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def __lowerCamelCase (UpperCAmelCase__ : int , UpperCAmelCase__ : int ): return number | (1 << position) def __lowerCamelCase (UpperCAmelCase__ : int , UpperCAmelCase__ : int ): return number & ~(1 << position) def __lo...
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def __lowerCamelCase (UpperCAmelCase__ : list[int] ): if not numbers: return 0 if not isinstance(UpperCAmelCase__ , (list, tuple) ) or not all( isinstance(UpperCAmelCase__ , UpperCAmelCase__ ) for number in numbers ): raise ValueError("numbers...
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import os from shutil import copyfile from typing import Any, Dict, List, Optional, Tuple import sentencepiece as spm from ...tokenization_utils import PreTrainedTokenizer from ...utils import logging _lowerCamelCase : Union[str, Any] = logging.get_logger(__name__) _lowerCamelCase : ...
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import functools import logging import os import sys import threading from logging import ( CRITICAL, # NOQA DEBUG, # NOQA ERROR, # NOQA FATAL, # NOQA INFO, # NOQA NOTSET, # NOQA WARN, # NOQA WARNING, # NOQA ) from typing import Optional import huggingface_hub.u...
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# this script reports modified .py files under the desired list of top-level sub-dirs passed as a list of arguments, e.g.: # python ./utils/get_modified_files.py utils src tests examples # # it uses git to find the forking point and which files were modified - i.e. files not under git won't be considered # since ...
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import os import tempfile import unittest from transformers.models.marian.convert_marian_tatoeba_to_pytorch import DEFAULT_REPO, TatoebaConverter from transformers.testing_utils import slow from transformers.utils import cached_property @unittest.skipUnless(os.path.exists(a ) , """Tatoeba direc...
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import math import time from typing import Dict, List, Optional from torch.utils.data import Dataset from transformers import SeqaSeqTrainer, is_torch_tpu_available from transformers.trainer_utils import PredictionOutput, speed_metrics if is_torch_tpu_available(check_device=False): import torch_xl...
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import inspect import unittest from transformers import ViTHybridConfig from transformers.testing_utils import require_accelerate, require_torch, require_vision, slow, torch_device from transformers.utils import cached_property, is_torch_available, is_vision_available from ...test_configuration_common import C...
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import argparse import os import re _lowerCamelCase : List[str] = '''src/diffusers''' # Pattern that looks at the indentation in a line. _lowerCamelCase : str = re.compile(r'''^(\s*)\S''') # Pattern that matches `"key":" and puts `key` in group 0. _lowerCamelCase : int ...
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from typing import Dict, Optional, Union import numpy as np from ...image_processing_utils import BaseImageProcessor, BatchFeature, get_size_dict from ...image_transforms import flip_channel_order, resize, to_channel_dimension_format, to_pil_image from ...image_utils import ( ChannelDimension, ImageIn...
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import os import time import pytest from datasets.utils.filelock import FileLock, Timeout def __lowerCamelCase (UpperCAmelCase__ : str ): SCREAMING_SNAKE_CASE = FileLock(str(tmpdir / "foo.lock" ) ) SCREAMING_SNAKE_CASE = FileLock(str(tmpdir / "fo...
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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, prepare_image_inputs ...
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from typing import Optional import pyspark from .. import Features, NamedSplit from ..download import DownloadMode from ..packaged_modules.spark.spark import Spark from .abc import AbstractDatasetReader class lowercase ( a ): def __init__( self : Dict , _U...
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from typing import Dict, List, Optional, Union import numpy as np from .feature_extraction_utils import BatchFeature, FeatureExtractionMixin from .utils import PaddingStrategy, TensorType, is_tf_tensor, is_torch_tensor, logging, to_numpy _lowerCamelCase : Optional[Any] = logging.get_logger(__na...
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import numpy as np import skfuzzy as fuzz if __name__ == "__main__": # Create universe of discourse in Python using linspace () _lowerCamelCase : 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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import functools def __lowerCamelCase (UpperCAmelCase__ : list[int] , UpperCAmelCase__ : list[int] ): # Validation if not isinstance(UpperCAmelCase__ , UpperCAmelCase__ ) or not all(isinstance(UpperCAmelCase__ , UpperCAmelCase__ ) for day in days ):...
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from typing import TYPE_CHECKING from ...utils import ( OptionalDependencyNotAvailable, _LazyModule, is_sentencepiece_available, is_torch_available, ) _lowerCamelCase : str = { '''configuration_speecht5''': [ '''SPEECHT5_PRETRAINED_CONFIG_ARCHIVE_MAP''', ...
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from __future__ import annotations import math def __lowerCamelCase (UpperCAmelCase__ : int ): if 1 < number < 4: # 2 and 3 are primes return True elif number < 2 or number % 2 == 0 or number % 3 == 0: # Negatives, 0, 1, all even numbers, al...
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import math import unittest def __lowerCamelCase (UpperCAmelCase__ : int ): assert isinstance(UpperCAmelCase__ , UpperCAmelCase__ ) and ( number >= 0 ), "'number' must been an int and positive" if 1 < number < 4: # 2 and 3 are primes ...
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import unittest import numpy as np from transformers.file_utils import is_torch_available, is_vision_available from transformers.testing_utils import require_torch, require_vision from ...test_image_processing_common import ImageProcessingSavingTestMixin, prepare_image_inputs if is_torch_available(): ...
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from ...configuration_utils import PretrainedConfig from ...utils import logging _lowerCamelCase : Optional[Any] = logging.get_logger(__name__) _lowerCamelCase : Tuple = { '''facebook/s2t-wav2vec2-large-en-de''': ( '''https://huggingface.co/facebook/s2t-wav2vec2-large-en...
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import argparse import json import requests import torch from huggingface_hub import hf_hub_download from PIL import Image from transformers import ViTImageProcessor, ViTMSNConfig, ViTMSNModel from transformers.image_utils import IMAGENET_DEFAULT_MEAN, IMAGENET_DEFAULT_STD torch.set_grad_enabled(False) ...
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# Copyright 2023 The HuggingFace Inc. team. All rights reserved. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required...
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import collections import os from shutil import copyfile from typing import Any, Dict, List, Optional, Tuple from ...tokenization_utils import PreTrainedTokenizer from ...utils import logging _lowerCamelCase : Dict = logging.get_logger(__name__) _lowerCamelCase : List[Any] = '''...
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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 lowercase ( unittest.TestCase ): ...
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import numpy as np def __lowerCamelCase (UpperCAmelCase__ : np.ndarray , UpperCAmelCase__ : np.ndarray , UpperCAmelCase__ : float = 1e-12 , UpperCAmelCase__ : int = 1_0_0 , ): assert np.shape(UpperCAmelCase__ )[0] == np.shape(UpperCAme...
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import numpy as np from PIL import Image def __lowerCamelCase (UpperCAmelCase__ : np.ndarray , UpperCAmelCase__ : int , UpperCAmelCase__ : int ): SCREAMING_SNAKE_CASE = np.array(UpperCAmelCase__ ) if arr.shape[0] != arr.shape[1]: ...
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import copy from typing import Any, Dict, List, Optional, Union import numpy as np import torch from ...audio_utils import mel_filter_bank, spectrogram, window_function from ...feature_extraction_sequence_utils import SequenceFeatureExtractor from ...feature_extraction_utils import BatchFeature from ...utils...
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import itertools import math def __lowerCamelCase (UpperCAmelCase__ : int ): if 1 < number < 4: # 2 and 3 are primes return True elif number < 2 or number % 2 == 0 or number % 3 == 0: # Negatives, 0, 1, all even numbers, all multiples of 3 are...
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import argparse import logging from collections import namedtuple import torch from model_bertabs import BertAbsSummarizer from models.model_builder import AbsSummarizer # The authors' implementation from transformers import BertTokenizer logging.basicConfig(level=logging.INFO) _lowerCamelCase : ...
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import bza import gzip import lzma import os import shutil import struct import tarfile import warnings import zipfile from abc import ABC, abstractmethod from pathlib import Path from typing import Dict, List, Optional, Type, Union from .. import config from .filelock import FileLock from .logging impo...
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def __lowerCamelCase (UpperCAmelCase__ : int ): assert isinstance(UpperCAmelCase__ , UpperCAmelCase__ ), F"The input value of [n={number}] is not an integer" if number == 1: return 2 elif number < 1: SCREAMING_SNAKE_CASE = F"The input value o...
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import builtins import sys from ...utils.imports import _is_package_available from . import cursor, input from .helpers import Direction, clear_line, forceWrite, linebreak, move_cursor, reset_cursor, writeColor from .keymap import KEYMAP _lowerCamelCase : Optional[int] = False try: _lo...
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import inspect import os import unittest import torch import accelerate from accelerate import Accelerator from accelerate.test_utils import execute_subprocess_async, require_multi_gpu from accelerate.utils import patch_environment class lowercase ( unittest.TestCase ): ...
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from ...configuration_utils import PretrainedConfig from ...utils import logging _lowerCamelCase : str = logging.get_logger(__name__) _lowerCamelCase : Tuple = { '''facebook/s2t-small-librispeech-asr''': ( '''https://huggingface.co/facebook/s2t-small-librispeech-asr/reso...
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import torch from diffusers import KDPMaDiscreteScheduler from diffusers.utils import torch_device from .test_schedulers import SchedulerCommonTest class lowercase ( a ): lowercase__ : Tuple = (KDPMaDiscreteScheduler,) lowercase__ : Optiona...
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def __lowerCamelCase (UpperCAmelCase__ : str , UpperCAmelCase__ : str ): assert x is not None assert y is not None SCREAMING_SNAKE_CASE = len(UpperCAmelCase__ ) SCREAMING_SNAKE_CASE = len(UpperCAmelCase__ ) # declaring the arra...
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from __future__ import annotations from typing import Dict from ...configuration_utils import PretrainedConfig _lowerCamelCase : Tuple = { '''susnato/ernie-m-base_pytorch''': '''https://huggingface.co/susnato/ernie-m-base_pytorch/blob/main/config.json''', '''susnato/ernie-m-large_pytor...
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import os import tempfile import unittest from transformers.models.marian.convert_marian_tatoeba_to_pytorch import DEFAULT_REPO, TatoebaConverter from transformers.testing_utils import slow from transformers.utils import cached_property @unittest.skipUnless(os.path.exists(a ) , """Tatoeba direc...
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from typing import TYPE_CHECKING from ...utils import ( OptionalDependencyNotAvailable, _LazyModule, is_flax_available, is_tf_available, is_tokenizers_available, is_torch_available, ) _lowerCamelCase : Optional[int] = { '''configuration_blenderbot''': [ ...
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from argparse import ArgumentParser from . import BaseTransformersCLICommand def __lowerCamelCase (UpperCAmelCase__ : Optional[Any] ): return DownloadCommand(args.model , args.cache_dir , args.force , args.trust_remote_code ) class lowercase ( a ...
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from __future__ import annotations from collections.abc import Iterator from typing import Generic, TypeVar _lowerCamelCase : Optional[Any] = TypeVar('''T''') class lowercase ( Generic[T] ): def __init__( self : Any , _UpperCamelCase : T ...
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import os import zipfile import requests from get_ci_error_statistics import download_artifact, get_artifacts_links def __lowerCamelCase (UpperCAmelCase__ : Tuple , UpperCAmelCase__ : Tuple=7 ): SCREAMING_SNAKE_CASE = None if token is not None: ...
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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 a...
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import json from typing import TYPE_CHECKING, List, Optional, Tuple from tokenizers import pre_tokenizers from ...tokenization_utils_fast import PreTrainedTokenizerFast from ...utils import logging if TYPE_CHECKING: from transformers.pipelines.conversational import Conversation _lowerCamelCase...
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def __lowerCamelCase (UpperCAmelCase__ : list[int] ): if not numbers: return 0 if not isinstance(UpperCAmelCase__ , (list, tuple) ) or not all( isinstance(UpperCAmelCase__ , UpperCAmelCase__ ) for number in numbers ): raise ValueError("numbers...
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def __lowerCamelCase (UpperCAmelCase__ : Dict ): SCREAMING_SNAKE_CASE = 0 SCREAMING_SNAKE_CASE = len(UpperCAmelCase__ ) for i in range(n - 1 ): for j in range(i + 1 , UpperCAmelCase__ ): if arr[i] > arr[j]: ...
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import functools import logging import os import sys import threading from logging import ( CRITICAL, # NOQA DEBUG, # NOQA ERROR, # NOQA FATAL, # NOQA INFO, # NOQA NOTSET, # NOQA WARN, # NOQA WARNING, # NOQA ) from typing import Optional import huggingface_hub.u...
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from ...configuration_utils import PretrainedConfig from ...utils import logging _lowerCamelCase : Union[str, Any] = logging.get_logger(__name__) _lowerCamelCase : str = { '''alibaba-damo/mgp-str-base''': '''https://huggingface.co/alibaba-damo/mgp-str-base/resolve/main/config.jso...
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import os import tempfile import unittest from transformers.models.marian.convert_marian_tatoeba_to_pytorch import DEFAULT_REPO, TatoebaConverter from transformers.testing_utils import slow from transformers.utils import cached_property @unittest.skipUnless(os.path.exists(a ) , """Tatoeba direc...
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import gc import random import unittest import numpy as np import torch from diffusers import DDIMScheduler, KandinskyVaaPipeline, KandinskyVaaPriorPipeline, UNetaDConditionModel, VQModel from diffusers.utils import floats_tensor, load_numpy, slow, torch_device from diffusers.utils.testing_utils import enabl...
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import inspect import unittest from transformers import ViTHybridConfig from transformers.testing_utils import require_accelerate, require_torch, require_vision, slow, torch_device from transformers.utils import cached_property, is_torch_available, is_vision_available from ...test_configuration_common import C...
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class lowercase ( a ): pass class lowercase ( a ): pass class lowercase : def __init__( self : Any ) -> int: '''simple docstring''' SCREAMING_SNAKE_CASE = [ ...
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from typing import Dict, Optional, Union import numpy as np from ...image_processing_utils import BaseImageProcessor, BatchFeature, get_size_dict from ...image_transforms import flip_channel_order, resize, to_channel_dimension_format, to_pil_image from ...image_utils import ( ChannelDimension, ImageIn...
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import os import jsonlines import numpy as np from tqdm import tqdm _lowerCamelCase : List[Any] = 20_48 _lowerCamelCase : List[str] = 40_96 _lowerCamelCase : Optional[Any] = 42 _lowerCamelCase : Optional[Any] = os.environ.pop('''PROCESS_TRAIN''', '''false...
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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, prepare_image_inputs ...
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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 a...
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from typing import Dict, List, Optional, Union import numpy as np from .feature_extraction_utils import BatchFeature, FeatureExtractionMixin from .utils import PaddingStrategy, TensorType, is_tf_tensor, is_torch_tensor, logging, to_numpy _lowerCamelCase : Optional[Any] = logging.get_logger(__na...
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from __future__ import annotations from collections.abc import Iterator from typing import Generic, TypeVar _lowerCamelCase : Optional[Any] = TypeVar('''T''') class lowercase ( Generic[T] ): def __init__( self : Any , _UpperCamelCase : T ...
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import functools def __lowerCamelCase (UpperCAmelCase__ : list[int] , UpperCAmelCase__ : list[int] ): # Validation if not isinstance(UpperCAmelCase__ , UpperCAmelCase__ ) or not all(isinstance(UpperCAmelCase__ , UpperCAmelCase__ ) for day in days ):...
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def __lowerCamelCase (UpperCAmelCase__ : int ): assert isinstance(UpperCAmelCase__ , UpperCAmelCase__ ), F"The input value of [n={number}] is not an integer" if number == 1: return 2 elif number < 1: SCREAMING_SNAKE_CASE = F"The input value o...
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from __future__ import annotations import math def __lowerCamelCase (UpperCAmelCase__ : int ): if 1 < number < 4: # 2 and 3 are primes return True elif number < 2 or number % 2 == 0 or number % 3 == 0: # Negatives, 0, 1, all even numbers, al...
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from manim import * class lowercase ( a ): def __snake_case( self : int ) -> str: '''simple docstring''' SCREAMING_SNAKE_CASE = Rectangle(height=0.5 , width=0.5 ) SCREAMING_SNAKE_CASE ...
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import unittest import numpy as np from transformers.file_utils import is_torch_available, is_vision_available from transformers.testing_utils import require_torch, require_vision from ...test_image_processing_common import ImageProcessingSavingTestMixin, prepare_image_inputs if is_torch_available(): ...
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from ...utils import logging from ..ta.modeling_tf_ta import TFTaEncoderModel, TFTaForConditionalGeneration, TFTaModel from .configuration_mta import MTaConfig _lowerCamelCase : Tuple = logging.get_logger(__name__) _lowerCamelCase : int = '''T5Config''' class lowercase ...
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import argparse import json import requests import torch from huggingface_hub import hf_hub_download from PIL import Image from transformers import ViTImageProcessor, ViTMSNConfig, ViTMSNModel from transformers.image_utils import IMAGENET_DEFAULT_MEAN, IMAGENET_DEFAULT_STD torch.set_grad_enabled(False) ...
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from collections import Counter from pathlib import Path from typing import Optional, Tuple import yaml class lowercase ( yaml.SafeLoader ): def __snake_case( self : Any , _UpperCamelCase : List[Any] ) -> Union[str, Any]: ...
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import collections import os from shutil import copyfile from typing import Any, Dict, List, Optional, Tuple from ...tokenization_utils import PreTrainedTokenizer from ...utils import logging _lowerCamelCase : Dict = logging.get_logger(__name__) _lowerCamelCase : List[Any] = '''...
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import os from argparse import ArgumentParser, Namespace from ..data import SingleSentenceClassificationProcessor as Processor from ..pipelines import TextClassificationPipeline from ..utils import is_tf_available, is_torch_available, logging from . import BaseTransformersCLICommand if not is_tf_available()...
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import numpy as np def __lowerCamelCase (UpperCAmelCase__ : np.ndarray , UpperCAmelCase__ : np.ndarray , UpperCAmelCase__ : float = 1e-12 , UpperCAmelCase__ : int = 1_0_0 , ): assert np.shape(UpperCAmelCase__ )[0] == np.shape(UpperCAme...
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import glob import os import random from string import ascii_lowercase, digits import cva import numpy as np # Parrameters _lowerCamelCase : Optional[int] = (7_20, 12_80) # Height, Width _lowerCamelCase : str = (0.4, 0.6) # if height or width lower than this scale, drop it. _low...
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import copy from typing import Any, Dict, List, Optional, Union import numpy as np import torch from ...audio_utils import mel_filter_bank, spectrogram, window_function from ...feature_extraction_sequence_utils import SequenceFeatureExtractor from ...feature_extraction_utils import BatchFeature from ...utils...
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# This script creates a super tiny model that is useful inside tests, when we just want to test that # the machinery works, without needing to the check the quality of the outcomes. # # This version creates a tiny model through reduction of a normal pre-trained model, but keeping the # full vocab, merges file, and ...
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import argparse import logging from collections import namedtuple import torch from model_bertabs import BertAbsSummarizer from models.model_builder import AbsSummarizer # The authors' implementation from transformers import BertTokenizer logging.basicConfig(level=logging.INFO) _lowerCamelCase : ...
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import argparse import os import re import packaging.version _lowerCamelCase : str = '''examples/''' _lowerCamelCase : List[Any] = { '''examples''': (re.compile(r'''^check_min_version\("[^"]+"\)\s*$''', re.MULTILINE), '''check_min_version("VERSION")\n'''), '''init''': (re....
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def __lowerCamelCase (UpperCAmelCase__ : int ): assert isinstance(UpperCAmelCase__ , UpperCAmelCase__ ), F"The input value of [n={number}] is not an integer" if number == 1: return 2 elif number < 1: SCREAMING_SNAKE_CASE = F"The input value o...
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import os from shutil import copyfile from typing import Any, Dict, List, Optional, Tuple import sentencepiece as spm from ...tokenization_utils import AddedToken, PreTrainedTokenizer from ...utils import logging _lowerCamelCase : Optional[Any] = logging.get_logger(__name__) _lowerCamelCas...
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import inspect import os import unittest import torch import accelerate from accelerate import Accelerator from accelerate.test_utils import execute_subprocess_async, require_multi_gpu from accelerate.utils import patch_environment class lowercase ( unittest.TestCase ): ...
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from typing import Dict, Optional, Union import numpy as np from ...image_processing_utils import BaseImageProcessor, BatchFeature, get_size_dict from ...image_transforms import flip_channel_order, resize, to_channel_dimension_format, to_pil_image from ...image_utils import ( ChannelDimension, ImageIn...
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import torch from diffusers import KDPMaDiscreteScheduler from diffusers.utils import torch_device from .test_schedulers import SchedulerCommonTest class lowercase ( a ): lowercase__ : Tuple = (KDPMaDiscreteScheduler,) lowercase__ : Optiona...
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class lowercase : def __init__( self : Dict ) -> Optional[Any]: '''simple docstring''' SCREAMING_SNAKE_CASE = {} def __snake_case( self : str ) -> None: '''simple docs...
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from __future__ import annotations from typing import Dict from ...configuration_utils import PretrainedConfig _lowerCamelCase : Tuple = { '''susnato/ernie-m-base_pytorch''': '''https://huggingface.co/susnato/ernie-m-base_pytorch/blob/main/config.json''', '''susnato/ernie-m-large_pytor...
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from __future__ import annotations import random import unittest from transformers import TransfoXLConfig, is_tf_available from transformers.testing_utils import require_tf, slow from ...test_configuration_common import ConfigTester from ...test_modeling_tf_common import TFModelTesterMixin, ids_tensor from...
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from typing import TYPE_CHECKING from ...utils import ( OptionalDependencyNotAvailable, _LazyModule, is_flax_available, is_tf_available, is_tokenizers_available, is_torch_available, ) _lowerCamelCase : Optional[int] = { '''configuration_blenderbot''': [ ...
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from __future__ import annotations from typing import Dict from ...configuration_utils import PretrainedConfig _lowerCamelCase : Tuple = { '''susnato/ernie-m-base_pytorch''': '''https://huggingface.co/susnato/ernie-m-base_pytorch/blob/main/config.json''', '''susnato/ernie-m-large_pytor...
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from __future__ import annotations from collections.abc import Iterator from typing import Generic, TypeVar _lowerCamelCase : Optional[Any] = TypeVar('''T''') class lowercase ( Generic[T] ): def __init__( self : Any , _UpperCamelCase : T ...
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from typing import List, Optional, Union from ...image_utils import ImageInput from ...processing_utils import ProcessorMixin from ...tokenization_utils_base import BatchEncoding, PaddingStrategy, PreTokenizedInput, TextInput, TruncationStrategy from ...utils import TensorType class lowercase ( ...
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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 a...
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from pathlib import Path from typing import List from transformers import is_torch_available, is_vision_available from transformers.testing_utils import get_tests_dir, is_tool_test from transformers.tools.agent_types import AGENT_TYPE_MAPPING, AgentAudio, AgentImage, AgentText if is_torch_available(): ...
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def __lowerCamelCase (UpperCAmelCase__ : list[int] ): if not numbers: return 0 if not isinstance(UpperCAmelCase__ , (list, tuple) ) or not all( isinstance(UpperCAmelCase__ , UpperCAmelCase__ ) for number in numbers ): raise ValueError("numbers...
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from __future__ import annotations import math def __lowerCamelCase (UpperCAmelCase__ : int ): if 1 < number < 4: # 2 and 3 are primes return True elif number < 2 or number % 2 == 0 or number % 3 == 0: # Negatives, 0, 1, all even numbers, al...
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import functools import logging import os import sys import threading from logging import ( CRITICAL, # NOQA DEBUG, # NOQA ERROR, # NOQA FATAL, # NOQA INFO, # NOQA NOTSET, # NOQA WARN, # NOQA WARNING, # NOQA ) from typing import Optional import huggingface_hub.u...
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from dataclasses import dataclass, field from typing import Tuple from ..utils import cached_property, is_torch_available, is_torch_tpu_available, logging, requires_backends from .benchmark_args_utils import BenchmarkArguments if is_torch_available(): import torch if is_torch_tpu_available(check_de...
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import os import tempfile import unittest from transformers.models.marian.convert_marian_tatoeba_to_pytorch import DEFAULT_REPO, TatoebaConverter from transformers.testing_utils import slow from transformers.utils import cached_property @unittest.skipUnless(os.path.exists(a ) , """Tatoeba direc...
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from ...configuration_utils import PretrainedConfig from ...utils import logging _lowerCamelCase : Optional[int] = logging.get_logger(__name__) _lowerCamelCase : Tuple = { '''microsoft/biogpt''': '''https://huggingface.co/microsoft/biogpt/resolve/main/config.json''', # See a...
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import inspect import unittest from transformers import ViTHybridConfig from transformers.testing_utils import require_accelerate, require_torch, require_vision, slow, torch_device from transformers.utils import cached_property, is_torch_available, is_vision_available from ...test_configuration_common import C...
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import math def __lowerCamelCase (UpperCAmelCase__ : int ): SCREAMING_SNAKE_CASE = [True] * n SCREAMING_SNAKE_CASE = False SCREAMING_SNAKE_CASE = False SCREAMING_SNAKE_CASE = True for i in range(3 , int(n**...
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from typing import Dict, Optional, Union import numpy as np from ...image_processing_utils import BaseImageProcessor, BatchFeature, get_size_dict from ...image_transforms import flip_channel_order, resize, to_channel_dimension_format, to_pil_image from ...image_utils import ( ChannelDimension, ImageIn...
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def __lowerCamelCase (UpperCAmelCase__ : Any ): SCREAMING_SNAKE_CASE = len(UpperCAmelCase__ ) while cur > 1: # Find the maximum number in arr SCREAMING_SNAKE_CASE = arr.index(max(arr[0:cur] ) ) # Reverse from 0 to mi SC...
647
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, prepare_image_inputs ...
647
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from collections.abc import Callable class lowercase : def __init__( self : List[str] , _UpperCamelCase : Callable | None = None ) -> None: '''simple docstring''' SCREAMING_SNAKE_CASE = [] # Store...
647
from typing import Dict, List, Optional, Union import numpy as np from .feature_extraction_utils import BatchFeature, FeatureExtractionMixin from .utils import PaddingStrategy, TensorType, is_tf_tensor, is_torch_tensor, logging, to_numpy _lowerCamelCase : Optional[Any] = logging.get_logger(__na...
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import timeit import numpy as np import datasets from datasets.arrow_writer import ArrowWriter from datasets.features.features import _ArrayXD def __lowerCamelCase (UpperCAmelCase__ : int ): def wrapper(*UpperCAmelCase__ : int , **UpperCAmelCase__ : Op...
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import functools def __lowerCamelCase (UpperCAmelCase__ : list[int] , UpperCAmelCase__ : list[int] ): # Validation if not isinstance(UpperCAmelCase__ , UpperCAmelCase__ ) or not all(isinstance(UpperCAmelCase__ , UpperCAmelCase__ ) for day in days ):...
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from collections import OrderedDict from typing import Mapping from ...configuration_utils import PretrainedConfig from ...onnx import OnnxConfig from ...utils import logging _lowerCamelCase : str = logging.get_logger(__name__) _lowerCamelCase : Dict = { '''junnyu/roformer_c...
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from __future__ import annotations import math def __lowerCamelCase (UpperCAmelCase__ : int ): if 1 < number < 4: # 2 and 3 are primes return True elif number < 2 or number % 2 == 0 or number % 3 == 0: # Negatives, 0, 1, all even numbers, al...
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from dataclasses import dataclass from typing import Tuple import numpy as np import torch @dataclass class lowercase : lowercase__ : torch.Tensor # [batch_size x 3] lowercase__ : torch.Tensor # [batch_size x 3] lowercase__ : torch.Tensor #...
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import unittest import numpy as np from transformers.file_utils import is_torch_available, is_vision_available from transformers.testing_utils import require_torch, require_vision from ...test_image_processing_common import ImageProcessingSavingTestMixin, prepare_image_inputs if is_torch_available(): ...
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import os from collections import deque import torch from torch.utils.data import Dataset class lowercase ( a ): def __init__( self : Any , _UpperCamelCase : Any="" , _UpperCamelCase : str="train" ) -> Optional[int]: ...
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import argparse import json import requests import torch from huggingface_hub import hf_hub_download from PIL import Image from transformers import ViTImageProcessor, ViTMSNConfig, ViTMSNModel from transformers.image_utils import IMAGENET_DEFAULT_MEAN, IMAGENET_DEFAULT_STD torch.set_grad_enabled(False) ...
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import unittest import numpy as np from transformers.file_utils import is_torch_available, is_vision_available from transformers.testing_utils import require_torch, require_vision from ...test_image_processing_common import ImageProcessingSavingTestMixin, prepare_image_inputs if is_torch_available(): ...
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import collections import os from shutil import copyfile from typing import Any, Dict, List, Optional, Tuple from ...tokenization_utils import PreTrainedTokenizer from ...utils import logging _lowerCamelCase : Dict = logging.get_logger(__name__) _lowerCamelCase : List[Any] = '''...
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import json from typing import List, Optional, Tuple from tokenizers import normalizers from ...tokenization_utils_fast import PreTrainedTokenizerFast from ...utils import logging from .tokenization_funnel import FunnelTokenizer _lowerCamelCase : Any = logging.get_logger(__name__) _lowerCa...
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import numpy as np def __lowerCamelCase (UpperCAmelCase__ : np.ndarray , UpperCAmelCase__ : np.ndarray , UpperCAmelCase__ : float = 1e-12 , UpperCAmelCase__ : int = 1_0_0 , ): assert np.shape(UpperCAmelCase__ )[0] == np.shape(UpperCAme...
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from dataclasses import dataclass from typing import List, Optional, Union import numpy as np import PIL from ...utils import BaseOutput, OptionalDependencyNotAvailable, is_torch_available, is_transformers_available from .timesteps import ( fastaa_timesteps, smartaa_timesteps, smartaa_timesteps,...
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import copy from typing import Any, Dict, List, Optional, Union import numpy as np import torch from ...audio_utils import mel_filter_bank, spectrogram, window_function from ...feature_extraction_sequence_utils import SequenceFeatureExtractor from ...feature_extraction_utils import BatchFeature from ...utils...
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# Copyright 2023 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 a...
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import argparse import logging from collections import namedtuple import torch from model_bertabs import BertAbsSummarizer from models.model_builder import AbsSummarizer # The authors' implementation from transformers import BertTokenizer logging.basicConfig(level=logging.INFO) _lowerCamelCase : ...
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import os import tempfile import unittest from pathlib import Path from transformers import AutoConfig, is_torch_available from transformers.testing_utils import require_torch, torch_device if is_torch_available(): from transformers import PyTorchBenchmark, PyTorchBenchmarkArguments @require_to...
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def __lowerCamelCase (UpperCAmelCase__ : int ): assert isinstance(UpperCAmelCase__ , UpperCAmelCase__ ), F"The input value of [n={number}] is not an integer" if number == 1: return 2 elif number < 1: SCREAMING_SNAKE_CASE = F"The input value o...
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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 require_elasticsear...
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import inspect import os import unittest import torch import accelerate from accelerate import Accelerator from accelerate.test_utils import execute_subprocess_async, require_multi_gpu from accelerate.utils import patch_environment class lowercase ( unittest.TestCase ): ...
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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_dimension_forma...
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import torch from diffusers import KDPMaDiscreteScheduler from diffusers.utils import torch_device from .test_schedulers import SchedulerCommonTest class lowercase ( a ): lowercase__ : Tuple = (KDPMaDiscreteScheduler,) lowercase__ : Optiona...
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import argparse import json from pathlib import Path import requests import torch from huggingface_hub import hf_hub_download from PIL import Image from transformers import BeitConfig, BeitForImageClassification, BeitForMaskedImageModeling, BeitImageProcessor from transformers.image_utils import PILImageRes...
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from __future__ import annotations from typing import Dict from ...configuration_utils import PretrainedConfig _lowerCamelCase : Tuple = { '''susnato/ernie-m-base_pytorch''': '''https://huggingface.co/susnato/ernie-m-base_pytorch/blob/main/config.json''', '''susnato/ernie-m-large_pytor...
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import argparse import logging from collections import namedtuple import torch from model_bertabs import BertAbsSummarizer from models.model_builder import AbsSummarizer # The authors' implementation from transformers import BertTokenizer logging.basicConfig(level=logging.INFO) _lowerCamelCase : ...
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from typing import TYPE_CHECKING from ...utils import ( OptionalDependencyNotAvailable, _LazyModule, is_flax_available, is_tf_available, is_tokenizers_available, is_torch_available, ) _lowerCamelCase : Optional[int] = { '''configuration_blenderbot''': [ ...
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def __lowerCamelCase (UpperCAmelCase__ : int = 1_0 , UpperCAmelCase__ : int = 2_2 ): SCREAMING_SNAKE_CASE = range(1 , UpperCAmelCase__ ) SCREAMING_SNAKE_CASE = range(1 , UpperCAmelCase__ ) return sum( 1 for power in powers ...
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from __future__ import annotations from collections.abc import Iterator from typing import Generic, TypeVar _lowerCamelCase : Optional[Any] = TypeVar('''T''') class lowercase ( Generic[T] ): def __init__( self : Any , _UpperCamelCase : T ...
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from typing import TYPE_CHECKING from ...utils import ( OptionalDependencyNotAvailable, _LazyModule, is_flax_available, is_tf_available, is_torch_available, ) _lowerCamelCase : Union[str, Any] = { '''configuration_vision_encoder_decoder''': ['''VisionEncoderDecoderCon...
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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 a...
647
1
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, prepare_image_inputs ...
647
def __lowerCamelCase (UpperCAmelCase__ : list[int] ): if not numbers: return 0 if not isinstance(UpperCAmelCase__ , (list, tuple) ) or not all( isinstance(UpperCAmelCase__ , UpperCAmelCase__ ) for number in numbers ): raise ValueError("numbers...
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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 a...
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import functools import logging import os import sys import threading from logging import ( CRITICAL, # NOQA DEBUG, # NOQA ERROR, # NOQA FATAL, # NOQA INFO, # NOQA NOTSET, # NOQA WARN, # NOQA WARNING, # NOQA ) from typing import Optional import huggingface_hub.u...
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import darl # noqa import gym import tqdm from diffusers.experimental import ValueGuidedRLPipeline _lowerCamelCase : Union[str, Any] = { '''n_samples''': 64, '''horizon''': 32, '''num_inference_steps''': 20, '''n_guide_steps''': 2, # can set to 0 for faster sampling, does not ...
647
import os import tempfile import unittest from transformers.models.marian.convert_marian_tatoeba_to_pytorch import DEFAULT_REPO, TatoebaConverter from transformers.testing_utils import slow from transformers.utils import cached_property @unittest.skipUnless(os.path.exists(a ) , """Tatoeba direc...
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import argparse import json import os import evaluate import torch from datasets import load_dataset from torch.optim import AdamW from torch.utils.data import DataLoader from transformers import AutoModelForSequenceClassification, AutoTokenizer, get_linear_schedule_with_warmup, set_seed from accelerate im...
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import inspect import unittest from transformers import ViTHybridConfig from transformers.testing_utils import require_accelerate, require_torch, require_vision, slow, torch_device from transformers.utils import cached_property, is_torch_available, is_vision_available from ...test_configuration_common import C...
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def __lowerCamelCase (UpperCAmelCase__ : list[int] ): if not numbers: return 0 if not isinstance(UpperCAmelCase__ , (list, tuple) ) or not all( isinstance(UpperCAmelCase__ , UpperCAmelCase__ ) for number in numbers ): raise ValueError("numbers...
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from typing import Dict, Optional, Union import numpy as np from ...image_processing_utils import BaseImageProcessor, BatchFeature, get_size_dict from ...image_transforms import flip_channel_order, resize, to_channel_dimension_format, to_pil_image from ...image_utils import ( ChannelDimension, ImageIn...
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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 a...
647
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, prepare_image_inputs ...
647
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from typing import TYPE_CHECKING from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available _lowerCamelCase : List[str] = { '''configuration_xlm_roberta_xl''': [ '''XLM_ROBERTA_XL_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''XLMRobertaXLConfig''', '...
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from typing import Dict, List, Optional, Union import numpy as np from .feature_extraction_utils import BatchFeature, FeatureExtractionMixin from .utils import PaddingStrategy, TensorType, is_tf_tensor, is_torch_tensor, logging, to_numpy _lowerCamelCase : Optional[Any] = logging.get_logger(__na...
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1
import json import os import re import shutil import tempfile import unittest from typing import Tuple from transformers import AddedToken, BatchEncoding, ByTaTokenizer from transformers.utils import cached_property, is_tf_available, is_torch_available from ...test_tokenization_common import TokenizerTeste...
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import functools def __lowerCamelCase (UpperCAmelCase__ : list[int] , UpperCAmelCase__ : list[int] ): # Validation if not isinstance(UpperCAmelCase__ , UpperCAmelCase__ ) or not all(isinstance(UpperCAmelCase__ , UpperCAmelCase__ ) for day in days ):...
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import unittest import numpy as np from diffusers import LMSDiscreteScheduler, OnnxStableDiffusionInpaintPipeline from diffusers.utils.testing_utils import ( is_onnx_available, load_image, nightly, require_onnxruntime, require_torch_gpu, ) from ..test_pipelines_onnx_common import Onn...
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from __future__ import annotations import math def __lowerCamelCase (UpperCAmelCase__ : int ): if 1 < number < 4: # 2 and 3 are primes return True elif number < 2 or number % 2 == 0 or number % 3 == 0: # Negatives, 0, 1, all even numbers, al...
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1
import warnings from pathlib import Path from typing import List, Tuple, Union import fire from torch import nn from transformers import AutoModelForSeqaSeqLM, AutoTokenizer, PreTrainedModel from transformers.utils import logging _lowerCamelCase : Optional[Any] = logging.get_logger(__name__)...
647
import unittest import numpy as np from transformers.file_utils import is_torch_available, is_vision_available from transformers.testing_utils import require_torch, require_vision from ...test_image_processing_common import ImageProcessingSavingTestMixin, prepare_image_inputs if is_torch_available(): ...
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import os from pathlib import Path import numpy as np import pytest from pack_dataset import pack_data_dir from parameterized import parameterized from save_len_file import save_len_file from torch.utils.data import DataLoader from transformers import AutoTokenizer from transformers.models.mbart.modeling_m...
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import argparse import json import requests import torch from huggingface_hub import hf_hub_download from PIL import Image from transformers import ViTImageProcessor, ViTMSNConfig, ViTMSNModel from transformers.image_utils import IMAGENET_DEFAULT_MEAN, IMAGENET_DEFAULT_STD torch.set_grad_enabled(False) ...
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import sacrebleu as scb from packaging import version from sacrebleu import CHRF import datasets _lowerCamelCase : Tuple = '''\ @inproceedings{popovic-2015-chrf, title = "chr{F}: character n-gram {F}-score for automatic {MT} evaluation", author = "Popovi{\'c}, Maja", booktitle = "Proc...
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import collections import os from shutil import copyfile from typing import Any, Dict, List, Optional, Tuple from ...tokenization_utils import PreTrainedTokenizer from ...utils import logging _lowerCamelCase : Dict = logging.get_logger(__name__) _lowerCamelCase : List[Any] = '''...
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from multiprocessing import Lock, Pipe, Process # lock used to ensure that two processes do not access a pipe at the same time _lowerCamelCase : List[Any] = Lock() def __lowerCamelCase (UpperCAmelCase__ : List[Any] , UpperCAmelCase__ : List[Any] , UpperCA...
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import numpy as np def __lowerCamelCase (UpperCAmelCase__ : np.ndarray , UpperCAmelCase__ : np.ndarray , UpperCAmelCase__ : float = 1e-12 , UpperCAmelCase__ : int = 1_0_0 , ): assert np.shape(UpperCAmelCase__ )[0] == np.shape(UpperCAme...
647
1
from __future__ import annotations import unittest from transformers import MobileBertConfig, is_tf_available from transformers.models.auto import get_values from transformers.testing_utils import require_tf, slow from ...test_configuration_common import ConfigTester from ...test_modeling_tf_common import T...
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import copy from typing import Any, Dict, List, Optional, Union import numpy as np import torch from ...audio_utils import mel_filter_bank, spectrogram, window_function from ...feature_extraction_sequence_utils import SequenceFeatureExtractor from ...feature_extraction_utils import BatchFeature from ...utils...
647
1
import unittest from transformers import RoFormerTokenizer, RoFormerTokenizerFast from transformers.testing_utils import require_rjieba, require_tokenizers from ...test_tokenization_common import TokenizerTesterMixin @require_rjieba @require_tokenizers class lowercase ( a , unittest....
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import argparse import logging from collections import namedtuple import torch from model_bertabs import BertAbsSummarizer from models.model_builder import AbsSummarizer # The authors' implementation from transformers import BertTokenizer logging.basicConfig(level=logging.INFO) _lowerCamelCase : ...
647
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import unittest from knapsack import greedy_knapsack as kp class lowercase ( unittest.TestCase ): def __snake_case( self : List[str] ) -> Union[str, Any]: '''simple docstring''' SCREAMING_SNAKE_CASE = [10, 20,...
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def __lowerCamelCase (UpperCAmelCase__ : int ): assert isinstance(UpperCAmelCase__ , UpperCAmelCase__ ), F"The input value of [n={number}] is not an integer" if number == 1: return 2 elif number < 1: SCREAMING_SNAKE_CASE = F"The input value o...
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1
from typing import List, Optional, Union import numpy as np from ...feature_extraction_sequence_utils import SequenceFeatureExtractor from ...feature_extraction_utils import BatchFeature from ...utils import PaddingStrategy, TensorType, logging _lowerCamelCase : Union[str, Any] = logging.get_l...
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import inspect import os import unittest import torch import accelerate from accelerate import Accelerator from accelerate.test_utils import execute_subprocess_async, require_multi_gpu from accelerate.utils import patch_environment class lowercase ( unittest.TestCase ): ...
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import unittest from transformers import is_flax_available from transformers.testing_utils import require_flax, require_sentencepiece, require_tokenizers, require_torch, slow if is_flax_available(): import optax from flax.training.common_utils import onehot from transformers import Au...
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import torch from diffusers import KDPMaDiscreteScheduler from diffusers.utils import torch_device from .test_schedulers import SchedulerCommonTest class lowercase ( a ): lowercase__ : Tuple = (KDPMaDiscreteScheduler,) lowercase__ : Optiona...
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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, prepare_image_inputs ...
647
from __future__ import annotations from typing import Dict from ...configuration_utils import PretrainedConfig _lowerCamelCase : Tuple = { '''susnato/ernie-m-base_pytorch''': '''https://huggingface.co/susnato/ernie-m-base_pytorch/blob/main/config.json''', '''susnato/ernie-m-large_pytor...
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import copy from dataclasses import dataclass from pathlib import Path from typing import Dict, Optional, Union @dataclass class lowercase : lowercase__ : Optional[Union[str, Path]] = None lowercase__ : bool = False lowercase__ ...
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from typing import TYPE_CHECKING from ...utils import ( OptionalDependencyNotAvailable, _LazyModule, is_flax_available, is_tf_available, is_tokenizers_available, is_torch_available, ) _lowerCamelCase : Optional[int] = { '''configuration_blenderbot''': [ ...
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import copy from dataclasses import dataclass, field from typing import ClassVar, Dict from ..features import ClassLabel, Features, Value from .base import TaskTemplate @dataclass(frozen=a ) class lowercase ( a ): # `task` is not a ClassVar since we want it to be part of the `as...
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from __future__ import annotations from collections.abc import Iterator from typing import Generic, TypeVar _lowerCamelCase : Optional[Any] = TypeVar('''T''') class lowercase ( Generic[T] ): def __init__( self : Any , _UpperCamelCase : T ...
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import argparse import json import requests import torch from huggingface_hub import hf_hub_download from PIL import Image from transformers import ViTImageProcessor, ViTMSNConfig, ViTMSNModel from transformers.image_utils import IMAGENET_DEFAULT_MEAN, IMAGENET_DEFAULT_STD torch.set_grad_enabled(False) ...
647
# 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 a...
647
1
import unittest from transformers import ( MODEL_FOR_SEQUENCE_CLASSIFICATION_MAPPING, TF_MODEL_FOR_SEQUENCE_CLASSIFICATION_MAPPING, Pipeline, ZeroShotClassificationPipeline, pipeline, ) from transformers.testing_utils import is_pipeline_test, nested_simplify, require_tf, require_torch, slo...
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def __lowerCamelCase (UpperCAmelCase__ : list[int] ): if not numbers: return 0 if not isinstance(UpperCAmelCase__ , (list, tuple) ) or not all( isinstance(UpperCAmelCase__ , UpperCAmelCase__ ) for number in numbers ): raise ValueError("numbers...
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from dataclasses import dataclass, field from typing import Optional @dataclass class lowercase : lowercase__ : Optional[str] = field( default="""codeparrot/codeparrot""" , metadata={"""help""": """Model name or path of model to be trained."""} ) ...
647
import functools import logging import os import sys import threading from logging import ( CRITICAL, # NOQA DEBUG, # NOQA ERROR, # NOQA FATAL, # NOQA INFO, # NOQA NOTSET, # NOQA WARN, # NOQA WARNING, # NOQA ) from typing import Optional import huggingface_hub.u...
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import unittest import numpy as np import torch from diffusers import VersatileDiffusionImageVariationPipeline from diffusers.utils.testing_utils import load_image, require_torch_gpu, slow, torch_device _lowerCamelCase : Union[str, Any] = False class lowercase ( unittest.Test...
647
import os import tempfile import unittest from transformers.models.marian.convert_marian_tatoeba_to_pytorch import DEFAULT_REPO, TatoebaConverter from transformers.testing_utils import slow from transformers.utils import cached_property @unittest.skipUnless(os.path.exists(a ) , """Tatoeba direc...
647
1
import unittest import numpy as np from transformers.testing_utils import require_torch, require_vision from transformers.utils import is_torch_available, is_vision_available from ...test_image_processing_common import ImageProcessingSavingTestMixin, prepare_image_inputs if is_torch_available(): ...
647
import inspect import unittest from transformers import ViTHybridConfig from transformers.testing_utils import require_accelerate, require_torch, require_vision, slow, torch_device from transformers.utils import cached_property, is_torch_available, is_vision_available from ...test_configuration_common import C...
647
1
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_video_inputs if is_torch_available(): ...
647
from typing import Dict, Optional, Union import numpy as np from ...image_processing_utils import BaseImageProcessor, BatchFeature, get_size_dict from ...image_transforms import flip_channel_order, resize, to_channel_dimension_format, to_pil_image from ...image_utils import ( ChannelDimension, ImageIn...
647
1
from typing import Dict, List, Optional, Union import numpy as np from .feature_extraction_utils import BatchFeature, FeatureExtractionMixin from .utils import PaddingStrategy, TensorType, is_tf_tensor, is_torch_tensor, logging, to_numpy _lowerCamelCase : Optional[Any] = logging.get_logger(__na...
647
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, prepare_image_inputs ...
647
1
import unittest from transformers import is_torch_available from transformers.testing_utils import require_torch, slow, torch_device from ...generation.test_utils import GenerationTesterMixin from ...test_configuration_common import ConfigTester from ...test_modeling_common import ModelTesterMixin, ids_tensor ...
647
from typing import Dict, List, Optional, Union import numpy as np from .feature_extraction_utils import BatchFeature, FeatureExtractionMixin from .utils import PaddingStrategy, TensorType, is_tf_tensor, is_torch_tensor, logging, to_numpy _lowerCamelCase : Optional[Any] = logging.get_logger(__na...
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1
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 __lowerCamelCase...
647
import functools def __lowerCamelCase (UpperCAmelCase__ : list[int] , UpperCAmelCase__ : list[int] ): # Validation if not isinstance(UpperCAmelCase__ , UpperCAmelCase__ ) or not all(isinstance(UpperCAmelCase__ , UpperCAmelCase__ ) for day in days ):...
647
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def __lowerCamelCase (UpperCAmelCase__ : Dict , UpperCAmelCase__ : str ): # "extended trapezoidal rule" # int(f) = dx/2 * (f1 + 2f2 + ... + fn) SCREAMING_SNAKE_CASE = (boundary[1] - boundary[0]) / steps SCREAMING_SNAKE_CASE = boundary[0] ...
647
from __future__ import annotations import math def __lowerCamelCase (UpperCAmelCase__ : int ): if 1 < number < 4: # 2 and 3 are primes return True elif number < 2 or number % 2 == 0 or number % 3 == 0: # Negatives, 0, 1, all even numbers, al...
647
1
import argparse import torch from transformers import MobileBertConfig, MobileBertForPreTraining, load_tf_weights_in_mobilebert from transformers.utils import logging logging.set_verbosity_info() def __lowerCamelCase (UpperCAmelCase__ : Optional[int] , UpperCAmelCase__ :...
647
import unittest import numpy as np from transformers.file_utils import is_torch_available, is_vision_available from transformers.testing_utils import require_torch, require_vision from ...test_image_processing_common import ImageProcessingSavingTestMixin, prepare_image_inputs if is_torch_available(): ...
647
1
def __lowerCamelCase (UpperCAmelCase__ : int = 1_0 , UpperCAmelCase__ : int = 1_0_0_0 , UpperCAmelCase__ : bool = True ): assert ( isinstance(UpperCAmelCase__ , UpperCAmelCase__ ) and isinstance(UpperCAmelCase__ , UpperCAmelCase__ ) ...
647
import argparse import json import requests import torch from huggingface_hub import hf_hub_download from PIL import Image from transformers import ViTImageProcessor, ViTMSNConfig, ViTMSNModel from transformers.image_utils import IMAGENET_DEFAULT_MEAN, IMAGENET_DEFAULT_STD torch.set_grad_enabled(False) ...
647
1
from collections import defaultdict class lowercase : def __init__( self : Optional[int] , _UpperCamelCase : Optional[int] , _UpperCamelCase : Any ) -> Optional[int]: '''simple docstring''' SCREAMING_SNAKE_CAS...
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import collections import os from shutil import copyfile from typing import Any, Dict, List, Optional, Tuple from ...tokenization_utils import PreTrainedTokenizer from ...utils import logging _lowerCamelCase : Dict = logging.get_logger(__name__) _lowerCamelCase : List[Any] = '''...
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1