code stringlengths 82 54.1k | code_codestyle int64 0 699 | style_context stringlengths 111 35.6k | style_context_codestyle int64 0 699 | label int64 0 1 |
|---|---|---|---|---|
'''simple docstring'''
from collections import OrderedDict
from typing import Mapping
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
lowerCamelCase : Dict = logging.get_logger(__name__)
lowerCamelCase : List[Any] = {
"junny... | 405 |
from collections.abc import Callable
def __lowerCAmelCase( _SCREAMING_SNAKE_CASE , _SCREAMING_SNAKE_CASE , _SCREAMING_SNAKE_CASE ) -> float:
"""simple docstring"""
_A = a
_A = b
if function(_SCREAMING_S... | 27 | 0 |
'''simple docstring'''
import json
import os
import unittest
from transformers.models.biogpt.tokenization_biogpt import VOCAB_FILES_NAMES, BioGptTokenizer
from transformers.testing_utils import slow
from ...test_tokenization_common import TokenizerTesterMixin
class lowerCAmelCase_ ( __snake_case ,unitt... | 18 |
import unittest
from transformers import AutoTokenizer, NystromformerConfig, is_torch_available
from transformers.testing_utils import require_torch, slow, torch_device
from ...test_configuration_common import ConfigTester
from ...test_modeling_common import ModelTesterMixin, ids_tensor, random_atte... | 27 | 0 |
def lowerCAmelCase ( UpperCamelCase__ : Optional[Any] , UpperCamelCase__ : Tuple ) -> Any:
"""simple docstring"""
__SCREAMING_SNAKE_CASE: Tuple = (boundary[1] - boundary[0]) / steps
__SCREAMING_SNAKE_CASE: str = boundary[0]
... | 202 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tf_available,
is_tokenizers_available,
is_torch_available,
)
__A : Dict = {
"configuration_blenderbot": [
"BLENDER... | 27 | 0 |
'''simple docstring'''
import argparse
import csv
import logging
import os
import random
import numpy as np
import torch
from torch.utils.data import DataLoader, RandomSampler, SequentialSampler, TensorDataset
from tqdm import tqdm, trange
from transformers import (
CONFIG_NAME,
WEIGHTS_NAME,
AdamW,
... | 451 |
import sys
from .dependency_versions_table import deps
from .utils.versions import require_version, require_version_core
# define which module versions we always want to check at run time
# (usually the ones defined in `install_requires` in setup.py)
#
# order specific notes:
# - tqdm must be c... | 27 | 0 |
"""simple docstring"""
from ..utils import DummyObject, requires_backends
class __snake_case ( metaclass=__snake_case ):
"""simple docstring"""
lowerCAmelCase_ : int = ['torch', 'torchsde']
def __init__( self :Dict , *UpperCamelCase__ :Dict , *... | 388 |
def __lowerCAmelCase( _SCREAMING_SNAKE_CASE , _SCREAMING_SNAKE_CASE ) -> int:
"""simple docstring"""
return int((input_a, input_a).count(0 ) != 0 )
def __lowerCAmelCase( ) -> None:
"""simple docstring"""
... | 27 | 0 |
import argparse
import json
from typing import List
from ltp import LTP
from transformers.models.bert.tokenization_bert import BertTokenizer
def _lowercase ( lowercase__ ):
if (
(cp >= 0X4e_00 and cp <= 0X9f_ff)
or (cp >= 0X34_00 and cp <= 0X4d_bf) #
or (cp... | 492 |
from __future__ import annotations
import unittest
from transformers import EsmConfig, is_tf_available
from transformers.testing_utils import require_tf, slow
from ...test_configuration_common import ConfigTester
from ...test_modeling_tf_common import TFModelTesterMixin, floats_tensor, ids_tensor... | 27 | 0 |
def _snake_case( SCREAMING_SNAKE_CASE__ ) -> int:
if n == 1 or not isinstance(_SCREAMING_SNAKE_CASE , _SCREAMING_SNAKE_CASE ):
return 0
elif n == 2:
return 1
else:
lowercase : Union[str, Any] = [0, 1]
... | 336 |
import logging
from pathlib import Path
import numpy as np
import pytorch_lightning as pl
import torch
from pytorch_lightning.callbacks import EarlyStopping, ModelCheckpoint
from pytorch_lightning.utilities import rank_zero_only
from utils_rag import save_json
def __lowerCAmelCase( ... | 27 | 0 |
import argparse
import os
from pathlib import Path
import torch
from bark.generation import _load_model as _bark_load_model
from huggingface_hub import hf_hub_download
from transformers import EncodecConfig, EncodecModel, set_seed
from transformers.models.bark.configuration_bark import (
B... | 387 |
def __lowerCAmelCase( _SCREAMING_SNAKE_CASE , _SCREAMING_SNAKE_CASE ) -> int:
"""simple docstring"""
print('\nThe shortest path matrix using Floyd Warshall algorithm\n' )
for i in range(_SCREAMING_SNAKE_CASE ):
for j in range(_SCREAM... | 27 | 0 |
"""simple docstring"""
from collections import OrderedDict
from typing import TYPE_CHECKING, Any, Mapping, Optional, Union
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
if TYPE_CHECKING:
from ... import FeatureExtractionMixi... | 602 |
# Copyright 2022 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 r... | 27 | 0 |
"""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/licenses/LICENS... | 224 |
from ... import PretrainedConfig
__A : Optional[Any] = {
"sijunhe/nezha-cn-base": "https://huggingface.co/sijunhe/nezha-cn-base/resolve/main/config.json",
}
class lowerCamelCase( __snake_case ):
'''simple docstring'''
__magic_name__ = ... | 27 | 0 |
from ... import PretrainedConfig
a_ = {
"sijunhe/nezha-cn-base": "https://huggingface.co/sijunhe/nezha-cn-base/resolve/main/config.json",
}
class _UpperCamelCase ( __snake_case ):
'''simple docstring'''
lowerCamelCase__ =NEZHA_PRETRAINED_CONFIG_ARCHIVE_MAP
lowerCa... | 25 |
from collections import defaultdict
from math import ceil, sqrt
def __lowerCAmelCase( _SCREAMING_SNAKE_CASE = 1_000_000 , _SCREAMING_SNAKE_CASE = 10 ) -> int:
"""simple docstring"""
_A = defaultdict(_SCREAMING_SNAKE_CASE )
... | 27 | 0 |
'''simple docstring'''
from __future__ import annotations
def _lowerCAmelCase ( _UpperCamelCase : Optional[Any] , _UpperCamelCase : int , _UpperCamelCase : List[Any] , _UpperCamelCase : Any , _UpperCamelCase : List[str] , ) -> None:
"""simple docstring"""
... | 405 |
from math import pi, sqrt, tan
def __lowerCAmelCase( _SCREAMING_SNAKE_CASE ) -> float:
"""simple docstring"""
if side_length < 0:
raise ValueError('surface_area_cube() only accepts non-negative values' )
return 6 * side_length**2
... | 27 | 0 |
'''simple docstring'''
import json
import os
import subprocess
import unittest
from ast import literal_eval
import pytest
from parameterized import parameterized, parameterized_class
from . import is_sagemaker_available
if is_sagemaker_available():
from sagemaker import Session, TrainingJobAnalytics
... | 18 |
import numpy as np
def __lowerCAmelCase( _SCREAMING_SNAKE_CASE ) -> np.array:
"""simple docstring"""
return (2 / (1 + np.exp(-2 * vector ))) - 1
if __name__ == "__main__":
import doctest
doctest.testmod()
| 27 | 0 |
import json
from typing import List, Optional, Tuple
from tokenizers import normalizers
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from .tokenization_electra import ElectraTokenizer
lowerCAmelCase : int = {"vocab_file": "vocab.txt", "tokenizer_file": "tokenizer.json"}
low... | 202 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_sentencepiece_available
__A : Optional[Any] = {}
try:
if not is_sentencepiece_available():
raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
... | 27 | 0 |
'''simple docstring'''
from typing import Dict, List, Optional, Union
import numpy as np
from transformers.utils import is_vision_available
from transformers.utils.generic import TensorType
from ...image_processing_utils import BaseImageProcessor, BatchFeature, get_size_dict
from ...image_transforms import (
c... | 451 |
import json
import os
from pathlib import Path
import pytest
from datasets.download.download_config import DownloadConfig
from datasets.download.download_manager import DownloadManager
from datasets.utils.file_utils import hash_url_to_filename
__A : List[Any] = "http://www.m... | 27 | 0 |
"""simple docstring"""
from typing import Mapping
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxSeqaSeqConfigWithPast
from ...utils import logging
__SCREAMING_SNAKE_CASE = logging.get_logger(__name__)
__SCREAMING_SNAKE_CASE = {
"t5-small": "https://huggin... | 388 |
from __future__ import annotations
from fractions import Fraction
from math import gcd, sqrt
def __lowerCAmelCase( _SCREAMING_SNAKE_CASE ) -> bool:
"""simple docstring"""
_A = int(number**0.5 )
return number == sq * sq
... | 27 | 0 |
from __future__ import annotations
import time
import numpy as np
_UpperCamelCase = [8, 5, 9, 7]
_UpperCamelCase = [
[2, 0, 1, 1],
[0, 1, 2, 1],
[4, 0, 0, 3],
[0, 2, 1, 0],
[1, 0, 3, 0],
]
_UpperCamelCase = [
[3, 2, 1, 4],
[0, 2, 5, 2],
[5, ... | 492 |
from __future__ import annotations
import math
def __lowerCAmelCase( _SCREAMING_SNAKE_CASE ) -> list[int]:
"""simple docstring"""
if num <= 0:
_A = F"{num}: Invalid input, please enter a positive integer."
raise ValueErro... | 27 | 0 |
def _snake_case( ) -> Union[str, Any]:
for n in range(1 , 1_000_000 ):
yield n * (n + 1) // 2
def _snake_case( SCREAMING_SNAKE_CASE__ ) -> List[Any]:
lowercase : Optional[int] = 1
lowercase : List[Any] ... | 336 |
__A : Dict = "Alexander Joslin"
import operator as op
from .stack import Stack
def __lowerCAmelCase( _SCREAMING_SNAKE_CASE ) -> int:
"""simple docstring"""
_A = {'*': op.mul, '/': op.truediv, '+': op.add, '-': op.sub}
... | 27 | 0 |
import collections
from typing import List, Optional, Union
from ...tokenization_utils_base import BatchEncoding
from ...utils import TensorType, add_end_docstrings, add_start_docstrings, logging
from ..bert.tokenization_bert_fast import BertTokenizerFast
from .tokenization_dpr import DPRContextEnc... | 387 |
import unittest
import numpy as np
import torch
from diffusers import KarrasVePipeline, KarrasVeScheduler, UNetaDModel
from diffusers.utils.testing_utils import enable_full_determinism, require_torch, slow, torch_device
enable_full_determinism()
class lowerCamelCase( un... | 27 | 0 |
"""simple docstring"""
# DISCLAIMER: This file is strongly influenced by https://github.com/yang-song/score_sde_pytorch
import math
from typing import Union
import torch
from ..configuration_utils import ConfigMixin, register_to_config
from ..utils import randn_tensor
from .scheduling_utils imp... | 602 |
import itertools
import os
import random
import tempfile
import unittest
import numpy as np
from transformers import TvltFeatureExtractor, is_datasets_available
from transformers.testing_utils import check_json_file_has_correct_format, require_torch, require_torchaudio
from transformers.utils.im... | 27 | 0 |
'''simple docstring'''
import argparse
import json
import os
from tensorflow.core.protobuf.saved_model_pba import SavedModel
# All paths are set with the intent you should run this script from the root of the repo with the command
# python utils/check_copies.py
UpperCamelCase_ = "."
... | 28 |
'''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_distilbert import DistilBertTokenizer
UpperCamelCase_ = logg... | 28 | 1 |
'''simple docstring'''
def lowercase__( __UpperCamelCase: int ):
"""simple docstring"""
if not isinstance(__UpperCamelCase ,__UpperCamelCase ) or number < 0:
raise ValueError('Input must be a non-negative integer' )
SCREAMING_SNAKE... | 28 |
'''simple docstring'''
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 AutoImageProcessor, ViTImageProcessor
from transformer... | 28 | 1 |
'''simple docstring'''
import warnings
from transformers import AutoTokenizer
from transformers.utils import is_torch_available
from transformers.utils.generic import ExplicitEnum
from ...processing_utils import ProcessorMixin
if is_torch_available():
import torch
class... | 28 |
'''simple docstring'''
class _a :
'''simple docstring'''
def __init__( self, A ):
'''simple docstring'''
SCREAMING_SNAKE_CASE : Tuple = val
SCREAMING_SNA... | 28 | 1 |
'''simple docstring'''
import torch
from torch import nn
from ...configuration_utils import ConfigMixin, register_to_config
from ...models import ModelMixin
class _a ( SCREAMING_SNAKE_CASE , SCREAMING_SNAKE_CASE ):
'''simple docstring'''
... | 28 |
'''simple docstring'''
import inspect
import warnings
from typing import Any, Dict, Optional, Union
from packaging import version
def lowercase__( *__UpperCamelCase: Union[str, Any] ,__UpperCamelCase: Optional[Union[Dict, Any]] = None ,__UpperCamelCase: Dict=True... | 28 | 1 |
'''simple docstring'''
from typing import Any
def lowercase__( __UpperCamelCase: list ):
"""simple docstring"""
if not input_list:
return []
SCREAMING_SNAKE_CASE : Union[str, Any] = [input_list.count(__UpperCamelCas... | 28 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tf_available,
is_tokenizers_available,
is_torch_available,
)
UpperCamelCase_ = {
"configuration_roformer":... | 28 | 1 |
'''simple docstring'''
from __future__ import annotations
def lowercase__( __UpperCamelCase: int ):
"""simple docstring"""
SCREAMING_SNAKE_CASE : Optional[Any] = 2
SCREAMING_SNAKE_CASE : Tuple = []
whi... | 28 |
'''simple docstring'''
def lowercase__( __UpperCamelCase: int ):
"""simple docstring"""
if not isinstance(__UpperCamelCase ,__UpperCamelCase ):
raise TypeError('Input value must be an \'int\' type' )
SCREAMING_SNAKE_CASE : i... | 28 | 1 |
'''simple docstring'''
from __future__ import annotations
def lowercase__( __UpperCamelCase: list[int] ): # This function is recursive
"""simple docstring"""
SCREAMING_SNAKE_CASE : Optional[int] = len(__UpperCamelCase )
# If... | 28 |
'''simple docstring'''
from typing import Dict
from .base import GenericTensor, Pipeline
class _a ( SCREAMING_SNAKE_CASE ):
'''simple docstring'''
def UpperCamelCase_ ( self, A=None, A=None, A=None, ... | 28 | 1 |
'''simple docstring'''
from pickle import UnpicklingError
import jax
import jax.numpy as jnp
import numpy as np
from flax.serialization import from_bytes
from flax.traverse_util import flatten_dict
from ..utils import logging
UpperCamelCase_ = logging.get_logger(__name__)
... | 28 |
'''simple docstring'''
from __future__ import annotations
import queue
class _a :
'''simple docstring'''
def __init__( self, A ):
'''simple docstring'''
SCREAMING_SNAKE_CA... | 28 | 1 |
'''simple docstring'''
import warnings
from ...utils import logging
from .image_processing_deit import DeiTImageProcessor
UpperCamelCase_ = logging.get_logger(__name__)
class _a ( SCREAMING_SNAKE_CASE ):
'''simple docstring'''
... | 28 |
'''simple docstring'''
import os
from glob import glob
import imageio
import torch
import torchvision
import wandb
from img_processing import custom_to_pil, loop_post_process, preprocess, preprocess_vqgan
from loaders import load_vqgan
from PIL import Image
from torch import nn
from trans... | 28 | 1 |
'''simple docstring'''
import copy
import random
from transformers import CLIPTokenizer
class _a ( SCREAMING_SNAKE_CASE ):
'''simple docstring'''
def __init__( self, *A, **A ):
'''simple doc... | 28 |
'''simple docstring'''
import os
from typing import Any, Callable, Dict, List, Optional, Tuple, Union
import torch
from torch import nn
from ...models.controlnet import ControlNetModel, ControlNetOutput
from ...models.modeling_utils import ModelMixin
from ...utils import logging
UpperCam... | 28 | 1 |
'''simple docstring'''
import glob
import os
import random
from string import ascii_lowercase, digits
import cva
UpperCamelCase_ = ""
UpperCamelCase_ = ""
UpperCamelCase_ = ""
UpperCamelCase_ = 1 # (0 is vertical, 1 is horizontal)
def lowercase__( ):
... | 28 |
'''simple docstring'''
from math import ceil
from typing import List, Optional, Union
import numpy as np
from ...audio_utils import mel_filter_bank, spectrogram, window_function
from ...feature_extraction_sequence_utils import BatchFeature, SequenceFeatureExtractor
from ...utils import TensorT... | 28 | 1 |
'''simple docstring'''
import copy
from ...configuration_utils import PretrainedConfig
from ...utils import logging
from ..auto import CONFIG_MAPPING
UpperCamelCase_ = logging.get_logger(__name__)
UpperCamelCase_ = {
"SenseTime/deformable-detr": "https://huggingface.co/s... | 28 |
'''simple docstring'''
from collections import defaultdict
from graphs.minimum_spanning_tree_prims import prisms_algorithm as mst
def lowercase__( ):
"""simple docstring"""
SCREAMING_SNAKE_CASE , SCREAMING_SNAKE_CASE : str = 9, 14 ... | 28 | 1 |
'''simple docstring'''
import json
import os
import unittest
from transformers.models.gptsan_japanese.tokenization_gptsan_japanese import (
VOCAB_FILES_NAMES,
GPTSanJapaneseTokenizer,
)
from transformers.testing_utils import require_tokenizers, slow
from ...test_tokenization_common ... | 28 |
'''simple docstring'''
import gc
import random
import tempfile
import unittest
import numpy as np
import torch
from PIL import Image
from transformers import CLIPTextConfig, CLIPTextModel, CLIPTokenizer
from diffusers import (
AutoencoderKL,
DDIMInverseScheduler,
DDIMSchedule... | 28 | 1 |
'''simple docstring'''
import argparse
import torch
from transformers import OpenAIGPTConfig, OpenAIGPTModel, load_tf_weights_in_openai_gpt
from transformers.utils import CONFIG_NAME, WEIGHTS_NAME, logging
logging.set_verbosity_info()
def lowercase__( __UpperCamelCase: List... | 28 |
'''simple docstring'''
def lowercase__( __UpperCamelCase: int = 1_00_00_00 ):
"""simple docstring"""
SCREAMING_SNAKE_CASE : Tuple = [i - 1 for i in range(limit + 1 )]
for i in range(2 ,limit + 1 ):
if phi[i] == ... | 28 | 1 |
'''simple docstring'''
from collections.abc import Callable
import numpy as np
def lowercase__( __UpperCamelCase: Callable ,__UpperCamelCase: float ,__UpperCamelCase: float ,__UpperCamelCase: float ,__UpperCamelCase: float ):
"""simple... | 28 |
'''simple docstring'''
import itertools
import json
import os
import unittest
from transformers import AddedToken, LongformerTokenizer, LongformerTokenizerFast
from transformers.models.longformer.tokenization_longformer import VOCAB_FILES_NAMES
from transformers.testing_utils import require_tok... | 28 | 1 |
'''simple docstring'''
UpperCamelCase_ = {
"A": ["B", "C", "E"],
"B": ["A", "D", "E"],
"C": ["A", "F", "G"],
"D": ["B"],
"E": ["A", "B", "D"],
"F": ["C"],
"G": ["C"],
}
def lowercase__( __UpperCamelCase: dict ,__UpperCamelCase: Dict ... | 28 |
'''simple docstring'''
import gc
import random
import unittest
import numpy as np
import torch
from transformers import CLIPTextConfig, CLIPTextModel, CLIPTextModelWithProjection, CLIPTokenizer
from diffusers import (
AutoencoderKL,
DiffusionPipeline,
EulerDiscreteScheduler,
... | 28 | 1 |
'''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/license... | 28 |
'''simple docstring'''
import warnings
from transformers import AutoTokenizer
from transformers.utils import is_torch_available
from transformers.utils.generic import ExplicitEnum
from ...processing_utils import ProcessorMixin
if is_torch_available():
import torch
class... | 28 | 1 |
'''simple docstring'''
UpperCamelCase_ = [
"Audio",
"Array2D",
"Array3D",
"Array4D",
"Array5D",
"ClassLabel",
"Features",
"Sequence",
"Value",
"Image",
"Translation",
"TranslationVariableLanguages",
]
from .audio import Audio
from .f... | 28 |
'''simple docstring'''
import argparse
import numpy as np
import torch
from transformers import SpeechTaHifiGan, SpeechTaHifiGanConfig, logging
logging.set_verbosity_info()
UpperCamelCase_ = logging.get_logger("transformers.models.speecht5")
def lowercase__( __UpperCame... | 28 | 1 |
'''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, Sch... | 28 |
'''simple docstring'''
from typing import Any
class _a :
'''simple docstring'''
def __init__( self, A ):
'''simple docstring'''
SCREAMING_SNAKE_CASE : str = ... | 28 | 1 |
'''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_comman... | 28 |
'''simple docstring'''
import json
import pathlib
import unittest
import numpy as np
from transformers.testing_utils import require_torch, require_vision, slow
from transformers.utils import is_torch_available, is_vision_available
from ...test_image_processing_common import ImageProcessingS... | 28 | 1 |
'''simple docstring'''
from ...configuration_utils import PretrainedConfig
from ...utils import logging
UpperCamelCase_ = logging.get_logger(__name__)
UpperCamelCase_ = {
"studio-ousia/luke-base": "https://huggingface.co/studio-ousia/luke-base/resolve/main/config.json",
... | 28 |
'''simple docstring'''
from typing import List, Optional, TypeVar
from .arrow_dataset import Dataset, _concatenate_map_style_datasets, _interleave_map_style_datasets
from .dataset_dict import DatasetDict, IterableDatasetDict
from .info import DatasetInfo
from .iterable_dataset import IterableData... | 28 | 1 |
'''simple docstring'''
from ..utils import DummyObject, requires_backends
class _a ( metaclass=SCREAMING_SNAKE_CASE ):
'''simple docstring'''
A : List[str] = ['''flax''']
def __init__( self, ... | 28 |
'''simple docstring'''
import inspect
import unittest
from transformers import MobileViTConfig
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_configura... | 28 | 1 |
'''simple docstring'''
import os
from collections import deque
import torch
from torch.utils.data import Dataset
class _a ( SCREAMING_SNAKE_CASE ):
'''simple docstring'''
def __init__( self, A="", A="train" ):
... | 28 |
'''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_distilbert import DistilBertTokenizer
UpperCamelCase_ = logg... | 28 | 1 |
'''simple docstring'''
import unittest
from transformers.models.xlm_prophetnet.tokenization_xlm_prophetnet import SPIECE_UNDERLINE, XLMProphetNetTokenizer
from transformers.testing_utils import get_tests_dir, require_sentencepiece, slow
from transformers.utils import cached_property
from ...tes... | 28 |
'''simple docstring'''
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 AutoImageProcessor, ViTImageProcessor
from transformer... | 28 | 1 |
'''simple docstring'''
import argparse
import torch
from transformers import BertForMaskedLM
if __name__ == "__main__":
UpperCamelCase_ = argparse.ArgumentParser(
description=(
"Extraction some layers of the full BertForMaskedLM or RObertaForMaskedLM f... | 28 |
'''simple docstring'''
class _a :
'''simple docstring'''
def __init__( self, A ):
'''simple docstring'''
SCREAMING_SNAKE_CASE : Tuple = val
SCREAMING_SNA... | 28 | 1 |
'''simple docstring'''
from __future__ import annotations
from typing import Any
class _a :
'''simple docstring'''
def __init__( self, A = 6 ):
'''simple docstring'''
SCRE... | 28 |
'''simple docstring'''
import inspect
import warnings
from typing import Any, Dict, Optional, Union
from packaging import version
def lowercase__( *__UpperCamelCase: Union[str, Any] ,__UpperCamelCase: Optional[Union[Dict, Any]] = None ,__UpperCamelCase: Dict=True... | 28 | 1 |
'''simple docstring'''
import argparse
from collections import defaultdict
def lowercase__( __UpperCamelCase: Union[str, Any] ,__UpperCamelCase: List[str] ,__UpperCamelCase: Tuple ,__UpperCamelCase: str ,__UpperCamelCase: Optional[Any] ):
... | 28 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tf_available,
is_tokenizers_available,
is_torch_available,
)
UpperCamelCase_ = {
"configuration_roformer":... | 28 | 1 |
'''simple docstring'''
from typing import List, Optional, Tuple, Union
import torch
from torch import nn
from torch.nn import CrossEntropyLoss
from ... import AutoBackbone
from ...modeling_outputs import SemanticSegmenterOutput
from ...modeling_utils import PreTrainedModel
from ...utils impo... | 28 |
'''simple docstring'''
def lowercase__( __UpperCamelCase: int ):
"""simple docstring"""
if not isinstance(__UpperCamelCase ,__UpperCamelCase ):
raise TypeError('Input value must be an \'int\' type' )
SCREAMING_SNAKE_CASE : i... | 28 | 1 |
'''simple docstring'''
import unittest
from transformers import is_vision_available
from transformers.pipelines import pipeline
from transformers.testing_utils import (
is_pipeline_test,
nested_simplify,
require_tf,
require_torch,
require_vision,
slow,
)
from .tes... | 28 |
'''simple docstring'''
from typing import Dict
from .base import GenericTensor, Pipeline
class _a ( SCREAMING_SNAKE_CASE ):
'''simple docstring'''
def UpperCamelCase_ ( self, A=None, A=None, A=None, ... | 28 | 1 |
'''simple docstring'''
import copy
import os
from typing import Union
from ...configuration_utils import PretrainedConfig
from ...utils import logging
UpperCamelCase_ = logging.get_logger(__name__)
UpperCamelCase_ = {
"BridgeTower/bridgetower-base": "https://huggingface... | 28 |
'''simple docstring'''
from __future__ import annotations
import queue
class _a :
'''simple docstring'''
def __init__( self, A ):
'''simple docstring'''
SCREAMING_SNAKE_CA... | 28 | 1 |
'''simple docstring'''
import itertools
import random
import unittest
import numpy as np
from transformers import BatchFeature, SpeechTaFeatureExtractor
from transformers.testing_utils import require_torch
from transformers.utils.import_utils import is_torch_available
from ...test_sequence... | 28 |
'''simple docstring'''
import os
from glob import glob
import imageio
import torch
import torchvision
import wandb
from img_processing import custom_to_pil, loop_post_process, preprocess, preprocess_vqgan
from loaders import load_vqgan
from PIL import Image
from torch import nn
from trans... | 28 | 1 |
'''simple docstring'''
import unittest
from transformers import 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_com... | 28 |
'''simple docstring'''
import os
from typing import Any, Callable, Dict, List, Optional, Tuple, Union
import torch
from torch import nn
from ...models.controlnet import ControlNetModel, ControlNetOutput
from ...models.modeling_utils import ModelMixin
from ...utils import logging
UpperCam... | 28 | 1 |
'''simple docstring'''
import json
import os
import re
import shutil
import tempfile
import unittest
from typing import Tuple
from transformers import AddedToken, BatchEncoding, ByTaTokenizer
from transformers.utils import cached_property, is_tf_available, is_torch_available
from ...test_t... | 28 |
'''simple docstring'''
from math import ceil
from typing import List, Optional, Union
import numpy as np
from ...audio_utils import mel_filter_bank, spectrogram, window_function
from ...feature_extraction_sequence_utils import BatchFeature, SequenceFeatureExtractor
from ...utils import TensorT... | 28 | 1 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_torch_available,
)
UpperCamelCase_ = {
"configuration_encodec": [
"ENCODEC_PRETRAINED_CONFIG_ARCHIVE_MAP",
"EncodecConfig"... | 28 |
'''simple docstring'''
from collections import defaultdict
from graphs.minimum_spanning_tree_prims import prisms_algorithm as mst
def lowercase__( ):
"""simple docstring"""
SCREAMING_SNAKE_CASE , SCREAMING_SNAKE_CASE : str = 9, 14 ... | 28 | 1 |
'''simple docstring'''
UpperCamelCase_ = range(2, 2_0 + 1)
UpperCamelCase_ = [1_0**k for k in range(ks[-1] + 1)]
UpperCamelCase_ = {}
def lowercase__( __UpperCamelCase: Optional[Any] ,__UpperCamelCase: List[Any] ,__UpperCamelCase: Optional[Any] ... | 28 |
'''simple docstring'''
import gc
import random
import tempfile
import unittest
import numpy as np
import torch
from PIL import Image
from transformers import CLIPTextConfig, CLIPTextModel, CLIPTokenizer
from diffusers import (
AutoencoderKL,
DDIMInverseScheduler,
DDIMSchedule... | 28 | 1 |
'''simple docstring'''
from datasets.utils.patching import _PatchedModuleObj, patch_submodule
from . import _test_patching
def lowercase__( ):
"""simple docstring"""
import os as original_os
from os import path as original_path
from os import re... | 28 |
'''simple docstring'''
def lowercase__( __UpperCamelCase: int = 1_00_00_00 ):
"""simple docstring"""
SCREAMING_SNAKE_CASE : Tuple = [i - 1 for i in range(limit + 1 )]
for i in range(2 ,limit + 1 ):
if phi[i] == ... | 28 | 1 |
'''simple docstring'''
import tempfile
import torch
from diffusers import IPNDMScheduler
from .test_schedulers import SchedulerCommonTest
class _a ( SCREAMING_SNAKE_CASE ):
'''simple docstring'''
A : Any = (IPND... | 28 |
'''simple docstring'''
import itertools
import json
import os
import unittest
from transformers import AddedToken, LongformerTokenizer, LongformerTokenizerFast
from transformers.models.longformer.tokenization_longformer import VOCAB_FILES_NAMES
from transformers.testing_utils import require_tok... | 28 | 1 |
'''simple docstring'''
import json
import os
import tempfile
import unittest
import numpy as np
from datasets import load_dataset
from transformers.testing_utils import require_torch, require_vision, slow
from transformers.utils import is_torch_available, is_vision_available
from ...test_... | 28 |
'''simple docstring'''
import gc
import random
import unittest
import numpy as np
import torch
from transformers import CLIPTextConfig, CLIPTextModel, CLIPTextModelWithProjection, CLIPTokenizer
from diffusers import (
AutoencoderKL,
DiffusionPipeline,
EulerDiscreteScheduler,
... | 28 | 1 |
'''simple docstring'''
from typing import Dict
from .base import GenericTensor, Pipeline
class _a ( SCREAMING_SNAKE_CASE ):
'''simple docstring'''
def UpperCamelCase_ ( self, A=None, A=None, A=None, ... | 28 |
'''simple docstring'''
import warnings
from transformers import AutoTokenizer
from transformers.utils import is_torch_available
from transformers.utils.generic import ExplicitEnum
from ...processing_utils import ProcessorMixin
if is_torch_available():
import torch
class... | 28 | 1 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tokenizers_available, is_torch_available
UpperCamelCase_ = {
"configuration_bloom": ["BLOOM_PRETRAINED_CONFIG_ARCHIVE_MAP", "BloomConfig", "BloomOnnxConfig"],... | 28 |
'''simple docstring'''
import argparse
import numpy as np
import torch
from transformers import SpeechTaHifiGan, SpeechTaHifiGanConfig, logging
logging.set_verbosity_info()
UpperCamelCase_ = logging.get_logger("transformers.models.speecht5")
def lowercase__( __UpperCame... | 28 | 1 |
'''simple docstring'''
import argparse
import datetime
import json
import time
import warnings
from logging import getLogger
from pathlib import Path
from typing import Dict, List
import torch
from tqdm import tqdm
from transformers import AutoModelForSeqaSeqLM, AutoTokenizer
from utils ... | 28 |
'''simple docstring'''
from typing import Any
class _a :
'''simple docstring'''
def __init__( self, A ):
'''simple docstring'''
SCREAMING_SNAKE_CASE : str = ... | 28 | 1 |
'''simple docstring'''
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`")
| 28 |
'''simple docstring'''
import json
import pathlib
import unittest
import numpy as np
from transformers.testing_utils import require_torch, require_vision, slow
from transformers.utils import is_torch_available, is_vision_available
from ...test_image_processing_common import ImageProcessingS... | 28 | 1 |
'''simple docstring'''
import inspect
import unittest
from transformers import MobileViTConfig
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_configura... | 28 |
'''simple docstring'''
from typing import List, Optional, TypeVar
from .arrow_dataset import Dataset, _concatenate_map_style_datasets, _interleave_map_style_datasets
from .dataset_dict import DatasetDict, IterableDatasetDict
from .info import DatasetInfo
from .iterable_dataset import IterableData... | 28 | 1 |
'''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_distilbert import DistilBertTokenizer
UpperCamelCase_ = logg... | 28 |
'''simple docstring'''
import inspect
import unittest
from transformers import MobileViTConfig
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_configura... | 28 | 1 |
'''simple docstring'''
from collections import defaultdict
from graphs.minimum_spanning_tree_prims import prisms_algorithm as mst
def lowercase__( ):
"""simple docstring"""
SCREAMING_SNAKE_CASE , SCREAMING_SNAKE_CASE : str = 9, 14 ... | 28 |
'''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_distilbert import DistilBertTokenizer
UpperCamelCase_ = logg... | 28 | 1 |
'''simple docstring'''
import argparse
import collections
import json
from pathlib import Path
import requests
import torch
import yaml
from huggingface_hub import hf_hub_download
from PIL import Image
from transformers import (
MobileViTImageProcessor,
MobileViTVaConfig,
Mo... | 28 |
'''simple docstring'''
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 AutoImageProcessor, ViTImageProcessor
from transformer... | 28 | 1 |
'''simple docstring'''
import math
class _a :
'''simple docstring'''
def UpperCamelCase_ ( self, A, A ):
'''simple docstring'''
SCREAMING_SNAKE_CASE : ... | 28 |
'''simple docstring'''
class _a :
'''simple docstring'''
def __init__( self, A ):
'''simple docstring'''
SCREAMING_SNAKE_CASE : Tuple = val
SCREAMING_SNA... | 28 | 1 |
'''simple docstring'''
import unittest
import numpy as np
from transformers.testing_utils import require_torch, require_vision
from transformers.utils import is_torch_available, is_vision_available
from ...test_image_processing_common import ImageProcessingSavingTestMixin
if is_torch_ava... | 28 |
'''simple docstring'''
import inspect
import warnings
from typing import Any, Dict, Optional, Union
from packaging import version
def lowercase__( *__UpperCamelCase: Union[str, Any] ,__UpperCamelCase: Optional[Union[Dict, Any]] = None ,__UpperCamelCase: Dict=True... | 28 | 1 |
'''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 _a :
'''simple docstring'''
A :... | 28 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tf_available,
is_tokenizers_available,
is_torch_available,
)
UpperCamelCase_ = {
"configuration_roformer":... | 28 | 1 |
'''simple docstring'''
import inspect
import unittest
class _a ( unittest.TestCase ):
'''simple docstring'''
def UpperCamelCase_ ( self ):
'''simple docstring'''
tr... | 28 |
'''simple docstring'''
def lowercase__( __UpperCamelCase: int ):
"""simple docstring"""
if not isinstance(__UpperCamelCase ,__UpperCamelCase ):
raise TypeError('Input value must be an \'int\' type' )
SCREAMING_SNAKE_CASE : i... | 28 | 1 |
'''simple docstring'''
def lowercase__( __UpperCamelCase: str ,__UpperCamelCase: str ):
"""simple docstring"""
def get_matched_characters(__UpperCamelCase: str ,__UpperCamelCase: str ) -> str:
SCREAMING_SNAKE_CASE : Opt... | 28 |
'''simple docstring'''
from typing import Dict
from .base import GenericTensor, Pipeline
class _a ( SCREAMING_SNAKE_CASE ):
'''simple docstring'''
def UpperCamelCase_ ( self, A=None, A=None, A=None, ... | 28 | 1 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tf_available,
is_tokenizers_available,
is_torch_available,
)
UpperCamelCase_ = {"configuration_opt": ["OPT_PRET... | 28 |
'''simple docstring'''
from __future__ import annotations
import queue
class _a :
'''simple docstring'''
def __init__( self, A ):
'''simple docstring'''
SCREAMING_SNAKE_CA... | 28 | 1 |
'''simple docstring'''
import argparse
import math
import traceback
import dateutil.parser as date_parser
import requests
def lowercase__( __UpperCamelCase: Optional[int] ):
"""simple docstring"""
SCREAMING_SNAKE_CASE : Optional[int] ... | 28 |
'''simple docstring'''
import os
from glob import glob
import imageio
import torch
import torchvision
import wandb
from img_processing import custom_to_pil, loop_post_process, preprocess, preprocess_vqgan
from loaders import load_vqgan
from PIL import Image
from torch import nn
from trans... | 28 | 1 |
'''simple docstring'''
import inspect
import warnings
from typing import Any, Dict, Optional, Union
from packaging import version
def lowercase__( *__UpperCamelCase: Union[str, Any] ,__UpperCamelCase: Optional[Union[Dict, Any]] = None ,__UpperCamelCase: Dict=True... | 28 |
'''simple docstring'''
import os
from typing import Any, Callable, Dict, List, Optional, Tuple, Union
import torch
from torch import nn
from ...models.controlnet import ControlNetModel, ControlNetOutput
from ...models.modeling_utils import ModelMixin
from ...utils import logging
UpperCam... | 28 | 1 |
'''simple docstring'''
from dataclasses import dataclass, field
from typing import Optional
@dataclass
class _a :
'''simple docstring'''
A : Optional[str] = field(
default='''codeparrot/codeparrot''' , m... | 28 |
'''simple docstring'''
from math import ceil
from typing import List, Optional, Union
import numpy as np
from ...audio_utils import mel_filter_bank, spectrogram, window_function
from ...feature_extraction_sequence_utils import BatchFeature, SequenceFeatureExtractor
from ...utils import TensorT... | 28 | 1 |
'''simple docstring'''
import numpy as np
def lowercase__( __UpperCamelCase: np.array ):
"""simple docstring"""
return 1 / (1 + np.exp(-vector ))
if __name__ == "__main__":
import doctest
doctest.testmod()
| 28 |
'''simple docstring'''
from collections import defaultdict
from graphs.minimum_spanning_tree_prims import prisms_algorithm as mst
def lowercase__( ):
"""simple docstring"""
SCREAMING_SNAKE_CASE , SCREAMING_SNAKE_CASE : str = 9, 14 ... | 28 | 1 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tf_available,
is_tokenizers_available,
is_torch_available,
)
UpperCamelCase_ = {
"configuration_roformer":... | 28 |
'''simple docstring'''
import gc
import random
import tempfile
import unittest
import numpy as np
import torch
from PIL import Image
from transformers import CLIPTextConfig, CLIPTextModel, CLIPTokenizer
from diffusers import (
AutoencoderKL,
DDIMInverseScheduler,
DDIMSchedule... | 28 | 1 |
'''simple docstring'''
from collections import deque
def lowercase__( __UpperCamelCase: List[Any] ):
"""simple docstring"""
SCREAMING_SNAKE_CASE : Tuple = len(__UpperCamelCase )
SCREAMING_SNAKE_CASE : str = ... | 28 |
'''simple docstring'''
def lowercase__( __UpperCamelCase: int = 1_00_00_00 ):
"""simple docstring"""
SCREAMING_SNAKE_CASE : Tuple = [i - 1 for i in range(limit + 1 )]
for i in range(2 ,limit + 1 ):
if phi[i] == ... | 28 | 1 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ....utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
UpperCamelCase_ = {
"configuration_trajectory_transformer": [
"TRAJECTORY_TRANSFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP",
"Traj... | 28 |
'''simple docstring'''
import itertools
import json
import os
import unittest
from transformers import AddedToken, LongformerTokenizer, LongformerTokenizerFast
from transformers.models.longformer.tokenization_longformer import VOCAB_FILES_NAMES
from transformers.testing_utils import require_tok... | 28 | 1 |
'''simple docstring'''
import os
from typing import Any, Callable, Dict, List, Optional, Tuple, Union
import torch
from torch import nn
from ...models.controlnet import ControlNetModel, ControlNetOutput
from ...models.modeling_utils import ModelMixin
from ...utils import logging
UpperCam... | 28 |
'''simple docstring'''
import gc
import random
import unittest
import numpy as np
import torch
from transformers import CLIPTextConfig, CLIPTextModel, CLIPTextModelWithProjection, CLIPTokenizer
from diffusers import (
AutoencoderKL,
DiffusionPipeline,
EulerDiscreteScheduler,
... | 28 | 1 |
'''simple docstring'''
import itertools
import json
import linecache
import os
import pickle
import re
import socket
import string
from collections import Counter
from logging import getLogger
from pathlib import Path
from typing import Callable, Dict, Iterable, List
import git
import to... | 28 |
'''simple docstring'''
import warnings
from transformers import AutoTokenizer
from transformers.utils import is_torch_available
from transformers.utils.generic import ExplicitEnum
from ...processing_utils import ProcessorMixin
if is_torch_available():
import torch
class... | 28 | 1 |
'''simple docstring'''
import unittest
from knapsack import greedy_knapsack as kp
class _a ( unittest.TestCase ):
'''simple docstring'''
def UpperCamelCase_ ( self ):
'''simple docstring'''
... | 28 |
'''simple docstring'''
import argparse
import numpy as np
import torch
from transformers import SpeechTaHifiGan, SpeechTaHifiGanConfig, logging
logging.set_verbosity_info()
UpperCamelCase_ = logging.get_logger("transformers.models.speecht5")
def lowercase__( __UpperCame... | 28 | 1 |
'''simple docstring'''
import unittest
import numpy as np
from transformers.testing_utils import require_torch, require_vision
from transformers.utils import is_torch_available, is_vision_available
from ...test_image_processing_common import ImageProcessingSavingTestMixin, prepare_video_input... | 28 |
'''simple docstring'''
from typing import Any
class _a :
'''simple docstring'''
def __init__( self, A ):
'''simple docstring'''
SCREAMING_SNAKE_CASE : str = ... | 28 | 1 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import _LazyModule
UpperCamelCase_ = {"tokenization_wav2vec2_phoneme": ["Wav2Vec2PhonemeCTCTokenizer"]}
if TYPE_CHECKING:
from .tokenization_wavaveca_phoneme import WavaVecaPhonemeCTCTokenizer
else:
... | 28 |
'''simple docstring'''
import json
import pathlib
import unittest
import numpy as np
from transformers.testing_utils import require_torch, require_vision, slow
from transformers.utils import is_torch_available, is_vision_available
from ...test_image_processing_common import ImageProcessingS... | 28 | 1 |
'''simple docstring'''
import logging
import os
import quant_trainer
import torch
from torch.utils.data import DataLoader
from transformers import Trainer, is_torch_tpu_available
from transformers.trainer_utils import PredictionOutput
UpperCamelCase_ = logging.getLogger(__name__)
... | 28 |
'''simple docstring'''
from typing import List, Optional, TypeVar
from .arrow_dataset import Dataset, _concatenate_map_style_datasets, _interleave_map_style_datasets
from .dataset_dict import DatasetDict, IterableDatasetDict
from .info import DatasetInfo
from .iterable_dataset import IterableData... | 28 | 1 |
'''simple docstring'''
from collections.abc import Callable
def lowercase__( __UpperCamelCase: Callable[[float], float] ,__UpperCamelCase: float ,__UpperCamelCase: float ):
"""simple docstring"""
SCREAMING_SNAKE_CASE : float ... | 28 |
'''simple docstring'''
import inspect
import unittest
from transformers import MobileViTConfig
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_configura... | 28 | 1 |
'''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/li... | 28 |
'''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_distilbert import DistilBertTokenizer
UpperCamelCase_ = logg... | 28 | 1 |
'''simple docstring'''
from __future__ import annotations
class _a :
'''simple docstring'''
def __init__( self, A = 0 ):
'''simple docstring'''
SCREAMING_SNAKE_CASE : ... | 28 |
'''simple docstring'''
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 AutoImageProcessor, ViTImageProcessor
from transformer... | 28 | 1 |
'''simple docstring'''
import argparse
import glob
import logging
import os
import time
from argparse import Namespace
import numpy as np
import torch
from lightning_base import BaseTransformer, add_generic_args, generic_train
from torch.utils.data import DataLoader, TensorDataset
from tr... | 28 |
'''simple docstring'''
class _a :
'''simple docstring'''
def __init__( self, A ):
'''simple docstring'''
SCREAMING_SNAKE_CASE : Tuple = val
SCREAMING_SNA... | 28 | 1 |
'''simple docstring'''
from __future__ import annotations
import queue
class _a :
'''simple docstring'''
def __init__( self, A ):
'''simple docstring'''
SCREAMING_SNAKE_CA... | 28 |
'''simple docstring'''
import inspect
import warnings
from typing import Any, Dict, Optional, Union
from packaging import version
def lowercase__( *__UpperCamelCase: Union[str, Any] ,__UpperCamelCase: Optional[Union[Dict, Any]] = None ,__UpperCamelCase: Dict=True... | 28 | 1 |
'''simple docstring'''
import json
import os
import tempfile
import datasets
from utils import generate_example_dataset, get_duration
UpperCamelCase_ = 5_0_0_0_0
UpperCamelCase_ = 5_0_0_0
UpperCamelCase_ , UpperCamelCase_ = os.path.split(__file__)
UpperCamelCase_... | 28 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tf_available,
is_tokenizers_available,
is_torch_available,
)
UpperCamelCase_ = {
"configuration_roformer":... | 28 | 1 |
'''simple docstring'''
# coding=utf-8
# Copyright 2020 The HuggingFace Inc. team.
#
# 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/license... | 28 |
'''simple docstring'''
def lowercase__( __UpperCamelCase: int ):
"""simple docstring"""
if not isinstance(__UpperCamelCase ,__UpperCamelCase ):
raise TypeError('Input value must be an \'int\' type' )
SCREAMING_SNAKE_CASE : i... | 28 | 1 |
'''simple docstring'''
from random import randint, random
def lowercase__( __UpperCamelCase: int ,__UpperCamelCase: int ,__UpperCamelCase: int ,__UpperCamelCase: bool = False ,__UpperCamelCase: bool = False ,__UpperCamelCase: int = 5 ,)... | 28 |
'''simple docstring'''
from typing import Dict
from .base import GenericTensor, Pipeline
class _a ( SCREAMING_SNAKE_CASE ):
'''simple docstring'''
def UpperCamelCase_ ( self, A=None, A=None, A=None, ... | 28 | 1 |
'''simple docstring'''
def lowercase__( __UpperCamelCase: int = 10_00 ):
"""simple docstring"""
return sum(e for e in range(3 ,__UpperCamelCase ) if e % 3 == 0 or e % 5 == 0 )
if __name__ == "__main__":
print(F"""{solution() = }""")
| 28 |
'''simple docstring'''
from __future__ import annotations
import queue
class _a :
'''simple docstring'''
def __init__( self, A ):
'''simple docstring'''
SCREAMING_SNAKE_CA... | 28 | 1 |
'''simple docstring'''
from ...processing_utils import ProcessorMixin
class _a ( SCREAMING_SNAKE_CASE ):
'''simple docstring'''
A : Optional[Any] = ['''image_processor''', '''feature_extractor''']
A : Any... | 28 |
'''simple docstring'''
import os
from glob import glob
import imageio
import torch
import torchvision
import wandb
from img_processing import custom_to_pil, loop_post_process, preprocess, preprocess_vqgan
from loaders import load_vqgan
from PIL import Image
from torch import nn
from trans... | 28 | 1 |
'''simple docstring'''
import logging
import os
from dataclasses import dataclass, field
from typing import Dict, Optional
import numpy as np
from utils_multiple_choice import MultipleChoiceDataset, Split, processors
import transformers
from transformers import (
AutoConfig,
AutoMo... | 28 |
'''simple docstring'''
import os
from typing import Any, Callable, Dict, List, Optional, Tuple, Union
import torch
from torch import nn
from ...models.controlnet import ControlNetModel, ControlNetOutput
from ...models.modeling_utils import ModelMixin
from ...utils import logging
UpperCam... | 28 | 1 |
'''simple docstring'''
UpperCamelCase_ = [
"DownloadConfig",
"DownloadManager",
"DownloadMode",
"StreamingDownloadManager",
]
from .download_config import DownloadConfig
from .download_manager import DownloadManager, DownloadMode
from .streaming_download_manager import ... | 28 |
'''simple docstring'''
from math import ceil
from typing import List, Optional, Union
import numpy as np
from ...audio_utils import mel_filter_bank, spectrogram, window_function
from ...feature_extraction_sequence_utils import BatchFeature, SequenceFeatureExtractor
from ...utils import TensorT... | 28 | 1 |
'''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 AutoModel... | 28 |
'''simple docstring'''
from collections import defaultdict
from graphs.minimum_spanning_tree_prims import prisms_algorithm as mst
def lowercase__( ):
"""simple docstring"""
SCREAMING_SNAKE_CASE , SCREAMING_SNAKE_CASE : str = 9, 14 ... | 28 | 1 |
'''simple docstring'''
import inspect
import unittest
from transformers import ConvNextVaConfig
from transformers.models.auto import get_values
from transformers.models.auto.modeling_auto import MODEL_FOR_BACKBONE_MAPPING_NAMES, MODEL_MAPPING_NAMES
from transformers.testing_utils import require_... | 28 |
'''simple docstring'''
import gc
import random
import tempfile
import unittest
import numpy as np
import torch
from PIL import Image
from transformers import CLIPTextConfig, CLIPTextModel, CLIPTokenizer
from diffusers import (
AutoencoderKL,
DDIMInverseScheduler,
DDIMSchedule... | 28 | 1 |
'''simple docstring'''
import sys
from collections import defaultdict
class _a :
'''simple docstring'''
def __init__( self ):
'''simple docstring'''
SCREAMING_SNAKE_CASE : ... | 28 |
'''simple docstring'''
def lowercase__( __UpperCamelCase: int = 1_00_00_00 ):
"""simple docstring"""
SCREAMING_SNAKE_CASE : Tuple = [i - 1 for i in range(limit + 1 )]
for i in range(2 ,limit + 1 ):
if phi[i] == ... | 28 | 1 |
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