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'''simple docstring''' from typing import TYPE_CHECKING from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tokenizers_available, is_torch_available __lowercase : Union[str, Any] = { 'configuration_roc_bert': ['ROC_BERT_PRETRAINED_CONFIG_ARCHIVE_MAP', 'RoCBertConfig'], 'tok...
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'''simple docstring''' import sys __lowercase : Union[str, Any] = ( '73167176531330624919225119674426574742355349194934' '96983520312774506326239578318016984801869478851843' '85861560789112949495459501737958331952853208805511' '12540698747158523863050715693290963295227443043557' ...
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'''simple docstring''' import argparse import torch from transformers import LxmertConfig, LxmertForPreTraining, load_tf_weights_in_lxmert from transformers.utils import logging logging.set_verbosity_info() def lowerCamelCase (_SCREAMING_SNAKE_CASE : Any , _SCREAMING_SNAKE_CASE ...
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'''simple docstring''' import json import os import re import unittest from transformers import CodeGenTokenizer, CodeGenTokenizerFast from transformers.models.codegen.tokenization_codegen import VOCAB_FILES_NAMES from transformers.testing_utils import require_tokenizers, slow from ...test_tokenization_common i...
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'''simple docstring''' from .glue import glue_convert_examples_to_features, glue_output_modes, glue_processors, glue_tasks_num_labels from .squad import SquadExample, SquadFeatures, SquadVaProcessor, SquadVaProcessor, squad_convert_examples_to_features from .utils import DataProcessor, InputExample, InputFeatures...
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'''simple docstring''' def lowerCamelCase (_SCREAMING_SNAKE_CASE : int , _SCREAMING_SNAKE_CASE : int ): if not isinstance(_SCREAMING_SNAKE_CASE , _SCREAMING_SNAKE_CASE ): raise ValueError('iterations must be defined as integers' ) if ...
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'''simple docstring''' import requests __lowercase : List[str] = 'https://newsapi.org/v1/articles?source=bbc-news&sortBy=top&apiKey=' def lowerCamelCase (_SCREAMING_SNAKE_CASE : str ): # fetching a list of articles in json format __a : List[str] = requ...
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'''simple docstring''' import unittest import numpy as np from transformers.testing_utils import require_pytesseract, require_torch from transformers.utils import is_pytesseract_available, is_torch_available from ...test_image_processing_common import ImageProcessingSavingTestMixin, prepare_image_inputs if i...
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'''simple docstring''' def lowerCamelCase (_SCREAMING_SNAKE_CASE : int = 1_000 ): __a : Any = 3 __a : Tuple = 0 while a < n: if a % 3 == 0 or a % 5 == 0: result += a elif a % 15 == 0: result -= a a ...
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'''simple docstring''' from __future__ import annotations from typing import Dict from ...configuration_utils import PretrainedConfig __lowercase : List[Any] = { 'susnato/ernie-m-base_pytorch': 'https://huggingface.co/susnato/ernie-m-base_pytorch/blob/main/config.json', 'susnato/ernie-m-l...
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'''simple docstring''' import sys import warnings from os.path import abspath, dirname, join # allow having multiple repository checkouts and not needing to remember to rerun # 'pip install -e .[dev]' when switching between checkouts and running tests. __lowercase : Dict = abspath(join(dirname(dirn...
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'''simple docstring''' import gc import importlib.metadata import tempfile import unittest from packaging import version from transformers import ( AutoModel, AutoModelForCausalLM, AutoModelForSeqaSeqLM, AutoModelForSequenceClassification, AutoTokenizer, BitsAndBytesConfig, pipeline,...
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'''simple docstring''' import logging import os import threading import time try: import warnings except ImportError: __lowercase : Optional[Any] = None try: import msvcrt except ImportError: __lowercase : int = None try: import fcntl except ImportError: __lowercase : ...
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'''simple docstring''' from dataclasses import dataclass from typing import Optional, Tuple import torch from torch import nn from transformers import RobertaPreTrainedModel, XLMRobertaConfig, XLMRobertaModel from transformers.utils import ModelOutput @dataclass class __UpperCamelCase ( lowerCAme...
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'''simple docstring''' import gc import unittest import numpy as np import torch from transformers import CLIPTextConfig, CLIPTextModel, CLIPTokenizer from diffusers import ( AutoencoderKL, DDIMScheduler, StableDiffusionAttendAndExcitePipeline, UNetaDConditionModel, ) from diffusers.utils import...
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'''simple docstring''' from typing import TYPE_CHECKING from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tokenizers_available, is_torch_available __lowercase : Union[str, Any] = { 'configuration_roc_bert': ['ROC_BERT_PRETRAINED_CONFIG_ARCHIVE_MAP', 'RoCBertConfig'], 'to...
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'''simple docstring''' import gc import random import unittest import numpy as np import torch from PIL import Image from transformers import XLMRobertaTokenizerFast from diffusers import DDIMScheduler, KandinskyInpaintPipeline, KandinskyPriorPipeline, UNetaDConditionModel, VQModel from diffusers.pipelines.kan...
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'''simple docstring''' from typing import Optional, Union import torch from torch import nn from torch.nn import BCEWithLogitsLoss, CrossEntropyLoss, MSELoss from ...activations import ACTaFN from ...modeling_outputs import BaseModelOutputWithPoolingAndNoAttention, ImageClassifierOutputWithNoAttention from ...m...
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from dataclasses import dataclass from typing import Optional, Tuple import torch from torch import nn from transformers import RobertaPreTrainedModel, XLMRobertaConfig, XLMRobertaModel from transformers.utils import ModelOutput @dataclass class __UpperCamelCase ( lowerCAmelCase_ ): A_ = ...
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'''simple docstring''' import json import os import re import sys import urllib.request import requests from bsa import BeautifulSoup __lowercase : str = { 'User-Agent': 'Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36' ' (KHTML, like Gecko) Chrome/70.0.3538.102 Safari/537.36 E...
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'''simple docstring''' from typing import TYPE_CHECKING from ...utils import ( OptionalDependencyNotAvailable, _LazyModule, is_flax_available, is_tf_available, is_torch_available, ) __lowercase : str = { 'configuration_wav2vec2': ['WAV_2_VEC_2_PRETRAINED_CONFIG_ARCHIVE_MAP'...
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'''simple docstring''' import os def lowerCamelCase (): with open(os.path.dirname(_SCREAMING_SNAKE_CASE ) + '/p022_names.txt' ) as file: __a : List[Any] = str(file.readlines()[0] ) __a : str = names.replace('"' , '' ).split('...
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'''simple docstring''' from __future__ import annotations from PIL import Image # Define glider example __lowercase : Union[str, Any] = [ [0, 1, 0, 0, 0, 0, 0, 0], [0, 0, 1, 0, 0, 0, 0, 0], [1, 1, 1, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0], [0, 0, ...
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'''simple docstring''' __lowercase : Optional[Any] = {'a': ['c', 'b'], 'b': ['d', 'e'], 'c': [], 'd': [], 'e': []} __lowercase : List[str] = ['a', 'b', 'c', 'd', 'e'] def lowerCamelCase (_SCREAMING_SNAKE_CASE : List[Any] , _SCREAMING_SNAKE_CASE : A...
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'''simple docstring''' import warnings from ...configuration_utils import PretrainedConfig from ...utils import logging __lowercase : Any = logging.get_logger(__name__) __lowercase : Dict = { 'RUCAIBox/mvp': 'https://huggingface.co/RUCAIBox/mvp/resolve/main/config.json', } c...
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'''simple docstring''' def lowerCamelCase (_SCREAMING_SNAKE_CASE : int ): return number & 1 == 0 if __name__ == "__main__": import doctest doctest.testmod()
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'''simple docstring''' import math import sys def lowerCamelCase (_SCREAMING_SNAKE_CASE : int ): if number != int(_SCREAMING_SNAKE_CASE ): raise ValueError('the value of input must be a natural number' ) if number < 0: raise ValueError('the va...
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'''simple docstring''' from typing import TYPE_CHECKING from ...utils import ( OptionalDependencyNotAvailable, _LazyModule, is_flax_available, is_tf_available, is_tokenizers_available, is_torch_available, ) __lowercase : Tuple = { 'configuration_distilbert': [ '...
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'''simple docstring''' from collections import OrderedDict from typing import Mapping from packaging import version from ...configuration_utils import PretrainedConfig from ...onnx import OnnxConfig from ...utils import logging __lowercase : Optional[Any] = logging.get_logger(__name__) __lowerca...
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'''simple docstring''' import shutil import tempfile import unittest from transformers import ClapFeatureExtractor, ClapProcessor, RobertaTokenizer, RobertaTokenizerFast from transformers.testing_utils import require_sentencepiece, require_torchaudio from .test_feature_extraction_clap import floats_list @r...
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'''simple docstring''' import doctest import glob import importlib import inspect import os import re from contextlib import contextmanager from functools import wraps from unittest.mock import patch import numpy as np import pytest from absl.testing import parameterized import datasets from datasets import load...
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'''simple docstring''' import unittest from transformers import DebertaVaConfig, 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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'''simple docstring''' import argparse import requests import torch # pip3 install salesforce-lavis # I'm actually installing a slightly modified version: pip3 install git+https://github.com/nielsrogge/LAVIS.git@fix_lavis_float32 (there's also the fix_lavis branch) # also note: to convert Vicuna checkpoints, we...
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'''simple docstring''' import os import socket from contextlib import contextmanager import torch from ..commands.config.default import write_basic_config # noqa: F401 from ..state import PartialState from .dataclasses import DistributedType from .imports import is_deepspeed_available, is_tpu_available from .t...
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'''simple docstring''' __lowercase : Optional[int] = '\n# Transformers installation\n! pip install transformers datasets\n# To install from source instead of the last release, comment the command above and uncomment the following one.\n# ! pip install git+https://github.com/huggingface/transformers.g...
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'''simple docstring''' from .imports import is_rich_available if is_rich_available(): from rich.traceback import install install(show_locals=False) else: raise ModuleNotFoundError('To use the rich extension, install rich with `pip install rich`')
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'''simple docstring''' import unittest from transformers import is_torch_available from transformers.testing_utils import require_torch if is_torch_available(): import torch from transformers.activations import gelu_new, gelu_python, get_activation @require_torch class __UpperCamelCase ( uni...
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'''simple docstring''' from __future__ import annotations from dataclasses import dataclass @dataclass class __UpperCamelCase : A_ = 42 A_ = None A_ = None def lowerCamelCase (_SCREAMING_SNAKE_CASE : TreeNode | None ): # Val...
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'''simple docstring''' import copy import json import os import tempfile from transformers import is_torch_available from .test_configuration_utils import config_common_kwargs class __UpperCamelCase ( lowerCAmelCase_ ): def __init__( self , __a , __a=None , __a...
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'''simple docstring''' # tests directory-specific settings - this file is run automatically # by pytest before any tests are run import sys import warnings from os.path import abspath, dirname, join # allow having multiple repository checkouts and not needing to remember to rerun # 'pip install -e .[dev]' when...
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'''simple docstring''' import numpy as np def lowerCamelCase (_SCREAMING_SNAKE_CASE : np.ndarray , _SCREAMING_SNAKE_CASE : float ): return np.where(vector > 0 , _SCREAMING_SNAKE_CASE , (alpha * (np.exp(_SCREAMING_SNAKE_CASE ) - 1)) ) ...
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'''simple docstring''' import re from filelock import FileLock try: import nltk __lowercase : Optional[Any] = True except (ImportError, ModuleNotFoundError): __lowercase : Dict = False if NLTK_AVAILABLE: with FileLock('.lock') as lock: nltk.download('punkt', quiet=True) ...
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'''simple docstring''' from typing import Optional, Union import torch from torch import nn from torch.nn import BCEWithLogitsLoss, CrossEntropyLoss, MSELoss from ...activations import ACTaFN from ...modeling_outputs import BaseModelOutputWithPoolingAndNoAttention, ImageClassifierOutputWithNoAttention from ...m...
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'''simple docstring''' import numpy as np import skfuzzy as fuzz if __name__ == "__main__": # Create universe of discourse in Python using linspace () __lowercase : int = np.linspace(start=0, stop=75, num=75, endpoint=True, retstep=False) # Create two fuzzy sets by defining any membership functi...
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'''simple docstring''' from __future__ import annotations def lowerCamelCase (_SCREAMING_SNAKE_CASE : list[int | float] , _SCREAMING_SNAKE_CASE : int , _SCREAMING_SNAKE_CASE : int ): if len(_SCREAMING_SNAKE_CASE ) == 0: raise Value...
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'''simple docstring''' import sys __lowercase : Union[str, Any] = ( '73167176531330624919225119674426574742355349194934' '96983520312774506326239578318016984801869478851843' '85861560789112949495459501737958331952853208805511' '12540698747158523863050715693290963295227443043557' ...
294
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'''simple docstring''' import argparse import shutil from pathlib import Path from tqdm import tqdm from transformers import AutoTokenizer def lowerCamelCase (_SCREAMING_SNAKE_CASE : str , _SCREAMING_SNAKE_CASE : Optional[int] , _SCREAMING_SNAKE_CASE : Tu...
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'''simple docstring''' import json import os import re import unittest from transformers import CodeGenTokenizer, CodeGenTokenizerFast from transformers.models.codegen.tokenization_codegen import VOCAB_FILES_NAMES from transformers.testing_utils import require_tokenizers, slow from ...test_tokenization_common i...
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'''simple docstring''' import numpy as np from nltk.translate import meteor_score import datasets from datasets.config import importlib_metadata, version __lowercase : List[str] = version.parse(importlib_metadata.version('nltk')) if NLTK_VERSION >= version.Version('3.6.4'): from nltk import word_...
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'''simple docstring''' def lowerCamelCase (_SCREAMING_SNAKE_CASE : int , _SCREAMING_SNAKE_CASE : int ): if not isinstance(_SCREAMING_SNAKE_CASE , _SCREAMING_SNAKE_CASE ): raise ValueError('iterations must be defined as integers' ) if ...
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'''simple docstring''' import baseaa def lowerCamelCase (_SCREAMING_SNAKE_CASE : str ): return baseaa.aaaencode(string.encode('utf-8' ) ) def lowerCamelCase (_SCREAMING_SNAKE_CASE : bytes ): return baseaa.aaadecode(_SCREAMING_SNAKE_CA...
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'''simple docstring''' import unittest import numpy as np from transformers.testing_utils import require_pytesseract, require_torch from transformers.utils import is_pytesseract_available, is_torch_available from ...test_image_processing_common import ImageProcessingSavingTestMixin, prepare_image_inputs if i...
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'''simple docstring''' import re def lowerCamelCase (_SCREAMING_SNAKE_CASE : str ): __a : Dict = re.compile(r'^(\+91[\-\s]?)?[0]?(91)?[789]\d{9}$' ) if match := re.search(_SCREAMING_SNAKE_CASE , _SCREAMING_SNAKE_CASE ): return match.str...
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'''simple docstring''' from __future__ import annotations from typing import Dict from ...configuration_utils import PretrainedConfig __lowercase : List[Any] = { 'susnato/ernie-m-base_pytorch': 'https://huggingface.co/susnato/ernie-m-base_pytorch/blob/main/config.json', 'susnato/ernie-m-l...
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'''simple docstring''' import functools def lowerCamelCase (_SCREAMING_SNAKE_CASE : list[int] , _SCREAMING_SNAKE_CASE : list[int] ): # Validation if not isinstance(_SCREAMING_SNAKE_CASE , _SCREAMING_SNAKE_CASE ) or not all(isinstance(_SCREAMIN...
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'''simple docstring''' import gc import importlib.metadata import tempfile import unittest from packaging import version from transformers import ( AutoModel, AutoModelForCausalLM, AutoModelForSeqaSeqLM, AutoModelForSequenceClassification, AutoTokenizer, BitsAndBytesConfig, pipeline,...
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'''simple docstring''' import os def lowerCamelCase (): with open(os.path.dirname(_SCREAMING_SNAKE_CASE ) + '/p022_names.txt' ) as file: __a : List[Any] = str(file.readlines()[0] ) __a : str = names.replace('"' , '' ).split('...
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'''simple docstring''' from dataclasses import dataclass from typing import Optional, Tuple import torch from torch import nn from transformers import RobertaPreTrainedModel, XLMRobertaConfig, XLMRobertaModel from transformers.utils import ModelOutput @dataclass class __UpperCamelCase ( lowerCAme...
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'''simple docstring''' from __future__ import annotations def lowerCamelCase (_SCREAMING_SNAKE_CASE : list[list[int]] ): # preprocessing the first row for i in range(1 , len(matrix[0] ) ): matrix[0][i] += matrix[0][i - 1] # preprocessing ...
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'''simple docstring''' from typing import TYPE_CHECKING from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tokenizers_available, is_torch_available __lowercase : Union[str, Any] = { 'configuration_roc_bert': ['ROC_BERT_PRETRAINED_CONFIG_ARCHIVE_MAP', 'RoCBertConfig'], 'to...
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'''simple docstring''' import argparse import os import re import zipfile import torch from transformers import AutoTokenizer, GPTaConfig def lowerCamelCase (_SCREAMING_SNAKE_CASE : Any , _SCREAMING_SNAKE_CASE : Optional[Any] , _SCREAMING_SNAKE_CASE : Li...
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'''simple docstring''' from typing import Optional, Union import torch from torch import nn from torch.nn import BCEWithLogitsLoss, CrossEntropyLoss, MSELoss from ...activations import ACTaFN from ...modeling_outputs import BaseModelOutputWithPoolingAndNoAttention, ImageClassifierOutputWithNoAttention from ...m...
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from typing import TYPE_CHECKING from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tf_available, is_torch_available __lowercase : Optional[Any] = { 'configuration_groupvit': [ 'GROUPVIT_PRETRAINED_CONFIG_ARCHIVE_MAP', 'GroupViTConfig', 'GroupViTOnnxConfi...
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'''simple docstring''' import json import os import re import sys import urllib.request import requests from bsa import BeautifulSoup __lowercase : str = { 'User-Agent': 'Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36' ' (KHTML, like Gecko) Chrome/70.0.3538.102 Safari/537.36 E...
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'''simple docstring''' import numpy as np import skfuzzy as fuzz if __name__ == "__main__": # Create universe of discourse in Python using linspace () __lowercase : int = np.linspace(start=0, stop=75, num=75, endpoint=True, retstep=False) # Create two fuzzy sets by defining any me...
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'''simple docstring''' import os def lowerCamelCase (): with open(os.path.dirname(_SCREAMING_SNAKE_CASE ) + '/p022_names.txt' ) as file: __a : List[Any] = str(file.readlines()[0] ) __a : str = names.replace('"' , '' ).split('...
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'''simple docstring''' from typing import TYPE_CHECKING from ...utils import ( OptionalDependencyNotAvailable, _LazyModule, is_sentencepiece_available, is_speech_available, is_torch_available, ) __lowercase : List[str] = { 'configuration_trocr': ['TROCR_PRETRAINED_CONFIG_AR...
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'''simple docstring''' __lowercase : Optional[Any] = {'a': ['c', 'b'], 'b': ['d', 'e'], 'c': [], 'd': [], 'e': []} __lowercase : List[str] = ['a', 'b', 'c', 'd', 'e'] def lowerCamelCase (_SCREAMING_SNAKE_CASE : List[Any] , _SCREAMING_SNAKE_CASE : A...
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'''simple docstring''' import logging import re import pytorch_quantization import pytorch_quantization.nn as quant_nn import torch from pytorch_quantization import calib from pytorch_quantization.tensor_quant import QuantDescriptor __lowercase : Tuple = logging.getLogger(__name__) __lowercase ...
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'''simple docstring''' def lowerCamelCase (_SCREAMING_SNAKE_CASE : int ): return number & 1 == 0 if __name__ == "__main__": import doctest doctest.testmod()
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'''simple docstring''' 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 __lowercase : Tuple = ( 'This metric will be removed from the l...
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'''simple docstring''' from typing import TYPE_CHECKING from ...utils import ( OptionalDependencyNotAvailable, _LazyModule, is_flax_available, is_tf_available, is_tokenizers_available, is_torch_available, ) __lowercase : Tuple = { 'configuration_distilbert': [ '...
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'''simple docstring''' from __future__ import annotations class __UpperCamelCase : def __init__( self , __a = 0 ): '''simple docstring''' __a : List[Any] = key def __UpperCAmelCase ( self , __a , __a ): ...
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'''simple docstring''' import shutil import tempfile import unittest from transformers import ClapFeatureExtractor, ClapProcessor, RobertaTokenizer, RobertaTokenizerFast from transformers.testing_utils import require_sentencepiece, require_torchaudio from .test_feature_extraction_clap import floats_list @r...
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'''simple docstring''' import inspect from typing import List, Optional, Tuple, Union import numpy as np import PIL import torch import torch.utils.checkpoint from ...models import UNetaDModel, VQModel from ...schedulers import ( DDIMScheduler, DPMSolverMultistepScheduler, EulerAncestralDiscreteSched...
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'''simple docstring''' import unittest from transformers import DebertaVaConfig, 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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'''simple docstring''' import os import unittest from transformers import BatchEncoding from transformers.models.bert.tokenization_bert import ( BasicTokenizer, WordpieceTokenizer, _is_control, _is_punctuation, _is_whitespace, ) from transformers.models.prophetnet.tokenization_prophetnet impo...
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'''simple docstring''' import os import socket from contextlib import contextmanager import torch from ..commands.config.default import write_basic_config # noqa: F401 from ..state import PartialState from .dataclasses import DistributedType from .imports import is_deepspeed_available, is_tpu_available from .t...
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'''simple docstring''' from typing import TYPE_CHECKING from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available __lowercase : List[str] = { 'configuration_upernet': ['UperNetConfig'], } try: if not is_torch_available(): raise OptionalDependenc...
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'''simple docstring''' from .imports import is_rich_available if is_rich_available(): from rich.traceback import install install(show_locals=False) else: raise ModuleNotFoundError('To use the rich extension, install rich with `pip install rich`')
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'''simple docstring''' from collections import OrderedDict from typing import Mapping from ...configuration_utils import PretrainedConfig from ...onnx import OnnxConfig from ...utils import logging __lowercase : Optional[int] = logging.get_logger(__name__) __lowercase : Any = { '...
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'''simple docstring''' from __future__ import annotations from dataclasses import dataclass @dataclass class __UpperCamelCase : A_ = 42 A_ = None A_ = None def lowerCamelCase (_SCREAMING_SNAKE_CASE : TreeNode | None ): # Val...
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'''simple docstring''' def lowerCamelCase (_SCREAMING_SNAKE_CASE : List[str]=28_123 ) -> Union[str, Any]: __a : Union[str, Any] = [1] * (limit + 1) for i in range(2 , int(limit**0.5 ) + 1 ): sum_divs[i * i] += i for k in range(i...
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'''simple docstring''' # tests directory-specific settings - this file is run automatically # by pytest before any tests are run import sys import warnings from os.path import abspath, dirname, join # allow having multiple repository checkouts and not needing to remember to rerun # 'pip install -e .[dev]' when...
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'''simple docstring''' __lowercase : Optional[Any] = {'a': ['c', 'b'], 'b': ['d', 'e'], 'c': [], 'd': [], 'e': []} __lowercase : List[str] = ['a', 'b', 'c', 'd', 'e'] def lowerCamelCase (_SCREAMING_SNAKE_CASE : List[Any] , _SCREAMING_SNAKE_CASE : A...
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'''simple docstring''' import re from filelock import FileLock try: import nltk __lowercase : Optional[Any] = True except (ImportError, ModuleNotFoundError): __lowercase : Dict = False if NLTK_AVAILABLE: with FileLock('.lock') as lock: nltk.download('punkt', quiet=True) ...
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'''simple docstring''' import argparse import json from pathlib import Path import requests import timm import torch from huggingface_hub import hf_hub_download from PIL import Image from transformers import DeiTConfig, DeiTForImageClassificationWithTeacher, DeiTImageProcessor from transformers.utils import log...
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'''simple docstring''' import numpy as np import skfuzzy as fuzz if __name__ == "__main__": # Create universe of discourse in Python using linspace () __lowercase : int = np.linspace(start=0, stop=75, num=75, endpoint=True, retstep=False) # Create two fuzzy sets by defining any membership functi...
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'''simple docstring''' from __future__ import annotations __lowercase : int = list[list[int]] # assigning initial values to the grid __lowercase : Matrix = [ [3, 0, 6, 5, 0, 8, 4, 0, 0], [5, 2, 0, 0, 0, 0, 0, 0, 0], [0, 8, 7, 0, 0, 0, 0, 3, 1], [0, 0, 3, 0, 1, 0, 0, 8, 0...
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'''simple docstring''' import sys __lowercase : Union[str, Any] = ( '73167176531330624919225119674426574742355349194934' '96983520312774506326239578318016984801869478851843' '85861560789112949495459501737958331952853208805511' '12540698747158523863050715693290963295227443043557' ...
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'''simple docstring''' import math from typing import Optional import numpy as np from ...configuration_utils import PretrainedConfig from ...utils import logging __lowercase : List[str] = logging.get_logger(__name__) __lowercase : Optional[int] = { 'facebook/encodec_24khz': 'ht...
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'''simple docstring''' import json import os import re import unittest from transformers import CodeGenTokenizer, CodeGenTokenizerFast from transformers.models.codegen.tokenization_codegen import VOCAB_FILES_NAMES from transformers.testing_utils import require_tokenizers, slow from ...test_tokenization_common i...
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'''simple docstring''' from __future__ import annotations import math def lowerCamelCase (_SCREAMING_SNAKE_CASE : int ): if num <= 0: __a : List[Any] = F"""{num}: Invalid input, please enter a positive integer.""" raise ValueError(_SCREAMING_SNAKE_C...
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'''simple docstring''' def lowerCamelCase (_SCREAMING_SNAKE_CASE : int , _SCREAMING_SNAKE_CASE : int ): if not isinstance(_SCREAMING_SNAKE_CASE , _SCREAMING_SNAKE_CASE ): raise ValueError('iterations must be defined as integers' ) if ...
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'''simple docstring''' import json import os import subprocess import unittest from ast import literal_eval import pytest from parameterized import parameterized, parameterized_class from . import is_sagemaker_available if is_sagemaker_available(): from sagemaker import Session, TrainingJobAnalytics from sa...
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'''simple docstring''' import unittest import numpy as np from transformers.testing_utils import require_pytesseract, require_torch from transformers.utils import is_pytesseract_available, is_torch_available from ...test_image_processing_common import ImageProcessingSavingTestMixin, prepare_image_inputs if i...
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'''simple docstring''' from transformers import HfArgumentParser, TensorFlowBenchmark, TensorFlowBenchmarkArguments def lowerCamelCase (): __a : Dict = HfArgumentParser(_SCREAMING_SNAKE_CASE ) __a : Union[str, Any] = parser.parse_args_into_dataclasses()[0] __a ...
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'''simple docstring''' from __future__ import annotations from typing import Dict from ...configuration_utils import PretrainedConfig __lowercase : List[Any] = { 'susnato/ernie-m-base_pytorch': 'https://huggingface.co/susnato/ernie-m-base_pytorch/blob/main/config.json', 'susnato/ernie-m-l...
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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_av...
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'''simple docstring''' import gc import importlib.metadata import tempfile import unittest from packaging import version from transformers import ( AutoModel, AutoModelForCausalLM, AutoModelForSeqaSeqLM, AutoModelForSequenceClassification, AutoTokenizer, BitsAndBytesConfig, pipeline,...
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'''simple docstring''' import unittest from transformers import TrOCRConfig from transformers.testing_utils import is_torch_available, require_torch, torch_device from ...generation.test_utils import GenerationTesterMixin from ...test_configuration_common import ConfigTester from ...test_modeling_common import ...
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'''simple docstring''' from dataclasses import dataclass from typing import Optional, Tuple import torch from torch import nn from transformers import RobertaPreTrainedModel, XLMRobertaConfig, XLMRobertaModel from transformers.utils import ModelOutput @dataclass class __UpperCamelCase ( lowerCAme...
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'''simple docstring''' import unittest from transformers.utils.backbone_utils import ( BackboneMixin, get_aligned_output_features_output_indices, verify_out_features_out_indices, ) class __UpperCamelCase ( unittest.TestCase ): def __UpperCAmelCase ( self ): ...
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'''simple docstring''' from typing import TYPE_CHECKING from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tokenizers_available, is_torch_available __lowercase : Union[str, Any] = { 'configuration_roc_bert': ['ROC_BERT_PRETRAINED_CONFIG_ARCHIVE_MAP', 'RoCBertConfig'], 'to...
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'''simple docstring''' from ..utils import DummyObject, requires_backends class __UpperCamelCase ( metaclass=lowerCAmelCase_ ): A_ = ["transformers", "torch", "note_seq"] def __init__( self , *__a , **__a ): '''simple docstring''' re...
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'''simple docstring''' from typing import Optional, Union import torch from torch import nn from torch.nn import BCEWithLogitsLoss, CrossEntropyLoss, MSELoss from ...activations import ACTaFN from ...modeling_outputs import BaseModelOutputWithPoolingAndNoAttention, ImageClassifierOutputWithNoAttention from ...m...
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from typing import TYPE_CHECKING from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available __lowercase : int = {'configuration_vit_msn': ['VIT_MSN_PRETRAINED_CONFIG_ARCHIVE_MAP', 'ViTMSNConfig']} try: if not is_torch_available(): raise OptionalDependencyNotAvailable() e...
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'''simple docstring''' import json import os import re import sys import urllib.request import requests from bsa import BeautifulSoup __lowercase : str = { 'User-Agent': 'Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36' ' (KHTML, like Gecko) Chrome/70.0.3538.102 Safari/537.36 E...
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'''simple docstring''' import logging import os import sys from dataclasses import dataclass, field from typing import Optional import numpy as np import torch from datasets import load_dataset from torchvision.transforms import Compose, Lambda, Normalize, RandomHorizontalFlip, RandomResizedCrop, ToTensor impor...
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'''simple docstring''' import os def lowerCamelCase (): with open(os.path.dirname(_SCREAMING_SNAKE_CASE ) + '/p022_names.txt' ) as file: __a : List[Any] = str(file.readlines()[0] ) __a : str = names.replace('"' , '' ).split('...
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'''simple docstring''' from dataclasses import dataclass from typing import Optional import torch from torch import nn from ..configuration_utils import ConfigMixin, register_to_config from ..utils import BaseOutput from .attention import BasicTransformerBlock from .modeling_utils import ModelMixin @datacl...
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'''simple docstring''' __lowercase : Optional[Any] = {'a': ['c', 'b'], 'b': ['d', 'e'], 'c': [], 'd': [], 'e': []} __lowercase : List[str] = ['a', 'b', 'c', 'd', 'e'] def lowerCamelCase (_SCREAMING_SNAKE_CASE : List[Any] , _SCREAMING_SNAKE_CASE : A...
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'''simple docstring''' import gc import random import unittest import numpy as np import torch from transformers import CLIPTextConfig, CLIPTextModel, CLIPTokenizer from diffusers import AutoencoderKL, CycleDiffusionPipeline, DDIMScheduler, UNetaDConditionModel from diffusers.utils import floats_tensor, load_im...
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'''simple docstring''' def lowerCamelCase (_SCREAMING_SNAKE_CASE : int ): return number & 1 == 0 if __name__ == "__main__": import doctest doctest.testmod()
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'''simple docstring''' from collections.abc import Callable def lowerCamelCase (_SCREAMING_SNAKE_CASE : Callable[[float], float] , _SCREAMING_SNAKE_CASE : float , _SCREAMING_SNAKE_CASE : float ): __a : float = a __a : float ...
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'''simple docstring''' from typing import TYPE_CHECKING from ...utils import ( OptionalDependencyNotAvailable, _LazyModule, is_flax_available, is_tf_available, is_tokenizers_available, is_torch_available, ) __lowercase : Tuple = { 'configuration_distilbert': [ '...
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'''simple docstring''' import warnings from ...utils import logging from .image_processing_clip import CLIPImageProcessor __lowercase : Optional[int] = logging.get_logger(__name__) class __UpperCamelCase ( lowerCAmelCase_ ): def __init__( self , *__a , **...
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'''simple docstring''' import shutil import tempfile import unittest from transformers import ClapFeatureExtractor, ClapProcessor, RobertaTokenizer, RobertaTokenizerFast from transformers.testing_utils import require_sentencepiece, require_torchaudio from .test_feature_extraction_clap import floats_list @r...
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'''simple docstring''' from __future__ import annotations from dataclasses import dataclass @dataclass class __UpperCamelCase : A_ = 42 A_ = None A_ = None def lowerCamelCase (_SCREAMING_SNAKE_CASE : TreeNode | None ): # Vali...
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'''simple docstring''' import unittest from transformers import DebertaVaConfig, 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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'''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 __lowercase : Optional[Any] = False class __...
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'''simple docstring''' import os import socket from contextlib import contextmanager import torch from ..commands.config.default import write_basic_config # noqa: F401 from ..state import PartialState from .dataclasses import DistributedType from .imports import is_deepspeed_available, is_tpu_available from .t...
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'''simple docstring''' class __UpperCamelCase : def __init__( self , __a , __a=None , __a=None ): '''simple docstring''' __a : Any = data __a : List[Any] = previous __a : Optional[int] = next_node def ...
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'''simple docstring''' from .imports import is_rich_available if is_rich_available(): from rich.traceback import install install(show_locals=False) else: raise ModuleNotFoundError('To use the rich extension, install rich with `pip install rich`')
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'''simple docstring''' from collections.abc import Iterator, MutableMapping from dataclasses import dataclass from typing import Generic, TypeVar __lowercase : List[Any] = TypeVar('KEY') __lowercase : str = TypeVar('VAL') @dataclass(frozen=lowerCAmelCase_ , slots=lowerCAmelCase...
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'''simple docstring''' from __future__ import annotations from dataclasses import dataclass @dataclass class __UpperCamelCase : A_ = 42 A_ = None A_ = None def lowerCamelCase (_SCREAMING_SNAKE_CASE : TreeNode | None ): # Val...
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'''simple docstring''' import unittest import numpy as np from transformers.testing_utils import require_pytesseract, require_torch from transformers.utils import is_pytesseract_available, is_torch_available from ...test_image_processing_common import ImageProcessingSavingTestMixin, prepare_image_inputs if i...
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'''simple docstring''' # tests directory-specific settings - this file is run automatically # by pytest before any tests are run import sys import warnings from os.path import abspath, dirname, join # allow having multiple repository checkouts and not needing to remember to rerun # 'pip install -e .[dev]' when...
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'''simple docstring''' from math import factorial class __UpperCamelCase : def __init__( self , __a , __a ): '''simple docstring''' __a : List[str] = real if isinstance(__a , __a ): __a : int = [1] *...
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'''simple docstring''' import re from filelock import FileLock try: import nltk __lowercase : Optional[Any] = True except (ImportError, ModuleNotFoundError): __lowercase : Dict = False if NLTK_AVAILABLE: with FileLock('.lock') as lock: nltk.download('punkt', quiet=True) ...
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'''simple docstring''' from __future__ import annotations from fractions import Fraction from math import gcd, sqrt def lowerCamelCase (_SCREAMING_SNAKE_CASE : int ): __a : int = int(number**0.5 ) return number == sq * sq def lowerCamelCase (_SC...
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'''simple docstring''' import numpy as np import skfuzzy as fuzz if __name__ == "__main__": # Create universe of discourse in Python using linspace () __lowercase : int = np.linspace(start=0, stop=75, num=75, endpoint=True, retstep=False) # Create two fuzzy sets by defining any membership functi...
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'''simple docstring''' from ...configuration_utils import PretrainedConfig from ...utils import logging __lowercase : str = logging.get_logger(__name__) __lowercase : Dict = { 'vinvino02/glpn-kitti': 'https://huggingface.co/vinvino02/glpn-kitti/resolve/main/config.json', # See ...
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'''simple docstring''' import sys __lowercase : Union[str, Any] = ( '73167176531330624919225119674426574742355349194934' '96983520312774506326239578318016984801869478851843' '85861560789112949495459501737958331952853208805511' '12540698747158523863050715693290963295227443043557' ...
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'''simple docstring''' import torch from accelerate import PartialState from accelerate.utils.operations import broadcast, gather, gather_object, pad_across_processes, reduce def lowerCamelCase (_SCREAMING_SNAKE_CASE : int ): return (torch.arange(state.num_processes ) + 1....
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'''simple docstring''' import json import os import re import unittest from transformers import CodeGenTokenizer, CodeGenTokenizerFast from transformers.models.codegen.tokenization_codegen import VOCAB_FILES_NAMES from transformers.testing_utils import require_tokenizers, slow from ...test_tokenization_common i...
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'''simple docstring''' import unittest import numpy as np import torch from diffusers import KarrasVePipeline, KarrasVeScheduler, UNetaDModel from diffusers.utils.testing_utils import enable_full_determinism, require_torch, slow, torch_device enable_full_determinism() class __UpperCamelCase ( ...
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'''simple docstring''' def lowerCamelCase (_SCREAMING_SNAKE_CASE : int , _SCREAMING_SNAKE_CASE : int ): if not isinstance(_SCREAMING_SNAKE_CASE , _SCREAMING_SNAKE_CASE ): raise ValueError('iterations must be defined as integers' ) if ...
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'''simple docstring''' from typing import TYPE_CHECKING from ...utils import ( OptionalDependencyNotAvailable, _LazyModule, is_tokenizers_available, is_torch_available, is_vision_available, ) __lowercase : str = { 'configuration_layoutlmv2': ['LAYOUTLMV2_PRETRAINED_CONFIG_A...
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'''simple docstring''' import unittest import numpy as np from transformers.testing_utils import require_pytesseract, require_torch from transformers.utils import is_pytesseract_available, is_torch_available from ...test_image_processing_common import ImageProcessingSavingTestMixin, prepare_image_inputs if i...
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'''simple docstring''' import unittest from transformers import load_tool from .test_tools_common import ToolTesterMixin __lowercase : List[str] = '\nHugging Face was founded in 2016 by French entrepreneurs Clément Delangue, Julien Chaumond, and Thomas Wolf originally as a company that developed ...
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'''simple docstring''' from __future__ import annotations from typing import Dict from ...configuration_utils import PretrainedConfig __lowercase : List[Any] = { 'susnato/ernie-m-base_pytorch': 'https://huggingface.co/susnato/ernie-m-base_pytorch/blob/main/config.json', 'susnato/ernie-m-l...
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'''simple docstring''' from typing import Dict, List, Optional, Tuple, Union import torch from ...models import AutoencoderKL, TransformeraDModel from ...schedulers import KarrasDiffusionSchedulers from ...utils import randn_tensor from ..pipeline_utils import DiffusionPipeline, ImagePipelineOutput class ...
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'''simple docstring''' import gc import importlib.metadata import tempfile import unittest from packaging import version from transformers import ( AutoModel, AutoModelForCausalLM, AutoModelForSeqaSeqLM, AutoModelForSequenceClassification, AutoTokenizer, BitsAndBytesConfig, pipeline,...
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'''simple docstring''' from typing import TYPE_CHECKING from ...utils import ( OptionalDependencyNotAvailable, _LazyModule, is_flax_available, is_tf_available, is_tokenizers_available, is_torch_available, ) __lowercase : Tuple = { 'configuration_distilbert': [ '...
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'''simple docstring''' from dataclasses import dataclass from typing import Optional, Tuple import torch from torch import nn from transformers import RobertaPreTrainedModel, XLMRobertaConfig, XLMRobertaModel from transformers.utils import ModelOutput @dataclass class __UpperCamelCase ( lowerCAme...
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'''simple docstring''' import pickle import numpy as np from matplotlib import pyplot as plt class __UpperCamelCase : def __init__( self , __a , __a , __a , __a , __a , __a=0.2 , __a=0.2 ): '''simple docstring''' ...
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'''simple docstring''' from typing import TYPE_CHECKING from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tokenizers_available, is_torch_available __lowercase : Union[str, Any] = { 'configuration_roc_bert': ['ROC_BERT_PRETRAINED_CONFIG_ARCHIVE_MAP', 'RoCBertConfig'], 'to...
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'''simple docstring''' from typing import TYPE_CHECKING from ...utils import ( OptionalDependencyNotAvailable, _LazyModule, is_flax_available, is_tf_available, is_tokenizers_available, is_torch_available, ) __lowercase : Optional[Any] = { 'configuration_whisper': ['WHI...
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'''simple docstring''' from typing import Optional, Union import torch from torch import nn from torch.nn import BCEWithLogitsLoss, CrossEntropyLoss, MSELoss from ...activations import ACTaFN from ...modeling_outputs import BaseModelOutputWithPoolingAndNoAttention, ImageClassifierOutputWithNoAttention from ...m...
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import inspect import unittest import warnings from math import ceil, floor from transformers import LevitConfig from transformers.file_utils import cached_property, is_torch_available, is_vision_available from transformers.models.auto import get_values from transformers.testing_utils import require_torch, require_...
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'''simple docstring''' import json import os import re import sys import urllib.request import requests from bsa import BeautifulSoup __lowercase : str = { 'User-Agent': 'Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36' ' (KHTML, like Gecko) Chrome/70.0.3538.102 Safari/537.36 E...
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'''simple docstring''' import os from itertools import chain from random import randrange, shuffle import pytest from .sola import PokerHand __lowercase : Optional[int] = ( '4S 3H 2C 7S 5H', '9D 8H 2C 6S 7H', '2D 6D 9D TH 7D', 'TC 8C 2S JH 6C', 'JH 8S TH AH QH', 'TS KS 5S 9...
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'''simple docstring''' import os def lowerCamelCase (): with open(os.path.dirname(_SCREAMING_SNAKE_CASE ) + '/p022_names.txt' ) as file: __a : List[Any] = str(file.readlines()[0] ) __a : str = names.replace('"' , '' ).split('...
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'''simple docstring''' def lowerCamelCase (_SCREAMING_SNAKE_CASE : int , _SCREAMING_SNAKE_CASE : int ): while a != 0: __a : int = b % a, a return b def lowerCamelCase (_SCREAMING_SNAKE_CASE : int , _SCREAMING_SNAKE...
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'''simple docstring''' __lowercase : Optional[Any] = {'a': ['c', 'b'], 'b': ['d', 'e'], 'c': [], 'd': [], 'e': []} __lowercase : List[str] = ['a', 'b', 'c', 'd', 'e'] def lowerCamelCase (_SCREAMING_SNAKE_CASE : List[Any] , _SCREAMING_SNAKE_CASE : A...
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'''simple docstring''' from typing import TYPE_CHECKING # rely on isort to merge the imports from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tokenizers_available, is_torch_available __lowercase : Any = {'configuration_mra': ['MRA_PRETRAINED_CONFIG_ARCHIVE_MAP', 'MraConfig']} ...
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'''simple docstring''' def lowerCamelCase (_SCREAMING_SNAKE_CASE : int ): return number & 1 == 0 if __name__ == "__main__": import doctest doctest.testmod()
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'''simple docstring''' import warnings from diffusers import StableDiffusionInpaintPipeline as StableDiffusionInpaintPipeline # noqa F401 warnings.warn( 'The `inpainting.py` script is outdated. Please use directly `from diffusers import' ' StableDiffusionInpaintPipeline` instead.' )
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'''simple docstring''' from typing import TYPE_CHECKING from ...utils import ( OptionalDependencyNotAvailable, _LazyModule, is_flax_available, is_tf_available, is_tokenizers_available, is_torch_available, ) __lowercase : Tuple = { 'configuration_distilbert': [ '...
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'''simple docstring''' def lowerCamelCase (_SCREAMING_SNAKE_CASE : float , _SCREAMING_SNAKE_CASE : float , _SCREAMING_SNAKE_CASE : float , _SCREAMING_SNAKE_CASE : float , _SCREAMING_SNAKE_CASE : float , ): __a :...
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'''simple docstring''' import shutil import tempfile import unittest from transformers import ClapFeatureExtractor, ClapProcessor, RobertaTokenizer, RobertaTokenizerFast from transformers.testing_utils import require_sentencepiece, require_torchaudio from .test_feature_extraction_clap import floats_list @r...
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'''simple docstring''' import json import os import re import unittest from transformers import CodeGenTokenizer, CodeGenTokenizerFast from transformers.models.codegen.tokenization_codegen import VOCAB_FILES_NAMES from transformers.testing_utils import require_tokenizers, slow from ...test_tokenization_common im...
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'''simple docstring''' import unittest from transformers import DebertaVaConfig, 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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'''simple docstring''' import time from dataclasses import dataclass from multiprocessing import Pool from unittest import TestCase from unittest.mock import patch import multiprocess import numpy as np import pytest from datasets.utils.py_utils import ( NestedDataStructure, asdict, iflatmap_unorder...
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'''simple docstring''' import os import socket from contextlib import contextmanager import torch from ..commands.config.default import write_basic_config # noqa: F401 from ..state import PartialState from .dataclasses import DistributedType from .imports import is_deepspeed_available, is_tpu_available from .t...
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'''simple docstring''' import pytest from datasets import inspect_metric, list_metrics, load_metric @pytest.fixture def lowerCamelCase (_SCREAMING_SNAKE_CASE : List[str] ): monkeypatch.setattr('datasets.utils.deprecation_utils._emitted_deprecation_warnings' , set() ...
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'''simple docstring''' from .imports import is_rich_available if is_rich_available(): from rich.traceback import install install(show_locals=False) else: raise ModuleNotFoundError('To use the rich extension, install rich with `pip install rich`')
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'''simple docstring''' def lowerCamelCase (_SCREAMING_SNAKE_CASE : int , _SCREAMING_SNAKE_CASE : Union[str, Any] , _SCREAMING_SNAKE_CASE : Dict , _SCREAMING_SNAKE_CASE : Tuple ): global f # a global dp table for knapsack if f[i][...
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'''simple docstring''' from __future__ import annotations from dataclasses import dataclass @dataclass class __UpperCamelCase : A_ = 42 A_ = None A_ = None def lowerCamelCase (_SCREAMING_SNAKE_CASE : TreeNode | None ): # Val...
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'''simple docstring''' from typing import TYPE_CHECKING from ...utils import ( OptionalDependencyNotAvailable, _LazyModule, is_torch_available, ) __lowercase : List[str] = { 'configuration_encodec': [ 'ENCODEC_PRETRAINED_CONFIG_ARCHIVE_MAP', 'EncodecConfig', ], ...
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'''simple docstring''' # tests directory-specific settings - this file is run automatically # by pytest before any tests are run import sys import warnings from os.path import abspath, dirname, join # allow having multiple repository checkouts and not needing to remember to rerun # 'pip install -e .[dev]' when...
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'''simple docstring''' import argparse import re import requests import torch # git clone https://github.com/salesforce/BLIP.git from models.blip import blip_decoder from models.blip_itm import blip_itm from models.blip_vqa import blip_vqa from PIL import Image from torchvision import transforms from torchvisio...
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'''simple docstring''' import re from filelock import FileLock try: import nltk __lowercase : Optional[Any] = True except (ImportError, ModuleNotFoundError): __lowercase : Dict = False if NLTK_AVAILABLE: with FileLock('.lock') as lock: nltk.download('punkt', quiet=True) ...
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'''simple docstring''' import os import sys import unittest __lowercase : 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 check_dummies # noqa: E402 from check_dummies import create_dummy_files, create...
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'''simple docstring''' import numpy as np import skfuzzy as fuzz if __name__ == "__main__": # Create universe of discourse in Python using linspace () __lowercase : int = np.linspace(start=0, stop=75, num=75, endpoint=True, retstep=False) # Create two fuzzy sets by defining any membership functi...
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'''simple docstring''' def lowerCamelCase (_SCREAMING_SNAKE_CASE : int , _SCREAMING_SNAKE_CASE : int ): return int((input_a, input_a).count(0 ) != 0 ) def lowerCamelCase (): assert nand_gate(0 , 0 ) == 1 assert nand_gate...
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'''simple docstring''' import sys __lowercase : Union[str, Any] = ( '73167176531330624919225119674426574742355349194934' '96983520312774506326239578318016984801869478851843' '85861560789112949495459501737958331952853208805511' '12540698747158523863050715693290963295227443043557' ...
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'''simple docstring''' import math def lowerCamelCase (_SCREAMING_SNAKE_CASE : str , _SCREAMING_SNAKE_CASE : List[str] ): if 0 not in (x, y): # We use the relation x^y = y*log10(x), where 10 is the base. return y * math.logaa(_SCREAMING_SNAKE_...
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'''simple docstring''' import json import os import re import unittest from transformers import CodeGenTokenizer, CodeGenTokenizerFast from transformers.models.codegen.tokenization_codegen import VOCAB_FILES_NAMES from transformers.testing_utils import require_tokenizers, slow from ...test_tokenization_common i...
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'''simple docstring''' import tempfile import torch from diffusers import IPNDMScheduler from .test_schedulers import SchedulerCommonTest class __UpperCamelCase ( lowerCAmelCase_ ): A_ = (IPNDMScheduler,) A_ = (("num_inference_steps", 50),) def __UpperCAmelCas...
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'''simple docstring''' def lowerCamelCase (_SCREAMING_SNAKE_CASE : int , _SCREAMING_SNAKE_CASE : int ): if not isinstance(_SCREAMING_SNAKE_CASE , _SCREAMING_SNAKE_CASE ): raise ValueError('iterations must be defined as integers' ) if ...
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'''simple docstring''' import json import os from typing import Optional, Tuple from ...tokenization_utils import PreTrainedTokenizer from ...utils import logging __lowercase : Optional[int] = logging.get_logger(__name__) __lowercase : Optional[int] = {'vocab_file': 'vocab.json'} __...
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'''simple docstring''' import unittest import numpy as np from transformers.testing_utils import require_pytesseract, require_torch from transformers.utils import is_pytesseract_available, is_torch_available from ...test_image_processing_common import ImageProcessingSavingTestMixin, prepare_image_inputs if i...
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import inspect import unittest import torch import torch.nn as nn from accelerate.hooks import ( AlignDevicesHook, ModelHook, SequentialHook, add_hook_to_module, attach_align_device_hook, remove_hook_from_module, remove_hook_from_submodules, ) from accelerate.test_utils import requir...
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import math import torch from torch import nn from ..configuration_utils import ConfigMixin, register_to_config from .attention_processor import Attention from .embeddings import get_timestep_embedding from .modeling_utils import ModelMixin class UpperCamelCase_ ( _lowerCamelCase , _lowe...
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import os import sys import unittest UpperCAmelCase_ = os.path.abspath(os.path.dirname(os.path.dirname(os.path.dirname(__file__)))) sys.path.append(os.path.join(git_repo_path, """utils""")) import check_dummies # noqa: E402 from check_dummies import create_dummy_files, create_dummy_object, find_b...
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from collections import OrderedDict from typing import Any, Mapping, Optional from ... import PreTrainedTokenizer, TensorType, is_torch_available from ...configuration_utils import PretrainedConfig from ...onnx import OnnxConfigWithPast from ...utils import logging UpperCAmelCase_ = logging.get_lo...
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from ..utils import DummyObject, requires_backends class UpperCamelCase_ ( metaclass=_lowerCamelCase ): lowerCAmelCase_ = ['''note_seq'''] def __init__( self , *lowerCAmelCase_ , **lowerCAmelCase_ ) -> List[str]: requires_backends(self , ...
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from cva import destroyAllWindows, imread, imshow, waitKey def lowerCamelCase__ ( UpperCamelCase__ : Dict ) -> Optional[Any]: '''simple docstring''' _snake_case , _snake_case = img.shape[0], img.shape[1] # converting each pixel's colo...
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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 b...
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import argparse import json import gdown import numpy as np import torch from huggingface_hub import hf_hub_download from transformers import ( VideoMAEConfig, VideoMAEForPreTraining, VideoMAEForVideoClassification, VideoMAEImageProcessor, ) def lowerCamelCase__ ( UpperCamelCa...
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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 .tokenization_albert imp...
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from typing import Optional import torch import torch.utils.checkpoint from torch import Tensor, nn from torch.nn import BCEWithLogitsLoss, CrossEntropyLoss, MSELoss from ...activations import ACTaFN from ...modeling_outputs import ( BackboneOutput, BaseModelOutputWithNoAttention, BaseModelOutputWit...
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def lowerCamelCase__ ( UpperCamelCase__ : float ) -> float: '''simple docstring''' if edge <= 0 or not isinstance(UpperCamelCase__ , UpperCamelCase__ ): raise ValueError('Length must be a positive.' ) return 3 * ((25 + 10 * (5 ** (1 / 2))) ** (1 ...
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def lowerCamelCase__ ( UpperCamelCase__ : list[list[int]] , UpperCamelCase__ : int , UpperCamelCase__ : int , UpperCamelCase__ : list[int] ) -> bool: '''simple docstring''' if graph[path[curr_ind - 1]][next_ver] == 0: ...
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def lowerCamelCase__ ( UpperCamelCase__ : int , UpperCamelCase__ : int ) -> int: '''simple docstring''' while second != 0: _snake_case = first & second first ^= second _snake_case = c << 1 retu...
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import argparse import OmegaConf import torch from diffusers import DDIMScheduler, LDMPipeline, UNetLDMModel, VQModel def lowerCamelCase__ ( UpperCamelCase__ : Dict , UpperCamelCase__ : List[str] , UpperCamelCase__ : Dict ) -> List[Any]: '''si...
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def lowerCamelCase__ ( UpperCamelCase__ : str ) -> list[int]: '''simple docstring''' _snake_case = [0 for i in range(len(UpperCamelCase__ ) )] # initialize interval's left pointer and right pointer _snake_case , _snake_case ...
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import unittest from typing import Tuple import torch from diffusers.utils import floats_tensor, randn_tensor, torch_all_close, torch_device from diffusers.utils.testing_utils import require_torch @require_torch class UpperCamelCase_ : @property def lowerCAmelCase ( self )...
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