmelCase_ , lowerCAmelCase_ ): __lowercase : Dict = F"Input value of [number={number}] must be an integer" raise TypeError(lower...
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from collections import namedtuple lowerCamelCase : List[Any] = namedtuple('''from_to''', '''from_ to''') lowerCamelCase : Tuple = { '''cubicmeter''': from_to(1, 1), '''litre''': from_to(0.0_01, 10_00), '''kilolitre''': from_to(1, 1), '''gallon''': fr...
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# flake8: noqa # Lint as: python3 lowerCamelCase : Optional[Any] = [ '''VerificationMode''', '''Version''', '''disable_progress_bar''', '''enable_progress_bar''', '''is_progress_bar_enabled''', '''experimental''', ] from .info_utils import VerificationMode from .log...
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import warnings from ...utils import logging from .image_processing_deit import DeiTImageProcessor lowerCamelCase : int = logging.get_logger(__name__) class lowerCAmelCase ( __a ): '''simple docstring''' def __init__( self : List[str] , *__a : List...
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lowerCamelCase : Tuple = {'''a''': ['''c''', '''b'''], '''b''': ['''d''', '''e'''], '''c''': [], '''d''': [], '''e''': []} lowerCamelCase : int = ['''a''', '''b''', '''c''', '''d''', '''e'''] def snake_case_ ( lowerCAmelCase_ : Optional[int] , low...
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import os import tempfile import unittest import numpy as np from diffusers.utils import is_flax_available from diffusers.utils.testing_utils import require_flax, slow if is_flax_available(): import jax import jax.numpy as jnp from flax.jax_utils import replicate from flax.training.common_utils import sh...
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import copy import tempfile import unittest from transformers import MaMaaaConfig, is_torch_available from transformers.testing_utils import require_sentencepiece, require_tokenizers, require_torch, slow, torch_device from transformers.utils import cached_property from ...generation.test_utils import Generatio...
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from typing import Dict, List, Optional, Union import numpy as np from ...image_processing_utils import BaseImageProcessor, BatchFeature, get_size_dict from ...image_transforms import ( center_crop, convert_to_rgb, get_resize_output_image_size, normalize, rescale, resize, to_channel...
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# Copyright 2023 The HuggingFace Inc. team. All rights reserved. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required ...
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import json from typing import 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 from .tokenization_mvp import MvpTokenizer lowerC...
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import unittest from transformers import CamembertTokenizer, CamembertTokenizerFast from transformers.testing_utils import get_tests_dir, require_sentencepiece, require_tokenizers, slow from transformers.utils import is_torch_available from ...test_tokenization_common import TokenizerTesterMixin lowerCamelCa...
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from __future__ import annotations import math lowerCamelCase : List[Any] = '''2020.9.26''' lowerCamelCase : str = '''xcodz-dot, cclaus, dhruvmanila''' def snake_case_ ( lowerCAmelCase_ : float , lowerCAmelCase_ : float , lowerCAmelCas...
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import argparse from transformers import ( TapasConfig, TapasForMaskedLM, TapasForQuestionAnswering, TapasForSequenceClassification, TapasModel, TapasTokenizer, load_tf_weights_in_tapas, ) from transformers.utils import logging logging.set_verbosity_info() def snake_case_ ...
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from typing import Optional import pyspark from .. import Features, NamedSplit from ..download import DownloadMode from ..packaged_modules.spark.spark import Spark from .abc import AbstractDatasetReader class lowerCAmelCase ( __a ): '''simple docstring''' def __init__( self : Un...
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def snake_case_ ( lowerCAmelCase_ : list ): if len(lowerCAmelCase_ ) <= 1: return [tuple(lowerCAmelCase_ )] __lowercase : Any = [] def generate(lowerCAmelCase_ : int , lowerCAmelCase_ : list ): if k ==...
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import inspect import warnings from typing import Any, Dict, Optional, Union from packaging import version def snake_case_ ( *lowerCAmelCase_ : Dict , lowerCAmelCase_ : Optional[Union[Dict, Any]] = None , lowerCAmelCase_ : List[Any]=True , lowerCAmelCase_ : List[Any...
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from __future__ import annotations def snake_case_ ( lowerCAmelCase_ : int , lowerCAmelCase_ : int ): if partitions <= 0: raise ValueError("""partitions must be a positive number!""" ) if partitions > number_of_bytes: raise ValueError(""...
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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 lowe...
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from math import pi def snake_case_ ( lowerCAmelCase_ : int , lowerCAmelCase_ : int ): return 2 * pi * radius * (angle / 360) if __name__ == "__main__": print(arc_length(90, 10))
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import pytest from datasets import inspect_metric, list_metrics, load_metric @pytest.fixture def snake_case_ ( lowerCAmelCase_ : Dict ): monkeypatch.setattr("""datasets.utils.deprecation_utils._emitted_deprecation_warnings""" , set() ) @pytest.fixture def snake_case_ ...
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import inspect import unittest from transformers import ConvNextVaConfig from transformers.models.auto import get_values from transformers.models.auto.modeling_auto import MODEL_FOR_BACKBONE_MAPPING_NAMES, MODEL_MAPPING_NAMES from transformers.testing_utils import require_torch, require_vision, slow, torch_devi...
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import logging import math from functools import partial from typing import Any, Callable, Dict, Iterable, List, Optional, Sequence, Tuple, Union import torch from .tensor_utils import tensor_tree_map, tree_map def snake_case_ ( lowerCAmelCase_ : Union[dict, list, tuple, torch.Tensor] ): ...
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import math def snake_case_ ( lowerCAmelCase_ : int ): if 1 < number < 4: # 2 and 3 are primes return True elif number < 2 or number % 2 == 0 or number % 3 == 0: # Negatives, 0, 1, all even numbers, all multiples of 3 are not primes ...
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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() lowerCamelCase : Union[str, Any] = logging.get_logger(__name__) def snake_case_ ( lower...
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from __future__ import annotations import math lowerCamelCase : List[Any] = '''2020.9.26''' lowerCamelCase : str = '''xcodz-dot, cclaus, dhruvmanila''' def snake_case_ ( lowerCAmelCase_ : float , lowerCAmelCase_ : float , lowerCAmelCas...
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from __future__ import annotations import unittest from transformers import is_tf_available from transformers.testing_utils import require_sentencepiece, require_tf, require_tokenizers, slow from ...test_configuration_common import ConfigTester from ...test_modeling_tf_common import TFModelTesterMixin, ids_te...
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from itertools import permutations def snake_case_ ( lowerCAmelCase_ : tuple ): if num[3] % 2 != 0: return False if (num[2] + num[3] + num[4]) % 3 != 0: return False if num[5] % 5 != 0: return False __lowercase : ...
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from __future__ import annotations from cmath import sqrt def snake_case_ ( lowerCAmelCase_ : int , lowerCAmelCase_ : int , lowerCAmelCase_ : int ): if a == 0: raise ValueError("""Coefficient 'a' must not be zero.""" ) __lowercase : ...
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import os from shutil import copyfile from typing import Any, Dict, List, Optional, Tuple import sentencepiece as spm from ...tokenization_utils import PreTrainedTokenizer from ...utils import logging lowerCamelCase : int = '''▁''' lowerCamelCase : Optional[int] = ...
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from __future__ import annotations from sys import maxsize from typing import Generic, TypeVar lowerCamelCase : List[str] = TypeVar('''T''') def snake_case_ ( lowerCAmelCase_ : int ): return (position - 1) // 2 def snake_case_ ( lowerCAmelCase_ : ...
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lowerCamelCase : Optional[Any] = '''ABCDEFGHIJKLMNOPQRSTUVWXYZ''' def snake_case_ ( ): __lowercase : List[str] = input("""Enter message: """ ) __lowercase : int = input("""Enter key [alphanumeric]: """ ) __lowercase : ...
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from dataclasses import dataclass, field from typing import Optional @dataclass class lowerCAmelCase : '''simple docstring''' _A : Optional[str] = field( default='''codeparrot/codeparrot''' , metadata={'''help''': '''Model name or path of model to be trained.'''} ) ...
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import secrets from random import shuffle from string import ascii_letters, ascii_lowercase, ascii_uppercase, digits, punctuation def snake_case_ ( lowerCAmelCase_ : int = 8 ): __lowercase : str = ascii_letters + digits + punctuation return "".join(secrets.choice(l...
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import sacrebleu as scb from packaging import version from sacrebleu import CHRF import datasets lowerCamelCase : Union[str, Any] = '''\ @inproceedings{popovic-2015-chrf, title = "chr{F}: character n-gram {F}-score for automatic {MT} evaluation", author = "Popovi{\'c}, Maja", ...
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import argparse import json from pathlib import Path import torch import torchaudio from datasets import load_dataset from huggingface_hub import hf_hub_download from transformers import ASTConfig, ASTFeatureExtractor, ASTForAudioClassification from transformers.utils import logging logging.set_verbosity_inf...
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import math from typing import Callable, List, Optional, Union import numpy as np import PIL import torch from PIL import Image from transformers import CLIPTextModel, CLIPTokenizer from diffusers.models import AutoencoderKL, UNetaDConditionModel from diffusers.pipelines.stable_diffusion.pipeline_stable_diffus...
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from ...configuration_utils import PretrainedConfig from ...utils import logging lowerCamelCase : Optional[Any] = logging.get_logger(__name__) lowerCamelCase : List[str] = { '''google/canine-s''': '''https://huggingface.co/google/canine-s/resolve/main/config.jso...
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import datasets lowerCamelCase : Optional[Any] = '''\ @InProceedings{conneau2018xnli, author = "Conneau, Alexis and Rinott, Ruty and Lample, Guillaume and Williams, Adina and Bowman, Samuel R. and Schwe...
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import random import unittest import numpy as np from diffusers import ( DPMSolverMultistepScheduler, EulerAncestralDiscreteScheduler, EulerDiscreteScheduler, LMSDiscreteScheduler, OnnxStableDiffusionImgaImgPipeline, PNDMScheduler, ) from diffusers.utils import floats_tensor from diffus...
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import pytest from datasets.parallel import ParallelBackendConfig, parallel_backend from datasets.utils.py_utils import map_nested from .utils import require_dill_gt_0_3_2, require_joblibspark, require_not_windows def snake_case_ ( lowerCAmelCase_ : List[Any] ): # picklable for multiproces...
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import math class lowerCAmelCase : '''simple docstring''' def __init__( self : Tuple , __a : int=0 ) -> Optional[Any]: # a graph with Node 0,1,...,N-1 """simple docstring""" __lowercase : Any = n __lowercase : ...
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import os from math import logaa def snake_case_ ( lowerCAmelCase_ : str = "base_exp.txt" ): __lowercase : float = 0 __lowercase : Union[str, Any] = 0 for i, line in enumerate(open(os.path.join(os.path.dirname(lowerCAmelCase_ ) , lowe...
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lowerCamelCase : Dict = '''0.21.0''' from .accelerator import Accelerator from .big_modeling import ( cpu_offload, cpu_offload_with_hook, disk_offload, dispatch_model, init_empty_weights, init_on_device, load_checkpoint_and_dispatch, ) from .data_loader import s...
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import gc import random import tempfile import unittest import numpy as np import torch from PIL import Image from transformers import CLIPTextConfig, CLIPTextModel, CLIPTokenizer from diffusers import ( AutoencoderKL, DDIMInverseScheduler, DDIMScheduler, DPMSolverMultistepInverseScheduler, ...
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from maths.prime_check import is_prime def snake_case_ ( lowerCAmelCase_ : int ): if not isinstance(lowerCAmelCase_ , lowerCAmelCase_ ): __lowercase : Dict = F"Input value of [number={number}] must be an integer" raise TypeError(lower...
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from dataclasses import dataclass from typing import Optional, Tuple, Union import torch import torch.nn as nn from ..configuration_utils import ConfigMixin, register_to_config from ..utils import BaseOutput from .embeddings import GaussianFourierProjection, TimestepEmbedding, Timesteps from .modeling_utils im...
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# flake8: noqa # Lint as: python3 lowerCamelCase : Optional[Any] = [ '''VerificationMode''', '''Version''', '''disable_progress_bar''', '''enable_progress_bar''', '''is_progress_bar_enabled''', '''experimental''', ] from .info_utils import VerificationMode from .log...
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from typing import Callable, Optional from .. import Features from ..packaged_modules.generator.generator import Generator from .abc import AbstractDatasetInputStream class lowerCAmelCase ( __a ): '''simple docstring''' def __init__( self : List[str] , __a : Callable ...
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lowerCamelCase : Tuple = {'''a''': ['''c''', '''b'''], '''b''': ['''d''', '''e'''], '''c''': [], '''d''': [], '''e''': []} lowerCamelCase : int = ['''a''', '''b''', '''c''', '''d''', '''e'''] def snake_case_ ( lowerCAmelCase_ : Optional[int] , low...
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def snake_case_ ( lowerCAmelCase_ : int , lowerCAmelCase_ : bool = False ): if n == 2: return True if not n % 2 or n < 2: return False if n > 5 and n % 10 not in (1, 3, 7, 9): # can quickly check last digit return False...
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import copy import tempfile import unittest from transformers import MaMaaaConfig, is_torch_available from transformers.testing_utils import require_sentencepiece, require_tokenizers, require_torch, slow, torch_device from transformers.utils import cached_property from ...generation.test_utils import Generatio...
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def snake_case_ ( lowerCAmelCase_ : dict ): __lowercase : set[int] = set() # To detect a back edge, keep track of vertices currently in the recursion stack __lowercase : set[int] = set() return any( node not in visited and dep...
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# Copyright 2023 The HuggingFace Inc. team. All rights reserved. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required ...
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class lowerCAmelCase : '''simple docstring''' def __init__( self : Union[str, Any] , __a : str ) -> int: """simple docstring""" __lowercase : Tuple = val __lowercase : str = None __lowercase ...
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import unittest from transformers import CamembertTokenizer, CamembertTokenizerFast from transformers.testing_utils import get_tests_dir, require_sentencepiece, require_tokenizers, slow from transformers.utils import is_torch_available from ...test_tokenization_common import TokenizerTesterMixin lowerCamelCa...
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from typing import Callable, Optional, Union from ...configuration_utils import PretrainedConfig from ...utils import logging lowerCamelCase : str = logging.get_logger(__name__) lowerCamelCase : Union[str, Any] = { '''microsoft/xprophetnet-large-wiki100-cased''...
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import argparse from transformers import ( TapasConfig, TapasForMaskedLM, TapasForQuestionAnswering, TapasForSequenceClassification, TapasModel, TapasTokenizer, load_tf_weights_in_tapas, ) from transformers.utils import logging logging.set_verbosity_info() def snake_case_ ...
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import os from shutil import copyfile from typing import List, Optional, Tuple from ...tokenization_utils import AddedToken from ...tokenization_utils_fast import PreTrainedTokenizerFast from ...utils import is_sentencepiece_available, logging if is_sentencepiece_available(): from .token...
0
def snake_case_ ( lowerCAmelCase_ : list ): if len(lowerCAmelCase_ ) <= 1: return [tuple(lowerCAmelCase_ )] __lowercase : Any = [] def generate(lowerCAmelCase_ : int , lowerCAmelCase_ : list ): if k ==...
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'''simple docstring''' from ...configuration_utils import PretrainedConfig from ...utils import logging SCREAMING_SNAKE_CASE_: Dict =logging.get_logger(__name__) SCREAMING_SNAKE_CASE_: Union[str, Any] ={ 'abeja/gpt-neox-japanese-2.7b': 'https://huggingface.co/abeja/gpt-neox-japanese-2.7b/resolve/m...
1
from __future__ import annotations def snake_case_ ( lowerCAmelCase_ : int , lowerCAmelCase_ : int ): if partitions <= 0: raise ValueError("""partitions must be a positive number!""" ) if partitions > number_of_bytes: raise ValueError(""...
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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 BertTokenizer, BertTokenizerFast from transformers.models.bert.tokenization_bert import VOCAB_FILES_NAMES from transformers.testing_utils import require_vision from ...
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from math import pi def snake_case_ ( lowerCAmelCase_ : int , lowerCAmelCase_ : int ): return 2 * pi * radius * (angle / 360) if __name__ == "__main__": print(arc_length(90, 10))
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'''simple docstring''' import math import os import re import sys import unittest from pathlib import Path from typing import Tuple from unittest.mock import patch from parameterized import parameterized from transformers.testing_utils import ( CaptureStderr, ExtendSysPath, TestCa...
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import inspect import unittest from transformers import ConvNextVaConfig from transformers.models.auto import get_values from transformers.models.auto.modeling_auto import MODEL_FOR_BACKBONE_MAPPING_NAMES, MODEL_MAPPING_NAMES from transformers.testing_utils import require_torch, require_vision, slow, torch_devi...
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'''simple docstring''' import os import unittest from transformers.models.cpmant.tokenization_cpmant import VOCAB_FILES_NAMES, CpmAntTokenizer from transformers.testing_utils import require_jieba, tooslow from ...test_tokenization_common import TokenizerTesterMixin @require_jieba class Uppe...
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import math def snake_case_ ( lowerCAmelCase_ : int ): if 1 < number < 4: # 2 and 3 are primes return True elif number < 2 or number % 2 == 0 or number % 3 == 0: # Negatives, 0, 1, all even numbers, all multiples of 3 are not primes ...
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import pyarrow.parquet as pq import pytest from datasets import Audio, Dataset, DatasetDict, Features, NamedSplit, Sequence, Value, config from datasets.features.image import Image from datasets.io.parquet import ParquetDatasetReader, ParquetDatasetWriter, get_writer_batch_size from ..utils import assert_arrow_mem...
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from __future__ import annotations import math lowerCamelCase : List[Any] = '''2020.9.26''' lowerCamelCase : str = '''xcodz-dot, cclaus, dhruvmanila''' def snake_case_ ( lowerCAmelCase_ : float , lowerCAmelCase_ : float , lowerCAmelCas...
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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 torchvision.transforms.functional import Interpo...
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from itertools import permutations def snake_case_ ( lowerCAmelCase_ : tuple ): if num[3] % 2 != 0: return False if (num[2] + num[3] + num[4]) % 3 != 0: return False if num[5] % 5 != 0: return False __lowercase : ...
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import inspect import unittest from huggingface_hub import hf_hub_download from transformers import ConvNextConfig, UperNetConfig from transformers.testing_utils import require_torch, require_torch_multi_gpu, require_vision, slow, torch_device from transformers.utils import is_torch_available, is_vision_av...
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import os from shutil import copyfile from typing import Any, Dict, List, Optional, Tuple import sentencepiece as spm from ...tokenization_utils import PreTrainedTokenizer from ...utils import logging lowerCamelCase : int = '''▁''' lowerCamelCase : Optional[int] = ...
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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_sentencepiece @require_tokenize...
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lowerCamelCase : Optional[Any] = '''ABCDEFGHIJKLMNOPQRSTUVWXYZ''' def snake_case_ ( ): __lowercase : List[str] = input("""Enter message: """ ) __lowercase : int = input("""Enter key [alphanumeric]: """ ) __lowercase : ...
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import warnings from ...utils import is_sklearn_available, requires_backends if is_sklearn_available(): from scipy.stats import pearsonr, spearmanr from sklearn.metrics import fa_score, matthews_corrcoef __lowerCAmelCase : str =( 'This metric will be removed from the library soon, metrics s...
9
import secrets from random import shuffle from string import ascii_letters, ascii_lowercase, ascii_uppercase, digits, punctuation def snake_case_ ( lowerCAmelCase_ : int = 8 ): __lowercase : str = ascii_letters + digits + punctuation return "".join(secrets.choice(l...
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from typing import Optional, Union import numpy as np from ...image_processing_utils import BaseImageProcessor, BatchFeature from ...image_transforms import get_image_size, pad, rescale, to_channel_dimension_format from ...image_utils import ChannelDimension, ImageInput, make_list_of_images, to_numpy_array, val...
10
import argparse import json from pathlib import Path import torch import torchaudio from datasets import load_dataset from huggingface_hub import hf_hub_download from transformers import ASTConfig, ASTFeatureExtractor, ASTForAudioClassification from transformers.utils import logging logging.set_verbosity_inf...
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import json import os import tempfile import datasets from utils import generate_example_dataset, get_duration lowerCAmelCase__ = 5_00_00 lowerCAmelCase__ = 50_00 lowerCAmelCase__ ,lowerCAmelCase__ = os.path.split(__file__) lowerCAmelCase__ = os.path.join(RESULTS_BASEPATH, 'results',...
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from ...configuration_utils import PretrainedConfig from ...utils import logging lowerCamelCase : Optional[Any] = logging.get_logger(__name__) lowerCamelCase : List[str] = { '''google/canine-s''': '''https://huggingface.co/google/canine-s/resolve/main/config.jso...
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from typing import List, Optional, Union from ...image_utils import ImageInput from ...processing_utils import ProcessorMixin from ...tokenization_utils_base import BatchEncoding, PaddingStrategy, PreTokenizedInput, TextInput, TruncationStrategy from ...utils import TensorType class lowerCamelCase__( ...
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import random import unittest import numpy as np from diffusers import ( DPMSolverMultistepScheduler, EulerAncestralDiscreteScheduler, EulerDiscreteScheduler, LMSDiscreteScheduler, OnnxStableDiffusionImgaImgPipeline, PNDMScheduler, ) from diffusers.utils import floats_tensor from diffus...
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import torch import torch.nn as nn from transformers import CLIPConfig, CLIPVisionModel, PreTrainedModel from ...utils import logging lowerCAmelCase : List[str] = logging.get_logger(__name__) def A_ ( _UpperCAmelCase , _UpperCAmelCase ): SCREAMING_SNAKE_CASE_: Optional[...
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import math class lowerCAmelCase : '''simple docstring''' def __init__( self : Tuple , __a : int=0 ) -> Optional[Any]: # a graph with Node 0,1,...,N-1 """simple docstring""" __lowercase : Any = n __lowercase : ...
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_lowerCamelCase : Tuple = """ # Transformers 설치 방법 ! pip install transformers datasets # 마지막 릴리스 대신 소스에서 설치하려면, 위 명령을 주석으로 바꾸고 아래 명령을 해제하세요. # ! pip install git+https://github.com/huggingface/transformers.git """ _lowerCamelCase : Tuple = [{"""type""": """code""", """content""": IN...
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lowerCamelCase : Dict = '''0.21.0''' from .accelerator import Accelerator from .big_modeling import ( cpu_offload, cpu_offload_with_hook, disk_offload, dispatch_model, init_empty_weights, init_on_device, load_checkpoint_and_dispatch, ) from .data_loader import s...
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def UpperCAmelCase ( a_ = 1_0_0_0_0_0_0 ) -> int: """simple docstring""" __A = [i - 1 for i in range(limit + 1 )] for i in range(2 , limit + 1 ): if phi[i] == i - 1: for j in range(2 * i , limit + 1 , a_ ): phi[j] -= ...
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from maths.prime_check import is_prime def snake_case_ ( lowerCAmelCase_ : int ): if not isinstance(lowerCAmelCase_ , lowerCAmelCase_ ): __lowercase : Dict = F"Input value of [number={number}] must be an integer" raise TypeError(lower...
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"""simple docstring""" from collections import UserDict from typing import List, Union from ..utils import ( add_end_docstrings, is_tf_available, is_torch_available, is_vision_available, logging, requires_backends, ) from .base import PIPELINE_INIT_ARGS, Pipeli...
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# flake8: noqa # Lint as: python3 lowerCamelCase : Optional[Any] = [ '''VerificationMode''', '''Version''', '''disable_progress_bar''', '''enable_progress_bar''', '''is_progress_bar_enabled''', '''experimental''', ] from .info_utils import VerificationMode from .log...
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"""simple docstring""" import inspect import unittest class _lowerCAmelCase ( unittest.TestCase ): """simple docstring""" def _lowercase ( self : Tuple ): try: import diffusers # noqa: F401 except ImportError: assert False def _lowercase ...
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lowerCamelCase : Tuple = {'''a''': ['''c''', '''b'''], '''b''': ['''d''', '''e'''], '''c''': [], '''d''': [], '''e''': []} lowerCamelCase : int = ['''a''', '''b''', '''c''', '''d''', '''e'''] def snake_case_ ( lowerCAmelCase_ : Optional[int] , low...
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import shutil import tempfile import unittest import numpy as np import pytest from transformers.testing_utils import require_vision from transformers.utils import is_vision_available if is_vision_available(): from PIL import Image from transformers import AutoProcessor, BertTokenizer, BlipImageProcessor, Blip...
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import copy import tempfile import unittest from transformers import MaMaaaConfig, is_torch_available from transformers.testing_utils import require_sentencepiece, require_tokenizers, require_torch, slow, torch_device from transformers.utils import cached_property from ...generation.test_utils import Generatio...
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from collections import defaultdict from graphs.minimum_spanning_tree_prims import prisms_algorithm as mst def lowerCamelCase_ ( ): lowerCamelCase_ , lowerCamelCase_ = 9, 1_4 # noqa: F841 lowerCamelCase_ = [ [0, 1, 4], [0, 7, 8], [1, 2, 8], [7, 8, 7...
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# Copyright 2023 The HuggingFace Inc. team. All rights reserved. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required ...
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def _snake_case( SCREAMING_SNAKE_CASE__ ) -> int: lowercase : Any = hex_num.strip() if not hex_num: raise ValueError("""No value was passed to the function""" ) lowercase : int = hex_num[0] == """-""" if is_negative:...
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import unittest from transformers import CamembertTokenizer, CamembertTokenizerFast from transformers.testing_utils import get_tests_dir, require_sentencepiece, require_tokenizers, slow from transformers.utils import is_torch_available from ...test_tokenization_common import TokenizerTesterMixin lowerCamelCa...
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def UpperCamelCase_( ) -> Dict: _lowercase : Union[str, Any] = [] _lowercase : Optional[Any] = 1 while len(lowerCamelCase_ ) < 1e6: constant.append(str(lowerCamelCase_ ) ) i += 1 _lowercase : int = ''.join(...
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import argparse from transformers import ( TapasConfig, TapasForMaskedLM, TapasForQuestionAnswering, TapasForSequenceClassification, TapasModel, TapasTokenizer, load_tf_weights_in_tapas, ) from transformers.utils import logging logging.set_verbosity_info() def snake_case_ ...
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'''simple docstring''' def UpperCAmelCase_ ( __lowercase : List[str] ) -> Dict: '''simple docstring''' _UpperCAmelCase = len(__lowercase ) while cur > 1: # Find the maximum number in arr _UpperCAmelCase = ...
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def snake_case_ ( lowerCAmelCase_ : list ): if len(lowerCAmelCase_ ) <= 1: return [tuple(lowerCAmelCase_ )] __lowercase : Any = [] def generate(lowerCAmelCase_ : int , lowerCAmelCase_ : list ): if k ==...
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'''simple docstring''' import warnings from typing import List, Optional, Tuple, Union import numpy as np import PIL import torch from ...models import UNetaDModel from ...schedulers import RePaintScheduler from ...utils import PIL_INTERPOLATION, logging, randn_tensor from ..pipeline_ut...
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from __future__ import annotations def snake_case_ ( lowerCAmelCase_ : int , lowerCAmelCase_ : int ): if partitions <= 0: raise ValueError("""partitions must be a positive number!""" ) if partitions > number_of_bytes: raise ValueError(""...
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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 if is_torch_available...
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from math import pi def snake_case_ ( lowerCAmelCase_ : int , lowerCAmelCase_ : int ): return 2 * pi * radius * (angle / 360) if __name__ == "__main__": print(arc_length(90, 10))
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"""simple docstring""" import inspect from typing import Callable, List, Optional, Union import torch from transformers import CLIPImageProcessor, CLIPTextModel, CLIPTokenizer from diffusers import DiffusionPipeline from diffusers.models import AutoencoderKL, UNetaDConditionModel from diffusers.pip...
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import inspect import unittest from transformers import ConvNextVaConfig from transformers.models.auto import get_values from transformers.models.auto.modeling_auto import MODEL_FOR_BACKBONE_MAPPING_NAMES, MODEL_MAPPING_NAMES from transformers.testing_utils import require_torch, require_vision, slow, torch_devi...
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import random import unittest import torch from diffusers import IFImgaImgSuperResolutionPipeline from diffusers.utils import floats_tensor from diffusers.utils.import_utils import is_xformers_available from diffusers.utils.testing_utils import skip_mps, torch_device from ..pipeline_params import TEXT_GUIDED_IM...
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import math def snake_case_ ( lowerCAmelCase_ : int ): if 1 < number < 4: # 2 and 3 are primes return True elif number < 2 or number % 2 == 0 or number % 3 == 0: # Negatives, 0, 1, all even numbers, all multiples of 3 are not primes ...
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'''simple docstring''' # Copyright 2023 The HuggingFace Inc. team. All rights reserved. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2....
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from __future__ import annotations import math lowerCamelCase : List[Any] = '''2020.9.26''' lowerCamelCase : str = '''xcodz-dot, cclaus, dhruvmanila''' def snake_case_ ( lowerCAmelCase_ : float , lowerCAmelCase_ : float , lowerCAmelCas...
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'''simple docstring''' from transformers import DistilBertTokenizer, DistilBertTokenizerFast from transformers.testing_utils import require_tokenizers, slow from ..bert.test_tokenization_bert import BertTokenizationTest @require_tokenizers class SCREAMING_SNAKE_CASE ( _a ): """s...
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from itertools import permutations def snake_case_ ( lowerCAmelCase_ : tuple ): if num[3] % 2 != 0: return False if (num[2] + num[3] + num[4]) % 3 != 0: return False if num[5] % 5 != 0: return False __lowercase : ...
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import json import os import tempfile from unittest.mock import patch import torch from torch.utils.data import DataLoader, TensorDataset from accelerate import DistributedType, infer_auto_device_map, init_empty_weights from accelerate.accelerator import Accelerator from accelerate.state impor...
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import os from shutil import copyfile from typing import Any, Dict, List, Optional, Tuple import sentencepiece as spm from ...tokenization_utils import PreTrainedTokenizer from ...utils import logging lowerCamelCase : int = '''▁''' lowerCamelCase : Optional[int] = ...
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import math from ...configuration_utils import PretrainedConfig from ...utils import logging __a = logging.get_logger(__name__) __a = { 'facebook/data2vec-base-960h': 'https://huggingface.co/facebook/data2vec-audio-base-960h/resolve/main/config.json', # See all Data2VecAudio mode...
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lowerCamelCase : Optional[Any] = '''ABCDEFGHIJKLMNOPQRSTUVWXYZ''' def snake_case_ ( ): __lowercase : List[str] = input("""Enter message: """ ) __lowercase : int = input("""Enter key [alphanumeric]: """ ) __lowercase : ...
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'''simple docstring''' from typing import TYPE_CHECKING from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tokenizers_available, is_torch_available __SCREAMING_SNAKE_CASE : Optional[int] = { """configuration_altclip""": [ """ALTCLIP_PRETRAINED_CONFIG_ARCHIVE_MAP""", ...
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import secrets from random import shuffle from string import ascii_letters, ascii_lowercase, ascii_uppercase, digits, punctuation def snake_case_ ( lowerCAmelCase_ : int = 8 ): __lowercase : str = ascii_letters + digits + punctuation return "".join(secrets.choice(l...
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def SCREAMING_SNAKE_CASE_ ( __A : int , __A : int ) -> int: """simple docstring""" return 1 if input_a == input_a else 0 def SCREAMING_SNAKE_CASE_ ( ) -> None: """simple docstring""" assert xnor_gate(0 , 0 ) == ...
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import argparse import json from pathlib import Path import torch import torchaudio from datasets import load_dataset from huggingface_hub import hf_hub_download from transformers import ASTConfig, ASTFeatureExtractor, ASTForAudioClassification from transformers.utils import logging logging.set_verbosity_inf...
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"""simple docstring""" import os import unittest from transformers.models.phobert.tokenization_phobert import VOCAB_FILES_NAMES, PhobertTokenizer from ...test_tokenization_common import TokenizerTesterMixin class _UpperCAmelCase ( _A , unittest.TestCase ): ...
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from ...configuration_utils import PretrainedConfig from ...utils import logging lowerCamelCase : Optional[Any] = logging.get_logger(__name__) lowerCamelCase : List[str] = { '''google/canine-s''': '''https://huggingface.co/google/canine-s/resolve/main/config.jso...
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'''simple docstring''' def snake_case_ (_a : Any ): UpperCAmelCase = [] UpperCAmelCase = set({'''(''', '''[''', '''{'''} ) UpperCAmelCase = set({''')''', ''']''', '''}'''} ) UpperCAmelCase = {'''{''': '''}''', '''[''': '''...
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import random import unittest import numpy as np from diffusers import ( DPMSolverMultistepScheduler, EulerAncestralDiscreteScheduler, EulerDiscreteScheduler, LMSDiscreteScheduler, OnnxStableDiffusionImgaImgPipeline, PNDMScheduler, ) from diffusers.utils import floats_tensor from diffus...
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'''simple docstring''' import copy import os import cva import numpy as np from matplotlib import pyplot as plt class UpperCAmelCase_ : """simple docstring""" def __init__( self : Dict ): snake_case__ : Optional[int] = """""" ...
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import math class lowerCAmelCase : '''simple docstring''' def __init__( self : Tuple , __a : int=0 ) -> Optional[Any]: # a graph with Node 0,1,...,N-1 """simple docstring""" __lowercase : Any = n __lowercase : ...
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from typing import TYPE_CHECKING from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_flax_available, is_torch_available _snake_case = { "configuration_longt5": ["LONGT5_PRETRAINED_CONFIG_ARCHIVE_MAP", "LongT5Config", "LongT5OnnxConfig"], } try: if not is_torch_available(): ...
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lowerCamelCase : Dict = '''0.21.0''' from .accelerator import Accelerator from .big_modeling import ( cpu_offload, cpu_offload_with_hook, disk_offload, dispatch_model, init_empty_weights, init_on_device, load_checkpoint_and_dispatch, ) from .data_loader import s...
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'''simple docstring''' import copy import os from typing import Union from ...configuration_utils import PretrainedConfig from ...utils import logging _lowerCAmelCase = logging.get_logger(__name__) _lowerCAmelCase = { '''google/pix2struct-textcaps-base''': ( '''https://hug...
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from maths.prime_check import is_prime def snake_case_ ( lowerCAmelCase_ : int ): if not isinstance(lowerCAmelCase_ , lowerCAmelCase_ ): __lowercase : Dict = F"Input value of [number={number}] must be an integer" raise TypeError(lower...
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import copy import inspect import unittest import numpy as np from huggingface_hub import hf_hub_download from transformers import TimesformerConfig from transformers.models.auto import get_values from transformers.testing_utils import require_torch, require_vision, slow, torch_device from transformers.utils i...
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# flake8: noqa # Lint as: python3 lowerCamelCase : Optional[Any] = [ '''VerificationMode''', '''Version''', '''disable_progress_bar''', '''enable_progress_bar''', '''is_progress_bar_enabled''', '''experimental''', ] from .info_utils import VerificationMode from .log...
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from __future__ import annotations import unittest import numpy as np from transformers import OPTConfig, is_tf_available from transformers.testing_utils import require_sentencepiece, require_tf, slow from ...test_configuration_common import ConfigTester from ...test_modeling_tf_common impor...
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lowerCamelCase : Tuple = {'''a''': ['''c''', '''b'''], '''b''': ['''d''', '''e'''], '''c''': [], '''d''': [], '''e''': []} lowerCamelCase : int = ['''a''', '''b''', '''c''', '''d''', '''e'''] def snake_case_ ( lowerCAmelCase_ : Optional[int] , low...
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"""simple docstring""" import argparse import json from pathlib import Path import torch import torchaudio from datasets import load_dataset from huggingface_hub import hf_hub_download from transformers import ASTConfig, ASTFeatureExtractor, ASTForAudioClassification from transformers.u...
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import copy import tempfile import unittest from transformers import MaMaaaConfig, is_torch_available from transformers.testing_utils import require_sentencepiece, require_tokenizers, require_torch, slow, torch_device from transformers.utils import cached_property from ...generation.test_utils import Generatio...
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'''simple docstring''' def SCREAMING_SNAKE_CASE_ (UpperCamelCase , UpperCamelCase ) -> int: if len(UpperCamelCase ) != len(UpperCamelCase ): raise ValueError("""String lengths must match!""" ) lowerCamelCase__ :...
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# Copyright 2023 The HuggingFace Inc. team. All rights reserved. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required ...
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'''simple docstring''' import json import os import unittest from transformers.models.gptsan_japanese.tokenization_gptsan_japanese import ( VOCAB_FILES_NAMES, GPTSanJapaneseTokenizer, ) from transformers.testing_utils import require_tokenizers, slow from ...test_tokenization_common import TokenizerTes...
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import unittest from transformers import CamembertTokenizer, CamembertTokenizerFast from transformers.testing_utils import get_tests_dir, require_sentencepiece, require_tokenizers, slow from transformers.utils import is_torch_available from ...test_tokenization_common import TokenizerTesterMixin lowerCamelCa...
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from string import ascii_lowercase, ascii_uppercase def lowerCamelCase ( SCREAMING_SNAKE_CASE ): '''simple docstring''' if not sentence: return "" __UpperCamelCase :Optional[Any] = dict(zip(SCREAMING_SNAKE_CASE , SCREAMING_SNAKE_CASE ) ) return lower_to_upper.get(sentenc...
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import argparse from transformers import ( TapasConfig, TapasForMaskedLM, TapasForQuestionAnswering, TapasForSequenceClassification, TapasModel, TapasTokenizer, load_tf_weights_in_tapas, ) from transformers.utils import logging logging.set_verbosity_info() def snake_case_ ...
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"""simple docstring""" from collections.abc import Callable import numpy as np def SCREAMING_SNAKE_CASE ( _lowerCamelCase : Callable ,_lowerCamelCase : float ,_lowerCamelCase : float ,_lowerCamelCase : float ,_lowerCamelCase : float )...
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def snake_case_ ( lowerCAmelCase_ : list ): if len(lowerCAmelCase_ ) <= 1: return [tuple(lowerCAmelCase_ )] __lowercase : Any = [] def generate(lowerCAmelCase_ : int , lowerCAmelCase_ : list ): if k ==...
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"""simple docstring""" # Copyright 2021 The HuggingFace Team. All rights reserved. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/...
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from __future__ import annotations def snake_case_ ( lowerCAmelCase_ : int , lowerCAmelCase_ : int ): if partitions <= 0: raise ValueError("""partitions must be a positive number!""" ) if partitions > number_of_bytes: raise ValueError(""...
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"""simple docstring""" from collections import OrderedDict from typing import TYPE_CHECKING, Any, List, Mapping, Optional, Union from ...configuration_utils import PretrainedConfig from ...onnx import OnnxConfig from ...utils import TensorType, logging if TYPE_CHECKING: from ...onnx.config import P...
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from math import pi def snake_case_ ( lowerCAmelCase_ : int , lowerCAmelCase_ : int ): return 2 * pi * radius * (angle / 360) if __name__ == "__main__": print(arc_length(90, 10))
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'''simple docstring''' from ...configuration_utils import PretrainedConfig from ...utils import logging lowerCamelCase : List[str] = logging.get_logger(__name__) lowerCamelCase : Any = {"ctrl": "https://huggingface.co/ctrl/resolve/main/config.json"} class A__ ( A_...
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import inspect import unittest from transformers import ConvNextVaConfig from transformers.models.auto import get_values from transformers.models.auto.modeling_auto import MODEL_FOR_BACKBONE_MAPPING_NAMES, MODEL_MAPPING_NAMES from transformers.testing_utils import require_torch, require_vision, slow, torch_devi...
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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 SCREAMING_SNAKE_CASE__ : ...
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import math def snake_case_ ( lowerCAmelCase_ : int ): if 1 < number < 4: # 2 and 3 are primes return True elif number < 2 or number % 2 == 0 or number % 3 == 0: # Negatives, 0, 1, all even numbers, all multiples of 3 are not primes ...
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import math import time from typing import Dict, List, Optional from torch.utils.data import Dataset from transformers import SeqaSeqTrainer, is_torch_tpu_available from transformers.trainer_utils import PredictionOutput, speed_metrics if is_torch_tpu_available(check_device=False): import torch_xla.core.xla_mo...
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from __future__ import annotations import math lowerCamelCase : List[Any] = '''2020.9.26''' lowerCamelCase : str = '''xcodz-dot, cclaus, dhruvmanila''' def snake_case_ ( lowerCAmelCase_ : float , lowerCAmelCase_ : float , lowerCAmelCas...
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def SCREAMING_SNAKE_CASE ( _UpperCAmelCase ) -> int: lowerCamelCase__ : List[Any] = abs(_UpperCAmelCase ) lowerCamelCase__ : Union[str, Any] = 0 while n > 0: res += n % 10 n //= 10 return res def SCREAMING_SNAKE_CASE ...
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from itertools import permutations def snake_case_ ( lowerCAmelCase_ : tuple ): if num[3] % 2 != 0: return False if (num[2] + num[3] + num[4]) % 3 != 0: return False if num[5] % 5 != 0: return False __lowercase : ...
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from diffusers.utils.testing_utils import require_onnxruntime @require_onnxruntime class __snake_case : pass
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import os from shutil import copyfile from typing import Any, Dict, List, Optional, Tuple import sentencepiece as spm from ...tokenization_utils import PreTrainedTokenizer from ...utils import logging lowerCamelCase : int = '''▁''' lowerCamelCase : Optional[int] = ...
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import argparse import json import requests import torch from huggingface_hub import hf_hub_download from PIL import Image from transformers import SegformerImageProcessor, SwinConfig, UperNetConfig, UperNetForSemanticSegmentation def A_ ( _lowerCAmelCase ) -> List[Any]: UpperCamelCase : ...
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lowerCamelCase : Optional[Any] = '''ABCDEFGHIJKLMNOPQRSTUVWXYZ''' def snake_case_ ( ): __lowercase : List[str] = input("""Enter message: """ ) __lowercase : int = input("""Enter key [alphanumeric]: """ ) __lowercase : ...
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'''simple docstring''' from ...configuration_utils import PretrainedConfig from ...utils import logging a__ : int =logging.get_logger(__name__) a__ : Dict ={ '''weiweishi/roc-bert-base-zh''': '''https://huggingface.co/weiweishi/roc-bert-base-zh/resolve/main/config.json''', } class ...
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import secrets from random import shuffle from string import ascii_letters, ascii_lowercase, ascii_uppercase, digits, punctuation def snake_case_ ( lowerCAmelCase_ : int = 8 ): __lowercase : str = ascii_letters + digits + punctuation return "".join(secrets.choice(l...
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"""simple docstring""" def UpperCAmelCase__ (lowerCAmelCase_ ): '''simple docstring''' if upper_limit < 0: raise ValueError("Limit for the Catalan sequence must be ≥ 0" ) __SCREAMING_SNAKE_CASE = [0] * (upper_limit + 1) # Base case: C(0) = C(1) = 1...
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import argparse import json from pathlib import Path import torch import torchaudio from datasets import load_dataset from huggingface_hub import hf_hub_download from transformers import ASTConfig, ASTFeatureExtractor, ASTForAudioClassification from transformers.utils import logging logging.set_verbosity_inf...
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'''simple docstring''' import os import sys import unittest a_ : Optional[Any] = os.path.abspath(os.path.dirname(os.path.dirname(os.path.dirname(__file__)))) sys.path.append(os.path.join(git_repo_path, """utils""")) import get_test_info # noqa: E402 from get_test_info import ( # noqa: E4...
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from ...configuration_utils import PretrainedConfig from ...utils import logging lowerCamelCase : Optional[Any] = logging.get_logger(__name__) lowerCamelCase : List[str] = { '''google/canine-s''': '''https://huggingface.co/google/canine-s/resolve/main/config.jso...
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'''simple docstring''' from math import pow def __magic_name__ ( __UpperCAmelCase, __UpperCAmelCase, __UpperCAmelCase, __UpperCAmelCase, __UpperCAmelCase, ) -> tuple[int, int]: '''simple docstring''' if current_sum == needed_sum: # If the sum of the power...
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import random import unittest import numpy as np from diffusers import ( DPMSolverMultistepScheduler, EulerAncestralDiscreteScheduler, EulerDiscreteScheduler, LMSDiscreteScheduler, OnnxStableDiffusionImgaImgPipeline, PNDMScheduler, ) from diffusers.utils import floats_tensor from diffus...
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"""simple docstring""" from typing import TYPE_CHECKING from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available A : Union[str, Any] = { "configuration_clipseg": [ "CLIPSEG_PRETRAINED_CONFIG_ARCHIVE_MAP", "CLIPSegConfig", "CLIPSegTextConfig",...
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import math class lowerCAmelCase : '''simple docstring''' def __init__( self : Tuple , __a : int=0 ) -> Optional[Any]: # a graph with Node 0,1,...,N-1 """simple docstring""" __lowercase : Any = n __lowercase : ...
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'''simple docstring''' import math def lowerCamelCase ( __lowerCamelCase : int ) ->str: _SCREAMING_SNAKE_CASE = 0 _SCREAMING_SNAKE_CASE = 0 while num > 0: _SCREAMING_SNAKE_CASE = num % 8 _SCREAMING_SNAKE_CASE = octal + (...
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lowerCamelCase : Dict = '''0.21.0''' from .accelerator import Accelerator from .big_modeling import ( cpu_offload, cpu_offload_with_hook, disk_offload, dispatch_model, init_empty_weights, init_on_device, load_checkpoint_and_dispatch, ) from .data_loader import s...
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import argparse import json from pathlib import Path import requests import torch from huggingface_hub import cached_download, hf_hub_url from PIL import Image from transformers import DPTConfig, DPTForDepthEstimation, DPTForSemanticSegmentation, DPTImageProcessor from transformers.utils import logging ...
59
from maths.prime_check import is_prime def snake_case_ ( lowerCAmelCase_ : int ): if not isinstance(lowerCAmelCase_ , lowerCAmelCase_ ): __lowercase : Dict = F"Input value of [number={number}] must be an integer" raise TypeError(lower...
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"""simple docstring""" import os from shutil import copyfile from typing import List, Optional, Tuple from ...tokenization_utils import AddedToken from ...tokenization_utils_fast import PreTrainedTokenizerFast from ...utils import is_sentencepiece_available, logging if is_sentencepiece_available(): from .to...
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# flake8: noqa # Lint as: python3 lowerCamelCase : Optional[Any] = [ '''VerificationMode''', '''Version''', '''disable_progress_bar''', '''enable_progress_bar''', '''is_progress_bar_enabled''', '''experimental''', ] from .info_utils import VerificationMode from .log...
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