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'''simple docstring''' from collections import UserDict from typing import List, Union from ..utils import ( add_end_docstrings, is_tf_available, is_torch_available, is_vision_available, logging, requires_backends, ) from .base import PIPELINE_INIT_ARGS, Pipeline if is_vision_availab...
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'''simple docstring''' from __future__ import annotations import unittest import numpy as np from transformers import OPTConfig, is_tf_available from transformers.testing_utils import require_sentencepiece, require_tf, slow from ...test_configuration_common import ConfigTester from ...test_modeling_tf_comm...
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'''simple docstring''' def _UpperCamelCase ( SCREAMING_SNAKE_CASE__ : List[str] , SCREAMING_SNAKE_CASE__ : int , SCREAMING_SNAKE_CASE__ : Union[str, Any] , SCREAMING_SNAKE_CASE__ : str ): '''simple docstring''' global f # a global dp t...
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'''simple docstring''' import unittest from transformers import PegasusTokenizer, PegasusTokenizerFast from transformers.testing_utils import get_tests_dir, require_sentencepiece, require_tokenizers, require_torch, slow from transformers.utils import cached_property from ...test_tokenization_common import To...
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'''simple docstring''' def _UpperCamelCase ( ): '''simple docstring''' UpperCAmelCase__ = [] UpperCAmelCase__ = 1 while len(SCREAMING_SNAKE_CASE__ ) < 1e6: constant.append(str(SCREAMING_SNAKE_CASE__ ) ) i += 1 UpperCAmelCase__ = ""...
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'''simple docstring''' import unittest import numpy as np def _UpperCamelCase ( SCREAMING_SNAKE_CASE__ : np.ndarray , SCREAMING_SNAKE_CASE__ : np.ndarray , SCREAMING_SNAKE_CASE__ : np.ndarray , SCREAMING_SNAKE_CASE__ : np.ndarray | None = None ...
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'''simple docstring''' import logging import os from .state import PartialState class lowerCAmelCase_ ( logging.LoggerAdapter ): '''simple docstring''' @staticmethod def SCREAMING_SNAKE_CASE__ ( _UpperCAmelCase : int ): """simple docstring""" ...
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'''simple docstring''' from collections import namedtuple import requests from lxml import html # type: ignore UpperCAmelCase_ = namedtuple('covid_data', 'cases deaths recovered') def _UpperCamelCase ( SCREAMING_SNAKE_CASE__ : str = "https://www.worldometers.info/coronavirus/" ...
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'''simple docstring''' import tempfile import unittest from transformers import AutoModelForSeqaSeqLM, AutoTokenizer from transformers.testing_utils import ( is_torch_available, require_optimum, require_torch, slow, ) if is_torch_available(): import torch @require_torch @require_optimum...
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'''simple docstring''' import copy from typing import Dict, List, Optional from ...configuration_utils import PretrainedConfig from ...utils import logging from ..auto import CONFIG_MAPPING UpperCAmelCase_ = { 'facebook/mask2former-swin-small-coco-instance': ( 'https://huggingface.c...
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'''simple docstring''' from __future__ import annotations import inspect import unittest from math import floor import numpy as np from transformers import CvtConfig from transformers.testing_utils import require_tf, require_vision, slow from transformers.utils import cached_property, is_tf_available, is_vi...
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'''simple docstring''' UpperCAmelCase_ = [ 'DownloadConfig', 'DownloadManager', 'DownloadMode', 'StreamingDownloadManager', ] from .download_config import DownloadConfig from .download_manager import DownloadManager, DownloadMode from .streaming_download_manager import StreamingDo...
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'''simple docstring''' import argparse import torch from transformers import BlenderbotConfig, BlenderbotForConditionalGeneration from transformers.utils import logging logging.set_verbosity_info() UpperCAmelCase_ = logging.get_logger(__name__) UpperCAmelCase_ = [ ['attention...
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'''simple docstring''' from typing import TYPE_CHECKING from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_sentencepiece_available UpperCAmelCase_ = {} try: if not is_sentencepiece_available(): raise OptionalDependencyNotAvailable() except OptionalDependencyNotAva...
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'''simple docstring''' import numpy as np from scipy.spatial.distance import cdist from sklearn.metrics import fa_score import datasets UpperCAmelCase_ = '\\n @inproceedings{kakwani2020indicnlpsuite,\n title={{IndicNLPSuite: Monolingual Corpora, Evaluation Benchmarks and Pre-trained Multi...
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'''simple docstring''' from typing import TYPE_CHECKING from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tf_available, is_torch_available UpperCAmelCase_ = { 'configuration_transfo_xl': ['TRANSFO_XL_PRETRAINED_CONFIG_ARCHIVE_MAP', 'TransfoXLConfig'], 'tokenization_tr...
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'''simple docstring''' import gc import random import unittest import numpy as np import torch from PIL import Image from diffusers import ( DDIMScheduler, KandinskyVaaImgaImgPipeline, KandinskyVaaPriorPipeline, UNetaDConditionModel, VQModel, ) from diffusers.utils import floats_tensor, l...
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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 UpperCAmelCase_ = { 'configuration_autoformer': [ 'AUTOFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP', 'Au...
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'''simple docstring''' 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 _UpperCamelCase ( ...
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'''simple docstring''' from typing import TYPE_CHECKING from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available, is_vision_available UpperCAmelCase_ = { 'configuration_mobilenet_v2': [ 'MOBILENET_V2_PRETRAINED_CONFIG_ARCHIVE_MAP', 'MobileNetV2Con...
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'''simple docstring''' from collections import deque class lowerCAmelCase_ : '''simple docstring''' def __init__( self : Dict , _UpperCAmelCase : str , _UpperCAmelCase : int , _UpperCAmelCase : int ): """simple docstring""" ...
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'''simple docstring''' from __future__ import annotations from collections.abc import Callable from typing import Generic, TypeVar UpperCAmelCase_ = TypeVar('T') UpperCAmelCase_ = TypeVar('U') class lowerCAmelCase_ ( Generic[T, U] ): '''simple docstring''' d...
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'''simple docstring''' # This model implementation is heavily inspired by https://github.com/haofanwang/ControlNet-for-Diffusers/ import gc import random import tempfile import unittest import numpy as np import torch from PIL import Image from transformers import CLIPTextConfig, CLIPTextModel, CLIPTokenizer...
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'''simple docstring''' import unittest from transformers import BigBirdTokenizer, BigBirdTokenizerFast from transformers.testing_utils import get_tests_dir, require_sentencepiece, require_tokenizers, require_torch, slow from transformers.utils import cached_property from ...test_tokenization_common import To...
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'''simple docstring''' from collections import namedtuple import requests from lxml import html # type: ignore UpperCAmelCase_ = namedtuple('covid_data', 'cases deaths recovered') def _UpperCamelCase ( SCREAMING_SNAKE_CASE__ : str = "https://www.worldometers.info/coronavirus/" ...
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'''simple docstring''' import unittest from parameterized import parameterized from transformers import OpenLlamaConfig, is_torch_available, set_seed from transformers.testing_utils import require_torch, torch_device from ...generation.test_utils import GenerationTesterMixin from ...test_configuration_commo...
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'''simple docstring''' class lowerCAmelCase_ : '''simple docstring''' def __init__( self : List[str] ): """simple docstring""" UpperCAmelCase__ = """""" UpperCAmelCase__ = """""" UpperCAmelCase__ = [] def ...
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'''simple docstring''' import gc import random import unittest import numpy as np import torch from diffusers import ( DDIMScheduler, KandinskyVaaControlnetPipeline, KandinskyVaaPriorPipeline, UNetaDConditionModel, VQModel, ) from diffusers.utils import floats_tensor, load_image, load_num...
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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...
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'''simple docstring''' from typing import TYPE_CHECKING from ...utils import ( OptionalDependencyNotAvailable, _LazyModule, is_flax_available, is_sentencepiece_available, is_tf_available, is_tokenizers_available, is_torch_available, ) UpperCAmelCase_ = {'configuratio...
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'''simple docstring''' import inspect import unittest from transformers import MobileNetVaConfig from transformers.testing_utils import require_torch, require_vision, slow, torch_device from transformers.utils import cached_property, is_torch_available, is_vision_available from ...test_configuration_common i...
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'''simple docstring''' import torch from transformers import AutoModel class lowerCAmelCase_ ( torch.nn.Module ): '''simple docstring''' def __init__( self : Tuple , _UpperCAmelCase : List[str]="sayef/fsner-bert-base-uncased" ): """simple docstring"...
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'''simple docstring''' import gc import random import unittest import numpy as np import torch from diffusers import ( DDIMScheduler, KandinskyVaaControlnetPipeline, KandinskyVaaPriorPipeline, UNetaDConditionModel, VQModel, ) from diffusers.utils import floats_tensor, load_image, load_num...
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'''simple docstring''' def _UpperCamelCase ( SCREAMING_SNAKE_CASE__ : str , SCREAMING_SNAKE_CASE__ : str ): '''simple docstring''' assert x is not None assert y is not None UpperCAmelCase__ = len(SCREAMING_SNAKE_CASE__ ) UpperCAmelCase__ ...
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'''simple docstring''' from __future__ import annotations from bisect import bisect_left from functools import total_ordering from heapq import merge @total_ordering class lowerCAmelCase_ ( lowerCamelCase_ ): '''simple docstring''' def __lt__( self : List[Any] , _Upper...
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'''simple docstring''' from __future__ import annotations from bisect import bisect_left from functools import total_ordering from heapq import merge @total_ordering class lowerCAmelCase_ ( lowerCamelCase_ ): '''simple docstring''' def __lt__( self : List[Any] , _Upper...
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'''simple docstring''' import json import pathlib import unittest import numpy as np from transformers.testing_utils import require_torch, require_vision, slow from transformers.utils import is_torch_available, is_vision_available from ...test_image_processing_common import ImageProcessingSavingTestMixin, p...
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'''simple docstring''' from typing import TYPE_CHECKING from ...utils import ( OptionalDependencyNotAvailable, _LazyModule, is_tf_available, is_tokenizers_available, is_torch_available, ) UpperCAmelCase_ = { 'configuration_longformer': [ 'LONGFORMER_PRETRAINED_CO...
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'''simple docstring''' import tempfile import torch from diffusers import PNDMScheduler from .test_schedulers import SchedulerCommonTest class lowerCAmelCase_ ( lowerCamelCase_ ): '''simple docstring''' lowerCAmelCase_ : int = (PNDMScheduler,) lowerCAmelCase_ ...
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'''simple docstring''' import os import tempfile import unittest from transformers import NezhaConfig, is_torch_available from transformers.models.auto import get_values from transformers.testing_utils import require_torch, require_torch_gpu, slow, torch_device from ...generation.test_utils import Generation...
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'''simple docstring''' import torch from torch import nn from torch.nn import CrossEntropyLoss, MSELoss from transformers.file_utils import add_start_docstrings, add_start_docstrings_to_model_forward from transformers.models.bert.modeling_bert import ( BERT_INPUTS_DOCSTRING, BERT_START_DOCSTRING, ...
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'''simple docstring''' import gc import random import unittest import numpy as np import torch from PIL import Image from diffusers import ( DDIMScheduler, KandinskyVaaImgaImgPipeline, KandinskyVaaPriorPipeline, UNetaDConditionModel, VQModel, ) from diffusers.utils import floats_tensor, l...
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'''simple docstring''' import argparse import os import torch from transformers.utils import WEIGHTS_NAME UpperCAmelCase_ = ['small', 'medium', 'large'] UpperCAmelCase_ = 'lm_head.decoder.weight' UpperCAmelCase_ = 'lm_head.weight' def _UpperCamelCase ( SCREAM...
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'''simple docstring''' import unittest from transformers import MPNetConfig, is_torch_available from transformers.testing_utils import require_torch, slow, torch_device from ...test_configuration_common import ConfigTester from ...test_modeling_common import ModelTesterMixin, ids_tensor, random_attention_mas...
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'''simple docstring''' import string def _UpperCamelCase ( SCREAMING_SNAKE_CASE__ : str ): '''simple docstring''' for key in range(len(string.ascii_uppercase ) ): UpperCAmelCase__ = """""" for symbol in message: if symbol in string.ascii_uppercase: ...
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'''simple docstring''' from __future__ import annotations import unittest import numpy as np from transformers import OPTConfig, is_tf_available from transformers.testing_utils import require_sentencepiece, require_tf, slow from ...test_configuration_common import ConfigTester from ...test_modeling_tf_comm...
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'''simple docstring''' import unittest from datasets import load_dataset from transformers.pipelines import pipeline from transformers.testing_utils import is_pipeline_test, nested_simplify, require_torch, slow @is_pipeline_test @require_torch class lowerCAmelCase_ ( unittest.TestCase ): '''s...
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'''simple docstring''' import unittest from transformers import PegasusTokenizer, PegasusTokenizerFast from transformers.testing_utils import get_tests_dir, require_sentencepiece, require_tokenizers, require_torch, slow from transformers.utils import cached_property from ...test_tokenization_common import To...
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'''simple docstring''' import os import pytest from transformers.dynamic_module_utils import get_imports UpperCAmelCase_ = '\nimport os\n' UpperCAmelCase_ = '\ndef foo():\n import os\n return False\n' UpperCAmelCase_ = '\ndef foo():\n def bar():\n if...
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'''simple docstring''' import unittest import numpy as np def _UpperCamelCase ( SCREAMING_SNAKE_CASE__ : np.ndarray , SCREAMING_SNAKE_CASE__ : np.ndarray , SCREAMING_SNAKE_CASE__ : np.ndarray , SCREAMING_SNAKE_CASE__ : np.ndarray | None = None ...
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'''simple docstring''' import os # All paths are set with the intent you should run this script from the root of the repo with the command # python utils/check_doctest_list.py UpperCAmelCase_ = '.' if __name__ == "__main__": UpperCAmelCase_ = os.path.join(REPO_PATH, 'utils/doc...
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'''simple docstring''' from collections import namedtuple import requests from lxml import html # type: ignore UpperCAmelCase_ = namedtuple('covid_data', 'cases deaths recovered') def _UpperCamelCase ( SCREAMING_SNAKE_CASE__ : str = "https://www.worldometers.info/coronavirus/" ...
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'''simple docstring''' import collections import inspect import unittest from typing import Dict, List, Tuple from transformers import MaskFormerSwinConfig from transformers.testing_utils import require_torch, require_torch_multi_gpu, torch_device from transformers.utils import is_torch_available from ...tes...
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'''simple docstring''' import copy from typing import Dict, List, Optional from ...configuration_utils import PretrainedConfig from ...utils import logging from ..auto import CONFIG_MAPPING UpperCAmelCase_ = { 'facebook/mask2former-swin-small-coco-instance': ( 'https://huggingface.c...
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'''simple docstring''' import unittest from knapsack import knapsack as k class lowerCAmelCase_ ( unittest.TestCase ): '''simple docstring''' def SCREAMING_SNAKE_CASE__ ( self : Optional[int] ): """simple docstring""" UpperCAmelCase__ ...
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'''simple docstring''' UpperCAmelCase_ = [ 'DownloadConfig', 'DownloadManager', 'DownloadMode', 'StreamingDownloadManager', ] from .download_config import DownloadConfig from .download_manager import DownloadManager, DownloadMode from .streaming_download_manager import StreamingDo...
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'''simple docstring''' import os import tempfile import unittest from transformers import FlaubertConfig, is_torch_available from transformers.testing_utils import require_torch, require_torch_gpu, slow, torch_device from ...test_configuration_common import ConfigTester from ...test_modeling_common import Mo...
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'''simple docstring''' from typing import TYPE_CHECKING from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_sentencepiece_available UpperCAmelCase_ = {} try: if not is_sentencepiece_available(): raise OptionalDependencyNotAvailable() except OptionalDependencyNotAva...
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'''simple docstring''' import os import time from dataclasses import dataclass, field from enum import Enum from typing import Dict, List, Optional, Union import torch from filelock import FileLock from torch.utils.data import Dataset from ...models.auto.modeling_auto import MODEL_FOR_QUESTION_ANSWERING_MAPP...
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'''simple docstring''' from typing import TYPE_CHECKING from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tf_available, is_torch_available UpperCAmelCase_ = { 'configuration_transfo_xl': ['TRANSFO_XL_PRETRAINED_CONFIG_ARCHIVE_MAP', 'TransfoXLConfig'], 'tokenization_tr...
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'''simple docstring''' import json import os import unittest from transformers import MgpstrTokenizer from transformers.models.mgp_str.tokenization_mgp_str import VOCAB_FILES_NAMES from transformers.testing_utils import require_tokenizers from ...test_tokenization_common import TokenizerTesterMixin @require...
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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 UpperCAmelCase_ = { 'configuration_autoformer': [ 'AUTOFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP', 'Au...
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'''simple docstring''' import argparse UpperCAmelCase_ = 'docs/source/_static/js/custom.js' def _UpperCamelCase ( SCREAMING_SNAKE_CASE__ : int ): '''simple docstring''' with open(SCREAMING_SNAKE_CASE__ , encoding="""utf-8""" , newline="""\n""" ...
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'''simple docstring''' from typing import TYPE_CHECKING from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available, is_vision_available UpperCAmelCase_ = { 'configuration_mobilenet_v2': [ 'MOBILENET_V2_PRETRAINED_CONFIG_ARCHIVE_MAP', 'MobileNetV2Con...
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'''simple docstring''' def _UpperCamelCase ( SCREAMING_SNAKE_CASE__ : int , SCREAMING_SNAKE_CASE__ : int ): '''simple docstring''' if a < 0 or b < 0: raise ValueError("""the value of both inputs must be positive""" ) UpperCAmelCase__ = str(bin(SC...
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'''simple docstring''' from __future__ import annotations from collections.abc import Callable from typing import Generic, TypeVar UpperCAmelCase_ = TypeVar('T') UpperCAmelCase_ = TypeVar('U') class lowerCAmelCase_ ( Generic[T, U] ): '''simple docstring''' d...
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'''simple docstring''' UpperCAmelCase_ = [sum(int(c, 1_0) ** 2 for c in i.__str__()) for i in range(1_0_0_0_0_0)] def _UpperCamelCase ( SCREAMING_SNAKE_CASE__ : int ): '''simple docstring''' UpperCAmelCase__ = 0 while number: # Increased Speed Slightly b...
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'''simple docstring''' import unittest from transformers import BigBirdTokenizer, BigBirdTokenizerFast from transformers.testing_utils import get_tests_dir, require_sentencepiece, require_tokenizers, require_torch, slow from transformers.utils import cached_property from ...test_tokenization_common import To...
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'''simple docstring''' import os import jsonlines import numpy as np from tqdm import tqdm UpperCAmelCase_ = 2_0_4_8 UpperCAmelCase_ = 4_0_9_6 UpperCAmelCase_ = 4_2 UpperCAmelCase_ = os.environ.pop('PROCESS_TRAIN', 'false') UpperCAmelCase_ = {...
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'''simple docstring''' import unittest from parameterized import parameterized from transformers import OpenLlamaConfig, is_torch_available, set_seed from transformers.testing_utils import require_torch, torch_device from ...generation.test_utils import GenerationTesterMixin from ...test_configuration_commo...
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'''simple docstring''' def _UpperCamelCase ( SCREAMING_SNAKE_CASE__ : str , SCREAMING_SNAKE_CASE__ : str ): '''simple docstring''' if not (isinstance(SCREAMING_SNAKE_CASE__ , SCREAMING_SNAKE_CASE__ ) and isinstance(SCREAMING_SNAKE_CASE__ , SCRE...
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'''simple docstring''' import gc import random import unittest import numpy as np import torch from diffusers import ( DDIMScheduler, KandinskyVaaControlnetPipeline, KandinskyVaaPriorPipeline, UNetaDConditionModel, VQModel, ) from diffusers.utils import floats_tensor, load_image, load_num...
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'''simple docstring''' from dataclasses import dataclass from typing import List, Optional, Union import numpy as np import PIL from PIL import Image from ...utils import ( BaseOutput, OptionalDependencyNotAvailable, is_flax_available, is_k_diffusion_available, is_k_diffusion_version, ...
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'''simple docstring''' from typing import TYPE_CHECKING from ...utils import ( OptionalDependencyNotAvailable, _LazyModule, is_flax_available, is_sentencepiece_available, is_tf_available, is_tokenizers_available, is_torch_available, ) UpperCAmelCase_ = {'configuratio...
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'''simple docstring''' from typing import List import jiwer import jiwer.transforms as tr from packaging import version import datasets from datasets.config import PY_VERSION if PY_VERSION < version.parse('3.8'): import importlib_metadata else: import importlib.metadata as importlib_metadata Uppe...
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'''simple docstring''' import torch from transformers import AutoModel class lowerCAmelCase_ ( torch.nn.Module ): '''simple docstring''' def __init__( self : Tuple , _UpperCAmelCase : List[str]="sayef/fsner-bert-base-uncased" ): """simple docstring"...
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'''simple docstring''' import gc import unittest import numpy as np import torch from diffusers import ( AudioDiffusionPipeline, AutoencoderKL, DDIMScheduler, DDPMScheduler, DiffusionPipeline, Mel, UNetaDConditionModel, UNetaDModel, ) from diffusers.utils import slow, torch_de...
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'''simple docstring''' def _UpperCamelCase ( SCREAMING_SNAKE_CASE__ : str , SCREAMING_SNAKE_CASE__ : str ): '''simple docstring''' assert x is not None assert y is not None UpperCAmelCase__ = len(SCREAMING_SNAKE_CASE__ ) UpperCAmelCase__ ...
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'''simple docstring''' import tempfile import unittest import numpy as np import transformers from transformers import GPTaTokenizer, GPTJConfig, is_flax_available, is_torch_available from transformers.testing_utils import is_pt_flax_cross_test, require_flax, tooslow from ...generation.test_flax_utils impor...
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'''simple docstring''' from __future__ import annotations from bisect import bisect_left from functools import total_ordering from heapq import merge @total_ordering class lowerCAmelCase_ ( lowerCamelCase_ ): '''simple docstring''' def __lt__( self : List[Any] , _Upper...
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from typing import TYPE_CHECKING from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available SCREAMING_SNAKE_CASE__ : str = { """configuration_swinv2""": ["""SWINV2_PRETRAINED_CONFIG_ARCHIVE_MAP""", """Swinv2Config"""], } try: if not is_torch_available(): ...
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'''simple docstring''' from typing import TYPE_CHECKING from ...utils import ( OptionalDependencyNotAvailable, _LazyModule, is_tf_available, is_tokenizers_available, is_torch_available, ) UpperCAmelCase_ = { 'configuration_longformer': [ 'LONGFORMER_PRETRAINED_CO...
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import warnings from ...processing_utils import ProcessorMixin from ...tokenization_utils_base import BatchEncoding class __lowerCamelCase (_a ): _lowercase = ["""image_processor""", """tokenizer"""] _lowercase = """CLIPImageProcessor""" _lowe...
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'''simple docstring''' import os import tempfile import unittest from transformers import NezhaConfig, is_torch_available from transformers.models.auto import get_values from transformers.testing_utils import require_torch, require_torch_gpu, slow, torch_device from ...generation.test_utils import Generation...
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from ...configuration_utils import PretrainedConfig from ...utils import logging UpperCAmelCase_ = logging.get_logger(__name__) UpperCAmelCase_ = {"""ctrl""": """https://huggingface.co/ctrl/resolve/main/config.json"""} class lowerCamelCase__ ( _A): """simple docstring"""...
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'''simple docstring''' import gc import random import unittest import numpy as np import torch from PIL import Image from diffusers import ( DDIMScheduler, KandinskyVaaImgaImgPipeline, KandinskyVaaPriorPipeline, UNetaDConditionModel, VQModel, ) from diffusers.utils import floats_tensor, l...
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'''simple docstring''' import warnings warnings.warn( 'memory_utils has been reorganized to utils.memory. Import `find_executable_batchsize` from the main `__init__`: ' '`from accelerate import find_executable_batch_size` to avoid this warning.', FutureWarning, )
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'''simple docstring''' import unittest from transformers import MPNetConfig, is_torch_available from transformers.testing_utils import require_torch, slow, torch_device from ...test_configuration_common import ConfigTester from ...test_modeling_common import ModelTesterMixin, ids_tensor, random_attention_mas...
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"""simple docstring""" import os import tempfile from functools import partial from unittest import TestCase from unittest.mock import patch import numpy as np import pytest from datasets.arrow_dataset import Dataset from datasets.search import ElasticSearchIndex, FaissIndex, MissingIndex from .utils import re...
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'''simple docstring''' from __future__ import annotations import unittest import numpy as np from transformers import OPTConfig, is_tf_available from transformers.testing_utils import require_sentencepiece, require_tf, slow from ...test_configuration_common import ConfigTester from ...test_modeling_tf_comm...
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'''simple docstring''' # Copyright 2021 The HuggingFace Team. All rights reserved. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # U...
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'''simple docstring''' import unittest from transformers import PegasusTokenizer, PegasusTokenizerFast from transformers.testing_utils import get_tests_dir, require_sentencepiece, require_tokenizers, require_torch, slow from transformers.utils import cached_property from ...test_tokenization_common import To...
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import argparse from torch import nn # transformers_old should correspond to branch `save_old_prophetnet_model_structure` here # original prophetnet_checkpoints are saved under `patrickvonplaten/..._old` respectively from transformers_old.modeling_prophetnet import ( ProphetNetForConditionalGeneration as Pr...
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'''simple docstring''' import unittest import numpy as np def _UpperCamelCase ( SCREAMING_SNAKE_CASE__ : np.ndarray , SCREAMING_SNAKE_CASE__ : np.ndarray , SCREAMING_SNAKE_CASE__ : np.ndarray , SCREAMING_SNAKE_CASE__ : np.ndarray | None = None ...
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"""simple docstring""" from ..utils import DummyObject, requires_backends class lowercase_ ( metaclass=__lowerCAmelCase ): '''simple docstring''' UpperCAmelCase : Union[str, Any] = ['''transformers''', '''torch''', '''note_seq'''] def __init__( self : str , ...
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'''simple docstring''' from collections import namedtuple import requests from lxml import html # type: ignore UpperCAmelCase_ = namedtuple('covid_data', 'cases deaths recovered') def _UpperCamelCase ( SCREAMING_SNAKE_CASE__ : str = "https://www.worldometers.info/coronavirus/" ...
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'''simple docstring''' from typing import List, Optional, Tuple from ...tokenization_utils_fast import PreTrainedTokenizerFast from ...utils import logging from .tokenization_herbert import HerbertTokenizer lowercase__ : Optional[Any] = logging.get_logger(__name__) ...
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'''simple docstring''' import copy from typing import Dict, List, Optional from ...configuration_utils import PretrainedConfig from ...utils import logging from ..auto import CONFIG_MAPPING UpperCAmelCase_ = { 'facebook/mask2former-swin-small-coco-instance': ( 'https://huggingface.c...
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import json import os import torch from diffusers import UNetaDModel os.makedirs('''hub/hopper-medium-v2/unet/hor32''', exist_ok=True) os.makedirs('''hub/hopper-medium-v2/unet/hor128''', exist_ok=True) os.makedirs('''hub/hopper-medium-v2/value_function''', exist_ok=True) def A ( __UpperCamelCase ...
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'''simple docstring''' UpperCAmelCase_ = [ 'DownloadConfig', 'DownloadManager', 'DownloadMode', 'StreamingDownloadManager', ] from .download_config import DownloadConfig from .download_manager import DownloadManager, DownloadMode from .streaming_download_manager import StreamingDo...
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from __future__ import annotations import numpy as np from numpy import floataa from numpy.typing import NDArray def _snake_case ( __snake_case , __snake_case , __snake_case , __snake_case , ): _UpperCamelCase , _UpperCamelCase = coefficient_matrix.shape _UpperCame...
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'''simple docstring''' from typing import TYPE_CHECKING from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_sentencepiece_available UpperCAmelCase_ = {} try: if not is_sentencepiece_available(): raise OptionalDependencyNotAvailable() except OptionalDependencyNotAva...
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'''simple docstring''' def lowerCAmelCase (__A): """simple docstring""" return credit_card_number.startswith(('''34''', '''35''', '''37''', '''4''', '''5''', '''6''')) def lowerCAmelCase (__A): """simple docstring""" _a = credit_card_number _a ...
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'''simple docstring''' from typing import TYPE_CHECKING from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tf_available, is_torch_available UpperCAmelCase_ = { 'configuration_transfo_xl': ['TRANSFO_XL_PRETRAINED_CONFIG_ARCHIVE_MAP', 'TransfoXLConfig'], 'tokenization_tr...
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# Copyright 2021 The HuggingFace Team. All rights reserved. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by...
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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 UpperCAmelCase_ = { 'configuration_autoformer': [ 'AUTOFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP', 'Au...
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'''simple docstring''' from collections import defaultdict from math import ceil, sqrt def UpperCAmelCase__ ( UpperCAmelCase_ : int = 1_00_00_00 , UpperCAmelCase_ : int = 10 ) -> int: __lowerCamelCase : defaultdict = defaultdict(Upp...
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'''simple docstring''' from typing import TYPE_CHECKING from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available, is_vision_available UpperCAmelCase_ = { 'configuration_mobilenet_v2': [ 'MOBILENET_V2_PRETRAINED_CONFIG_ARCHIVE_MAP', 'MobileNetV2Con...
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import time from contextlib import contextmanager from pathlib import Path import pytest import requests from huggingface_hub.hf_api import HfApi, HfFolder a__ = '''__DUMMY_TRANSFORMERS_USER__''' a__ = '''Dummy User''' a__ = '''hf_hZEmnoOEYISjraJtbySaKCN...
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'''simple docstring''' from __future__ import annotations from collections.abc import Callable from typing import Generic, TypeVar UpperCAmelCase_ = TypeVar('T') UpperCAmelCase_ = TypeVar('U') class lowerCAmelCase_ ( Generic[T, U] ): '''simple docstring''' d...
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from typing import List, Union from ..utils import ( add_end_docstrings, is_tf_available, is_torch_available, is_vision_available, logging, requires_backends, ) from .base import PIPELINE_INIT_ARGS, Pipeline if is_vision_available(): from PIL import Image from ..image...
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'''simple docstring''' import unittest from transformers import BigBirdTokenizer, BigBirdTokenizerFast from transformers.testing_utils import get_tests_dir, require_sentencepiece, require_tokenizers, require_torch, slow from transformers.utils import cached_property from ...test_tokenization_common import To...
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import argparse import re import numpy as np import requests import torch from huggingface_hub import hf_hub_download from PIL import Image from transformers import ( SamConfig, SamImageProcessor, SamModel, SamProcessor, SamVisionConfig, ) __A : Optional[Any] = ...
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'''simple docstring''' import unittest from parameterized import parameterized from transformers import OpenLlamaConfig, is_torch_available, set_seed from transformers.testing_utils import require_torch, torch_device from ...generation.test_utils import GenerationTesterMixin from ...test_configuration_commo...
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import argparse import json import os import sys import tempfile import unittest from argparse import Namespace from dataclasses import dataclass, field from enum import Enum from pathlib import Path from typing import List, Literal, Optional import yaml from transformers import HfArgumentParser, TrainingArguments ...
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'''simple docstring''' import gc import random import unittest import numpy as np import torch from diffusers import ( DDIMScheduler, KandinskyVaaControlnetPipeline, KandinskyVaaPriorPipeline, UNetaDConditionModel, VQModel, ) from diffusers.utils import floats_tensor, load_image, load_num...
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'''simple docstring''' from ...configuration_utils import PretrainedConfig from ...utils import logging _SCREAMING_SNAKE_CASE = logging.get_logger(__name__) _SCREAMING_SNAKE_CASE = { "bigcode/gpt_bigcode-santacoder": "https://huggingface.co/bigcode/gpt_bigcode-santacoder/resolve/mai...
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'''simple docstring''' from typing import TYPE_CHECKING from ...utils import ( OptionalDependencyNotAvailable, _LazyModule, is_flax_available, is_sentencepiece_available, is_tf_available, is_tokenizers_available, is_torch_available, ) UpperCAmelCase_ = {'configuratio...
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"""simple docstring""" import argparse import torch from transformers import BertForMaskedLM if __name__ == "__main__": _a = argparse.ArgumentParser( description=( """Extraction some layers of the full BertForMaskedLM or RObertaForMaskedLM for Transfer Lear...
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'''simple docstring''' import torch from transformers import AutoModel class lowerCAmelCase_ ( torch.nn.Module ): '''simple docstring''' def __init__( self : Tuple , _UpperCAmelCase : List[str]="sayef/fsner-bert-base-uncased" ): """simple docstring"...
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import warnings from typing import List, Optional, Union from ...processing_utils import ProcessorMixin from ...tokenization_utils_base import BatchEncoding, PaddingStrategy, PreTokenizedInput, TextInput, TruncationStrategy from ...utils import TensorType class lowercase_ (lowercase__ ): snake_c...
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'''simple docstring''' def _UpperCamelCase ( SCREAMING_SNAKE_CASE__ : str , SCREAMING_SNAKE_CASE__ : str ): '''simple docstring''' assert x is not None assert y is not None UpperCAmelCase__ = len(SCREAMING_SNAKE_CASE__ ) UpperCAmelCase__ ...
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import contextlib import csv import json import os import sqlitea import tarfile import textwrap import zipfile import pyarrow as pa import pyarrow.parquet as pq import pytest import datasets import datasets.config @pytest.fixture(scope="""session""" ) def lowerCAmelCase_ ( ):...
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'''simple docstring''' from __future__ import annotations from bisect import bisect_left from functools import total_ordering from heapq import merge @total_ordering class lowerCAmelCase_ ( lowerCamelCase_ ): '''simple docstring''' def __lt__( self : List[Any] , _Upper...
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'''simple docstring''' import json import os import unittest from transformers import BatchEncoding, LEDTokenizer, LEDTokenizerFast from transformers.models.led.tokenization_led import VOCAB_FILES_NAMES from transformers.testing_utils import require_tokenizers, require_torch from transformers.uti...
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'''simple docstring''' from typing import TYPE_CHECKING from ...utils import ( OptionalDependencyNotAvailable, _LazyModule, is_tf_available, is_tokenizers_available, is_torch_available, ) UpperCAmelCase_ = { 'configuration_longformer': [ 'LONGFORMER_PRETRAINED_CO...
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def _snake_case (__lowercase): UpperCamelCase_ = 1 for i in range(1 , num + 1): fact *= i return fact def _snake_case (__lowercase): UpperCamelCase_ = 0 while number > 0: UpperCamelCase_ = number % 10 sum_of_di...
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'''simple docstring''' import os import tempfile import unittest from transformers import NezhaConfig, is_torch_available from transformers.models.auto import get_values from transformers.testing_utils import require_torch, require_torch_gpu, slow, torch_device from ...generation.test_utils import Generation...
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'''simple docstring''' import argparse import json import requests import timm import torch from huggingface_hub import hf_hub_download from PIL import Image from transformers import AutoImageProcessor, SwinConfig, SwinForImageClassification def _UpperCamelCase (_lowerCamelCase : List[Any] ...
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'''simple docstring''' import gc import random import unittest import numpy as np import torch from PIL import Image from diffusers import ( DDIMScheduler, KandinskyVaaImgaImgPipeline, KandinskyVaaPriorPipeline, UNetaDConditionModel, VQModel, ) from diffusers.utils import floats_tensor, l...
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import gc import random import unittest import numpy as np import torch from PIL import Image from transformers import CLIPTextConfig, CLIPTextModel, CLIPTokenizer from diffusers import AutoencoderKL, PNDMScheduler, StableDiffusionInpaintPipeline, UNetaDConditionModel from diffusers.utils import floats_tensor, load...
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'''simple docstring''' import unittest from transformers import MPNetConfig, is_torch_available from transformers.testing_utils import require_torch, slow, torch_device from ...test_configuration_common import ConfigTester from ...test_modeling_common import ModelTesterMixin, ids_tensor, random_attention_mas...
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'''simple docstring''' import math __UpperCamelCase = 10 __UpperCamelCase = 7 __UpperCamelCase = BALLS_PER_COLOUR * NUM_COLOURS def _a ( _lowerCamelCase = 20 ) -> str: """simple docstring""" __snake_case : ...
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'''simple docstring''' from __future__ import annotations import unittest import numpy as np from transformers import OPTConfig, is_tf_available from transformers.testing_utils import require_sentencepiece, require_tf, slow from ...test_configuration_common import ConfigTester from ...test_modeling_tf_comm...
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import importlib import os import fsspec import pytest from fsspec import register_implementation from fsspec.registry import _registry as _fsspec_registry from datasets.filesystems import COMPRESSION_FILESYSTEMS, HfFileSystem, extract_path_from_uri, is_remote_filesystem from .utils import requ...
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'''simple docstring''' import unittest from transformers import PegasusTokenizer, PegasusTokenizerFast from transformers.testing_utils import get_tests_dir, require_sentencepiece, require_tokenizers, require_torch, slow from transformers.utils import cached_property from ...test_tokenization_common import To...
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'''simple docstring''' import warnings from ...utils import logging from .image_processing_videomae import VideoMAEImageProcessor UpperCamelCase_ = logging.get_logger(__name__) class _a ( SCREAMING_SNAKE_CASE ): '''simple docstring''' ...
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'''simple docstring''' import unittest import numpy as np def _UpperCamelCase ( SCREAMING_SNAKE_CASE__ : np.ndarray , SCREAMING_SNAKE_CASE__ : np.ndarray , SCREAMING_SNAKE_CASE__ : np.ndarray , SCREAMING_SNAKE_CASE__ : np.ndarray | None = None ...
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"""simple docstring""" # flake8: noqa # Lint as: python3 from typing import Dict, List, Optional, Type from .. import config from ..utils import logging from .formatting import ( ArrowFormatter, CustomFormatter, Formatter, PandasFormatter, PythonFormatter, TensorFormatter, format_table,...
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'''simple docstring''' from collections import namedtuple import requests from lxml import html # type: ignore UpperCAmelCase_ = namedtuple('covid_data', 'cases deaths recovered') def _UpperCamelCase ( SCREAMING_SNAKE_CASE__ : str = "https://www.worldometers.info/coronavirus/" ...
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from __future__ import annotations import math __a = '2020.9.26' __a = 'xcodz-dot, cclaus, dhruvmanila' def lowerCamelCase__ ( _lowercase , _lowercase , _lowercase , _lowercase , _lowercase ): '''simple docstring''' if not all(isinstance(...
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'''simple docstring''' import copy from typing import Dict, List, Optional from ...configuration_utils import PretrainedConfig from ...utils import logging from ..auto import CONFIG_MAPPING UpperCAmelCase_ = { 'facebook/mask2former-swin-small-coco-instance': ( 'https://huggingface.c...
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from maths.prime_check import is_prime def UpperCAmelCase_ ( __UpperCAmelCase : int ) -> int: if not isinstance(__UpperCAmelCase , __UpperCAmelCase ): SCREAMING_SNAKE_CASE_ = f"Input value of [number={number}] must be an integer" raise TypeE...
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'''simple docstring''' UpperCAmelCase_ = [ 'DownloadConfig', 'DownloadManager', 'DownloadMode', 'StreamingDownloadManager', ] from .download_config import DownloadConfig from .download_manager import DownloadManager, DownloadMode from .streaming_download_manager import StreamingDo...
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print((lambda quine: quine % quine)("print((lambda quine: quine %% quine)(%r))"))
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'''simple docstring''' from typing import TYPE_CHECKING from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_sentencepiece_available UpperCAmelCase_ = {} try: if not is_sentencepiece_available(): raise OptionalDependencyNotAvailable() except OptionalDependencyNotAva...
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import copy from dataclasses import dataclass, field from typing import ClassVar, Dict from ..features import ClassLabel, Features, Image from .base import TaskTemplate @dataclass(frozen=snake_case_ ) class __magic_name__ (snake_case_ ): '''simple docstring''' __lo...
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'''simple docstring''' from typing import TYPE_CHECKING from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tf_available, is_torch_available UpperCAmelCase_ = { 'configuration_transfo_xl': ['TRANSFO_XL_PRETRAINED_CONFIG_ARCHIVE_MAP', 'TransfoXLConfig'], 'tokenization_tr...
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"""simple docstring""" import argparse from tax import checkpoints from transformers import AutoConfig, FlaxAutoModelForSeqaSeqLM def __snake_case ( _lowercase ,_lowercase ,_lowercase ): """simple docstring""" UpperCamelCase = AutoConfig.from_pretrained(_l...
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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 UpperCAmelCase_ = { 'configuration_autoformer': [ 'AUTOFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP', 'Au...
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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 by a...
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'''simple docstring''' from typing import TYPE_CHECKING from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available, is_vision_available UpperCAmelCase_ = { 'configuration_mobilenet_v2': [ 'MOBILENET_V2_PRETRAINED_CONFIG_ARCHIVE_MAP', 'MobileNetV2Con...
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# coding=utf-8 # Copyright 2023 The HuggingFace Inc. team. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicab...
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'''simple docstring''' from __future__ import annotations from collections.abc import Callable from typing import Generic, TypeVar UpperCAmelCase_ = TypeVar('T') UpperCAmelCase_ = TypeVar('U') class lowerCAmelCase_ ( Generic[T, U] ): '''simple docstring''' d...
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import json from typing import Iterator, List, Union from tokenizers import AddedToken, Regex, Tokenizer, decoders, normalizers, pre_tokenizers, trainers from tokenizers.implementations.base_tokenizer import BaseTokenizer from tokenizers.models import Unigram from tokenizers.processors import TemplateProcessing ...
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'''simple docstring''' import unittest from transformers import BigBirdTokenizer, BigBirdTokenizerFast from transformers.testing_utils import get_tests_dir, require_sentencepiece, require_tokenizers, require_torch, slow from transformers.utils import cached_property from ...test_tokenization_common import To...
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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 A_ : List[str] = logging.get_logger(__name__) A_ : Dict = ...
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'''simple docstring''' import unittest from parameterized import parameterized from transformers import OpenLlamaConfig, is_torch_available, set_seed from transformers.testing_utils import require_torch, torch_device from ...generation.test_utils import GenerationTesterMixin from ...test_configuration_commo...
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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 lowerCAmelCase_ = { # 1536-bit 5: { '''prime''': int( ...
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'''simple docstring''' import gc import random import unittest import numpy as np import torch from diffusers import ( DDIMScheduler, KandinskyVaaControlnetPipeline, KandinskyVaaPriorPipeline, UNetaDConditionModel, VQModel, ) from diffusers.utils import floats_tensor, load_image, load_num...
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import logging import math from functools import partial from typing import Any, Callable, Dict, Iterable, List, Optional, Sequence, Tuple, Union import torch from .tensor_utils import tensor_tree_map, tree_map def UpperCamelCase ( snake_case__ : Union[dict, list, tuple, torch.Tensor] ) ...
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'''simple docstring''' from typing import TYPE_CHECKING from ...utils import ( OptionalDependencyNotAvailable, _LazyModule, is_flax_available, is_sentencepiece_available, is_tf_available, is_tokenizers_available, is_torch_available, ) UpperCAmelCase_ = {'configuratio...
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'''simple docstring''' import torch from diffusers import DDPMScheduler from .test_schedulers import SchedulerCommonTest class lowercase_ (lowerCamelCase__ ): """simple docstring""" SCREAMING_SNAKE_CASE : Dict = (DDPMScheduler,) def SCREAMING_SNAK...
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'''simple docstring''' import torch from transformers import AutoModel class lowerCAmelCase_ ( torch.nn.Module ): '''simple docstring''' def __init__( self : Tuple , _UpperCAmelCase : List[str]="sayef/fsner-bert-base-uncased" ): """simple docstring"...
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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 ....
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'''simple docstring''' def _UpperCamelCase ( SCREAMING_SNAKE_CASE__ : str , SCREAMING_SNAKE_CASE__ : str ): '''simple docstring''' assert x is not None assert y is not None UpperCAmelCase__ = len(SCREAMING_SNAKE_CASE__ ) UpperCAmelCase__ ...
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from __future__ import annotations from math import pi from typing import Protocol import matplotlib.pyplot as plt import numpy as np class _a ( UpperCamelCase__ ): def lowerCamelCase_ ( self: List[Any] , UpperCamelCase_: float ) -> float: ...
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'''simple docstring''' from __future__ import annotations from bisect import bisect_left from functools import total_ordering from heapq import merge @total_ordering class lowerCAmelCase_ ( lowerCamelCase_ ): '''simple docstring''' def __lt__( self : List[Any] , _Upper...
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'''simple docstring''' import unittest from transformers import DonutProcessor UpperCAmelCase_ : List[Any] = 'naver-clova-ix/donut-base' class UpperCAmelCase__ ( unittest.TestCase ): def lowerCamelCase_ ( self : List[str] ): _lowerCamelCase : List...
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'''simple docstring''' from typing import TYPE_CHECKING from ...utils import ( OptionalDependencyNotAvailable, _LazyModule, is_tf_available, is_tokenizers_available, is_torch_available, ) UpperCAmelCase_ = { 'configuration_longformer': [ 'LONGFORMER_PRETRAINED_CO...
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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 UpperCamelCase = logging.get_logger(__name__) UpperCamelCase = { "facebook/data...
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'''simple docstring''' import os import tempfile import unittest from transformers import NezhaConfig, is_torch_available from transformers.models.auto import get_values from transformers.testing_utils import require_torch, require_torch_gpu, slow, torch_device from ...generation.test_utils import Generation...
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"""simple docstring""" def lowerCamelCase_( _lowerCamelCase , _lowerCamelCase ) -> int: '''simple docstring''' _lowerCamelCase : List[str] = "" for i in table: res += inp[i - 1] return res def lowerCamelCase_( _lowerCamelCase ) ...
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'''simple docstring''' import gc import random import unittest import numpy as np import torch from PIL import Image from diffusers import ( DDIMScheduler, KandinskyVaaImgaImgPipeline, KandinskyVaaPriorPipeline, UNetaDConditionModel, VQModel, ) from diffusers.utils import floats_tensor, l...
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def UpperCAmelCase__ ( ): __a : Union[str, Any] = 0 for i in range(1 , 1_0_0_1 ): total += i**i return str(lowerCamelCase_ )[-1_0:] if __name__ == "__main__": print(solution())
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'''simple docstring''' import unittest from transformers import MPNetConfig, is_torch_available from transformers.testing_utils import require_torch, slow, torch_device from ...test_configuration_common import ConfigTester from ...test_modeling_common import ModelTesterMixin, ids_tensor, random_attention_mas...
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'''simple docstring''' from typing import Dict, List, Optional, Union import numpy as np from ...image_processing_utils import BaseImageProcessor, BatchFeature, get_size_dict from ...image_transforms import ( center_crop, get_resize_output_image_size, normalize, rescale, resize, to_channel_d...
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'''simple docstring''' from __future__ import annotations import unittest import numpy as np from transformers import OPTConfig, is_tf_available from transformers.testing_utils import require_sentencepiece, require_tf, slow from ...test_configuration_common import ConfigTester from ...test_modeling_tf_comm...
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"""simple docstring""" from math import pi, sqrt, tan def lowercase__ ( snake_case_ :float ): if side_length < 0: raise ValueError('''surface_area_cube() only accepts non-negative values''' ) return 6 * side_length**2 def lowercase__ ( ...
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'''simple docstring''' import unittest from transformers import PegasusTokenizer, PegasusTokenizerFast from transformers.testing_utils import get_tests_dir, require_sentencepiece, require_tokenizers, require_torch, slow from transformers.utils import cached_property from ...test_tokenization_common import To...
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'''simple docstring''' import unittest import numpy as np import torch from .utils_summarization import build_mask, compute_token_type_ids, process_story, truncate_or_pad class UpperCamelCase__ (unittest.TestCase ): '''simple docstring''' def UpperCamelCase_ ( s...
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'''simple docstring''' import unittest import numpy as np def _UpperCamelCase ( SCREAMING_SNAKE_CASE__ : np.ndarray , SCREAMING_SNAKE_CASE__ : np.ndarray , SCREAMING_SNAKE_CASE__ : np.ndarray , SCREAMING_SNAKE_CASE__ : np.ndarray | None = None ...
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'''simple docstring''' import argparse import collections import numpy as np import torch from flax import traverse_util from tax import checkpoints from transformers import MTaConfig, UMTaEncoderModel, UMTaForConditionalGeneration from transformers.utils import logging logging.set_verbosity_info() def ...
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'''simple docstring''' from collections import namedtuple import requests from lxml import html # type: ignore UpperCAmelCase_ = namedtuple('covid_data', 'cases deaths recovered') def _UpperCamelCase ( SCREAMING_SNAKE_CASE__ : str = "https://www.worldometers.info/coronavirus/" ...
603
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"""simple docstring""" from itertools import permutations def __A ( a_ :tuple) -> bool: if num[3] % 2 != 0: return False if (num[2] + num[3] + num[4]) % 3 != 0: return False if num[5] % 5 != 0: return False __a : List...
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'''simple docstring''' import copy from typing import Dict, List, Optional from ...configuration_utils import PretrainedConfig from ...utils import logging from ..auto import CONFIG_MAPPING UpperCAmelCase_ = { 'facebook/mask2former-swin-small-coco-instance': ( 'https://huggingface.c...
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import faiss # noqa: F401 # Here to have a nice missing dependency error message early on import numpy # noqa: F401 # Here to have a nice missing dependency error message early on import requests # noqa: F401 # Here to have a nice missing dependency error message early on import sklearn # noqa: F401 # Here to...
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'''simple docstring''' UpperCAmelCase_ = [ 'DownloadConfig', 'DownloadManager', 'DownloadMode', 'StreamingDownloadManager', ] from .download_config import DownloadConfig from .download_manager import DownloadManager, DownloadMode from .streaming_download_manager import StreamingDo...
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from __future__ import annotations def a__ ( lowercase__ , lowercase__ = None ): '''simple docstring''' UpperCAmelCase_ =word_bank or [] # create a table UpperCAmelCase_ =len(lowercase__ ) + 1 UpperCAmelCase_ ...
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'''simple docstring''' from typing import TYPE_CHECKING from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_sentencepiece_available UpperCAmelCase_ = {} try: if not is_sentencepiece_available(): raise OptionalDependencyNotAvailable() except OptionalDependencyNotAva...
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from json import JSONDecodeError # Workaround for requests.exceptions.JSONDecodeError import requests def UpperCAmelCase ( a_ = "isbn/0140328726" ) -> dict: """simple docstring""" __A = olid.strip().strip("/" ) # Remove leading/trailing whitespace & slashes i...
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'''simple docstring''' from typing import TYPE_CHECKING from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tf_available, is_torch_available UpperCAmelCase_ = { 'configuration_transfo_xl': ['TRANSFO_XL_PRETRAINED_CONFIG_ARCHIVE_MAP', 'TransfoXLConfig'], 'tokenization_tr...
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'''simple docstring''' import collections import json import math import os import re import time from fnmatch import fnmatch from typing import Dict import requests from slack_sdk import WebClient _a : int = WebClient(token=os.environ["CI_SLACK_BOT_TOKEN"]) def _a (lowercase__ : ...
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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 UpperCAmelCase_ = { 'configuration_autoformer': [ 'AUTOFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP', 'Au...
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from collections.abc import Sequence from queue import Queue class _lowerCAmelCase: """simple docstring""" def __init__( self , _lowerCamelCase , _lowerCamelCase , _lowerCamelCase , _lowerCamelCase=None , _lowerC...
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'''simple docstring''' from typing import TYPE_CHECKING from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available, is_vision_available UpperCAmelCase_ = { 'configuration_mobilenet_v2': [ 'MOBILENET_V2_PRETRAINED_CONFIG_ARCHIVE_MAP', 'MobileNetV2Con...
603
0
"""simple docstring""" def __lowerCAmelCase ( ): '''simple docstring''' for n in range(1 , 1_0_0_0_0_0_0 ): yield n * (n + 1) // 2 def __lowerCAmelCase ( __UpperCamelCase : int ): '''simple docstring''' ...
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'''simple docstring''' from __future__ import annotations from collections.abc import Callable from typing import Generic, TypeVar UpperCAmelCase_ = TypeVar('T') UpperCAmelCase_ = TypeVar('U') class lowerCAmelCase_ ( Generic[T, U] ): '''simple docstring''' d...
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import argparse import os # New Code # import evaluate import torch from datasets import load_dataset from torch.optim import AdamW from torch.utils.data import DataLoader from transformers import AutoModelForSequenceClassification, AutoTokenizer, get_linear_schedule_with_warmup, set_seed from accelerate import...
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'''simple docstring''' import unittest from transformers import BigBirdTokenizer, BigBirdTokenizerFast from transformers.testing_utils import get_tests_dir, require_sentencepiece, require_tokenizers, require_torch, slow from transformers.utils import cached_property from ...test_tokenization_common import To...
603
0