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import os import socket from contextlib import contextmanager import torch from ..commands.config.default import write_basic_config # noqa: F401 from ..state import PartialState from .dataclasses import DistributedType from .imports import is_deepspeed_available, is_tpu_available from .transformer_engine import ...
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from ...configuration_utils import PretrainedConfig from ...utils import logging __lowerCAmelCase : str =logging.get_logger(__name__) __lowerCAmelCase : Any ={ # See all MEGATRON_BERT models at https://huggingface.co/models?filter=bert } class _lowercase ( A__ ):...
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'''simple docstring''' import sacrebleu as scb from packaging import version from sacrebleu import CHRF import datasets lowerCAmelCase__ = '''\ @inproceedings{popovic-2015-chrf, title = "chr{F}: character n-gram {F}-score for automatic {MT} evaluation", author = "Popovi{\'c}, Maja", book...
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import os import sys import unittest __lowerCAmelCase : List[Any] =os.path.abspath(os.path.dirname(os.path.dirname(os.path.dirname(__file__)))) sys.path.append(os.path.join(git_repo_path, 'utils')) import check_dummies # noqa: E402 from check_dummies import create_dummy_files, create_dummy_obj...
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'''simple docstring''' import json import os import shutil import tempfile import unittest import numpy as np import pytest from transformers import BertTokenizer, BertTokenizerFast from transformers.models.bert.tokenization_bert import VOCAB_FILES_NAMES from transformers.testing_utils import require_vision fr...
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import math from numpy import inf from scipy.integrate import quad def _UpperCamelCase ( lowercase__ ): if num <= 0: raise ValueError('''math domain error''' ) return quad(lowercase__ , 0 , lowercase__ , args=(lowercase__) )[0] def _UpperCamelCase ( l...
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from argparse import ArgumentParser from ..pipelines import Pipeline, PipelineDataFormat, get_supported_tasks, pipeline from ..utils import logging from . import BaseTransformersCLICommand lowerCAmelCase = logging.get_logger(__name__) # pylint: disable=invalid-name def _a ( SCREAMING_SNA...
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def _UpperCamelCase ( lowercase__ , lowercase__ , lowercase__ ): if principal <= 0: raise Exception('''Principal borrowed must be > 0''' ) if rate_per_annum < 0: raise Exception('''Rate of interest must be >= 0''' ) if years_to_repay <= 0 or not isinsta...
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'''simple docstring''' from __future__ import annotations import math import numpy as np from numpy.linalg import norm def A_ ( _lowerCAmelCase : np.ndarray , _lowerCAmelCase : np.ndarray ): """simple docstring""" return math.sqrt(sum(pow(a - b , ...
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from maths.is_square_free import is_square_free from maths.prime_factors import prime_factors def _UpperCamelCase ( lowercase__ ): __SCREAMING_SNAKE_CASE : Tuple = prime_factors(lowercase__ ) if is_square_free(lowercase__ ): return -1 if len(lowercase__ ) % 2 else 1 ...
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import numpy as np import torch import tqdm from ...models.unet_ad import UNetaDModel from ...pipelines import DiffusionPipeline from ...utils import randn_tensor from ...utils.dummy_pt_objects import DDPMScheduler class lowerCAmelCase_ ( lowercase ): """simple docstring""" de...
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import json import os import shutil import sys import tempfile import unittest import unittest.mock as mock from pathlib import Path from huggingface_hub import HfFolder, delete_repo from requests.exceptions import HTTPError from transformers import AutoConfig, BertConfig, GPTaConfig from transformers.configuratio...
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"""simple docstring""" def lowerCamelCase_( _lowerCamelCase = 100 ) -> int: '''simple docstring''' _lowerCamelCase : List[str] = set() _lowerCamelCase : Optional[Any] = 0 _lowerCamelCase : Optional[int] = n + 1 # maximum limi...
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from typing import TYPE_CHECKING from ...utils import ( OptionalDependencyNotAvailable, _LazyModule, is_sentencepiece_available, is_tokenizers_available, is_torch_available, ) __lowerCAmelCase : Any ={ 'configuration_llama': ['LLAMA_PRETRAINED_CONFIG_ARCHIVE_MAP', 'Llama...
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from __future__ import annotations import math import numpy as np from numpy.linalg import norm def UpperCAmelCase__ ( lowerCamelCase_ : np.ndarray , lowerCamelCase_ : np.ndarray ): return math.sqrt(sum(pow(a - b , 2 ) for a, b in zip(lowerCam...
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from ...configuration_utils import PretrainedConfig from ...utils import logging __lowerCAmelCase : Dict =logging.get_logger(__name__) __lowerCAmelCase : List[Any] ={ 'google/switch-base-8': 'https://huggingface.co/google/switch-base-8/blob/main/config.json', } class _...
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'''simple docstring''' import gc import unittest import torch from parameterized import parameterized from diffusers import AutoencoderKL from diffusers.utils import floats_tensor, load_hf_numpy, require_torch_gpu, slow, torch_all_close, torch_device from diffusers.utils.import_utils import is_xformers_available fr...
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from dataclasses import dataclass from typing import List, Optional, Union import numpy as np import torch from ...utils import BaseOutput, OptionalDependencyNotAvailable, is_torch_available, is_transformers_available @dataclass class _lowercase ( A__ ): '''simple docstring''' SCREAMING_S...
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"""simple docstring""" from collections import OrderedDict from typing import Mapping from packaging import version from ...configuration_utils import PretrainedConfig from ...onnx import OnnxConfig from ...utils import logging from ...utils.backbone_utils import BackboneConfigMixin, get_aligned_...
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from datetime import datetime import requests def _UpperCamelCase ( lowercase__ ): __SCREAMING_SNAKE_CASE : Optional[int] = '''https://downloadgram.net/wp-json/wppress/video-downloader/video?url=''' __SCREAMING_SNAKE_CASE : Tuple = requests.get(base_url + url ).js...
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'''simple docstring''' import json from typing import List, Optional, Tuple from tokenizers import normalizers from ...tokenization_utils_fast import PreTrainedTokenizerFast from ...utils import logging from .tokenization_convbert import ConvBertTokenizer UpperCamelCase : str = logging.ge...
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import gc import random import unittest import numpy as np import torch from PIL import Image from transformers import CLIPTextConfig, CLIPTextModel, CLIPTokenizer from diffusers import ( AutoencoderKL, DDIMScheduler, EulerAncestralDiscreteScheduler, LMSDiscreteScheduler, PNDMScheduler, Sta...
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'''simple docstring''' from ...configuration_utils import PretrainedConfig from ...utils import logging a__ : Union[str, Any] = logging.get_logger(__name__) a__ : Optional[int] = { # See all MEGATRON_BERT models at https://huggingface.co/models?filter=bert } ...
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# DISCLAIMER: This code is strongly influenced by https://github.com/pesser/pytorch_diffusion # and https://github.com/hojonathanho/diffusion import math from dataclasses import dataclass from typing import List, Optional, Tuple, Union import numpy as np import torch from diffusers.configuration_utils import Confi...
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"""simple docstring""" import unittest import numpy as np import timeout_decorator # noqa from transformers import BlenderbotSmallConfig, is_flax_available from transformers.testing_utils import require_flax, slow from ...generation.test_flax_utils import FlaxGenerationTesterMixin ...
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from dataclasses import dataclass, field from typing import ClassVar, Dict from ..features import Features, Value from .base import TaskTemplate @dataclass(frozen=A__ ) class _lowercase ( A__ ): '''simple docstring''' SCREAMING_SNAKE_CASE__ : str = field(default=''...
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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 _snake_case : Union[str, Any] = ( 'This metric will be removed from the...
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def _UpperCamelCase ( lowercase__ = 10**9 ): __SCREAMING_SNAKE_CASE : List[str] = 1 __SCREAMING_SNAKE_CASE : int = 2 __SCREAMING_SNAKE_CASE : Union[str, Any] = 0 __SCREAMING_SNAKE_CASE : Dict = 0 __SCREAMING_SNAKE_CA...
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class A : def __init__( self: Dict ) -> Tuple: '''simple docstring''' UpperCAmelCase_ =0 UpperCAmelCase_ =0 UpperCAmelCase_ ={} def lowerCAmelCase__ ( self: Option...
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def _UpperCamelCase ( lowercase__ , lowercase__ ): __SCREAMING_SNAKE_CASE : str = len(lowercase__ ) __SCREAMING_SNAKE_CASE : Optional[int] = len(lowercase__ ) __SCREAMING_SNAKE_CASE : List[str] = [[False for _ in range(m + 1 )] for _ in ...
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from .imports import is_rich_available if is_rich_available(): from rich.traceback import install install(show_locals=False) else: raise ModuleNotFoundError('To use the rich extension, install rich with `pip install rich`')
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from scipy.stats import pearsonr import datasets __lowerCAmelCase : str ='\nPearson correlation coefficient and p-value for testing non-correlation.\nThe Pearson correlation coefficient measures the linear relationship between two datasets. The calculation of the p-value relies on the assumptio...
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'''simple docstring''' from collections.abc import Generator from math import sin def _a (lowercase__ : bytes ) -> bytes: """simple docstring""" if len(lowercase__ ) != 3_2: raise ValueError('Input must be of length 32' ) __snake_case = ...
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import json from typing import List, Optional, Tuple from tokenizers import normalizers from ...tokenization_utils_fast import PreTrainedTokenizerFast from ...utils import logging from .tokenization_mobilebert import MobileBertTokenizer __lowerCAmelCase : List[str] =logging.get_logger(__name__...
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from __future__ import annotations def snake_case (UpperCAmelCase__ ) -> float: if not nums: raise ValueError('List is empty' ) return sum(UpperCAmelCase__ ) / len(UpperCAmelCase__ ) if __name__ == "__main__": import doctest doctest.testmod()
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import os def _UpperCamelCase ( lowercase__ ): __SCREAMING_SNAKE_CASE : Optional[Any] = len(grid[0] ) __SCREAMING_SNAKE_CASE : str = len(lowercase__ ) __SCREAMING_SNAKE_CASE : Optional[int] = 0 __SCREAMING_SNAKE_CASE : Any = ...
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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, ) __lowerCAmelCase : List[str] = { '''configuration_m...
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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 import ConfigTester from ...te...
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from typing import TYPE_CHECKING from ...utils import ( OptionalDependencyNotAvailable, _LazyModule, is_torch_available, ) __A = { "configuration_swiftformer": [ "SWIFTFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP", "SwiftFormerConfig", "SwiftFormerOnnxConfig", ...
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import os from datetime import datetime as dt from github import Github __lowerCAmelCase : List[Any] =[ 'good first issue', 'good second issue', 'good difficult issue', 'enhancement', 'new pipeline/model', 'new scheduler', 'wip', ] def _UpperCamelCase ( ): ...
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# Copyright 2021 The HuggingFace Team. All rights reserved. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by app...
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from ...configuration_utils import PretrainedConfig from ...utils import logging __lowerCAmelCase : Dict =logging.get_logger(__name__) __lowerCAmelCase : Dict ={ 'google/canine-s': 'https://huggingface.co/google/canine-s/resolve/main/config.json', # See all CANINE mod...
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# Usage: # ./gen-card-facebook-wmt19.py import os from pathlib import Path def _A ( lowerCAmelCase_ : str , lowerCAmelCase_ : Dict , lowerCAmelCase_ : int ): """simple docstring""" lowerCAmelCase__ = { "en": "Machine learning is ...
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from ...configuration_utils import PretrainedConfig from ...utils import logging __lowerCAmelCase : List[Any] =logging.get_logger(__name__) __lowerCAmelCase : Tuple ={ 'transfo-xl-wt103': 'https://huggingface.co/transfo-xl-wt103/resolve/main/config.json', } class _lowe...
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from __future__ import annotations snake_case = [ [-1, 0], # left [0, -1], # down [1, 0], # right [0, 1], # up ] def lowerCamelCase__ ( lowercase , lowercase , lowercase , lowercase , lowercase , ): """simple docstring""" SCREAMING_SNAKE_CASE...
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from ...configuration_utils import PretrainedConfig from ...utils import logging __lowerCAmelCase : str =logging.get_logger(__name__) __lowerCAmelCase : Any ={ # See all MEGATRON_BERT models at https://huggingface.co/models?filter=bert } class _lowercase ( A__ ):...
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from unittest import TestCase from datasets import Dataset from minhash_deduplication import deduplicate_dataset, make_duplicate_clusters def lowerCamelCase__ ( ): __UpperCAmelCase : int = { """repo_name""": ["""test_repo1""", """test_repo2""", """test_r...
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import os import sys import unittest __lowerCAmelCase : List[Any] =os.path.abspath(os.path.dirname(os.path.dirname(os.path.dirname(__file__)))) sys.path.append(os.path.join(git_repo_path, 'utils')) import check_dummies # noqa: E402 from check_dummies import create_dummy_files, create_dummy_obj...
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import warnings from typing import Any, Dict, List, Optional, Union import numpy as np from ...audio_utils import mel_filter_bank, optimal_fft_length, spectrogram, window_function from ...feature_extraction_sequence_utils import SequenceFeatureExtractor from ...feature_extraction_utils import BatchFeature from ...uti...
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import math from numpy import inf from scipy.integrate import quad def _UpperCamelCase ( lowercase__ ): if num <= 0: raise ValueError('''math domain error''' ) return quad(lowercase__ , 0 , lowercase__ , args=(lowercase__) )[0] def _UpperCamelCase ( l...
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"""simple docstring""" from __future__ import annotations from collections import deque from collections.abc import Sequence from dataclasses import dataclass from typing import Any @dataclass class __lowercase : snake_case_ = 42 snake_case_ = ...
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def _UpperCamelCase ( lowercase__ , lowercase__ , lowercase__ ): if principal <= 0: raise Exception('''Principal borrowed must be > 0''' ) if rate_per_annum < 0: raise Exception('''Rate of interest must be >= 0''' ) if years_to_repay <= 0 or not isinsta...
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import argparse import hashlib # hashlib is only used inside the Test class import struct class lowerCAmelCase_ : def __init__( self , _lowerCAmelCase ): _lowercase : int = data _lowercase : Optional[int] = [0x67_452_301, 0xef_cda_...
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from maths.is_square_free import is_square_free from maths.prime_factors import prime_factors def _UpperCamelCase ( lowercase__ ): __SCREAMING_SNAKE_CASE : Tuple = prime_factors(lowercase__ ) if is_square_free(lowercase__ ): return -1 if len(lowercase__ ) % 2 else 1 ...
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from typing import Dict, Iterable, List, Optional, Union import numpy as np from ...image_processing_utils import BaseImageProcessor, BatchFeature, get_size_dict from ...image_transforms import ( center_crop, get_resize_output_image_size, normalize, rescale, resize, to_c...
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import json import os import shutil import sys import tempfile import unittest import unittest.mock as mock from pathlib import Path from huggingface_hub import HfFolder, delete_repo from requests.exceptions import HTTPError from transformers import AutoConfig, BertConfig, GPTaConfig from transformers.configuratio...
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import os import unittest from huggingface_hub.utils import are_progress_bars_disabled import transformers.models.bart.tokenization_bart from transformers import logging from transformers.testing_utils import CaptureLogger, mockenv, mockenv_context from transformers.utils.logging import disable_progress_bar, e...
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from typing import TYPE_CHECKING from ...utils import ( OptionalDependencyNotAvailable, _LazyModule, is_sentencepiece_available, is_tokenizers_available, is_torch_available, ) __lowerCAmelCase : Any ={ 'configuration_llama': ['LLAMA_PRETRAINED_CONFIG_ARCHIVE_MAP', 'Llama...
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'''simple docstring''' import argparse import json import requests import torch from huggingface_hub import hf_hub_download from PIL import Image from torchvision import transforms from transformers import BitImageProcessor, FocalNetConfig, FocalNetForImageClassification from transformers.image...
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from ...configuration_utils import PretrainedConfig from ...utils import logging __lowerCAmelCase : Dict =logging.get_logger(__name__) __lowerCAmelCase : List[Any] ={ 'google/switch-base-8': 'https://huggingface.co/google/switch-base-8/blob/main/config.json', } class _...
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from math import ceil, sqrt def _SCREAMING_SNAKE_CASE ( lowercase : int = 1_00_00_00 ): '''simple docstring''' lowerCamelCase_ = 0 for outer_width in range(3 , (limit // 4) + 2 ): if outer_width**2 > limit: ...
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from dataclasses import dataclass from typing import List, Optional, Union import numpy as np import torch from ...utils import BaseOutput, OptionalDependencyNotAvailable, is_torch_available, is_transformers_available @dataclass class _lowercase ( A__ ): '''simple docstring''' SCREAMING_S...
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'''simple docstring''' from typing import Mapping from ...configuration_utils import PretrainedConfig from ...onnx import OnnxSeqaSeqConfigWithPast from ...utils import logging _lowerCamelCase = logging.get_logger(__name__) _lowerCamelCase = { """t5-small""": """https:...
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from datetime import datetime import requests def _UpperCamelCase ( lowercase__ ): __SCREAMING_SNAKE_CASE : Optional[int] = '''https://downloadgram.net/wp-json/wppress/video-downloader/video?url=''' __SCREAMING_SNAKE_CASE : Tuple = requests.get(base_url + url ).js...
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'''simple docstring''' # Logistic Regression from scratch # In[62]: # In[63]: # importing all the required libraries import numpy as np from matplotlib import pyplot as plt from sklearn import datasets def UpperCamelCase ( lowercase_ : Tuple ) -> Optional[Any]: '''simple docstring''' ...
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import gc import random import unittest import numpy as np import torch from PIL import Image from transformers import CLIPTextConfig, CLIPTextModel, CLIPTokenizer from diffusers import ( AutoencoderKL, DDIMScheduler, EulerAncestralDiscreteScheduler, LMSDiscreteScheduler, PNDMScheduler, Sta...
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a_ : str = 'Alexander Joslin' import operator as op from .stack import Stack def lowerCamelCase__ (_UpperCAmelCase): SCREAMING_SNAKE_CASE = {'*': op.mul, '/': op.truediv, '+': op.add, '-': op.sub} SCREAMING_SNAKE_CASE = Stack() SCREAMING_SNAKE_CASE ...
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# DISCLAIMER: This code is strongly influenced by https://github.com/pesser/pytorch_diffusion # and https://github.com/hojonathanho/diffusion import math from dataclasses import dataclass from typing import List, Optional, Tuple, Union import numpy as np import torch from diffusers.configuration_utils import Confi...
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import argparse import gdown import numpy as np import torch from huggingface_hub import hf_hub_download from transformers import ( CLIPTokenizer, CLIPTokenizerFast, VideoMAEImageProcessor, XCLIPConfig, XCLIPModel, XCLIPProcessor, XCLIPTextConfig, XCLIPVisionConfig, ) def a__...
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from dataclasses import dataclass, field from typing import ClassVar, Dict from ..features import Features, Value from .base import TaskTemplate @dataclass(frozen=A__ ) class _lowercase ( A__ ): '''simple docstring''' SCREAMING_SNAKE_CASE__ : str = field(default=''...
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'''simple docstring''' import json import sys def a__ ( lowerCAmelCase__ , lowerCAmelCase__ ) -> List[str]: with open(lowerCAmelCase__ , encoding='''utf-8''' ) as f: UpperCAmelCase__ : Union[str, Any] = json.load(lowerCAmelCase__ ) ...
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def _UpperCamelCase ( lowercase__ = 10**9 ): __SCREAMING_SNAKE_CASE : List[str] = 1 __SCREAMING_SNAKE_CASE : int = 2 __SCREAMING_SNAKE_CASE : Union[str, Any] = 0 __SCREAMING_SNAKE_CASE : Dict = 0 __SCREAMING_SNAKE_CA...
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"""simple docstring""" import gc import unittest import numpy as np import torch import torch.nn.functional as F from transformers import ( ClapTextConfig, ClapTextModelWithProjection, RobertaTokenizer, SpeechTaHifiGan, SpeechTaHifiGanConfig, ) from diffusers impor...
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def _UpperCamelCase ( lowercase__ , lowercase__ ): __SCREAMING_SNAKE_CASE : str = len(lowercase__ ) __SCREAMING_SNAKE_CASE : Optional[int] = len(lowercase__ ) __SCREAMING_SNAKE_CASE : List[str] = [[False for _ in range(m + 1 )] for _ in ...
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"""simple docstring""" import argparse from argparse import Namespace import torch from torch import nn from transformers import XGLMConfig, XGLMForCausalLM def _UpperCamelCase ( UpperCamelCase ) -> Tuple: """simple docstring""" __UpperCAmelCase : int ...
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from scipy.stats import pearsonr import datasets __lowerCAmelCase : str ='\nPearson correlation coefficient and p-value for testing non-correlation.\nThe Pearson correlation coefficient measures the linear relationship between two datasets. The calculation of the p-value relies on the assumptio...
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'''simple docstring''' from PIL import Image def lowerCAmelCase_ ( snake_case_ : Image ) -> Image: '''simple docstring''' UpperCAmelCase_ , UpperCAmelCase_ = image.size UpperCAmelCase_ = 0 UpperCAmelCase_ = image.l...
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import json from typing import List, Optional, Tuple from tokenizers import normalizers from ...tokenization_utils_fast import PreTrainedTokenizerFast from ...utils import logging from .tokenization_mobilebert import MobileBertTokenizer __lowerCAmelCase : List[str] =logging.get_logger(__name__...
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import timeit import numpy as np import datasets from datasets.arrow_writer import ArrowWriter from datasets.features.features import _ArrayXD def _lowerCamelCase ( __lowerCamelCase ) -> List[Any]: '''simple docstring''' def wrapper(*__lowerCamelCase , ...
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import os def _UpperCamelCase ( lowercase__ ): __SCREAMING_SNAKE_CASE : Optional[Any] = len(grid[0] ) __SCREAMING_SNAKE_CASE : str = len(lowercase__ ) __SCREAMING_SNAKE_CASE : Optional[int] = 0 __SCREAMING_SNAKE_CASE : Any = ...
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import json import os from collections import Counter import torch import torchvision import torchvision.transforms as transforms from PIL import Image from torch import nn from torch.utils.data import Dataset __UpperCamelCase : Optional[Any] = {1: (1, 1), 2: (2, 1), 3: (3, 1), 4: (2, 2), 5: (5, 1...
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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 import ConfigTester from ...te...
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import numpy as np import torch from torch.utils.data import Dataset from utils import logger class a (_lowerCAmelCase ): """simple docstring""" def __init__( self : int , lowerCamelCase : List[Any] , lowerCamelCase : str ) -> ...
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import os from datetime import datetime as dt from github import Github __lowerCAmelCase : List[Any] =[ 'good first issue', 'good second issue', 'good difficult issue', 'enhancement', 'new pipeline/model', 'new scheduler', 'wip', ] def _UpperCamelCase ( ): ...
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"""simple docstring""" from typing import TYPE_CHECKING from ....utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available lowerCamelCase = { """configuration_trajectory_transformer""": [ """TRAJECTORY_TRANSFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP""", ...
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from ...configuration_utils import PretrainedConfig from ...utils import logging __lowerCAmelCase : Dict =logging.get_logger(__name__) __lowerCAmelCase : Dict ={ 'google/canine-s': 'https://huggingface.co/google/canine-s/resolve/main/config.json', # See all CANINE mod...
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"""simple docstring""" from typing import TYPE_CHECKING from ...utils import ( OptionalDependencyNotAvailable, _LazyModule, is_flax_available, is_sentencepiece_available, is_tf_available, is_tokenizers_available, is_torch_available, ) lowerCAmelCase__ = {'''co...
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from ...configuration_utils import PretrainedConfig from ...utils import logging __lowerCAmelCase : List[Any] =logging.get_logger(__name__) __lowerCAmelCase : Tuple ={ 'transfo-xl-wt103': 'https://huggingface.co/transfo-xl-wt103/resolve/main/config.json', } class _lowe...
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import argparse from collections import OrderedDict from pathlib import Path import torch from huggingface_hub import hf_hub_download from PIL import Image from torchvision.transforms import functional as F from transformers import DetrImageProcessor, TableTransformerConfig, TableTransformerForObjectDetection from t...
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from ...configuration_utils import PretrainedConfig from ...utils import logging __lowerCAmelCase : str =logging.get_logger(__name__) __lowerCAmelCase : Any ={ # See all MEGATRON_BERT models at https://huggingface.co/models?filter=bert } class _lowercase ( A__ ):...
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import functools from typing import Any def _a ( lowercase__ : str , lowercase__ : list[str] ): '''simple docstring''' if not isinstance(lowercase__ , lowercase__ ) or len(lowercase__ ) == 0: raise ValueError('the string should be not empty string' ) ...
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import os import sys import unittest __lowerCAmelCase : List[Any] =os.path.abspath(os.path.dirname(os.path.dirname(os.path.dirname(__file__)))) sys.path.append(os.path.join(git_repo_path, 'utils')) import check_dummies # noqa: E402 from check_dummies import create_dummy_files, create_dummy_obj...
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import argparse import io import requests import torch from omegaconf import OmegaConf from diffusers import AutoencoderKL from diffusers.pipelines.stable_diffusion.convert_from_ckpt import ( assign_to_checkpoint, conv_attn_to_linear, create_vae_diffusers_config, renew_vae_attention_pa...
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import math from numpy import inf from scipy.integrate import quad def _UpperCamelCase ( lowercase__ ): if num <= 0: raise ValueError('''math domain error''' ) return quad(lowercase__ , 0 , lowercase__ , args=(lowercase__) )[0] def _UpperCamelCase ( l...
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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_MAPPING, FEATURE...
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def _UpperCamelCase ( lowercase__ , lowercase__ , lowercase__ ): if principal <= 0: raise Exception('''Principal borrowed must be > 0''' ) if rate_per_annum < 0: raise Exception('''Rate of interest must be >= 0''' ) if years_to_repay <= 0 or not isinsta...
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"""simple docstring""" import os from dataclasses import dataclass, field from io import BytesIO from typing import TYPE_CHECKING, Any, ClassVar, Dict, Optional, Union import numpy as np import pyarrow as pa from .. import config from ..download.streaming_download_manager import xopen, xsplitext from...
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from maths.is_square_free import is_square_free from maths.prime_factors import prime_factors def _UpperCamelCase ( lowercase__ ): __SCREAMING_SNAKE_CASE : Tuple = prime_factors(lowercase__ ) if is_square_free(lowercase__ ): return -1 if len(lowercase__ ) % 2 else 1 ...
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import gc import random import unittest import numpy as np import torch from transformers import CLIPImageProcessor, CLIPVisionConfig, CLIPVisionModel from diffusers import HeunDiscreteScheduler, PriorTransformer, ShapEImgaImgPipeline from diffusers.pipelines.shap_e import ShapERenderer from diffusers.utils import...
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import json import os import shutil import sys import tempfile import unittest import unittest.mock as mock from pathlib import Path from huggingface_hub import HfFolder, delete_repo from requests.exceptions import HTTPError from transformers import AutoConfig, BertConfig, GPTaConfig from transformers.configuratio...
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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/...
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from typing import TYPE_CHECKING from ...utils import ( OptionalDependencyNotAvailable, _LazyModule, is_sentencepiece_available, is_tokenizers_available, is_torch_available, ) __lowerCAmelCase : Any ={ 'configuration_llama': ['LLAMA_PRETRAINED_CONFIG_ARCHIVE_MAP', 'Llama...
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"""simple docstring""" def _snake_case ( snake_case__ : list ): if not grid or not grid[0]: raise TypeError('The grid does not contain the appropriate information' ) for cell_n in range(1 , len(grid[0] ) ): grid[0][cell_n] += grid[0][cell_n - 1] A = grid[0] for row_n in range(1 ...
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from ...configuration_utils import PretrainedConfig from ...utils import logging __lowerCAmelCase : Dict =logging.get_logger(__name__) __lowerCAmelCase : List[Any] ={ 'google/switch-base-8': 'https://huggingface.co/google/switch-base-8/blob/main/config.json', } class _...
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'''simple docstring''' def _lowerCAmelCase ( __magic_name__ : Optional[int] ) -> Union[str, Any]: return [ { 0: [1, 2], 1: [0, 2], 2: [0, 1, 3, 5], 3: [2, 4], 4: [3], 5: [2, 6, 8], ...
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from dataclasses import dataclass from typing import List, Optional, Union import numpy as np import torch from ...utils import BaseOutput, OptionalDependencyNotAvailable, is_torch_available, is_transformers_available @dataclass class _lowercase ( A__ ): '''simple docstring''' SCREAMING_S...
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"""simple docstring""" from typing import Any, Dict, List, Optional, Tuple, Union import torch from torch import nn from torch.utils.data import DistributedSampler, RandomSampler from transformers import PreTrainedModel, Trainer, logging from transformers.integrations import is_fairscale_available from tra...
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from datetime import datetime import requests def _UpperCamelCase ( lowercase__ ): __SCREAMING_SNAKE_CASE : Optional[int] = '''https://downloadgram.net/wp-json/wppress/video-downloader/video?url=''' __SCREAMING_SNAKE_CASE : Tuple = requests.get(base_url + url ).js...
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'''simple docstring''' import unittest import numpy as np from transformers import RobertaPreLayerNormConfig, is_flax_available from transformers.testing_utils import require_flax, slow from ...test_modeling_flax_common import FlaxModelTesterMixin, floats_tensor, ids_tensor, random_attention_mask if is_f...
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import gc import random import unittest import numpy as np import torch from PIL import Image from transformers import CLIPTextConfig, CLIPTextModel, CLIPTokenizer from diffusers import ( AutoencoderKL, DDIMScheduler, EulerAncestralDiscreteScheduler, LMSDiscreteScheduler, PNDMScheduler, Sta...
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"""simple docstring""" import ast import os import re import shutil import tempfile import unittest from unittest import mock import torch from accelerate.test_utils.examples import compare_against_test from accelerate.test_utils.testing import TempDirTestCase, require_trackers, run_command, slow from accelera...
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# DISCLAIMER: This code is strongly influenced by https://github.com/pesser/pytorch_diffusion # and https://github.com/hojonathanho/diffusion import math from dataclasses import dataclass from typing import List, Optional, Tuple, Union import numpy as np import torch from diffusers.configuration_utils import Confi...
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"""simple docstring""" from __future__ import annotations import requests __lowerCamelCase = set( 'approved_at_utc approved_by author_flair_background_color\nauthor_flair_css_class author_flair_richtext author_flair_template_id author_fullname\nauthor_premium can_mod_post cate...
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from dataclasses import dataclass, field from typing import ClassVar, Dict from ..features import Features, Value from .base import TaskTemplate @dataclass(frozen=A__ ) class _lowercase ( A__ ): '''simple docstring''' SCREAMING_SNAKE_CASE__ : str = field(default=''...
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from __future__ import annotations import collections import pprint from pathlib import Path def a ( snake_case__: str ): '''simple docstring''' return "".join(sorted(snake_case__ ) ) def a ( snake_case__: str ): '''simple docstring''' ...
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def _UpperCamelCase ( lowercase__ = 10**9 ): __SCREAMING_SNAKE_CASE : List[str] = 1 __SCREAMING_SNAKE_CASE : int = 2 __SCREAMING_SNAKE_CASE : Union[str, Any] = 0 __SCREAMING_SNAKE_CASE : Dict = 0 __SCREAMING_SNAKE_CA...
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'''simple docstring''' import json import os import tempfile import transformers import datasets from utils import generate_example_dataset, get_duration lowercase__ : Optional[int] = 50_00_00 lowercase__ , lowercase__ : List[str] = os.path.split(__file__) lowercase__ : str...
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def _UpperCamelCase ( lowercase__ , lowercase__ ): __SCREAMING_SNAKE_CASE : str = len(lowercase__ ) __SCREAMING_SNAKE_CASE : Optional[int] = len(lowercase__ ) __SCREAMING_SNAKE_CASE : List[str] = [[False for _ in range(m + 1 )] for _ in ...
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from collections.abc import Generator def a (): __a , __a = 0, 1 while True: __a , __a = b, a + b yield b def a (lowerCAmelCase__ = 1_000 ): __a = 1 __a = fibonacci_generator() while len(str(next(lowerCAmelCase__ ) ) ) < n...
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from scipy.stats import pearsonr import datasets __lowerCAmelCase : str ='\nPearson correlation coefficient and p-value for testing non-correlation.\nThe Pearson correlation coefficient measures the linear relationship between two datasets. The calculation of the p-value relies on the assumptio...
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import unittest from transformers import AutoTokenizer, FalconConfig, is_torch_available from transformers.testing_utils import require_torch, slow, torch_device from ...generation.test_utils import GenerationTesterMixin from ...test_configuration_common import ConfigTester from ...test_modeling_common import M...
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import json from typing import List, Optional, Tuple from tokenizers import normalizers from ...tokenization_utils_fast import PreTrainedTokenizerFast from ...utils import logging from .tokenization_mobilebert import MobileBertTokenizer __lowerCAmelCase : List[str] =logging.get_logger(__name__...
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import math from collections import defaultdict from typing import List, Optional, Tuple, Union import numpy as np import torch from ..configuration_utils import ConfigMixin, register_to_config from .scheduling_utils import KarrasDiffusionSchedulers, SchedulerMixin, SchedulerOutput def ...
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import os def _UpperCamelCase ( lowercase__ ): __SCREAMING_SNAKE_CASE : Optional[Any] = len(grid[0] ) __SCREAMING_SNAKE_CASE : str = len(lowercase__ ) __SCREAMING_SNAKE_CASE : Optional[int] = 0 __SCREAMING_SNAKE_CASE : Any = ...
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"""simple docstring""" from .integrations import ( is_optuna_available, is_ray_available, is_sigopt_available, is_wandb_available, run_hp_search_optuna, run_hp_search_ray, run_hp_search_sigopt, run_hp_search_wandb, ) from .trainer_utils import ( HPSearchBa...
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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 import ConfigTester from ...te...
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"""simple docstring""" import sys snake_case = ( '''73167176531330624919225119674426574742355349194934''' '''96983520312774506326239578318016984801869478851843''' '''85861560789112949495459501737958331952853208805511''' '''1254069874715852386305071569329096329522744...
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import os from datetime import datetime as dt from github import Github __lowerCAmelCase : List[Any] =[ 'good first issue', 'good second issue', 'good difficult issue', 'enhancement', 'new pipeline/model', 'new scheduler', 'wip', ] def _UpperCamelCase ( ): ...
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"""simple docstring""" import argparse import torch from safetensors.torch import load_file from diffusers import StableDiffusionPipeline def _lowerCamelCase ( UpperCAmelCase_ : Union[str, Any], UpperCAmelCase_ : List[str], UpperCAmelCase_ : Optional[int...
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from ...configuration_utils import PretrainedConfig from ...utils import logging __lowerCAmelCase : Dict =logging.get_logger(__name__) __lowerCAmelCase : Dict ={ 'google/canine-s': 'https://huggingface.co/google/canine-s/resolve/main/config.json', # See all CANINE mod...
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import argparse import requests import torch # pip3 install salesforce-lavis # I'm actually installing a slightly modified version: pip3 install git+https://github.com/nielsrogge/LAVIS.git@fix_lavis_float32 (there's also the fix_lavis branch) # also note: to convert Vicuna checkpoints, we had to include /home/ni...
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from ...configuration_utils import PretrainedConfig from ...utils import logging __lowerCAmelCase : List[Any] =logging.get_logger(__name__) __lowerCAmelCase : Tuple ={ 'transfo-xl-wt103': 'https://huggingface.co/transfo-xl-wt103/resolve/main/config.json', } class _lowe...
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import math import tensorflow as tf from packaging import version def lowerCamelCase_ ( lowerCAmelCase__ : Optional[int] ) -> Any: '''simple docstring''' A = tf.convert_to_tensor(lowerCAmelCase__ ) A = 0.5 * (1.0 + tf.math.erf(x ...
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from ...configuration_utils import PretrainedConfig from ...utils import logging __lowerCAmelCase : str =logging.get_logger(__name__) __lowerCAmelCase : Any ={ # See all MEGATRON_BERT models at https://huggingface.co/models?filter=bert } class _lowercase ( A__ ):...
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'''simple docstring''' from itertools import product from cva import COLOR_BGR2GRAY, cvtColor, imread, imshow, waitKey from numpy import dot, exp, mgrid, pi, ravel, square, uinta, zeros def _SCREAMING_SNAKE_CASE ( __snake_case : Union[str, Any] , __snake_case : List[Any] ): ...
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import os import sys import unittest __lowerCAmelCase : List[Any] =os.path.abspath(os.path.dirname(os.path.dirname(os.path.dirname(__file__)))) sys.path.append(os.path.join(git_repo_path, 'utils')) import check_dummies # noqa: E402 from check_dummies import create_dummy_files, create_dummy_obj...
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import os try: from .build_directory_md import good_file_paths except ImportError: from build_directory_md import good_file_paths # type: ignore __a: str = list(good_file_paths()) assert filepaths, "good_file_paths() failed!" __a: List[Any] = [file for file in filepaths if f...
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import math from numpy import inf from scipy.integrate import quad def _UpperCamelCase ( lowercase__ ): if num <= 0: raise ValueError('''math domain error''' ) return quad(lowercase__ , 0 , lowercase__ , args=(lowercase__) )[0] def _UpperCamelCase ( l...
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'''simple docstring''' import math from collections import defaultdict from typing import List, Optional, Tuple, Union import numpy as np import torch from ..configuration_utils import ConfigMixin, register_to_config from .scheduling_utils import KarrasDiffusionSchedulers, SchedulerMixin, SchedulerOutput def ...
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def _UpperCamelCase ( lowercase__ , lowercase__ , lowercase__ ): if principal <= 0: raise Exception('''Principal borrowed must be > 0''' ) if rate_per_annum < 0: raise Exception('''Rate of interest must be >= 0''' ) if years_to_repay <= 0 or not isinsta...
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"""simple docstring""" import logging import torch from accelerate import Accelerator from arguments import EvaluationArguments from datasets import load_dataset from torch.utils.data import IterableDataset from torch.utils.data.dataloader import DataLoader from transformers import AutoModelForCausalLM, AutoT...
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from maths.is_square_free import is_square_free from maths.prime_factors import prime_factors def _UpperCamelCase ( lowercase__ ): __SCREAMING_SNAKE_CASE : Tuple = prime_factors(lowercase__ ) if is_square_free(lowercase__ ): return -1 if len(lowercase__ ) % 2 else 1 ...
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'''simple docstring''' from typing import Optional, Tuple import jax import jax.numpy as jnp from flax import linen as nn from flax.core.frozen_dict import FrozenDict from transformers import CLIPConfig, FlaxPreTrainedModel from transformers.models.clip.modeling_flax_clip import FlaxCLIPVisionModule def ...
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import json import os import shutil import sys import tempfile import unittest import unittest.mock as mock from pathlib import Path from huggingface_hub import HfFolder, delete_repo from requests.exceptions import HTTPError from transformers import AutoConfig, BertConfig, GPTaConfig from transformers.configuratio...
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"""simple docstring""" import warnings from contextlib import contextmanager from ...processing_utils import ProcessorMixin class SCREAMING_SNAKE_CASE__ ( A__ ): __lowerCAmelCase : str = '''Speech2TextFeatureExtractor''' __lowerCAmelCase : Tuple = '''Speech2TextTokenizer''' def _...
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from typing import TYPE_CHECKING from ...utils import ( OptionalDependencyNotAvailable, _LazyModule, is_sentencepiece_available, is_tokenizers_available, is_torch_available, ) __lowerCAmelCase : Any ={ 'configuration_llama': ['LLAMA_PRETRAINED_CONFIG_ARCHIVE_MAP', 'Llama...
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import argparse import os import pickle import sys import torch from transformers import TransfoXLConfig, TransfoXLLMHeadModel, load_tf_weights_in_transfo_xl from transformers.models.transfo_xl import tokenization_transfo_xl as data_utils from transformers.models.transfo_xl.tokenization_transfo...
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from ...configuration_utils import PretrainedConfig from ...utils import logging __lowerCAmelCase : Dict =logging.get_logger(__name__) __lowerCAmelCase : List[Any] ={ 'google/switch-base-8': 'https://huggingface.co/google/switch-base-8/blob/main/config.json', } class _...
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import gc import random import unittest import numpy as np import torch from PIL import Image from diffusers import ( DDIMScheduler, KandinskyVaaControlnetImgaImgPipeline, KandinskyVaaPriorEmbaEmbPipeline, UNetaDConditionModel, VQModel, ) from diffusers.utils import floats_tensor, load_image...
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from dataclasses import dataclass from typing import List, Optional, Union import numpy as np import torch from ...utils import BaseOutput, OptionalDependencyNotAvailable, is_torch_available, is_transformers_available @dataclass class _lowercase ( A__ ): '''simple docstring''' SCREAMING_S...
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'''simple docstring''' import os import unittest from tempfile import TemporaryDirectory import torch import torch.nn as nn from accelerate.utils import ( OffloadedWeightsLoader, extract_submodules_state_dict, load_offloaded_weight, offload_state_dict, offload_weight, ) class A__ ...
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from datetime import datetime import requests def _UpperCamelCase ( lowercase__ ): __SCREAMING_SNAKE_CASE : Optional[int] = '''https://downloadgram.net/wp-json/wppress/video-downloader/video?url=''' __SCREAMING_SNAKE_CASE : Tuple = requests.get(base_url + url ).js...
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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 import ConfigTester from ...tes...
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import gc import random import unittest import numpy as np import torch from PIL import Image from transformers import CLIPTextConfig, CLIPTextModel, CLIPTokenizer from diffusers import ( AutoencoderKL, DDIMScheduler, EulerAncestralDiscreteScheduler, LMSDiscreteScheduler, PNDMScheduler, Sta...
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import json import multiprocessing import os import re from collections import defaultdict import torch from accelerate import Accelerator from accelerate.utils import set_seed from arguments import HumanEvalArguments from datasets import load_dataset, load_metric from torch.utils.data import It...
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# DISCLAIMER: This code is strongly influenced by https://github.com/pesser/pytorch_diffusion # and https://github.com/hojonathanho/diffusion import math from dataclasses import dataclass from typing import List, Optional, Tuple, Union import numpy as np import torch from diffusers.configuration_utils import Confi...
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"""simple docstring""" import unittest from diffusers.models.unet_ad_blocks import * # noqa F403 from diffusers.utils import torch_device from .test_unet_blocks_common import UNetBlockTesterMixin class _UpperCAmelCase ( A__ , unittest.TestCase ): SCREAMING_SNA...
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from dataclasses import dataclass, field from typing import ClassVar, Dict from ..features import Features, Value from .base import TaskTemplate @dataclass(frozen=A__ ) class _lowercase ( A__ ): '''simple docstring''' SCREAMING_SNAKE_CASE__ : str = field(default=''...
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"""simple docstring""" import re import warnings from contextlib import contextmanager from ...processing_utils import ProcessorMixin class _UpperCAmelCase ( A__ ): a__ : List[str] = ['''image_processor''', '''tokenizer'''] a__ : Any = '''AutoImageProcessor'''...
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def _UpperCamelCase ( lowercase__ = 10**9 ): __SCREAMING_SNAKE_CASE : List[str] = 1 __SCREAMING_SNAKE_CASE : int = 2 __SCREAMING_SNAKE_CASE : Union[str, Any] = 0 __SCREAMING_SNAKE_CASE : Dict = 0 __SCREAMING_SNAKE_CA...
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from typing import TYPE_CHECKING from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available UpperCamelCase_ = { 'configuration_time_series_transformer': [ 'TIME_SERIES_TRANSFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP', 'TimeSeriesTransformerConfig', ], ...
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def _UpperCamelCase ( lowercase__ , lowercase__ ): __SCREAMING_SNAKE_CASE : str = len(lowercase__ ) __SCREAMING_SNAKE_CASE : Optional[int] = len(lowercase__ ) __SCREAMING_SNAKE_CASE : List[str] = [[False for _ in range(m + 1 )] for _ in ...
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"""simple docstring""" from binascii import hexlify from hashlib import shaaaa from os import urandom # RFC 3526 - More Modular Exponential (MODP) Diffie-Hellman groups for # Internet Key Exchange (IKE) https://tools.ietf.org/html/rfc3526 __lowerCamelCase = { # 1536-bit 5: { 'prime': ...
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from scipy.stats import pearsonr import datasets __lowerCAmelCase : str ='\nPearson correlation coefficient and p-value for testing non-correlation.\nThe Pearson correlation coefficient measures the linear relationship between two datasets. The calculation of the p-value relies on the assumptio...
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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 __a = get_tests_dir('fixtures/test_sente...
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import json from typing import List, Optional, Tuple from tokenizers import normalizers from ...tokenization_utils_fast import PreTrainedTokenizerFast from ...utils import logging from .tokenization_mobilebert import MobileBertTokenizer __lowerCAmelCase : List[str] =logging.get_logger(__name__...
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"""simple docstring""" import numpy as np from transformers import Pipeline def _snake_case ( UpperCamelCase : Union[str, Any] ): UpperCAmelCase : List[Any] = np.max(lowercase__ , axis=-1 , keepdims=lowercase__ ) UpperCAmelCase : List[str] = np.exp(...
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import os def _UpperCamelCase ( lowercase__ ): __SCREAMING_SNAKE_CASE : Optional[Any] = len(grid[0] ) __SCREAMING_SNAKE_CASE : str = len(lowercase__ ) __SCREAMING_SNAKE_CASE : Optional[int] = 0 __SCREAMING_SNAKE_CASE : Any = ...
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import copy from typing import Dict, Optional from ...configuration_utils import PretrainedConfig from ...utils import logging from ..auto import CONFIG_MAPPING from ..detr import DetrConfig from ..swin import SwinConfig SCREAMING_SNAKE_CASE__ : Optional[int] = { 'facebook/...
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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 import ConfigTester from ...te...
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def _SCREAMING_SNAKE_CASE ( SCREAMING_SNAKE_CASE :List[str] ) -> List[str]: return number & 1 == 0 if __name__ == "__main__": import doctest doctest.testmod()
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import os from datetime import datetime as dt from github import Github __lowerCAmelCase : List[Any] =[ 'good first issue', 'good second issue', 'good difficult issue', 'enhancement', 'new pipeline/model', 'new scheduler', 'wip', ] def _UpperCamelCase ( ): ...
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'''simple docstring''' from ...configuration_utils import PretrainedConfig from ...utils import logging lowerCamelCase : List[Any] = logging.get_logger(__name__) lowerCamelCase : Tuple = { 'transfo-xl-wt103': 'https://huggingface.co/transfo-xl-wt103/resolve/main/config.json', } cla...
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from ...configuration_utils import PretrainedConfig from ...utils import logging __lowerCAmelCase : Dict =logging.get_logger(__name__) __lowerCAmelCase : Dict ={ 'google/canine-s': 'https://huggingface.co/google/canine-s/resolve/main/config.json', # See all CANINE mod...
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import importlib import torch import yaml from omegaconf import OmegaConf from taming.models.vqgan import VQModel def a(lowercase__ , lowercase__=False ): '''simple docstring''' snake_case_ = OmegaConf.load(lowercase__ ) if display: print(yaml.dump(OmegaConf.to_container(lowerca...
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from ...configuration_utils import PretrainedConfig from ...utils import logging __lowerCAmelCase : List[Any] =logging.get_logger(__name__) __lowerCAmelCase : Tuple ={ 'transfo-xl-wt103': 'https://huggingface.co/transfo-xl-wt103/resolve/main/config.json', } class _lowe...
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def _lowerCAmelCase ( __magic_name__ :str , __magic_name__ :Union[str, Any] ): return price * (1 + tax_rate) if __name__ == "__main__": print(f"{price_plus_tax(100, 0.25) = }") print(f"{price_plus_tax(125.50, 0.05) = }")
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from ...configuration_utils import PretrainedConfig from ...utils import logging __lowerCAmelCase : str =logging.get_logger(__name__) __lowerCAmelCase : Any ={ # See all MEGATRON_BERT models at https://huggingface.co/models?filter=bert } class _lowercase ( A__ ):...
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"""simple docstring""" import gc import unittest from transformers import MODEL_FOR_MASKED_LM_MAPPING, TF_MODEL_FOR_MASKED_LM_MAPPING, FillMaskPipeline, pipeline from transformers.pipelines import PipelineException from transformers.testing_utils import ( is_pipeline_test, is_torch_...
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import os import sys import unittest __lowerCAmelCase : List[Any] =os.path.abspath(os.path.dirname(os.path.dirname(os.path.dirname(__file__)))) sys.path.append(os.path.join(git_repo_path, 'utils')) import check_dummies # noqa: E402 from check_dummies import create_dummy_files, create_dummy_obj...
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"""simple docstring""" from typing import TYPE_CHECKING from ...file_utils import _LazyModule, is_tokenizers_available, is_torch_available, is_vision_available from ...utils import OptionalDependencyNotAvailable _lowercase : Any = {'configuration_dpt': ['DPT_PRETRAINED_CONFIG_ARC...
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import math from numpy import inf from scipy.integrate import quad def _UpperCamelCase ( lowercase__ ): if num <= 0: raise ValueError('''math domain error''' ) return quad(lowercase__ , 0 , lowercase__ , args=(lowercase__) )[0] def _UpperCamelCase ( l...
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from __future__ import annotations def _lowerCamelCase ( lowerCamelCase_: Union[str, Any] ): '''simple docstring''' A : Dict = 0.0_0 A : Union[str, Any] = 0 for resistor in resistors: if resistor <= 0: A : List[A...
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def _UpperCamelCase ( lowercase__ , lowercase__ , lowercase__ ): if principal <= 0: raise Exception('''Principal borrowed must be > 0''' ) if rate_per_annum < 0: raise Exception('''Rate of interest must be >= 0''' ) if years_to_repay <= 0 or not isinsta...
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"""simple docstring""" import time import unittest from transformers import is_torch_available from transformers.testing_utils import require_torch, torch_device from ..test_modeling_common import ids_tensor if is_torch_available(): import torch from transformers.generation import ( MaxLengthCriteri...
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from maths.is_square_free import is_square_free from maths.prime_factors import prime_factors def _UpperCamelCase ( lowercase__ ): __SCREAMING_SNAKE_CASE : Tuple = prime_factors(lowercase__ ) if is_square_free(lowercase__ ): return -1 if len(lowercase__ ) % 2 else 1 ...
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'''simple docstring''' from __future__ import annotations from collections.abc import Sequence from typing import Literal def __UpperCAmelCase ( a_: Tuple, a_: Any ): _UpperCAmelCase : Optional[int] = list(lowercase__ ) _UpperCAmelCase : Optional[int] = li...
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import json import os import shutil import sys import tempfile import unittest import unittest.mock as mock from pathlib import Path from huggingface_hub import HfFolder, delete_repo from requests.exceptions import HTTPError from transformers import AutoConfig, BertConfig, GPTaConfig from transformers.configuratio...
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"""simple docstring""" from dataclasses import dataclass from typing import List, Optional, Union import numpy as np import torch from ...utils import BaseOutput, OptionalDependencyNotAvailable, is_torch_available, is_transformers_available @dataclass class SCREAMING_SNAKE_CASE__ ( A__ ): __lowerC...
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from typing import TYPE_CHECKING from ...utils import ( OptionalDependencyNotAvailable, _LazyModule, is_sentencepiece_available, is_tokenizers_available, is_torch_available, ) __lowerCAmelCase : Any ={ 'configuration_llama': ['LLAMA_PRETRAINED_CONFIG_ARCHIVE_MAP', 'Llama...
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def _lowerCamelCase ( __lowerCamelCase ) -> Optional[Any]: '''simple docstring''' if not isinstance(lowercase__ , lowercase__ ): raise TypeError("""only integers accepted as input""" ) else: UpperCAmelCase__ : int ...
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from ...configuration_utils import PretrainedConfig from ...utils import logging __lowerCAmelCase : Dict =logging.get_logger(__name__) __lowerCAmelCase : List[Any] ={ 'google/switch-base-8': 'https://huggingface.co/google/switch-base-8/blob/main/config.json', } class _...
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import numpy # List of input, output pairs _UpperCAmelCase = ( ((5, 2, 3), 15), ((6, 5, 9), 25), ((11, 12, 13), 41), ((1, 1, 1), 8), ((11, 12, 13), 41), ) _UpperCAmelCase = (((515, 22, 13), 555), ((61, 35, 49), 150)) _UpperCAmelCase = [2, 4, 1, 5] _UpperCAmelCase ...
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from dataclasses import dataclass from typing import List, Optional, Union import numpy as np import torch from ...utils import BaseOutput, OptionalDependencyNotAvailable, is_torch_available, is_transformers_available @dataclass class _lowercase ( A__ ): '''simple docstring''' SCREAMING_S...
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'''simple docstring''' import unittest from pathlib import Path from tempfile import TemporaryDirectory from transformers import AutoConfig, TFGPTaLMHeadModel, is_keras_nlp_available, is_tf_available from transformers.models.gpta.tokenization_gpta import GPTaTokenizer from transformers.testing_utils import require_k...
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from datetime import datetime import requests def _UpperCamelCase ( lowercase__ ): __SCREAMING_SNAKE_CASE : Optional[int] = '''https://downloadgram.net/wp-json/wppress/video-downloader/video?url=''' __SCREAMING_SNAKE_CASE : Tuple = requests.get(base_url + url ).js...
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import itertools import os import random import tempfile import unittest import numpy as np from datasets import load_dataset from transformers import is_speech_available from transformers.testing_utils import check_json_file_has_correct_format, require_torch, require_torchaudio from transformers.utils.import_utils...
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import gc import random import unittest import numpy as np import torch from PIL import Image from transformers import CLIPTextConfig, CLIPTextModel, CLIPTokenizer from diffusers import ( AutoencoderKL, DDIMScheduler, EulerAncestralDiscreteScheduler, LMSDiscreteScheduler, PNDMScheduler, Sta...
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import warnings from diffusers import StableDiffusionImgaImgPipeline # noqa F401 warnings.warn( 'The `image_to_image.py` script is outdated. Please use directly `from diffusers import' ' StableDiffusionImg2ImgPipeline` instead.' )
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# DISCLAIMER: This code is strongly influenced by https://github.com/pesser/pytorch_diffusion # and https://github.com/hojonathanho/diffusion import math from dataclasses import dataclass from typing import List, Optional, Tuple, Union import numpy as np import torch from diffusers.configuration_utils import Confi...
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