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def UpperCamelCase ( lowerCAmelCase__ = 1000 ): '''simple docstring''' lowercase = -1 lowercase = 0 for a in range(1 , n // 3 ): # Solving the two equations a**2+b**2=c**2 and a+b+c=N eliminating c lowercase = (n * n - 2 * a *...
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from __future__ import annotations __a = [] def __lowercase ( _UpperCamelCase, _UpperCamelCase, _UpperCamelCase ) ->bool: """simple docstring""" for i in range(len(_UpperCamelCase ) ): if board[row][i] == 1: return False for i in r...
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"""simple docstring""" import argparse import torch # Step 1. clone https://github.com/microsoft/unilm # Step 2. git checkout to https://github.com/microsoft/unilm/commit/b94ec76c36f02fb2b0bf0dcb0b8554a2185173cd # Step 3. cd unilm # Step 4. ln -s $(realpath wavlm/modules.py) ./ # create simlink # import classes f...
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from typing import TYPE_CHECKING from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tf_available, is_torch_available __a = { '''configuration_ctrl''': ['''CTRL_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''CTRLConfig'''], '''tokenization_ctrl''': ['''CTRLTokenizer'''], } try: if not ...
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def UpperCamelCase( __UpperCamelCase : int ): lowerCAmelCase_ : Union[str, Any] = int(__UpperCamelCase ) if decimal in (0, 1): # Exit cases for the recursion return str(__UpperCamelCase ) lowerCAmelCase_ , lowerCAmelCase_ : Tuple = divmod(__UpperCamelCase ,...
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from collections.abc import Callable class __SCREAMING_SNAKE_CASE : def __init__( self , SCREAMING_SNAKE_CASE__ = None ): # Stores actual heap items. lowercase : list = [] # Stores indexes of each item for supporting update...
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'''simple docstring''' import unittest from transformers import DebertaConfig, is_torch_available from transformers.testing_utils import require_sentencepiece, require_tokenizers, require_torch, slow, torch_device from ...test_configuration_common import ConfigTester from ...test_modeling_common import ModelT...
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from dataclasses import dataclass from typing import List, Optional, Union import numpy as np import torch from ...utils import BaseOutput, OptionalDependencyNotAvailable, is_torch_available, is_transformers_available @dataclass class __SCREAMING_SNAKE_CASE ( A__ ): A : Union[List[np....
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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 T...
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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 from .tokenization_blenderbot import Ble...
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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_configuration_common import...
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from transformers import HfArgumentParser, TensorFlowBenchmark, TensorFlowBenchmarkArguments def __lowercase ( ) ->int: """simple docstring""" lowercase : Tuple = HfArgumentParser(_UpperCamelCase ) lowercase : List[str] = parser.parse_args_in...
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from ...configuration_utils import PretrainedConfig from ...utils import logging __lowerCAmelCase : Optional[Any] = logging.get_logger(__name__) __lowerCAmelCase : str = {'openai-gpt': 'https://huggingface.co/openai-gpt/resolve/main/config.json'} class snake_case__ (_Up...
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def __lowercase ( _UpperCamelCase, _UpperCamelCase, _UpperCamelCase, _UpperCamelCase ) ->Union[str, Any]: """simple docstring""" lowercase : Union[str, Any] = [False] * len(_UpperCamelCase ) lowercase : Optional[int] = [] queue.appe...
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"""simple docstring""" import functools import logging import os import sys import threading from logging import ( CRITICAL, # NOQA DEBUG, # NOQA ERROR, # NOQA FATAL, # NOQA INFO, # NOQA NOTSET, # NOQA WARN, # NOQA WARNING, # NOQA ) from typing import Optional import h...
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from typing import List from .keymap import KEYMAP, get_character def __lowercase ( _UpperCamelCase ) ->int: """simple docstring""" def decorator(_UpperCamelCase ): lowercase : str = getattr(_UpperCamelCase, '''handle_key''', [] ) han...
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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 if is_torch_avai...
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import logging import os from .state import PartialState class __SCREAMING_SNAKE_CASE ( logging.LoggerAdapter ): @staticmethod def __lowerCamelCase ( SCREAMING_SNAKE_CASE__ ): lowercase : List[Any] = PartialState() return not ...
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'''simple docstring''' import inspect import tempfile import unittest from huggingface_hub import hf_hub_download from transformers import is_torch_available from transformers.testing_utils import is_flaky, require_torch, slow, torch_device from ...test_configuration_common import ConfigT...
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import argparse import pytorch_lightning as pl import torch from torch import nn from transformers import LongformerForQuestionAnswering, LongformerModel class __SCREAMING_SNAKE_CASE ( pl.LightningModule ): def __init__( self , SCREAMING_SNAKE_CASE__ ): super...
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"""simple docstring""" def lowercase_ ( _lowerCamelCase: List[Any] ) -> list: '''simple docstring''' for i in range(len(_UpperCamelCase ) - 1 , 0 , -1 ): __lowerCamelCase : Optional[Any] = False f...
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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 __a = logging.get_logger(__name__) __a = { '''hustvl/yolos-small''': '''https://hug...
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"""simple docstring""" def __lowercase ( _a = 100 ): snake_case_ : List[Any] = (n * (n + 1) // 2) ** 2 snake_case_ : Any = n * (n + 1) * (2 * n + 1) // 6 return sum_cubes - sum_squares if __name__ == "__main__": print(f'{solution() = }')
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import importlib.metadata import operator import re import sys from typing import Optional from packaging import version __a = { '''<''': operator.lt, '''<=''': operator.le, '''==''': operator.eq, '''!=''': operator.ne, '''>=''': operator.ge, '''>''': operator.gt, } def __lo...
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import argparse import json import os import fairseq import torch from fairseq.data import Dictionary from transformers import ( UniSpeechConfig, UniSpeechForCTC, UniSpeechForPreTraining, WavaVecaFeatureExtractor, WavaVecaPhonemeCTCTokenizer, WavaVecaProcessor, logging, ) logging.se...
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import copy from ...configuration_utils import PretrainedConfig from ...utils import logging from ..auto import CONFIG_MAPPING __a = logging.get_logger(__name__) __a = { '''ut/deta''': '''https://huggingface.co/ut/deta/resolve/main/config.json''', } class __SCREAMING_SNAKE_CASE ...
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"""simple docstring""" def lowerCamelCase_ (): return [list(range(1000 - i , -1000 - i , -1 ) ) for i in range(1000 )] _lowerCAmelCase :Union[str, Any] = generate_large_matrix() _lowerCAmelCase :Any = ( [[4, 3, 2, -1], [3, 2, 1, -1], [1, 1,...
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def __lowercase ( ) ->List[Any]: """simple docstring""" lowercase : Union[str, Any] = 0 for i in range(1, 1001 ): total += i**i return str(_UpperCamelCase )[-10:] if __name__ == "__main__": print(solution())
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def a ( _UpperCAmelCase : Optional[Any] , _UpperCAmelCase : int , _UpperCAmelCase : Tuple , _UpperCAmelCase : List[Any] , _UpperCAmelCase : List[str] ): '''simple docstring''' if index == number_of_item...
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import os import re import shutil import sys import tempfile import unittest import black __a = os.path.abspath(os.path.dirname(os.path.dirname(os.path.dirname(__file__)))) sys.path.append(os.path.join(git_repo_path, '''utils''')) import check_copies # noqa: E402 # This is the reference code that wi...
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'''simple docstring''' from typing import TYPE_CHECKING from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available, is_vision_available lowerCAmelCase : int ={'''configuration_yolos''': ['''YOLOS_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''YolosConfig''', '...
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import math class __SCREAMING_SNAKE_CASE : def __init__( self , SCREAMING_SNAKE_CASE__=0 ): # a graph with Node 0,1,...,N-1 lowercase : List[Any] = n lowercase : List[Any] = [ [math.inf for j in rang...
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'''simple docstring''' from __future__ import annotations from collections.abc import Callable def __UpperCamelCase ( lowercase__ : Tuple, lowercase__ : List[str], lowercase__ : int, lowercase__ : str = 1_00, ): '''simple docstring''' __lowercase =...
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from __future__ import annotations def __lowercase ( _UpperCamelCase ) ->float: """simple docstring""" if not nums: raise ValueError('''List is empty''' ) return sum(_UpperCamelCase ) / len(_UpperCamelCase ) if __name__ == "__main__": import doctest docte...
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'''simple docstring''' import logging import os import random import sys from dataclasses import dataclass, field from typing import Optional import datasets import numpy as np import pandas as pd from datasets import load_dataset import transformers from transformers import ( AutoConfig, BartForSequenceCl...
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import warnings from ...utils import logging from .image_processing_deit import DeiTImageProcessor __a = logging.get_logger(__name__) class __SCREAMING_SNAKE_CASE ( A__ ): def __init__( self , *SCREAMING_SNAKE_CASE__ , **SCREAMING_SNAKE_CASE__ ): ...
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"""simple docstring""" from collections.abc import Iterable from typing import Generic, TypeVar _A = TypeVar("""_T""") class lowerCamelCase ( Generic[_T] ): '''simple docstring''' def __init__(self , _lowerCamelCase = None ): """simple docstring""" Upper...
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from typing import List, Optional, Union import numpy as np import tensorflow as tf from .utils import logging __a = logging.get_logger(__name__) def __lowercase ( _UpperCamelCase ) ->List[int]: """simple docstring""" if isinstance(_UpperCamelCase, np.ndarray ): ...
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"""simple docstring""" import requests def __A ( a_ :Any , a_ :Dict) -> None: __a : Union[str, Any] = {'''Content-Type''': '''application/json'''} __a : Union[str, Any] = requests.post(_UpperCamelCase , json={'''text'...
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def __lowercase ( _UpperCamelCase = 4000000 ) ->int: """simple docstring""" lowercase : int = [] lowercase , lowercase : str = 0, 1 while b <= n: if b % 2 == 0: even_fibs.append(_UpperCamelCase ) ...
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'''simple docstring''' # This code is adapted from OpenAI's release # https://github.com/openai/human-eval/blob/master/human_eval/execution.py import contextlib import faulthandler import io import multiprocessing import os import platform import signal import tempfile def ...
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from collections import OrderedDict from typing import Any, Mapping, Optional, Union from ...configuration_utils import PretrainedConfig from ...feature_extraction_utils import FeatureExtractionMixin from ...onnx import OnnxConfig from ...onnx.utils import compute_effective_axis_dimension from ...tokenization_utils...
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"""simple docstring""" import os import shutil from pathlib import Path from typing import Optional, Union import numpy as np from huggingface_hub import hf_hub_download from ..utils import ONNX_EXTERNAL_WEIGHTS_NAME, ONNX_WEIGHTS_NAME, is_onnx_available, logging if is_onnx_available(): import onnxruntime ...
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import secrets from random import shuffle from string import ascii_letters, ascii_lowercase, ascii_uppercase, digits, punctuation def __lowercase ( _UpperCamelCase = 8 ) ->str: """simple docstring""" lowercase : List[str] = ascii_letters + digits + punctuation ...
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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 .t...
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from __future__ import annotations __a = [] def __lowercase ( _UpperCamelCase, _UpperCamelCase, _UpperCamelCase ) ->bool: """simple docstring""" for i in range(len(_UpperCamelCase ) ): if board[row][i] == 1: return False for i in r...
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import time import unittest from transformers import is_torch_available from transformers.testing_utils import require_torch, torch_device from ..test_modeling_common import ids_tensor if is_torch_available(): import torch from transformers.generation import ( MaxLengthCriteria, MaxNewTokensCr...
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from typing import TYPE_CHECKING from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tf_available, is_torch_available __a = { '''configuration_ctrl''': ['''CTRL_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''CTRLConfig'''], '''tokenization_ctrl''': ['''CTRLTokenizer'''], } try: if not ...
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"""simple docstring""" import argparse import shlex import runhouse as rh if __name__ == "__main__": # Refer to https://runhouse-docs.readthedocs-hosted.com/en/latest/api/python/cluster.html#hardware-setup for cloud access # setup instructions, if using on-demand hardware # If user passes --user <user> --...
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from collections.abc import Callable class __SCREAMING_SNAKE_CASE : def __init__( self , SCREAMING_SNAKE_CASE__ = None ): # Stores actual heap items. lowercase : list = [] # Stores indexes of each item for supporting update...
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def a ( _UpperCAmelCase : Optional[Any] ): '''simple docstring''' __UpperCAmelCase : Union[str, Any] = int(_UpperCamelCase ) if decimal in (0, 1): # Exit cases for the recursion return str(_UpperCamelCase ) __...
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from dataclasses import dataclass from typing import List, Optional, Union import numpy as np import torch from ...utils import BaseOutput, OptionalDependencyNotAvailable, is_torch_available, is_transformers_available @dataclass class __SCREAMING_SNAKE_CASE ( A__ ): A : Union[List[np....
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'''simple docstring''' import gc import tempfile import unittest import numpy as np import torch from diffusers import VersatileDiffusionPipeline from diffusers.utils.testing_utils import load_image, nightly, require_torch_gpu, torch_device lowerCAmelCase : List[Any] =...
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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 from .tokenization_blenderbot import Ble...
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'''simple docstring''' import logging import os import sys from dataclasses import dataclass, field from importlib import import_module from typing import Dict, List, Optional, Tuple import numpy as np from seqeval.metrics import accuracy_score, fa_score, precision_score, recall_score from torch import nn from util...
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from transformers import HfArgumentParser, TensorFlowBenchmark, TensorFlowBenchmarkArguments def __lowercase ( ) ->int: """simple docstring""" lowercase : Tuple = HfArgumentParser(_UpperCamelCase ) lowercase : List[str] = parser.parse_args_in...
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'''simple docstring''' def lowercase ( __magic_name__ ): '''simple docstring''' if not isinstance(_UpperCamelCase , _UpperCamelCase ): UpperCAmelCase : List[str] = F"Input value of [number={number}] must be an integer" raise TypeErr...
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def __lowercase ( _UpperCamelCase, _UpperCamelCase, _UpperCamelCase, _UpperCamelCase ) ->Union[str, Any]: """simple docstring""" lowercase : Union[str, Any] = [False] * len(_UpperCamelCase ) lowercase : Optional[int] = [] queue.appe...
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"""simple docstring""" import importlib import os import sys # This is required to make the module import works (when the python process is running from the root of the repo) sys.path.append(""".""") def a__ ( lowerCAmelCase ) -> str: UpperCAmelCase__ : List[str] = test_file.s...
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from typing import List from .keymap import KEYMAP, get_character def __lowercase ( _UpperCamelCase ) ->int: """simple docstring""" def decorator(_UpperCamelCase ): lowercase : str = getattr(_UpperCamelCase, '''handle_key''', [] ) han...
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"""simple docstring""" from math import cos, sin, sqrt, tau from audio_filters.iir_filter import IIRFilter def __A ( a_ :List[str] , a_ :Optional[int] , a_ :str = 1 / sqrt(2)) -> IIRFilter: __a : Optional[Any] = tau * frequency / sam...
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import logging import os from .state import PartialState class __SCREAMING_SNAKE_CASE ( logging.LoggerAdapter ): @staticmethod def __lowerCamelCase ( SCREAMING_SNAKE_CASE__ ): lowercase : List[Any] = PartialState() return not ...
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'''simple docstring''' import inspect import unittest from transformers import ConvNextConfig 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...
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import argparse import pytorch_lightning as pl import torch from torch import nn from transformers import LongformerForQuestionAnswering, LongformerModel class __SCREAMING_SNAKE_CASE ( pl.LightningModule ): def __init__( self , SCREAMING_SNAKE_CASE__ ): super...
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"""simple docstring""" import logging import os from dataclasses import dataclass, field from typing import Dict, Optional import numpy as np from utils_multiple_choice import MultipleChoiceDataset, Split, processors import transformers from transformers import ( AutoConfig, AutoModelForMultipleChoice, ...
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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 __a = logging.get_logger(__name__) __a = { '''hustvl/yolos-small''': '''https://hug...
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"""simple docstring""" import functools import operator from ...configuration_utils import PretrainedConfig from ...utils import logging lowercase__ : Any = logging.get_logger(__name__) lowercase__ : Dict = { '''asapp/sew-tiny-100k''': '''https://huggingface.co/asapp/sew-tiny-10...
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import importlib.metadata import operator import re import sys from typing import Optional from packaging import version __a = { '''<''': operator.lt, '''<=''': operator.le, '''==''': operator.eq, '''!=''': operator.ne, '''>=''': operator.ge, '''>''': operator.gt, } def __lo...
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from typing import TYPE_CHECKING from ...utils import ( OptionalDependencyNotAvailable, _LazyModule, is_flax_available, is_tf_available, is_torch_available, is_vision_available, ) _lowerCamelCase : Any = {"""configuration_vit""": ["""VIT_PRETRAINED_CONFIG_ARCHIVE_MAP""", ...
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import copy from ...configuration_utils import PretrainedConfig from ...utils import logging from ..auto import CONFIG_MAPPING __a = logging.get_logger(__name__) __a = { '''ut/deta''': '''https://huggingface.co/ut/deta/resolve/main/config.json''', } class __SCREAMING_SNAKE_CASE ...
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"""simple docstring""" from __future__ import annotations from collections import deque from collections.abc import Sequence from dataclasses import dataclass from typing import Any @dataclass class _UpperCAmelCase : '''simple docstring''' a__ =42 a__ =None ...
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def __lowercase ( ) ->List[Any]: """simple docstring""" lowercase : Union[str, Any] = 0 for i in range(1, 1001 ): total += i**i return str(_UpperCamelCase )[-10:] if __name__ == "__main__": print(solution())
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import collections from typing import List, Optional, Union from ...tokenization_utils_base import BatchEncoding from ...utils import TensorType, add_end_docstrings, add_start_docstrings, logging from ..bert.tokenization_bert_fast import BertTokenizerFast from .tokenization_dpr import DPRContextEncoderTo...
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import os import re import shutil import sys import tempfile import unittest import black __a = os.path.abspath(os.path.dirname(os.path.dirname(os.path.dirname(__file__)))) sys.path.append(os.path.join(git_repo_path, '''utils''')) import check_copies # noqa: E402 # This is the reference code that wi...
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'''simple docstring''' from torch import nn def UpperCAmelCase_ ( __lowerCamelCase : int ): if act_fn in ["swish", "silu"]: return nn.SiLU() elif act_fn == "mish": return nn.Mish() elif act_fn == "gelu": return nn.GELU() else: raise Va...
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import math class __SCREAMING_SNAKE_CASE : def __init__( self , SCREAMING_SNAKE_CASE__=0 ): # a graph with Node 0,1,...,N-1 lowercase : List[Any] = n lowercase : List[Any] = [ [math.inf for j in rang...
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'''simple docstring''' from __future__ import annotations class lowerCAmelCase : def __init__( self : int , __lowercase : Tuple ): """simple docstring""" __lowercase =TypeError( 'Matrices must be formed from...
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from __future__ import annotations def __lowercase ( _UpperCamelCase ) ->float: """simple docstring""" if not nums: raise ValueError('''List is empty''' ) return sum(_UpperCamelCase ) / len(_UpperCamelCase ) if __name__ == "__main__": import doctest docte...
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'''simple docstring''' import argparse import json import os import tensorstore as ts import torch from flax import serialization from flax.traverse_util import flatten_dict, unflatten_dict from tensorflow.io import gfile from transformers.modeling_utils import dtype_byte_size from transformers.models.switch_trans...
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import warnings from ...utils import logging from .image_processing_deit import DeiTImageProcessor __a = logging.get_logger(__name__) class __SCREAMING_SNAKE_CASE ( A__ ): def __init__( self , *SCREAMING_SNAKE_CASE__ , **SCREAMING_SNAKE_CASE__ ): ...
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"""simple docstring""" class lowerCamelCase : '''simple docstring''' def __init__(self ): """simple docstring""" UpperCAmelCase__ : dict[str, TrieNode] = {} # Mapping from char to TrieNode UpperCAmelCase__ : Dict = False def ...
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from typing import List, Optional, Union import numpy as np import tensorflow as tf from .utils import logging __a = logging.get_logger(__name__) def __lowercase ( _UpperCamelCase ) ->List[int]: """simple docstring""" if isinstance(_UpperCamelCase, np.ndarray ): ...
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"""simple docstring""" import os from typing import BinaryIO, Optional, Union import numpy as np import pyarrow.parquet as pq from .. import Audio, Dataset, Features, Image, NamedSplit, Value, config from ..features.features import FeatureType, _visit from ..formatting import query_ta...
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def __lowercase ( _UpperCamelCase = 4000000 ) ->int: """simple docstring""" lowercase : int = [] lowercase , lowercase : str = 0, 1 while b <= n: if b % 2 == 0: even_fibs.append(_UpperCamelCase ) ...
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'''simple docstring''' import json import os import tempfile import unittest import unittest.mock as mock from pathlib import Path from requests.exceptions import HTTPError from transformers.utils import ( CONFIG_NAME, FLAX_WEIGHTS_NAME, TF2_WEIGHTS_NAME, TRANSFORMERS_C...
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from collections import OrderedDict from typing import Any, Mapping, Optional, Union from ...configuration_utils import PretrainedConfig from ...feature_extraction_utils import FeatureExtractionMixin from ...onnx import OnnxConfig from ...onnx.utils import compute_effective_axis_dimension from ...tokenization_utils...
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"""simple docstring""" import argparse import pytorch_lightning as pl import torch from torch import nn from transformers import LongformerForQuestionAnswering, LongformerModel class _snake_case ( pl.LightningModule ): def __init__( self : Union[str, Any] , UpperCAmel...
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import secrets from random import shuffle from string import ascii_letters, ascii_lowercase, ascii_uppercase, digits, punctuation def __lowercase ( _UpperCamelCase = 8 ) ->str: """simple docstring""" lowercase : List[str] = ascii_letters + digits + punctuation ...
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"""simple docstring""" import torch from diffusers import DDIMParallelScheduler from .test_schedulers import SchedulerCommonTest class _UpperCAmelCase ( A__): _lowerCAmelCase : Dict = (DDIMParallelScheduler,) _lowerCAmelCase : Union[str, Any] = (('eta', 0.0), ('num_infe...
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from __future__ import annotations __a = [] def __lowercase ( _UpperCamelCase, _UpperCamelCase, _UpperCamelCase ) ->bool: """simple docstring""" for i in range(len(_UpperCamelCase ) ): if board[row][i] == 1: return False for i in r...
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from typing import Dict, Iterable, List, Optional, Union import numpy as np from ...image_processing_utils import BaseImageProcessor, BatchFeature, get_size_dict from ...image_transforms import ( center_crop, get_resize_output_image_size, normalize, rescale, resize, to_channel_dimension_f...
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from typing import TYPE_CHECKING from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tf_available, is_torch_available __a = { '''configuration_ctrl''': ['''CTRL_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''CTRLConfig'''], '''tokenization_ctrl''': ['''CTRLTokenizer'''], } try: if not ...
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"""simple docstring""" import json import os from typing import Optional, Tuple import regex as re from ...tokenization_utils import PreTrainedTokenizer from ...utils import logging _lowerCAmelCase :Tuple = logging.get_logger(__name__) _lowerCAmelCase :str = { 'vocab_file': 'vocab.jso...
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from collections.abc import Callable class __SCREAMING_SNAKE_CASE : def __init__( self , SCREAMING_SNAKE_CASE__ = None ): # Stores actual heap items. lowercase : list = [] # Stores indexes of each item for supporting update...
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from ...configuration_utils import PretrainedConfig from ...utils import logging __A =logging.get_logger(__name__) __A ={ "microsoft/swinv2-tiny-patch4-window8-256": ( "https://huggingface.co/microsoft/swinv2-tiny-patch4-window8-256/resolve/main/config.json" ), } class ...
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from dataclasses import dataclass from typing import List, Optional, Union import numpy as np import torch from ...utils import BaseOutput, OptionalDependencyNotAvailable, is_torch_available, is_transformers_available @dataclass class __SCREAMING_SNAKE_CASE ( A__ ): A : Union[List[np....
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'''simple docstring''' import argparse import numpy as np import torch from transformers import SpeechTaHifiGan, SpeechTaHifiGanConfig, logging logging.set_verbosity_info() lowerCAmelCase : List[Any] =logging.get_logger('''transformers.models.speecht5''') def Upp...
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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 from .tokenization_blenderbot import Ble...
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'''simple docstring''' from typing import TYPE_CHECKING from ...utils import ( OptionalDependencyNotAvailable, _LazyModule, is_tf_available, is_torch_available, is_vision_available, ) UpperCAmelCase = { '''configuration_efficientformer''': [ '''EFFICIENTFORMER_PRETRAINED_...
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from transformers import HfArgumentParser, TensorFlowBenchmark, TensorFlowBenchmarkArguments def __lowercase ( ) ->int: """simple docstring""" lowercase : Tuple = HfArgumentParser(_UpperCamelCase ) lowercase : List[str] = parser.parse_args_in...
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'''simple docstring''' import html from ...feature_extraction_utils import BatchFeature, FeatureExtractionMixin from ...utils import is_bsa_available, logging, requires_backends if is_bsa_available(): import bsa from bsa import BeautifulSoup a : Any = logging.get_logger(__name__) clas...
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def __lowercase ( _UpperCamelCase, _UpperCamelCase, _UpperCamelCase, _UpperCamelCase ) ->Union[str, Any]: """simple docstring""" lowercase : Union[str, Any] = [False] * len(_UpperCamelCase ) lowercase : Optional[int] = [] queue.appe...
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"""simple docstring""" from dataclasses import dataclass from typing import List, Optional, Union import numpy as np import torch from ...utils import BaseOutput, OptionalDependencyNotAvailable, is_torch_available, is_transformers_available @dataclass class lowerCamelCase ( A__ ): '''simple docstri...
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from typing import List from .keymap import KEYMAP, get_character def __lowercase ( _UpperCamelCase ) ->int: """simple docstring""" def decorator(_UpperCamelCase ): lowercase : str = getattr(_UpperCamelCase, '''handle_key''', [] ) han...
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"""simple docstring""" import gc import random import unittest import numpy as np import torch from transformers import CLIPTextConfig, CLIPTextModel, CLIPTokenizer import diffusers from diffusers import ( AutoencoderKL, EulerDiscreteScheduler, StableDiffusionLatentUps...
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import logging import os from .state import PartialState class __SCREAMING_SNAKE_CASE ( logging.LoggerAdapter ): @staticmethod def __lowerCamelCase ( SCREAMING_SNAKE_CASE__ ): lowercase : List[Any] = PartialState() return not ...
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'''simple docstring''' from argparse import ArgumentParser, Namespace from typing import Any, List, Optional from ..pipelines import Pipeline, get_supported_tasks, pipeline from ..utils import logging from . import BaseTransformersCLICommand try: from fastapi import Body, FastAPI, HTTPE...
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import argparse import pytorch_lightning as pl import torch from torch import nn from transformers import LongformerForQuestionAnswering, LongformerModel class __SCREAMING_SNAKE_CASE ( pl.LightningModule ): def __init__( self , SCREAMING_SNAKE_CASE__ ): super...
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"""simple docstring""" from functools import lru_cache def lowercase_ ( _lowerCamelCase: List[str] ) -> set: '''simple docstring''' __lowerCamelCase : Optional[int] = 2 __lowerCamelCase : Optional[Any] = set() ...
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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 __a = logging.get_logger(__name__) __a = { '''hustvl/yolos-small''': '''https://hug...
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"""simple docstring""" import math class _UpperCAmelCase : def _snake_case ( self : Optional[int] , lowercase_ : Tuple , lowercase_ : List[Any] ): snake_case_ : Optional[int] = 0.0 snake_case_ : Any = 0.0 for i in range...
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import importlib.metadata import operator import re import sys from typing import Optional from packaging import version __a = { '''<''': operator.lt, '''<=''': operator.le, '''==''': operator.eq, '''!=''': operator.ne, '''>=''': operator.ge, '''>''': operator.gt, } def __lo...
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import json import os import unittest from transformers.models.ctrl.tokenization_ctrl import VOCAB_FILES_NAMES, CTRLTokenizer from ...test_tokenization_common import TokenizerTesterMixin class UpperCamelCase_ ( A__ , unittest.TestCase ): '''simple docstring''' UpperCAmelCase__ ...
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import copy from ...configuration_utils import PretrainedConfig from ...utils import logging from ..auto import CONFIG_MAPPING __a = logging.get_logger(__name__) __a = { '''ut/deta''': '''https://huggingface.co/ut/deta/resolve/main/config.json''', } class __SCREAMING_SNAKE_CASE ...
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"""simple docstring""" import json import os from dataclasses import dataclass from functools import partial from typing import Callable import flax.linen as nn import jax import jax.numpy as jnp import joblib import optax import wandb from flax import jax_utils, struct, traverse_util from flax.serialization impor...
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def __lowercase ( ) ->List[Any]: """simple docstring""" lowercase : Union[str, Any] = 0 for i in range(1, 1001 ): total += i**i return str(_UpperCamelCase )[-10:] if __name__ == "__main__": print(solution())
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import math def a ( _UpperCAmelCase : Optional[Any] = 1_00 ): '''simple docstring''' __UpperCAmelCase : Tuple = sum(i * i for i in range(1 , n + 1 ) ) __UpperCAmelCase : List[Any] = int(math.pow...
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import os import re import shutil import sys import tempfile import unittest import black __a = os.path.abspath(os.path.dirname(os.path.dirname(os.path.dirname(__file__)))) sys.path.append(os.path.join(git_repo_path, '''utils''')) import check_copies # noqa: E402 # This is the reference code that wi...
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'''simple docstring''' import unittest from transformers import BertGenerationTokenizer from transformers.testing_utils import get_tests_dir, require_sentencepiece, require_torch, slow from transformers.utils import cached_property from ...test_tokenization_common import TokenizerTesterMixin ...
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import math class __SCREAMING_SNAKE_CASE : def __init__( self , SCREAMING_SNAKE_CASE__=0 ): # a graph with Node 0,1,...,N-1 lowercase : List[Any] = n lowercase : List[Any] = [ [math.inf for j in rang...
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'''simple docstring''' from importlib import import_module from .logging import get_logger UpperCAmelCase = get_logger(__name__) class lowerCAmelCase : def __init__( self : Tuple , __lowercase : Dict , __lowercase : Any=None ): ...
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from __future__ import annotations def __lowercase ( _UpperCamelCase ) ->float: """simple docstring""" if not nums: raise ValueError('''List is empty''' ) return sum(_UpperCamelCase ) / len(_UpperCamelCase ) if __name__ == "__main__": import doctest docte...
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'''simple docstring''' import dataclasses import json import warnings from dataclasses import dataclass, field from time import time from typing import List from ..utils import logging a : Dict = logging.get_logger(__name__) def lowercase ( __magic_name__=None , __magic_name__=No...
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import warnings from ...utils import logging from .image_processing_deit import DeiTImageProcessor __a = logging.get_logger(__name__) class __SCREAMING_SNAKE_CASE ( A__ ): def __init__( self , *SCREAMING_SNAKE_CASE__ , **SCREAMING_SNAKE_CASE__ ): ...
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"""simple docstring""" from dataclasses import dataclass from enum import Enum from typing import List, Optional, Union import numpy as np import PIL from PIL import Image from ...utils import BaseOutput, is_torch_available, is_transformers_available @dataclass class lowerCamelCase ( A__ ): '''simp...
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from typing import List, Optional, Union import numpy as np import tensorflow as tf from .utils import logging __a = logging.get_logger(__name__) def __lowercase ( _UpperCamelCase ) ->List[int]: """simple docstring""" if isinstance(_UpperCamelCase, np.ndarray ): ...
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"""simple docstring""" def __A ( a_ :List[Any] , a_ :Tuple) -> Optional[int]: __a : Tuple = (boundary[1] - boundary[0]) / steps __a : List[str] = boundary[0] __a : Any = boundary[1] __a : Union[st...
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def __lowercase ( _UpperCamelCase = 4000000 ) ->int: """simple docstring""" lowercase : int = [] lowercase , lowercase : str = 0, 1 while b <= n: if b % 2 == 0: even_fibs.append(_UpperCamelCase ) ...
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'''simple docstring''' import json import re from typing import TYPE_CHECKING, List, Optional, Tuple, Union import numpy as np from ...utils import is_tf_available, is_torch_available, logging if TYPE_CHECKING: if is_torch_available(): import torch if is_tf_available(): i...
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from collections import OrderedDict from typing import Any, Mapping, Optional, Union from ...configuration_utils import PretrainedConfig from ...feature_extraction_utils import FeatureExtractionMixin from ...onnx import OnnxConfig from ...onnx.utils import compute_effective_axis_dimension from ...tokenization_utils...
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"""simple docstring""" import gc import unittest import torch from transformers import CLIPTextConfig, CLIPTextModel, CLIPTextModelWithProjection, CLIPTokenizer from diffusers import ( AutoencoderKL, DDIMScheduler, DDPMScheduler, PriorTransformer, StableUnCLIPPipeline, UNetaDConditionMode...
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import secrets from random import shuffle from string import ascii_letters, ascii_lowercase, ascii_uppercase, digits, punctuation def __lowercase ( _UpperCamelCase = 8 ) ->str: """simple docstring""" lowercase : List[str] = ascii_letters + digits + punctuation ...
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"""simple docstring""" import unittest import numpy as np import torch from transformers import CLIPTextConfig, CLIPTextModel from diffusers import DDIMScheduler, LDMPipeline, UNetaDModel, VQModel from diffusers.utils.testing_utils import enable_full_determinism, require_torch, slow, torch_device enable_full_d...
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from __future__ import annotations __a = [] def __lowercase ( _UpperCamelCase, _UpperCamelCase, _UpperCamelCase ) ->bool: """simple docstring""" for i in range(len(_UpperCamelCase ) ): if board[row][i] == 1: return False for i in r...
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from ...configuration_utils import PretrainedConfig from ...utils import logging _lowerCamelCase : Optional[int] = logging.get_logger(__name__) _lowerCamelCase : str = { """facebook/dpr-ctx_encoder-single-nq-base""": ( """https://huggingface.co/facebook/dpr-ctx_encode...
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from typing import TYPE_CHECKING from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tf_available, is_torch_available __a = { '''configuration_ctrl''': ['''CTRL_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''CTRLConfig'''], '''tokenization_ctrl''': ['''CTRLTokenizer'''], } try: if not ...
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"""simple docstring""" from datetime import datetime import matplotlib.pyplot as plt import torch def lowerCamelCase_ (UpperCamelCase__ : List[str] ): for param in module.parameters(): _UpperCAmelCase : Optional[int] = False def lowerCamelCase_ (): ...
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from collections.abc import Callable class __SCREAMING_SNAKE_CASE : def __init__( self , SCREAMING_SNAKE_CASE__ = None ): # Stores actual heap items. lowercase : list = [] # Stores indexes of each item for supporting update...
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from typing import TYPE_CHECKING from ...utils import ( OptionalDependencyNotAvailable, _LazyModule, is_flax_available, is_tf_available, is_torch_available, ) __A ={"configuration_unispeech": ["UNISPEECH_PRETRAINED_CONFIG_ARCHIVE_MAP", "UniSpeechConfig"]} try: if n...
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from dataclasses import dataclass from typing import List, Optional, Union import numpy as np import torch from ...utils import BaseOutput, OptionalDependencyNotAvailable, is_torch_available, is_transformers_available @dataclass class __SCREAMING_SNAKE_CASE ( A__ ): A : Union[List[np....
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'''simple docstring''' import contextlib import copy import random from typing import Any, Dict, Iterable, Optional, Union import numpy as np import torch from .utils import deprecate, is_transformers_available if is_transformers_available(): import transformers def UpperCAmelC...
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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 from .tokenization_blenderbot import Ble...
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'''simple docstring''' import argparse import os import torch from transformers import ( XLNetConfig, XLNetForQuestionAnswering, XLNetForSequenceClassification, XLNetLMHeadModel, load_tf_weights_in_xlnet, ) from transformers.utils import CONFIG_NAME, WEIGHTS_NAME, logging UpperCAmelCase ...
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from transformers import HfArgumentParser, TensorFlowBenchmark, TensorFlowBenchmarkArguments def __lowercase ( ) ->int: """simple docstring""" lowercase : Tuple = HfArgumentParser(_UpperCamelCase ) lowercase : List[str] = parser.parse_args_in...
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'''simple docstring''' import secrets from random import shuffle from string import ascii_letters, ascii_lowercase, ascii_uppercase, digits, punctuation def lowercase ( __magic_name__ = 8 ): '''simple docstring''' UpperCAmelCase : List[str] = ascii_letters...
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def __lowercase ( _UpperCamelCase, _UpperCamelCase, _UpperCamelCase, _UpperCamelCase ) ->Union[str, Any]: """simple docstring""" lowercase : Union[str, Any] = [False] * len(_UpperCamelCase ) lowercase : Optional[int] = [] queue.appe...
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"""simple docstring""" # limitations under the License. # NOTE: This file is deprecated and will be removed in a future version. # It only exists so that temporarely `from diffusers.pipelines import DiffusionPipeline` works from .pipelines import DiffusionPipeline, ImagePipelineOutput # noqa: F401 from .utils impo...
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from typing import List from .keymap import KEYMAP, get_character def __lowercase ( _UpperCamelCase ) ->int: """simple docstring""" def decorator(_UpperCamelCase ): lowercase : str = getattr(_UpperCamelCase, '''handle_key''', [] ) han...
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"""simple docstring""" def __A ( a_ :Optional[int] , a_ :int) -> int: return number | (1 << position) def __A ( a_ :Union[str, Any] , a_ :List[str]) -> int: return number & ~(1 << position) def __A ( a_ :Optional[int]...
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import logging import os from .state import PartialState class __SCREAMING_SNAKE_CASE ( logging.LoggerAdapter ): @staticmethod def __lowerCamelCase ( SCREAMING_SNAKE_CASE__ ): lowercase : List[Any] = PartialState() return not ...
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'''simple docstring''' from ...configuration_utils import PretrainedConfig from ...utils import logging __A : Optional[Any] = logging.get_logger(__name__) __A : int = { "microsoft/cvt-13": "https://huggingface.co/microsoft/cvt-13/resolve/main/conf...
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import argparse import pytorch_lightning as pl import torch from torch import nn from transformers import LongformerForQuestionAnswering, LongformerModel class __SCREAMING_SNAKE_CASE ( pl.LightningModule ): def __init__( self , SCREAMING_SNAKE_CASE__ ): super...
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"""simple docstring""" import json import os from functools import lru_cache from typing import List, Optional, Tuple import regex as re from ...tokenization_utils import AddedToken, PreTrainedTokenizer from ...utils import logging __A = logging.get_logger(__name__) __A = {'''vocab_file''': '''vocab....
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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 __a = logging.get_logger(__name__) __a = { '''hustvl/yolos-small''': '''https://hug...
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"""simple docstring""" import os def __lowercase ( ): snake_case_ : int = os.path.join(os.path.dirname(_UpperCamelCase ) , '''num.txt''' ) with open(_UpperCamelCase ) as file_hand: return str(sum(int(_UpperCamelCase ) for line in file_hand ) )[:10] if __nam...
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import importlib.metadata import operator import re import sys from typing import Optional from packaging import version __a = { '''<''': operator.lt, '''<=''': operator.le, '''==''': operator.eq, '''!=''': operator.ne, '''>=''': operator.ge, '''>''': operator.gt, } def __lo...
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from __future__ import annotations import numpy as np from numpy import floataa from numpy.typing import NDArray def SCREAMING_SNAKE_CASE ( lowercase_ , lowercase_ , lowercase_ , lowercase_ , ) -> list[float]: """simple docstring""" A__ = coefficient_...
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import copy from ...configuration_utils import PretrainedConfig from ...utils import logging from ..auto import CONFIG_MAPPING __a = logging.get_logger(__name__) __a = { '''ut/deta''': '''https://huggingface.co/ut/deta/resolve/main/config.json''', } class __SCREAMING_SNAKE_CASE ...
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"""simple docstring""" from collections.abc import Callable from math import pi, sqrt from random import uniform from statistics import mean def lowerCamelCase_ (UpperCamelCase__ : Any ): def is_in_circle(UpperCamelCase__ : Any , UpperCamelCase__ : Optional[Any] ) -> bool...
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def __lowercase ( ) ->List[Any]: """simple docstring""" lowercase : Union[str, Any] = 0 for i in range(1, 1001 ): total += i**i return str(_UpperCamelCase )[-10:] if __name__ == "__main__": print(solution())
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from __future__ import annotations def a ( _UpperCAmelCase : Any ): '''simple docstring''' return [ord(_UpperCamelCase ) - 96 for elem in plain] def a ( _UpperCAmelCase : Optional[Any] ): ''...
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import os import re import shutil import sys import tempfile import unittest import black __a = os.path.abspath(os.path.dirname(os.path.dirname(os.path.dirname(__file__)))) sys.path.append(os.path.join(git_repo_path, '''utils''')) import check_copies # noqa: E402 # This is the reference code that wi...
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'''simple docstring''' from copy import deepcopy from typing import Optional, Union import numpy as np from ...processing_utils import ProcessorMixin from ...tokenization_utils_base import BatchEncoding from ...utils import TensorType, is_tf_available, is_torch_available if is_torch_avail...
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import math class __SCREAMING_SNAKE_CASE : def __init__( self , SCREAMING_SNAKE_CASE__=0 ): # a graph with Node 0,1,...,N-1 lowercase : List[Any] = n lowercase : List[Any] = [ [math.inf for j in rang...
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'''simple docstring''' from __future__ import annotations from collections import Counter from random import random class lowerCAmelCase : def __init__( self : int ): """simple docstring""" __lowercase ={} def snake_ca...
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from __future__ import annotations def __lowercase ( _UpperCamelCase ) ->float: """simple docstring""" if not nums: raise ValueError('''List is empty''' ) return sum(_UpperCamelCase ) / len(_UpperCamelCase ) if __name__ == "__main__": import doctest docte...
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'''simple docstring''' import logging import os from .state import PartialState class UpperCamelCase__ ( logging.LoggerAdapter ): """simple docstring""" @staticmethod def A_ ( snake_case ): '''simple docstring''' UpperCAmelCase : List[Any] = Pa...
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import warnings from ...utils import logging from .image_processing_deit import DeiTImageProcessor __a = logging.get_logger(__name__) class __SCREAMING_SNAKE_CASE ( A__ ): def __init__( self , *SCREAMING_SNAKE_CASE__ , **SCREAMING_SNAKE_CASE__ ): ...
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"""simple docstring""" from typing import TYPE_CHECKING from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available _A = { """configuration_swinv2""": ["""SWINV2_PRETRAINED_CONFIG_ARCHIVE_MAP""", """Swinv2Config"""], } try: if not is_torch_available(): raise Optio...
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from typing import List, Optional, Union import numpy as np import tensorflow as tf from .utils import logging __a = logging.get_logger(__name__) def __lowercase ( _UpperCamelCase ) ->List[int]: """simple docstring""" if isinstance(_UpperCamelCase, np.ndarray ): ...
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"""simple docstring""" from ....configuration_utils import PretrainedConfig from ....utils import logging A = logging.get_logger(__name__) # TODO: upload to AWS A = { '''yjernite/retribert-base-uncased''': ( '''https://huggingface.co/yjernite/retrib...
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def __lowercase ( _UpperCamelCase = 4000000 ) ->int: """simple docstring""" lowercase : int = [] lowercase , lowercase : str = 0, 1 while b <= n: if b % 2 == 0: even_fibs.append(_UpperCamelCase ) ...
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'''simple docstring''' def UpperCamelCase_ ( A__ : Union[str, Any] ): '''simple docstring''' lowerCAmelCase_ : str = 0 for ch in input_str: lowerCAmelCase_ : Dict = ord(_UpperCamelCase ) lowerCAmelCase_ : str = pow(2...
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from collections import OrderedDict from typing import Any, Mapping, Optional, Union from ...configuration_utils import PretrainedConfig from ...feature_extraction_utils import FeatureExtractionMixin from ...onnx import OnnxConfig from ...onnx.utils import compute_effective_axis_dimension from ...tokenization_utils...
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"""simple docstring""" def lowercase_ ( ) -> List[Any]: '''simple docstring''' __lowerCamelCase : Union[str, Any] = 0 for i in range(1 , 1001 ): total += i**i return str(_UpperCamelCase )[-10:] if __name__ ...
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import secrets from random import shuffle from string import ascii_letters, ascii_lowercase, ascii_uppercase, digits, punctuation def __lowercase ( _UpperCamelCase = 8 ) ->str: """simple docstring""" lowercase : List[str] = ascii_letters + digits + punctuation ...
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"""simple docstring""" from typing import TYPE_CHECKING from ...utils import ( OptionalDependencyNotAvailable, _LazyModule, is_sentencepiece_available, is_tokenizers_available, is_torch_available, ) lowercase__ : Union[str, Any] = {'''configuration_reformer''': ['''REFORMER_PRE...
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from __future__ import annotations __a = [] def __lowercase ( _UpperCamelCase, _UpperCamelCase, _UpperCamelCase ) ->bool: """simple docstring""" for i in range(len(_UpperCamelCase ) ): if board[row][i] == 1: return False for i in r...
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from sklearn.metrics import matthews_corrcoef import datasets _lowerCamelCase : str = """ Compute the Matthews correlation coefficient (MCC) The Matthews correlation coefficient is used in machine learning as a measure of the quality of binary and multiclass classifications. It takes into accou...
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from typing import TYPE_CHECKING from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tf_available, is_torch_available __a = { '''configuration_ctrl''': ['''CTRL_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''CTRLConfig'''], '''tokenization_ctrl''': ['''CTRLTokenizer'''], } try: if not ...
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"""simple docstring""" from transformers import HfArgumentParser, TensorFlowBenchmark, TensorFlowBenchmarkArguments def lowerCamelCase_ (): _UpperCAmelCase : Tuple = HfArgumentParser(_UpperCamelCase ) _UpperCAmelCase : List[str] = parser.parse_args_in...
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from collections.abc import Callable class __SCREAMING_SNAKE_CASE : def __init__( self , SCREAMING_SNAKE_CASE__ = None ): # Stores actual heap items. lowercase : list = [] # Stores indexes of each item for supporting update...
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def a ( _UpperCAmelCase : Optional[Any] = 4_00_00_00 ): '''simple docstring''' __UpperCAmelCase : int = [] __UpperCAmelCase : str = 0, 1 while b <= n: if b % 2 == 0: even_fibs.append(_UpperCamel...
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from dataclasses import dataclass from typing import List, Optional, Union import numpy as np import torch from ...utils import BaseOutput, OptionalDependencyNotAvailable, is_torch_available, is_transformers_available @dataclass class __SCREAMING_SNAKE_CASE ( A__ ): A : Union[List[np....
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'''simple docstring''' from __future__ import annotations import unittest from transformers import is_tf_available from transformers.testing_utils import require_tf, slow from ...test_configuration_common import ConfigTester from ...test_modeling_tf_common import TFModelTesterMixin, ids_tens...
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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 from .tokenization_blenderbot import Ble...
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'''simple docstring''' def __UpperCamelCase ( lowercase__ : List[Any], lowercase__ : str ): '''simple docstring''' assert x is not None assert y is not None __lowercase =len(_UpperCamelCase ) __lowercase =len(_UpperCamelCase ) ...
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from transformers import HfArgumentParser, TensorFlowBenchmark, TensorFlowBenchmarkArguments def __lowercase ( ) ->int: """simple docstring""" lowercase : Tuple = HfArgumentParser(_UpperCamelCase ) lowercase : List[str] = parser.parse_args_in...
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'''simple docstring''' from __future__ import annotations def lowercase ( __magic_name__ ): '''simple docstring''' if len(_UpperCamelCase ) == 0: return array UpperCAmelCase : Union[str, Any] = min(_UpperCamelCase ), max(_UpperC...
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def __lowercase ( _UpperCamelCase, _UpperCamelCase, _UpperCamelCase, _UpperCamelCase ) ->Union[str, Any]: """simple docstring""" lowercase : Union[str, Any] = [False] * len(_UpperCamelCase ) lowercase : Optional[int] = [] queue.appe...
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"""simple docstring""" from binascii import hexlify from hashlib import shaaaa from os import urandom # RFC 3526 - More Modular Exponential (MODP) Diffie-Hellman groups for # Internet Key Exchange (IKE) https://tools.ietf.org/html/rfc3526 _A = { # 1536-bit 5: { """prime""": int( ...
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from typing import List from .keymap import KEYMAP, get_character def __lowercase ( _UpperCamelCase ) ->int: """simple docstring""" def decorator(_UpperCamelCase ): lowercase : str = getattr(_UpperCamelCase, '''handle_key''', [] ) han...
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"""simple docstring""" from typing import TYPE_CHECKING # rely on isort to merge the imports from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available A = {'''configuration_focalnet''': ['''FOCALNET_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''FocalNetConf...
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import logging import os from .state import PartialState class __SCREAMING_SNAKE_CASE ( logging.LoggerAdapter ): @staticmethod def __lowerCamelCase ( SCREAMING_SNAKE_CASE__ ): lowercase : List[Any] = PartialState() return not ...
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'''simple docstring''' import inspect import unittest import torch import torch.nn as nn from accelerate.hooks import ( AlignDevicesHook, ModelHook, SequentialHook, add_hook_to_module, attach_align_device_hook, remove_hook_from_module, remove_hook_from_submo...
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import argparse import pytorch_lightning as pl import torch from torch import nn from transformers import LongformerForQuestionAnswering, LongformerModel class __SCREAMING_SNAKE_CASE ( pl.LightningModule ): def __init__( self , SCREAMING_SNAKE_CASE__ ): super...
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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 __A = '''\ @INPROCEEDINGS{Papineni02bleu:a, author = {Kishore Papineni and Salim Roukos and Todd Ward and Wei-jing Zhu}, title = {BLEU: a Method for Au...
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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 __a = logging.get_logger(__name__) __a = { '''hustvl/yolos-small''': '''https://hug...
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"""simple docstring""" from __future__ import annotations import unittest from transformers import EsmConfig, is_tf_available from transformers.testing_utils import require_tf, slow from ...test_configuration_common import ConfigTester from ...test_modeling_tf_common import TFModelTesterMixin, floats_tensor, id...
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import importlib.metadata import operator import re import sys from typing import Optional from packaging import version __a = { '''<''': operator.lt, '''<=''': operator.le, '''==''': operator.eq, '''!=''': operator.ne, '''>=''': operator.ge, '''>''': operator.gt, } def __lo...
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