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"""simple docstring""" from collections import OrderedDict from typing import Any, Mapping, Optional from ... import PreTrainedTokenizer from ...configuration_utils import PretrainedConfig from ...file_utils import TensorType, is_torch_available from ...onnx import OnnxConfig, OnnxConfigWithPast...
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'''simple docstring''' import io import json import fsspec import pytest from datasets import Dataset, DatasetDict, Features, NamedSplit, Value from datasets.io.json import JsonDatasetReader, JsonDatasetWriter from ..utils import assert_arrow_memory_doesnt_increase, assert_arrow_memory_increases def ...
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from datasets.utils.patching import _PatchedModuleObj, patch_submodule from . import _test_patching def UpperCAmelCase ( ): """simple docstring""" import os as original_os from os import path as original_path from os import rename as original_rename from os.path import di...
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'''simple docstring''' from itertools import zip_longest import requests from bsa import BeautifulSoup from pandas import DataFrame def lowerCamelCase__ ( _A = "laptop" ): a : Any = f"""https://www.amazon.in/laptop/s?k={product}""" a : Tuple = {...
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"""simple docstring""" from math import sqrt import numpy as np from sympy import symbols # Coefficient # Speed of light (m/s) __A : Optional[int] = 299_792_458 # Symbols __A : str = symbols('''ct x y z''') def lowercase ( __snake_case : ...
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'''simple docstring''' import gc import random import unittest import numpy as np import torch from transformers import ( CLIPImageProcessor, CLIPTextConfig, CLIPTextModel, CLIPTokenizer, CLIPVisionConfig, CLIPVisionModelWithProjection, ) from diffusers import AutoencoderKL, DDIMSche...
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'''simple docstring''' import copy import tempfile import unittest from transformers import MaMaaaConfig, is_torch_available from transformers.testing_utils import require_sentencepiece, require_tokenizers, require_torch, slow, torch_device from transformers.utils import cached_property from ...g...
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'''simple docstring''' from typing import Mapping from ...configuration_utils import PretrainedConfig from ...onnx import OnnxSeqaSeqConfigWithPast from ...utils import logging lowerCAmelCase: Union[str, Any] = logging.get_logger(__name__) lowerCAmelCase: List[str] = ...
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from math import pi def lowercase_ ( _A : Any , _A : List[str] ): """simple docstring""" return 2 * pi * radius * (angle / 360) if __name__ == "__main__": print(arc_length(90, 10))
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'''simple docstring''' from __future__ import annotations from math import pi, sqrt def lowerCamelCase__ ( _A , _A ): if inductance <= 0: raise ValueError('Inductance cannot be 0 or negative' ) elif capacitance <= 0: raise ValueError('Capacitance cannot be 0 or negative...
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import warnings from ...utils import logging from .image_processing_beit import BeitImageProcessor lowerCamelCase__ : Optional[Any] = logging.get_logger(__name__) class lowerCamelCase_ ( lowerCamelCase__ ): '''simple docstring''' def __init__( self : Any...
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'''simple docstring''' import collections import os from typing import List, Optional, Tuple from transformers.utils import is_jieba_available, requires_backends if is_jieba_available(): import jieba from ...tokenization_utils import PreTrainedTokenizer from ...utils import logging lowerCAmelCase: ...
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from math import acos, sin from typing import List, Tuple, Union import numpy as np import torch from PIL import Image from ...models import AutoencoderKL, UNetaDConditionModel from ...schedulers import DDIMScheduler, DDPMScheduler from ...utils import randn_tensor from ..pipeline_utils import AudioPipelineOutput, B...
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'''simple docstring''' from __future__ import annotations import unittest from transformers import is_tf_available, is_torch_available from transformers.testing_utils import DUMMY_UNKNOWN_IDENTIFIER, SMALL_MODEL_IDENTIFIER, is_pt_tf_cross_test, slow if is_tf_available(): from transformers import ( ...
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"""simple docstring""" import unittest from transformers import JukeboxTokenizer from transformers.testing_utils import require_torch class _lowerCamelCase ( unittest.TestCase ): UpperCAmelCase_ = JukeboxTokenizer UpperCAmelCase_ = { "artist": "Zac Bro...
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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 lowerCAmelCase: List[Any] = logging.get_logger(__name__) lowerCAmelCase: List[Any] ...
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'''simple docstring''' def a_ ( lowerCamelCase : Optional[Any] ): return 10 - x * x def a_ ( lowerCamelCase : List[str] , lowerCamelCase : Any ): # Bolzano theory in order to find if there is a root between a and b if equation(_A ) * equation(_A ) ...
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'''simple docstring''' def lowerCamelCase__ ( _A ): return 10 - x * x def lowerCamelCase__ ( _A , _A ): # Bolzano theory in order to find if there is a root between a and b if equation(_A ) * equation(_A ) >= 0: raise ValueError('Wrong space!' ) ...
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from typing import Dict, List, Optional, Union import numpy as np from ...image_processing_utils import BaseImageProcessor, BatchFeature, get_size_dict from ...image_transforms import rescale, resize, to_channel_dimension_format from ...image_utils import ( ChannelDimension, ImageInput, PILIm...
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'''simple docstring''' import unittest from transformers import EsmConfig, is_torch_available from transformers.testing_utils import TestCasePlus, require_torch, slow, torch_device from ...test_configuration_common import ConfigTester from ...test_modeling_common import ModelTesterMixin, ids_tensor, random_...
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import inspect import unittest from datasets import load_dataset from packaging import version from transformers import BeitConfig from transformers.models.auto import get_values from transformers.testing_utils import require_torch, require_torch_multi_gpu, require_vision, slow, torch_device from...
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'''simple docstring''' from typing import Optional from torch import nn from .transformer_ad import TransformeraDModel, TransformeraDModelOutput class a__( nn.Module ): def __init__( self : Any , __snake_case : int = 16 , __snake_case : int = 88 , __snake_...
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"""simple docstring""" import json import os import unittest from transformers.models.ctrl.tokenization_ctrl import VOCAB_FILES_NAMES, CTRLTokenizer from ...test_tokenization_common import TokenizerTesterMixin class a__ ( lowerCamelCase__, unittest.TestCase ): _lowerCa...
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'''simple docstring''' from typing import TYPE_CHECKING from ...utils import ( OptionalDependencyNotAvailable, _LazyModule, is_sentencepiece_available, is_torch_available, ) lowerCAmelCase: Union[str, Any] = { 'configuration_speecht5': [ 'SPEECHT5_PRETRAINED...
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from typing import TYPE_CHECKING from ...utils import ( OptionalDependencyNotAvailable, _LazyModule, is_tf_available, is_torch_available, is_vision_available, ) __a : Union[str, Any] = { 'configuration_blip': [ 'BLIP_PRETRAINED_CONFIG_ARCHIVE_MAP', 'BlipConfig', ...
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'''simple docstring''' # Copyright 2023 The HuggingFace Team. All rights reserved. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0...
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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 # # =================# __A : Tuple = [ # (stable-diffusion, HF Diffusers) ('time_embed...
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'''simple docstring''' import json from typing import Dict, List, Optional, Tuple, Union from tokenizers import pre_tokenizers, processors from ...tokenization_utils_base import AddedToken, BatchEncoding, EncodedInput from ...tokenization_utils_fast import PreTrainedTokenizerFast from ...utils import Paddin...
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'''simple docstring''' from typing import TYPE_CHECKING # rely on isort to merge the imports from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tokenizers_available, is_torch_available _lowerCamelCase : Tuple = {'configuration_mra': ['MRA_PRETRAINED_CONFIG_ARCHIVE_MAP...
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'''simple docstring''' import copy import os import cva import numpy as np from matplotlib import pyplot as plt class a__: def __init__( self : Tuple ): a : Optional[int] = '' a : Optional[Any] = '' a : str = ...
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from copy import deepcopy class _lowercase : """simple docstring""" def __init__( self : Union[str, Any] , __lowerCamelCase : list[int] | None = None , __lowerCamelCase : int | None = None ): '''simpl...
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'''simple docstring''' import baseaa import io import json import os from copy import deepcopy from ..optimizer import AcceleratedOptimizer from ..scheduler import AcceleratedScheduler class a__: def __init__( self : List[Any] , __snake_case : Union[str, Any] ): if isin...
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import argparse import pathlib import fairseq import torch from fairseq.models.roberta import RobertaModel as FairseqRobertaModel from fairseq.modules import TransformerSentenceEncoderLayer from packaging import version from transformers import XLMRobertaConfig, XLMRobertaXLForMaskedLM, XLMRobertaXLForSequenceCl...
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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 accel...
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from typing import TYPE_CHECKING from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available lowercase__ :str = { 'configuration_mgp_str': ['MGP_STR_PRETRAINED_CONFIG_ARCHIVE_MAP', 'MgpstrConfig'], 'processing_mgp_str': ['MgpstrProcessor'], 'tokenization_mgp_str': ['Mgpstr...
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'''simple docstring''' 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...
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"""simple docstring""" import argparse import collections import numpy as np import torch from flax import traverse_util from tax import checkpoints from transformers import MTaConfig, UMTaEncoderModel, UMTaForConditionalGeneration from transformers.utils import logging logging.set_verbosity_info() def...
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'''simple docstring''' import inspect from typing import Optional, Union import numpy as np import PIL import torch from torch.nn import functional as F from torchvision import transforms from transformers import CLIPFeatureExtractor, CLIPModel, CLIPTextModel, CLIPTokenizer from diffusers import ( Autoe...
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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....
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'''simple docstring''' # 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/l...
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'''simple docstring''' from typing import List import jiwer import jiwer.transforms as tr from packaging import version import datasets from datasets.config import PY_VERSION if PY_VERSION < version.parse('''3.8'''): import importlib_metadata else: import importlib.metada...
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'''simple docstring''' import json import os import unittest from transformers.models.blenderbot_small.tokenization_blenderbot_small import ( VOCAB_FILES_NAMES, BlenderbotSmallTokenizer, ) from ...test_tokenization_common import TokenizerTesterMixin class A ( SCREA...
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'''simple docstring''' import os import re from shutil import copyfile from typing import List, Optional, Tuple from ...tokenization_utils import PreTrainedTokenizer from ...utils import logging _lowerCAmelCase = logging.get_logger(__name__) _lowerCAmelCase = { ...
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'''simple docstring''' from typing import Optional, Tuple, Union import tensorflow as tf from ...activations_tf import ACTaFN from ...file_utils import add_code_sample_docstrings, add_start_docstrings, add_start_docstrings_to_model_forward from ...modeling_tf_outputs import ( TFBaseM...
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'''simple docstring''' import importlib.metadata import operator import re import sys from typing import Optional from packaging import version _lowerCAmelCase = { '''<''': operator.lt, '''<=''': operator.le, '''==''': operator.eq, '''!=''': operator.ne, ...
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'''simple docstring''' import torch from torch import nn from torch.nn import CrossEntropyLoss, MSELoss from transformers.file_utils import add_start_docstrings, add_start_docstrings_to_model_forward from transformers.models.bert.modeling_bert import ( BERT_INPUTS_DOCSTRING, BERT_...
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'''simple docstring''' def __lowerCAmelCase ( snake_case__ , snake_case__ , snake_case__ , snake_case__ ): global f # a global dp table for knapsack if f[i][j] < 0: if j < wt[i - 1]: __UpperCamelCase : int = mf_k...
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'''simple docstring''' import os from huggingface_hub.constants import HUGGINGFACE_HUB_CACHE, hf_cache_home _lowerCAmelCase = HUGGINGFACE_HUB_CACHE _lowerCAmelCase = '''config.json''' _lowerCAmelCase = '''diffusion_pytorch_model.bin''' _lowerCAmelCase ...
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'''simple docstring''' from __future__ import annotations import os import tempfile import unittest from transformers import ConvBertConfig, is_tf_available from transformers.testing_utils import require_tf, slow from ...test_configuration_common import ConfigTester from ...test_mode...
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'''simple docstring''' from __future__ import annotations import os import tempfile import unittest from transformers import ConvBertConfig, is_tf_available from transformers.testing_utils import require_tf, slow from ...test_configuration_common import ConfigTester from ...test_mode...
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'''simple docstring''' # tests directory-specific settings - this file is run automatically # by pytest before any tests are run import sys import warnings from os.path import abspath, dirname, join # allow having multiple repository checkouts and not needing to remember to rerun # 'p...
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'''simple docstring''' import argparse import json from dataclasses import dataclass, field from functools import partial from pathlib import Path from typing import List import timm import torch import torch.nn as nn from huggingface_hub import hf_hub_download from torch import Tenso...
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'''simple docstring''' from maths.prime_check import is_prime def __lowerCAmelCase ( snake_case__ ): if not isinstance(snake_case__ , snake_case__ ): __UpperCamelCase : Optional[int] = F"Input value of [number={number}] must be an intege...
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'''simple docstring''' import argparse import json import logging import os import shutil import sys import tempfile import unittest from unittest import mock import torch from accelerate.utils import write_basic_config from transformers.testing_utils import TestCasePlus, get_gpu_c...
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'''simple docstring''' def __lowerCAmelCase ( snake_case__ , snake_case__ ): __UpperCamelCase : list[list[str]] = [[] for _ in range(snake_case__ )] __UpperCamelCase : Optional[Any] = key - 1 if key <= 0: raise Va...
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'''simple docstring''' from maths.prime_check import is_prime def __lowerCAmelCase ( snake_case__ ): if not isinstance(snake_case__ , snake_case__ ): __UpperCamelCase : Optional[int] = F"Input value of [number={number}] must be an intege...
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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 YolosConfig, YolosForObjectDetection, YolosImageProcessor from transformers.utils import ...
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'''simple docstring''' def __lowerCAmelCase ( snake_case__ , snake_case__ , snake_case__ , snake_case__ , snake_case__ , ): __UpperCamelCase : Dict = [redshift, radiation_density, matter_density, dark_energy] if any(p...
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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 _lowerCAmelCase = logging.get_logger(__name__...
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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 _lowerCAmelCase = '''src/tr...
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'''simple docstring''' from datasets.utils.patching import _PatchedModuleObj, patch_submodule from . import _test_patching def __lowerCAmelCase ( ): import os as original_os from os import path as original_path from os import rename as original_rename from os.path ...
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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 A ( SCREAMI...
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'''simple docstring''' import functools def __lowerCAmelCase ( snake_case__ , snake_case__ ): # Validation if not isinstance(snake_case__ , snake_case__ ) or not all(isinstance(snake_case__ , snake_case__ ) for day in days ): ...
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'''simple docstring''' def __lowerCAmelCase ( snake_case__ ): return "".join([hex(snake_case__ )[2:].zfill(2 ).upper() for byte in list(snake_case__ )] ) def __lowerCAmelCase ( snake_case__ ): # Check data validity, following RFC3548 ...
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'''simple docstring''' import copy from dataclasses import dataclass, field from typing import ClassVar, Dict from ..features import Audio, Features, Value from .base import TaskTemplate @dataclass(frozen=SCREAMING_SNAKE_CASE__ ) class A ( SCREAMING_SNAKE_CASE__ ): ...
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'''simple docstring''' import argparse import json import logging import os import sys from unittest.mock import patch from transformers.testing_utils import TestCasePlus, get_gpu_count, slow _lowerCAmelCase = [ os.path.join(os.path.dirname(__file__), dirname) for...
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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....
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'''simple docstring''' import unittest from transformers import TrOCRConfig from transformers.testing_utils import is_torch_available, require_torch, torch_device from ...generation.test_utils import GenerationTesterMixin from ...test_configuration_common import ConfigTester from ...test...
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'''simple docstring''' import argparse import json from pathlib import Path import requests import torch from huggingface_hub import cached_download, hf_hub_download, hf_hub_url from PIL import Image from transformers import DetaConfig, DetaForObjectDetection, DetaImageProcessor, SwinC...
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'''simple docstring''' import argparse from pathlib import Path import fairseq import torch from fairseq.models.xmod import XMODModel as FairseqXmodModel from packaging import version from transformers import XmodConfig, XmodForMaskedLM, XmodForSequenceClassification from transformers....
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'''simple docstring''' class A : '''simple docstring''' def __init__(self , _UpperCAmelCase = "" , _UpperCAmelCase = False ) -> None: # Mapping from the first character of the prefix of the node __UpperCamelCase : dict[str, RadixN...
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'''simple docstring''' def __lowerCAmelCase ( snake_case__ ): return [ txt[:a] + txt[a].upper() + txt[a + 1 :] for a in range(len(snake_case__ ) ) if txt[a].isalpha() ] if __name__ == "__main__": __import__('''doctest''').testmod(...
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'''simple docstring''' from ...configuration_utils import PretrainedConfig from ...utils import logging _lowerCAmelCase = logging.get_logger(__name__) _lowerCAmelCase = { '''vinvino02/glpn-kitti''': '''https://huggingface.co/vinvino02/glpn-kitti/resolve/main/conf...
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'''simple docstring''' def __lowerCAmelCase ( snake_case__ , snake_case__ , snake_case__ ): def count_of_possible_combinations(snake_case__ ) -> int: if target < 0: return 0 if target == 0: return 1 return sum(co...
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'''simple docstring''' import argparse import json import os import torch from torch import nn from transformers import NllbMoeConfig, NllbMoeModel from transformers.modeling_utils import dtype_byte_size from transformers.utils import WEIGHTS_INDEX_NAME, WEIGHTS_NAME def __lowerC...
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'''simple docstring''' # tests directory-specific settings - this file is run automatically # by pytest before any tests are run import sys import warnings from os.path import abspath, dirname, join # allow having multiple repository checkouts and not needing to remember to rerun # 'p...
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'''simple docstring''' from dataclasses import dataclass from enum import Enum from typing import List, Optional, Union import numpy as np import PIL from PIL import Image from ...utils import BaseOutput, is_torch_available, is_transformers_available @dataclass class A ( S...
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'''simple docstring''' import unittest from typing import Dict, List, Optional, Union import numpy as np from transformers.testing_utils import require_torch, require_vision from transformers.utils import is_torch_available, is_vision_available from ...test_image_processing_common impo...
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'''simple docstring''' import datasets import faiss import numpy as np import streamlit as st import torch from elasticsearch import Elasticsearch from elia_utils import ( embed_questions_for_retrieval, make_qa_sas_model, qa_sas_generate, query_es_index, query_qa_de...
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'''simple docstring''' import argparse import os import gluonnlp as nlp import mxnet as mx import numpy as np import torch from gluonnlp.base import get_home_dir from gluonnlp.model.bert import BERTEncoder from gluonnlp.model.utils import _load_vocab from gluonnlp.vocab import Vocab f...
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'''simple docstring''' from __future__ import annotations import unittest from transformers import BlenderbotSmallConfig, BlenderbotSmallTokenizer, is_tf_available from transformers.testing_utils import require_tf, require_tokenizers, slow from transformers.utils import cached_property ...
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'''simple docstring''' import os import tempfile from functools import partial from unittest import TestCase from unittest.mock import patch import datasets import datasets.config from .utils import require_beam class A ( datasets.BeamBasedBuilder ): '''simpl...
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'''simple docstring''' import argparse import pickle import numpy as np import torch from torch import nn from transformers import ReformerConfig, ReformerModelWithLMHead from transformers.utils import logging logging.set_verbosity_info() def __lowerCAmelCase ( snake_c...
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'''simple docstring''' # 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/l...
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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, "m...
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'''simple docstring''' import json import os import unittest from transformers.models.blenderbot_small.tokenization_blenderbot_small import ( VOCAB_FILES_NAMES, BlenderbotSmallTokenizer, ) from ...test_tokenization_common import TokenizerTesterMixin class A ( SCREA...
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'''simple docstring''' from __future__ import annotations from collections.abc import Callable from typing import Any, Generic, TypeVar _lowerCAmelCase = TypeVar('''T''') class A ( Generic[T] ): '''simple docstring''' def __init__(self , ...
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'''simple docstring''' from typing import Optional, Tuple, Union import tensorflow as tf from ...activations_tf import ACTaFN from ...file_utils import add_code_sample_docstrings, add_start_docstrings, add_start_docstrings_to_model_forward from ...modeling_tf_outputs import ( TFBaseM...
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'''simple docstring''' def __lowerCAmelCase ( snake_case__ ): if num < 0: return False __UpperCamelCase : int = num __UpperCamelCase : int = 0 while num > 0: __UpperCamelCase : Optional[Any] = rev_nu...
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'''simple docstring''' import torch from torch import nn from torch.nn import CrossEntropyLoss, MSELoss from transformers.file_utils import add_start_docstrings, add_start_docstrings_to_model_forward from transformers.models.bert.modeling_bert import ( BERT_INPUTS_DOCSTRING, BERT_...
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'''simple docstring''' import argparse import json import logging import os import sys from unittest.mock import patch from transformers.testing_utils import TestCasePlus, get_gpu_count, slow _lowerCAmelCase = [ os.path.join(os.path.dirname(__file__), dirname) for...
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'''simple docstring''' import os from huggingface_hub.constants import HUGGINGFACE_HUB_CACHE, hf_cache_home _lowerCAmelCase = HUGGINGFACE_HUB_CACHE _lowerCAmelCase = '''config.json''' _lowerCAmelCase = '''diffusion_pytorch_model.bin''' _lowerCAmelCase ...
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'''simple docstring''' # flake8: noqa # Lint as: python3 from typing import Dict, List, Optional, Type from .. import config from ..utils import logging from .formatting import ( ArrowFormatter, CustomFormatter, Formatter, PandasFormatter, PythonFormatter, T...
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'''simple docstring''' from __future__ import annotations import os import tempfile import unittest from transformers import ConvBertConfig, is_tf_available from transformers.testing_utils import require_tf, slow from ...test_configuration_common import ConfigTester from ...test_mode...
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'''simple docstring''' from typing import Dict, List, Optional, Tuple, 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, ...
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'''simple docstring''' import argparse import json from dataclasses import dataclass, field from functools import partial from pathlib import Path from typing import List import timm import torch import torch.nn as nn from huggingface_hub import hf_hub_download from torch import Tenso...
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'''simple docstring''' 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.sha...
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'''simple docstring''' import argparse import json import logging import os import shutil import sys import tempfile import unittest from unittest import mock import torch from accelerate.utils import write_basic_config from transformers.testing_utils import TestCasePlus, get_gpu_c...
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'''simple docstring''' import re import tempfile from pathlib import Path import pytest import yaml from datasets.utils.readme import ReadMe # @pytest.fixture # def example_yaml_structure(): _lowerCAmelCase = yaml.safe_load( '''\ name: "" allow_empty: false allow_...
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'''simple docstring''' from maths.prime_check import is_prime def __lowerCAmelCase ( snake_case__ ): if not isinstance(snake_case__ , snake_case__ ): __UpperCamelCase : Optional[int] = F"Input value of [number={number}] must be an intege...
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'''simple docstring''' import argparse import torch from transformers import ( SpeechTaConfig, SpeechTaFeatureExtractor, SpeechTaForSpeechToSpeech, SpeechTaForSpeechToText, SpeechTaForTextToSpeech, SpeechTaProcessor, SpeechTaTokenizer, logging, ) fr...
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'''simple docstring''' def __lowerCAmelCase ( snake_case__ , snake_case__ , snake_case__ , snake_case__ , snake_case__ , ): __UpperCamelCase : Dict = [redshift, radiation_density, matter_density, dark_energy] if any(p...
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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 _lowerCAmelCase = '''src/tr...
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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 _lowerCAmelCase = '''src/tr...
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'''simple docstring''' # Usage: # ./gen-card-facebook-wmt19.py import os from pathlib import Path def __lowerCAmelCase ( snake_case__ , snake_case__ , snake_case__ ): __UpperCamelCase : int = { "en": "Machine learning is great,...
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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 A ( SCREAMI...
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'''simple docstring''' def __lowerCAmelCase ( snake_case__ ): __UpperCamelCase : str = current_set.copy() for row_index, row in enumerate(snake_case__ ): __UpperCamelCase : List[str] = row[0] for column_index, column in e...
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'''simple docstring''' def __lowerCAmelCase ( snake_case__ ): return "".join([hex(snake_case__ )[2:].zfill(2 ).upper() for byte in list(snake_case__ )] ) def __lowerCAmelCase ( snake_case__ ): # Check data validity, following RFC3548 ...
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'''simple docstring''' import argparse import logging import os from datetime import datetime import numpy as np import torch from torch import nn from torch.utils.data import DataLoader, RandomSampler, TensorDataset from tqdm import tqdm from transformers import GPTaLMHeadModel ...
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'''simple docstring''' import argparse import json import logging import os import sys from unittest.mock import patch from transformers.testing_utils import TestCasePlus, get_gpu_count, slow _lowerCAmelCase = [ os.path.join(os.path.dirname(__file__), dirname) for...
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'''simple docstring''' from ...utils import logging from ..ta.modeling_tf_ta import TFTaEncoderModel, TFTaForConditionalGeneration, TFTaModel from .configuration_mta import MTaConfig _lowerCAmelCase = logging.get_logger(__name__) _lowerCAmelCase = '''T5Config''' ...
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'''simple docstring''' import unittest from transformers import TrOCRConfig from transformers.testing_utils import is_torch_available, require_torch, torch_device from ...generation.test_utils import GenerationTesterMixin from ...test_configuration_common import ConfigTester from ...test...
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'''simple docstring''' import os try: from .build_directory_md import good_file_paths except ImportError: from build_directory_md import good_file_paths # type: ignore _lowerCAmelCase = list(good_file_paths()) assert filepaths, "good_file_paths() failed!" _lowerCAm...
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'''simple docstring''' import argparse from pathlib import Path import fairseq import torch from fairseq.models.xmod import XMODModel as FairseqXmodModel from packaging import version from transformers import XmodConfig, XmodForMaskedLM, XmodForSequenceClassification from transformers....
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'''simple docstring''' from ...configuration_utils import PretrainedConfig from ...utils import logging from ...utils.backbone_utils import BackboneConfigMixin, get_aligned_output_features_output_indices _lowerCAmelCase = logging.get_logger(__name__) _lowerCAmelCase = ...
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'''simple docstring''' def __lowerCAmelCase ( snake_case__ ): return [ txt[:a] + txt[a].upper() + txt[a + 1 :] for a in range(len(snake_case__ ) ) if txt[a].isalpha() ] if __name__ == "__main__": __import__('''doctest''').testmod(...
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'''simple docstring''' import os from huggingface_hub.constants import HUGGINGFACE_HUB_CACHE, hf_cache_home _lowerCAmelCase = HUGGINGFACE_HUB_CACHE _lowerCAmelCase = '''config.json''' _lowerCAmelCase = '''diffusion_pytorch_model.bin''' _lowerCAmelCase ...
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'''simple docstring''' def __lowerCAmelCase ( snake_case__ , snake_case__ , snake_case__ ): def count_of_possible_combinations(snake_case__ ) -> int: if target < 0: return 0 if target == 0: return 1 return sum(co...
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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 __lowerCAmelCase ( snake_case__ ): __UpperCamelCase : Op...
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'''simple docstring''' # tests directory-specific settings - this file is run automatically # by pytest before any tests are run import sys import warnings from os.path import abspath, dirname, join # allow having multiple repository checkouts and not needing to remember to rerun # 'p...
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'''simple docstring''' import math def __lowerCAmelCase ( snake_case__ , snake_case__ ): __UpperCamelCase : Optional[int] = len(snake_case__ ) __UpperCamelCase : int = int(math.floor(math.sqrt(snake_case__ ) ) ...
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'''simple docstring''' import unittest from typing import Dict, List, Optional, Union import numpy as np from transformers.testing_utils import require_torch, require_vision from transformers.utils import is_torch_available, is_vision_available from ...test_image_processing_common impo...
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'''simple docstring''' import pandas as pd from matplotlib import pyplot as plt from sklearn.linear_model import LinearRegression # Splitting the dataset into the Training set and Test set from sklearn.model_selection import train_test_split # Fitting Polynomial Regression to the dataset...
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'''simple docstring''' import argparse import os import gluonnlp as nlp import mxnet as mx import numpy as np import torch from gluonnlp.base import get_home_dir from gluonnlp.model.bert import BERTEncoder from gluonnlp.model.utils import _load_vocab from gluonnlp.vocab import Vocab f...
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'''simple docstring''' 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, TableTransf...
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'''simple docstring''' import os import tempfile from functools import partial from unittest import TestCase from unittest.mock import patch import datasets import datasets.config from .utils import require_beam class A ( datasets.BeamBasedBuilder ): '''simpl...
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'''simple docstring''' def __lowerCAmelCase ( snake_case__ ): __UpperCamelCase : List[str] = 0 for ch in input_str: __UpperCamelCase : int = ord(snake_case__ ) __UpperCamelCase : Optional[int] = pow(2 ...
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'''simple docstring''' # 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/l...
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'''simple docstring''' from __future__ import annotations import unittest from transformers import is_tf_available from transformers.testing_utils import require_sentencepiece, require_tf, require_tokenizers, slow if is_tf_available(): import tensorflow as tf from transfor...
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'''simple docstring''' import json import os import unittest from transformers.models.blenderbot_small.tokenization_blenderbot_small import ( VOCAB_FILES_NAMES, BlenderbotSmallTokenizer, ) from ...test_tokenization_common import TokenizerTesterMixin class A ( SCREA...
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'''simple docstring''' import argparse import logging from collections import namedtuple import torch from model_bertabs import BertAbsSummarizer from models.model_builder import AbsSummarizer # The authors' implementation from transformers import BertTokenizer logging.basicConfig...
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'''simple docstring''' from typing import Optional, Tuple, Union import tensorflow as tf from ...activations_tf import ACTaFN from ...file_utils import add_code_sample_docstrings, add_start_docstrings, add_start_docstrings_to_model_forward from ...modeling_tf_outputs import ( TFBaseM...
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'''simple docstring''' def __lowerCAmelCase ( snake_case__ , snake_case__ , snake_case__ ): __UpperCamelCase : Union[str, Any] = (num_of_terms / 2) * (2 * first_term + (num_of_terms - 1) * common_diff) # formula for sum of series retur...
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'''simple docstring''' import torch from torch import nn from torch.nn import CrossEntropyLoss, MSELoss from transformers.file_utils import add_start_docstrings, add_start_docstrings_to_model_forward from transformers.models.bert.modeling_bert import ( BERT_INPUTS_DOCSTRING, BERT_...
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'''simple docstring''' from typing import TYPE_CHECKING from ....utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available _lowerCAmelCase = { '''configuration_mctct''': ['''MCTCT_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''MCTCTConfig'''], '''feature_extra...
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'''simple docstring''' import os from huggingface_hub.constants import HUGGINGFACE_HUB_CACHE, hf_cache_home _lowerCAmelCase = HUGGINGFACE_HUB_CACHE _lowerCAmelCase = '''config.json''' _lowerCAmelCase = '''diffusion_pytorch_model.bin''' _lowerCAmelCase ...
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'''simple docstring''' from .constants import ( MODEL_NAME, OPTIMIZER_NAME, RNG_STATE_NAME, SAFE_WEIGHTS_INDEX_NAME, SAFE_WEIGHTS_NAME, SCALER_NAME, SCHEDULER_NAME, TORCH_LAUNCH_PARAMS, WEIGHTS_INDEX_NAME, WEIGHTS_NAME, ) from .dataclasses impor...
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'''simple docstring''' from __future__ import annotations import os import tempfile import unittest from transformers import ConvBertConfig, is_tf_available from transformers.testing_utils import require_tf, slow from ...test_configuration_common import ConfigTester from ...test_mode...
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'''simple docstring''' import sys def __lowerCAmelCase ( snake_case__ ): __UpperCamelCase : Dict = len(snake_case__ ) __UpperCamelCase : List[str] = [[0 for x in range(snake_case__ )] for x in range(snake_case__ )] __U...
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'''simple docstring''' import argparse import json from dataclasses import dataclass, field from functools import partial from pathlib import Path from typing import List import timm import torch import torch.nn as nn from huggingface_hub import hf_hub_download from torch import Tenso...
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'''simple docstring''' import pprint import requests _lowerCAmelCase = '''https://zenquotes.io/api''' def __lowerCAmelCase ( ): return requests.get(API_ENDPOINT_URL + "/today" ).json() def __lowerCAmelCase ( ): return requests.get(API_ENDPOIN...
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'''simple docstring''' import argparse import json import logging import os import shutil import sys import tempfile import unittest from unittest import mock import torch from accelerate.utils import write_basic_config from transformers.testing_utils import TestCasePlus, get_gpu_c...
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'''simple docstring''' import os from typing import Dict, List, Union import tensorflow as tf from keras_nlp.tokenizers import BytePairTokenizer from tensorflow_text import pad_model_inputs from .tokenization_gpta import GPTaTokenizer class A ( tf.keras.layers.Layer ): ...
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'''simple docstring''' from maths.prime_check import is_prime def __lowerCAmelCase ( snake_case__ ): if not isinstance(snake_case__ , snake_case__ ): __UpperCamelCase : Optional[int] = F"Input value of [number={number}] must be an intege...
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'''simple docstring''' import inspect import unittest from datasets import load_dataset from packaging import version from transformers import BeitConfig from transformers.models.auto import get_values from transformers.testing_utils import require_torch, require_torch_multi_gpu, requir...
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'''simple docstring''' def __lowerCAmelCase ( snake_case__ , snake_case__ , snake_case__ , snake_case__ , snake_case__ , ): __UpperCamelCase : Dict = [redshift, radiation_density, matter_density, dark_energy] if any(p...
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'''simple docstring''' from ..utils import DummyObject, requires_backends class A ( metaclass=SCREAMING_SNAKE_CASE__ ): '''simple docstring''' A = ["torch", "scipy"] def __init__(self , *_UpperCAmelCase , **_UpperCAmelCase ) -> Lis...
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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 _lowerCAmelCase = '''src/tr...
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'''simple docstring''' # DISCLAIMER: This file is strongly influenced by https://github.com/ermongroup/ddim from dataclasses import dataclass from typing import Optional, Tuple, Union import flax import jax import jax.numpy as jnp from ..configuration_utils import ConfigMixin, registe...
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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 A ( SCREAMI...
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'''simple docstring''' import inspect import jax import jax.lax as lax import jax.numpy as jnp from ..utils import add_start_docstrings from ..utils.logging import get_logger _lowerCAmelCase = get_logger(__name__) _lowerCAmelCase = R''' Args: inp...
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'''simple docstring''' def __lowerCAmelCase ( snake_case__ ): return "".join([hex(snake_case__ )[2:].zfill(2 ).upper() for byte in list(snake_case__ )] ) def __lowerCAmelCase ( snake_case__ ): # Check data validity, following RFC3548 ...
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'''simple docstring''' import argparse import json import logging import os import shutil import sys import tempfile import unittest from unittest import mock import torch from accelerate.utils import write_basic_config from transformers.testing_utils import TestCasePlus, get_gpu_c...
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'''simple docstring''' import argparse import json import logging import os import sys from unittest.mock import patch from transformers.testing_utils import TestCasePlus, get_gpu_count, slow _lowerCAmelCase = [ os.path.join(os.path.dirname(__file__), dirname) for...
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'''simple docstring''' import inspect import unittest from huggingface_hub import hf_hub_download from transformers import ConvNextConfig, UperNetConfig from transformers.testing_utils import require_torch, require_torch_multi_gpu, require_vision, slow, torch_device from transformers.uti...
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'''simple docstring''' import unittest from transformers import TrOCRConfig from transformers.testing_utils import is_torch_available, require_torch, torch_device from ...generation.test_utils import GenerationTesterMixin from ...test_configuration_common import ConfigTester from ...test...
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'''simple docstring''' from __future__ import annotations import math def __lowerCAmelCase ( snake_case__ , snake_case__ , snake_case__ , snake_case__ , snake_case__ ): if depth < 0: raise ValueError("Depth cannot be less than ...
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'''simple docstring''' import argparse from pathlib import Path import fairseq import torch from fairseq.models.xmod import XMODModel as FairseqXmodModel from packaging import version from transformers import XmodConfig, XmodForMaskedLM, XmodForSequenceClassification from transformers....
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'''simple docstring''' # Copyright 2023 The HuggingFace Team. All rights reserved. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/l...
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'''simple docstring''' def __lowerCAmelCase ( snake_case__ ): return [ txt[:a] + txt[a].upper() + txt[a + 1 :] for a in range(len(snake_case__ ) ) if txt[a].isalpha() ] if __name__ == "__main__": __import__('''doctest''').testmod(...
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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_funnel import FunnelTokenizer _lowerCAmelCase = log...
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'''simple docstring''' def __lowerCAmelCase ( snake_case__ , snake_case__ , snake_case__ ): def count_of_possible_combinations(snake_case__ ) -> int: if target < 0: return 0 if target == 0: return 1 return sum(co...
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'''simple docstring''' def __lowerCAmelCase ( snake_case__ ): __UpperCamelCase : Optional[int] = [0 for i in range(len(snake_case__ ) )] # initialize interval's left pointer and right pointer __UpperCamelCase , __UpperCamelCase : ...
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'''simple docstring''' # tests directory-specific settings - this file is run automatically # by pytest before any tests are run import sys import warnings from os.path import abspath, dirname, join # allow having multiple repository checkouts and not needing to remember to rerun # 'p...
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'''simple docstring''' from manim import * class A ( SCREAMING_SNAKE_CASE__ ): '''simple docstring''' def a_ (self ) -> List[str]: __UpperCamelCase : Tuple = Rectangle(height=0.5 , width=0.5 ) __Upp...
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'''simple docstring''' import unittest from typing import Dict, List, Optional, Union import numpy as np from transformers.testing_utils import require_torch, require_vision from transformers.utils import is_torch_available, is_vision_available from ...test_image_processing_common impo...
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'''simple docstring''' from dataclasses import dataclass from typing import Optional, Tuple, Union import torch import torch.nn as nn from ..configuration_utils import ConfigMixin, register_to_config from ..utils import BaseOutput, apply_forward_hook from .modeling_utils import ModelMix...
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'''simple docstring''' import argparse import os import gluonnlp as nlp import mxnet as mx import numpy as np import torch from gluonnlp.base import get_home_dir from gluonnlp.model.bert import BERTEncoder from gluonnlp.model.utils import _load_vocab from gluonnlp.vocab import Vocab f...
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'''simple docstring''' from datetime import datetime import matplotlib.pyplot as plt import torch def __lowerCAmelCase ( snake_case__ ): for param in module.parameters(): __UpperCamelCase : Any = False def __lowerCAmelCase ( ): __...
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'''simple docstring''' import os import tempfile from functools import partial from unittest import TestCase from unittest.mock import patch import datasets import datasets.config from .utils import require_beam class A ( datasets.BeamBasedBuilder ): '''simpl...
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'''simple docstring''' import collections import os import re from pathlib import Path _lowerCAmelCase = '''src/transformers''' # Matches is_xxx_available() _lowerCAmelCase = re.compile(R'''is\_([a-z_]*)_available()''') # Catches a one-line _import_struct = {xxx...
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'''simple docstring''' # 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/l...
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'''simple docstring''' import random from typing import Any def __lowerCAmelCase ( snake_case__ ): for _ in range(len(snake_case__ ) ): __UpperCamelCase : Union[str, Any] = random.randint(0 , len(snake_case__ ) - 1 ) ...
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'''simple docstring''' import json import os import unittest from transformers.models.blenderbot_small.tokenization_blenderbot_small import ( VOCAB_FILES_NAMES, BlenderbotSmallTokenizer, ) from ...test_tokenization_common import TokenizerTesterMixin class A ( SCREA...
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'''simple docstring''' import importlib import os import fsspec import pytest from fsspec import register_implementation from fsspec.registry import _registry as _fsspec_registry from datasets.filesystems import COMPRESSION_FILESYSTEMS, HfFileSystem, extract_path_from_uri, is_remote_fil...
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'''simple docstring''' from typing import Optional, Tuple, Union import tensorflow as tf from ...activations_tf import ACTaFN from ...file_utils import add_code_sample_docstrings, add_start_docstrings, add_start_docstrings_to_model_forward from ...modeling_tf_outputs import ( TFBaseM...
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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 A ( unittest.TestCase ): '''simple docstring''' def a_ (self ) -> ...
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'''simple docstring''' import torch from torch import nn from torch.nn import CrossEntropyLoss, MSELoss from transformers.file_utils import add_start_docstrings, add_start_docstrings_to_model_forward from transformers.models.bert.modeling_bert import ( BERT_INPUTS_DOCSTRING, BERT_...
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'''simple docstring''' def __lowerCAmelCase ( snake_case__ ): return "".join([hex(snake_case__ )[2:].zfill(2 ).upper() for byte in list(snake_case__ )] ) def __lowerCAmelCase ( snake_case__ ): # Check data validity, following RFC3548 ...
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'''simple docstring''' import os from huggingface_hub.constants import HUGGINGFACE_HUB_CACHE, hf_cache_home _lowerCAmelCase = HUGGINGFACE_HUB_CACHE _lowerCAmelCase = '''config.json''' _lowerCAmelCase = '''diffusion_pytorch_model.bin''' _lowerCAmelCase ...
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'''simple docstring''' import math def __lowerCAmelCase ( snake_case__ , snake_case__ ): if initial_intensity < 0: raise ValueError("The value of intensity cannot be negative" ) # handling of negative values of initial intensity if angle < 0...
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'''simple docstring''' from __future__ import annotations import os import tempfile import unittest from transformers import ConvBertConfig, is_tf_available from transformers.testing_utils import require_tf, slow from ...test_configuration_common import ConfigTester from ...test_mode...
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'''simple docstring''' import numpy as np from cva import COLOR_BGR2GRAY, cvtColor, imread from numpy import array, uinta from PIL import Image from digital_image_processing import change_contrast as cc from digital_image_processing import convert_to_negative as cn from digital_image_proc...
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'''simple docstring''' import argparse import json from dataclasses import dataclass, field from functools import partial from pathlib import Path from typing import List import timm import torch import torch.nn as nn from huggingface_hub import hf_hub_download from torch import Tenso...
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'''simple docstring''' from collections import Counter from pathlib import Path from typing import Optional, Tuple import yaml class A ( yaml.SafeLoader ): '''simple docstring''' def a_ (self , _UpperCAmelCase ) -> List[Any]: ...
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'''simple docstring''' import argparse import json import logging import os import shutil import sys import tempfile import unittest from unittest import mock import torch from accelerate.utils import write_basic_config from transformers.testing_utils import TestCasePlus, get_gpu_c...
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'''simple docstring''' import unicodedata from dataclasses import dataclass from typing import Optional, Union import numpy as np from transformers.data.data_collator import DataCollatorMixin from transformers.file_utils import PaddingStrategy from transformers.tokenization_utils_base i...
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'''simple docstring''' from maths.prime_check import is_prime def __lowerCAmelCase ( snake_case__ ): if not isinstance(snake_case__ , snake_case__ ): __UpperCamelCase : Optional[int] = F"Input value of [number={number}] must be an intege...
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'''simple docstring''' import inspect import unittest from transformers import DecisionTransformerConfig, is_torch_available from transformers.testing_utils import require_torch, slow, torch_device from ...generation.test_utils import GenerationTesterMixin from ...test_configuration_comm...
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'''simple docstring''' def __lowerCAmelCase ( snake_case__ , snake_case__ , snake_case__ , snake_case__ , snake_case__ , ): __UpperCamelCase : Dict = [redshift, radiation_density, matter_density, dark_energy] if any(p...
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'''simple docstring''' import argparse import json from collections import OrderedDict import torch from huggingface_hub import cached_download, hf_hub_url from transformers import AutoImageProcessor, CvtConfig, CvtForImageClassification def __lowerCAmelCase ( snake_case__ ...
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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 _lowerCAmelCase = '''src/tr...
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'''simple docstring''' from __future__ import annotations import time import numpy as np _lowerCAmelCase = [8, 5, 9, 7] _lowerCAmelCase = [ [2, 0, 1, 1], [0, 1, 2, 1], [4, 0, 0, 3], [0, 2, 1, 0], [1, 0, 3, 0], ] _lowerCAmelCase = ...
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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 A ( SCREAMI...
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'''simple docstring''' import re from pathlib import Path from unittest import TestCase import pytest @pytest.mark.integration class A ( SCREAMING_SNAKE_CASE__ ): '''simple docstring''' def a_ (self , _UpperCAmelCase ) -> Union...
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'''simple docstring''' def __lowerCAmelCase ( snake_case__ ): return "".join([hex(snake_case__ )[2:].zfill(2 ).upper() for byte in list(snake_case__ )] ) def __lowerCAmelCase ( snake_case__ ): # Check data validity, following RFC3548 ...
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'''simple docstring''' import argparse import json from pathlib import Path import requests import timm import torch from huggingface_hub import hf_hub_download from PIL import Image from transformers import DeiTImageProcessor, ViTConfig, ViTForImageClassification, ViTImageProcessor, ...
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'''simple docstring''' import argparse import json import logging import os import sys from unittest.mock import patch from transformers.testing_utils import TestCasePlus, get_gpu_count, slow _lowerCAmelCase = [ os.path.join(os.path.dirname(__file__), dirname) for...
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'''simple docstring''' def __lowerCAmelCase ( snake_case__ = 4_000_000 ): __UpperCamelCase : int = [] __UpperCamelCase , __UpperCamelCase : Any = 0, 1 while b <= n: if b % 2 == 0: even_fibs.append(snake_case__ ...
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'''simple docstring''' import unittest from transformers import TrOCRConfig from transformers.testing_utils import is_torch_available, require_torch, torch_device from ...generation.test_utils import GenerationTesterMixin from ...test_configuration_common import ConfigTester from ...test...
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