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import json import os import tempfile import unittest import numpy as np from datasets import load_dataset 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 im...
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import os import unittest from transformers import MobileBertTokenizer, MobileBertTokenizerFast from transformers.models.bert.tokenization_bert import ( VOCAB_FILES_NAMES, BasicTokenizer, WordpieceTokenizer, _is_control, _is_punctuation, _is_whitespace, ) from transfor...
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def _lowerCamelCase ( __lowerCamelCase , __lowerCamelCase , __lowerCamelCase , __lowerCamelCase ) -> str: '''simple docstring''' global f # a global dp table for knapsack if f[i][j] < 0: if j < wt[i - 1]: UpperCAmelCase__...
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import argparse import re import requests import torch # git clone https://github.com/salesforce/BLIP.git from models.blip import blip_decoder from models.blip_itm import blip_itm from models.blip_vqa import blip_vqa from PIL import Image from torchvision import transforms from torchvision.t...
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import argparse 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 Accel...
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from ...configuration_utils import PretrainedConfig from ...utils import logging SCREAMING_SNAKE_CASE__ : Tuple = logging.get_logger(__name__) SCREAMING_SNAKE_CASE__ : List[Any] = { """MIT/ast-finetuned-audioset-10-10-0.4593""": ( """https://huggingface.c...
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from math import factorial def _lowerCamelCase ( __lowerCamelCase , __lowerCamelCase ) -> int: '''simple docstring''' # If either of the conditions are true, the function is being asked # to calculate a factorial of a negative number, which is not ...
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import warnings from ...utils import logging from .image_processing_glpn import GLPNImageProcessor SCREAMING_SNAKE_CASE__ : Dict = logging.get_logger(__name__) class UpperCAmelCase_ ( __lowerCamelCase ): def __init__( self , *_lowerCAmelCa...
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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 ConvNextConfig, SegformerImageProcessor, UperNetConfig, UperNetForSemanticSegmentation def _lowerCamelCase ( __lowerCamelCase ...
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import json from typing import List, Optional, Tuple from tokenizers import normalizers from ...tokenization_utils_base import BatchEncoding from ...tokenization_utils_fast import PreTrainedTokenizerFast from ...utils import PaddingStrategy, logging from .tokenization_realm import RealmTokenizer...
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import copy import os from typing import Union from ...configuration_utils import PretrainedConfig from ...models.auto.modeling_auto import MODEL_FOR_CAUSAL_LM_MAPPING_NAMES from ...utils import logging from ..auto import CONFIG_MAPPING SCREAMING_SNAKE_CASE__ : Dict = logging.ge...
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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 # # U...
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from typing import Optional import numpy as np import torch from torch import nn from transformers import GPTaConfig, GPTaLMHeadModel from transformers.modeling_utils import ModuleUtilsMixin from ...configuration_utils import ConfigMixin, register_to_config from ...models import ModelMixin ...
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from __future__ import annotations import inspect import unittest from transformers import ViTConfig from transformers.testing_utils import require_tf, require_vision, slow from transformers.utils import cached_property, is_tf_available, is_vision_available from ...test_configuration_common im...
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from pathlib import PurePosixPath from typing import Optional import fsspec from fsspec import AbstractFileSystem from huggingface_hub.hf_api import DatasetInfo from ..utils.file_utils import get_authentication_headers_for_url from ..utils.hub import hf_hub_url class UpperCAme...
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from functools import lru_cache @lru_cache def _lowerCamelCase ( __lowerCamelCase ) -> int: '''simple docstring''' if num < 0: raise ValueError("""Number should not be negative.""" ) return 1 if num in (0, 1) else num * factorial(num - ...
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import json from typing import List, Optional, Tuple from tokenizers import normalizers from ...tokenization_utils_fast import PreTrainedTokenizerFast from .tokenization_electra import ElectraTokenizer SCREAMING_SNAKE_CASE__ : List[str] = {"""vocab_file""": """vocab.txt""", """t...
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import argparse import hashlib # hashlib is only used inside the Test class import struct class UpperCAmelCase_ : def __init__( self , _lowerCAmelCase ): UpperCAmelCase__ : Any = data UpperCAmelCase__ : List[Any] ...
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import os import shutil import sys import tempfile import unittest from pathlib import Path import pytest import transformers from transformers import ( BERT_PRETRAINED_CONFIG_ARCHIVE_MAP, GPT2_PRETRAINED_CONFIG_ARCHIVE_MAP, AutoTokenizer, BertConfig, BertTokenizer, ...
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from importlib import import_module from .logging import get_logger SCREAMING_SNAKE_CASE__ : Union[str, Any] = get_logger(__name__) class UpperCAmelCase_ : def __init__( self , _lowerCAmelCase , _lowerCAmelCase=None ): UpperC...
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import warnings from typing import List, Optional, Union from ...processing_utils import ProcessorMixin from ...tokenization_utils_base import BatchEncoding, PaddingStrategy, PreTokenizedInput, TextInput, TruncationStrategy from ...utils import TensorType class UpperCAmelCase_ ( ...
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from typing import List, Optional, Union from ...configuration_utils import PretrainedConfig from ...utils import logging SCREAMING_SNAKE_CASE__ : str = logging.get_logger(__name__) SCREAMING_SNAKE_CASE__ : Any = { """huggingface/informer-tourism-monthly""": ( ...
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# Copyright 2022 The HuggingFace Team and The OpenBMB 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/LIC...
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def _lowerCamelCase ( __lowerCamelCase ) -> bool: '''simple docstring''' if p < 2: raise ValueError("""p should not be less than 2!""" ) elif p == 2: return True UpperCAmelCase__ : Tuple = 4 UpperCAmelCase_...
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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 , ...
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from typing import TYPE_CHECKING from ...utils import ( OptionalDependencyNotAvailable, _LazyModule, is_tf_available, is_torch_available, is_vision_available, ) SCREAMING_SNAKE_CASE__ : Any = { """configuration_mobilevit""": ["""MOBILEVIT_PRETRAINED_CON...
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from __future__ import annotations import unittest from transformers import BlenderbotConfig, BlenderbotTokenizer, is_tf_available from transformers.testing_utils import require_tf, require_tokenizers, slow from transformers.utils import cached_property from ...test_configuration_common import ...
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from __future__ import annotations SCREAMING_SNAKE_CASE__ : List[str] = 8.988e9 # units = N * m^s * C^-2 def _lowerCamelCase ( __lowerCamelCase , __lowerCamelCase , __lowerCamelCase , __lowerCamelCase ) -> dict[str, float]: '''simpl...
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import baseaa def _lowerCamelCase ( __lowerCamelCase ) -> bytes: '''simple docstring''' return baseaa.baaencode(string.encode("""utf-8""" ) ) def _lowerCamelCase ( __lowerCamelCase ) -> str: '''simple docstring''...
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class UpperCAmelCase_ : def __init__( self , _lowerCAmelCase ): # we need a list not a string, so do something to change the type UpperCAmelCase__ : Dict = arr.split(""",""" ) def __UpperCAmelCase ( self ): ...
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import numpy as np from PIL import Image def _lowerCamelCase ( __lowerCamelCase , __lowerCamelCase , __lowerCamelCase ) -> np.ndarray: '''simple docstring''' UpperCAmelCase__ : Dict = np.array(__lowerCamelCase ) if arr.s...
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from ....configuration_utils import PretrainedConfig from ....utils import logging SCREAMING_SNAKE_CASE__ : List[str] = logging.get_logger(__name__) SCREAMING_SNAKE_CASE__ : Any = { """Visual-Attention-Network/van-base""": ( """https://huggingface.co/Visu...
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import unittest import numpy as np import timeout_decorator # noqa from transformers import BlenderbotConfig, is_flax_available from transformers.testing_utils import jax_device, require_flax, slow from ...generation.test_flax_utils import FlaxGenerationTesterMixin from ...test_modeling_flax_...
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import argparse import os import torch from transformers import FlavaImageCodebook, FlavaImageCodebookConfig def _lowerCamelCase ( __lowerCamelCase , __lowerCamelCase , __lowerCamelCase , __lowerCamelCase ) -> Any: '''simple docstring''' ...
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from typing import TYPE_CHECKING from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_speech_available, is_torch_available SCREAMING_SNAKE_CASE__ : List[str] = { """configuration_audio_spectrogram_transformer""": [ """AUDIO_SPECTROGRAM_TRANSFORMER_PRETRA...
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def _lowerCamelCase ( __lowerCamelCase ) -> int: '''simple docstring''' return 1 if digit in (0, 1) else (digit * factorial(digit - 1 )) def _lowerCamelCase ( __lowerCamelCase ) -> bool: '''simple docstring''' UpperCAmelCas...
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def _lowerCamelCase ( __lowerCamelCase ) -> list: '''simple docstring''' if any(not isinstance(__lowerCamelCase , __lowerCamelCase ) or x < 0 for x in sequence ): raise TypeError("""Sequence must be list of non-negative integers""" ) ...
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def _lowerCamelCase ( __lowerCamelCase = 100_0000 ) -> int: '''simple docstring''' UpperCAmelCase__ : Tuple = [i - 1 for i in range(limit + 1 )] for i in range(2 , limit + 1 ): if phi[i] == i - 1: for j ...
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from ....configuration_utils import PretrainedConfig from ....utils import logging SCREAMING_SNAKE_CASE__ : List[str] = logging.get_logger(__name__) SCREAMING_SNAKE_CASE__ : Any = { """Visual-Attention-Network/van-base""": ( """https://huggingface.co/Visu...
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from ...configuration_utils import PretrainedConfig from ...utils import logging SCREAMING_SNAKE_CASE__ : Dict = logging.get_logger(__name__) SCREAMING_SNAKE_CASE__ : Tuple = { """google/realm-cc-news-pretrained-embedder""": ( """https://huggingface.co/go...
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from typing import TYPE_CHECKING from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available, is_vision_available SCREAMING_SNAKE_CASE__ : Any = { """configuration_mobilenet_v2""": [ """MOBILENET_V2_PRETRAINED_CONFIG_ARCHIVE_MAP""", """...
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import gc import unittest from parameterized import parameterized from diffusers import FlaxUNetaDConditionModel from diffusers.utils import is_flax_available from diffusers.utils.testing_utils import load_hf_numpy, require_flax, slow if is_flax_available(): import jax import j...
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import argparse import hashlib # hashlib is only used inside the Test class import struct class UpperCAmelCase_ : def __init__( self , _lowerCAmelCase ): UpperCAmelCase__ : Any = data UpperCAmelCase__ : List[Any] ...
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import json import os import tempfile import unittest import numpy as np from datasets import load_dataset 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 im...
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import logging from pathlib import Path import numpy as np import pytorch_lightning as pl import torch from pytorch_lightning.callbacks import EarlyStopping, ModelCheckpoint from pytorch_lightning.utilities import rank_zero_only from utils_rag import save_json def _lowerCamelCase ...
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import os import unittest from transformers import MobileBertTokenizer, MobileBertTokenizerFast from transformers.models.bert.tokenization_bert import ( VOCAB_FILES_NAMES, BasicTokenizer, WordpieceTokenizer, _is_control, _is_punctuation, _is_whitespace, ) from transfor...
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from importlib import import_module from .logging import get_logger SCREAMING_SNAKE_CASE__ : Union[str, Any] = get_logger(__name__) class UpperCAmelCase_ : def __init__( self , _lowerCAmelCase , _lowerCAmelCase=None ): UpperC...
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import argparse import re import requests import torch # git clone https://github.com/salesforce/BLIP.git from models.blip import blip_decoder from models.blip_itm import blip_itm from models.blip_vqa import blip_vqa from PIL import Image from torchvision import transforms from torchvision.t...
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from ...configuration_utils import PretrainedConfig from ...utils import logging SCREAMING_SNAKE_CASE__ : Union[str, Any] = logging.get_logger(__name__) SCREAMING_SNAKE_CASE__ : List[Any] = { """google/vivit-b-16x2-kinetics400""": ( """https://huggingface...
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from ...configuration_utils import PretrainedConfig from ...utils import logging SCREAMING_SNAKE_CASE__ : Tuple = logging.get_logger(__name__) SCREAMING_SNAKE_CASE__ : List[Any] = { """MIT/ast-finetuned-audioset-10-10-0.4593""": ( """https://huggingface.c...
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from .data_collator import ( DataCollatorForLanguageModeling, DataCollatorForPermutationLanguageModeling, DataCollatorForSeqaSeq, DataCollatorForSOP, DataCollatorForTokenClassification, DataCollatorForWholeWordMask, DataCollatorWithPadding, DefaultDataCollator, ...
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import warnings from ...utils import logging from .image_processing_glpn import GLPNImageProcessor SCREAMING_SNAKE_CASE__ : Dict = logging.get_logger(__name__) class UpperCAmelCase_ ( __lowerCamelCase ): def __init__( self , *_lowerCAmelCa...
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import os from typing import Dict, List, Tuple, TypeVar, Union SCREAMING_SNAKE_CASE__ : Any = TypeVar("""T""") SCREAMING_SNAKE_CASE__ : List[Any] = Union[List[T], Tuple[T, ...]] SCREAMING_SNAKE_CASE__ : int = Union[T, List[T], Dict[str, T]] SCREAMING_SN...
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import json from typing import List, Optional, Tuple from tokenizers import normalizers from ...tokenization_utils_base import BatchEncoding from ...tokenization_utils_fast import PreTrainedTokenizerFast from ...utils import PaddingStrategy, logging from .tokenization_realm import RealmTokenizer...
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from ...utils import logging from ..ta.modeling_tf_ta import TFTaEncoderModel, TFTaForConditionalGeneration, TFTaModel from .configuration_mta import MTaConfig SCREAMING_SNAKE_CASE__ : List[Any] = logging.get_logger(__name__) SCREAMING_SNAKE_CASE__ : Any = """T5Config...
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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 # # U...
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import glob import os import random from string import ascii_lowercase, digits import cva SCREAMING_SNAKE_CASE__ : Optional[int] = """""" SCREAMING_SNAKE_CASE__ : Union[str, Any] = """""" SCREAMING_SNAKE_CASE__ : Any = """""" SCREAMING_SNAKE_CASE__ : ...
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from __future__ import annotations import inspect import unittest from transformers import ViTConfig from transformers.testing_utils import require_tf, require_vision, slow from transformers.utils import cached_property, is_tf_available, is_vision_available from ...test_configuration_common im...
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class UpperCAmelCase_ : def __init__( self , _lowerCAmelCase ): # we need a list not a string, so do something to change the type UpperCAmelCase__ : Dict = arr.split(""",""" ) def __UpperCAmelCase ( self ): ...
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from functools import lru_cache @lru_cache def _lowerCamelCase ( __lowerCamelCase ) -> int: '''simple docstring''' if num < 0: raise ValueError("""Number should not be negative.""" ) return 1 if num in (0, 1) else num * factorial(num - ...
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import random import unittest import torch from diffusers import IFInpaintingPipeline from diffusers.utils import floats_tensor from diffusers.utils.import_utils import is_xformers_available from diffusers.utils.testing_utils import skip_mps, torch_device from ..pipeline_params import ( ...
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import argparse import hashlib # hashlib is only used inside the Test class import struct class UpperCAmelCase_ : def __init__( self , _lowerCAmelCase ): UpperCAmelCase__ : Any = data UpperCAmelCase__ : List[Any] ...
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import gc import unittest from diffusers import FlaxStableDiffusionInpaintPipeline from diffusers.utils import is_flax_available, load_image, slow from diffusers.utils.testing_utils import require_flax if is_flax_available(): import jax import jax.numpy as jnp from flax.jax...
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from importlib import import_module from .logging import get_logger SCREAMING_SNAKE_CASE__ : Union[str, Any] = get_logger(__name__) class UpperCAmelCase_ : def __init__( self , _lowerCAmelCase , _lowerCAmelCase=None ): UpperC...
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# Lint as: python3 import sys from collections.abc import Mapping from typing import TYPE_CHECKING import numpy as np import pyarrow as pa from .. import config from ..utils.py_utils import map_nested from .formatting import TensorFormatter if TYPE_CHECKING: import torch ...
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from typing import List, Optional, Union from ...configuration_utils import PretrainedConfig from ...utils import logging SCREAMING_SNAKE_CASE__ : str = logging.get_logger(__name__) SCREAMING_SNAKE_CASE__ : Any = { """huggingface/informer-tourism-monthly""": ( ...
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from typing import TYPE_CHECKING from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tokenizers_available, is_torch_available SCREAMING_SNAKE_CASE__ : Optional[Any] = { """configuration_mvp""": ["""MVP_PRETRAINED_CONFIG_ARCHIVE_MAP""", """MvpConfig""", """MvpOnn...
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def _lowerCamelCase ( __lowerCamelCase ) -> bool: '''simple docstring''' if p < 2: raise ValueError("""p should not be less than 2!""" ) elif p == 2: return True UpperCAmelCase__ : Tuple = 4 UpperCAmelCase_...
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import argparse import os import gluonnlp as nlp import mxnet as mx import numpy as np import torch from gluonnlp.base import get_home_dir from gluonnlp.model.bert import BERTEncoder from gluonnlp.model.utils import _load_vocab from gluonnlp.vocab import Vocab from packaging import version fr...
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from typing import TYPE_CHECKING from ...utils import ( OptionalDependencyNotAvailable, _LazyModule, is_tf_available, is_torch_available, is_vision_available, ) SCREAMING_SNAKE_CASE__ : Any = { """configuration_mobilevit""": ["""MOBILEVIT_PRETRAINED_CON...
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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_d...
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from __future__ import annotations SCREAMING_SNAKE_CASE__ : List[str] = 8.988e9 # units = N * m^s * C^-2 def _lowerCamelCase ( __lowerCamelCase , __lowerCamelCase , __lowerCamelCase , __lowerCamelCase ) -> dict[str, float]: '''simpl...
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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, ) SCREAMING_SNAKE_CASE__ : Union[str, Any] = { """configuration_bl...
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class UpperCAmelCase_ : def __init__( self , _lowerCAmelCase ): # we need a list not a string, so do something to change the type UpperCAmelCase__ : Dict = arr.split(""",""" ) def __UpperCAmelCase ( self ): ...
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import importlib import sys from argparse import REMAINDER, ArgumentParser from pathlib import Path import torch_xla.distributed.xla_multiprocessing as xmp def _lowerCamelCase ( ) -> List[Any]: '''simple docstring''' UpperCAmelCase__ : List[Any] =...
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from ....configuration_utils import PretrainedConfig from ....utils import logging SCREAMING_SNAKE_CASE__ : List[str] = logging.get_logger(__name__) SCREAMING_SNAKE_CASE__ : Any = { """Visual-Attention-Network/van-base""": ( """https://huggingface.co/Visu...
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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 SCREAMING_SNAKE_CASE__ : Any = logging.get_logger(__name__) SCREAMING_SNAKE_CASE__ : Tuple =...
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import argparse import os import torch from transformers import FlavaImageCodebook, FlavaImageCodebookConfig def _lowerCamelCase ( __lowerCamelCase , __lowerCamelCase , __lowerCamelCase , __lowerCamelCase ) -> Any: '''simple docstring''' ...
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from __future__ import annotations import json import requests from bsa import BeautifulSoup from fake_useragent import UserAgent SCREAMING_SNAKE_CASE__ : Union[str, Any] = {"""UserAgent""": UserAgent().random} def _lowerCamelCase ( __lowerCamelCase ) -...
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def _lowerCamelCase ( __lowerCamelCase ) -> int: '''simple docstring''' return 1 if digit in (0, 1) else (digit * factorial(digit - 1 )) def _lowerCamelCase ( __lowerCamelCase ) -> bool: '''simple docstring''' UpperCAmelCas...
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import json import os import unittest from transformers import BatchEncoding, MvpTokenizer, MvpTokenizerFast from transformers.models.roberta.tokenization_roberta import VOCAB_FILES_NAMES from transformers.testing_utils import require_tokenizers, require_torch from transformers.utils import cached...
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def _lowerCamelCase ( __lowerCamelCase = 100_0000 ) -> int: '''simple docstring''' UpperCAmelCase__ : Tuple = [i - 1 for i in range(limit + 1 )] for i in range(2 , limit + 1 ): if phi[i] == i - 1: for j ...
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import math SCREAMING_SNAKE_CASE__ : Union[str, Any] = 10 SCREAMING_SNAKE_CASE__ : List[Any] = 7 SCREAMING_SNAKE_CASE__ : Optional[Any] = BALLS_PER_COLOUR * NUM_COLOURS def _lowerCamelCase ( __lowerCamelCase = 20 ) -> str: ...
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from ...configuration_utils import PretrainedConfig from ...utils import logging SCREAMING_SNAKE_CASE__ : Dict = logging.get_logger(__name__) SCREAMING_SNAKE_CASE__ : Tuple = { """google/realm-cc-news-pretrained-embedder""": ( """https://huggingface.co/go...
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import argparse import intel_extension_for_pytorch as ipex import torch from diffusers import DPMSolverMultistepScheduler, StableDiffusionPipeline SCREAMING_SNAKE_CASE__ : Any = argparse.ArgumentParser("""Stable Diffusion script with intel optimization""", add_help=False) parser...
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import gc import unittest from parameterized import parameterized from diffusers import FlaxUNetaDConditionModel from diffusers.utils import is_flax_available from diffusers.utils.testing_utils import load_hf_numpy, require_flax, slow if is_flax_available(): import jax import j...
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from binascii import hexlify from hashlib import shaaaa from os import urandom # RFC 3526 - More Modular Exponential (MODP) Diffie-Hellman groups for # Internet Key Exchange (IKE) https://tools.ietf.org/html/rfc3526 SCREAMING_SNAKE_CASE__ : Union[str, Any] = { # 1536-bit 5...
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import json import os import tempfile import unittest import numpy as np from datasets import load_dataset 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 im...
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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 # # U...
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import os import unittest from transformers import MobileBertTokenizer, MobileBertTokenizerFast from transformers.models.bert.tokenization_bert import ( VOCAB_FILES_NAMES, BasicTokenizer, WordpieceTokenizer, _is_control, _is_punctuation, _is_whitespace, ) from transfor...
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import importlib import os import fsspec import pytest from fsspec import register_implementation from fsspec.registry import _registry as _fsspec_registry from datasets.filesystems import COMPRESSION_FILESYSTEMS, HfFileSystem, extract_path_from_uri, is_remote_filesystem from .utils import re...
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import argparse import re import requests import torch # git clone https://github.com/salesforce/BLIP.git from models.blip import blip_decoder from models.blip_itm import blip_itm from models.blip_vqa import blip_vqa from PIL import Image from torchvision import transforms from torchvision.t...
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import argparse import os import torch from transformers import FlavaImageCodebook, FlavaImageCodebookConfig def _lowerCamelCase ( __lowerCamelCase , __lowerCamelCase , __lowerCamelCase , __lowerCamelCase ) -> Any: '''simple docstring''' ...
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from ...configuration_utils import PretrainedConfig from ...utils import logging SCREAMING_SNAKE_CASE__ : Tuple = logging.get_logger(__name__) SCREAMING_SNAKE_CASE__ : List[Any] = { """MIT/ast-finetuned-audioset-10-10-0.4593""": ( """https://huggingface.c...
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import re import tempfile from pathlib import Path import pytest import yaml from datasets.utils.readme import ReadMe # @pytest.fixture # def example_yaml_structure(): SCREAMING_SNAKE_CASE__ : List[str] = yaml.safe_load( """\ name: \"\" allow_empty: false allow_empty_t...
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import warnings from ...utils import logging from .image_processing_glpn import GLPNImageProcessor SCREAMING_SNAKE_CASE__ : Dict = logging.get_logger(__name__) class UpperCAmelCase_ ( __lowerCamelCase ): def __init__( self , *_lowerCAmelCa...
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import math def _lowerCamelCase ( __lowerCamelCase , __lowerCamelCase ) -> float: '''simple docstring''' if ( not isinstance(__lowerCamelCase , (int, float) ) or power_factor < -1 or power_factor > 1 ): ...
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import json from typing import List, Optional, Tuple from tokenizers import normalizers from ...tokenization_utils_base import BatchEncoding from ...tokenization_utils_fast import PreTrainedTokenizerFast from ...utils import PaddingStrategy, logging from .tokenization_realm import RealmTokenizer...
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from queue import Queue from typing import TYPE_CHECKING, Optional if TYPE_CHECKING: from ..models.auto import AutoTokenizer class UpperCAmelCase_ : def __UpperCAmelCase ( self , _lowerCAmelCase ): raise NotImplementedError() ...
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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 # # U...
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import json import unittest import numpy as np from huggingface_hub import hf_hub_download 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 ImageProcessingSavi...
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from __future__ import annotations import inspect import unittest from transformers import ViTConfig from transformers.testing_utils import require_tf, require_vision, slow from transformers.utils import cached_property, is_tf_available, is_vision_available from ...test_configuration_common im...
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import argparse import glob import logging import os import time from argparse import Namespace import numpy as np import torch from lightning_base import BaseTransformer, add_generic_args, generic_train from torch.utils.data import DataLoader, TensorDataset from transformers import glue_com...
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from functools import lru_cache @lru_cache def _lowerCamelCase ( __lowerCamelCase ) -> int: '''simple docstring''' if num < 0: raise ValueError("""Number should not be negative.""" ) return 1 if num in (0, 1) else num * factorial(num - ...
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from typing import TYPE_CHECKING from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available SCREAMING_SNAKE_CASE__ : Any = { """configuration_blip_2""": [ """BLIP_2_PRETRAINED_CONFIG_ARCHIVE_MAP""", """Blip2Config""", """Blip2...
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import argparse import hashlib # hashlib is only used inside the Test class import struct class UpperCAmelCase_ : def __init__( self , _lowerCAmelCase ): UpperCAmelCase__ : Any = data UpperCAmelCase__ : List[Any] ...
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import os from dataclasses import dataclass, field from io import BytesIO from typing import TYPE_CHECKING, Any, ClassVar, Dict, Optional, Union import numpy as np import pyarrow as pa from .. import config from ..download.streaming_download_manager import xopen, xsplitext from ..table import ...
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from importlib import import_module from .logging import get_logger SCREAMING_SNAKE_CASE__ : Union[str, Any] = get_logger(__name__) class UpperCAmelCase_ : def __init__( self , _lowerCAmelCase , _lowerCAmelCase=None ): UpperC...
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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) SCREAMING_...
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from typing import List, Optional, Union from ...configuration_utils import PretrainedConfig from ...utils import logging SCREAMING_SNAKE_CASE__ : str = logging.get_logger(__name__) SCREAMING_SNAKE_CASE__ : Any = { """huggingface/informer-tourism-monthly""": ( ...
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from abc import ABC, abstractmethod from argparse import ArgumentParser class UpperCAmelCase_ ( __lowerCamelCase ): @staticmethod @abstractmethod def __UpperCAmelCase ( _lowerCAmelCase ): raise NotImplementedError() @abstract...
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def _lowerCamelCase ( __lowerCamelCase ) -> bool: '''simple docstring''' if p < 2: raise ValueError("""p should not be less than 2!""" ) elif p == 2: return True UpperCAmelCase__ : Tuple = 4 UpperCAmelCase_...
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from typing import TYPE_CHECKING from ...utils import ( OptionalDependencyNotAvailable, _LazyModule, is_tokenizers_available, is_torch_available, is_vision_available, ) SCREAMING_SNAKE_CASE__ : int = { """configuration_layoutlmv2""": ["""LAYOUTLMV2_PRET...
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from typing import TYPE_CHECKING from ...utils import ( OptionalDependencyNotAvailable, _LazyModule, is_tf_available, is_torch_available, is_vision_available, ) SCREAMING_SNAKE_CASE__ : Any = { """configuration_mobilevit""": ["""MOBILEVIT_PRETRAINED_CON...
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from __future__ import annotations import unittest from transformers import is_tf_available from transformers.testing_utils import require_sentencepiece, require_tf, require_tokenizers, slow if is_tf_available(): import numpy as np import tensorflow as tf from transforme...
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from __future__ import annotations SCREAMING_SNAKE_CASE__ : List[str] = 8.988e9 # units = N * m^s * C^-2 def _lowerCamelCase ( __lowerCamelCase , __lowerCamelCase , __lowerCamelCase , __lowerCamelCase ) -> dict[str, float]: '''simpl...
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from .glue import glue_convert_examples_to_features, glue_output_modes, glue_processors, glue_tasks_num_labels from .squad import SquadExample, SquadFeatures, SquadVaProcessor, SquadVaProcessor, squad_convert_examples_to_features from .utils import DataProcessor, InputExample, InputFeatures, SingleSente...
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class UpperCAmelCase_ : def __init__( self , _lowerCAmelCase ): # we need a list not a string, so do something to change the type UpperCAmelCase__ : Dict = arr.split(""",""" ) def __UpperCAmelCase ( self ): ...
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import argparse from pathlib import Path from typing import Dict, OrderedDict, Tuple import torch from audiocraft.models import MusicGen from transformers import ( AutoFeatureExtractor, AutoTokenizer, EncodecModel, MusicgenDecoderConfig, MusicgenForConditionalGeneration, ...
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from ....configuration_utils import PretrainedConfig from ....utils import logging SCREAMING_SNAKE_CASE__ : List[str] = logging.get_logger(__name__) SCREAMING_SNAKE_CASE__ : Any = { """Visual-Attention-Network/van-base""": ( """https://huggingface.co/Visu...
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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_availab...
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import argparse import os import torch from transformers import FlavaImageCodebook, FlavaImageCodebookConfig def _lowerCamelCase ( __lowerCamelCase , __lowerCamelCase , __lowerCamelCase , __lowerCamelCase ) -> Any: '''simple docstring''' ...
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import json import os from typing import Dict, List, Optional, Tuple from ...tokenization_utils import PreTrainedTokenizer from ...utils import logging SCREAMING_SNAKE_CASE__ : Optional[int] = logging.get_logger(__name__) SCREAMING_SNAKE_CASE__ : List[Any] = { ...
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def _lowerCamelCase ( __lowerCamelCase ) -> int: '''simple docstring''' return 1 if digit in (0, 1) else (digit * factorial(digit - 1 )) def _lowerCamelCase ( __lowerCamelCase ) -> bool: '''simple docstring''' UpperCAmelCas...
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import functools import operator from ...configuration_utils import PretrainedConfig from ...utils import logging SCREAMING_SNAKE_CASE__ : Dict = logging.get_logger(__name__) SCREAMING_SNAKE_CASE__ : int = { """microsoft/unispeech-large-1500h-cv""": ( ...
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def _lowerCamelCase ( __lowerCamelCase = 100_0000 ) -> int: '''simple docstring''' UpperCAmelCase__ : Tuple = [i - 1 for i in range(limit + 1 )] for i in range(2 , limit + 1 ): if phi[i] == i - 1: for j ...
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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 # # U...
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from ...configuration_utils import PretrainedConfig from ...utils import logging SCREAMING_SNAKE_CASE__ : Dict = logging.get_logger(__name__) SCREAMING_SNAKE_CASE__ : Tuple = { """google/realm-cc-news-pretrained-embedder""": ( """https://huggingface.co/go...
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from __future__ import annotations import pandas as pd def _lowerCamelCase ( __lowerCamelCase , __lowerCamelCase , __lowerCamelCase ) -> list[int]: '''simple docstring''' UpperCAmelCase__ : List[Any] = [0] * no_of_processes ...
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import gc import unittest from parameterized import parameterized from diffusers import FlaxUNetaDConditionModel from diffusers.utils import is_flax_available from diffusers.utils.testing_utils import load_hf_numpy, require_flax, slow if is_flax_available(): import jax import j...
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def _lowerCamelCase ( __lowerCamelCase ) -> bool: '''simple docstring''' if p < 2: raise ValueError("""p should not be less than 2!""" ) elif p == 2: return True UpperCAmelCase__ : Tuple = 4 UpperCAmelCase_...
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import json import os import tempfile import unittest import numpy as np from datasets import load_dataset 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 im...
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from typing import List, Optional, Union import torch from ...models import UNetaDConditionModel, VQModel from ...pipelines import DiffusionPipeline from ...pipelines.pipeline_utils import ImagePipelineOutput from ...schedulers import DDPMScheduler from ...utils import ( is_accelerate_avail...
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import os import unittest from transformers import MobileBertTokenizer, MobileBertTokenizerFast from transformers.models.bert.tokenization_bert import ( VOCAB_FILES_NAMES, BasicTokenizer, WordpieceTokenizer, _is_control, _is_punctuation, _is_whitespace, ) from transfor...
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from __future__ import annotations from typing import TypedDict class UpperCAmelCase_ ( __lowerCamelCase ): __lowerCamelCase = 42 __lowerCamelCase = 42 def _lowerCamelCase ( __lowerCamelCase ) -> list[str]: '''s...
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import argparse import re import requests import torch # git clone https://github.com/salesforce/BLIP.git from models.blip import blip_decoder from models.blip_itm import blip_itm from models.blip_vqa import blip_vqa from PIL import Image from torchvision import transforms from torchvision.t...
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class UpperCAmelCase_ : def __init__( self , _lowerCAmelCase , _lowerCAmelCase ): UpperCAmelCase__ : Dict = name UpperCAmelCase__ : Union[str, Any] = val def __str__( self ): return f"{sel...
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from ...configuration_utils import PretrainedConfig from ...utils import logging SCREAMING_SNAKE_CASE__ : Tuple = logging.get_logger(__name__) SCREAMING_SNAKE_CASE__ : List[Any] = { """MIT/ast-finetuned-audioset-10-10-0.4593""": ( """https://huggingface.c...
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from math import factorial class UpperCAmelCase_ : def __init__( self , _lowerCAmelCase , _lowerCAmelCase ): UpperCAmelCase__ : str = real if isinstance(_lowerCAmelCase , _lowerCAmelCase ): UpperCA...
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import warnings from ...utils import logging from .image_processing_glpn import GLPNImageProcessor SCREAMING_SNAKE_CASE__ : Dict = logging.get_logger(__name__) class UpperCAmelCase_ ( __lowerCamelCase ): def __init__( self , *_lowerCAmelCa...
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import os import posixpath import uuid from dataclasses import dataclass from typing import TYPE_CHECKING, Iterable, List, Optional, Tuple, Union import numpy as np import pyarrow as pa import datasets from datasets.arrow_writer import ArrowWriter, ParquetWriter from datasets.config import MA...
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import json from typing import List, Optional, Tuple from tokenizers import normalizers from ...tokenization_utils_base import BatchEncoding from ...tokenization_utils_fast import PreTrainedTokenizerFast from ...utils import PaddingStrategy, logging from .tokenization_realm import RealmTokenizer...
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import json import os import re import sys import urllib.request import requests from bsa import BeautifulSoup SCREAMING_SNAKE_CASE__ : int = { """User-Agent""": """Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36""" """ (KHTML, like Gecko) Chrome/70.0.3538.1...
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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 # # U...
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import math import unittest from transformers import BioGptConfig, 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_co...
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from __future__ import annotations import inspect import unittest from transformers import ViTConfig from transformers.testing_utils import require_tf, require_vision, slow from transformers.utils import cached_property, is_tf_available, is_vision_available from ...test_configuration_common im...
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from typing import TYPE_CHECKING from ...utils import ( OptionalDependencyNotAvailable, _LazyModule, is_tf_available, is_torch_available, is_vision_available, ) SCREAMING_SNAKE_CASE__ : Any = { """configuration_mobilevit""": ["""MOBILEVIT_PRETRAINED_CON...
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from functools import lru_cache @lru_cache def _lowerCamelCase ( __lowerCamelCase ) -> int: '''simple docstring''' if num < 0: raise ValueError("""Number should not be negative.""" ) return 1 if num in (0, 1) else num * factorial(num - ...
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import tempfile import torch from diffusers import ( DEISMultistepScheduler, DPMSolverMultistepScheduler, DPMSolverSinglestepScheduler, UniPCMultistepScheduler, ) from .test_schedulers import SchedulerCommonTest class UpperCAmelCase_ ( __lowerCamelCase )...
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import argparse import hashlib # hashlib is only used inside the Test class import struct class UpperCAmelCase_ : def __init__( self , _lowerCAmelCase ): UpperCAmelCase__ : Any = data UpperCAmelCase__ : List[Any] ...
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import os import unittest from transformers import MobileBertTokenizer, MobileBertTokenizerFast from transformers.models.bert.tokenization_bert import ( VOCAB_FILES_NAMES, BasicTokenizer, WordpieceTokenizer, _is_control, _is_punctuation, _is_whitespace, ) from transfor...
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from importlib import import_module from .logging import get_logger SCREAMING_SNAKE_CASE__ : Union[str, Any] = get_logger(__name__) class UpperCAmelCase_ : def __init__( self , _lowerCAmelCase , _lowerCAmelCase=None ): UpperC...
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import random from .binary_exp_mod import bin_exp_mod def _lowerCamelCase ( __lowerCamelCase , __lowerCamelCase=1000 ) -> List[Any]: '''simple docstring''' if n < 2: return False if n % 2 == 0: return n == 2 # this ...
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from typing import List, Optional, Union from ...configuration_utils import PretrainedConfig from ...utils import logging SCREAMING_SNAKE_CASE__ : str = logging.get_logger(__name__) SCREAMING_SNAKE_CASE__ : Any = { """huggingface/informer-tourism-monthly""": ( ...
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import os from shutil import copyfile from typing import List, Optional, Tuple from ...tokenization_utils import AddedToken from ...tokenization_utils_fast import PreTrainedTokenizerFast from ...utils import is_sentencepiece_available, logging if is_sentencepiece_available(): from .toke...
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def _lowerCamelCase ( __lowerCamelCase ) -> bool: '''simple docstring''' if p < 2: raise ValueError("""p should not be less than 2!""" ) elif p == 2: return True UpperCAmelCase__ : Tuple = 4 UpperCAmelCase_...
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from ...configuration_utils import PretrainedConfig SCREAMING_SNAKE_CASE__ : Tuple = { """google/tapas-base-finetuned-sqa""": ( """https://huggingface.co/google/tapas-base-finetuned-sqa/resolve/main/config.json""" ), """google/tapas-base-finetuned-wtq""": ( ...
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from typing import TYPE_CHECKING from ...utils import ( OptionalDependencyNotAvailable, _LazyModule, is_tf_available, is_torch_available, is_vision_available, ) SCREAMING_SNAKE_CASE__ : Any = { """configuration_mobilevit""": ["""MOBILEVIT_PRETRAINED_CON...
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from typing import Dict import numpy as np from ..utils import add_end_docstrings, is_tf_available, is_torch_available, logging from .base import PIPELINE_INIT_ARGS, GenericTensor, Pipeline, PipelineException if is_tf_available(): import tensorflow as tf from ..tf_utils import ...
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from __future__ import annotations SCREAMING_SNAKE_CASE__ : List[str] = 8.988e9 # units = N * m^s * C^-2 def _lowerCamelCase ( __lowerCamelCase , __lowerCamelCase , __lowerCamelCase , __lowerCamelCase ) -> dict[str, float]: '''simpl...
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from __future__ import annotations from math import pi def _lowerCamelCase ( __lowerCamelCase , __lowerCamelCase , __lowerCamelCase ) -> dict[str, float]: '''simple docstring''' if (inductance, frequency, reactance).count(0 ) != 1: ...
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class UpperCAmelCase_ : def __init__( self , _lowerCAmelCase ): # we need a list not a string, so do something to change the type UpperCAmelCase__ : Dict = arr.split(""",""" ) def __UpperCAmelCase ( self ): ...
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import numpy as np import torch import tqdm from ...models.unet_ad import UNetaDModel from ...pipelines import DiffusionPipeline from ...utils import randn_tensor from ...utils.dummy_pt_objects import DDPMScheduler class UpperCAmelCase_ ( __lowerCamelCase ): def...
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from ....configuration_utils import PretrainedConfig from ....utils import logging SCREAMING_SNAKE_CASE__ : List[str] = logging.get_logger(__name__) SCREAMING_SNAKE_CASE__ : Any = { """Visual-Attention-Network/van-base""": ( """https://huggingface.co/Visu...
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1
from __future__ import annotations SCREAMING_SNAKE_CASE__ : List[str] = 8.988e9 # units = N * m^s * C^-2 def _lowerCamelCase ( __lowerCamelCase , __lowerCamelCase , __lowerCamelCase , __lowerCamelCase ) -> dict[str, float]: '''simpl...
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import argparse import os import torch from transformers import FlavaImageCodebook, FlavaImageCodebookConfig def _lowerCamelCase ( __lowerCamelCase , __lowerCamelCase , __lowerCamelCase , __lowerCamelCase ) -> Any: '''simple docstring''' ...
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import os from itertools import chain from random import randrange, shuffle import pytest from .sola import PokerHand SCREAMING_SNAKE_CASE__ : Optional[int] = ( """4S 3H 2C 7S 5H""", """9D 8H 2C 6S 7H""", """2D 6D 9D TH 7D""", """TC 8C 2S JH 6C""", """JH 8...
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def _lowerCamelCase ( __lowerCamelCase ) -> int: '''simple docstring''' return 1 if digit in (0, 1) else (digit * factorial(digit - 1 )) def _lowerCamelCase ( __lowerCamelCase ) -> bool: '''simple docstring''' UpperCAmelCas...
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import argparse import json import math import os import time import traceback import zipfile from collections import Counter import requests def _lowerCamelCase ( __lowerCamelCase , __lowerCamelCase=None ) -> str: '''simple docstring''' UpperCAm...
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def _lowerCamelCase ( __lowerCamelCase = 100_0000 ) -> int: '''simple docstring''' UpperCAmelCase__ : Tuple = [i - 1 for i in range(limit + 1 )] for i in range(2 , limit + 1 ): if phi[i] == i - 1: for j ...
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import string def _lowerCamelCase ( __lowerCamelCase ) -> None: '''simple docstring''' for key in range(len(string.ascii_uppercase ) ): UpperCAmelCase__ : Union[str, Any] = """""" for symbol in message: ...
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from ...configuration_utils import PretrainedConfig from ...utils import logging SCREAMING_SNAKE_CASE__ : Dict = logging.get_logger(__name__) SCREAMING_SNAKE_CASE__ : Tuple = { """google/realm-cc-news-pretrained-embedder""": ( """https://huggingface.co/go...
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def _lowerCamelCase ( __lowerCamelCase = 6008_5147_5143 ) -> int: '''simple docstring''' try: UpperCAmelCase__ : Union[str, Any] = int(__lowerCamelCase ) except (TypeError, ValueError): raise TypeError("""Parameter n mus...
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import gc import unittest from parameterized import parameterized from diffusers import FlaxUNetaDConditionModel from diffusers.utils import is_flax_available from diffusers.utils.testing_utils import load_hf_numpy, require_flax, slow if is_flax_available(): import jax import j...
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import json import sys def _lowerCamelCase ( __lowerCamelCase , __lowerCamelCase ) -> Optional[Any]: '''simple docstring''' with open(__lowerCamelCase , encoding="""utf-8""" ) as f: UpperCAmelCase__ : Any = json.loa...
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import json import os import tempfile import unittest import numpy as np from datasets import load_dataset 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 im...
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from __future__ import annotations SCREAMING_SNAKE_CASE__ : List[Any] = 10 def _lowerCamelCase ( __lowerCamelCase ) -> list[int]: '''simple docstring''' UpperCAmelCase__ : Any = 1 UpperCAmelCase__ : int = ...
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import os import unittest from transformers import MobileBertTokenizer, MobileBertTokenizerFast from transformers.models.bert.tokenization_bert import ( VOCAB_FILES_NAMES, BasicTokenizer, WordpieceTokenizer, _is_control, _is_punctuation, _is_whitespace, ) from transfor...
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import argparse import json from pathlib import Path import torch import torchaudio from datasets import load_dataset from huggingface_hub import hf_hub_download from transformers import ASTConfig, ASTFeatureExtractor, ASTForAudioClassification from transformers.utils import logging loggi...
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import argparse import re import requests import torch # git clone https://github.com/salesforce/BLIP.git from models.blip import blip_decoder from models.blip_itm import blip_itm from models.blip_vqa import blip_vqa from PIL import Image from torchvision import transforms from torchvision.t...
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import itertools import os from collections import Counter, defaultdict from concurrent.futures import ThreadPoolExecutor, as_completed import numpy as np import datasets from .execute import check_correctness SCREAMING_SNAKE_CASE__ : Dict = """\ @misc{chen2021evaluating, ...
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from ...configuration_utils import PretrainedConfig from ...utils import logging SCREAMING_SNAKE_CASE__ : Tuple = logging.get_logger(__name__) SCREAMING_SNAKE_CASE__ : List[Any] = { """MIT/ast-finetuned-audioset-10-10-0.4593""": ( """https://huggingface.c...
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def _lowerCamelCase ( __lowerCamelCase , __lowerCamelCase ) -> int: '''simple docstring''' return int(input_a == input_a == 0 ) def _lowerCamelCase ( ) -> None: '''simple docstring''' print("""Truth Table of NOR Gate:""" ...
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import warnings from ...utils import logging from .image_processing_glpn import GLPNImageProcessor SCREAMING_SNAKE_CASE__ : Dict = logging.get_logger(__name__) class UpperCAmelCase_ ( __lowerCamelCase ): def __init__( self , *_lowerCAmelCa...
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import os import tempfile import unittest import uuid from pathlib import Path from transformers.testing_utils import get_tests_dir, require_soundfile, require_torch, require_vision from transformers.tools.agent_types import AgentAudio, AgentImage, AgentText from transformers.utils import is_soun...
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import json from typing import List, Optional, Tuple from tokenizers import normalizers from ...tokenization_utils_base import BatchEncoding from ...tokenization_utils_fast import PreTrainedTokenizerFast from ...utils import PaddingStrategy, logging from .tokenization_realm import RealmTokenizer...
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from dataclasses import dataclass from typing import Dict, Optional, Union import torch import torch.nn.functional as F from torch import nn from ..configuration_utils import ConfigMixin, register_to_config from ..utils import BaseOutput from .attention import BasicTransformerBlock from .atten...
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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 # # U...
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import functools import gc import inspect import torch from .imports import is_npu_available, is_xpu_available def _lowerCamelCase ( *__lowerCamelCase ) -> Optional[int]: '''simple docstring''' if not isinstance(__lowerCamelCase , __lowerCamelCase ...
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from __future__ import annotations import inspect import unittest from transformers import ViTConfig from transformers.testing_utils import require_tf, require_vision, slow from transformers.utils import cached_property, is_tf_available, is_vision_available from ...test_configuration_common im...
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1
import dataclasses import json import warnings from dataclasses import dataclass, field from time import time from typing import List from ..utils import logging SCREAMING_SNAKE_CASE__ : int = logging.get_logger(__name__) def _lowerCamelCase ( __lowerCamelC...
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from functools import lru_cache @lru_cache def _lowerCamelCase ( __lowerCamelCase ) -> int: '''simple docstring''' if num < 0: raise ValueError("""Number should not be negative.""" ) return 1 if num in (0, 1) else num * factorial(num - ...
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import random import unittest import numpy as np from diffusers import ( DPMSolverMultistepScheduler, EulerAncestralDiscreteScheduler, EulerDiscreteScheduler, LMSDiscreteScheduler, OnnxStableDiffusionImgaImgPipeline, PNDMScheduler, ) from diffusers.utils import float...
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import argparse import hashlib # hashlib is only used inside the Test class import struct class UpperCAmelCase_ : def __init__( self , _lowerCAmelCase ): UpperCAmelCase__ : Any = data UpperCAmelCase__ : List[Any] ...
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SCREAMING_SNAKE_CASE__ : dict[tuple[int, int, int], int] = {} def _lowerCamelCase ( __lowerCamelCase , __lowerCamelCase , __lowerCamelCase ) -> int: '''simple docstring''' # if we are absent twice, or late 3 consecutive days, # ...
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from importlib import import_module from .logging import get_logger SCREAMING_SNAKE_CASE__ : Union[str, Any] = get_logger(__name__) class UpperCAmelCase_ : def __init__( self , _lowerCAmelCase , _lowerCAmelCase=None ): UpperC...
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import argparse import json import os import fairseq import torch from torch import nn from transformers import ( SpeechaTextaConfig, SpeechaTextaForCausalLM, SpeechaTextaTokenizer, SpeechEncoderDecoderConfig, SpeechEncoderDecoderModel, WavaVecaConfig, WavaVeca...
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from typing import List, Optional, Union from ...configuration_utils import PretrainedConfig from ...utils import logging SCREAMING_SNAKE_CASE__ : str = logging.get_logger(__name__) SCREAMING_SNAKE_CASE__ : Any = { """huggingface/informer-tourism-monthly""": ( ...
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from ...configuration_utils import PretrainedConfig from ...utils import logging SCREAMING_SNAKE_CASE__ : List[Any] = logging.get_logger(__name__) SCREAMING_SNAKE_CASE__ : List[str] = { """weiweishi/roc-bert-base-zh""": """https://huggingface.co/weiweishi/roc-bert...
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def _lowerCamelCase ( __lowerCamelCase ) -> bool: '''simple docstring''' if p < 2: raise ValueError("""p should not be less than 2!""" ) elif p == 2: return True UpperCAmelCase__ : Tuple = 4 UpperCAmelCase_...
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1