code stringlengths 87 55.2k | code_codestyle int64 0 349 | style_context stringlengths 135 49.1k | style_context_codestyle int64 0 349 | label int64 0 1 |
|---|---|---|---|---|
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,
AutoModelForMultipleChoice,
AutoTokenizer,
DataC... | 20 |
from __future__ import annotations
def lowerCamelCase__ ( snake_case_ : list[int] ) -> list[int]: # This function is recursive
__snake_case = len(snake_case_ )
# If the array contains only one element, we return it (it's the stop condition o... | 24 | 0 |
import copy
import os
from typing import Union
from ...configuration_utils import PretrainedConfig
from ...models.auto.modeling_auto import MODEL_FOR_CAUSAL_LM_MAPPING_NAMES
from ...utils import logging
from ..auto import CONFIG_MAPPING
SCREAMING_SNAKE_CASE : Tuple = logging.get_logger(__nam... | 21 |
import unittest
from transformers import LiltConfig, is_torch_available
from transformers.testing_utils import require_torch, slow, torch_device
from ...generation.test_utils import GenerationTesterMixin
from ...test_configuration_common import ConfigTester
from ...test_modeling_common import Model... | 24 | 0 |
'''simple docstring'''
import json
import os
from typing import Optional, Tuple
from ...tokenization_utils import PreTrainedTokenizer
from ...utils import logging
__SCREAMING_SNAKE_CASE :int = logging.get_logger(__name__)
__SCREAMING_SNAKE_CASE :Optional[Any] = {'''vocab_file''':... | 22 |
import unittest
from transformers import MODEL_FOR_DOCUMENT_QUESTION_ANSWERING_MAPPING, AutoTokenizer, is_vision_available
from transformers.pipelines import pipeline
from transformers.pipelines.document_question_answering import apply_tesseract
from transformers.testing_utils import (
is_pipelin... | 24 | 0 |
'''simple docstring'''
import os
from datetime import datetime as dt
from github import Github
UpperCamelCase__: Union[str, Any] = [
"good first issue",
"feature request",
"wip",
]
def snake_case_ ( ) -> int:
UpperCAmelCase : Di... | 23 |
from __future__ import annotations
def lowerCamelCase__ ( snake_case_ : list[int] , snake_case_ : int ) -> list[list[int]]:
__snake_case = []
__snake_case = []
__snake_case = 0
__snake_case ... | 24 | 0 |
"""simple docstring"""
def lowercase_ ( _snake_case ,_snake_case ):
if b == 0:
return 1
if (b % 2) == 0:
return actual_power(_snake_case ,int(b / 2 ) ) * actual_power(_snake_case ,int(b / 2 ) )
else:
return... | 25 |
import inspect
import unittest
from transformers import ConvNextConfig
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_backbone_common import BackboneTesterM... | 24 | 0 |
from __future__ import annotations
from math import ceil, floor, sqrt
def lowerCAmelCase_ ( snake_case_ = 2000000 ):
_A : list[int] = [0]
_A : int
for idx in range(1,ceil(sqrt(target * 2 ) * 1.1 ) ):
triangle_numbers.append(t... | 26 |
def lowerCamelCase__ ( ) -> int:
return [
a * b * (1000 - a - b)
for a in range(1 , 999 )
for b in range(snake_case_ , 999 )
if (a * a + b * b == (1000 - a - b) ** 2)
][0]
if __name__ == "__main__":
print(F'... | 24 | 0 |
'''simple docstring'''
from collections import OrderedDict
from typing import Mapping
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
__lowercase : List[str] = logging.get_logger(__name__)
__lowercase : Dict = {
'distilb... | 27 |
import os
import unittest
from transformers.models.bartpho.tokenization_bartpho import VOCAB_FILES_NAMES, BartphoTokenizer
from transformers.testing_utils import get_tests_dir
from ...test_tokenization_common import TokenizerTesterMixin
snake_case_ = get_tests_dir('fixtures/test_sentencepi... | 24 | 0 |
'''simple docstring'''
import absl # noqa: F401 # Here to have a nice missing dependency error message early on
import nltk # noqa: F401 # Here to have a nice missing dependency error message early on
import numpy # noqa: F401 # Here to have a nice missing dependency error message early on
import six... | 28 |
def lowerCamelCase__ ( snake_case_ : int ) -> int:
if not isinstance(snake_case_ , snake_case_ ) or number < 0:
raise ValueError('''Input must be a non-negative integer''' )
__snake_case = 0
while number:
# This way we... | 24 | 0 |
# 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
#
# U... | 29 |
from math import loga
def lowerCamelCase__ ( snake_case_ : int ) -> int:
if a < 0:
raise ValueError('''Input value must be a positive integer''' )
elif isinstance(snake_case_ , snake_case_ ):
raise TypeError('''Input value mus... | 24 | 0 |
import argparse
from transformers import CLIPImageProcessor, CLIPVisionModelWithProjection
from diffusers import UnCLIPImageVariationPipeline, UnCLIPPipeline
if __name__ == "__main__":
__a = argparse.ArgumentParser()
parser.add_argument('--dump_path', default=None, type=str, require... | 30 |
from typing import List, Union
import numpy as np
from ..utils import add_end_docstrings, is_torch_available, is_vision_available, logging, requires_backends
from .base import PIPELINE_INIT_ARGS, Pipeline
if is_vision_available():
from PIL import Image
from ..image_utils import load_... | 24 | 0 |
'''simple docstring'''
import argparse
import torch
# Step 1. clone https://github.com/microsoft/unilm
# Step 2. git checkout to https://github.com/microsoft/unilm/commit/b94ec76c36f02fb2b0bf0dcb0b8554a2185173cd
# Step 3. cd unilm
# Step 4. ln -s $(realpath wavlm/modules.py) ./ # create simlink
# import classes
... | 31 |
from datasets.utils.patching import _PatchedModuleObj, patch_submodule
from . import _test_patching
def lowerCamelCase__ ( ) -> Any:
import os as original_os
from os import path as original_path
from os import rename as original_rename
from os.path import dir... | 24 | 0 |
import logging
import os
from typing import Dict, List, Optional, Union
import torch
import torch.nn as nn
from accelerate.utils.imports import (
is_abit_bnb_available,
is_abit_bnb_available,
is_bnb_available,
)
from ..big_modeling import dispatch_model, init_empty_weights
from .datac... | 32 |
import logging
import os
import sys
from dataclasses import dataclass, field
from typing import Optional
from seqaseq_trainer import SeqaSeqTrainer
from seqaseq_training_args import SeqaSeqTrainingArguments
import transformers
from transformers import (
AutoConfig,
AutoModelForSeqaSeqL... | 24 | 0 |
"""simple docstring"""
import unittest
from transformers import is_torch_available
from transformers.testing_utils import require_sentencepiece, require_tokenizers, require_torch, slow
if is_torch_available():
import torch
from transformers import XLMRobertaModel
... | 33 |
from math import pi
def lowerCamelCase__ ( snake_case_ : int , snake_case_ : int ) -> float:
return 2 * pi * radius * (angle / 360)
if __name__ == "__main__":
print(arc_length(90, 10))
| 24 | 0 |
'''simple docstring'''
from __future__ import annotations
def snake_case_ (_a : float , _a : float , _a : float , ):
if (electron_conc, hole_conc, intrinsic_conc).count(0 ) != 1:
raise ValueError('''You cannot supply more or less than 2 value... | 34 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
snake_case_ = logging.get_logger(__name__)
snake_case_ = {
'sayakpaul/vit-msn-base': 'https://huggingface.co/sayakpaul/vit-msn-base/resolve/main/config.json',
# See all ViT MSN models at https://hug... | 24 | 0 |
'''simple docstring'''
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_config... | 35 |
import random
import unittest
import numpy as np
from diffusers import (
DPMSolverMultistepScheduler,
EulerAncestralDiscreteScheduler,
EulerDiscreteScheduler,
LMSDiscreteScheduler,
OnnxStableDiffusionImgaImgPipeline,
PNDMScheduler,
)
from diffusers.utils import floats_... | 24 | 0 |
import logging
import math
from functools import partial
from typing import Any, Callable, Dict, Iterable, List, Optional, Sequence, Tuple, Union
import torch
from .tensor_utils import tensor_tree_map, tree_map
def A ( _lowerCamelCase ):
'''simple docstring'''
_lowerCAmelC... | 36 |
import logging
import os
from dataclasses import dataclass
from typing import List, Optional, Union
import tqdm
from filelock import FileLock
from transformers import (
BartTokenizer,
BartTokenizerFast,
DataProcessor,
PreTrainedTokenizer,
RobertaTokenizer,
RobertaToke... | 24 | 0 |
'''simple docstring'''
from datetime import datetime as dt
import os
from github import Github
_lowerCAmelCase = [
'''good first issue''',
'''good second issue''',
'''good difficult issue''',
'''feature request''',
'''new model''',
'''wip''',
]
def _SCREAMING_SNAKE_CASE... | 37 |
import warnings
from ...processing_utils import ProcessorMixin
from ...tokenization_utils_base import BatchEncoding
class SCREAMING_SNAKE_CASE__ ( _UpperCAmelCase ):
A_ : List[str] = ['image_processor', 'tokenizer']
A_ : Optional[Any] = 'CLI... | 24 | 0 |
import copy
import re
class _SCREAMING_SNAKE_CASE :
snake_case__ : str = """hp"""
snake_case__ : Dict = {}
snake_case__ : Tuple = None
@classmethod
def _A ( cls : Union[str, Any] , __lowerCamelCase : Optional[Any] , __low... | 38 |
import os
import unittest
from huggingface_hub.utils import are_progress_bars_disabled
import transformers.models.bart.tokenization_bart
from transformers import logging
from transformers.testing_utils import CaptureLogger, mockenv, mockenv_context
from transformers.utils.logging import disable_pr... | 24 | 0 |
from collections import OrderedDict
from typing import Mapping
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
_a = logging.get_logger(__name__)
_a = {
'''junnyu/roformer_chinese_small''': '''https://huggingfa... | 39 |
import os
import unittest
from transformers.models.cpmant.tokenization_cpmant import VOCAB_FILES_NAMES, CpmAntTokenizer
from transformers.testing_utils import require_jieba, tooslow
from ...test_tokenization_common import TokenizerTesterMixin
@require_jieba
class SCREAMING_SNAKE_CASE__ ( ... | 24 | 0 |
"""simple docstring"""
import random
import timeit
from functools import wraps
from typing import Callable, Optional
from ..configuration_utils import PretrainedConfig
from ..models.auto.modeling_tf_auto import TF_MODEL_MAPPING, TF_MODEL_WITH_LM_HEAD_MAPPING
from ..utils import is_pyanvml_a... | 40 |
import copy
import inspect
import unittest
from transformers import AutoBackbone
from transformers.configuration_utils import PretrainedConfig
from transformers.testing_utils import require_timm, require_torch, torch_device
from transformers.utils.import_utils import is_torch_available
from ...te... | 24 | 0 |
'''simple docstring'''
from transformers import BertTokenizer, EncoderDecoderModel, SeqaSeqTrainer, SeqaSeqTrainingArguments
from transformers.testing_utils import TestCasePlus, require_torch, slow
from transformers.utils import is_datasets_available
if is_datasets_available():
i... | 41 |
import os
import pytest
from transformers.dynamic_module_utils import get_imports
snake_case_ = '\nimport os\n'
snake_case_ = '\ndef foo():\n import os\n return False\n'
snake_case_ = '\ndef foo():\n def bar():\n if True:\n import os\n return... | 24 | 0 |
'''simple docstring'''
import argparse
import json
import os
import fairseq
import torch
from fairseq.data import Dictionary
# Register SEW's fairseq modules
from sew_asapp import tasks # noqa: F401
from transformers import (
SEWConfig,
SEWForCTC,
SEWModel,
WavaVecaCTCTokenizer,
WavaVeca... | 42 |
import socket
def lowerCamelCase__ ( ) -> Any:
__snake_case = socket.socket(socket.AF_INET , socket.SOCK_STREAM )
__snake_case = socket.gethostname()
__snake_case = 1_2312
sock.connect((host, port) ... | 24 | 0 |
# Copyright 2023 The HuggingFace Team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicabl... | 43 |
from __future__ import annotations
def lowerCamelCase__ ( snake_case_ : list[int] ) -> list[int]: # This function is recursive
__snake_case = len(snake_case_ )
# If the array contains only one element, we return it (it's the stop condition o... | 24 | 0 |
"""simple docstring"""
from ...configuration_utils import PretrainedConfig
from ...utils import logging
_a : str = logging.get_logger(__name__)
_a : Optional[Any] = {
'sayakpaul/vit-msn-base': 'https://huggingface.co/sayakpaul/vit-msn-base/resolve/main/config.json',
# ... | 44 |
import unittest
from transformers import LiltConfig, is_torch_available
from transformers.testing_utils import require_torch, slow, torch_device
from ...generation.test_utils import GenerationTesterMixin
from ...test_configuration_common import ConfigTester
from ...test_modeling_common import Model... | 24 | 0 |
"""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/lice... | 45 |
import unittest
from transformers import MODEL_FOR_DOCUMENT_QUESTION_ANSWERING_MAPPING, AutoTokenizer, is_vision_available
from transformers.pipelines import pipeline
from transformers.pipelines.document_question_answering import apply_tesseract
from transformers.testing_utils import (
is_pipelin... | 24 | 0 |
"""simple docstring"""
from math import isclose, sqrt
def UpperCAmelCase__ ( SCREAMING_SNAKE_CASE : float , SCREAMING_SNAKE_CASE : float , SCREAMING_SNAKE_CASE : float ):
'''simple docstring'''
lowerCAmelCase = ... | 46 |
from __future__ import annotations
def lowerCamelCase__ ( snake_case_ : list[int] , snake_case_ : int ) -> list[list[int]]:
__snake_case = []
__snake_case = []
__snake_case = 0
__snake_case ... | 24 | 0 |
'''simple docstring'''
def _lowerCAmelCase ( ) -> list[list[int]]:
"""simple docstring"""
return [list(range(10_00 - i , -10_00 - i , -1 ) ) for i in range(10_00 )]
lowerCamelCase : Optional[Any] = generate_large_matrix()
lowerCamelCase : ... | 47 |
import inspect
import unittest
from transformers import ConvNextConfig
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_backbone_common import BackboneTesterM... | 24 | 0 |
from typing import List, Optional, Union
from ...image_utils import ImageInput
from ...processing_utils import ProcessorMixin
from ...tokenization_utils_base import BatchEncoding, PaddingStrategy, PreTokenizedInput, TextInput, TruncationStrategy
from ...utils import TensorType
class UpperCame... | 48 |
def lowerCamelCase__ ( ) -> int:
return [
a * b * (1000 - a - b)
for a in range(1 , 999 )
for b in range(snake_case_ , 999 )
if (a * a + b * b == (1000 - a - b) ** 2)
][0]
if __name__ == "__main__":
print(F'... | 24 | 0 |
import inspect
import unittest
from huggingface_hub import hf_hub_download
from transformers import ASTConfig
from transformers.testing_utils import require_torch, require_torchaudio, slow, torch_device
from transformers.utils import cached_property, is_torch_available, is_torchaudio_available
from ...test_confi... | 49 |
import os
import unittest
from transformers.models.bartpho.tokenization_bartpho import VOCAB_FILES_NAMES, BartphoTokenizer
from transformers.testing_utils import get_tests_dir
from ...test_tokenization_common import TokenizerTesterMixin
snake_case_ = get_tests_dir('fixtures/test_sentencepi... | 24 | 0 |
from transformers import DistilBertTokenizer, DistilBertTokenizerFast
from transformers.testing_utils import require_tokenizers, slow
from ..bert.test_tokenization_bert import BertTokenizationTest
@require_tokenizers
class lowerCAmelCase ( __UpperCamelCase ):
UpperCAmelCase__ = Dist... | 50 |
def lowerCamelCase__ ( snake_case_ : int ) -> int:
if not isinstance(snake_case_ , snake_case_ ) or number < 0:
raise ValueError('''Input must be a non-negative integer''' )
__snake_case = 0
while number:
# This way we... | 24 | 0 |
def A (__A : int , __A : int ) -> bool:
"""simple docstring"""
return numa ^ numa < 0
if __name__ == "__main__":
import doctest
doctest.testmod()
| 51 |
from math import loga
def lowerCamelCase__ ( snake_case_ : int ) -> int:
if a < 0:
raise ValueError('''Input value must be a positive integer''' )
elif isinstance(snake_case_ , snake_case_ ):
raise TypeError('''Input value mus... | 24 | 0 |
def A_ ( _lowerCAmelCase ) -> str:
UpperCamelCase : Tuple = 0
# if input_string is "aba" than new_input_string become "a|b|a"
UpperCamelCase : Any = ""
UpperCamelCase : List[Any] = ""
# append each character + "|" in new_string for range(0, length-1)... | 52 |
from typing import List, Union
import numpy as np
from ..utils import add_end_docstrings, is_torch_available, is_vision_available, logging, requires_backends
from .base import PIPELINE_INIT_ARGS, Pipeline
if is_vision_available():
from PIL import Image
from ..image_utils import load_... | 24 | 0 |
'''simple docstring'''
import os
from typing import List, Optional, Union
from ...image_processing_utils import BatchFeature
from ...image_utils import ImageInput
from ...processing_utils import ProcessorMixin
from ...tokenization_utils_base import PaddingStrategy, PreTokenizedInput, TextInput, TruncationStrateg... | 53 |
from datasets.utils.patching import _PatchedModuleObj, patch_submodule
from . import _test_patching
def lowerCamelCase__ ( ) -> Any:
import os as original_os
from os import path as original_path
from os import rename as original_rename
from os.path import dir... | 24 | 0 |
"""simple docstring"""
def UpperCAmelCase__ (lowerCAmelCase_ ):
'''simple docstring'''
__SCREAMING_SNAKE_CASE = 0
__SCREAMING_SNAKE_CASE = len(lowerCAmelCase_ )
for i in range(n - 1 ):
for j in range(i + 1 , lowerCAmelCase_ ):
... | 54 |
import logging
import os
import sys
from dataclasses import dataclass, field
from typing import Optional
from seqaseq_trainer import SeqaSeqTrainer
from seqaseq_training_args import SeqaSeqTrainingArguments
import transformers
from transformers import (
AutoConfig,
AutoModelForSeqaSeqL... | 24 | 0 |
'''simple docstring'''
a_ : str = """
# Transformers installation
! pip install transformers datasets
# To install from source instead of the last release, comment the command above and uncomment the following one.
# ! pip install git+https://github.com/huggingface/transformers.git
"""
a_ : Any... | 55 |
from math import pi
def lowerCamelCase__ ( snake_case_ : int , snake_case_ : int ) -> float:
return 2 * pi * radius * (angle / 360)
if __name__ == "__main__":
print(arc_length(90, 10))
| 24 | 0 |
'''simple docstring'''
import math
from collections.abc import Iterator
from itertools import takewhile
def __magic_name__ ( __UpperCAmelCase ) -> bool:
'''simple docstring'''
if 1 < number < 4:
# 2 and 3 are primes
return True
elif number < 2 or number % 2 == 0 or... | 56 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
snake_case_ = logging.get_logger(__name__)
snake_case_ = {
'sayakpaul/vit-msn-base': 'https://huggingface.co/sayakpaul/vit-msn-base/resolve/main/config.json',
# See all ViT MSN models at https://hug... | 24 | 0 |
"""simple docstring"""
class _UpperCamelCase ( lowerCAmelCase__ ):
'''simple docstring'''
pass
class _UpperCamelCase ( lowerCAmelCase__ ):
'''simple docstring'''
pass
class _UpperCamelCase :
'''simple docstring'''
def __init__( self ... | 57 |
import random
import unittest
import numpy as np
from diffusers import (
DPMSolverMultistepScheduler,
EulerAncestralDiscreteScheduler,
EulerDiscreteScheduler,
LMSDiscreteScheduler,
OnnxStableDiffusionImgaImgPipeline,
PNDMScheduler,
)
from diffusers.utils import floats_... | 24 | 0 |
'''simple docstring'''
from __future__ import annotations
import math
lowercase_ = """2020.9.26"""
lowercase_ = """xcodz-dot, cclaus, dhruvmanila"""
def lowerCamelCase ( __lowerCamelCase : float , __lowerCamelCase : float , __lowerCamelCase : float , ... | 58 |
import logging
import os
from dataclasses import dataclass
from typing import List, Optional, Union
import tqdm
from filelock import FileLock
from transformers import (
BartTokenizer,
BartTokenizerFast,
DataProcessor,
PreTrainedTokenizer,
RobertaTokenizer,
RobertaToke... | 24 | 0 |
def UpperCamelCase ( __lowerCamelCase : int ):
snake_case : Union[str, Any] = len(__lowerCamelCase )
while cur > 1:
# Find the maximum number in arr
snake_case : Dict = arr.index(max(arr[0:cur] ) )
... | 59 |
import warnings
from ...processing_utils import ProcessorMixin
from ...tokenization_utils_base import BatchEncoding
class SCREAMING_SNAKE_CASE__ ( _UpperCAmelCase ):
A_ : List[str] = ['image_processor', 'tokenizer']
A_ : Optional[Any] = 'CLI... | 24 | 0 |
"""simple docstring"""
def _snake_case ( _snake_case : int = 1000 ):
return sum(2 * a * ((a - 1) // 2) for a in range(3 , n + 1 ) )
if __name__ == "__main__":
print(solution())
| 60 |
import os
import unittest
from huggingface_hub.utils import are_progress_bars_disabled
import transformers.models.bart.tokenization_bart
from transformers import logging
from transformers.testing_utils import CaptureLogger, mockenv, mockenv_context
from transformers.utils.logging import disable_pr... | 24 | 0 |
"""simple docstring"""
import inspect
import unittest
from huggingface_hub import hf_hub_download
from transformers import ASTConfig
from transformers.testing_utils import require_torch, require_torchaudio, slow, torch_device
from transformers.utils import cached_property, is_torch_available, is_torchaudio_avai... | 61 |
import os
import unittest
from transformers.models.cpmant.tokenization_cpmant import VOCAB_FILES_NAMES, CpmAntTokenizer
from transformers.testing_utils import require_jieba, tooslow
from ...test_tokenization_common import TokenizerTesterMixin
@require_jieba
class SCREAMING_SNAKE_CASE__ ( ... | 24 | 0 |
import argparse
import json
import subprocess
def _UpperCAmelCase ( SCREAMING_SNAKE_CASE__ : List[str] , SCREAMING_SNAKE_CASE__ : Tuple ):
__UpperCamelCase =[]
__UpperCamelCase =(
F'curl -H "Accept: application/vnd.github+json" -H "Authorizatio... | 62 |
import copy
import inspect
import unittest
from transformers import AutoBackbone
from transformers.configuration_utils import PretrainedConfig
from transformers.testing_utils import require_timm, require_torch, torch_device
from transformers.utils.import_utils import is_torch_available
from ...te... | 24 | 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, TrainingJobAnalyti... | 63 |
import os
import pytest
from transformers.dynamic_module_utils import get_imports
snake_case_ = '\nimport os\n'
snake_case_ = '\ndef foo():\n import os\n return False\n'
snake_case_ = '\ndef foo():\n def bar():\n if True:\n import os\n return... | 24 | 0 |
"""simple docstring"""
def UpperCAmelCase__ (snake_case__ : list ):
"""simple docstring"""
if len(snake_case__ ) <= 1:
return [tuple(snake_case__ )]
_snake_case : List[Any] = []
def generate(snake_case__ : int , snake_case__... | 64 |
import socket
def lowerCamelCase__ ( ) -> Any:
__snake_case = socket.socket(socket.AF_INET , socket.SOCK_STREAM )
__snake_case = socket.gethostname()
__snake_case = 1_2312
sock.connect((host, port) ... | 24 | 0 |
import pytest
from datasets import inspect_metric, list_metrics, load_metric
@pytest.fixture
def lowerCAmelCase_ ( __A ) -> Union[str, Any]:
'''simple docstring'''
monkeypatch.setattr("datasets.utils.deprecation_utils._emitted_deprecation_warnings", set(... | 65 |
from __future__ import annotations
def lowerCamelCase__ ( snake_case_ : list[int] ) -> list[int]: # This function is recursive
__snake_case = len(snake_case_ )
# If the array contains only one element, we return it (it's the stop condition o... | 24 | 0 |
"""simple docstring"""
from collections import OrderedDict
from typing import Any, List, Mapping, Optional
from ... import PreTrainedTokenizer, TensorType, is_torch_available
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfigWithPast, PatchingSpec
from ...utils import logging
__a ... | 66 |
import unittest
from transformers import LiltConfig, is_torch_available
from transformers.testing_utils import require_torch, slow, torch_device
from ...generation.test_utils import GenerationTesterMixin
from ...test_configuration_common import ConfigTester
from ...test_modeling_common import Model... | 24 | 0 |
'''simple docstring'''
import argparse
import torch
from transformers import FunnelBaseModel, FunnelConfig, FunnelModel, load_tf_weights_in_funnel
from transformers.utils import logging
logging.set_verbosity_info()
def __lowerCAmelCase ( UpperCamelCase__ , UpperCamelCase__ , UpperCamelCase__... | 67 |
import unittest
from transformers import MODEL_FOR_DOCUMENT_QUESTION_ANSWERING_MAPPING, AutoTokenizer, is_vision_available
from transformers.pipelines import pipeline
from transformers.pipelines.document_question_answering import apply_tesseract
from transformers.testing_utils import (
is_pipelin... | 24 | 0 |
import unittest
from transformers import is_torch_available
from transformers.testing_utils import require_torch
if is_torch_available():
import torch
from transformers.activations import gelu_new, gelu_python, get_activation
@require_torch
class a__ ( unittest.TestCase ):
"""simple docstring"""
... | 68 |
from __future__ import annotations
def lowerCamelCase__ ( snake_case_ : list[int] , snake_case_ : int ) -> list[list[int]]:
__snake_case = []
__snake_case = []
__snake_case = 0
__snake_case ... | 24 | 0 |
"""simple docstring"""
from __future__ import annotations
import unittest
from transformers import BlenderbotConfig, BlenderbotTokenizer, is_tf_available
from transformers.testing_utils import require_tf, require_tokenizers, slow
from transformers.utils import cached_property
from ...test_configuration_common impo... | 69 |
import inspect
import unittest
from transformers import ConvNextConfig
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_backbone_common import BackboneTesterM... | 24 | 0 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tokenizers_available
A__ : str ={'''tokenization_herbert''': ['''HerbertTokenizer''']}
try:
if not is_tokenizers_available():
rai... | 70 |
def lowerCamelCase__ ( ) -> int:
return [
a * b * (1000 - a - b)
for a in range(1 , 999 )
for b in range(snake_case_ , 999 )
if (a * a + b * b == (1000 - a - b) ** 2)
][0]
if __name__ == "__main__":
print(F'... | 24 | 0 |
def A ( a_ ,a_ ,a_ ) -> Tuple:
if n == 0:
return 1
elif n % 2 == 1:
return (binary_exponentiation(a_ ,n - 1 ,a_ ) * a) % mod
else:
__UpperCamelCase : Dict =binary_exponentiatio... | 71 |
import os
import unittest
from transformers.models.bartpho.tokenization_bartpho import VOCAB_FILES_NAMES, BartphoTokenizer
from transformers.testing_utils import get_tests_dir
from ...test_tokenization_common import TokenizerTesterMixin
snake_case_ = get_tests_dir('fixtures/test_sentencepi... | 24 | 0 |
"""simple docstring"""
import argparse
import os
import torch
from diffusers import (
CMStochasticIterativeScheduler,
ConsistencyModelPipeline,
UNetaDModel,
)
lowerCAmelCase__ = {
'''sample_size''': 32,
'''in_channels''': 3,
'''out_channels''': 3,
'''layers_per_block'... | 72 |
def lowerCamelCase__ ( snake_case_ : int ) -> int:
if not isinstance(snake_case_ , snake_case_ ) or number < 0:
raise ValueError('''Input must be a non-negative integer''' )
__snake_case = 0
while number:
# This way we... | 24 | 0 |
import math
from typing import Dict, Iterable, List, Optional, Tuple, Union
import numpy as np
from ...image_processing_utils import BaseImageProcessor, BatchFeature, get_size_dict
from ...image_transforms import normalize, rescale, resize, to_channel_dimension_format
from ...image_utils import (
IMAG... | 73 |
from math import loga
def lowerCamelCase__ ( snake_case_ : int ) -> int:
if a < 0:
raise ValueError('''Input value must be a positive integer''' )
elif isinstance(snake_case_ , snake_case_ ):
raise TypeError('''Input value mus... | 24 | 0 |
"""simple docstring"""
from ...configuration_utils import PretrainedConfig
from ...utils import logging
_lowercase = logging.get_logger(__name__)
_lowercase = {
'''google/switch-base-8''': '''https://huggingface.co/google/switch-base-8/blob/main/config.json''',
}
class lowerCAm... | 74 |
from typing import List, Union
import numpy as np
from ..utils import add_end_docstrings, is_torch_available, is_vision_available, logging, requires_backends
from .base import PIPELINE_INIT_ARGS, Pipeline
if is_vision_available():
from PIL import Image
from ..image_utils import load_... | 24 | 0 |
'''simple docstring'''
import os
import socket
from contextlib import contextmanager
import torch
from ..commands.config.default import write_basic_config # noqa: F401
from ..state import PartialState
from .dataclasses import DistributedType
from .imports import is_deepspeed_available, is_tpu_available
from... | 75 |
from datasets.utils.patching import _PatchedModuleObj, patch_submodule
from . import _test_patching
def lowerCamelCase__ ( ) -> Any:
import os as original_os
from os import path as original_path
from os import rename as original_rename
from os.path import dir... | 24 | 0 |
import math
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 SchedulerMixin, SchedulerOutput
class _UpperCamelCase ( __A , __A ):
'''simple docstring'''
... | 76 |
import logging
import os
import sys
from dataclasses import dataclass, field
from typing import Optional
from seqaseq_trainer import SeqaSeqTrainer
from seqaseq_training_args import SeqaSeqTrainingArguments
import transformers
from transformers import (
AutoConfig,
AutoModelForSeqaSeqL... | 24 | 0 |
"""simple docstring"""
import json
import os
from dataclasses import dataclass
from functools import partial
from typing import Callable
import flax.linen as nn
import jax
import jax.numpy as jnp
import joblib
import optax
import wandb
from flax import jax_utils, struct, traverse_util
from flax.serialization impo... | 77 |
from math import pi
def lowerCamelCase__ ( snake_case_ : int , snake_case_ : int ) -> float:
return 2 * pi * radius * (angle / 360)
if __name__ == "__main__":
print(arc_length(90, 10))
| 24 | 0 |
"""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, Resi... | 78 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
snake_case_ = logging.get_logger(__name__)
snake_case_ = {
'sayakpaul/vit-msn-base': 'https://huggingface.co/sayakpaul/vit-msn-base/resolve/main/config.json',
# See all ViT MSN models at https://hug... | 24 | 0 |
'''simple docstring'''
import gc
import random
import unittest
import numpy as np
import torch
from transformers import CLIPTextConfig, CLIPTextModel, CLIPTokenizer
from diffusers import AutoencoderKL, CycleDiffusionPipeline, DDIMScheduler, UNetaDConditionModel
from diffusers.utils import floats_tensor, lo... | 79 |
import random
import unittest
import numpy as np
from diffusers import (
DPMSolverMultistepScheduler,
EulerAncestralDiscreteScheduler,
EulerDiscreteScheduler,
LMSDiscreteScheduler,
OnnxStableDiffusionImgaImgPipeline,
PNDMScheduler,
)
from diffusers.utils import floats_... | 24 | 0 |
'''simple docstring'''
from pathlib import Path
import cva
import numpy as np
from matplotlib import pyplot as plt
def _UpperCamelCase ( __A , __A , __A , __A , __A ) -> np.ndarray:
'''simple docstring'''
UpperCamelCase__ = c... | 80 |
import logging
import os
from dataclasses import dataclass
from typing import List, Optional, Union
import tqdm
from filelock import FileLock
from transformers import (
BartTokenizer,
BartTokenizerFast,
DataProcessor,
PreTrainedTokenizer,
RobertaTokenizer,
RobertaToke... | 24 | 0 |
"""simple docstring"""
import math
from typing import Callable, List, Optional, Union
import numpy as np
import PIL
import torch
from PIL import Image
from transformers import CLIPTextModel, CLIPTokenizer
from diffusers.models import AutoencoderKL, UNetaDConditionModel
from diffusers.pi... | 81 |
import warnings
from ...processing_utils import ProcessorMixin
from ...tokenization_utils_base import BatchEncoding
class SCREAMING_SNAKE_CASE__ ( _UpperCAmelCase ):
A_ : List[str] = ['image_processor', 'tokenizer']
A_ : Optional[Any] = 'CLI... | 24 | 0 |
import inspect
import re
from transformers.utils import direct_transformers_import
# All paths are set with the intent you should run this script from the root of the repo with the command
# python utils/check_config_docstrings.py
A__ = """src/transformers"""
# This is to make sure the transformers... | 82 |
import os
import unittest
from huggingface_hub.utils import are_progress_bars_disabled
import transformers.models.bart.tokenization_bart
from transformers import logging
from transformers.testing_utils import CaptureLogger, mockenv, mockenv_context
from transformers.utils.logging import disable_pr... | 24 | 0 |
'''simple docstring'''
from __future__ import annotations
from statistics import mean
def A__ ( UpperCAmelCase_ , UpperCAmelCase_ , UpperCAmelCase_ ):
_UpperCamelCase : List[Any] = [0] * no_of_processes
_UpperCamelCase : Union[str, Any] = [0] * no_of_process... | 83 |
import os
import unittest
from transformers.models.cpmant.tokenization_cpmant import VOCAB_FILES_NAMES, CpmAntTokenizer
from transformers.testing_utils import require_jieba, tooslow
from ...test_tokenization_common import TokenizerTesterMixin
@require_jieba
class SCREAMING_SNAKE_CASE__ ( ... | 24 | 0 |
"""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/lice... | 84 |
import copy
import inspect
import unittest
from transformers import AutoBackbone
from transformers.configuration_utils import PretrainedConfig
from transformers.testing_utils import require_timm, require_torch, torch_device
from transformers.utils.import_utils import is_torch_available
from ...te... | 24 | 0 |
'''simple docstring'''
def UpperCamelCase_( snake_case : int ):
'''simple docstring'''
return 1 if digit in (0, 1) else (digit * factorial(digit - 1 ))
def UpperCamelCase_( snake_case : int ):
'''simple docstring'''
snak... | 85 |
import os
import pytest
from transformers.dynamic_module_utils import get_imports
snake_case_ = '\nimport os\n'
snake_case_ = '\ndef foo():\n import os\n return False\n'
snake_case_ = '\ndef foo():\n def bar():\n if True:\n import os\n return... | 24 | 0 |
"""simple docstring"""
# flake8: noqa
# Lint as: python3
lowerCamelCase__ = [
"""VerificationMode""",
"""Version""",
"""disable_progress_bar""",
"""enable_progress_bar""",
"""is_progress_bar_enabled""",
"""experimental""",
]
from .info_utils import VerificationMode
from .logging... | 86 |
import socket
def lowerCamelCase__ ( ) -> Any:
__snake_case = socket.socket(socket.AF_INET , socket.SOCK_STREAM )
__snake_case = socket.gethostname()
__snake_case = 1_2312
sock.connect((host, port) ... | 24 | 0 |
# Author: OMKAR PATHAK, Nwachukwu Chidiebere
# Use a Python dictionary to construct the graph.
from __future__ import annotations
from pprint import pformat
from typing import Generic, TypeVar
UpperCamelCase = TypeVar('''T''')
class snake_case_ ( Generic[T] ):
... | 87 |
from __future__ import annotations
def lowerCamelCase__ ( snake_case_ : list[int] ) -> list[int]: # This function is recursive
__snake_case = len(snake_case_ )
# If the array contains only one element, we return it (it's the stop condition o... | 24 | 0 |
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.import_utils... | 88 |
import unittest
from transformers import LiltConfig, is_torch_available
from transformers.testing_utils import require_torch, slow, torch_device
from ...generation.test_utils import GenerationTesterMixin
from ...test_configuration_common import ConfigTester
from ...test_modeling_common import Model... | 24 | 0 |
'''simple docstring'''
from ..utils import DummyObject, requires_backends
class __magic_name__ ( metaclass=_UpperCamelCase ):
lowerCAmelCase : str = ['note_seq']
def __init__( self : Tuple ,*_UpperCAmelCase : List[Any] ,**_UpperCAmelCase... | 89 |
import unittest
from transformers import MODEL_FOR_DOCUMENT_QUESTION_ANSWERING_MAPPING, AutoTokenizer, is_vision_available
from transformers.pipelines import pipeline
from transformers.pipelines.document_question_answering import apply_tesseract
from transformers.testing_utils import (
is_pipelin... | 24 | 0 |
from math import pi, sqrt, tan
def lowerCamelCase_ ( UpperCamelCase__ : float ) -> float:
"""simple docstring"""
if side_length < 0:
raise ValueError('surface_area_cube() only accepts non-negative values' )
return 6 * s... | 90 |
from __future__ import annotations
def lowerCamelCase__ ( snake_case_ : list[int] , snake_case_ : int ) -> list[list[int]]:
__snake_case = []
__snake_case = []
__snake_case = 0
__snake_case ... | 24 | 0 |
"""simple docstring"""
from __future__ import annotations
import math
import numpy as np
from numpy.linalg import norm
def _A (__a , __a ) -> float:
"""simple docstring"""
return math.sqrt(sum(pow(a - b , 2 ) for a, b in zip(__a , __a ) ... | 91 |
import inspect
import unittest
from transformers import ConvNextConfig
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_backbone_common import BackboneTesterM... | 24 | 0 |
import requests
from bsa import BeautifulSoup
def _a ( SCREAMING_SNAKE_CASE_ : str = "https://www.worldometers.info/coronavirus" ):
__lowerCAmelCase = BeautifulSoup(requests.get(SCREAMING_SNAKE_CASE_ ).text , "html.parser" )
__lowerCAmelCase ... | 92 |
def lowerCamelCase__ ( ) -> int:
return [
a * b * (1000 - a - b)
for a in range(1 , 999 )
for b in range(snake_case_ , 999 )
if (a * a + b * b == (1000 - a - b) ** 2)
][0]
if __name__ == "__main__":
print(F'... | 24 | 0 |
'''simple docstring'''
import json
import os
import tempfile
from transformers.testing_utils import check_json_file_has_correct_format
class lowerCAmelCase__ :
lowerCAmelCase_ = None
def _snake_case ( self ):
"""simple docst... | 93 |
import os
import unittest
from transformers.models.bartpho.tokenization_bartpho import VOCAB_FILES_NAMES, BartphoTokenizer
from transformers.testing_utils import get_tests_dir
from ...test_tokenization_common import TokenizerTesterMixin
snake_case_ = get_tests_dir('fixtures/test_sentencepi... | 24 | 0 |
def __lowerCamelCase ( UpperCAmelCase_ : list , UpperCAmelCase_ : int , UpperCAmelCase_ : int = 0 , UpperCAmelCase_ : int = 0 ):
"""simple docstring"""
a :List[str] = right or len(UpperCAmelCase_ ) - 1
if left > right:
... | 94 |
def lowerCamelCase__ ( snake_case_ : int ) -> int:
if not isinstance(snake_case_ , snake_case_ ) or number < 0:
raise ValueError('''Input must be a non-negative integer''' )
__snake_case = 0
while number:
# This way we... | 24 | 0 |
import logging
import os
import sys
from dataclasses import dataclass, field
from importlib import import_module
from typing import Dict, List, Optional, Tuple
import numpy as np
from seqeval.metrics import accuracy_score, fa_score, precision_score, recall_score
from torch import nn
from utils_ne... | 95 |
from math import loga
def lowerCamelCase__ ( snake_case_ : int ) -> int:
if a < 0:
raise ValueError('''Input value must be a positive integer''' )
elif isinstance(snake_case_ , snake_case_ ):
raise TypeError('''Input value mus... | 24 | 0 |
"""simple docstring"""
def _snake_case ( lowercase__ ):
_lowerCamelCase : Optional[Any] = 1
_lowerCamelCase : Tuple = 2
while i * i <= n:
_lowerCamelCase : Optional[int] = 0
while n % i == 0:
n //= i
... | 96 |
from typing import List, Union
import numpy as np
from ..utils import add_end_docstrings, is_torch_available, is_vision_available, logging, requires_backends
from .base import PIPELINE_INIT_ARGS, Pipeline
if is_vision_available():
from PIL import Image
from ..image_utils import load_... | 24 | 0 |
'''simple docstring'''
import logging
import os
import threading
import time
try:
import warnings
except ImportError:
__snake_case = None
try:
import msvcrt
except ImportError:
__snake_case = None
try:
import fcntl
except ImportError:
__snake_case = Non... | 97 |
from datasets.utils.patching import _PatchedModuleObj, patch_submodule
from . import _test_patching
def lowerCamelCase__ ( ) -> Any:
import os as original_os
from os import path as original_path
from os import rename as original_rename
from os.path import dir... | 24 | 0 |
"""simple docstring"""
import gc
import random
import unittest
import numpy as np
import torch
from PIL import Image
from transformers import CLIPTextConfig, CLIPTextModel, CLIPTokenizer
from diffusers import AutoencoderKL, PNDMScheduler, StableDiffusionInpaintPipeline, UNetaDConditionModel
from diffusers.utils... | 98 |
import logging
import os
import sys
from dataclasses import dataclass, field
from typing import Optional
from seqaseq_trainer import SeqaSeqTrainer
from seqaseq_training_args import SeqaSeqTrainingArguments
import transformers
from transformers import (
AutoConfig,
AutoModelForSeqaSeqL... | 24 | 0 |
import doctest
import logging
import os
import unittest
from pathlib import Path
from typing import List, Union
import transformers
from transformers.testing_utils import require_tf, require_torch, slow
lowercase : List[Any] = logging.getLogger()
@unittest.skip('''Temporarily disable t... | 99 |
from math import pi
def lowerCamelCase__ ( snake_case_ : int , snake_case_ : int ) -> float:
return 2 * pi * radius * (angle / 360)
if __name__ == "__main__":
print(arc_length(90, 10))
| 24 | 0 |
"""simple docstring"""
import os
from collections import namedtuple
import pytest
from datasets import ClassLabel, Features, Sequence, Value
from datasets.commands.test import TestCommand
from datasets.info import DatasetInfo, DatasetInfosDict
__magic_name__ = namedtuple(
"_TestCommandArgs",
[... | 100 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
snake_case_ = logging.get_logger(__name__)
snake_case_ = {
'sayakpaul/vit-msn-base': 'https://huggingface.co/sayakpaul/vit-msn-base/resolve/main/config.json',
# See all ViT MSN models at https://hug... | 24 | 0 |
import gc
import unittest
import numpy as np
import torch
from diffusers import AutoencoderKL, DDIMScheduler, DiTPipeline, DPMSolverMultistepScheduler, TransformeraDModel
from diffusers.utils import is_xformers_available, load_numpy, slow, torch_device
from diffusers.utils.testing_utils import enable_full_determinis... | 101 |
import random
import unittest
import numpy as np
from diffusers import (
DPMSolverMultistepScheduler,
EulerAncestralDiscreteScheduler,
EulerDiscreteScheduler,
LMSDiscreteScheduler,
OnnxStableDiffusionImgaImgPipeline,
PNDMScheduler,
)
from diffusers.utils import floats_... | 24 | 0 |
"""simple docstring"""
import functools
from typing import Any
def lowercase ( _snake_case : str , _snake_case : list[str] ) ->bool:
"""simple docstring"""
if not isinstance(_snake_case , _snake_case ) or len(_snake_case ) == 0:
raise ValueEr... | 102 |
import logging
import os
from dataclasses import dataclass
from typing import List, Optional, Union
import tqdm
from filelock import FileLock
from transformers import (
BartTokenizer,
BartTokenizerFast,
DataProcessor,
PreTrainedTokenizer,
RobertaTokenizer,
RobertaToke... | 24 | 0 |
import os
import unittest
from transformers.models.bartpho.tokenization_bartpho import VOCAB_FILES_NAMES, BartphoTokenizer
from transformers.testing_utils import get_tests_dir
from ...test_tokenization_common import TokenizerTesterMixin
A__ : Dict = get_tests_dir('''fixtures/test_sentencepiece_bpe.... | 103 |
import warnings
from ...processing_utils import ProcessorMixin
from ...tokenization_utils_base import BatchEncoding
class SCREAMING_SNAKE_CASE__ ( _UpperCAmelCase ):
A_ : List[str] = ['image_processor', 'tokenizer']
A_ : Optional[Any] = 'CLI... | 24 | 0 |
'''simple docstring'''
import argparse
import fairseq
import torch
from transformers import UniSpeechSatConfig, UniSpeechSatForCTC, UniSpeechSatForPreTraining, logging
logging.set_verbosity_info()
lowerCAmelCase__ = logging.get_logger(__name__)
lowerCAmelCase__ = {
'''post_extract_p... | 104 |
import os
import unittest
from huggingface_hub.utils import are_progress_bars_disabled
import transformers.models.bart.tokenization_bart
from transformers import logging
from transformers.testing_utils import CaptureLogger, mockenv, mockenv_context
from transformers.utils.logging import disable_pr... | 24 | 0 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_tf_available,
is_tokenizers_available,
is_torch_available,
)
a : str = {
'''configuration_deberta''': ['''DEBERTA_PRETRAI... | 105 |
import os
import unittest
from transformers.models.cpmant.tokenization_cpmant import VOCAB_FILES_NAMES, CpmAntTokenizer
from transformers.testing_utils import require_jieba, tooslow
from ...test_tokenization_common import TokenizerTesterMixin
@require_jieba
class SCREAMING_SNAKE_CASE__ ( ... | 24 | 0 |
"""simple docstring"""
from __future__ import annotations
__UpperCamelCase : Dict = 1.6021e-19 # units = C
def __SCREAMING_SNAKE_CASE ( A_ , A_ , A_ , ):
if (conductivity, electron_conc, mobility).count(0 ) != 1:
raise ValueError('''You cannot supply mo... | 106 |
import copy
import inspect
import unittest
from transformers import AutoBackbone
from transformers.configuration_utils import PretrainedConfig
from transformers.testing_utils import require_timm, require_torch, torch_device
from transformers.utils.import_utils import is_torch_available
from ...te... | 24 | 0 |
from math import sqrt
def __magic_name__ ( A : int ):
'''simple docstring'''
a = 0
for i in range(1, int(sqrt(A ) + 1 ) ):
if n % i == 0 and i != sqrt(A ):
total += i + n // i
elif i == sqrt(A ):
total += i
return total - n
... | 107 |
import os
import pytest
from transformers.dynamic_module_utils import get_imports
snake_case_ = '\nimport os\n'
snake_case_ = '\ndef foo():\n import os\n return False\n'
snake_case_ = '\ndef foo():\n def bar():\n if True:\n import os\n return... | 24 | 0 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tf_available, is_torch_available
lowerCAmelCase__ = {
'''configuration_ctrl''': ['''CTRL_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''CTRLConfig'''],
'''tokenization_ctrl'... | 108 |
import socket
def lowerCamelCase__ ( ) -> Any:
__snake_case = socket.socket(socket.AF_INET , socket.SOCK_STREAM )
__snake_case = socket.gethostname()
__snake_case = 1_2312
sock.connect((host, port) ... | 24 | 0 |
"""simple docstring"""
import json
from typing import List, Optional, Tuple
from tokenizers import pre_tokenizers, processors
from ...tokenization_utils_base import AddedToken, BatchEncoding
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import logging
from .tokenization_roberta impo... | 109 |
from __future__ import annotations
def lowerCamelCase__ ( snake_case_ : list[int] ) -> list[int]: # This function is recursive
__snake_case = len(snake_case_ )
# If the array contains only one element, we return it (it's the stop condition o... | 24 | 0 |
from __future__ import annotations
import json
import requests
from bsa import BeautifulSoup
from fake_useragent import UserAgent
lowerCAmelCase = {'UserAgent': UserAgent().random}
def _a ( SCREAMING_SNAKE_CASE ):
"""simple docstring"""
lowercase__ ... | 110 |
import unittest
from transformers import LiltConfig, is_torch_available
from transformers.testing_utils import require_torch, slow, torch_device
from ...generation.test_utils import GenerationTesterMixin
from ...test_configuration_common import ConfigTester
from ...test_modeling_common import Model... | 24 | 0 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
UpperCamelCase_ = {
'''configuration_luke''': ['''LUKE_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''LukeConfig'''],
'''tokenization_luke''': ['''LukeTokenizer'''],
}
try:
if n... | 345 |
import unittest
from transformers import MODEL_FOR_DOCUMENT_QUESTION_ANSWERING_MAPPING, AutoTokenizer, is_vision_available
from transformers.pipelines import pipeline
from transformers.pipelines.document_question_answering import apply_tesseract
from transformers.testing_utils import (
is_pipelin... | 24 | 0 |
"""simple docstring"""
import shutil
import tempfile
import unittest
from transformers import (
SPIECE_UNDERLINE,
AddedToken,
BatchEncoding,
NllbTokenizer,
NllbTokenizerFast,
is_torch_available,
)
from transformers.testing_utils import (
get_tests_dir,
nested_simplify,
require_... | 57 |
from __future__ import annotations
def lowerCamelCase__ ( snake_case_ : list[int] , snake_case_ : int ) -> list[list[int]]:
__snake_case = []
__snake_case = []
__snake_case = 0
__snake_case ... | 24 | 0 |
import os
from shutil import copyfile
from typing import List, Optional, Tuple
from tokenizers import processors
from ...tokenization_utils import AddedToken, BatchEncoding
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import is_sentencepiece_available, logging
if is_sent... | 30 |
import inspect
import unittest
from transformers import ConvNextConfig
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_backbone_common import BackboneTesterM... | 24 | 0 |
import argparse
from tax import checkpoints
from transformers import AutoConfig, FlaxAutoModelForSeqaSeqLM
def a_ ( _A , _A , _A ) -> Optional[int]:
"""simple docstring"""
snake_case__ = AutoConfig.from_pretrained(snake_case_ ... | 307 |
def lowerCamelCase__ ( ) -> int:
return [
a * b * (1000 - a - b)
for a in range(1 , 999 )
for b in range(snake_case_ , 999 )
if (a * a + b * b == (1000 - a - b) ** 2)
][0]
if __name__ == "__main__":
print(F'... | 24 | 0 |
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 transformers import CLIPModel, CLIP... | 308 |
import os
import unittest
from transformers.models.bartpho.tokenization_bartpho import VOCAB_FILES_NAMES, BartphoTokenizer
from transformers.testing_utils import get_tests_dir
from ...test_tokenization_common import TokenizerTesterMixin
snake_case_ = get_tests_dir('fixtures/test_sentencepi... | 24 | 0 |
'''simple docstring'''
import shutil
import tempfile
import unittest
import numpy as np
import pytest
from transformers import is_speech_available, is_vision_available
from transformers.testing_utils import require_torch
if is_vision_available():
from transformers import TvltImageProcessor
if is_speech_... | 145 |
def lowerCamelCase__ ( snake_case_ : int ) -> int:
if not isinstance(snake_case_ , snake_case_ ) or number < 0:
raise ValueError('''Input must be a non-negative integer''' )
__snake_case = 0
while number:
# This way we... | 24 | 0 |
import random
import unittest
import numpy as np
from diffusers import (
DPMSolverMultistepScheduler,
EulerAncestralDiscreteScheduler,
EulerDiscreteScheduler,
LMSDiscreteScheduler,
OnnxStableDiffusionImgaImgPipeline,
PNDMScheduler,
)
from diffusers.utils import floats_tensor
from diffusers... | 36 |
from math import loga
def lowerCamelCase__ ( snake_case_ : int ) -> int:
if a < 0:
raise ValueError('''Input value must be a positive integer''' )
elif isinstance(snake_case_ , snake_case_ ):
raise TypeError('''Input value mus... | 24 | 0 |
'''simple docstring'''
import argparse
import os
import re
import torch
from flax.traverse_util import flatten_dict
from tax import checkpoints
from transformers import (
AutoTokenizer,
PixaStructConfig,
PixaStructForConditionalGeneration,
PixaStructImageProcessor,
PixaStructProcessor,
... | 75 |
from typing import List, Union
import numpy as np
from ..utils import add_end_docstrings, is_torch_available, is_vision_available, logging, requires_backends
from .base import PIPELINE_INIT_ARGS, Pipeline
if is_vision_available():
from PIL import Image
from ..image_utils import load_... | 24 | 0 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tf_available,
is_torch_available,
)
__A : Tuple = {"configuration_unispeech": ["UNISPEECH_PRETRAINED_... | 120 |
from datasets.utils.patching import _PatchedModuleObj, patch_submodule
from . import _test_patching
def lowerCamelCase__ ( ) -> Any:
import os as original_os
from os import path as original_path
from os import rename as original_rename
from os.path import dir... | 24 | 0 |
import inspect
import re
from transformers.utils import direct_transformers_import
# All paths are set with the intent you should run this script from the root of the repo with the command
# python utils/check_config_docstrings.py
a : Union[str, Any] = 'src/transformers'
# This ... | 147 |
import logging
import os
import sys
from dataclasses import dataclass, field
from typing import Optional
from seqaseq_trainer import SeqaSeqTrainer
from seqaseq_training_args import SeqaSeqTrainingArguments
import transformers
from transformers import (
AutoConfig,
AutoModelForSeqaSeqL... | 24 | 0 |
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