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from math import factorial, radians def lowerCAmelCase__ ( lowerCamelCase_ : float ,lowerCamelCase_ : int = 18 ,lowerCamelCase_ : int = 10): '''simple docstring''' lowerCAmelCase__ : int = angle_in_degrees - ((angle_in_degrees // 360.0)...
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from typing import Optional import pyspark from .. import Features, NamedSplit from ..download import DownloadMode from ..packaged_modules.spark.spark import Spark from .abc import AbstractDatasetReader class lowerCamelCase__ ( lowerCamelCase__): '''simple docstring''' def __init__(self ...
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def lowerCAmelCase__ ( lowerCamelCase_ : int = 1000000): '''simple docstring''' lowerCAmelCase__ : List[Any] = set(range(3 ,lowerCamelCase_ ,2)) primes.add(2) for p in range(3 ,lowerCamelCase_ ,2): if p not in primes: continue ...
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import os import jsonlines import numpy as np from tqdm import tqdm __snake_case : List[str] =2_0_4_8 __snake_case : List[Any] =4_0_9_6 __snake_case : Tuple =4_2 __snake_case : List[Any] =os.environ.pop('PROCESS_TRAIN', 'false') __snake_case :...
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import shutil import tempfile import unittest import numpy as np import pytest from transformers.testing_utils import require_vision from transformers.utils import is_vision_available if is_vision_available(): from PIL import Image from transformers import ( AutoProcessor, B...
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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 enable_ful...
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from arguments import InitializationArguments from transformers import AutoConfig, AutoModelForCausalLM, AutoTokenizer, HfArgumentParser # Configuration __snake_case : Any =HfArgumentParser(InitializationArguments) __snake_case : Any =parser.parse_args() # Load codeparrot tokeniz...
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from __future__ import absolute_import, division, print_function, unicode_literals from torch import nn from torch.nn import CrossEntropyLoss, MSELoss from transformers import RobertaConfig from transformers.file_utils import add_start_docstrings, add_start_docstrings_to_model_forward from transformers.models.rob...
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from ...configuration_utils import PretrainedConfig from ...utils import logging from ...utils.backbone_utils import BackboneConfigMixin, get_aligned_output_features_output_indices __snake_case : Tuple =logging.get_logger(__name__) __snake_case : Tuple ={ 'shi-labs/nat-mini-in...
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__snake_case : str ='\n# Transformers installation\n! pip install transformers datasets\n# To install from source instead of the last release, comment the command above and uncomment the following one.\n# ! pip install git+https://github.com/huggingface/transformers.git\n' __snake_case : ...
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import os import unittest from tempfile import TemporaryDirectory import torch import torch.nn as nn from accelerate.utils import ( OffloadedWeightsLoader, extract_submodules_state_dict, load_offloaded_weight, offload_state_dict, offload_weight, ) class lowerCamelCase__ ( nn.Modul...
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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) de...
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import warnings 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 __snake_case : Optional[int] =logging.get_logger(__name__) __snake_case ...
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import requests __snake_case : Optional[int] ='YOUR API KEY' def lowerCAmelCase__ ( lowerCamelCase_ : str ,lowerCamelCase_ : str = giphy_api_key): '''simple docstring''' lowerCAmelCase__ : Tuple = '''+'''.join(query.split()) lo...
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def lowerCAmelCase__ ( lowerCamelCase_ : int): '''simple docstring''' if upper_limit < 0: raise ValueError('''Limit for the Catalan sequence must be ≥ 0''') lowerCAmelCase__ : Optional[int] = [0] * (upper_limit + 1) # Base case: C(0) = C(1) = 1 ...
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from collections.abc import Callable class lowerCamelCase__ : '''simple docstring''' def __init__(self ,__lowerCamelCase = None ) -> None: """simple docstring""" lowerCAmelCase__ : list = [] # Stores indexes of each item for supporting updates and ...
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def lowerCAmelCase__ ( lowerCamelCase_ : int): '''simple docstring''' if isinstance(lowerCamelCase_ ,lowerCamelCase_): raise TypeError('''\'float\' object cannot be interpreted as an integer''') if isinstance(lowerCamelCase_ ,lowerCamelCase_): raise T...
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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 AutoToke...
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import json import os import subprocess import unittest from ast import literal_eval import pytest from parameterized import parameterized_class from . import is_sagemaker_available if is_sagemaker_available(): from sagemaker import Session, TrainingJobAnalytics from sagemaker.huggingface import H...
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import torch from diffusers import KDPMaDiscreteScheduler from diffusers.utils import torch_device from .test_schedulers import SchedulerCommonTest class lowerCamelCase__ ( lowerCamelCase__): '''simple docstring''' snake_case_ =(KDPMaDiscreteScheduler,) snake_case_ =10 def...
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import inspect import unittest from datasets import load_dataset from packaging import version from transformers import BeitConfig from transformers.models.auto import get_values from transformers.testing_utils import require_torch, require_torch_multi_gpu, require_vision, slow, torch_device from transformers.uti...
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import inspect import os import sys import unittest import accelerate from accelerate.test_utils import execute_subprocess_async, require_tpu class lowerCamelCase__ ( unittest.TestCase): '''simple docstring''' def lowerCAmelCase__ (self ) -> str: """simple docstring""" ...
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from typing import TYPE_CHECKING from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tokenizers_available, is_torch_available __snake_case : Tuple ={ 'configuration_mvp': ['MVP_PRETRAINED_CONFIG_ARCHIVE_MAP', 'MvpConfig', 'MvpOnnxConfig'], 'tokenization_mvp': ['MvpTokeniz...
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import os import unittest from transformers.models.bartpho.tokenization_bartpho import VOCAB_FILES_NAMES, BartphoTokenizer from transformers.testing_utils import get_tests_dir from ...test_tokenization_common import TokenizerTesterMixin __snake_case : List[Any] =get_tests_dir('fixtures/test_sent...
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def lowerCAmelCase__ ( lowerCamelCase_ : int ,lowerCamelCase_ : int): '''simple docstring''' return number | (1 << position) def lowerCAmelCase__ ( lowerCamelCase_ : int ,lowerCamelCase_ : int): '''simple docs...
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import math import unittest def lowerCAmelCase__ ( lowerCamelCase_ : int): '''simple docstring''' assert isinstance(lowerCamelCase_ ,lowerCamelCase_) and ( number >= 0 ), "'number' must been an int and positive" if 1 < number < 4: # 2 and 3 a...
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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 __snake_case : Union[str, Any] =logging.get_logger(__name__) __snake_case : Optiona...
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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 import get_logg...
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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 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(): import ...
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import math import time from typing import Dict, List, Optional from torch.utils.data import Dataset from transformers import SeqaSeqTrainer, is_torch_tpu_available from transformers.trainer_utils import PredictionOutput, speed_metrics if is_torch_tpu_available(check_device=False): import torch_xla.core....
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def lowerCAmelCase__ ( lowerCamelCase_ : Dict): '''simple docstring''' lowerCAmelCase__ : Optional[Any] = len(lowerCamelCase_) while cur > 1: # Find the maximum number in arr lowerCAmelCase__ : Tuple = arr.index(max(arr[0:cur])) ...
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import argparse import os import re __snake_case : Optional[int] ='src/diffusers' # Pattern that looks at the indentation in a line. __snake_case : str =re.compile(R'^(\s*)\S') # Pattern that matches `"key":" and puts `key` in group 0. __snake_case : str =re.compil...
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import logging import os import sys from dataclasses import dataclass, field from importlib import import_module from typing import Dict, List, Optional, Tuple import numpy as np from seqeval.metrics import accuracy_score, fa_score, precision_score, recall_score from torch import nn from utils_ner import Split, To...
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import os import time import pytest from datasets.utils.filelock import FileLock, Timeout def lowerCAmelCase__ ( lowerCamelCase_ : Optional[Any]): '''simple docstring''' lowerCAmelCase__ : Tuple = FileLock(str(tmpdir / '''foo.lock''')) lowerCAmelCase__ :...
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from typing import TYPE_CHECKING from ...utils import ( OptionalDependencyNotAvailable, _LazyModule, is_torch_available, ) __snake_case : int ={ 'configuration_gpt_bigcode': ['GPT_BIGCODE_PRETRAINED_CONFIG_ARCHIVE_MAP', 'GPTBigCodeConfig'], } try: if not is_torch_available...
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from typing import Optional import pyspark from .. import Features, NamedSplit from ..download import DownloadMode from ..packaged_modules.spark.spark import Spark from .abc import AbstractDatasetReader class lowerCamelCase__ ( lowerCamelCase__): '''simple docstring''' def __init__(self ...
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import copy from dataclasses import dataclass from pathlib import Path from typing import Dict, Optional, Union @dataclass class lowerCamelCase__ : '''simple docstring''' snake_case_ =None snake_case_ =False snake_case_ =False snake_case_ =False snake_case_ =Non...
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import numpy as np import skfuzzy as fuzz if __name__ == "__main__": # Create universe of discourse in Python using linspace () __snake_case : Tuple =np.linspace(start=0, stop=7_5, num=7_5, endpoint=True, retstep=False) # Create two fuzzy sets by defining any membership functi...
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def lowerCAmelCase__ ( lowerCamelCase_ : Dict ,lowerCamelCase_ : Optional[int]): '''simple docstring''' lowerCAmelCase__ : int = (boundary[1] - boundary[0]) / steps lowerCAmelCase__ : Optional[int] = boundary[0] lowerCAmelCase__ : ...
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from typing import TYPE_CHECKING from ...utils import ( OptionalDependencyNotAvailable, _LazyModule, is_sentencepiece_available, is_torch_available, ) __snake_case : Union[str, Any] ={ 'configuration_speecht5': [ 'SPEECHT5_PRETRAINED_CONFIG_ARCHIVE_MAP', 'SPEEC...
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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 TFMode...
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import math import unittest def lowerCAmelCase__ ( lowerCamelCase_ : int): '''simple docstring''' assert isinstance(lowerCamelCase_ ,lowerCamelCase_) and ( number >= 0 ), "'number' must been an int and positive" if 1 < number < 4: # 2 and 3 a...
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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 GenerationTesterMixin from ...test_con...
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from ...configuration_utils import PretrainedConfig from ...utils import logging __snake_case : Optional[int] =logging.get_logger(__name__) __snake_case : List[Any] ={ 'facebook/s2t-wav2vec2-large-en-de': ( 'https://huggingface.co/facebook/s2t-wav2vec2-large-en-de/reso...
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from typing import Optional import pyspark from .. import Features, NamedSplit from ..download import DownloadMode from ..packaged_modules.spark.spark import Spark from .abc import AbstractDatasetReader class lowerCamelCase__ ( lowerCamelCase__): '''simple docstring''' def __init__(self ...
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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 ...
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import os import jsonlines import numpy as np from tqdm import tqdm __snake_case : List[str] =2_0_4_8 __snake_case : List[Any] =4_0_9_6 __snake_case : Tuple =4_2 __snake_case : List[Any] =os.environ.pop('PROCESS_TRAIN', 'false') __snake_case :...
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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 lowerCamelCase__ ( unittest.TestCase): ''...
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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 enable_ful...
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import numpy as np from PIL import Image def lowerCAmelCase__ ( lowerCamelCase_ : np.ndarray ,lowerCamelCase_ : int ,lowerCamelCase_ : int): '''simple docstring''' lowerCAmelCase__ : List[str] = np.array(lowerCamelCase_) if arr.shap...
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from __future__ import absolute_import, division, print_function, unicode_literals from torch import nn from torch.nn import CrossEntropyLoss, MSELoss from transformers import RobertaConfig from transformers.file_utils import add_start_docstrings, add_start_docstrings_to_model_forward from transformers.models.rob...
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import itertools import math def lowerCAmelCase__ ( lowerCamelCase_ : int): '''simple docstring''' 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...
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__snake_case : str ='\n# Transformers installation\n! pip install transformers datasets\n# To install from source instead of the last release, comment the command above and uncomment the following one.\n# ! pip install git+https://github.com/huggingface/transformers.git\n' __snake_case : ...
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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 import get_logg...
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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) de...
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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 __snake_case : List[Any] =False try: __snake_case ...
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import requests __snake_case : Optional[int] ='YOUR API KEY' def lowerCAmelCase__ ( lowerCamelCase_ : str ,lowerCamelCase_ : str = giphy_api_key): '''simple docstring''' lowerCAmelCase__ : Tuple = '''+'''.join(query.split()) lo...
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from ...configuration_utils import PretrainedConfig from ...utils import logging __snake_case : Union[str, Any] =logging.get_logger(__name__) __snake_case : Dict ={ 'facebook/s2t-small-librispeech-asr': ( 'https://huggingface.co/facebook/s2t-small-librispeech-asr/resol...
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from collections.abc import Callable class lowerCamelCase__ : '''simple docstring''' def __init__(self ,__lowerCamelCase = None ) -> None: """simple docstring""" lowerCAmelCase__ : list = [] # Stores indexes of each item for supporting updates and ...
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def lowerCAmelCase__ ( lowerCamelCase_ : str ,lowerCamelCase_ : str): '''simple docstring''' assert x is not None assert y is not None lowerCAmelCase__ : Tuple = len(lowerCamelCase_) lowerCAmelCase__ : List[Any] = len(lowerCamelCase...
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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 AutoToke...
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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(lowerCamelCase__) , """Tatoeba di...
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import torch from diffusers import KDPMaDiscreteScheduler from diffusers.utils import torch_device from .test_schedulers import SchedulerCommonTest class lowerCamelCase__ ( lowerCamelCase__): '''simple docstring''' snake_case_ =(KDPMaDiscreteScheduler,) snake_case_ =10 def...
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from argparse import ArgumentParser from . import BaseTransformersCLICommand def lowerCAmelCase__ ( lowerCamelCase_ : Dict): '''simple docstring''' return DownloadCommand(args.model ,args.cache_dir ,args.force ,args.trust_remote_code) class lowerCamelCase_...
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import inspect import os import sys import unittest import accelerate from accelerate.test_utils import execute_subprocess_async, require_tpu class lowerCamelCase__ ( unittest.TestCase): '''simple docstring''' def lowerCAmelCase__ (self ) -> str: """simple docstring""" ...
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import os import zipfile import requests from get_ci_error_statistics import download_artifact, get_artifacts_links def lowerCAmelCase__ ( lowerCamelCase_ : List[str] ,lowerCamelCase_ : List[Any]=7): '''simple docstring''' lowerCAmelCase__ : Any =...
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import os import unittest from transformers.models.bartpho.tokenization_bartpho import VOCAB_FILES_NAMES, BartphoTokenizer from transformers.testing_utils import get_tests_dir from ...test_tokenization_common import TokenizerTesterMixin __snake_case : List[Any] =get_tests_dir('fixtures/test_sent...
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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 __snake_case : ...
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import math import unittest def lowerCAmelCase__ ( lowerCamelCase_ : int): '''simple docstring''' assert isinstance(lowerCamelCase_ ,lowerCamelCase_) and ( number >= 0 ), "'number' must been an int and positive" if 1 < number < 4: # 2 and 3 a...
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def lowerCAmelCase__ ( lowerCamelCase_ : Optional[Any]): '''simple docstring''' lowerCAmelCase__ : Optional[Any] = 0 lowerCAmelCase__ : Tuple = len(lowerCamelCase_) for i in range(n - 1): for j in range(i + 1 ,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 import get_logg...
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from ...configuration_utils import PretrainedConfig from ...utils import logging __snake_case : Optional[int] =logging.get_logger(__name__) __snake_case : List[Any] ={ 'alibaba-damo/mgp-str-base': 'https://huggingface.co/alibaba-damo/mgp-str-base/resolve/main/config.json', } ...
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import unittest import numpy as np from transformers.testing_utils import require_torch, require_vision from transformers.utils import is_torch_available, is_vision_available from ...test_image_processing_common import ImageProcessingSavingTestMixin, prepare_video_inputs if is_torch_available(): import ...
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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 enable_ful...
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def lowerCAmelCase__ ( lowerCamelCase_ : Dict): '''simple docstring''' lowerCAmelCase__ : Optional[Any] = len(lowerCamelCase_) while cur > 1: # Find the maximum number in arr lowerCAmelCase__ : Tuple = arr.index(max(arr[0:cur])) ...
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class lowerCamelCase__ ( lowerCamelCase__): '''simple docstring''' pass class lowerCamelCase__ ( lowerCamelCase__): '''simple docstring''' pass class lowerCamelCase__ : '''simple docstring''' def __init__(self ) -> Tuple: """simple doc...
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import logging import os import sys from dataclasses import dataclass, field from importlib import import_module from typing import Dict, List, Optional, Tuple import numpy as np from seqeval.metrics import accuracy_score, fa_score, precision_score, recall_score from torch import nn from utils_ner import Split, To...
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import os import jsonlines import numpy as np from tqdm import tqdm __snake_case : List[str] =2_0_4_8 __snake_case : List[Any] =4_0_9_6 __snake_case : Tuple =4_2 __snake_case : List[Any] =os.environ.pop('PROCESS_TRAIN', 'false') __snake_case :...
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from typing import TYPE_CHECKING from ...utils import ( OptionalDependencyNotAvailable, _LazyModule, is_torch_available, ) __snake_case : int ={ 'configuration_gpt_bigcode': ['GPT_BIGCODE_PRETRAINED_CONFIG_ARCHIVE_MAP', 'GPTBigCodeConfig'], } try: if not is_torch_available...
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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 appli...
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import copy from dataclasses import dataclass from pathlib import Path from typing import Dict, Optional, Union @dataclass class lowerCamelCase__ : '''simple docstring''' snake_case_ =None snake_case_ =False snake_case_ =False snake_case_ =False snake_case_ =Non...
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from __future__ import annotations from collections.abc import Iterator from typing import Generic, TypeVar __snake_case : int =TypeVar('T') class lowerCamelCase__ ( Generic[T]): '''simple docstring''' def __init__(self ,__lowerCamelCase ) -> Optional[Any]: ...
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def lowerCAmelCase__ ( lowerCamelCase_ : Dict ,lowerCamelCase_ : Optional[int]): '''simple docstring''' lowerCAmelCase__ : int = (boundary[1] - boundary[0]) / steps lowerCAmelCase__ : Optional[int] = boundary[0] lowerCAmelCase__ : ...
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def lowerCAmelCase__ ( lowerCamelCase_ : int): '''simple docstring''' assert isinstance(lowerCamelCase_ ,lowerCamelCase_), f"""The input value of [n={number}] is not an integer""" if number == 1: return 2 elif number < 1: lowerCAmelCase__ : s...
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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 TFMode...
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from manim import * class lowerCamelCase__ ( lowerCamelCase__): '''simple docstring''' def lowerCAmelCase__ (self ) -> List[str]: """simple docstring""" lowerCAmelCase__ : Union[str, Any] = Rectangle(height=0.5 ,width=0.5 ) lowerCAmelC...
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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 GenerationTesterMixin from ...test_con...
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from ...utils import logging from ..ta.modeling_tf_ta import TFTaEncoderModel, TFTaForConditionalGeneration, TFTaModel from .configuration_mta import MTaConfig __snake_case : List[str] =logging.get_logger(__name__) __snake_case : Optional[Any] ='T5Config' class lowerCamelCas...
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from typing import Optional import pyspark from .. import Features, NamedSplit from ..download import DownloadMode from ..packaged_modules.spark.spark import Spark from .abc import AbstractDatasetReader class lowerCamelCase__ ( lowerCamelCase__): '''simple docstring''' def __init__(self ...
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from collections import Counter from pathlib import Path from typing import Optional, Tuple import yaml class lowerCamelCase__ ( yaml.SafeLoader): '''simple docstring''' def lowerCAmelCase__ (self ,__lowerCamelCase ) -> Any: """simple docstring""" lower...
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import os import jsonlines import numpy as np from tqdm import tqdm __snake_case : List[str] =2_0_4_8 __snake_case : List[Any] =4_0_9_6 __snake_case : Tuple =4_2 __snake_case : List[Any] =os.environ.pop('PROCESS_TRAIN', 'false') __snake_case :...
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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() and ...
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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 enable_ful...
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import glob import os import random from string import ascii_lowercase, digits import cva import numpy as np # Parrameters __snake_case : Dict =(7_2_0, 1_2_8_0) # Height, Width __snake_case : List[str] =(0.4, 0.6) # if height or width lower than this scale, drop it. __snake_case ...
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from __future__ import absolute_import, division, print_function, unicode_literals from torch import nn from torch.nn import CrossEntropyLoss, MSELoss from transformers import RobertaConfig from transformers.file_utils import add_start_docstrings, add_start_docstrings_to_model_forward from transformers.models.rob...
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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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__snake_case : str ='\n# Transformers installation\n! pip install transformers datasets\n# To install from source instead of the last release, comment the command above and uncomment the following one.\n# ! pip install git+https://github.com/huggingface/transformers.git\n' __snake_case : ...
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import argparse import os import re import packaging.version __snake_case : Union[str, Any] ='examples/' __snake_case : Optional[Any] ={ 'examples': (re.compile(R'^check_min_version\("[^"]+"\)\s*$', re.MULTILINE), 'check_min_version("VERSION")\n'), 'init': (re.compile(R'^_...
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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) de...
647
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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 __snake_case : Optional[int] =logging.get_logger(__name__) __snake_case : ...
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import requests __snake_case : Optional[int] ='YOUR API KEY' def lowerCAmelCase__ ( lowerCamelCase_ : str ,lowerCamelCase_ : str = giphy_api_key): '''simple docstring''' lowerCAmelCase__ : Tuple = '''+'''.join(query.split()) lo...
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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, ImageInput,...
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from collections.abc import Callable class lowerCamelCase__ : '''simple docstring''' def __init__(self ,__lowerCamelCase = None ) -> None: """simple docstring""" lowerCAmelCase__ : list = [] # Stores indexes of each item for supporting updates and ...
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class lowerCamelCase__ : '''simple docstring''' def __init__(self ) -> Union[str, Any]: """simple docstring""" lowerCAmelCase__ : List[Any] = {} def lowerCAmelCase__ (self ) -> None: """simple docstring""" print(self.vertex ...
647
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 AutoToke...
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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 ...te...
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import torch from diffusers import KDPMaDiscreteScheduler from diffusers.utils import torch_device from .test_schedulers import SchedulerCommonTest class lowerCamelCase__ ( lowerCamelCase__): '''simple docstring''' snake_case_ =(KDPMaDiscreteScheduler,) snake_case_ =10 def...
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from __future__ import annotations from typing import Dict from ...configuration_utils import PretrainedConfig __snake_case : List[Any] ={ 'susnato/ernie-m-base_pytorch': 'https://huggingface.co/susnato/ernie-m-base_pytorch/blob/main/config.json', 'susnato/ernie-m-large_pytorch': 'https:...
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import inspect import os import sys import unittest import accelerate from accelerate.test_utils import execute_subprocess_async, require_tpu class lowerCamelCase__ ( unittest.TestCase): '''simple docstring''' def lowerCAmelCase__ (self ) -> str: """simple docstring""" ...
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from typing import List, Optional, Union from ...image_utils import ImageInput from ...processing_utils import ProcessorMixin from ...tokenization_utils_base import BatchEncoding, PaddingStrategy, PreTokenizedInput, TextInput, TruncationStrategy from ...utils import TensorType class lowerCamelCase__ ( ...
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import os import unittest from transformers.models.bartpho.tokenization_bartpho import VOCAB_FILES_NAMES, BartphoTokenizer from transformers.testing_utils import get_tests_dir from ...test_tokenization_common import TokenizerTesterMixin __snake_case : List[Any] =get_tests_dir('fixtures/test_sent...
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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(): imp...
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import math import unittest def lowerCAmelCase__ ( lowerCamelCase_ : int): '''simple docstring''' assert isinstance(lowerCamelCase_ ,lowerCamelCase_) and ( number >= 0 ), "'number' must been an int and positive" if 1 < number < 4: # 2 and 3 a...
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from __future__ import annotations import math def lowerCAmelCase__ ( lowerCamelCase_ : int): '''simple docstring''' if 1 < number < 4: # 2 and 3 are primes return True elif number < 2 or number % 2 == 0 or number % 3 == 0: # Negatives, 0, ...
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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 import get_logg...
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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_device=F...
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import unittest import numpy as np from transformers.testing_utils import require_torch, require_vision from transformers.utils import is_torch_available, is_vision_available from ...test_image_processing_common import ImageProcessingSavingTestMixin, prepare_video_inputs if is_torch_available(): import ...
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from ...configuration_utils import PretrainedConfig from ...utils import logging __snake_case : str =logging.get_logger(__name__) __snake_case : Tuple ={ 'microsoft/biogpt': 'https://huggingface.co/microsoft/biogpt/resolve/main/config.json', # See all BioGPT models at http...
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def lowerCAmelCase__ ( lowerCamelCase_ : Dict): '''simple docstring''' lowerCAmelCase__ : Optional[Any] = len(lowerCamelCase_) while cur > 1: # Find the maximum number in arr lowerCAmelCase__ : Tuple = arr.index(max(arr[0:cur])) ...
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import math def lowerCAmelCase__ ( lowerCamelCase_ : int): '''simple docstring''' lowerCAmelCase__ : int = [True] * n lowerCAmelCase__ : Any = False lowerCAmelCase__ : Optional[Any] = False lowerCAmelCase__ : List[str] = ...
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import logging import os import sys from dataclasses import dataclass, field from importlib import import_module from typing import Dict, List, Optional, Tuple import numpy as np from seqeval.metrics import accuracy_score, fa_score, precision_score, recall_score from torch import nn from utils_ner import Split, To...
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def lowerCAmelCase__ ( lowerCamelCase_ : Dict): '''simple docstring''' lowerCAmelCase__ : Optional[Any] = len(lowerCamelCase_) while cur > 1: # Find the maximum number in arr lowerCAmelCase__ : Tuple = arr.index(max(arr[0:cur])) ...
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from typing import TYPE_CHECKING from ...utils import ( OptionalDependencyNotAvailable, _LazyModule, is_torch_available, ) __snake_case : int ={ 'configuration_gpt_bigcode': ['GPT_BIGCODE_PRETRAINED_CONFIG_ARCHIVE_MAP', 'GPTBigCodeConfig'], } try: if not is_torch_available...
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from collections.abc import Callable class lowerCamelCase__ : '''simple docstring''' def __init__(self ,__lowerCamelCase = None ) -> None: """simple docstring""" lowerCAmelCase__ : list = [] # Stores indexes of each item for supporting updates and ...
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import copy from dataclasses import dataclass from pathlib import Path from typing import Dict, Optional, Union @dataclass class lowerCamelCase__ : '''simple docstring''' snake_case_ =None snake_case_ =False snake_case_ =False snake_case_ =False snake_case_ =Non...
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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__ ( lowerCamelCase_ : List[Any]): '''simple docstring''' def wrapper(*lowerCamelCase_ : Any ,...
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def lowerCAmelCase__ ( lowerCamelCase_ : Dict ,lowerCamelCase_ : Optional[int]): '''simple docstring''' lowerCAmelCase__ : int = (boundary[1] - boundary[0]) / steps lowerCAmelCase__ : Optional[int] = boundary[0] lowerCAmelCase__ : ...
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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 __snake_case : Union[str, Any] =logging.get_logger(__name__) __snake_case : Optional[int] ={ 'junnyu/...
647
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 TFMode...
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from dataclasses import dataclass from typing import Tuple import numpy as np import torch @dataclass class lowerCamelCase__ : '''simple docstring''' snake_case_ =42 # [batch_size x 3] snake_case_ =42 # [batch_size x 3] snake_case_ =42 # [batch_size x 3] snake_case_ ...
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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 GenerationTesterMixin from ...test_con...
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import os from collections import deque import torch from torch.utils.data import Dataset class lowerCamelCase__ ( lowerCamelCase__): '''simple docstring''' def __init__(self ,__lowerCamelCase="" ,__lowerCamelCase="train" ) -> Optional[Any]: """simple docstring""" ...
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from typing import Optional import pyspark from .. import Features, NamedSplit from ..download import DownloadMode from ..packaged_modules.spark.spark import Spark from .abc import AbstractDatasetReader class lowerCamelCase__ ( lowerCamelCase__): '''simple docstring''' def __init__(self ...
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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(): im...
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import os import jsonlines import numpy as np from tqdm import tqdm __snake_case : List[str] =2_0_4_8 __snake_case : List[Any] =4_0_9_6 __snake_case : Tuple =4_2 __snake_case : List[Any] =os.environ.pop('PROCESS_TRAIN', 'false') __snake_case :...
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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 __snake_case : List[Any] =logging.get_logger(__name__) __snake_cas...
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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 enable_ful...
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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, s...
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from __future__ import absolute_import, division, print_function, unicode_literals from torch import nn from torch.nn import CrossEntropyLoss, MSELoss from transformers import RobertaConfig from transformers.file_utils import add_start_docstrings, add_start_docstrings_to_model_forward from transformers.models.rob...
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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 appli...
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__snake_case : str ='\n# Transformers installation\n! pip install transformers datasets\n# To install from source instead of the last release, comment the command above and uncomment the following one.\n# ! pip install git+https://github.com/huggingface/transformers.git\n' __snake_case : ...
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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_torch clas...
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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) de...
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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_elasticsearch, requ...
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import requests __snake_case : Optional[int] ='YOUR API KEY' def lowerCAmelCase__ ( lowerCamelCase_ : str ,lowerCamelCase_ : str = giphy_api_key): '''simple docstring''' lowerCAmelCase__ : Tuple = '''+'''.join(query.split()) lo...
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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_format, ) fr...
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from collections.abc import Callable class lowerCamelCase__ : '''simple docstring''' def __init__(self ,__lowerCamelCase = None ) -> None: """simple docstring""" lowerCAmelCase__ : list = [] # Stores indexes of each item for supporting updates and ...
647
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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 PILImageResamplin...
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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 AutoToke...
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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) __snake_case : Any ...
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import torch from diffusers import KDPMaDiscreteScheduler from diffusers.utils import torch_device from .test_schedulers import SchedulerCommonTest class lowerCamelCase__ ( lowerCamelCase__): '''simple docstring''' snake_case_ =(KDPMaDiscreteScheduler,) snake_case_ =10 def...
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def lowerCAmelCase__ ( lowerCamelCase_ : int = 10 ,lowerCamelCase_ : int = 22): '''simple docstring''' lowerCAmelCase__ : Any = range(1 ,lowerCamelCase_) lowerCAmelCase__ : Dict = range(1 ,lowerCamelCase_) return sum( 1 for p...
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import inspect import os import sys import unittest import accelerate from accelerate.test_utils import execute_subprocess_async, require_tpu class lowerCamelCase__ ( unittest.TestCase): '''simple docstring''' def lowerCAmelCase__ (self ) -> str: """simple docstring""" ...
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from typing import TYPE_CHECKING from ...utils import ( OptionalDependencyNotAvailable, _LazyModule, is_flax_available, is_tf_available, is_torch_available, ) __snake_case : int ={ 'configuration_vision_encoder_decoder': ['VisionEncoderDecoderConfig', 'VisionEncoderDecoder...
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import os import unittest from transformers.models.bartpho.tokenization_bartpho import VOCAB_FILES_NAMES, BartphoTokenizer from transformers.testing_utils import get_tests_dir from ...test_tokenization_common import TokenizerTesterMixin __snake_case : List[Any] =get_tests_dir('fixtures/test_sent...
647
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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 if is_...
647
import math import unittest def lowerCAmelCase__ ( lowerCamelCase_ : int): '''simple docstring''' assert isinstance(lowerCamelCase_ ,lowerCamelCase_) and ( number >= 0 ), "'number' must been an int and positive" if 1 < number < 4: # 2 and 3 a...
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1
# 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 applic...
647
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 import get_logg...
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import darl # noqa import gym import tqdm from diffusers.experimental import ValueGuidedRLPipeline __snake_case : List[str] ={ 'n_samples': 6_4, 'horizon': 3_2, 'num_inference_steps': 2_0, 'n_guide_steps': 2, # can set to 0 for faster sampling, does not use value network 'sca...
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import unittest import numpy as np from transformers.testing_utils import require_torch, require_vision from transformers.utils import is_torch_available, is_vision_available from ...test_image_processing_common import ImageProcessingSavingTestMixin, prepare_video_inputs if is_torch_available(): import ...
647
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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 import Ac...
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def lowerCAmelCase__ ( lowerCamelCase_ : Dict): '''simple docstring''' lowerCAmelCase__ : Optional[Any] = len(lowerCamelCase_) while cur > 1: # Find the maximum number in arr lowerCAmelCase__ : Tuple = arr.index(max(arr[0:cur])) ...
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def lowerCAmelCase__ ( lowerCamelCase_ : list[int]): '''simple docstring''' if not numbers: return 0 if not isinstance(lowerCamelCase_ ,(list, tuple)) or not all( isinstance(lowerCamelCase_ ,lowerCamelCase_) for number in numbers): raise Valu...
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import logging import os import sys from dataclasses import dataclass, field from importlib import import_module from typing import Dict, List, Optional, Tuple import numpy as np from seqeval.metrics import accuracy_score, fa_score, precision_score, recall_score from torch import nn from utils_ner import Split, To...
647
1
# 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 appli...
647
from typing import TYPE_CHECKING from ...utils import ( OptionalDependencyNotAvailable, _LazyModule, is_torch_available, ) __snake_case : int ={ 'configuration_gpt_bigcode': ['GPT_BIGCODE_PRETRAINED_CONFIG_ARCHIVE_MAP', 'GPTBigCodeConfig'], } try: if not is_torch_available...
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from typing import TYPE_CHECKING from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available __snake_case : List[str] ={ 'configuration_xlm_roberta_xl': [ 'XLM_ROBERTA_XL_PRETRAINED_CONFIG_ARCHIVE_MAP', 'XLMRobertaXLConfig', 'XLMRobertaXLOnnxCo...
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import copy from dataclasses import dataclass from pathlib import Path from typing import Dict, Optional, Union @dataclass class lowerCamelCase__ : '''simple docstring''' snake_case_ =None snake_case_ =False snake_case_ =False snake_case_ =False snake_case_ =Non...
647
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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 TokenizerTesterMixin ...
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def lowerCAmelCase__ ( lowerCamelCase_ : Dict ,lowerCamelCase_ : Optional[int]): '''simple docstring''' lowerCAmelCase__ : int = (boundary[1] - boundary[0]) / steps lowerCAmelCase__ : Optional[int] = boundary[0] lowerCAmelCase__ : ...
647
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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 OnnxPipeline...
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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 TFMode...
647
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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 __snake_case : Tuple =logging.get_logger(__name__) def ...
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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 GenerationTesterMixin from ...test_con...
647
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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_mbart im...
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from typing import Optional import pyspark from .. import Features, NamedSplit from ..download import DownloadMode from ..packaged_modules.spark.spark import Spark from .abc import AbstractDatasetReader class lowerCamelCase__ ( lowerCamelCase__): '''simple docstring''' def __init__(self ...
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import sacrebleu as scb from packaging import version from sacrebleu import CHRF import datasets __snake_case : Any ='\\n@inproceedings{popovic-2015-chrf,\n title = "chr{F}: character n-gram {F}-score for automatic {MT} evaluation",\n author = "Popovi{\'c}, Maja",\n booktitle = "Proceedi...
647
import os import jsonlines import numpy as np from tqdm import tqdm __snake_case : List[str] =2_0_4_8 __snake_case : List[Any] =4_0_9_6 __snake_case : Tuple =4_2 __snake_case : List[Any] =os.environ.pop('PROCESS_TRAIN', 'false') __snake_case :...
647
1
from multiprocessing import Lock, Pipe, Process # lock used to ensure that two processes do not access a pipe at the same time __snake_case : Dict =Lock() def lowerCAmelCase__ ( lowerCamelCase_ : Any ,lowerCamelCase_ : Dict ,lowerCamelCase_ : ...
647
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 enable_ful...
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 TFMode...
647
from __future__ import absolute_import, division, print_function, unicode_literals from torch import nn from torch.nn import CrossEntropyLoss, MSELoss from transformers import RobertaConfig from transformers.file_utils import add_start_docstrings, add_start_docstrings_to_model_forward from transformers.models.rob...
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 lowerCamelCase__ ( lowerCamelCase__ , ...
647
__snake_case : str ='\n# Transformers installation\n! pip install transformers datasets\n# To install from source instead of the last release, comment the command above and uncomment the following one.\n# ! pip install git+https://github.com/huggingface/transformers.git\n' __snake_case : ...
647
1
import unittest from knapsack import greedy_knapsack as kp class lowerCamelCase__ ( unittest.TestCase): '''simple docstring''' def lowerCAmelCase__ (self ) -> Optional[Any]: """simple docstring""" lowerCAmelCase__ : int = [10, 20, 30, 40, 50, 60] ...
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) de...
647
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 __snake_case : Tuple =logging.get_logger(__name__) ...
647
import requests __snake_case : Optional[int] ='YOUR API KEY' def lowerCAmelCase__ ( lowerCamelCase_ : str ,lowerCamelCase_ : str = giphy_api_key): '''simple docstring''' lowerCAmelCase__ : Tuple = '''+'''.join(query.split()) lo...
647
1
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 AutoToke...
647
from collections.abc import Callable class lowerCamelCase__ : '''simple docstring''' def __init__(self ,__lowerCamelCase = None ) -> None: """simple docstring""" lowerCAmelCase__ : list = [] # Stores indexes of each item for supporting updates and ...
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 if is_...
647
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 AutoToke...
647
1
import copy from dataclasses import dataclass from pathlib import Path from typing import Dict, Optional, Union @dataclass class lowerCamelCase__ : '''simple docstring''' snake_case_ =None snake_case_ =False snake_case_ =False snake_case_ =False snake_case_ =Non...
647
import torch from diffusers import KDPMaDiscreteScheduler from diffusers.utils import torch_device from .test_schedulers import SchedulerCommonTest class lowerCamelCase__ ( lowerCamelCase__): '''simple docstring''' snake_case_ =(KDPMaDiscreteScheduler,) snake_case_ =10 def...
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1
import copy from dataclasses import dataclass, field from typing import ClassVar, Dict from ..features import ClassLabel, Features, Value from .base import TaskTemplate @dataclass(frozen=lowerCamelCase__) class lowerCamelCase__ ( lowerCamelCase__): '''simple docstring''' snake_case_ =f...
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import inspect import os import sys import unittest import accelerate from accelerate.test_utils import execute_subprocess_async, require_tpu class lowerCamelCase__ ( unittest.TestCase): '''simple docstring''' def lowerCAmelCase__ (self ) -> str: """simple docstring""" ...
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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) de...
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import os import unittest from transformers.models.bartpho.tokenization_bartpho import VOCAB_FILES_NAMES, BartphoTokenizer from transformers.testing_utils import get_tests_dir from ...test_tokenization_common import TokenizerTesterMixin __snake_case : List[Any] =get_tests_dir('fixtures/test_sent...
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