code stringlengths 82 53.2k | code_codestyle int64 0 721 | style_context stringlengths 91 41.9k | style_context_codestyle int64 0 699 | label int64 0 1 |
|---|---|---|---|---|
'''simple docstring'''
import unittest
from transformers.testing_utils import CaptureStdout
from transformers.tools.python_interpreter import evaluate
def lowercase__( __UpperCamelCase: Tuple ):
"""simple docstring"""
return x + 2
class ... | 28 |
from ..utils import (
OptionalDependencyNotAvailable,
is_flax_available,
is_scipy_available,
is_torch_available,
is_torchsde_available,
)
try:
if not is_torch_available():
raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
from ..utils.dummy_pt_objects impo... | 100 | 0 |
from collections.abc import Callable
from math import pi, sqrt
from random import uniform
from statistics import mean
def UpperCAmelCase__ ( lowerCamelCase_ : int ):
def is_in_circle(lowerCamelCase_ : float , lowerCamelCase_ : float ) -> b... | 707 |
def UpperCAmelCase__ ( lowerCamelCase_ : int = 3 , lowerCamelCase_ : int = 7 , lowerCamelCase_ : int = 1_0_0_0_0_0_0 ):
__a : Optional[int] = 0
__a : Any = 1
for current_denominator in range(1 , limit + 1 ):... | 577 | 0 |
"""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,... | 96 |
'''simple docstring'''
__A : List[Any] = {
0: '0',
1: '1',
2: '2',
3: '3',
4: '4',
5: '5',
6: '6',
7: '7',
8: '8',
9: '9',
10: 'a',
11: 'b',
12: 'c',
13: 'd',
14: 'e',
15: 'f',
}
def UpperCAmelCase ( lowerCamelCase_ :float ... | 334 | 0 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_sentencepiece_available,
is_tokenizers_available,
is_torch_available,
)
__A ={}
try:
if not is_sentencepiece_available():
raise Optiona... | 113 |
'''simple docstring'''
import importlib
import os
from dataclasses import dataclass
from enum import Enum
from typing import Any, Dict, Optional, Union
import torch
from ..utils import BaseOutput
__A ='scheduler_config.json'
class _snake_case ( a__ ):
lowerCAmelCase ... | 113 | 1 |
"""simple docstring"""
import gc
import random
import unittest
import torch
from diffusers import (
IFImgaImgPipeline,
IFImgaImgSuperResolutionPipeline,
IFInpaintingPipeline,
IFInpaintingSuperResolutionPipeline,
IFPipeline,
IFSuperResolutionPipeline,
)
from diffusers.m... | 361 |
"""simple docstring"""
# Lint as: python3
import os
import re
import urllib.parse
from pathlib import Path
from typing import Callable, List, Optional, Union
from zipfile import ZipFile
from ..utils.file_utils import cached_path, hf_github_url
from ..utils.logging import get_logger
from ..utils.ve... | 361 | 1 |
'''simple docstring'''
lowerCAmelCase_ : Union[str, Any] = tuple[float, float, float]
lowerCAmelCase_ : List[Any] = tuple[float, float, float]
def __a ( __lowerCamelCase : Pointad , __lowerCamelCase : Pointad ) -> Vectorad:
'''simple docstring'''
lowercas... | 461 | '''simple docstring'''
def __a ( __lowerCamelCase : int = 200 ) -> int:
'''simple docstring'''
lowercase_ = [1, 2, 5, 10, 20, 50, 100, 200]
lowercase_ = [0] * (pence + 1)
lowercase_ = 1 # base case: 1 way to make 0 pence
for coin in coins:
... | 461 | 1 |
import argparse
from torch import nn
# transformers_old should correspond to branch `save_old_prophetnet_model_structure` here
# original prophetnet_checkpoints are saved under `patrickvonplaten/..._old` respectively
from transformers_old.modeling_prophetnet import (
ProphetNetForConditionalGeneration as ProphetN... | 64 |
"""simple docstring"""
import argparse
import requests
import torch
from PIL import Image
from torchvision.transforms import Compose, Normalize, Resize, ToTensor
from transformers import SwinaSRConfig, SwinaSRForImageSuperResolution, SwinaSRImageProcessor
def _SCREAMING_SNAKE_CASE (_UpperCAmelCase : ... | 4 | 0 |
"""simple docstring"""
import argparse
import gdown
import numpy as np
import torch
from huggingface_hub import hf_hub_download
from transformers import (
CLIPTokenizer,
CLIPTokenizerFast,
VideoMAEImageProcessor,
XCLIPConfig,
XCLIPModel,
XCLIPProcessor,
XCL... | 21 |
"""simple docstring"""
# Copyright (c) 2021-, NVIDIA CORPORATION. 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/... | 21 | 1 |
'''simple docstring'''
# NOTE: This file is deprecated and will be removed in a future version.
# It only exists so that temporarely `from diffusers.pipelines import DiffusionPipeline` works
from ...utils import deprecate
from ..controlnet.multicontrolnet import MultiControlNetModel # noqa: F401
from ..contr... | 526 |
'''simple docstring'''
# Copyright 2023 The HuggingFace Inc. team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENS... | 526 | 1 |
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 (
SwiftFormerConfig,
SwiftFormerForImageClassification,
ViTImageProcessor,
)
from transformers.utils import logging
logging.s... | 707 |
import inspect
import unittest
from transformers import RegNetConfig, is_flax_available
from transformers.testing_utils import require_flax, slow
from transformers.utils import cached_property, is_vision_available
from ...test_configuration_common import ConfigTester
from ...test_modeling_flax_common import Fla... | 188 | 0 |
import math
def UpperCamelCase ( ):
'''simple docstring'''
A_ : Optional[Any] = input('Enter message: ' )
A_ : List[Any] = int(input(f'''Enter key [2-{len(lowercase_ ) - 1}]: ''' ) )
A_ : Tuple = input('Encryption... | 558 |
'''simple docstring'''
import math
from typing import Optional
import numpy as np
from ...configuration_utils import PretrainedConfig
from ...utils import logging
_UpperCAmelCase : int = logging.get_logger(__name__)
_UpperCAmelCase : Optional[Any] = {
'''facebook/encodec_24khz''': '''https://huggingf... | 72 | 0 |
"""simple docstring"""
def lowerCamelCase_( ) -> list[list[int]]:
'''simple docstring'''
return [list(range(1000 - i , -1000 - i , -1 ) ) for i in range(1000 )]
_lowerCAmelCase : str = generate_large_matrix()
_lowerCAmelCase : Union[str, ... | 708 |
"""simple docstring"""
import json
import os
import unittest
from transformers import BatchEncoding, MvpTokenizer, MvpTokenizerFast
from transformers.models.roberta.tokenization_roberta import VOCAB_FILES_NAMES
from transformers.testing_utils import require_tokenizers, require_torch
from transformers.utils im... | 386 | 0 |
"""simple docstring"""
def A__ ( __lowerCamelCase ):
"""simple docstring"""
return " ".join(
''.join(word[::-1] ) if len(__lowerCamelCase ) > 4 else word for word in sentence.split() )
if __name__ == "__main__":
import doctest
doctest.testmod()
print(r... | 589 |
"""simple docstring"""
from typing import TYPE_CHECKING
# rely on isort to merge the imports
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
a__ : Any = {
"""configuration_informer""": [
"""INFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP""",
... | 589 | 1 |
'''simple docstring'''
from pathlib import Path
import fire
from tqdm import tqdm
def lowerCAmelCase ( UpperCamelCase__ : Tuple="ro" , UpperCamelCase__ : Any="en" , UpperCamelCase__ : Dict="wmt16" , UpperCamelCase__ : Dict=None ):
"""si... | 654 | '''simple docstring'''
import heapq
import sys
import numpy as np
__lowerCAmelCase : Any = tuple[int, int]
class A :
def __init__( self : Optional[int] ) -> int:
__UpperCAmelCase = []
__UpperCAmelCase ... | 654 | 1 |
def __SCREAMING_SNAKE_CASE ( UpperCamelCase__ ) -> list[list]:
'''simple docstring'''
UpperCAmelCase = current_set.copy()
for row_index, row in enumerate(UpperCamelCase__ ):
UpperCAmelCase = row[0]
for column_index, column in enume... | 130 |
import os
from shutil import copyfile
from typing import List, Optional, Tuple
from ...tokenization_utils import AddedToken
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import is_sentencepiece_available, logging
if is_sentencepiece_available():
from .tokenization_xlnet impor... | 130 | 1 |
'''simple docstring'''
import unittest
import numpy as np
from transformers import DistilBertConfig, is_flax_available
from transformers.testing_utils import require_flax, slow
from ...test_modeling_flax_common import FlaxModelTesterMixin, ids_tensor, random_attention_mask
if is_flax... | 338 |
'''simple docstring'''
import sys
import turtle
def _lowerCAmelCase ( __snake_case : tuple[float, float] , __snake_case : tuple[float, float] ) -> tuple[float, float]:
return (pa[0] + pa[0]) / 2, (pa[1] + pa[1]) / 2
def _lower... | 338 | 1 |
import argparse
import requests
import torch
# pip3 install salesforce-lavis
# I'm actually installing a slightly modified version: pip3 install git+https://github.com/nielsrogge/LAVIS.git@fix_lavis_float32 (there's also the fix_lavis branch)
# also note: to convert Vicuna checkpoints, we had to include /home/... | 183 |
import tempfile
import torch
from diffusers import IPNDMScheduler
from .test_schedulers import SchedulerCommonTest
class _UpperCAmelCase ( A__ ):
"""simple docstring"""
lowercase__ = (IPNDMScheduler,)
lowercase__ = (("""num_inference_steps""", 50),)
d... | 183 | 1 |
"""simple docstring"""
import tempfile
import numpy as np
import torch
from transformers import AutoTokenizer, TaEncoderModel
from diffusers import DDPMScheduler, UNetaDConditionModel
from diffusers.models.attention_processor import AttnAddedKVProcessor
from diffusers.pipelines.deepfloyd_if import IFWat... | 378 |
"""simple docstring"""
from collections import OrderedDict
from typing import Mapping
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
lowerCAmelCase_ : Tuple = logging.get_logger(__name__)
lowerCAmelCase_ : List[str]... | 378 | 1 |
'''simple docstring'''
def __a ( _UpperCamelCase: str , _UpperCamelCase: str ) -> bool:
"""simple docstring"""
_snake_case = len(_UpperCamelCase ) + 1
_snake_case = len(_UpperCamelCase ) + 1
# dp is a 2d matrix where dp[i][j] de... | 185 |
'''simple docstring'''
import itertools
import os
from collections import Counter, defaultdict
from concurrent.futures import ThreadPoolExecutor, as_completed
import numpy as np
import datasets
from .execute import check_correctness
UpperCamelCase_ : Dict = '''\
@misc{chen2021evaluating,
... | 185 | 1 |
'''simple docstring'''
from __future__ import annotations
import string
from itertools import cycle, product
from pathlib import Path
UpperCamelCase__ : str = (
string.ascii_letters + string.digits + string.punctuation + string.whitespace
)
UpperCamelCase__ : list[int] = [o... | 178 |
'''simple docstring'''
import warnings
from ...utils import logging
from .image_processing_deit import DeiTImageProcessor
UpperCamelCase__ : List[str] = logging.get_logger(__name__)
class _UpperCamelCase ( lowerCamelCase__ ):
'''simple docstring'''
def __init__... | 178 | 1 |
'''simple docstring'''
import json
import logging
import os
import sys
from time import time
from unittest.mock import patch
from transformers.testing_utils import TestCasePlus, require_torch_tpu
logging.basicConfig(level=logging.DEBUG)
lowercase_ : Any = logging.getLogger()
def SCRE... | 588 |
'''simple docstring'''
import unittest
import numpy as np
from transformers import BertConfig, is_flax_available
from transformers.testing_utils import require_flax, slow
from ...test_modeling_flax_common import FlaxModelTesterMixin, floats_tensor, ids_tensor, random_attention_mask
if is_flax_available():
... | 588 | 1 |
from __future__ import annotations
def lowerCAmelCase_ ( __UpperCAmelCase: list[int] , __UpperCAmelCase: int ) -> list[list[int]]:
UpperCamelCase__ : list[list[int]] = []
UpperCamelCase__ : list[int] = []
UpperCamelCase_... | 369 |
import unittest
from transformers import BigBirdConfig, is_flax_available
from transformers.testing_utils import require_flax, slow
from ...test_modeling_flax_common import FlaxModelTesterMixin, ids_tensor, random_attention_mask
if is_flax_available():
import jax
from transformers.models... | 369 | 1 |
import unittest
from transformers import PegasusConfig, PegasusTokenizer, is_flax_available
from transformers.testing_utils import require_flax, slow
from ...test_configuration_common import ConfigTester
from ...test_modeling_flax_common import FlaxModelTesterMixin, ids_tensor
if is_flax_available():
... | 345 |
from collections import OrderedDict
from typing import Mapping
from packaging import version
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
from ...utils.backbone_utils import BackboneConfigMixin, get_aligned_output_features_output_indices
_UpperCAm... | 362 | 0 |
'''simple docstring'''
import string
def _lowerCAmelCase( UpperCAmelCase_ : str ) -> str:
lowerCAmelCase__ = """"""
for i in sequence:
lowerCAmelCase__ = ord(UpperCAmelCase_ )
if 65 <= extract <= 90:
... | 211 |
'''simple docstring'''
import copy
from typing import Dict, Optional
from ...configuration_utils import PretrainedConfig
from ...utils import logging
from ..auto import CONFIG_MAPPING
from ..detr import DetrConfig
from ..swin import SwinConfig
_UpperCamelCase = {
"""faceboo... | 211 | 1 |
"""simple docstring"""
from typing import Any, Dict, Optional
import torch
import torch.nn.functional as F
from torch import nn
from ..utils import maybe_allow_in_graph
from .activations import get_activation
from .attention_processor import Attention
from .embeddings import CombinedTimestepLabelEmbeddings... | 674 |
"""simple docstring"""
import os
import re
import warnings
from shutil import copyfile
from typing import TYPE_CHECKING, Any, Dict, List, Optional, Tuple
import sentencepiece as spm
from ...tokenization_utils import PreTrainedTokenizer
if TYPE_CHECKING:
from ...tokenization_utils_base import TextInpu... | 674 | 1 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
UpperCAmelCase__ : Any = {
'configuration_bigbird_pegasus': [
'BIGBIRD_PEGASUS_PRETRAINED_CONFIG_ARCHIVE_MAP',
'BigBi... | 545 |
"""simple docstring"""
from math import pi, sqrt, tan
def lowercase_ ( _snake_case ):
if side_length < 0:
raise ValueError("""surface_area_cube() only accepts non-negative values""" )
return 6 * side_length**2
def lowercase_ ( _snake_case ,_snake_c... | 545 | 1 |
"""simple docstring"""
import contextlib
import os
import sqlitea
import pytest
from datasets import Dataset, Features, Value
from datasets.io.sql import SqlDatasetReader, SqlDatasetWriter
from ..utils import assert_arrow_memory_doesnt_increase, assert_arrow_memory_increases, require_sqlalchemy... | 602 |
"""simple docstring"""
from ...configuration_utils import PretrainedConfig
from ...utils import logging
__A : List[Any] = logging.get_logger(__name__)
__A : Optional[Any] = {
"google/vivit-b-16x2-kinetics400": (
"https://huggingface.co/google/vivit-b-16x2-kineti... | 602 | 1 |
"""simple docstring"""
import copy
from typing import Any, Dict, List, Optional, Union
import numpy as np
from ...audio_utils import mel_filter_bank, spectrogram, window_function
from ...feature_extraction_sequence_utils import SequenceFeatureExtractor
from ...feature_extraction_utils import BatchFeature
f... | 295 |
"""simple docstring"""
# Copyright 2023 The HuggingFace Inc. team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE... | 295 | 1 |
'''simple docstring'''
# Copyright 2022 The HuggingFace Team and The OpenBMB 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... | 150 |
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 IterableDataset, _concatenate_iterable_datasets, _i... | 569 | 0 |
"""simple docstring"""
import unittest
from transformers import DebertaConfig, is_torch_available
from transformers.testing_utils import require_sentencepiece, require_tokenizers, require_torch, slow, torch_device
from ...test_configuration_common import ConfigTester
from ...test_modeling_common import ModelTest... | 263 |
"""simple docstring"""
import collections.abc
from typing import Optional, Tuple, Union
import torch
import torch.utils.checkpoint
from torch import nn
from torch.nn import BCEWithLogitsLoss, CrossEntropyLoss, MSELoss
from ...activations import ACTaFN
from ...modeling_outputs import BaseModelOutputWithNoAttentio... | 263 | 1 |
"""simple docstring"""
class UpperCamelCase__ :
"""simple docstring"""
def __init__( self , SCREAMING_SNAKE_CASE__ = "" , SCREAMING_SNAKE_CASE__ = False ) -> None:
# Mapping from the first character of the prefix of the node
A__ = ... | 104 |
import argparse
import json
from collections import OrderedDict
from pathlib import Path
import requests
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from transformers import (
ConditionalDetrConfig,
ConditionalDetrForObjectDetection,
ConditionalDetrForSegm... | 509 | 0 |
class __lowerCAmelCase :
def __init__( self ):
'''simple docstring'''
__lowerCamelCase = {}
def lowerCamelCase ( self ):
'''simple docstring'''
print(self.vertex )
for i in self.vertex:
print(__UpperCAmelCase , ''' -> '... | 708 |
import unittest
from transformers import RoFormerTokenizer, RoFormerTokenizerFast
from transformers.testing_utils import require_rjieba, require_tokenizers
from ...test_tokenization_common import TokenizerTesterMixin
@require_rjieba
@require_tokenizers
class __lowerCAmelCase ( lowerCAmelCase__ , unittest... | 622 | 0 |
'''simple docstring'''
import importlib.metadata
import operator
import re
import sys
from typing import Optional
from packaging import version
A = {
'''<''': operator.lt,
'''<=''': operator.le,
'''==''': operator.eq,
'''!=''': operator.ne,
'''>=''': operator.ge,
'''>'... | 125 |
'''simple docstring'''
from typing import List, Optional, Tuple, Union
import torch
from ...utils import logging, randn_tensor
from ..pipeline_utils import AudioPipelineOutput, DiffusionPipeline
A = logging.get_logger(__name__) # pylint: disable=invalid-name
class __SCREAMING_SNAKE_C... | 125 | 1 |
'''simple docstring'''
import importlib
import sys
from argparse import REMAINDER, ArgumentParser
from pathlib import Path
import torch_xla.distributed.xla_multiprocessing as xmp
def _SCREAMING_SNAKE_CASE ( ) -> int:
"""simple docstring"""
... | 713 |
'''simple docstring'''
def _SCREAMING_SNAKE_CASE ( A : list ) -> list:
"""simple docstring"""
__snake_case : Tuple = False
while is_sorted is False: # Until all the indices are traversed keep looping
__snake_case : ... | 61 | 0 |
import torch
from diffusers import CMStochasticIterativeScheduler
from .test_schedulers import SchedulerCommonTest
class __magic_name__ (snake_case_ ):
'''simple docstring'''
__lowercase : str = (CMStochasticIterativeScheduler,)
__lowercase :... | 33 |
"""simple docstring"""
from __future__ import annotations
import requests
def lowercase ( lowerCAmelCase__ : str ) -> dict:
__a = f'''https://hacker-news.firebaseio.com/v0/item/{story_id}.json?print=pretty'''
return requests.get(lowerCAmelCase__ ).json()
def... | 695 | 0 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tf_available,
is_tokenizers_available,
is_torch_available,
)
__SCREAMING_SNAKE_CASE ={
"configuration_roformer": ["ROFORMER_PRETR... | 477 | """simple docstring"""
import random
import unittest
import torch
from diffusers import IFImgaImgSuperResolutionPipeline
from diffusers.utils import floats_tensor
from diffusers.utils.import_utils import is_xformers_available
from diffusers.utils.testing_utils import skip_mps, torch_device
from ..pipeline_par... | 477 | 1 |
import argparse
import os
import evaluate
import torch
from datasets import load_dataset
from torch.optim import AdamW
from torch.utils.data import DataLoader
from transformers import AutoModelForSequenceClassification, AutoTokenizer, get_linear_schedule_with_warmup, set_seed
from accelerate import Accelerator, D... | 622 |
from sklearn.metrics import matthews_corrcoef
import datasets
a__ : Any = "\nCompute the Matthews correlation coefficient (MCC)\n\nThe Matthews correlation coefficient is used in machine learning as a\nmeasure of the quality of binary and multiclass classifications. It takes\ninto account true a... | 622 | 1 |
'''simple docstring'''
lowercase__ : List[Any] = 2_56
# Modulus to hash a string
lowercase__ : Union[str, Any] = 1_00_00_03
def _lowerCAmelCase ( __snake_case : str , __snake_case : str ) -> bool:
__A :... | 718 |
'''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
fro... | 338 | 0 |
"""simple docstring"""
from sklearn.metrics import recall_score
import datasets
SCREAMING_SNAKE_CASE_ = "\nRecall is the fraction of the positive examples that were correctly labeled by the model as positive. It can be computed with the equation:\nRecall = TP / (TP + FN)\nWhere TP is the true... | 373 |
"""simple docstring"""
import numpy as np
import torch
from torch.utils.data import DataLoader
from accelerate.utils.dataclasses import DistributedType
class lowerCamelCase__ :
def __init__( self : Optional[Any] , _lowercase : int=2 , _lowercase : Option... | 690 | 0 |
from collections import OrderedDict
from typing import TYPE_CHECKING, Any, Mapping, Optional, Union
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig, OnnxSeqaSeqConfigWithPast
from ...utils import logging
if TYPE_CHECKING:
from ...feature_extraction_utils import FeatureExtrac... | 710 |
import warnings
from typing import List, Optional, Union
from ...processing_utils import ProcessorMixin
from ...tokenization_utils_base import BatchEncoding, PaddingStrategy, PreTokenizedInput, TextInput, TruncationStrategy
from ...utils import TensorType
class _UpperCamelCase ( __snake_case )... | 546 | 0 |
from collections import OrderedDict
from ...utils import logging
from .auto_factory import _BaseAutoModelClass, _LazyAutoMapping, auto_class_update
from .configuration_auto import CONFIG_MAPPING_NAMES
_lowerCamelCase = logging.get_logger(__name__)
_lowerCamelCase = OrderedDict(
[
... | 6 |
from torch import nn
def SCREAMING_SNAKE_CASE__ ( UpperCamelCase__: str ):
if act_fn in ["swish", "silu"]:
return nn.SiLU()
elif act_fn == "mish":
return nn.Mish()
elif act_fn == "gelu":
return nn.GELU()
else:
raise ValueError(f'''Unsupported activation function:... | 6 | 1 |
import logging
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_START_DOCSTRING,
Bert... | 76 |
import json
import os
import tempfile
from transformers.testing_utils import check_json_file_has_correct_format
class UpperCAmelCase_ :
'''simple docstring'''
a__ = None
def _lowercase ( self : Optional[int] ) -> str:
... | 76 | 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, SchedulerOutput
de... | 78 | '''simple docstring'''
from typing import Optional, Union
import numpy as np
from ...image_processing_utils import BaseImageProcessor, BatchFeature
from ...image_transforms import get_image_size, pad, rescale, to_channel_dimension_format
from ...image_utils import ChannelDimension, ImageInput, make_list_of_image... | 78 | 1 |
import re
def lowerCAmelCase__ ( _a : str ):
return [char.split() for char in re.split(R"[^ a-z A-Z 0-9 \s]" , str_ )]
def lowerCAmelCase__ ( _a : str ):
snake_case_ : List[str] = split_input(str_ )
return "".join(
["".join([cha... | 114 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
lowercase : Any = logging.get_logger(__name__)
lowercase : str = {
'''naver-clova-ix/donut-base''': '''https://huggingface.co/naver-clova-ix/donut-base/resolve/main/config.json''',
# See all Do... | 114 | 1 |
'''simple docstring'''
import tempfile
import unittest
import numpy as np
from huggingface_hub import HfFolder, delete_repo
from requests.exceptions import HTTPError
from transformers import BertConfig, is_flax_available
from transformers.testing_utils import TOKEN, USER, is_staging_test, require_flax
if is_... | 98 |
from typing import Optional
from .. import Features, NamedSplit
from ..packaged_modules.text.text import Text
from ..utils.typing import NestedDataStructureLike, PathLike
from .abc import AbstractDatasetReader
class lowerCamelCase_ ( lowerCAmelCase__ ):
'''simple docstring'''
... | 639 | 0 |
'''simple docstring'''
import gc
import random
import unittest
import numpy as np
import torch
from transformers import XLMRobertaTokenizer
from diffusers import (
AltDiffusionImgaImgPipeline,
AutoencoderKL,
PNDMScheduler,
UNetaDConditionModel,
)
from diffusers.image... | 702 |
import requests
def a (_lowerCAmelCase , _lowerCAmelCase ):
SCREAMING_SNAKE_CASE_ = {'''Content-Type''': '''application/json'''}
SCREAMING_SNAKE_CASE_ = requests.post(_lowerCAmelCase , json={'''text''': message_body} , headers=_lowerCAmelCase )
i... | 89 | 0 |
"""simple docstring"""
import time
from dataclasses import dataclass
from multiprocessing import Pool
from unittest import TestCase
from unittest.mock import patch
import multiprocess
import numpy as np
import pytest
from datasets.utils.py_utils import (
NestedDataStructure,
asdict,
iflatmap_unord... | 163 |
"""simple docstring"""
from __future__ import annotations
def __UpperCamelCase ( SCREAMING_SNAKE_CASE , SCREAMING_SNAKE_CASE , SCREAMING_SNAKE_CASE , ) -> tuple[str, float]:
"""simple docstring"""
if (stress, tangential_force, area).count(0 ) != 1:
... | 163 | 1 |
'''simple docstring'''
import torch
from diffusers import EulerDiscreteScheduler
from diffusers.utils import torch_device
from .test_schedulers import SchedulerCommonTest
class a__( lowerCAmelCase__ ):
'''simple docstring'''
UpperCAmelCase_ : List[str] = (EulerDiscreteSc... | 605 | '''simple docstring'''
from math import ceil, sqrt
def snake_case__ ( _A: int = 1000000 ) -> int:
'''simple docstring'''
lowerCAmelCase = 0
for outer_width in range(3 , (limit // 4) + 2 ):
if outer_width**2 > limit:
lowerCAmelCase ... | 605 | 1 |
from __future__ import annotations
from math import pow, sqrt
def lowerCamelCase__ ( _lowercase , _lowercase , _lowercase ):
'''simple docstring'''
if (resistance, reactance, impedance).count(0 ) != 1:
raise ValueError('''One and only one argument must be 0''' )
i... | 30 |
import unittest
import numpy as np
def lowerCamelCase__ ( _lowercase , _lowercase , _lowercase , _lowercase = None , ):
'''simple docstring'''
UpperCAmelCase_ : Dict = np.shape(_lowercase )
UpperCAmelCase_ : Optional[Any] = np.shape(_lowerc... | 30 | 1 |
'''simple docstring'''
from collections.abc import Callable
import numpy as np
def UpperCamelCase_ ( A__ , A__ , A__ , A__ , A__ ):
a_ = int(np.ceil((x_end - xa) / step_size ) )
a_ = np.zeros((n + 1,) )
a_ = ya
a_ = xa
for k in range(... | 511 |
'''simple docstring'''
from __future__ import annotations
def UpperCamelCase_ ( A__ , A__ , A__ , A__ ):
if (direction == 1 and array[indexa] > array[indexa]) or (
direction == 0 and array[indexa] < array[indexa]
):
a_ , a_ = array[indexa], array[indexa]
... | 511 | 1 |
from __future__ import annotations
from cmath import sqrt
def SCREAMING_SNAKE_CASE__ ( snake_case_, snake_case_, snake_case_ ) -> List[str]:
"""simple docstring"""
if a == 0:
raise ValueError('''Coefficient \'a\' must not be zero.''' )
a = b * b - 4 * a... | 387 |
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 TensorType, logging
UpperCAmelCase : Any ... | 457 | 0 |
"""simple docstring"""
from math import factorial
__UpperCamelCase : dict[str, int] = {str(digit): factorial(digit) for digit in range(1_0)}
def __UpperCAmelCase ( _snake_case : int ):
if not isinstance(__UpperCamelCase, __UpperCamelCase ):
raise TypeE... | 711 | """simple docstring"""
def __UpperCAmelCase ( _snake_case : int ):
if num < 0:
return False
_lowercase = num
_lowercase = 0
while num > 0:
_lowercase = rev_num * 1_0 + (num % 1_0)
num //= 1_0
return num_copy == rev_num
if... | 227 | 0 |
"""simple docstring"""
from collections.abc import Sequence
def lowercase_ ( _lowerCamelCase: Sequence[float] , _lowerCamelCase: bool = False ) -> float:
'''simple docstring'''
if not arr:
return 0
__lowerCamelCase : int = 0 if allow_empty_sub... | 646 | """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 import ImageProcessingSavingTe... | 646 | 1 |
import argparse
import os
import evaluate
import torch
from datasets import load_dataset
from torch.optim import AdamW
from torch.utils.data import DataLoader
from transformers import AutoModelForSequenceClassification, AutoTokenizer, get_linear_schedule_with_warmup, set_seed
from accelerate import Accelera... | 718 | import unittest
from transformers.utils.backbone_utils import (
BackboneMixin,
get_aligned_output_features_output_indices,
verify_out_features_out_indices,
)
class __snake_case ( unittest.TestCase ):
'''simple docstring'''
def _SCREAMING_SNAKE_CASE (... | 15 | 0 |
import json
import os
import unittest
from transformers import AutoTokenizer, GPTaTokenizer, GPTaTokenizerFast
from transformers.models.gpta.tokenization_gpta import VOCAB_FILES_NAMES
from transformers.testing_utils import require_tokenizers
from ...test_tokenization_common import TokenizerTesterMixin
@require_... | 30 |
'''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_ : Dict = {
'configuration_distilbert': [
... | 365 | 0 |
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 : int
__A : Node | None = None
__A : ... | 392 |
from collections import namedtuple
lowercase : List[str] = namedtuple("""from_to""", """from_ to""")
lowercase : Tuple = {
"""cubicmeter""": from_to(1, 1),
"""litre""": from_to(0.001, 1_0_0_0),
"""kilolitre""": from_to(1, 1),
"""gallon""": from_to(0.00_454, 264.172),
... | 392 | 1 |
import argparse
import json
import os
import fairseq
import torch
from fairseq.data import Dictionary
from transformers import (
WavaVecaConformerConfig,
WavaVecaConformerForCTC,
WavaVecaConformerForPreTraining,
WavaVecaCTCTokenizer,
WavaVecaFeatureExtractor,
WavaVecaProcessor,
logg... | 324 |
from collections import deque
def UpperCamelCase ( _A ):
"""simple docstring"""
__magic_name__ : Union[str, Any] = len(_A )
__magic_name__ : Optional[int] = deque()
__magic_name__ : Tuple = [False for _ in range(_A )]
... | 324 | 1 |
"""simple docstring"""
def __lowerCAmelCase (_UpperCamelCase ):
__lowerCAmelCase : List[Any] = [0 for i in range(len(_UpperCamelCase ) )]
# initialize interval's left pointer and right pointer
__lowerCAmelCase : List[str] = 0, 0
for i in range(1 , len(_UpperCamelCase ... | 710 |
"""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 DetrConfig, DetrForObjectDetection, DetrForSegmentation, DetrImageProcessor, ResNetConfig
from transformers.utils ... | 549 | 0 |
"""simple docstring"""
import sys
def _UpperCamelCase ( A ):
UpperCamelCase_ =len(A )
UpperCamelCase_ =[[0 for x in range(A )] for x in range(A )]
UpperCamelCase_ =[[0 for x in range(A )] for x in range(A )]
for chain_length in ra... | 391 |
"""simple docstring"""
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 im... | 391 | 1 |
from __future__ import annotations
import os
from collections.abc import Mapping
snake_case_ = tuple[int, int]
class _lowercase :
def __init__( self , _UpperCAmelCase , _UpperCAmelCase ):
A : set[int] = vertices
A : dict[EdgeT, int... | 700 |
'''simple docstring'''
import argparse
import os
import re
import numpy as np
import PIL
import torch
from timm import create_model
from torch.optim.lr_scheduler import OneCycleLR
from torch.utils.data import DataLoader, Dataset
from torchvision.transforms import Compose, RandomResizedCrop, Resize, ToTenso... | 537 | 0 |
from __future__ import annotations
def a__ ( A__, A__ ):
SCREAMING_SNAKE_CASE_ : Any = sorted(numsa + numsa )
SCREAMING_SNAKE_CASE_ , SCREAMING_SNAKE_CASE_ : Union[str, Any] = divmod(len(a__ ), 2 )
if mod == 1:
return... | 101 | """simple docstring"""
import asyncio
import os
import re
import sys
import tempfile
import unittest
from contextlib import contextmanager
from copy import deepcopy
from distutils.util import strtobool
from enum import Enum
from importlib.util import find_spec
from pathlib import Path
from unittest.mock import patch
... | 420 | 0 |
from urllib.parse import quote
import pytest
from datasets.utils.hub import hf_hub_url
@pytest.mark.parametrize("""repo_id""" , ["""canonical_dataset_name""", """org-name/dataset-name"""] )
@pytest.mark.parametrize("""path""" , ["""filename.csv""", """filename with blanks.csv"""] ... | 649 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_tf_available,
is_tokenizers_available,
is_torch_available,
)
lowerCamelCase : int = {
'''configuration_funnel''': ['''FUNNEL_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''Funnel... | 649 | 1 |
def _lowercase ( __UpperCamelCase : Any , __UpperCamelCase : Optional[int] , __UpperCamelCase : List[Any] , __UpperCamelCase : List[Any] ):
if height >= 1:
move_tower(height - 1 , __UpperCamelCase , __UpperCamelCase , __UpperCamelCase )
... | 214 |
def _lowercase ( __UpperCamelCase : list ):
snake_case__ = False
while is_sorted is False: # Until all the indices are traversed keep looping
snake_case__ = True
for i in range(0 , len(__UpperCamelCase ) - 1 , 2 ): # iterating o... | 214 | 1 |
"""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/LICENSE-2.... | 183 |
"""simple docstring"""
import inspect
import unittest
from transformers import RegNetConfig, is_flax_available
from transformers.testing_utils import require_flax, slow
from transformers.utils import cached_property, is_vision_available
from ...test_configuration_common import ConfigTester
from ...test_m... | 183 | 1 |
import json
import os
import shutil
import tempfile
import unittest
import numpy as np
import pytest
from transformers import CLIPTokenizer, CLIPTokenizerFast
from transformers.models.clip.tokenization_clip import VOCAB_FILES_NAMES
from transformers.testing_utils import require_vision
from transformers.utils impo... | 9 |
'''simple docstring'''
from __future__ import annotations
import unittest
import numpy as np
from transformers import BlipTextConfig
from transformers.testing_utils import require_tf, slow
from transformers.utils import is_tf_available
from ...test_configuration_common import ConfigTester
from ...test_m... | 531 | 0 |
from typing import List, Optional, Tuple, Union
import torch
from ...models import UNetaDModel
from ...schedulers import KarrasVeScheduler
from ...utils import randn_tensor
from ..pipeline_utils import DiffusionPipeline, ImagePipelineOutput
class lowerCAmelCase ( __UpperCamelCase ):
UpperCA... | 188 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
_UpperCAmelCase : Dict = logging.get_logger(__name__)
_UpperCAmelCase : Union[str, Any] = {
"""naver-clova-ix/donut-base""": """https://huggingface.co/naver-clova-ix/donut-base/resolve/mai... | 188 | 1 |
"""simple docstring"""
from ...configuration_utils import PretrainedConfig
from ...utils import logging
_A : Optional[int] = logging.get_logger(__name__)
_A : Tuple = {
"""facebook/s2t-wav2vec2-large-en-de""": (
"""https://huggingface.co/facebook/s2t-wav2v... | 361 |
"""simple docstring"""
from __future__ import annotations
from math import pow, sqrt
def __magic_name__ ( __snake_case : float , __snake_case : float , __snake_case : float ) -> dict[str, float]:
if (resistance, reactance, impedance).count... | 361 | 1 |
"""simple docstring"""
import copy
import os
from typing import Union
from ...configuration_utils import PretrainedConfig
from ...utils import logging
UpperCAmelCase : str = logging.get_logger(__name__)
UpperCAmelCase : Optional[int] = {
"Salesforce/blip-vqa-base": "https://huggingface.c... | 121 | """simple docstring"""
import gc
import tempfile
import unittest
import numpy as np
import torch
from diffusers import VersatileDiffusionPipeline
from diffusers.utils.testing_utils import load_image, nightly, require_torch_gpu, torch_device
UpperCAmelCase : Dict = False
class __SCREAMING_SNAKE_C... | 121 | 1 |
'''simple docstring'''
def __UpperCAmelCase ( lowerCamelCase_) -> Tuple:
UpperCamelCase__ : Union[str, Any] = 1
UpperCamelCase__ : str = 2
while i * i <= n:
UpperCamelCase__ : List[Any] = 0
while n % i ... | 596 |
'''simple docstring'''
from math import sqrt
def __UpperCAmelCase ( lowerCamelCase_ = 1_000_000) -> int:
UpperCamelCase__ : int = 0
UpperCamelCase__ : int = 0
UpperCamelCase__ : int
while num_cuboids <= l... | 596 | 1 |
from manim import *
class lowerCAmelCase_ ( _SCREAMING_SNAKE_CASE ):
def __a ( self ):
_lowercase : Any = Rectangle(height=0.5 , width=0.5 )
_lowercase : Optional[int] = Rectangle(height=0.46 , width=0.46 ).s... | 703 |
from __future__ import annotations
import unittest
from transformers import MobileBertConfig, is_tf_available
from transformers.models.auto import get_values
from transformers.testing_utils import require_tf, slow
from ...test_configuration_common import ConfigTester
from ...test_modeling_tf_common import TFM... | 677 | 0 |
from __future__ import annotations
import unittest
from transformers import AutoTokenizer, MBartConfig, is_tf_available
from transformers.testing_utils import require_sentencepiece, require_tf, require_tokenizers, slow
from transformers.utils import cached_property
from ...test_configuration_common import Con... | 80 | """simple docstring"""
def UpperCAmelCase__ ( lowerCAmelCase__ :int = 1_0**9 ) -> int:
'''simple docstring'''
lowercase = 1
lowercase = 2
lowercase = 0
lowercase = 0
lowercase ... | 359 | 0 |
def snake_case_ ( SCREAMING_SNAKE_CASE_ ) -> list:
# bit count represents no. of bits in the gray code
if bit_count < 0:
raise ValueError("The given input must be positive" )
# get the generated string sequence
lowercase__ : Opti... | 298 |
import inspect
import os
import unittest
import torch
import accelerate
from accelerate import debug_launcher
from accelerate.test_utils import (
execute_subprocess_async,
require_cpu,
require_huggingface_suite,
require_multi_gpu,
require_single_gpu,
)
from accelerate.util... | 298 | 1 |
# Copyright 2023 The HuggingFace Inc. team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless requ... | 693 |
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 import BertTokenizer
a_ :Tuple = logging.get_logger(__name__)
a_ :Optional[An... | 35 | 0 |
"""simple docstring"""
from typing import Any
def lowerCamelCase_ ( _lowerCamelCase , _lowerCamelCase , _lowerCamelCase , _lowerCamelCase , _lowerCamelCase , ):
_validation(
_lowerCamelCase , _lowerCamelCase , _lowerCamelCase , _lowerCame... | 696 |
"""simple docstring"""
import os
def lowerCamelCase_ ( ):
with open(os.path.dirname(_lowerCamelCase ) + '/p022_names.txt' ) as file:
lowerCamelCase__ : Union[str, Any] = str(file.readlines()[0] )
lowerCamelCase__ : int = names.replace('"' , '' ... | 696 | 1 |
from collections.abc import Sequence
def __magic_name__ ( lowercase , lowercase ) -> float:
"""simple docstring"""
return sum(c * (x**i) for i, c in enumerate(lowercase ) )
def __magic_name__ ( lowercase , lowercase ) ... | 458 |
from string import ascii_uppercase
UpperCAmelCase_ = {char: i for i, char in enumerate(ascii_uppercase)}
UpperCAmelCase_ = dict(enumerate(ascii_uppercase))
def __magic_name__ ( lowercase , lowercase ) -> str:
"""simple docstring"""
... | 458 | 1 |
from __future__ import annotations
from collections.abc import Callable
from typing import Generic, TypeVar
UpperCAmelCase = TypeVar('''T''')
UpperCAmelCase = TypeVar('''U''')
class A_ ( Generic[T, U] ):
'''simple docstring'''
def __init__( self , snake_case , snake... | 718 |
from itertools import product
from cva import COLOR_BGR2GRAY, cvtColor, imread, imshow, waitKey
from numpy import dot, exp, mgrid, pi, ravel, square, uinta, zeros
def UpperCAmelCase_ ( __SCREAMING_SNAKE_CASE , __SCREAMING_SNAKE_CASE ):
lowercase = k_size // 2
lowercase ... | 565 | 0 |
"""simple docstring"""
import io
import math
from typing import Dict, Optional, Union
import numpy as np
from huggingface_hub import hf_hub_download
from ...image_processing_utils import BaseImageProcessor, BatchFeature
from ...image_transforms import convert_to_rgb, normalize, to_chann... | 104 |
def __lowercase ( _UpperCamelCase ) ->list[int]:
"""simple docstring"""
lowercase : Optional[Any] = len(_UpperCamelCase )
for i in range(_UpperCamelCase ):
for j in range(i + 1, _UpperCamelCase ):
if numbers[j] < numbers[i... | 319 | 0 |
'''simple docstring'''
import os
import sys
import unittest
a = os.path.abspath(os.path.dirname(os.path.dirname(os.path.dirname(__file__))))
sys.path.append(os.path.join(git_repo_path, 'utils'))
import get_test_info # noqa: E402
from get_test_info import ( # noqa: E402
ge... | 347 |
'''simple docstring'''
import sys
from collections import defaultdict
class a_ :
def __init__( self : Union[str, Any] ) -> Optional[int]:
snake_case: Any =[]
def UpperCamelCase ( self : List[str] , a_ : ... | 347 | 1 |
from ...utils import logging
from ..ta.modeling_tf_ta import TFTaEncoderModel, TFTaForConditionalGeneration, TFTaModel
from .configuration_mta import MTaConfig
UpperCAmelCase_ = logging.get_logger(__name__)
UpperCAmelCase_ = "T5Config"
class __UpperCamelCase ( A__ ):
... | 32 |
from __future__ import annotations
def A__ ( SCREAMING_SNAKE_CASE_ : int ) -> bool:
"""simple docstring"""
_UpperCAmelCase = str(SCREAMING_SNAKE_CASE_ )
return len(SCREAMING_SNAKE_CASE_ ) == 9 and set(SCREAMING_SNAKE_CASE_ ) == set('''12... | 32 | 1 |
def lowerCAmelCase__ ( a__ ) ->Tuple:
'''simple docstring'''
_UpperCamelCase = 0
_UpperCamelCase = len(a__ )
for i in range(n - 1 ):
for j in range(i + 1 , a__ ):
if arr[i] > arr[j]:
num_inversions += 1
return num_inversions
def ... | 703 | import logging
from transformers import PretrainedConfig
lowerCamelCase__ = logging.getLogger(__name__)
lowerCamelCase__ = {
'''bertabs-finetuned-cnndm''': '''https://huggingface.co/remi/bertabs-finetuned-cnndm-extractive-abstractive-summarization/resolve/main/config.json''',
}
class _Upp... | 82 | 0 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
a_ : Dict = logging.get_logger(__name__)
a_ : List[str] = {
'studio-ousia/luke-base': 'https://huggingface.co/studio-ousia/luke-base/resolve/main/config.json',
'studio-ousia/luke-large': ... | 73 |
def __UpperCAmelCase ( lowerCamelCase_ : List[str] , lowerCamelCase_ : Optional[Any] ) -> int:
"""simple docstring"""
SCREAMING_SNAKE_CASE_ : List[Any] = [0 for i in range(r + 1 )]
# nc0 = 1
SCREAMING_SNAKE_CASE_ : Dict = 1... | 105 | 0 |
from __future__ import annotations
def snake_case (__lowercase , __lowercase = None , __lowercase = None , __lowercase = False , ) -> tuple[int, float, str]:
'''simple docstring'''
_snake_case : Dict = cipher_alphabet or [chr(__lowercase ) for i in ran... | 580 | import math
def snake_case (__lowercase , __lowercase ) -> float:
'''simple docstring'''
if (
not isinstance(__lowercase , (int, float) )
or power_factor < -1
or power_factor > 1
):
raise ValueError("power_factor must be a valid fl... | 580 | 1 |
import math
import random
from typing import Any
from .hill_climbing import SearchProblem
def __lowercase ( lowerCamelCase : int , lowerCamelCase : bool = True , lowerCamelCase : float = math.inf , lowerCamelCase : float = -math.inf , lowerCamelCase : float = math.inf , ... | 417 |
'''simple docstring'''
import logging
import os
from typing import List, TextIO, Union
from conllu import parse_incr
from utils_ner import InputExample, Split, TokenClassificationTask
__magic_name__ : List[Any] =logging.getLogger(__name__)
class UpperCamelCase_ ( A ):
"""simple docst... | 664 | 0 |
from math import factorial, radians
def UpperCamelCase ( _A : float , _A : int = 18 , _A : int = 10 )-> float:
"""simple docstring"""
A__ = angle_in_degrees - ((angle_in_degrees // 360.0) * 360.0)
# Converting from degrees to r... | 232 |
import argparse
import evaluate
import torch
from datasets import load_dataset
from torch.optim import AdamW
from torch.utils.data import DataLoader
from transformers import AutoModelForSequenceClassification, AutoTokenizer, get_linear_schedule_with_warmup, set_seed
from accelerate import Accelerator, Distributed... | 232 | 1 |
"""simple docstring"""
import tempfile
import torch
from diffusers import (
DEISMultistepScheduler,
DPMSolverMultistepScheduler,
DPMSolverSinglestepScheduler,
UniPCMultistepScheduler,
)
from .test_schedulers import SchedulerCommonTest
class __A ( A_ ... | 560 |
"""simple docstring"""
from ...processing_utils import ProcessorMixin
class __A ( A_ ):
'''simple docstring'''
lowerCAmelCase : Tuple = "SpeechT5FeatureExtractor"
lowerCAmelCase : Optional[Any] = "SpeechT5Toke... | 560 | 1 |
import colorsys
from PIL import Image # type: ignore
def UpperCAmelCase__ ( lowerCamelCase_ : float , lowerCamelCase_ : float , lowerCamelCase_ : int ) -> List[str]:
__a : List[Any] = x
__a : Any = y
for step in... | 718 |
import os
from shutil import copyfile
from typing import List, Optional, Tuple
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import is_sentencepiece_available, logging
if is_sentencepiece_available():
from .tokenization_pegasus import PegasusTokenizer
els... | 577 | 0 |
from dataclasses import dataclass
from typing import Optional, Tuple
import torch
from torch import nn
from transformers import RobertaPreTrainedModel, XLMRobertaConfig, XLMRobertaModel
from transformers.utils import ModelOutput
@dataclass
class __magic_name__ ( _lowerCAmelCase):
_UpperCAmelCase : Opti... | 333 |
'''simple docstring'''
import os
import zipfile
import requests
from get_ci_error_statistics import download_artifact, get_artifacts_links
def __snake_case (__UpperCAmelCase , __UpperCAmelCase=7 ):
"""simple docstring"""
lowerCamelCase_ : List[Any] = None
if tok... | 501 | 0 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available, is_vision_available
lowerCamelCase__ = {"configuration_glpn": ["GLPN_PRETRAINED_CONFIG_ARCHIVE_MAP", "GLPNConfig"]}
try:
if not is_vision_available():
raise OptionalDependencyNotAvaila... | 202 |
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 Tensor
from transformers import AutoImageProcessor, ResNetCo... | 202 | 1 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
lowerCamelCase_ : Tuple = logging.get_logger(__name__)
lowerCamelCase_ : Any = {
"""abeja/gpt-neox-japanese-2.7b""": """https://huggingface.co/abeja/gpt-neox-japanese-2.7b/resolve/main/config... | 559 | import logging
import re
import pytorch_quantization
import pytorch_quantization.nn as quant_nn
import torch
from pytorch_quantization import calib
from pytorch_quantization.tensor_quant import QuantDescriptor
lowerCamelCase_ : Any = logging.getLogger(__name__)
lowerCamelCase_ : ... | 559 | 1 |
"""simple docstring"""
from collections.abc import Callable
from math import pi, sqrt
from random import uniform
from statistics import mean
def _UpperCAmelCase ( __lowerCamelCase : int ) -> Tuple:
# A local function to see if a dot lands in the circle.
def is_in_circle(__lower... | 716 |
"""simple docstring"""
from __future__ import annotations
import math
from collections import Counter
from string import ascii_lowercase
def _UpperCAmelCase ( __lowerCamelCase : str ) -> None:
_snake_case , _snake_case = analyze_text(__lowerCamelCase )
_snake_case ... | 430 | 0 |
'''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
SCREAMING_SNAKE_CASE ... | 94 |
"""simple docstring"""
import json
from typing import TYPE_CHECKING, List, Optional, Tuple
from tokenizers import pre_tokenizers
from ...tokenization_utils_base import BatchEncoding
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import logging
from .tokenization_gpta import GPTaT... | 289 | 0 |
"""simple docstring"""
import argparse
lowercase = """docs/source/_static/js/custom.js"""
def A__ ( _UpperCAmelCase : Any ) -> List[Any]:
'''simple docstring'''
with open(_UpperCAmelCase , encoding="utf-8" , newline="\n" ) as f:
snake_case__ : Li... | 700 |
"""simple docstring"""
from ..utils import DummyObject, requires_backends
class SCREAMING_SNAKE_CASE_ ( metaclass=_lowercase):
'''simple docstring'''
__magic_name__ : List[str] = ['''torch''']
def __init__( self , *lowerCamelCase__ , **... | 150 | 0 |
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 import ImageProcessingSavingTestMixin, prepare_image_in... | 81 | """simple docstring"""
from __future__ import annotations
from random import random
from typing import Generic, TypeVar
__lowerCAmelCase : Dict = TypeVar("KT")
__lowerCAmelCase : Optional[Any] = TypeVar("VT")
class a_ ( Generic[KT, VT] ):
def __init__( s... | 644 | 0 |
def a ( SCREAMING_SNAKE_CASE_ : int , SCREAMING_SNAKE_CASE_ : int ):
"""simple docstring"""
if a < 0 or b < 0:
raise ValueError('''the value of both inputs must be positive''' )
UpperCamelCase : int = st... | 643 |
import json
import os
import unittest
from transformers import DebertaTokenizer, DebertaTokenizerFast
from transformers.models.deberta.tokenization_deberta import VOCAB_FILES_NAMES
from transformers.testing_utils import slow
from ...test_tokenization_common import TokenizerTesterMixin
class Up... | 643 | 1 |
'''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,
rescale,
resize,
to_ch... | 48 |
'''simple docstring'''
import logging
import numpy as np
import pytest
from scipy.linalg import eigh
logging.basicConfig(level=logging.INFO, format="%(message)s")
def A ( UpperCamelCase_ : np.ndarray ) -> np.ndarray:
'''simple docstring'''
return input_array.reshape((... | 48 | 1 |
'''simple docstring'''
def UpperCamelCase_ ( A__ ):
a_ = len(A__ )
a_ = len(matrix[0] )
a_ = min(A__ , A__ )
for row in range(A__ ):
# Check if diagonal element is not zero
if matrix[row][row] != 0:
# Eliminate all the elements below the diagonal
for col in r... | 713 |
'''simple docstring'''
def UpperCamelCase_ ( A__ = 50 ):
a_ = [[0] * 3 for _ in range(length + 1 )]
for row_length in range(length + 1 ):
for tile_length in range(2 , 5 ):
for tile_start in range(row_length - tile_length + 1 ):
different_colour_ways_number[row_length][tile_length... | 511 | 0 |
import unittest
from .lib import (
Matrix,
Vector,
axpy,
square_zero_matrix,
unit_basis_vector,
zero_vector,
)
class lowerCAmelCase__( unittest.TestCase ):
'''simple docstring'''
def UpperCamelCase_ ( self ) -> None:
... | 249 |
import requests
from bsa import BeautifulSoup
def lowerCamelCase__ (__lowerCamelCase = "AAPL" ):
_SCREAMING_SNAKE_CASE : Dict = f"""https://in.finance.yahoo.com/quote/{symbol}?s={symbol}"""
_SCREAMING_SNAKE_CASE : str = BeautifulSoup(reque... | 249 | 1 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tensorflow_text_available, is_torch_available
_lowerCAmelCase :List[str] = {
"""configuration_ernie""": ["""ERNIE_PRETRAINED_CONFIG_ARCHIVE_MAP""", """ErnieConfig... | 179 | '''simple docstring'''
from __future__ import annotations
import unittest
from transformers import LEDConfig, is_tf_available
from transformers.testing_utils import require_tf, slow
from ...test_configuration_common import ConfigTester
from ...test_modeling_tf_common import TFModelTesterMixin, ids... | 179 | 1 |
"""simple docstring"""
from typing import Optional, Union
import numpy as np
from ...image_processing_utils import BaseImageProcessor, BatchFeature
from ...image_transforms import get_image_size, pad, rescale, to_channel_dimension_format
from ...image_utils import ChannelDimension, ImageInput... | 58 |
"""simple docstring"""
# Usage:
# ./gen-card-facebook-wmt19.py
import os
from pathlib import Path
def __lowerCAmelCase ( __UpperCamelCase : int , __UpperCamelCase : str , __UpperCamelCase : Any ):
'''simple docstring'''
... | 58 | 1 |
'''simple docstring'''
class __lowerCamelCase :
"""simple docstring"""
def __init__( self : Optional[int] ) -> None:
lowerCAmelCase__ = {} # Mapping from char to TrieNode
lowerCAmelCase__ = False
def a ( self : s... | 710 |
import argparse
from collections import OrderedDict
from pathlib import Path
import torch
from transformers import (
VisualBertConfig,
VisualBertForMultipleChoice,
VisualBertForPreTraining,
VisualBertForQuestionAnswering,
VisualBertForVisualReasoning,
)
from transformers.uti... | 125 | 0 |
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