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from .configuration_bert_masked import MaskedBertConfig from .modeling_bert_masked import ( MaskedBertForMultipleChoice, MaskedBertForQuestionAnswering, MaskedBertForSequenceClassification, MaskedBertForTokenClassification, MaskedBertModel, ) from .modules import *
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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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"""simple docstring""" from __future__ import annotations from typing import TypedDict class SCREAMING_SNAKE_CASE__ ( __lowerCamelCase ): _a = 42 _a = 42 def lowercase (snake_case__ : Optional[int] ) -> list[str]: '''sim...
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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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"""simple docstring""" import argparse import json import math import os import time import traceback import zipfile from collections import Counter import requests def UpperCAmelCase__ ( SCREAMING_SNAKE_CASE : str , SCREAMING_SNAKE_CASE : Optional[int]=None ): '''simple ...
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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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"""simple docstring""" import qiskit def __magic_name__ ( lowercase = 2 ): SCREAMING_SNAKE_CASE_: str =qubits # Using Aer's simulator SCREAMING_SNAKE_CASE_: Tuple =qiskit.Aer.get_backend("""aer_simulator""" ) # Creating a Quantum Circuit acting on t...
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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 unittest import numpy as np import torch from diffusers import DDIMPipeline, DDIMScheduler, UNetaDModel from diffusers.utils.testing_utils import enable_full_determinism, require_torch_gpu, slow, torch_device from ..pipeline_params import UNCONDITIONAL_IMAGE_GENERATION_BATCH_PARAMS, UNCONDITIONAL_IMAGE_...
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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 .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, SingleSentenceClass...
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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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UpperCamelCase_ = {} def SCREAMING_SNAKE_CASE ( snake_case__ , snake_case__ , snake_case__ ) -> int: # if we are absent twice, or late 3 consecutive days, # no further prize strings are possible if late == 3 or absent == 2: return 0 # if we have no days ...
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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 ...configuration_utils import PretrainedConfig from ...utils import logging UpperCamelCase : Optional[int] = logging.get_logger(__name__) UpperCamelCase : List[str] = { """facebook/s2t-small-librispeech-asr""": ( """https://huggingface.co/facebook/s2t-small...
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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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'''simple docstring''' import functools import operator from ...configuration_utils import PretrainedConfig from ...utils import logging _UpperCAmelCase : Dict = logging.get_logger(__name__) _UpperCAmelCase : int = { """microsoft/unispeech-large-1500h-cv""": ( """https://huggingface.co/microso...
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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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'''simple docstring''' from ...configuration_utils import PretrainedConfig from ...utils import logging UpperCAmelCase : Optional[int] = logging.get_logger(__name__) UpperCAmelCase : Union[str, Any] = { """studio-ousia/luke-base""": """https://huggingface.co/studio-ousia/luke-base/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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'''simple docstring''' def A_ ( _lowerCAmelCase : Dict = 600851475143 ): """simple docstring""" try: _lowerCamelCase : Union[str, Any] = int(__lowerCamelCase ) except (TypeError, ValueError): raise TypeError("Parameter n must be int...
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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 shutil import tempfile import unittest from transformers import ( SPIECE_UNDERLINE, AddedToken, BatchEncoding, NllbTokenizer, NllbTokenizerFast, is_torch_available, ) from transformers.testing_utils import ( get_tests_dir, nested_simplify, require_sentencepiece...
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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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"""simple docstring""" from typing import TYPE_CHECKING from ...utils import ( OptionalDependencyNotAvailable, _LazyModule, is_tf_available, is_torch_available, is_vision_available, ) a = { """configuration_efficientformer""": [ """EFFICIENTFORMER_PRETRAINED_CONFIG_ARC...
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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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"""simple docstring""" from __future__ import annotations def UpperCAmelCase__ ( SCREAMING_SNAKE_CASE : Optional[Any] , SCREAMING_SNAKE_CASE : List[str] , SCREAMING_SNAKE_CASE : List[Any] , SCREAMING_SNAKE_CASE : List[Any] ): '''simple docstring''' if (...
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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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"""simple docstring""" import enum import os from hashlib import shaaaa from typing import Optional from .. import config from .logging import get_logger _UpperCAmelCase = get_logger(__name__) class a ( enum.Enum ): UpperCamelCase : Dict = 'all_checks...
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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 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 transformers.testing_utils i...
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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 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 .attention_pro...
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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 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 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 json from typing import List, Optional, Tuple from tokenizers import normalizers from ...tokenization_utils_fast import PreTrainedTokenizerFast from .tokenization_electra import ElectraTokenizer UpperCamelCase : List[str] = {"""vocab_file""": """vocab.txt""", """tokenizer_file""": """t...
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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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'''simple docstring''' from numpy import exp, pi, sqrt def UpperCamelCase ( lowercase_ : str , lowercase_ : List[Any] = 0.0 , lowercase_ : Dict = 1.0 ) -> int: '''simple docstring''' return 1 / sqrt(2 * pi * sigma**2 ) * exp(-((x - mu) ** 2) / (2 * sigm...
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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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'''simple docstring''' from collections import OrderedDict from typing import Mapping from ...configuration_utils import PretrainedConfig from ...onnx import OnnxConfig from ...utils import logging UpperCAmelCase : Any = logging.get_logger(__name__) UpperCAmelCase : Tuple = { """fac...
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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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'''simple docstring''' 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__ ( __lowerCame...
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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 logging from dataclasses import dataclass, field from typing import Optional from seqaseq_trainer import arg_to_scheduler from transformers import TrainingArguments A_ = logging.getLogger(__name__) @dataclass class __lowercase ( __lowerCamelCase ): lowerca...
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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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"""simple docstring""" from typing import TYPE_CHECKING from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available, is_vision_available a = { """configuration_mobilenet_v2""": [ """MOBILENET_V2_PRETRAINED_CONFIG_ARCHIVE_MAP""", """MobileNetV2Config""", ...
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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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"""simple docstring""" # 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....
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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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"""simple docstring""" import copy import inspect import unittest import numpy as np from huggingface_hub import hf_hub_download from transformers import TimesformerConfig from transformers.models.auto import get_values from transformers.testing_utils import require_torch, require_vision, slow, torc...
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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 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_common import Mode...
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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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def _lowerCAmelCase ( lowerCAmelCase_ :List[str] )->list: '''simple docstring''' snake_case_ = [0] * len(__lowerCamelCase ) for i in range(1 , len(__lowerCamelCase ) ): # use last results for better performance - dynamic programming ...
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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 warnings from ...utils import logging from .image_processing_glpn import GLPNImageProcessor UpperCamelCase_ = logging.get_logger(__name__) class _SCREAMING_SNAKE_CASE ( __lowerCamelCase ): def __init__(self , *UpperCAmelCase , **UpperCAmelCase): '''simple docst...
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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 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 A__ ( __lowerCamelCase ): """simple docstring""" def __init__( self : List...
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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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'''simple docstring''' import unittest from parameterized import parameterized from transformers import AutoTokenizer, GPTNeoXConfig, is_torch_available, set_seed from transformers.testing_utils import require_torch, slow, torch_device from ...generation.test_utils import GenerationTesterMixin from ...test_configu...
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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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'''simple docstring''' import functools import gc import inspect import torch from .imports import is_npu_available, is_xpu_available def a__ ( *a__ ): """simple docstring""" if not isinstance(__lowerCamelCase , __lowerCamelCase ): __SCREAMING_SNAKE_CASE = lis...
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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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'''simple docstring''' UpperCAmelCase_ : Union[str, Any] = """0.21.0""" from .accelerator import Accelerator from .big_modeling import ( cpu_offload, cpu_offload_with_hook, disk_offload, dispatch_model, init_empty_weights, init_on_device, load_checkpoint_and_dispatch, ) f...
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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 random from .binary_exp_mod import bin_exp_mod def __UpperCAmelCase ( UpperCAmelCase, UpperCAmelCase=1000 )-> List[Any]: """simple docstring""" if n < 2: return False if n % 2 == 0: return n == 2 # this means n is...
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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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"""simple docstring""" from itertools import permutations def lowercase (snake_case__ : List[Any] ) -> bool: '''simple docstring''' if num[3] % 2 != 0: return False if (num[2] + num[3] + num[4]) % 3 != 0: return False if num[5] % 5 != 0: ...
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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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"""simple docstring""" SCREAMING_SNAKE_CASE__ = 8.3_14_45_98 def UpperCAmelCase__ ( SCREAMING_SNAKE_CASE : Dict , SCREAMING_SNAKE_CASE : Union[str, Any] ): '''simple docstring''' if temperature < 0: raise Exception("""Temperature cannot be less tha...
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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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"""simple docstring""" import os from tempfile import TemporaryDirectory from unittest import TestCase import pytest from absl.testing import parameterized from datasets import config from datasets.arrow_reader import HF_GCP_BASE_URL from datasets.builder import DatasetBuilder from datasets.dataset...
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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 dataclasses import dataclass from typing import List, Optional, Union import numpy as np import PIL from PIL import Image from ...utils import ( BaseOutput, OptionalDependencyNotAvailable, is_flax_available, is_k_diffusion_available, is_k_diffusion_version, is_onnx_available, is...
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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 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 Accelerator, ...
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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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def SCREAMING_SNAKE_CASE ( snake_case__ , snake_case__ , snake_case__ ) -> float: __UpperCAmelCase =(num_of_terms / 2) * (2 * first_term + (num_of_terms - 1) * common_diff) # formula for sum of series return total def SCREAMING_SNAKE_CASE ( ) -> str: pri...
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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 os import re # All paths are set with the intent you should run this script from the root of the repo with the command # python utils/check_dummies.py UpperCamelCase : int = """src/diffusers""" # Matches is_xxx_available() UpperCamelCase : Union[str, Any] ...
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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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'''simple docstring''' 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_ut...
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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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'''simple docstring''' from __future__ import annotations from collections.abc import Iterator class lowerCAmelCase__ : """simple docstring""" def __init__( self : Any , __SCREAMING_SNAKE_CASE : str ) -> str: """simple docstring""" __SCREAMING_SNAKE...
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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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'''simple docstring''' from typing import TYPE_CHECKING from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available UpperCAmelCase_ : Any = { """configuration_blip_2""": [ """BLIP_2_PRETRAINED_CONFIG_ARCHIVE_MAP""", """Blip2Config""", """Blip2QF...
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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 tempfile import unittest from make_student import create_student_by_copying_alternating_layers from transformers import AutoConfig from transformers.file_utils import cached_property from transformers.testing_utils import require_torch A_ = """sshleifer/bart-tiny-random""" A_ = """pa...
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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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"""simple docstring""" a = [ """Audio""", """Array2D""", """Array3D""", """Array4D""", """Array5D""", """ClassLabel""", """Features""", """Sequence""", """Value""", """Image""", """Translation""", """TranslationVariableLanguages""", ] from .audio import Au...
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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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"""simple docstring""" import argparse import json import os import fairseq import torch from torch import nn from transformers import ( SpeechaTextaConfig, SpeechaTextaForCausalLM, SpeechaTextaTokenizer, SpeechEncoderDecoderConfig, SpeechEncoderDecoderModel, WavaVecaConfig, Wav...
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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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"""simple docstring""" 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 __magic_name__ ( lo...
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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 re import tempfile from pathlib import Path import pytest import yaml from datasets.utils.readme import ReadMe # @pytest.fixture # def example_yaml_structure(): lowerCAmelCase_ = yaml.safe_load( "\\nname: \"\"\nallow_empty: false\nallow_empty_text: true\nsubsections:\n - name: \"Dataset Card f...
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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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class __lowerCAmelCase : """simple docstring""" def __init__( self : str , _lowerCAmelCase : int ) -> Tuple: """simple docstring""" # we need a list not a string, so do something to change the type snake_case_ ...
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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 os import torch from transformers.utils import WEIGHTS_NAME UpperCamelCase_ = ["""small""", """medium""", """large"""] UpperCamelCase_ = """lm_head.decoder.weight""" UpperCamelCase_ = """lm_head.weight""" def SCREAMING_SNAKE_CASE ( snake_case__ , snake_c...
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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 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 UpperCamelCase : Dict = logging.get_logger(__name__) Upp...
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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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'''simple docstring''' import subprocess import sys from transformers import BertConfig, BertModel, BertTokenizer, pipeline from transformers.testing_utils import TestCasePlus, require_torch class __magic_name__ ( __lowerCamelCase ): @require_torch def _A( self ): # this test...
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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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'''simple docstring''' 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 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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'''simple docstring''' 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 UpperCAmelCase_ : Dict = """\ @misc{chen2021evaluating, t...
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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 typing import TYPE_CHECKING from ...utils import ( OptionalDependencyNotAvailable, _LazyModule, is_flax_available, is_tf_available, is_tokenizers_available, is_torch_available, ) A_ = { """configuration_blenderbot_small""": [ """BLENDERBOT_SMALL_PRETRAINE...
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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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"""simple docstring""" import argparse import logging import os from pathlib import Path from typing import Any, Dict import pytorch_lightning as pl from pytorch_lightning.utilities import rank_zero_info from transformers import ( AdamW, AutoConfig, AutoModel, AutoModelForPreTraining, ...
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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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"""simple docstring""" import json import pathlib import unittest import numpy as np from transformers.testing_utils import require_torch, require_vision, slow from transformers.utils import is_torch_available, is_vision_available from ...test_image_processing_common import ImageProcessingSavingTestMixin,...
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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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"""simple docstring""" import random import unittest import numpy as np from diffusers import ( DPMSolverMultistepScheduler, EulerAncestralDiscreteScheduler, EulerDiscreteScheduler, LMSDiscreteScheduler, OnnxStableDiffusionImgaImgPipeline, PNDMScheduler, ) from diffusers....
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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 __future__ import annotations from typing import Generic, TypeVar lowerCAmelCase_ = TypeVar("T") class A (Generic[T] ): def __init__( self , lowercase_ ) -> Optional[int]: '''simple docstring''' _snake_case : Union[str, Any] ...
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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 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 array_ca...
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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 unittest import numpy as np import torch from diffusers import ScoreSdeVePipeline, ScoreSdeVeScheduler, UNetaDModel from diffusers.utils.testing_utils import enable_full_determinism, require_torch, slow, torch_device enable_full_determinism() class _SCREAMING_SNAKE_CASE ( unittest.TestCa...
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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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from ...configuration_utils import PretrainedConfig from ...utils import logging UpperCamelCase : List[Any] = logging.get_logger(__name__) UpperCamelCase : List[str] = { """weiweishi/roc-bert-base-zh""": """https://huggingface.co/weiweishi/roc-bert-base-zh/resolve/main/...
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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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'''simple docstring''' from collections import namedtuple _UpperCAmelCase : Dict = namedtuple('''from_to''', '''from_ to''') _UpperCAmelCase : Optional[Any] = { """cubicmeter""": from_to(1, 1), """litre""": from_to(0.001, 10_00), """kilolitre""": from_to(1, 1), """gallon""": from_to(0.0_0454...
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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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'''simple docstring''' import itertools import json import linecache import os import pickle import re import socket import string from collections import Counter from logging import getLogger from pathlib import Path from typing import Callable, Dict, Iterable, List import git import torch from torch.utils.data ...
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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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'''simple docstring''' import string def A_ ( _lowerCAmelCase : int ): """simple docstring""" for key in range(len(string.ascii_uppercase ) ): _lowerCamelCase : Union[str, Any] = """""" for symbol in message: i...
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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 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 __lowercase ( __l...
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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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"""simple docstring""" from collections import Counter from pathlib import Path from typing import Optional, Tuple import yaml class SCREAMING_SNAKE_CASE__ ( yaml.SafeLoader ): def __lowercase ( self : List[Any] , lowerCAmelCase : Dict ...
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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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"""simple docstring""" from typing import Dict, List, Optional, Union import numpy as np from ...image_processing_utils import BaseImageProcessor, BatchFeature, get_size_dict from ...image_transforms import ( center_crop, get_resize_output_image_size, normalize, rescale, resize, to_...
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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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"""simple docstring""" from ....configuration_utils import PretrainedConfig from ....utils import logging _UpperCAmelCase = logging.get_logger(__name__) _UpperCAmelCase = { """Visual-Attention-Network/van-base""": ( """https://huggingface.co/Visual-Attention-Network/van-base/...
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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 from typing import Dict, List, Optional, Tuple from ...tokenization_utils import PreTrainedTokenizer from ...utils import logging lowerCAmelCase_ = logging.get_logger(__name__) lowerCAmelCase_ = { """vocab_file""": """vocab.json""", """tokenizer_config_file""": """tokenize...
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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 typing import Any class __lowerCAmelCase : """simple docstring""" def __init__( self : int , _lowerCAmelCase : int ) -> Any: """simple docstring""" snake_case_ = data snake_case_ = ...
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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 unittest from transformers import MODEL_FOR_ZERO_SHOT_OBJECT_DETECTION_MAPPING, is_vision_available, pipeline from transformers.testing_utils import ( is_pipeline_test, nested_simplify, require_tf, require_torch, require_vision, slow, ) from .test_pipelines_common import ANY if is...
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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 __future__ import annotations def UpperCamelCase_ ( __a , __a , __a , __a , __a , ) -> None: a__ : Any = len(__lowerCamelCase ) # If row is equal to the size of the board it means there are a queen in each row in # the current board (possible_bo...
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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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'''simple docstring''' import os from typing import Dict, List, Tuple, TypeVar, Union _UpperCAmelCase : Any = TypeVar('''T''') _UpperCAmelCase : List[Any] = Union[List[T], Tuple[T, ...]] _UpperCAmelCase : int = Union[T, List[T], Dict[str, T]] _UpperCAmelCase : Optional[int] = Union[str, bytes, os.P...
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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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'''simple docstring''' import requests UpperCAmelCase : Optional[Any] = """""" # <-- Put your OpenWeatherMap appid here! UpperCAmelCase : Optional[int] = """https://api.openweathermap.org/data/2.5/""" def a__ ( a__ = "Chicago" , a__ = APPID ): """simple docst...
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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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'''simple docstring''' import unittest from diffusers.pipelines.pipeline_utils import is_safetensors_compatible class UpperCAmelCase__ ( unittest.TestCase ): def lowerCamelCase_ ( self : Optional[Any] ): _lowerCamelCase : Any = [ """safety_ch...
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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 __UpperCAmelCase ( UpperCAmelCase, UpperCAmelCase )-> int: """simple docstring""" lowercase = 1 # To kept the Calculated Value # Since C(n, k) = C(n, n-k) if k > (n - k): lowercase = n - k # Calculate C(n,k) for i in...
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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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"""simple docstring""" from __future__ import annotations a = 1_0 def lowercase (snake_case__ : Any ) -> list[int]: '''simple docstring''' lowerCAmelCase = 1 lowerCAmelCase = max(__lowerCamelCase ) while placement <= max_digit: # d...
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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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"""simple docstring""" import argparse import intel_extension_for_pytorch as ipex import torch from diffusers import DPMSolverMultistepScheduler, StableDiffusionPipeline SCREAMING_SNAKE_CASE__ = argparse.ArgumentParser("Stable Diffusion script with intel optimization", add_help=False) parser.add_argum...
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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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"""simple docstring""" from typing import TYPE_CHECKING from ...utils import ( OptionalDependencyNotAvailable, _LazyModule, is_torch_available, ) _UpperCAmelCase = { """configuration_gpt_bigcode""": ["""GPT_BIGCODE_PRETRAINED_CONFIG_ARCHIVE_MAP""", """GPTBigCodeConfig"""], }...
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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 os from shutil import copyfile from typing import List, Optional, Tuple from ...tokenization_utils import AddedToken from ...tokenization_utils_fast import PreTrainedTokenizerFast from ...utils import is_sentencepiece_available, logging if is_sentencepiece_available(): from .tokenization_albert impor...
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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 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_available, ...
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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 argparse import hashlib # hashlib is only used inside the Test class import struct class _SCREAMING_SNAKE_CASE : def __init__(self , UpperCAmelCase): '''simple docstring''' __UpperCAmelCase =data __UpperCAmelCase =[0x67_452_301, 0xEF_CDA_B89, 0x98_BAD...
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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.transforms.functional im...
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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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'''simple docstring''' import glob import os import random from string import ascii_lowercase, digits import cva _UpperCAmelCase : Optional[int] = """""" _UpperCAmelCase : Union[str, Any] = """""" _UpperCAmelCase : Any = """""" _UpperCAmelCase : List[Any] = 1 # (0 is vertical, 1 is horizontal) d...
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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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'''simple docstring''' import warnings from ...utils import logging from .image_processing_flava import FlavaImageProcessor UpperCAmelCase : Optional[Any] = logging.get_logger(__name__) class lowerCAmelCase__ ( __lowerCamelCase ): """simple docstring""" def __init__( self ...
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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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'''simple docstring''' # 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/li...
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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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def __UpperCAmelCase ( UpperCAmelCase )-> float: """simple docstring""" if not nums: # Makes sure that the list is not empty raise ValueError('''List is empty''' ) lowercase = sum(__lowerCamelCase ) / len(__lowerCamelCase ...
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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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"""simple docstring""" from math import factorial class SCREAMING_SNAKE_CASE__ : def __init__( self : List[str] , lowerCAmelCase : List[str] , lowerCAmelCase : Optional[int] ): lowerCAmelCase = real if isinst...
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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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0
"""simple docstring""" import unittest from transformers import DebertaConfig, is_torch_available from transformers.testing_utils import require_sentencepiece, require_tokenizers, require_torch, slow, torch_device from ...test_configuration_common import ConfigTester from ...test_modeling_common import Mod...
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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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"""simple docstring""" from collections import deque from .hash_table import HashTable class a ( __lowerCamelCase ): def __init__( self : Optional[Any] , *lowerCAmelCase : List[Any] , **lowerCAmelCase : Union[str, Any] ) -> int: ...
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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 math def A_ ( lowercase_ ) -> bool: if 1 < number < 4: # 2 and 3 are primes return True elif number < 2 or number % 2 == 0 or number % 3 == 0: # Negatives, 0, 1, all even numbers, all multiples of 3 are not primes r...
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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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def _lowerCAmelCase ( lowerCAmelCase_ :Dict , lowerCAmelCase_ :List[str] , lowerCAmelCase_ :Union[str, Any] , lowerCAmelCase_ :List[str] )->str: '''simple docstring''' global f # a global dp table for knapsack if f[i][j] < 0: if j < wt[i - 1]:...
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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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0
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_property from ....
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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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0
from dataclasses import dataclass, field from typing import TYPE_CHECKING, Any, ClassVar, Dict, List, Optional, Union import pyarrow as pa if TYPE_CHECKING: from .features import FeatureType @dataclass class A__ : """simple docstring""" _lowercase = 4_2 _lowercase = None ...
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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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0
'''simple docstring''' import unittest from datasets import load_dataset from transformers import BloomTokenizerFast from transformers.testing_utils import require_tokenizers from ...test_tokenization_common import TokenizerTesterMixin @require_tokenizers class __magic_name__ ( __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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0
'''simple docstring''' 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 RealmTok...
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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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'''simple docstring''' 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_modelin...
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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 time import unittest from transformers import is_torch_available from transformers.testing_utils import require_torch, torch_device from ..test_modeling_common import ids_tensor if is_torch_available(): import torch from transformers.generation import ( MaxLengthCriteria, ...
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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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0