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"""simple docstring""" from . import ( albert, align, altclip, audio_spectrogram_transformer, auto, autoformer, bark, bart, barthez, bartpho, beit, bert, bert_generation, bert_japanese, bertweet, big_bird, bigbird_pegasus, biogpt, bit,...
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"""simple docstring""" import random import timeit from functools import wraps from typing import Callable, Optional from ..configuration_utils import PretrainedConfig from ..models.auto.modeling_tf_auto import TF_MODEL_MAPPING, TF_MODEL_WITH_LM_HEAD_MAPPING from ..utils import is_pyanvml_available, is_tf_ava...
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"""simple docstring""" import re def __UpperCAmelCase ( snake_case_ : str ) -> Union[str, Any]: """simple docstring""" if len(re.findall("""[ATCG]""" , __lowerCamelCase ) ) != len(__lowerCamelCase ): raise ValueError("""Invalid Strand""" ) ...
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"""simple docstring""" from ...configuration_utils import PretrainedConfig from ...utils import logging SCREAMING_SNAKE_CASE : int = logging.get_logger(__name__) SCREAMING_SNAKE_CASE : Any = { '''transfo-xl-wt103''': '''https://huggingface.co/transfo-xl-wt103/resolve/main/c...
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"""simple docstring""" SCREAMING_SNAKE_CASE : int = 2_5_6 # Modulus to hash a string SCREAMING_SNAKE_CASE : List[Any] = 1_0_0_0_0_0_3 def __UpperCAmelCase ( snake_case_ : str , snake_case_ : str ) -> bool: """simple docstring""" ...
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"""simple docstring""" import math def __UpperCAmelCase ( snake_case_ : int ) -> list[int]: """simple docstring""" _lowerCAmelCase = [] _lowerCAmelCase = 2 _lowerCAmelCase = int(math.sqrt(snake_case_ ) ) # Size ...
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"""simple docstring""" import argparse import os import re import packaging.version SCREAMING_SNAKE_CASE : Dict = '''examples/''' SCREAMING_SNAKE_CASE : str = { '''examples''': (re.compile(R'''^check_min_version\(\"[^\"]+\"\)\s*$''', re.MULTILINE), '''check_min_version(\"V...
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"""simple docstring""" import glob import os import random from string import ascii_lowercase, digits import cva import numpy as np # Parrameters SCREAMING_SNAKE_CASE : Any = (7_2_0, 1_2_8_0) # Height, Width SCREAMING_SNAKE_CASE : List[str] = (0.4, 0.6) # if height or width lo...
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"""simple docstring""" from ...configuration_utils import PretrainedConfig from ...utils import logging SCREAMING_SNAKE_CASE : Dict = logging.get_logger(__name__) class __lowerCamelCase ( __lowercase ): __UpperCamelCase = '''timm_backbone''' def __init__...
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"""simple docstring""" # tests directory-specific settings - this file is run automatically # by pytest before any tests are run import sys import warnings from os.path import abspath, dirname, join # allow having multiple repository checkouts and not needing to remember to rerun # 'pip install -e .[dev]' w...
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"""simple docstring""" from dataclasses import asdict, dataclass from typing import Optional from ...configuration_utils import PretrainedConfig from ...utils import logging SCREAMING_SNAKE_CASE : List[str] = logging.get_logger(__name__) # TODO Update this SCREAMING_SNAKE_CASE : Any ...
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"""simple docstring""" # 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...
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"""simple docstring""" from __future__ import annotations from typing import Any def __UpperCAmelCase ( snake_case_ : list ) -> int: """simple docstring""" if not postfix_notation: return 0 _lowerCAmelCase = {'''+''', '''-''', '''*''', '''/'...
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"""simple docstring""" from math import isqrt def __UpperCAmelCase ( snake_case_ : int ) -> list[int]: """simple docstring""" _lowerCAmelCase = [True] * max_number for i in range(2 , isqrt(max_number - 1 ) + 1 ): if is_prime[i]: ...
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"""simple docstring""" from __future__ import annotations import csv import requests from bsa import BeautifulSoup def __UpperCAmelCase ( snake_case_ : str = "" ): """simple docstring""" _lowerCAmelCase = url or """https://www.imdb.com/chart/top/?ref_=nv_mv...
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"""simple docstring""" # 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...
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"""simple docstring""" import gc import random import unittest import numpy as np import torch from PIL import Image from diffusers import ( DDIMScheduler, KandinskyVaaImgaImgPipeline, KandinskyVaaPriorPipeline, UNetaDConditionModel, VQModel, ) from diffusers.utils import floats_tensor, l...
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"""simple docstring""" from __future__ import annotations import queue class __lowerCamelCase : def __init__(self , lowerCamelCase ): '''simple docstring''' _lowerCAmelCase = data _lowerCAmelCase = None _lowerCAmelCase = ...
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"""simple docstring""" import inspect import unittest import numpy as np from tests.test_modeling_common import floats_tensor from transformers import DetrConfig, MaskFormerConfig, SwinConfig, is_torch_available, is_vision_available from transformers.testing_utils import require_torch, require_torch_multi_gp...
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"""simple docstring""" from __future__ import annotations class __lowerCamelCase : def __init__(self , lowerCamelCase , lowerCamelCase ): '''simple docstring''' _lowerCAmelCase , _lowerCAmelCase = text, pattern _lowerCAmelCase , _low...
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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, ) SCREAMING_SNAKE_CASE : Optional[Any] = {'''configuration_deit''': ['''DEIT_PRETRAINED_CON...
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"""simple docstring""" import unittest import numpy as np import torch from diffusers import VersatileDiffusionImageVariationPipeline from diffusers.utils.testing_utils import load_image, require_torch_gpu, slow, torch_device SCREAMING_SNAKE_CASE : List[str] = False class __lowerCamelCase...
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"""simple docstring""" from typing import TYPE_CHECKING from ...utils import ( OptionalDependencyNotAvailable, _LazyModule, is_sentencepiece_available, is_tokenizers_available, is_torch_available, ) SCREAMING_SNAKE_CASE : str = { '''configuration_llama''': ['''LLAMA_PR...
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"""simple docstring""" import gc import unittest import numpy as np import torch from diffusers import AutoencoderKL, DDIMScheduler, DiTPipeline, DPMSolverMultistepScheduler, TransformeraDModel from diffusers.utils import is_xformers_available, load_numpy, slow, torch_device from diffusers.utils.testing_util...
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"""simple docstring""" def __UpperCAmelCase ( snake_case_ : int , snake_case_ : int ) -> int: """simple docstring""" return x if y == 0 else greatest_common_divisor(UpperCAmelCase__ , x % y ) def __UpperCAmelCase ( snake_case_ : int...
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"""simple docstring""" from operator import delitem, getitem, setitem import pytest from data_structures.hashing.hash_map import HashMap def __UpperCAmelCase ( snake_case_ : Union[str, Any] ) -> Dict: """simple docstring""" return getitem, k def __UpperCAm...
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"""simple docstring""" import os from pathlib import Path import numpy as np import pytest from pack_dataset import pack_data_dir from parameterized import parameterized from save_len_file import save_len_file from torch.utils.data import DataLoader from transformers import AutoTokenizer from transformers.mo...
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"""simple docstring""" def __UpperCAmelCase ( snake_case_ : int , snake_case_ : list[int] , snake_case_ : int ) -> int: """simple docstring""" def count_of_possible_combinations(snake_case_ : int ) -> int: if target < 0: r...
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"""simple docstring""" import warnings from ...utils import logging from .image_processing_segformer import SegformerImageProcessor SCREAMING_SNAKE_CASE : Dict = logging.get_logger(__name__) class __lowerCamelCase ( lowercase__ ): def __init__(self , *lowerCamelCas...
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"""simple docstring""" from __future__ import annotations import string from itertools import cycle, product from pathlib import Path SCREAMING_SNAKE_CASE : str = ( string.ascii_letters + string.digits + string.punctuation + string.whitespace ) SCREAMING_SNAKE_CASE : list[int] ...
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"""simple docstring""" import logging import os import threading import time try: import warnings except ImportError: SCREAMING_SNAKE_CASE : Tuple = None try: import msvcrt except ImportError: SCREAMING_SNAKE_CASE : List[str] = None try: import fcntl except ImportErr...
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"""simple docstring""" def __UpperCAmelCase ( snake_case_ : int = 1000000 ) -> int: """simple docstring""" _lowerCAmelCase = limit + 1 _lowerCAmelCase = [0] * limit for first_term in range(1 , snake_case_ ): for n in range(sn...
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"""simple docstring""" from __future__ import annotations from math import pi, sqrt def __UpperCAmelCase ( snake_case_ : Union[str, Any] , snake_case_ : Dict ) -> Optional[Any]: """simple docstring""" if inductance <= 0: ...
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"""simple docstring""" from functools import reduce SCREAMING_SNAKE_CASE : int = ( '''73167176531330624919225119674426574742355349194934''' '''96983520312774506326239578318016984801869478851843''' '''85861560789112949495459501737958331952853208805511''' '''1254069874715852386305...
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"""simple docstring""" import unittest import numpy as np from transformers.testing_utils import require_torch, require_vision from transformers.utils import is_torch_available, is_vision_available from ...test_image_processing_common import ImageProcessingSavingTestMixin, prepare_image_inputs if is_torch...
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"""simple docstring""" def __UpperCAmelCase ( snake_case_ : int = 600851475143 ) -> int: """simple docstring""" try: _lowerCAmelCase = int(snake_case_ ) except (TypeError, ValueError): raise TypeError("""Parameter n must be int or castable ...
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"""simple docstring""" import argparse import torch from transformers import GPTaLMHeadModel, RobertaForMaskedLM if __name__ == "__main__": SCREAMING_SNAKE_CASE : List[Any] = argparse.ArgumentParser( description=( '''Extraction some layers of the full Ro...
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"""simple docstring""" import logging import os import sys from dataclasses import dataclass, field from typing import Optional from seqaseq_trainer import SeqaSeqTrainer from seqaseq_training_args import SeqaSeqTrainingArguments import transformers from transformers import ( AutoConfig, AutoModelFor...
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"""simple docstring""" import copy import os from collections import OrderedDict from typing import TYPE_CHECKING, Any, Dict, Mapping, Optional, Union if TYPE_CHECKING: from ...processing_utils import ProcessorMixin from ...utils import TensorType from ...configuration_utils import PretrainedConfig fr...
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"""simple docstring""" from typing import TYPE_CHECKING # rely on isort to merge the imports from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available SCREAMING_SNAKE_CASE : List[Any] = {'''configuration_focalnet''': ['''FOCALNET_PRETRAINED_CONFIG_ARCHIVE_MAP''', ''...
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import os import tempfile import unittest from transformers.models.marian.convert_marian_tatoeba_to_pytorch import DEFAULT_REPO, TatoebaConverter from transformers.testing_utils import slow from transformers.utils import cached_property @unittest.skipUnless(os.path.exists(__lowerCamelCase ) , 'Tato...
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"""simple docstring""" import unittest import numpy as np from transformers.testing_utils import require_torch, require_vision from transformers.utils import is_torch_available, is_vision_available from ...test_image_processing_common import ImageProcessingSavingTestMixin, prepare_image_inputs if is_torch...
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import gc import unittest import numpy as np import torch from transformers import CLIPTextConfig, CLIPTextModel, CLIPTokenizer from diffusers import TransformeraDModel, VQDiffusionPipeline, VQDiffusionScheduler, VQModel from diffusers.pipelines.vq_diffusion.pipeline_vq_diffusion import LearnedClassifierFreeSampl...
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"""simple docstring""" def __UpperCAmelCase ( snake_case_ : list ) -> list: """simple docstring""" for i in range(len(snake_case_ ) - 1 , 0 , -1 ): _lowerCAmelCase = False for j in range(snake_case_ , 0 , -1 ): ...
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"""simple docstring""" import gc import random import unittest import numpy as np import torch from PIL import Image from transformers import XLMRobertaTokenizerFast from diffusers import DDIMScheduler, KandinskyImgaImgPipeline, KandinskyPriorPipeline, UNetaDConditionModel, VQModel from diffusers.pipelines.k...
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"""simple docstring""" import random import timeit from functools import wraps from typing import Callable, Optional from ..configuration_utils import PretrainedConfig from ..models.auto.modeling_tf_auto import TF_MODEL_MAPPING, TF_MODEL_WITH_LM_HEAD_MAPPING from ..utils import is_pyanvml_available, is_tf_ava...
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"""simple docstring""" import math import flax.linen as nn import jax.numpy as jnp def __UpperCAmelCase ( snake_case_ : jnp.ndarray , snake_case_ : int , snake_case_ : float = 1 , snake_case_ : float = 1 , snake_case_ : float = 1.0e4 , s...
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"""simple docstring""" from ...configuration_utils import PretrainedConfig from ...utils import logging SCREAMING_SNAKE_CASE : int = logging.get_logger(__name__) SCREAMING_SNAKE_CASE : Any = { '''transfo-xl-wt103''': '''https://huggingface.co/transfo-xl-wt103/resolve/main/c...
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"""simple docstring""" import os from shutil import copyfile from typing import Any, Dict, List, Optional, Tuple import sentencepiece as spm from ...tokenization_utils import AddedToken, PreTrainedTokenizer from ...utils import logging SCREAMING_SNAKE_CASE : Any = logging.get_logger(__name__...
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"""simple docstring""" import math def __UpperCAmelCase ( snake_case_ : int ) -> list[int]: """simple docstring""" _lowerCAmelCase = [] _lowerCAmelCase = 2 _lowerCAmelCase = int(math.sqrt(snake_case_ ) ) # Size ...
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"""simple docstring""" from abc import ABC, abstractmethod from argparse import ArgumentParser class __lowerCamelCase ( __snake_case ): @staticmethod @abstractmethod def A__ (lowerCamelCase ): '''simple docstring''' raise NotImplementedError() ...
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"""simple docstring""" import glob import os import random from string import ascii_lowercase, digits import cva import numpy as np # Parrameters SCREAMING_SNAKE_CASE : Any = (7_2_0, 1_2_8_0) # Height, Width SCREAMING_SNAKE_CASE : List[str] = (0.4, 0.6) # if height or width lo...
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"""simple docstring""" import random import timeit from functools import wraps from typing import Callable, Optional from ..configuration_utils import PretrainedConfig from ..models.auto.modeling_tf_auto import TF_MODEL_MAPPING, TF_MODEL_WITH_LM_HEAD_MAPPING from ..utils import is_pyanvml_available, is_tf_ava...
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"""simple docstring""" # tests directory-specific settings - this file is run automatically # by pytest before any tests are run import sys import warnings from os.path import abspath, dirname, join # allow having multiple repository checkouts and not needing to remember to rerun # 'pip install -e .[dev]' w...
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"""simple docstring""" import warnings from ...processing_utils import ProcessorMixin from ...tokenization_utils_base import BatchEncoding class __lowerCamelCase ( SCREAMING_SNAKE_CASE__ ): __UpperCamelCase = ['image_processor', 'tokenizer'] __UpperCamelCase = '...
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"""simple docstring""" # 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...
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"""simple docstring""" def __UpperCAmelCase ( snake_case_ : Optional[int] ) -> int: """simple docstring""" if num < 0: return False _lowerCAmelCase = num _lowerCAmelCase = 0 while num > 0: _lowerCAmelCase = r...
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"""simple docstring""" from math import isqrt def __UpperCAmelCase ( snake_case_ : int ) -> list[int]: """simple docstring""" _lowerCAmelCase = [True] * max_number for i in range(2 , isqrt(max_number - 1 ) + 1 ): if is_prime[i]: ...
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"""simple docstring""" print((lambda quine: quine % quine)('''print((lambda quine: quine %% quine)(%r))'''))
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"""simple docstring""" # 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...
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"""simple docstring""" def __UpperCAmelCase ( snake_case_ : str ) -> Optional[Any]: """simple docstring""" _lowerCAmelCase = [] _lowerCAmelCase = [] _lowerCAmelCase = { """^""": 3, """*""": 2, """/""": 2...
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"""simple docstring""" from __future__ import annotations import queue class __lowerCamelCase : def __init__(self , lowerCamelCase ): '''simple docstring''' _lowerCAmelCase = data _lowerCAmelCase = None _lowerCAmelCase = ...
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"""simple docstring""" import argparse import torch from datasets import load_dataset from donut import DonutModel from transformers import ( DonutImageProcessor, DonutProcessor, DonutSwinConfig, DonutSwinModel, MBartConfig, MBartForCausalLM, VisionEncoderDecoderModel, XLMRobe...
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"""simple docstring""" from __future__ import annotations class __lowerCamelCase : def __init__(self , lowerCamelCase , lowerCamelCase ): '''simple docstring''' _lowerCAmelCase , _lowerCAmelCase = text, pattern _lowerCAmelCase , _low...
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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 SCREAMING_SNAKE_CASE : Optional[int] = logging.get_logger(__name__) SCREAMING_SNAKE_CASE : ...
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"""simple docstring""" import unittest import numpy as np import torch from diffusers import VersatileDiffusionImageVariationPipeline from diffusers.utils.testing_utils import load_image, require_torch_gpu, slow, torch_device SCREAMING_SNAKE_CASE : List[str] = False class __lowerCamelCase...
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"""simple docstring""" from __future__ import annotations import unittest from transformers import is_tf_available from transformers.testing_utils import require_tf, slow from ...test_configuration_common import ConfigTester from ...test_modeling_tf_common import TFModelTesterMixin, ids_tensor, random_atten...
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"""simple docstring""" import gc import unittest import numpy as np import torch from diffusers import AutoencoderKL, DDIMScheduler, DiTPipeline, DPMSolverMultistepScheduler, TransformeraDModel from diffusers.utils import is_xformers_available, load_numpy, slow, torch_device from diffusers.utils.testing_util...
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"""simple docstring""" import argparse import json import os import evaluate import torch from datasets import load_dataset from torch.optim import AdamW from torch.utils.data import DataLoader from transformers import AutoModelForSequenceClassification, AutoTokenizer, get_linear_schedule_with_warmup, set_see...
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"""simple docstring""" from operator import delitem, getitem, setitem import pytest from data_structures.hashing.hash_map import HashMap def __UpperCAmelCase ( snake_case_ : Union[str, Any] ) -> Dict: """simple docstring""" return getitem, k def __UpperCAm...
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"""simple docstring""" # Algorithm for the pigeonhole sorting def __UpperCAmelCase ( snake_case_ : Optional[Any] ) -> Optional[Any]: """simple docstring""" _lowerCAmelCase = min(__lowerCAmelCase ) # min() finds the minimum value _lowerCAmel...
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"""simple docstring""" def __UpperCAmelCase ( snake_case_ : int , snake_case_ : list[int] , snake_case_ : int ) -> int: """simple docstring""" def count_of_possible_combinations(snake_case_ : int ) -> int: if target < 0: r...
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"""simple docstring""" from collections import namedtuple SCREAMING_SNAKE_CASE : Any = namedtuple('''from_to''', '''from_ to''') SCREAMING_SNAKE_CASE : Any = { """cubicmeter""": from_to(1, 1), """litre""": from_to(0.0_0_1, 1_0_0_0), """kilolitre""": from_to(1, 1), ...
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"""simple docstring""" from __future__ import annotations import string from itertools import cycle, product from pathlib import Path SCREAMING_SNAKE_CASE : str = ( string.ascii_letters + string.digits + string.punctuation + string.whitespace ) SCREAMING_SNAKE_CASE : list[int] ...
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"""simple docstring""" import bza import gzip import lzma import os import shutil import struct import tarfile import warnings import zipfile from abc import ABC, abstractmethod from pathlib import Path from typing import Dict, List, Optional, Type, Union from .. import config from .filelock import FileLock f...
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"""simple docstring""" def __UpperCAmelCase ( snake_case_ : int = 1000000 ) -> int: """simple docstring""" _lowerCAmelCase = limit + 1 _lowerCAmelCase = [0] * limit for first_term in range(1 , snake_case_ ): for n in range(sn...
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"""simple docstring""" import importlib import sys from argparse import REMAINDER, ArgumentParser from pathlib import Path import torch_xla.distributed.xla_multiprocessing as xmp def __UpperCAmelCase ( ) -> Tuple: """simple docstring""" _lowerC...
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"""simple docstring""" from functools import reduce SCREAMING_SNAKE_CASE : int = ( '''73167176531330624919225119674426574742355349194934''' '''96983520312774506326239578318016984801869478851843''' '''85861560789112949495459501737958331952853208805511''' '''1254069874715852386305...
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"""simple docstring""" import unittest from transformers import MODEL_FOR_DOCUMENT_QUESTION_ANSWERING_MAPPING, AutoTokenizer, is_vision_available from transformers.pipelines import pipeline from transformers.pipelines.document_question_answering import apply_tesseract from transformers.testing_utils import ( ...
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"""simple docstring""" def __UpperCAmelCase ( snake_case_ : int = 600851475143 ) -> int: """simple docstring""" try: _lowerCAmelCase = int(snake_case_ ) except (TypeError, ValueError): raise TypeError("""Parameter n must be int or castable ...
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"""simple docstring""" import contextlib import copy import random from typing import Any, Dict, Iterable, Optional, Union import numpy as np import torch from .utils import deprecate, is_transformers_available if is_transformers_available(): import transformers def _...
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"""simple docstring""" import logging import os import sys from dataclasses import dataclass, field from typing import Optional from seqaseq_trainer import SeqaSeqTrainer from seqaseq_training_args import SeqaSeqTrainingArguments import transformers from transformers import ( AutoConfig, AutoModelFor...
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"""simple docstring""" import unittest import numpy as np from transformers.testing_utils import require_flax, require_tf, require_torch from transformers.utils import ( expand_dims, flatten_dict, is_flax_available, is_tf_available, is_torch_available, reshape, squeeze, tran...
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"""simple docstring""" from typing import TYPE_CHECKING # rely on isort to merge the imports from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available SCREAMING_SNAKE_CASE : List[Any] = {'''configuration_focalnet''': ['''FOCALNET_PRETRAINED_CONFIG_ARCHIVE_MAP''', ''...
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def __UpperCAmelCase ( snake_case_ : int = 1000000 ) -> Dict: """simple docstring""" _lowerCAmelCase = set(range(3 , snake_case_ , 2 ) ) primes.add(2 ) for p in range(3 , snake_case_ , 2 ): if p not in primes: cont...
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"""simple docstring""" import unittest import numpy as np from transformers.testing_utils import require_torch, require_vision from transformers.utils import is_torch_available, is_vision_available from ...test_image_processing_common import ImageProcessingSavingTestMixin, prepare_image_inputs if is_torch...
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import logging import os from dataclasses import dataclass from enum import Enum from typing import List, Optional, Union from filelock import FileLock from transformers import PreTrainedTokenizer, is_tf_available, is_torch_available SCREAMING_SNAKE_CASE : List[str] = logging.getLogger(__name__) ...
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"""simple docstring""" def __UpperCAmelCase ( snake_case_ : list ) -> list: """simple docstring""" for i in range(len(snake_case_ ) - 1 , 0 , -1 ): _lowerCAmelCase = False for j in range(snake_case_ , 0 , -1 ): ...
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"""simple docstring""" import os def __UpperCAmelCase ( snake_case_ : str = "matrix.txt" ) -> int: """simple docstring""" with open(os.path.join(os.path.dirname(_UpperCAmelCase ) , _UpperCAmelCase ) ) as in_file: _lowerCAmelCase = in...
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"""simple docstring""" import random import timeit from functools import wraps from typing import Callable, Optional from ..configuration_utils import PretrainedConfig from ..models.auto.modeling_tf_auto import TF_MODEL_MAPPING, TF_MODEL_WITH_LM_HEAD_MAPPING from ..utils import is_pyanvml_available, is_tf_ava...
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"""simple docstring""" from typing import TYPE_CHECKING from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tokenizers_available, is_torch_available SCREAMING_SNAKE_CASE : Union[str, Any] = { '''configuration_mvp''': ['''MVP_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''MvpConfig'...
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"""simple docstring""" from ...configuration_utils import PretrainedConfig from ...utils import logging SCREAMING_SNAKE_CASE : int = logging.get_logger(__name__) SCREAMING_SNAKE_CASE : Any = { '''transfo-xl-wt103''': '''https://huggingface.co/transfo-xl-wt103/resolve/main/c...
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"""simple docstring""" from math import factorial def __UpperCAmelCase ( snake_case_ : int = 100 ) -> List[str]: """simple docstring""" return sum(int(snake_case_ ) for x in str(factorial(snake_case_ ) ) ) if __name__ == "__main__": print(solution(in...
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"""simple docstring""" import math def __UpperCAmelCase ( snake_case_ : int ) -> list[int]: """simple docstring""" _lowerCAmelCase = [] _lowerCAmelCase = 2 _lowerCAmelCase = int(math.sqrt(snake_case_ ) ) # Size ...
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"""simple docstring""" import glob import os import random from string import ascii_lowercase, digits import cva import numpy as np # Parrameters SCREAMING_SNAKE_CASE : Optional[Any] = (7_2_0, 1_2_8_0) # Height, Width SCREAMING_SNAKE_CASE : Tuple = (0.4, 0.6) # if height or w...
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"""simple docstring""" import glob import os import random from string import ascii_lowercase, digits import cva import numpy as np # Parrameters SCREAMING_SNAKE_CASE : Any = (7_2_0, 1_2_8_0) # Height, Width SCREAMING_SNAKE_CASE : List[str] = (0.4, 0.6) # if height or width lo...
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"""simple docstring""" import inspect import unittest import warnings from math import ceil, floor from transformers import LevitConfig from transformers.file_utils import cached_property, is_torch_available, is_vision_available from transformers.models.auto import get_values from transformers.testing_utils i...
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"""simple docstring""" # tests directory-specific settings - this file is run automatically # by pytest before any tests are run import sys import warnings from os.path import abspath, dirname, join # allow having multiple repository checkouts and not needing to remember to rerun # 'pip install -e .[dev]' w...
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"""simple docstring""" from __future__ import annotations from bisect import bisect_left from functools import total_ordering from heapq import merge @total_ordering class __lowerCamelCase ( __SCREAMING_SNAKE_CASE ): def __lt__(self , lowerCamelCase ): '''simple docstring...
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"""simple docstring""" # 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...
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"""simple docstring""" import pytest from datasets.splits import SplitDict, SplitInfo from datasets.utils.py_utils import asdict @pytest.mark.parametrize( """split_dict""" , [ SplitDict(), SplitDict({"""train""": SplitInfo(name="""train""" , num_bytes=1337 , num_examples=...
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"""simple docstring""" from math import isqrt def __UpperCAmelCase ( snake_case_ : int ) -> list[int]: """simple docstring""" _lowerCAmelCase = [True] * max_number for i in range(2 , isqrt(max_number - 1 ) + 1 ): if is_prime[i]: ...
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"""simple docstring""" def __UpperCAmelCase ( snake_case_ : str , snake_case_ : Tuple ): """simple docstring""" _lowerCAmelCase = len(SCREAMING_SNAKE_CASE_ ) _lowerCAmelCase = len(SCREAMING_SNAKE_CASE_ ) _lowerCAmelCase ...
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"""simple docstring""" # 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...
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"""simple docstring""" from typing import TYPE_CHECKING from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_sentencepiece_available SCREAMING_SNAKE_CASE : Dict = {} try: if not is_sentencepiece_available(): raise OptionalDependencyNotAvailable() except OptionalDependen...
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"""simple docstring""" from __future__ import annotations import queue class __lowerCamelCase : def __init__(self , lowerCamelCase ): '''simple docstring''' _lowerCAmelCase = data _lowerCAmelCase = None _lowerCAmelCase = ...
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"""simple docstring""" import string def __UpperCAmelCase ( snake_case_ : str ) -> None: """simple docstring""" for key in range(len(string.ascii_uppercase ) ): _lowerCAmelCase = """""" for symbol in message: if symbol in str...
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"""simple docstring""" from __future__ import annotations class __lowerCamelCase : def __init__(self , lowerCamelCase , lowerCamelCase ): '''simple docstring''' _lowerCAmelCase , _lowerCAmelCase = text, pattern _lowerCAmelCase , _low...
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"""simple docstring""" def __UpperCAmelCase ( snake_case_ : Optional[Any] , snake_case_ : List[str] = 0 ) -> list: """simple docstring""" _lowerCAmelCase = length or len(a__ ) _lowerCAmelCase = False for i in range(length -...
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"""simple docstring""" import unittest import numpy as np import torch from diffusers import VersatileDiffusionImageVariationPipeline from diffusers.utils.testing_utils import load_image, require_torch_gpu, slow, torch_device SCREAMING_SNAKE_CASE : List[str] = False class __lowerCamelCase...
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"""simple docstring""" import unittest import numpy as np from transformers.testing_utils import require_torch, require_vision from transformers.utils import is_torch_available, is_vision_available from ...test_image_processing_common import ImageProcessingSavingTestMixin, prepare_image_inputs if is_torch...
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"""simple docstring""" import gc import unittest import numpy as np import torch from diffusers import AutoencoderKL, DDIMScheduler, DiTPipeline, DPMSolverMultistepScheduler, TransformeraDModel from diffusers.utils import is_xformers_available, load_numpy, slow, torch_device from diffusers.utils.testing_util...
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"""simple docstring""" import inspect import unittest from transformers import MobileNetVaConfig from transformers.testing_utils import require_torch, require_vision, slow, torch_device from transformers.utils import cached_property, is_torch_available, is_vision_available from ...test_configuration_common i...
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"""simple docstring""" from operator import delitem, getitem, setitem import pytest from data_structures.hashing.hash_map import HashMap def __UpperCAmelCase ( snake_case_ : Union[str, Any] ) -> Dict: """simple docstring""" return getitem, k def __UpperCAm...
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"""simple docstring""" import numpy as np from scipy.spatial.distance import cdist from sklearn.metrics import fa_score import datasets SCREAMING_SNAKE_CASE : Tuple = "\\n @inproceedings{kakwani2020indicnlpsuite,\n title={{IndicNLPSuite: Monolingual Corpora, Evaluation Benchmarks and Pr...
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"""simple docstring""" def __UpperCAmelCase ( snake_case_ : int , snake_case_ : list[int] , snake_case_ : int ) -> int: """simple docstring""" def count_of_possible_combinations(snake_case_ : int ) -> int: if target < 0: r...
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"""simple docstring""" from collections import Counter import numpy as np from sklearn import datasets from sklearn.model_selection import train_test_split SCREAMING_SNAKE_CASE : Union[str, Any] = datasets.load_iris() SCREAMING_SNAKE_CASE : str = np.array(data['''data''']) SC...
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"""simple docstring""" from __future__ import annotations import string from itertools import cycle, product from pathlib import Path SCREAMING_SNAKE_CASE : str = ( string.ascii_letters + string.digits + string.punctuation + string.whitespace ) SCREAMING_SNAKE_CASE : list[int] ...
317
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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 SCREAMING_SNAKE_CASE : int = get_logger(__name__) class __lowerCamelCase ( enum.Enum ): __UpperCamelCase = 'a...
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"""simple docstring""" def __UpperCAmelCase ( snake_case_ : int = 1000000 ) -> int: """simple docstring""" _lowerCAmelCase = limit + 1 _lowerCAmelCase = [0] * limit for first_term in range(1 , snake_case_ ): for n in range(sn...
317
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"""simple docstring""" import os def __UpperCAmelCase ( ) -> Optional[Any]: """simple docstring""" with open(os.path.dirname(UpperCAmelCase_ ) + """/p022_names.txt""" ) as file: _lowerCAmelCase = str(file.readlines()[0] ...
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"""simple docstring""" from functools import reduce SCREAMING_SNAKE_CASE : int = ( '''73167176531330624919225119674426574742355349194934''' '''96983520312774506326239578318016984801869478851843''' '''85861560789112949495459501737958331952853208805511''' '''1254069874715852386305...
317
0
"""simple docstring""" import builtins import sys from ...utils.imports import _is_package_available from . import cursor, input from .helpers import Direction, clear_line, forceWrite, linebreak, move_cursor, reset_cursor, writeColor from .keymap import KEYMAP __SCREAMING_SNAKE_CASE : str = F...
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"""simple docstring""" def __UpperCAmelCase ( snake_case_ : int = 600851475143 ) -> int: """simple docstring""" try: _lowerCAmelCase = int(snake_case_ ) except (TypeError, ValueError): raise TypeError("""Parameter n must be int or castable ...
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"""simple docstring""" from manim import * class __lowerCamelCase ( __lowercase ): def A__ (self ): '''simple docstring''' _lowerCAmelCase = Rectangle(height=0.5 , width=0.5 ) _lowerCAmelCase ...
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"""simple docstring""" import logging import os import sys from dataclasses import dataclass, field from typing import Optional from seqaseq_trainer import SeqaSeqTrainer from seqaseq_training_args import SeqaSeqTrainingArguments import transformers from transformers import ( AutoConfig, AutoModelFor...
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"""simple docstring""" import argparse import os import transformers from .convert_slow_tokenizer import SLOW_TO_FAST_CONVERTERS from .utils import logging logging.set_verbosity_info() SCREAMING_SNAKE_CASE : Any = logging.get_logger(__name__) SCREAMING_SNAKE_CASE : Optional[Any]...
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"""simple docstring""" from typing import TYPE_CHECKING # rely on isort to merge the imports from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available SCREAMING_SNAKE_CASE : List[Any] = {'''configuration_focalnet''': ['''FOCALNET_PRETRAINED_CONFIG_ARCHIVE_MAP''', ''...
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import argparse import os import re SCREAMING_SNAKE_CASE : Union[str, Any] = '''src/transformers''' # Pattern that looks at the indentation in a line. SCREAMING_SNAKE_CASE : List[Any] = re.compile(R'''^(\s*)\S''') # Pattern that matches `"key":" and puts `key` in group 0. SCREAMING_...
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"""simple docstring""" import unittest import numpy as np from transformers.testing_utils import require_torch, require_vision from transformers.utils import is_torch_available, is_vision_available from ...test_image_processing_common import ImageProcessingSavingTestMixin, prepare_image_inputs if is_torch...
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from typing import TYPE_CHECKING from ...utils import ( OptionalDependencyNotAvailable, _LazyModule, is_tf_available, is_tokenizers_available, is_torch_available, ) SCREAMING_SNAKE_CASE : Tuple = { '''configuration_funnel''': ['''FUNNEL_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''...
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"""simple docstring""" def __UpperCAmelCase ( snake_case_ : list ) -> list: """simple docstring""" for i in range(len(snake_case_ ) - 1 , 0 , -1 ): _lowerCAmelCase = False for j in range(snake_case_ , 0 , -1 ): ...
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"""simple docstring""" import copy from ...configuration_utils import PretrainedConfig from ...utils import add_start_docstrings SCREAMING_SNAKE_CASE : int = R'''\n [`RagConfig`] stores the configuration of a *RagModel*. Configuration objects inherit from [`PretrainedConfig`] and\n can ...
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"""simple docstring""" import random import timeit from functools import wraps from typing import Callable, Optional from ..configuration_utils import PretrainedConfig from ..models.auto.modeling_tf_auto import TF_MODEL_MAPPING, TF_MODEL_WITH_LM_HEAD_MAPPING from ..utils import is_pyanvml_available, is_tf_ava...
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"""simple docstring""" import operator as op SCREAMING_SNAKE_CASE : str = "scaler.pt" SCREAMING_SNAKE_CASE : List[str] = "pytorch_model" SCREAMING_SNAKE_CASE : List[str] = "random_states" SCREAMING_SNAKE_CASE : Optional[int] = "optimizer" SCREAMING_...
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"""simple docstring""" from ...configuration_utils import PretrainedConfig from ...utils import logging SCREAMING_SNAKE_CASE : int = logging.get_logger(__name__) SCREAMING_SNAKE_CASE : Any = { '''transfo-xl-wt103''': '''https://huggingface.co/transfo-xl-wt103/resolve/main/c...
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"""simple docstring""" import json import os from functools import lru_cache from typing import Dict, List, Optional, Tuple, Union import regex as re from ...tokenization_utils import AddedToken, PreTrainedTokenizer from ...tokenization_utils_base import BatchEncoding, EncodedInput from ...utils import Paddi...
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"""simple docstring""" import math def __UpperCAmelCase ( snake_case_ : int ) -> list[int]: """simple docstring""" _lowerCAmelCase = [] _lowerCAmelCase = 2 _lowerCAmelCase = int(math.sqrt(snake_case_ ) ) # Size ...
317
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"""simple docstring""" def __UpperCAmelCase ( ) -> int: """simple docstring""" return [ a * b * (1000 - a - b) for a in range(1 , 999 ) for b in range(__lowerCAmelCase , 999 ) if (a * a + b * b == (1000 - a - b) ** 2) ][0] if __name__ ...
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"""simple docstring""" import glob import os import random from string import ascii_lowercase, digits import cva import numpy as np # Parrameters SCREAMING_SNAKE_CASE : Any = (7_2_0, 1_2_8_0) # Height, Width SCREAMING_SNAKE_CASE : List[str] = (0.4, 0.6) # if height or width lo...
317
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"""simple docstring""" from typing import List import numpy as np def __UpperCAmelCase ( snake_case_ : dict ) -> int: """simple docstring""" _lowerCAmelCase = {key: len(_lowercase ) for key, value in gen_kwargs.items() if isinstance(_lowercase ,...
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"""simple docstring""" # tests directory-specific settings - this file is run automatically # by pytest before any tests are run import sys import warnings from os.path import abspath, dirname, join # allow having multiple repository checkouts and not needing to remember to rerun # 'pip install -e .[dev]' w...
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"""simple docstring""" import sys import warnings from os.path import abspath, dirname, join # allow having multiple repository checkouts and not needing to remember to rerun # 'pip install -e .[dev]' when switching between checkouts and running tests. SCREAMING_SNAKE_CASE : int = abspath(join...
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"""simple docstring""" # 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...
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"""simple docstring""" import argparse import json from pathlib import Path import requests import timm import torch from huggingface_hub import hf_hub_download from PIL import Image from timm.data import resolve_data_config from timm.data.transforms_factory import create_transform from transformers import (...
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"""simple docstring""" from math import isqrt def __UpperCAmelCase ( snake_case_ : int ) -> list[int]: """simple docstring""" _lowerCAmelCase = [True] * max_number for i in range(2 , isqrt(max_number - 1 ) + 1 ): if is_prime[i]: ...
317
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"""simple docstring""" from __future__ import annotations from collections.abc import Callable from typing import Generic, TypeVar SCREAMING_SNAKE_CASE : Optional[Any] = TypeVar('''T''') SCREAMING_SNAKE_CASE : List[str] = TypeVar('''U''') class __lowerCamelCase ( Generic[...
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"""simple docstring""" # 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...
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"""simple docstring""" import copy from typing import Any, Dict, List, Optional, Union import numpy as np from ...audio_utils import mel_filter_bank, spectrogram, window_function from ...feature_extraction_sequence_utils import SequenceFeatureExtractor from ...feature_extraction_utils import BatchFeature fro...
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"""simple docstring""" from __future__ import annotations import queue class __lowerCamelCase : def __init__(self , lowerCamelCase ): '''simple docstring''' _lowerCAmelCase = data _lowerCAmelCase = None _lowerCAmelCase = ...
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"""simple docstring""" import json import os import subprocess import unittest from ast import literal_eval import pytest from parameterized import parameterized, parameterized_class from . import is_sagemaker_available if is_sagemaker_available(): from sagemaker import Session, TrainingJobAnalytics fr...
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"""simple docstring""" from __future__ import annotations class __lowerCamelCase : def __init__(self , lowerCamelCase , lowerCamelCase ): '''simple docstring''' _lowerCAmelCase , _lowerCAmelCase = text, pattern _lowerCAmelCase , _low...
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"""simple docstring""" import heapq import sys import numpy as np SCREAMING_SNAKE_CASE : List[str] = tuple[int, int] class __lowerCamelCase : def __init__(self ): '''simple docstring''' _lowerCAmelCase = [] _lowerCAmelCase = ...
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"""simple docstring""" import unittest import numpy as np import torch from diffusers import VersatileDiffusionImageVariationPipeline from diffusers.utils.testing_utils import load_image, require_torch_gpu, slow, torch_device SCREAMING_SNAKE_CASE : List[str] = False class __lowerCamelCase...
317
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"""simple docstring""" def __UpperCAmelCase ( snake_case_ : Tuple ) -> Optional[int]: """simple docstring""" _lowerCAmelCase = [False] * len(snake_case_ ) _lowerCAmelCase = [-1] * len(snake_case_ ) def dfs(snake_case_ : Uni...
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"""simple docstring""" import gc import unittest import numpy as np import torch from diffusers import AutoencoderKL, DDIMScheduler, DiTPipeline, DPMSolverMultistepScheduler, TransformeraDModel from diffusers.utils import is_xformers_available, load_numpy, slow, torch_device from diffusers.utils.testing_util...
317
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"""simple docstring""" import fire from transformers import AutoConfig, AutoModelForSeqaSeqLM, AutoTokenizer def __UpperCAmelCase ( snake_case_ : str , snake_case_ : str , **snake_case_ : List[str] ) -> str: """simple docstring""" _lowerCAme...
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"""simple docstring""" from operator import delitem, getitem, setitem import pytest from data_structures.hashing.hash_map import HashMap def __UpperCAmelCase ( snake_case_ : Union[str, Any] ) -> Dict: """simple docstring""" return getitem, k def __UpperCAm...
317
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"""simple docstring""" from __future__ import annotations import collections import pprint from pathlib import Path def __UpperCAmelCase ( snake_case_ : Tuple ) -> List[Any]: """simple docstring""" return "".join(sorted(__a ) ) def __UpperCAmelCase ...
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"""simple docstring""" def __UpperCAmelCase ( snake_case_ : int , snake_case_ : list[int] , snake_case_ : int ) -> int: """simple docstring""" def count_of_possible_combinations(snake_case_ : int ) -> int: if target < 0: r...
317
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"""simple docstring""" import gc import random import unittest import numpy as np import torch from transformers import CLIPTextConfig, CLIPTextModel, CLIPTokenizer import diffusers from diffusers import ( AutoencoderKL, EulerDiscreteScheduler, StableDiffusionLatentUpscalePipeline, StableDi...
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"""simple docstring""" from __future__ import annotations import string from itertools import cycle, product from pathlib import Path SCREAMING_SNAKE_CASE : str = ( string.ascii_letters + string.digits + string.punctuation + string.whitespace ) SCREAMING_SNAKE_CASE : list[int] ...
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"""simple docstring""" import string # frequency taken from https://en.wikipedia.org/wiki/Letter_frequency SCREAMING_SNAKE_CASE : List[str] = { '''E''': 1_2.7_0, '''T''': 9.0_6, '''A''': 8.1_7, '''O''': 7.5_1, '''I''': 6.9_7, '''N''': 6.7_5, '''S''': 6.3_3, '''H'...
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"""simple docstring""" def __UpperCAmelCase ( snake_case_ : int = 1000000 ) -> int: """simple docstring""" _lowerCAmelCase = limit + 1 _lowerCAmelCase = [0] * limit for first_term in range(1 , snake_case_ ): for n in range(sn...
317
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"""simple docstring""" from typing import TYPE_CHECKING from ....utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available SCREAMING_SNAKE_CASE : Tuple = { """configuration_trajectory_transformer""": [ """TRAJECTORY_TRANSFORMER_PRETRAINED_CONFIG...
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"""simple docstring""" from functools import reduce SCREAMING_SNAKE_CASE : int = ( '''73167176531330624919225119674426574742355349194934''' '''96983520312774506326239578318016984801869478851843''' '''85861560789112949495459501737958331952853208805511''' '''1254069874715852386305...
317
0
"""simple docstring""" 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, InputFeatu...
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"""simple docstring""" def __UpperCAmelCase ( snake_case_ : int = 600851475143 ) -> int: """simple docstring""" try: _lowerCAmelCase = int(snake_case_ ) except (TypeError, ValueError): raise TypeError("""Parameter n must be int or castable ...
317
0
"""simple docstring""" from abc import ABC, abstractmethod from typing import List, Optional class __lowerCamelCase ( UpperCamelCase__ ): def __init__(self ): '''simple docstring''' self.test() def A__ (self ...
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"""simple docstring""" import logging import os import sys from dataclasses import dataclass, field from typing import Optional from seqaseq_trainer import SeqaSeqTrainer from seqaseq_training_args import SeqaSeqTrainingArguments import transformers from transformers import ( AutoConfig, AutoModelFor...
317
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"""simple docstring""" def __UpperCAmelCase ( snake_case_ : str = "The quick brown fox jumps over the lazy dog" , ) -> Optional[Any]: """simple docstring""" _lowerCAmelCase = set() # Replace all the whitespace in our sentence _lowerCAmelCase ...
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"""simple docstring""" from typing import TYPE_CHECKING # rely on isort to merge the imports from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available SCREAMING_SNAKE_CASE : List[Any] = {'''configuration_focalnet''': ['''FOCALNET_PRETRAINED_CONFIG_ARCHIVE_MAP''', ''...
317
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def __UpperCAmelCase ( snake_case_ : int , snake_case_ : int ) -> int: """simple docstring""" while a != 0: _lowerCAmelCase = b % a, a return b def __UpperCAmelCase ( snake_case_ : int , snake_case_ : int )...
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"""simple docstring""" import unittest import numpy as np from transformers.testing_utils import require_torch, require_vision from transformers.utils import is_torch_available, is_vision_available from ...test_image_processing_common import ImageProcessingSavingTestMixin, prepare_image_inputs if is_torch...
317
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from typing import Callable, Optional, Union from ...configuration_utils import PretrainedConfig from ...utils import logging SCREAMING_SNAKE_CASE : Union[str, Any] = logging.get_logger(__name__) SCREAMING_SNAKE_CASE : Tuple = { 'microsoft/xprophetnet-large-wiki100-cased': ( ...
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"""simple docstring""" def __UpperCAmelCase ( snake_case_ : list ) -> list: """simple docstring""" for i in range(len(snake_case_ ) - 1 , 0 , -1 ): _lowerCAmelCase = False for j in range(snake_case_ , 0 , -1 ): ...
317
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"""simple docstring""" def __UpperCAmelCase ( snake_case_ : List[str] , snake_case_ : Union[str, Any] , snake_case_ : int ) -> Dict: """simple docstring""" return round(float(moles / volume ) * nfactor ) def __UpperCAmelCase ( sn...
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"""simple docstring""" import random import timeit from functools import wraps from typing import Callable, Optional from ..configuration_utils import PretrainedConfig from ..models.auto.modeling_tf_auto import TF_MODEL_MAPPING, TF_MODEL_WITH_LM_HEAD_MAPPING from ..utils import is_pyanvml_available, is_tf_ava...
317
0
"""simple docstring""" from functools import lru_cache @lru_cache def __UpperCAmelCase ( snake_case_ : Union[str, Any] ) -> int: """simple docstring""" if num < 0: raise ValueError("""Number should not be negative.""" ) return 1 if num in (0, 1) else nu...
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"""simple docstring""" from ...configuration_utils import PretrainedConfig from ...utils import logging SCREAMING_SNAKE_CASE : int = logging.get_logger(__name__) SCREAMING_SNAKE_CASE : Any = { '''transfo-xl-wt103''': '''https://huggingface.co/transfo-xl-wt103/resolve/main/c...
317
0
"""simple docstring""" from collections import defaultdict class __lowerCamelCase : def __init__(self , lowerCamelCase , lowerCamelCase ): '''simple docstring''' _lowerCAmelCase = total # total no of tasks (N) # DP table will have a dimension of...
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"""simple docstring""" import math def __UpperCAmelCase ( snake_case_ : int ) -> list[int]: """simple docstring""" _lowerCAmelCase = [] _lowerCAmelCase = 2 _lowerCAmelCase = int(math.sqrt(snake_case_ ) ) # Size ...
317
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"""simple docstring""" from typing import List, Optional, Union from ...configuration_utils import PretrainedConfig from ...utils import logging SCREAMING_SNAKE_CASE : Optional[Any] = logging.get_logger(__name__) SCREAMING_SNAKE_CASE : Any = { '''huggingface/informer-tour...
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"""simple docstring""" import glob import os import random from string import ascii_lowercase, digits import cva import numpy as np # Parrameters SCREAMING_SNAKE_CASE : Any = (7_2_0, 1_2_8_0) # Height, Width SCREAMING_SNAKE_CASE : List[str] = (0.4, 0.6) # if height or width lo...
317
0
"""simple docstring""" from typing import TYPE_CHECKING from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tokenizers_available, is_torch_available SCREAMING_SNAKE_CASE : str = { '''configuration_bloom''': ['''BLOOM_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''BloomConfig''', ''...
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"""simple docstring""" # tests directory-specific settings - this file is run automatically # by pytest before any tests are run import sys import warnings from os.path import abspath, dirname, join # allow having multiple repository checkouts and not needing to remember to rerun # 'pip install -e .[dev]' w...
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"""simple docstring""" from ...utils import is_torch_available, is_transformers_available if is_transformers_available() and is_torch_available(): from .pipeline_vq_diffusion import LearnedClassifierFreeSamplingEmbeddings, VQDiffusionPipeline
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"""simple docstring""" # 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...
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"""simple docstring""" def __UpperCAmelCase ( snake_case_ : list , snake_case_ : int = 0 ) -> list: """simple docstring""" _lowerCAmelCase = length or len(snake_case__ ) _lowerCAmelCase = False for i in range(length - 1 ...
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"""simple docstring""" from math import isqrt def __UpperCAmelCase ( snake_case_ : int ) -> list[int]: """simple docstring""" _lowerCAmelCase = [True] * max_number for i in range(2 , isqrt(max_number - 1 ) + 1 ): if is_prime[i]: ...
317
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"""simple docstring""" from ..models.auto import AutoModelForSeqaSeqLM, AutoTokenizer from .base import PipelineTool SCREAMING_SNAKE_CASE : Tuple = { "Acehnese Arabic": "ace_Arab", "Acehnese Latin": "ace_Latn", "Mesopotamian Arabic": "acm_Arab", "Ta'izzi-Adeni Arabic": "acq_Ara...
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"""simple docstring""" # 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...
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"""simple docstring""" from argparse import ArgumentParser, Namespace from ..utils import logging from . import BaseTransformersCLICommand def __UpperCAmelCase ( snake_case_ : List[Any] ) -> Optional[int]: """simple docstring""" return ConvertCommand( args.m...
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"""simple docstring""" from __future__ import annotations import queue class __lowerCamelCase : def __init__(self , lowerCamelCase ): '''simple docstring''' _lowerCAmelCase = data _lowerCAmelCase = None _lowerCAmelCase = ...
317
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"""simple docstring""" import argparse import json import os import torch from transformers.file_utils import has_file from diffusers import UNetaDConditionModel, UNetaDModel SCREAMING_SNAKE_CASE : Dict = False SCREAMING_SNAKE_CASE : int = True SCREAMING_SNAKE_CASE : L...
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"""simple docstring""" from __future__ import annotations class __lowerCamelCase : def __init__(self , lowerCamelCase , lowerCamelCase ): '''simple docstring''' _lowerCAmelCase , _lowerCAmelCase = text, pattern _lowerCAmelCase , _low...
317
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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_...
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"""simple docstring""" import unittest import numpy as np import torch from diffusers import VersatileDiffusionImageVariationPipeline from diffusers.utils.testing_utils import load_image, require_torch_gpu, slow, torch_device SCREAMING_SNAKE_CASE : List[str] = False class __lowerCamelCase...
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"""simple docstring""" def __UpperCAmelCase ( snake_case_ : str , snake_case_ : Tuple ) -> bool: """simple docstring""" _lowerCAmelCase = len(__SCREAMING_SNAKE_CASE ) _lowerCAmelCase = [[False] * (required_sum + 1) for _ in ra...
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"""simple docstring""" import gc import unittest import numpy as np import torch from diffusers import AutoencoderKL, DDIMScheduler, DiTPipeline, DPMSolverMultistepScheduler, TransformeraDModel from diffusers.utils import is_xformers_available, load_numpy, slow, torch_device from diffusers.utils.testing_util...
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