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"""simple docstring""" from __future__ import annotations UpperCAmelCase = tuple[int, int, int] UpperCAmelCase = tuple[str, str, str] # used alphabet -------------------------- # from string.ascii_uppercase UpperCAmelCase = """ABCDEFGHIJKLMNOPQRSTUVWXYZ""" # -------------------------- default ...
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"""simple docstring""" # NOTE: This file is deprecated and will be removed in a future version. # It only exists so that temporarely `from diffusers.pipelines import DiffusionPipeline` works from ...utils import deprecate from ..controlnet.pipeline_flax_controlnet import FlaxStableDiffusionControlNetPipeline # noqa:...
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"""simple docstring""" import inspect import unittest from transformers import DPTConfig from transformers.file_utils import is_torch_available, is_vision_available from transformers.models.auto import get_values from transformers.testing_utils import require_torch, require_vision, slow, torch_device from ...test_co...
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"""simple docstring""" import argparse from diffusers.pipelines.stable_diffusion.convert_from_ckpt import download_controlnet_from_original_ckpt if __name__ == "__main__": UpperCAmelCase = argparse.ArgumentParser() parser.add_argument( """--checkpoint_path""", default=None, type=str, required=True...
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"""simple docstring""" import json import sys import tempfile import unittest from pathlib import Path import transformers from transformers import ( CONFIG_MAPPING, IMAGE_PROCESSOR_MAPPING, AutoConfig, AutoImageProcessor, CLIPConfig, CLIPImageProcessor, ) from transformers.testing_utils impor...
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"""simple docstring""" from __future__ import annotations UpperCAmelCase = 8.988E9 # units = N * m^s * C^-2 def lowercase ( a__ : float , a__ : float , a__ : float , a__ : float ) -> dict[str, float]: _UpperCamelCase = abs(chargea ...
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"""simple docstring""" from math import atan, cos, radians, sin, tan from .haversine_distance import haversine_distance UpperCAmelCase = 6_37_81_37.0 UpperCAmelCase = 6_35_67_52.31_42_45 UpperCAmelCase = 6_378_137 def lowercase ( a__ : float , a__ : float , a__ ...
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"""simple docstring""" import copy import json import os import tempfile from transformers import is_torch_available from .test_configuration_utils import config_common_kwargs class UpperCAmelCase_ ( _lowercase): def __init__( self : Any , __UpperCamelCase : Optional...
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"""simple docstring""" from PIL import Image def lowercase ( a__ : Image ) -> Image: _UpperCamelCase , _UpperCamelCase = image.size _UpperCamelCase = 0 _UpperCamelCase = image.load() for i in range(a__ ): ...
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"""simple docstring""" import qiskit def lowercase ( a__ : int = 2 ) -> qiskit.result.counts.Counts: _UpperCamelCase = qubits # Using Aer's simulator _UpperCamelCase = qiskit.Aer.get_backend('''aer_simulator''' ) # Creating a Quan...
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"""simple docstring""" UpperCAmelCase = { "joule": 1.0, "kilojoule": 1_000, "megajoule": 1_000_000, "gigajoule": 1_000_000_000, "wattsecond": 1.0, "watthour": 3_600, "kilowatthour": 3_600_000, "newtonmeter": 1.0, "calorie_nutr": 4_186.8, "kilocalorie_nutr": 4_186_800.00, ...
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"""simple docstring""" from scipy.stats import pearsonr, spearmanr from sklearn.metrics import fa_score, matthews_corrcoef import datasets UpperCAmelCase = """\ @inproceedings{wang2019glue, title={{GLUE}: A Multi-Task Benchmark and Analysis Platform for Natural Language Understanding}, author={Wang, Alex...
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"""simple docstring""" from __future__ import annotations def lowercase ( a__ : list , a__ : int | None = None , a__ : int | None = None ) -> None: if start is None: _UpperCamelCase = 0 if end is None: _UpperCamelCase ...
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"""simple docstring""" from __future__ import annotations from PIL import Image # Define glider example UpperCAmelCase = [ [0, 1, 0, 0, 0, 0, 0, 0], [0, 0, 1, 0, 0, 0, 0, 0], [1, 1, 1, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0], [0,...
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"""simple docstring""" def lowercase ( a__ : int , a__ : int ) -> int: return int((input_a, input_a).count(1 ) != 0 ) def lowercase ( ) -> None: assert or_gate(0 , 0 ) == 0 assert or_gate(0 , 1 ) == 1 assert or...
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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-2.0 # #...
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"""simple docstring""" import math import random def lowercase ( a__ : float , a__ : bool = False ) -> float: if deriv: return value * (1 - value) return 1 / (1 + math.exp(-value )) # Initial Value UpperCAmelCase = 0.02 def lowerc...
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"""simple docstring""" from __future__ import annotations import math def lowercase ( a__ : int ) -> list[int]: if num <= 0: _UpperCamelCase = F'''{num}: Invalid input, please enter a positive integer.''' raise ValueError(a__ ) _Upp...
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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 = logging.get_logger(__name__) UpperCAmelCase = { """facebook/xlm-roberta-xl""": """...
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"""simple docstring""" from typing import Callable, List, Optional, Tuple, Union import torch from transformers import CLIPTextModel, CLIPTokenizer from ...configuration_utils import ConfigMixin, register_to_config from ...models import ModelMixin, TransformeraDModel, VQModel from ...schedulers import VQDiffusionSch...
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"""simple docstring""" import unittest from transformers import PegasusConfig, PegasusTokenizer, is_flax_available from transformers.testing_utils import require_flax, slow from ...test_configuration_common import ConfigTester from ...test_modeling_flax_common import FlaxModelTesterMixin, ids_tensor if is_flax_ava...
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"""simple docstring""" import copy from ...configuration_utils import PretrainedConfig from ...utils import logging from ..auto import CONFIG_MAPPING UpperCAmelCase = logging.get_logger(__name__) UpperCAmelCase = { """ut/deta""": """https://huggingface.co/ut/deta/resolve/main/config.json""", } ...
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"""simple docstring""" from collections import defaultdict from pathlib import Path import pandas as pd from rouge_cli import calculate_rouge_path from utils import calculate_rouge UpperCAmelCase = [ """Prosecutor: \"No videos were used in the crash investigation\" German papers say they saw a cell phon...
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"""simple docstring""" def lowercase ( a__ : Tuple , a__ : str ) -> Tuple: return (pointa[0] - pointa[0]) ** 2 + (pointa[1] - pointa[1]) ** 2 def lowercase ( a__ : Optional[int] , a__ : List[str]=0 ) -> Optional[Any]: return ...
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"""simple docstring""" import os import unittest from transformers.models.bartpho.tokenization_bartpho import VOCAB_FILES_NAMES, BartphoTokenizer from transformers.testing_utils import get_tests_dir from ...test_tokenization_common import TokenizerTesterMixin UpperCAmelCase = get_tests_dir("""fixtures/test_...
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"""simple docstring""" import unittest from huggingface_hub import hf_hub_download from transformers import MODEL_FOR_VIDEO_CLASSIFICATION_MAPPING, VideoMAEFeatureExtractor from transformers.pipelines import VideoClassificationPipeline, pipeline from transformers.testing_utils import ( is_pipeline_test, nest...
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"""simple docstring""" import numpy as np def lowercase ( a__ : Optional[Any] , a__ : str , a__ : Union[str, Any] , a__ : Any , a__ : List[str] ) -> Dict: _UpperCamelCase = int(np.ceil((x_end - xa) / h ) ) _UpperCamelCa...
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"""simple docstring""" # limitations under the License. # NOTE: This file is deprecated and will be removed in a future version. # It only exists so that temporarely `from diffusers.pipelines import DiffusionPipeline` works from .pipelines import DiffusionPipeline, ImagePipelineOutput # noqa: F401 from .utils impor...
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"""simple docstring""" from collections import namedtuple UpperCAmelCase = namedtuple("""from_to""", """from_ to""") UpperCAmelCase = { """cubicmeter""": from_to(1, 1), """litre""": from_to(0.0_01, 1_000), """kilolitre""": from_to(1, 1), """gallon""": from_to(0.0_04_54, 2_64.1_72), ...
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"""simple docstring""" import warnings from typing import List import numpy as np from ...processing_utils import ProcessorMixin from ...tokenization_utils_base import BatchEncoding from ...utils import is_flax_available, is_tf_available, is_torch_available class UpperCAmelCase_ ( _lowercase): ...
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"""simple docstring""" def lowercase ( a__ : Union[str, Any] , a__ : Optional[int] ) -> int: # "extended trapezoidal rule" # int(f) = dx/2 * (f1 + 2f2 + ... + fn) _UpperCamelCase = (boundary[1] - boundary[0]) / steps _UpperCamelCase = ...
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"""simple docstring""" import unittest from transformers import PegasusConfig, PegasusTokenizer, is_flax_available from transformers.testing_utils import require_flax, slow from ...test_configuration_common import ConfigTester from ...test_modeling_flax_common import FlaxModelTesterMixin, ids_tensor if is_flax_ava...
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"""simple docstring""" def lowercase ( a__ : int ) -> List[Any]: _UpperCamelCase = 0 _UpperCamelCase = len(a__ ) for i in range(n - 1 ): for j in range(i + 1 , a__ ): if arr[i] > arr[j]: ...
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"""simple docstring""" import importlib.metadata import operator import re import sys from typing import Optional from packaging import version UpperCAmelCase = { """<""": operator.lt, """<=""": operator.le, """==""": operator.eq, """!=""": operator.ne, """>=""": operator.ge, """>""":...
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"""simple docstring""" from ...configuration_utils import PretrainedConfig from ...utils import logging UpperCAmelCase = logging.get_logger(__name__) UpperCAmelCase = { """transfo-xl-wt103""": """https://huggingface.co/transfo-xl-wt103/resolve/main/config.json""", } class UpperCAmelCas...
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"""simple docstring""" import numpy as np def lowercase ( a__ : Optional[Any] , a__ : str , a__ : Union[str, Any] , a__ : Any , a__ : List[str] ) -> Dict: _UpperCamelCase = int(np.ceil((x_end - xa) / h ) ) _UpperCamelCa...
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"""simple docstring""" import warnings from ...utils import is_sklearn_available, requires_backends if is_sklearn_available(): from scipy.stats import pearsonr, spearmanr from sklearn.metrics import fa_score, matthews_corrcoef UpperCAmelCase = ( """This metric will be removed from the library soon,...
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"""simple docstring""" import unittest import numpy as np from transformers import RoFormerConfig, is_flax_available from transformers.testing_utils import require_flax, slow from ...test_modeling_flax_common import FlaxModelTesterMixin, ids_tensor, random_attention_mask if is_flax_available(): import jax.numpy...
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"""simple docstring""" def lowercase ( a__ : Union[str, Any] ) -> List[Any]: _UpperCamelCase = [0] * len(a__ ) _UpperCamelCase = [] _UpperCamelCase = [] _UpperCamelCase = 0 for values in graph.values(): ...
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"""simple docstring""" import argparse import json from pathlib import Path import requests import torch from huggingface_hub import hf_hub_download from PIL import Image from transformers import ( MobileViTConfig, MobileViTForImageClassification, MobileViTForSemanticSegmentation, MobileViTImageProce...
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"""simple docstring""" def lowercase ( a__ : int = 1000000 ) -> int: _UpperCamelCase = [i - 1 for i in range(limit + 1 )] for i in range(2 , limit + 1 ): if phi[i] == i - 1: for j in range(2 * i , limit + 1 , a__ ): ...
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"""simple docstring""" from typing import List, Optional, Union from ...image_utils import ImageInput from ...processing_utils import ProcessorMixin from ...tokenization_utils_base import BatchEncoding, PaddingStrategy, PreTokenizedInput, TextInput, TruncationStrategy from ...utils import TensorType class ...
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"""simple docstring""" import warnings from ...utils import logging from .image_processing_segformer import SegformerImageProcessor UpperCAmelCase = logging.get_logger(__name__) class UpperCAmelCase_ ( _lowercase): def __init__( self : List[str] , *__UpperCamelCas...
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"""simple docstring""" import unittest from transformers import ( MODEL_FOR_SEQ_TO_SEQ_CAUSAL_LM_MAPPING, TF_MODEL_FOR_SEQ_TO_SEQ_CAUSAL_LM_MAPPING, TextaTextGenerationPipeline, pipeline, ) from transformers.testing_utils import is_pipeline_test, require_tf, require_torch from transformers.utils impor...
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"""simple docstring""" from ...configuration_utils import PretrainedConfig from ...utils import logging UpperCAmelCase = logging.get_logger(__name__) UpperCAmelCase = { """bigcode/gpt_bigcode-santacoder""": """https://huggingface.co/bigcode/gpt_bigcode-santacoder/resolve/main/config.json""", } ...
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"""simple docstring""" # NOTE: This file is deprecated and will be removed in a future version. # It only exists so that temporarely `from diffusers.pipelines import DiffusionPipeline` works from ...utils import deprecate from ..controlnet.pipeline_flax_controlnet import FlaxStableDiffusionControlNetPipeline # noqa:...
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"""simple docstring""" from __future__ import annotations def lowercase ( a__ : list[int | float] , a__ : int , a__ : int ) -> int | float: if len(a__ ) == 0: raise ValueError('''find_max() arg is an empty sequence''' ) if ( left...
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"""simple docstring""" import argparse from diffusers.pipelines.stable_diffusion.convert_from_ckpt import download_controlnet_from_original_ckpt if __name__ == "__main__": UpperCAmelCase = argparse.ArgumentParser() parser.add_argument( """--checkpoint_path""", default=None, type=str, required=True...
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"""simple docstring""" def lowercase ( a__ : Tuple , a__ : str ) -> Tuple: return (pointa[0] - pointa[0]) ** 2 + (pointa[1] - pointa[1]) ** 2 def lowercase ( a__ : Optional[int] , a__ : List[str]=0 ) -> Optional[Any]: return ...
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"""simple docstring""" from __future__ import annotations UpperCAmelCase = 8.988E9 # units = N * m^s * C^-2 def lowercase ( a__ : float , a__ : float , a__ : float , a__ : float ) -> dict[str, float]: _UpperCamelCase = abs(chargea ...
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"""simple docstring""" import unittest from transformers import DebertaVaConfig, 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 ModelTester...
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"""simple docstring""" import copy import json import os import tempfile from transformers import is_torch_available from .test_configuration_utils import config_common_kwargs class UpperCAmelCase_ ( _lowercase): def __init__( self : Any , __UpperCamelCase : Optional...
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"""simple docstring""" import datasets from .evaluate import evaluate UpperCAmelCase = """\ @article{hendrycks2021cuad, title={CUAD: An Expert-Annotated NLP Dataset for Legal Contract Review}, author={Dan Hendrycks and Collin Burns and Anya Chen and Spencer Ball}, journal={arXiv preprint ar...
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"""simple docstring""" import qiskit def lowercase ( a__ : int = 2 ) -> qiskit.result.counts.Counts: _UpperCamelCase = qubits # Using Aer's simulator _UpperCamelCase = qiskit.Aer.get_backend('''aer_simulator''' ) # Creating a Quan...
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"""simple docstring""" from __future__ import annotations from cmath import sqrt def lowercase ( a__ : int , a__ : int , a__ : int ) -> tuple[complex, complex]: if a == 0: raise ValueError('''Coefficient \'a\' must not be zero.''' ) _UpperC...
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"""simple docstring""" from scipy.stats import pearsonr, spearmanr from sklearn.metrics import fa_score, matthews_corrcoef import datasets UpperCAmelCase = """\ @inproceedings{wang2019glue, title={{GLUE}: A Multi-Task Benchmark and Analysis Platform for Natural Language Understanding}, author={Wang, Alex...
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"""simple docstring""" import copy from ...configuration_utils import PretrainedConfig from ...utils import logging from ..auto import CONFIG_MAPPING UpperCAmelCase = logging.get_logger(__name__) UpperCAmelCase = { """ut/deta""": """https://huggingface.co/ut/deta/resolve/main/config.json""", } ...
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"""simple docstring""" from __future__ import annotations from PIL import Image # Define glider example UpperCAmelCase = [ [0, 1, 0, 0, 0, 0, 0, 0], [0, 0, 1, 0, 0, 0, 0, 0], [1, 1, 1, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0], [0,...
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"""simple docstring""" # A Bipartite Graph is a graph whose vertices can be divided into two independent sets, # U and V such that every edge (u, v) either connects a vertex from U to V or a vertex # from V to U. In other words, for every edge (u, v), either u belongs to U and v to V, # or u belongs to V and v to U. W...
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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-2.0 # #...
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"""simple docstring""" import re from typing import Callable, List, Optional, Union import tensorflow as tf try: from tensorflow.keras.optimizers.legacy import Adam except ImportError: from tensorflow.keras.optimizers import Adam class UpperCAmelCase_ ( tf.keras.optimizers.schedules.LearningRat...
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"""simple docstring""" from __future__ import annotations import math def lowercase ( a__ : int ) -> list[int]: if num <= 0: _UpperCamelCase = F'''{num}: Invalid input, please enter a positive integer.''' raise ValueError(a__ ) _Upp...
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"""simple docstring""" import os import unittest from transformers import FunnelTokenizer, FunnelTokenizerFast from transformers.models.funnel.tokenization_funnel import VOCAB_FILES_NAMES from transformers.testing_utils import require_tokenizers from ...test_tokenization_common import TokenizerTesterMixin @re...
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"""simple docstring""" from typing import Callable, List, Optional, Tuple, Union import torch from transformers import CLIPTextModel, CLIPTokenizer from ...configuration_utils import ConfigMixin, register_to_config from ...models import ModelMixin, TransformeraDModel, VQModel from ...schedulers import VQDiffusionSch...
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"""simple docstring""" import dataclasses import json import sys import types from argparse import ArgumentDefaultsHelpFormatter, ArgumentParser, ArgumentTypeError from copy import copy from enum import Enum from inspect import isclass from pathlib import Path from typing import Any, Callable, Dict, Iterable, List, Li...
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"""simple docstring""" import copy from ...configuration_utils import PretrainedConfig from ...utils import logging from ..auto import CONFIG_MAPPING UpperCAmelCase = logging.get_logger(__name__) UpperCAmelCase = { """ut/deta""": """https://huggingface.co/ut/deta/resolve/main/config.json""", } ...
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"""simple docstring""" def lowercase ( a__ : str = "The quick brown fox jumps over the lazy dog" , ) -> bool: _UpperCamelCase = set() # Replace all the whitespace in our sentence _UpperCamelCase = input_str.replace(''' ''' , '''''' ) f...
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"""simple docstring""" def lowercase ( a__ : Tuple , a__ : str ) -> Tuple: return (pointa[0] - pointa[0]) ** 2 + (pointa[1] - pointa[1]) ** 2 def lowercase ( a__ : Optional[int] , a__ : List[str]=0 ) -> Optional[Any]: return ...
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"""simple docstring""" def lowercase ( a__ : str ) -> bool: _UpperCamelCase = 0 for ch in input_str: _UpperCamelCase = ord(a__ ) _UpperCamelCase = pow(2 , a__ ) # If we already turned on bit for cu...
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"""simple docstring""" import unittest from huggingface_hub import hf_hub_download from transformers import MODEL_FOR_VIDEO_CLASSIFICATION_MAPPING, VideoMAEFeatureExtractor from transformers.pipelines import VideoClassificationPipeline, pipeline from transformers.testing_utils import ( is_pipeline_test, nest...
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"""simple docstring""" import requests UpperCAmelCase = """""" # <-- Put your OpenWeatherMap appid here! UpperCAmelCase = """https://api.openweathermap.org/data/2.5/""" def lowercase ( a__ : str = "Chicago" , a__ : str = APPID ) -> dict: return requests...
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"""simple docstring""" # limitations under the License. # NOTE: This file is deprecated and will be removed in a future version. # It only exists so that temporarely `from diffusers.pipelines import DiffusionPipeline` works from .pipelines import DiffusionPipeline, ImagePipelineOutput # noqa: F401 from .utils impor...
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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-2.0 # #...
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"""simple docstring""" import warnings from typing import List import numpy as np from ...processing_utils import ProcessorMixin from ...tokenization_utils_base import BatchEncoding from ...utils import is_flax_available, is_tf_available, is_torch_available class UpperCAmelCase_ ( _lowercase): ...
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"""simple docstring""" import os from argparse import ArgumentParser from typing import List import torch.utils.data from datasets import Dataset, IterableDataset from datasets.distributed import split_dataset_by_node UpperCAmelCase = 4 UpperCAmelCase = 3 class UpperCAmelCase_ ( _low...
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"""simple docstring""" import unittest from transformers import PegasusConfig, PegasusTokenizer, is_flax_available from transformers.testing_utils import require_flax, slow from ...test_configuration_common import ConfigTester from ...test_modeling_flax_common import FlaxModelTesterMixin, ids_tensor if is_flax_ava...
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"""simple docstring""" import unittest import numpy as np import torch from torch import nn from transformers import ( CLIPImageProcessor, CLIPTextConfig, CLIPTextModelWithProjection, CLIPTokenizer, CLIPVisionConfig, CLIPVisionModelWithProjection, ) from diffusers import KandinskyVaaPriorPipe...
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"""simple docstring""" import importlib.metadata import operator import re import sys from typing import Optional from packaging import version UpperCAmelCase = { """<""": operator.lt, """<=""": operator.le, """==""": operator.eq, """!=""": operator.ne, """>=""": operator.ge, """>""":...
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"""simple docstring""" import numpy as np from PIL import Image def lowercase ( a__ : np.ndarray , a__ : int , a__ : int ) -> np.ndarray: _UpperCamelCase = np.array(a__ ) if arr.shape[0] != arr.shape[1]: raise ValueError('''The i...
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"""simple docstring""" import numpy as np def lowercase ( a__ : Optional[Any] , a__ : str , a__ : Union[str, Any] , a__ : Any , a__ : List[str] ) -> Dict: _UpperCamelCase = int(np.ceil((x_end - xa) / h ) ) _UpperCamelCa...
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"""simple docstring""" import argparse import torch from transformers import ( UniSpeechSatConfig, UniSpeechSatForAudioFrameClassification, UniSpeechSatForSequenceClassification, UniSpeechSatForXVector, WavaVecaFeatureExtractor, logging, ) logging.set_verbosity_info() UpperCAmelCase =...
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"""simple docstring""" import unittest import numpy as np from transformers import RoFormerConfig, is_flax_available from transformers.testing_utils import require_flax, slow from ...test_modeling_flax_common import FlaxModelTesterMixin, ids_tensor, random_attention_mask if is_flax_available(): import jax.numpy...
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"""simple docstring""" from pathlib import Path from typing import List from transformers import is_torch_available, is_vision_available from transformers.testing_utils import get_tests_dir, is_tool_test from transformers.tools.agent_types import AGENT_TYPE_MAPPING, AgentAudio, AgentImage, AgentText if is_torch_ava...
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"""simple docstring""" import argparse import json from pathlib import Path import requests import torch from huggingface_hub import hf_hub_download from PIL import Image from transformers import ( MobileViTConfig, MobileViTForImageClassification, MobileViTForSemanticSegmentation, MobileViTImageProce...
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"""simple docstring""" import pytest from datasets.utils.sharding import _distribute_shards, _number_of_shards_in_gen_kwargs, _split_gen_kwargs @pytest.mark.parametrize( '''kwargs, expected''' , [ ({'''num_shards''': 0, '''max_num_jobs''': 1}, []), ({'''num_shards''': 10, '''max_num_jobs'...
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"""simple docstring""" from typing import List, Optional, Union from ...image_utils import ImageInput from ...processing_utils import ProcessorMixin from ...tokenization_utils_base import BatchEncoding, PaddingStrategy, PreTokenizedInput, TextInput, TruncationStrategy from ...utils import TensorType class ...
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"""simple docstring""" import io import math from typing import Dict, Optional, Union import numpy as np from huggingface_hub import hf_hub_download from ...image_processing_utils import BaseImageProcessor, BatchFeature from ...image_transforms import convert_to_rgb, normalize, to_channel_dimension_format, to_pil_im...
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"""simple docstring""" import unittest from transformers import ( MODEL_FOR_SEQ_TO_SEQ_CAUSAL_LM_MAPPING, TF_MODEL_FOR_SEQ_TO_SEQ_CAUSAL_LM_MAPPING, TextaTextGenerationPipeline, pipeline, ) from transformers.testing_utils import is_pipeline_test, require_tf, require_torch from transformers.utils impor...
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"""simple docstring""" import multiprocessing import time from arguments import PretokenizationArguments from datasets import load_dataset from transformers import AutoTokenizer, HfArgumentParser def lowercase ( a__ : List[str] ) -> Any: _UpperCamelCase = {} ...
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"""simple docstring""" # NOTE: This file is deprecated and will be removed in a future version. # It only exists so that temporarely `from diffusers.pipelines import DiffusionPipeline` works from ...utils import deprecate from ..controlnet.pipeline_flax_controlnet import FlaxStableDiffusionControlNetPipeline # noqa:...
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"""simple docstring""" import tempfile import unittest import numpy as np from huggingface_hub import HfFolder, delete_repo from requests.exceptions import HTTPError from transformers import BertConfig, is_flax_available from transformers.testing_utils import TOKEN, USER, is_staging_test, require_flax if is_flax_a...
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"""simple docstring""" import argparse from diffusers.pipelines.stable_diffusion.convert_from_ckpt import download_controlnet_from_original_ckpt if __name__ == "__main__": UpperCAmelCase = argparse.ArgumentParser() parser.add_argument( """--checkpoint_path""", default=None, type=str, required=True...
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"""simple docstring""" import os from argparse import ArgumentParser, Namespace from ..data import SingleSentenceClassificationProcessor as Processor from ..pipelines import TextClassificationPipeline from ..utils import is_tf_available, is_torch_available, logging from . import BaseTransformersCLICommand if not is...
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"""simple docstring""" from __future__ import annotations UpperCAmelCase = 8.988E9 # units = N * m^s * C^-2 def lowercase ( a__ : float , a__ : float , a__ : float , a__ : float ) -> dict[str, float]: _UpperCamelCase = abs(chargea ...
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"""simple docstring""" import json import os import sys import tempfile import unittest from pathlib import Path from shutil import copyfile from huggingface_hub import HfFolder, Repository, create_repo, delete_repo from requests.exceptions import HTTPError import transformers from transformers import ( CONFIG_M...
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"""simple docstring""" import copy import json import os import tempfile from transformers import is_torch_available from .test_configuration_utils import config_common_kwargs class UpperCAmelCase_ ( _lowercase): def __init__( self : Any , __UpperCamelCase : Optional...
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"""simple docstring""" UpperCAmelCase = """ # Transformers installation ! pip install transformers datasets # To install from source instead of the last release, comment the command above and uncomment the following one. # ! pip install git+https://github.com/huggingface/transformers.git """ UpperCAmelCase ...
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"""simple docstring""" import qiskit def lowercase ( a__ : int = 2 ) -> qiskit.result.counts.Counts: _UpperCamelCase = qubits # Using Aer's simulator _UpperCamelCase = qiskit.Aer.get_backend('''aer_simulator''' ) # Creating a Quan...
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"""simple docstring""" import string from math import logaa def lowercase ( a__ : str , a__ : str ) -> int: _UpperCamelCase = document.translate( str.maketrans('''''' , '''''' , string.punctuation ) ).replace('''\n''' , '''''' ...
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"""simple docstring""" from scipy.stats import pearsonr, spearmanr from sklearn.metrics import fa_score, matthews_corrcoef import datasets UpperCAmelCase = """\ @inproceedings{wang2019glue, title={{GLUE}: A Multi-Task Benchmark and Analysis Platform for Natural Language Understanding}, author={Wang, Alex...
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"""simple docstring""" import unittest from accelerate import debug_launcher from accelerate.test_utils import require_cpu, test_ops, test_script @require_cpu class UpperCAmelCase_ ( unittest.TestCase): def _UpperCamelCase ( self : int ) -> str: debug_launcher...
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"""simple docstring""" from __future__ import annotations from PIL import Image # Define glider example UpperCAmelCase = [ [0, 1, 0, 0, 0, 0, 0, 0], [0, 0, 1, 0, 0, 0, 0, 0], [1, 1, 1, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0], [0,...
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"""simple docstring""" from typing import TYPE_CHECKING from ...utils import ( OptionalDependencyNotAvailable, _LazyModule, is_flax_available, is_tf_available, is_tokenizers_available, is_torch_available, ) UpperCAmelCase = { """configuration_blenderbot_small""": [ """BLEN...
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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-2.0 # #...
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"""simple docstring""" import warnings from ...utils import logging from .image_processing_beit import BeitImageProcessor UpperCAmelCase = logging.get_logger(__name__) class UpperCAmelCase_ ( _lowercase): def __init__( self : Optional[Any] , *__UpperCamelCase : ...
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"""simple docstring""" from __future__ import annotations import math def lowercase ( a__ : int ) -> list[int]: if num <= 0: _UpperCamelCase = F'''{num}: Invalid input, please enter a positive integer.''' raise ValueError(a__ ) _Upp...
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"""simple docstring""" from transformers import HfArgumentParser, TensorFlowBenchmark, TensorFlowBenchmarkArguments def lowercase ( ) -> List[Any]: _UpperCamelCase = HfArgumentParser(a__ ) _UpperCamelCase = parser.parse_args_into_dataclasses()[0] ...
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"""simple docstring""" from typing import Callable, List, Optional, Tuple, Union import torch from transformers import CLIPTextModel, CLIPTokenizer from ...configuration_utils import ConfigMixin, register_to_config from ...models import ModelMixin, TransformeraDModel, VQModel from ...schedulers import VQDiffusionSch...
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"""simple docstring""" import re from pathlib import Path from unittest import TestCase import pytest @pytest.mark.integration class UpperCAmelCase_ ( _lowercase): def _UpperCamelCase ( self : Optional[Any] , __UpperCamelCase : str ) -> List[str]: ...
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"""simple docstring""" import copy from ...configuration_utils import PretrainedConfig from ...utils import logging from ..auto import CONFIG_MAPPING UpperCAmelCase = logging.get_logger(__name__) UpperCAmelCase = { """ut/deta""": """https://huggingface.co/ut/deta/resolve/main/config.json""", } ...
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"""simple docstring""" import logging import os import sys from dataclasses import dataclass, field from itertools import chain from typing import Optional, Union import datasets import numpy as np import torch from datasets import load_dataset import transformers from transformers import ( AutoConfig, AutoM...
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"""simple docstring""" def lowercase ( a__ : Tuple , a__ : str ) -> Tuple: return (pointa[0] - pointa[0]) ** 2 + (pointa[1] - pointa[1]) ** 2 def lowercase ( a__ : Optional[int] , a__ : List[str]=0 ) -> Optional[Any]: return ...
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"""simple docstring""" import math import random from typing import Any from .hill_climbing import SearchProblem def lowercase ( a__ : List[Any] , a__ : bool = True , a__ : float = math.inf , a__ : float = -math.inf , a__ : float = math.inf , a__ : float =...
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"""simple docstring""" import unittest from huggingface_hub import hf_hub_download from transformers import MODEL_FOR_VIDEO_CLASSIFICATION_MAPPING, VideoMAEFeatureExtractor from transformers.pipelines import VideoClassificationPipeline, pipeline from transformers.testing_utils import ( is_pipeline_test, nest...
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"""simple docstring""" import argparse import os.path as osp import re import torch from safetensors.torch import load_file, save_file # =================# # UNet Conversion # # =================# UpperCAmelCase = [ # (stable-diffusion, HF Diffusers) ("""time_embed.0.weight""", """time_embedding.lin...
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"""simple docstring""" # limitations under the License. # NOTE: This file is deprecated and will be removed in a future version. # It only exists so that temporarely `from diffusers.pipelines import DiffusionPipeline` works from .pipelines import DiffusionPipeline, ImagePipelineOutput # noqa: F401 from .utils impor...
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"""simple docstring""" import unittest from transformers import is_torch_available from transformers.testing_utils import require_torch if is_torch_available(): import torch from transformers.generation import DisjunctiveConstraint @require_torch class UpperCAmelCase_ ( unittest.TestCase): ...
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"""simple docstring""" import warnings from typing import List import numpy as np from ...processing_utils import ProcessorMixin from ...tokenization_utils_base import BatchEncoding from ...utils import is_flax_available, is_tf_available, is_torch_available class UpperCAmelCase_ ( _lowercase): ...
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"""simple docstring""" from typing import Optional from urllib.parse import quote import huggingface_hub as hfh from packaging import version def lowercase ( a__ : str , a__ : str , a__ : Optional[str] = None ) -> str: if version.parse(hfh.__version__ ).re...
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"""simple docstring""" import unittest from transformers import PegasusConfig, PegasusTokenizer, is_flax_available from transformers.testing_utils import require_flax, slow from ...test_configuration_common import ConfigTester from ...test_modeling_flax_common import FlaxModelTesterMixin, ids_tensor if is_flax_ava...
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"""simple docstring""" import argparse import os from transformers.utils import direct_transformers_import # All paths are set with the intent you should run this script from the root of the repo with the command # python utils/check_task_guides.py UpperCAmelCase = """src/transformers""" UpperCAmelCase ...
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"""simple docstring""" import importlib.metadata import operator import re import sys from typing import Optional from packaging import version UpperCAmelCase = { """<""": operator.lt, """<=""": operator.le, """==""": operator.eq, """!=""": operator.ne, """>=""": operator.ge, """>""":...
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"""simple docstring""" import random import unittest import torch from diffusers import IFImgaImgSuperResolutionPipeline 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 im...
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"""simple docstring""" import numpy as np def lowercase ( a__ : Optional[Any] , a__ : str , a__ : Union[str, Any] , a__ : Any , a__ : List[str] ) -> Dict: _UpperCamelCase = int(np.ceil((x_end - xa) / h ) ) _UpperCamelCa...
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"""simple docstring""" from math import sqrt def lowercase ( a__ : int = 1000000 ) -> int: _UpperCamelCase = 0 _UpperCamelCase = 0 _UpperCamelCase = 42 while num_cuboids <= limit: max_cuboid_size += 1 f...
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"""simple docstring""" import unittest import numpy as np from transformers import RoFormerConfig, is_flax_available from transformers.testing_utils import require_flax, slow from ...test_modeling_flax_common import FlaxModelTesterMixin, ids_tensor, random_attention_mask if is_flax_available(): import jax.numpy...
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"""simple docstring""" import os import tempfile import unittest from pathlib import Path from transformers import AutoConfig, is_tf_available from transformers.testing_utils import require_tf if is_tf_available(): import tensorflow as tf from transformers import TensorFlowBenchmark, TensorFlowBenchmarkArgumen...
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"""simple docstring""" import argparse import json from pathlib import Path import requests import torch from huggingface_hub import hf_hub_download from PIL import Image from transformers import ( MobileViTConfig, MobileViTForImageClassification, MobileViTForSemanticSegmentation, MobileViTImageProce...
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"""simple docstring""" import argparse import shutil from pathlib import Path from tqdm import tqdm from transformers import AutoTokenizer def lowercase ( a__ : int , a__ : List[str] , a__ : Dict , a__ : Union[str, Any]=1024 ) -> Union[str, Any]: _Upp...
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"""simple docstring""" from typing import List, Optional, Union from ...image_utils import ImageInput from ...processing_utils import ProcessorMixin from ...tokenization_utils_base import BatchEncoding, PaddingStrategy, PreTokenizedInput, TextInput, TruncationStrategy from ...utils import TensorType class ...
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"""simple docstring""" import collections import tempfile import unittest import numpy as np from transformers.testing_utils import ( is_pt_flax_cross_test, require_flax, require_torch, require_vision, slow, torch_device, ) from transformers.utils import is_flax_available, is_torch_available,...
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"""simple docstring""" import unittest from transformers import ( MODEL_FOR_SEQ_TO_SEQ_CAUSAL_LM_MAPPING, TF_MODEL_FOR_SEQ_TO_SEQ_CAUSAL_LM_MAPPING, TextaTextGenerationPipeline, pipeline, ) from transformers.testing_utils import is_pipeline_test, require_tf, require_torch from transformers.utils impor...
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"""simple docstring""" from __future__ import annotations def lowercase ( a__ : int | str ) -> bool: _UpperCamelCase = str(a__ ) return n == n[::-1] def lowercase ( a__ : int = 1000000 ) -> List[Any]: _UpperCamelC...
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"""simple docstring""" # NOTE: This file is deprecated and will be removed in a future version. # It only exists so that temporarely `from diffusers.pipelines import DiffusionPipeline` works from ...utils import deprecate from ..controlnet.pipeline_flax_controlnet import FlaxStableDiffusionControlNetPipeline # noqa:...
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"""simple docstring""" from typing import List, Optional, Union from ...configuration_utils import PretrainedConfig from ...utils import logging UpperCAmelCase = logging.get_logger(__name__) UpperCAmelCase = { """huggingface/time-series-transformer-tourism-monthly""": ( """https://hugging...
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"""simple docstring""" import argparse from diffusers.pipelines.stable_diffusion.convert_from_ckpt import download_controlnet_from_original_ckpt if __name__ == "__main__": UpperCAmelCase = argparse.ArgumentParser() parser.add_argument( """--checkpoint_path""", default=None, type=str, required=True...
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"""simple docstring""" import gc import random import unittest import numpy as np import torch from transformers import CLIPTextConfig, CLIPTextModel, CLIPTokenizer from diffusers import AutoencoderKL, CycleDiffusionPipeline, DDIMScheduler, UNetaDConditionModel from diffusers.utils import floats_tensor, load_image, ...
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"""simple docstring""" from __future__ import annotations UpperCAmelCase = 8.988E9 # units = N * m^s * C^-2 def lowercase ( a__ : float , a__ : float , a__ : float , a__ : float ) -> dict[str, float]: _UpperCamelCase = abs(chargea ...
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"""simple docstring""" import unittest from dataclasses import dataclass import pytest from accelerate.commands.config.config_args import SageMakerConfig from accelerate.utils import ComputeEnvironment from accelerate.utils.launch import _convert_nargs_to_dict @dataclass class UpperCAmelCase_ ( _low...
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"""simple docstring""" import copy import json import os import tempfile from transformers import is_torch_available from .test_configuration_utils import config_common_kwargs class UpperCAmelCase_ ( _lowercase): def __init__( self : Any , __UpperCamelCase : Optional...
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"""simple docstring""" import warnings warnings.warn( """memory_utils has been reorganized to utils.memory. Import `find_executable_batchsize` from the main `__init__`: """ """`from accelerate import find_executable_batch_size` to avoid this warning.""", FutureWarning, )
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"""simple docstring""" import qiskit def lowercase ( a__ : int = 2 ) -> qiskit.result.counts.Counts: _UpperCamelCase = qubits # Using Aer's simulator _UpperCamelCase = qiskit.Aer.get_backend('''aer_simulator''' ) # Creating a Quan...
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"""simple docstring""" import os import tempfile import unittest import uuid from pathlib import Path from transformers.testing_utils import get_tests_dir, require_soundfile, require_torch, require_vision from transformers.tools.agent_types import AgentAudio, AgentImage, AgentText from transformers.utils import is_so...
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"""simple docstring""" from scipy.stats import pearsonr, spearmanr from sklearn.metrics import fa_score, matthews_corrcoef import datasets UpperCAmelCase = """\ @inproceedings{wang2019glue, title={{GLUE}: A Multi-Task Benchmark and Analysis Platform for Natural Language Understanding}, author={Wang, Alex...
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"""simple docstring""" def lowercase ( a__ : int , a__ : int ) -> int: while b: _UpperCamelCase , _UpperCamelCase = b, a % b return a def lowercase ( a__ : int , a__ : int ) -> int: retu...
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"""simple docstring""" from __future__ import annotations from PIL import Image # Define glider example UpperCAmelCase = [ [0, 1, 0, 0, 0, 0, 0, 0], [0, 0, 1, 0, 0, 0, 0, 0], [1, 1, 1, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0], [0,...
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"""simple docstring""" import secrets from random import shuffle from string import ascii_letters, ascii_lowercase, ascii_uppercase, digits, punctuation def lowercase ( a__ : int = 8 ) -> str: _UpperCamelCase = ascii_letters + digits + punctuation return "".j...
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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-2.0 # #...
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"""simple docstring""" import dataclasses import re import string from typing import Any, Dict, Iterator, List, Mapping, Optional, Sequence, Tuple import numpy as np from . import residue_constants UpperCAmelCase = Mapping[str, np.ndarray] UpperCAmelCase = Mapping[str, Any] # Is a nested dict. Upper...
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"""simple docstring""" from __future__ import annotations import math def lowercase ( a__ : int ) -> list[int]: if num <= 0: _UpperCamelCase = F'''{num}: Invalid input, please enter a positive integer.''' raise ValueError(a__ ) _Upp...
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"""simple docstring""" import re from filelock import FileLock try: import nltk UpperCAmelCase = True except (ImportError, ModuleNotFoundError): UpperCAmelCase = False if NLTK_AVAILABLE: with FileLock(""".lock""") as lock: nltk.download("""punkt""", quiet=True) def lowercase ...
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"""simple docstring""" from typing import Callable, List, Optional, Tuple, Union import torch from transformers import CLIPTextModel, CLIPTokenizer from ...configuration_utils import ConfigMixin, register_to_config from ...models import ModelMixin, TransformeraDModel, VQModel from ...schedulers import VQDiffusionSch...
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"""simple docstring""" import unittest import numpy as np from transformers import RoFormerConfig, is_flax_available from transformers.testing_utils import require_flax, slow from ...test_modeling_flax_common import FlaxModelTesterMixin, ids_tensor, random_attention_mask if is_flax_available(): import jax.numpy...
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"""simple docstring""" import copy from ...configuration_utils import PretrainedConfig from ...utils import logging from ..auto import CONFIG_MAPPING UpperCAmelCase = logging.get_logger(__name__) UpperCAmelCase = { """ut/deta""": """https://huggingface.co/ut/deta/resolve/main/config.json""", } ...
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"""simple docstring""" from typing import TYPE_CHECKING from ...utils import ( OptionalDependencyNotAvailable, _LazyModule, is_flax_available, is_tf_available, is_tokenizers_available, is_torch_available, ) UpperCAmelCase = { """configuration_roformer""": ["""ROFORMER_PRETRAINED_C...
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"""simple docstring""" def lowercase ( a__ : Tuple , a__ : str ) -> Tuple: return (pointa[0] - pointa[0]) ** 2 + (pointa[1] - pointa[1]) ** 2 def lowercase ( a__ : Optional[int] , a__ : List[str]=0 ) -> Optional[Any]: return ...
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"""simple docstring""" class UpperCAmelCase_ : def __init__( self : Optional[Any] ) -> None: _UpperCamelCase = {} # Mapping from char to TrieNode _UpperCamelCase = False def _UpperCamelCase ( self : List[str] , ...
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"""simple docstring""" import unittest from huggingface_hub import hf_hub_download from transformers import MODEL_FOR_VIDEO_CLASSIFICATION_MAPPING, VideoMAEFeatureExtractor from transformers.pipelines import VideoClassificationPipeline, pipeline from transformers.testing_utils import ( is_pipeline_test, nest...
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"""simple docstring""" 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_avai...
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"""simple docstring""" # limitations under the License. # NOTE: This file is deprecated and will be removed in a future version. # It only exists so that temporarely `from diffusers.pipelines import DiffusionPipeline` works from .pipelines import DiffusionPipeline, ImagePipelineOutput # noqa: F401 from .utils impor...
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"""simple docstring""" def lowercase ( a__ : int ) -> "list[int]": if upper_limit < 0: raise ValueError('''Limit for the Catalan sequence must be ≥ 0''' ) _UpperCamelCase = [0] * (upper_limit + 1) # Base case: C(0) = C(1) = 1 _UpperCamelCa...
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"""simple docstring""" import warnings from typing import List import numpy as np from ...processing_utils import ProcessorMixin from ...tokenization_utils_base import BatchEncoding from ...utils import is_flax_available, is_tf_available, is_torch_available class UpperCAmelCase_ ( _lowercase): ...
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"""simple docstring""" from typing import Dict, List, Optional, Union import numpy as np from .feature_extraction_utils import BatchFeature, FeatureExtractionMixin from .utils import PaddingStrategy, TensorType, is_tf_tensor, is_torch_tensor, logging, to_numpy UpperCAmelCase = logging.get_logger(__name__) ...
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"""simple docstring""" import unittest from transformers import PegasusConfig, PegasusTokenizer, is_flax_available from transformers.testing_utils import require_flax, slow from ...test_configuration_common import ConfigTester from ...test_modeling_flax_common import FlaxModelTesterMixin, ids_tensor if is_flax_ava...
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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 PreTrainedTokenizer from ...utils import logging UpperCAmelCase = logging.get_logger(__name__) UpperCAmelCase = """▁""" Upp...
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"""simple docstring""" import importlib.metadata import operator import re import sys from typing import Optional from packaging import version UpperCAmelCase = { """<""": operator.lt, """<=""": operator.le, """==""": operator.eq, """!=""": operator.ne, """>=""": operator.ge, """>""":...
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"""simple docstring""" from __future__ import annotations from collections import deque class UpperCAmelCase_ : def __init__( self : str , __UpperCamelCase : list[str] ) -> Union[str, Any]: _UpperCamelCase = [] self.adlist.append( ...
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"""simple docstring""" import numpy as np def lowercase ( a__ : Optional[Any] , a__ : str , a__ : Union[str, Any] , a__ : Any , a__ : List[str] ) -> Dict: _UpperCamelCase = int(np.ceil((x_end - xa) / h ) ) _UpperCamelCa...
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"""simple docstring""" from jiwer import compute_measures import datasets UpperCAmelCase = """\ @inproceedings{inproceedings, author = {Morris, Andrew and Maier, Viktoria and Green, Phil}, year = {2004}, month = {01}, pages = {}, title = {From WER and RIL to MER and WIL: improved evaluati...
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"""simple docstring""" import unittest import numpy as np from transformers import RoFormerConfig, is_flax_available from transformers.testing_utils import require_flax, slow from ...test_modeling_flax_common import FlaxModelTesterMixin, ids_tensor, random_attention_mask if is_flax_available(): import jax.numpy...
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"""simple docstring""" import gc import unittest import numpy as np import torch from transformers import CLIPTextConfig, CLIPTextModel, CLIPTokenizer from diffusers import AutoencoderKL, DDIMScheduler, LDMTextToImagePipeline, UNetaDConditionModel from diffusers.utils.testing_utils import ( enable_full_determini...
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"""simple docstring""" import argparse import json from pathlib import Path import requests import torch from huggingface_hub import hf_hub_download from PIL import Image from transformers import ( MobileViTConfig, MobileViTForImageClassification, MobileViTForSemanticSegmentation, MobileViTImageProce...
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"""simple docstring""" import json import multiprocessing as mp import re from collections import defaultdict from functools import partial from typing import Dict, List, Optional, Set, Tuple, Type from datasets import Dataset from datasketch import MinHash, MinHashLSH from dpu_utils.utils.iterators import ThreadedIt...
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"""simple docstring""" from typing import List, Optional, Union from ...image_utils import ImageInput from ...processing_utils import ProcessorMixin from ...tokenization_utils_base import BatchEncoding, PaddingStrategy, PreTokenizedInput, TextInput, TruncationStrategy from ...utils import TensorType class ...
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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, convert_to_rgb, get_resize_output_image_size, normalize, rescale, resiz...
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"""simple docstring""" import unittest from transformers import ( MODEL_FOR_SEQ_TO_SEQ_CAUSAL_LM_MAPPING, TF_MODEL_FOR_SEQ_TO_SEQ_CAUSAL_LM_MAPPING, TextaTextGenerationPipeline, pipeline, ) from transformers.testing_utils import is_pipeline_test, require_tf, require_torch from transformers.utils impor...
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"""simple docstring""" from itertools import permutations def lowercase ( a__ : tuple ) -> bool: if num[3] % 2 != 0: return False if (num[2] + num[3] + num[4]) % 3 != 0: return False if num[5] % 5 != 0: return False _UpperCamelCa...
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"""simple docstring""" # NOTE: This file is deprecated and will be removed in a future version. # It only exists so that temporarely `from diffusers.pipelines import DiffusionPipeline` works from ...utils import deprecate from ..controlnet.pipeline_flax_controlnet import FlaxStableDiffusionControlNetPipeline # noqa:...
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"""simple docstring""" import unittest from transformers import ( MODEL_FOR_SEQ_TO_SEQ_CAUSAL_LM_MAPPING, TF_MODEL_FOR_SEQ_TO_SEQ_CAUSAL_LM_MAPPING, TextaTextGenerationPipeline, pipeline, ) from transformers.testing_utils import is_pipeline_test, require_tf, require_torch from transformers.utils impor...
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"""simple docstring""" import argparse from diffusers.pipelines.stable_diffusion.convert_from_ckpt import download_controlnet_from_original_ckpt if __name__ == "__main__": UpperCAmelCase = argparse.ArgumentParser() parser.add_argument( """--checkpoint_path""", default=None, type=str, required=True...
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"""simple docstring""" import copy import re class UpperCAmelCase_ : snake_case__ = '''hp''' snake_case__ = {} snake_case__ = None @classmethod def _UpperCamelCase ( cls : Optional[Any] , __UpperCamelCase : Any , ...
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"""simple docstring""" from __future__ import annotations UpperCAmelCase = 8.988E9 # units = N * m^s * C^-2 def lowercase ( a__ : float , a__ : float , a__ : float , a__ : float ) -> dict[str, float]: _UpperCamelCase = abs(chargea ...
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"""simple docstring""" import argparse import torch from transformers import BertForMaskedLM if __name__ == "__main__": UpperCAmelCase = argparse.ArgumentParser( description=( """Extraction some layers of the full BertForMaskedLM or RObertaForMaskedLM for Transfer Learned""" """ ...
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"""simple docstring""" import copy import json import os import tempfile from transformers import is_torch_available from .test_configuration_utils import config_common_kwargs class UpperCAmelCase_ ( _lowercase): def __init__( self : Any , __UpperCamelCase : Optional...
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"""simple docstring""" import argparse import json import os import torch from transformers import LukeConfig, LukeModel, LukeTokenizer, RobertaTokenizer from transformers.tokenization_utils_base import AddedToken @torch.no_grad() def lowercase ( a__ : List[str] , a__ : Optional[int] ...
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"""simple docstring""" import qiskit def lowercase ( a__ : int = 2 ) -> qiskit.result.counts.Counts: _UpperCamelCase = qubits # Using Aer's simulator _UpperCamelCase = qiskit.Aer.get_backend('''aer_simulator''' ) # Creating a Quan...
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"""simple docstring""" import argparse from pathlib import Path from typing import Dict, OrderedDict, Tuple import torch from audiocraft.models import MusicGen from transformers import ( AutoFeatureExtractor, AutoTokenizer, EncodecModel, MusicgenDecoderConfig, MusicgenForConditionalGeneration, ...
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"""simple docstring""" from scipy.stats import pearsonr, spearmanr from sklearn.metrics import fa_score, matthews_corrcoef import datasets UpperCAmelCase = """\ @inproceedings{wang2019glue, title={{GLUE}: A Multi-Task Benchmark and Analysis Platform for Natural Language Understanding}, author={Wang, Alex...
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"""simple docstring""" import itertools import math def lowercase ( a__ : int ) -> 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 mult...
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"""simple docstring""" from __future__ import annotations from PIL import Image # Define glider example UpperCAmelCase = [ [0, 1, 0, 0, 0, 0, 0, 0], [0, 0, 1, 0, 0, 0, 0, 0], [1, 1, 1, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0], [0,...
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"""simple docstring""" import random import unittest import numpy as np import torch from diffusers import ( DPMSolverMultistepScheduler, EulerAncestralDiscreteScheduler, EulerDiscreteScheduler, LMSDiscreteScheduler, OnnxStableDiffusionUpscalePipeline, PNDMScheduler, ) from diffusers.utils im...
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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-2.0 # #...
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"""simple docstring""" import collections import os import re from pathlib import Path UpperCAmelCase = """src/transformers""" # Matches is_xxx_available() UpperCAmelCase = re.compile(r"""is\_([a-z_]*)_available()""") # Catches a one-line _import_struct = {xxx} UpperCAmelCase = re.compile(r"""...
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"""simple docstring""" from __future__ import annotations import math def lowercase ( a__ : int ) -> list[int]: if num <= 0: _UpperCamelCase = F'''{num}: Invalid input, please enter a positive integer.''' raise ValueError(a__ ) _Upp...
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"""simple docstring""" import argparse import json from pathlib import Path import requests import torch from huggingface_hub import hf_hub_download from PIL import Image from transformers import ( MobileViTConfig, MobileViTForImageClassification, MobileViTForSemanticSegmentation, MobileViTImageProce...
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"""simple docstring""" from typing import Callable, List, Optional, Tuple, Union import torch from transformers import CLIPTextModel, CLIPTokenizer from ...configuration_utils import ConfigMixin, register_to_config from ...models import ModelMixin, TransformeraDModel, VQModel from ...schedulers import VQDiffusionSch...
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"""simple docstring""" import importlib import os import sys # This is required to make the module import works (when the python process is running from the root of the repo) sys.path.append(""".""") def lowercase ( a__ : List[str] ) -> List[str]: _UpperCamelCase = ...
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"""simple docstring""" import copy from ...configuration_utils import PretrainedConfig from ...utils import logging from ..auto import CONFIG_MAPPING UpperCAmelCase = logging.get_logger(__name__) UpperCAmelCase = { """ut/deta""": """https://huggingface.co/ut/deta/resolve/main/config.json""", } ...
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"""simple docstring""" UpperCAmelCase = frozenset( [ """prompt""", """height""", """width""", """guidance_scale""", """negative_prompt""", """prompt_embeds""", """negative_prompt_embeds""", """cross_attention_kwargs""", ] ) UpperCAmelCase ...
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"""simple docstring""" def lowercase ( a__ : Tuple , a__ : str ) -> Tuple: return (pointa[0] - pointa[0]) ** 2 + (pointa[1] - pointa[1]) ** 2 def lowercase ( a__ : Optional[int] , a__ : List[str]=0 ) -> Optional[Any]: return ...
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