code stringlengths 82 54.1k | code_codestyle int64 0 699 | style_context stringlengths 111 35.6k | style_context_codestyle int64 0 699 | label int64 0 1 |
|---|---|---|---|---|
import unittest
from pathlib import Path
from tempfile import TemporaryDirectory
from transformers import AutoConfig, TFAutoModel, is_tensorflow_text_available, is_tf_available
from transformers.models.bert.tokenization_bert import BertTokenizer
from transformers.testing_utils import require_tensorflow_text, requir... | 81 |
'''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, TrainingJobAna... | 75 | 0 |
"""simple docstring"""
def a__ ( lowerCAmelCase__ = 50 ):
UpperCAmelCase_ = [1] * (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 ):
... | 82 |
'''simple docstring'''
import math_equivalence # From: git+https://github.com/hendrycks/math.git
import datasets
UpperCamelCase__ = '''\
@article{hendrycksmath2021,
title={Measuring Mathematical Problem Solving With the MATH Dataset},
author={Dan Hendrycks
and Collin Burns
and Saura... | 75 | 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, TruncationStr... | 83 |
'''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_b... | 75 | 0 |
UpperCAmelCase = '''
# 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
'''
UpperCAmelCase = [{'''type''... | 84 |
'''simple docstring'''
import random
from typing import Any
def a__ ( lowerCAmelCase__ ) -> list[Any]:
for _ in range(len(lowerCAmelCase__ ) ):
UpperCAmelCase__ : int = random.randint(0 , len(lowerCAmelCase__ ) - 1 )
UpperCAmelCas... | 75 | 0 |
from typing import List, Optional, Union
import numpy as np
import tensorflow as tf
from .utils import logging
SCREAMING_SNAKE_CASE__ : int = logging.get_logger(__name__)
def _a ( lowercase__ : Union[tf.Tensor, np.ndarray] ):
'''simple docstring'''
... | 85 |
'''simple docstring'''
import math
def a__ ( lowerCAmelCase__ ) -> list[int]:
UpperCAmelCase__ : List[Any] = []
UpperCAmelCase__ : Dict = 2
UpperCAmelCase__ : Optional[Any] = int(math.sqrt(lowerCAmelCase__ )... | 75 | 0 |
import json
import os
from pathlib import Path
import pytest
from datasets.download.download_config import DownloadConfig
from datasets.download.download_manager import DownloadManager
from datasets.utils.file_utils import hash_url_to_filename
__a :str = 'http://www.mocksite.com/file1.txt'
... | 86 |
'''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 diff... | 75 | 0 |
import timeit
import numpy as np
import datasets
from datasets.arrow_writer import ArrowWriter
from datasets.features.features import _ArrayXD
def SCREAMING_SNAKE_CASE ( lowercase_ ) -> List[str]:
"""simple docstring"""
def wrapper(*lowercase_ , **lowercase_ ):
... | 87 |
'''simple docstring'''
import unittest
import numpy as np
import timeout_decorator # noqa
from transformers import BlenderbotConfig, is_flax_available
from transformers.testing_utils import jax_device, require_flax, slow
from ...generation.test_flax_utils import FlaxGenerationTesterMixin
from ...tes... | 75 | 0 |
"""simple docstring"""
import functools
def _snake_case ( __snake_case : str , __snake_case : str ):
"""simple docstring"""
_lowerCamelCase : int = len(__snake_case )
_lowerCamelCase : List[Any] = len(__snake_case )
... | 88 |
'''simple docstring'''
import os
import tempfile
from functools import partial
from unittest import TestCase
from unittest.mock import patch
import datasets
import datasets.config
from .utils import require_beam
class lowerCamelCase_ ( datasets.BeamBasedBuilder ):
... | 75 | 0 |
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 import logging
logging.set... | 89 |
'''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-... | 75 | 0 |
'''simple docstring'''
import unittest
from transformers import BertGenerationTokenizer
from transformers.testing_utils import get_tests_dir, require_sentencepiece, require_torch, slow
from transformers.utils import cached_property
from ...test_tokenization_common import TokenizerTesterMixin
... | 90 |
'''simple docstring'''
import argparse
import torch
from transformers import GPTaConfig, GPTaModel, load_tf_weights_in_gpta
from transformers.utils import CONFIG_NAME, WEIGHTS_NAME, logging
logging.set_verbosity_info()
def a__ ( lowerCAmelCase__ , lowerCAmelCase__ , lowerC... | 75 | 0 |
"""simple docstring"""
from math import sqrt
def _snake_case ( snake_case__ : int ):
A = 0
for i in range(1 , int(sqrt(snake_case__ ) + 1 ) ):
if n % i == 0 and i != sqrt(snake_case__ ):
total += i + n // i
elif i == sqrt(snake_case__ ):
total += i
return total - n
... | 91 |
'''simple docstring'''
from __future__ import annotations
import copy
import inspect
import unittest
import numpy as np
from transformers import is_tf_available, is_vision_available
from transformers.models.auto import get_values
from transformers.testing_utils import require_tf, slow
from transfor... | 75 | 0 |
'''simple docstring'''
import argparse
import json
import os
import fairseq
import torch
from fairseq.data import Dictionary
from transformers import (
WavaVecaConformerConfig,
WavaVecaConformerForCTC,
WavaVecaConformerForPreTraining,
WavaVecaCTCTokenizer,
WavaVecaFeatureExtractor,
Wava... | 92 |
'''simple docstring'''
import webbrowser
from sys import argv
from urllib.parse import parse_qs, quote
import requests
from bsa import BeautifulSoup
from fake_useragent import UserAgent
if __name__ == "__main__":
UpperCamelCase__ = '''%20'''.join(argv[1:]) if len(argv) > 1 else quote(str(in... | 75 | 0 |
"""simple docstring"""
from __future__ import annotations
def __A (_SCREAMING_SNAKE_CASE ) ->float:
"""simple docstring"""
if not nums:
raise ValueError('List is empty' )
return sum(_SCREAMING_SNAKE_CASE ) / len(_SCREAMING_SNAKE_CASE )
if __name__ == "__main__":
i... | 93 |
'''simple docstring'''
from pathlib import Path
import cva
import numpy as np
from matplotlib import pyplot as plt
def a__ ( lowerCAmelCase__ , lowerCAmelCase__ , lowerCAmelCase__ , lowerCAmelCase__ , lowerCAmelCase__ ) -> np.ndarray:
UpperCAmelCase__ ... | 75 | 0 |
'''simple docstring'''
def lowercase_ ( __A : Tuple ) -> Tuple:
"""simple docstring"""
lowercase : int =len(__A )
lowercase : int =sum(__A )
lowercase : List[Any] =[[False for x in range(s + 1 )] for y in range(n + 1 ... | 94 |
'''simple docstring'''
from datetime import datetime as dt
import os
from github import Github
UpperCamelCase__ = [
'''good first issue''',
'''good second issue''',
'''good difficult issue''',
'''feature request''',
'''new model''',
'''wip''',
]
def ... | 75 | 0 |
"""simple docstring"""
import re
def snake_case ( A__ ):
UpperCAmelCase_ : Optional[int] = re.compile(r"^(\+91[\-\s]?)?[0]?(91)?[789]\d{9}$" )
if match := re.search(A__ ,A__ ):
return match.string == phone
return False
if __name__ == "__main__":
print(indian_phone_... | 95 |
'''simple docstring'''
from typing import List, Optional, Tuple, Union
import torch
from ...utils import logging, randn_tensor
from ..pipeline_utils import AudioPipelineOutput, DiffusionPipeline
UpperCamelCase__ = logging.get_logger(__name__) # pylint: disable=invalid-name
class ... | 75 | 0 |
"""simple docstring"""
from __future__ import annotations
import requests
__lowerCamelCase = set(
'approved_at_utc approved_by author_flair_background_color\nauthor_flair_css_class author_flair_richtext author_flair_template_id author_fullname\nauthor_premium can_mod_post cate... | 96 |
'''simple docstring'''
from math import factorial
def a__ ( lowerCAmelCase__ , lowerCAmelCase__ , lowerCAmelCase__ ) -> float:
if successes > trials:
raise ValueError('''successes must be lower or equal to trials''' )
if trials < 0 or successes < 0:
... | 75 | 0 |
import io
import itertools
import json
from dataclasses import dataclass
from typing import Optional
import pyarrow as pa
import pyarrow.json as paj
import datasets
from datasets.table import table_cast
from datasets.utils.file_utils import readline
__a = datasets.utils.logging.get_logger(... | 97 |
'''simple docstring'''
from typing import Dict, Iterable, List, Optional, Union
import numpy as np
from ...image_processing_utils import BaseImageProcessor, BatchFeature, get_size_dict
from ...image_transforms import (
center_crop,
get_resize_output_image_size,
normalize,
rescale,
... | 75 | 0 |
'''simple docstring'''
import warnings
from ...utils import logging
from .image_processing_segformer import SegformerImageProcessor
lowercase__ : Union[str, Any] = logging.get_logger(__name__)
class __lowerCAmelCase ( __magic_name__ ):
"""simple docstring"""
... | 98 |
'''simple docstring'''
import math
def a__ ( ) -> None:
UpperCAmelCase__ : List[str] = input('''Enter message: ''' )
UpperCAmelCase__ : Any = int(input(F"""Enter key [2-{len(lowerCAmelCase__ ) - 1}]: """ ) )
UpperCAmelCase__ ... | 75 | 0 |
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
SCREAMING_SNAKE_CASE = logging.getLogger(__name__)
SCREAMING_SNAKE_CASE ... | 99 |
'''simple docstring'''
class lowerCamelCase_ :
def __init__( self : str , _A : Union[str, Any] , _A : Optional[int] ):
'''simple docstring'''
UpperCAmelCase__ : Optional[Any] = name
... | 75 | 0 |
import unittest
import numpy as np
from transformers import is_flax_available
from transformers.testing_utils import require_flax
from ..test_modeling_flax_common import ids_tensor
if is_flax_available():
import jax
import jax.numpy as jnp
from transformers.generation import (
FlaxForcedBOSToken... | 100 |
'''simple docstring'''
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
UpperCamelCase__ = '''src/transformers'... | 75 | 0 |
import argparse
from collections import OrderedDict
from pathlib import Path
import torch
from transformers import (
VisualBertConfig,
VisualBertForMultipleChoice,
VisualBertForPreTraining,
VisualBertForQuestionAnswering,
VisualBertForVisualReasoning,
)
from transformers.utils i... | 101 |
'''simple docstring'''
from ..utils import DummyObject, requires_backends
class lowerCamelCase_ ( metaclass=__a ):
lowerCAmelCase__ = ['torch', 'torchsde']
def __init__( self : Tuple , *_A : Any , **_A : Optional[Any] ... | 75 | 0 |
"""simple docstring"""
import logging
from pathlib import Path
import numpy as np
import pytorch_lightning as pl
import torch
from pytorch_lightning.callbacks import EarlyStopping, ModelCheckpoint
from pytorch_lightning.utilities import rank_zero_only
from utils_rag import save_json
def ... | 102 |
'''simple docstring'''
from ...configuration_utils import PretrainedConfig
from ...utils import logging
UpperCamelCase__ = logging.get_logger(__name__)
UpperCamelCase__ = {'''ctrl''': '''https://huggingface.co/ctrl/resolve/main/config.json'''}
class lowerCamelCase_ ( ... | 75 | 0 |
"""simple docstring"""
from .glue import GlueDataset, GlueDataTrainingArguments
from .language_modeling import (
LineByLineTextDataset,
LineByLineWithRefDataset,
LineByLineWithSOPTextDataset,
TextDataset,
TextDatasetForNextSentencePrediction,
)
from .squad import SquadDa... | 103 |
'''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, TrainingJobAna... | 75 | 0 |
"""simple docstring"""
import json
import os
import unittest
from typing import Tuple
from transformers import WavaVecaPhonemeCTCTokenizer
from transformers.models.wavaveca.tokenization_wavaveca import VOCAB_FILES_NAMES
from transformers.models.wavaveca_phoneme.tokenization_wavaveca_phone... | 104 |
'''simple docstring'''
import math_equivalence # From: git+https://github.com/hendrycks/math.git
import datasets
UpperCamelCase__ = '''\
@article{hendrycksmath2021,
title={Measuring Mathematical Problem Solving With the MATH Dataset},
author={Dan Hendrycks
and Collin Burns
and Saura... | 75 | 0 |
import collections
import tempfile
import unittest
import numpy as np
from transformers.testing_utils import (
is_pt_flax_cross_test,
require_flax,
require_torch,
require_vision,
slow,
torch_device,
)
from transformers.utils import is_flax_available, is_torch_available, is_vision_availabl... | 105 |
'''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_b... | 75 | 0 |
from collections.abc import Sequence
def lowerCamelCase_ ( lowerCAmelCase__ : Sequence[int] | None = None ) -> int:
'''simple docstring'''
if nums is None or not nums:
raise ValueError('Input sequence should not be empty' )
A = n... | 106 |
'''simple docstring'''
import random
from typing import Any
def a__ ( lowerCAmelCase__ ) -> list[Any]:
for _ in range(len(lowerCAmelCase__ ) ):
UpperCAmelCase__ : int = random.randint(0 , len(lowerCAmelCase__ ) - 1 )
UpperCAmelCas... | 75 | 0 |
'''simple docstring'''
import os
import pytest
from datasets import (
get_dataset_config_info,
get_dataset_config_names,
get_dataset_infos,
get_dataset_split_names,
inspect_dataset,
inspect_metric,
)
_UpperCAmelCase : List[str] = pytest.mark.integration
@pytes... | 107 |
'''simple docstring'''
import math
def a__ ( lowerCAmelCase__ ) -> list[int]:
UpperCAmelCase__ : List[Any] = []
UpperCAmelCase__ : Dict = 2
UpperCAmelCase__ : Optional[Any] = int(math.sqrt(lowerCAmelCase__ )... | 75 | 0 |
import inspect
import unittest
from transformers import MobileViTConfig
from transformers.testing_utils import require_torch, require_vision, slow, torch_device
from transformers.utils import cached_property, is_torch_available, is_vision_available
from ...test_configuration_common import ConfigTester
from ...... | 108 |
'''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 diff... | 75 | 0 |
'''simple docstring'''
from collections import OrderedDict
from typing import TYPE_CHECKING, Any, List, Mapping, Optional
from packaging import version
if TYPE_CHECKING:
from ... import PreTrainedTokenizer, TensorType
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfigWithP... | 109 |
'''simple docstring'''
import unittest
import numpy as np
import timeout_decorator # noqa
from transformers import BlenderbotConfig, is_flax_available
from transformers.testing_utils import jax_device, require_flax, slow
from ...generation.test_flax_utils import FlaxGenerationTesterMixin
from ...tes... | 75 | 0 |
"""simple docstring"""
from __future__ import annotations
import unittest
from transformers import is_tf_available
from transformers.testing_utils import require_sentencepiece, require_tf, require_tokenizers, slow
from ...test_configuration_common import ConfigTester
from ...test_modeling_tf_common import TFMode... | 110 |
'''simple docstring'''
import os
import tempfile
from functools import partial
from unittest import TestCase
from unittest.mock import patch
import datasets
import datasets.config
from .utils import require_beam
class lowerCamelCase_ ( datasets.BeamBasedBuilder ):
... | 75 | 0 |
'''simple docstring'''
import sys
from collections.abc import Mapping
from typing import TYPE_CHECKING
import numpy as np
import pyarrow as pa
from .. import config
from ..utils.py_utils import map_nested
from .formatting import TensorFormatter
if TYPE_CHECKING:
import torch
class __lowerCAmelCas... | 665 |
'''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-... | 75 | 0 |
from typing import Callable, Dict, Optional, Tuple
import torch
from torch import nn
from torch.distributions import (
AffineTransform,
Distribution,
Independent,
NegativeBinomial,
Normal,
StudentT,
TransformedDistribution,
)
class lowercase_ ( __a ):
... | 443 |
'''simple docstring'''
import argparse
import torch
from transformers import GPTaConfig, GPTaModel, load_tf_weights_in_gpta
from transformers.utils import CONFIG_NAME, WEIGHTS_NAME, logging
logging.set_verbosity_info()
def a__ ( lowerCAmelCase__ , lowerCAmelCase__ , lowerC... | 75 | 0 |
from typing import List, Optional, Union
import numpy as np
import torch
import torchaudio.compliance.kaldi as ta_kaldi
from ...feature_extraction_sequence_utils import SequenceFeatureExtractor
from ...feature_extraction_utils import BatchFeature
from ...utils import PaddingStrategy, TensorType, logging... | 99 |
'''simple docstring'''
from __future__ import annotations
import copy
import inspect
import unittest
import numpy as np
from transformers import is_tf_available, is_vision_available
from transformers.models.auto import get_values
from transformers.testing_utils import require_tf, slow
from transfor... | 75 | 0 |
'''simple docstring'''
from ....configuration_utils import PretrainedConfig
from ....utils import logging
lowercase = logging.get_logger(__name__)
lowercase = {
'''CarlCochet/trajectory-transformer-halfcheetah-medium-v2''': (
'''https://huggingface.co/CarlCochet/trajector... | 211 |
'''simple docstring'''
import webbrowser
from sys import argv
from urllib.parse import parse_qs, quote
import requests
from bsa import BeautifulSoup
from fake_useragent import UserAgent
if __name__ == "__main__":
UpperCamelCase__ = '''%20'''.join(argv[1:]) if len(argv) > 1 else quote(str(in... | 75 | 0 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
_UpperCamelCase = logging.get_logger(__name__)
_UpperCamelCase = {
'''google/switch-base-8''': '''https://huggingface.co/google/switch-base-8/blob/main/config.json''',
}
class _lowerCamelCase ( _... | 243 |
'''simple docstring'''
from pathlib import Path
import cva
import numpy as np
from matplotlib import pyplot as plt
def a__ ( lowerCAmelCase__ , lowerCAmelCase__ , lowerCAmelCase__ , lowerCAmelCase__ , lowerCAmelCase__ ) -> np.ndarray:
UpperCAmelCase__ ... | 75 | 0 |
"""simple docstring"""
from math import pi
def lowercase_ ( _lowerCamelCase: List[Any] , _lowerCamelCase: Any ) -> float:
'''simple docstring'''
return 2 * pi * radius * (angle / 360)
if __name__ == "__main__":
print(arc_length(90, 10)) | 646 |
'''simple docstring'''
from datetime import datetime as dt
import os
from github import Github
UpperCamelCase__ = [
'''good first issue''',
'''good second issue''',
'''good difficult issue''',
'''feature request''',
'''new model''',
'''wip''',
]
def ... | 75 | 0 |
'''simple docstring'''
import json
import sys
def __UpperCAmelCase ( a_: str, a_: Optional[int] ):
with open(lowerCAmelCase__, encoding="utf-8" ) as f:
_UpperCAmelCase : Union[str, Any] = json.load(lowerCAmelCase__ )
_UpperCAmelCase : str = ['''... | 494 |
'''simple docstring'''
from typing import List, Optional, Tuple, Union
import torch
from ...utils import logging, randn_tensor
from ..pipeline_utils import AudioPipelineOutput, DiffusionPipeline
UpperCamelCase__ = logging.get_logger(__name__) # pylint: disable=invalid-name
class ... | 75 | 0 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
_lowerCAmelCase : int = {
"configuration_megatron_bert": ["MEGATRON_BERT_PRETRAINED_CONFIG_ARCHIVE_MAP", "MegatronBertConfig"],
}
try:
if not is_tor... | 289 |
'''simple docstring'''
from math import factorial
def a__ ( lowerCAmelCase__ , lowerCAmelCase__ , lowerCAmelCase__ ) -> float:
if successes > trials:
raise ValueError('''successes must be lower or equal to trials''' )
if trials < 0 or successes < 0:
... | 75 | 0 |
"""simple docstring"""
from datetime import datetime as dt
import os
from github import Github
snake_case : List[Any] = [
"""good first issue""",
"""good second issue""",
"""good difficult issue""",
"""feature request""",
"""new model""",
"""wip""",
]
d... | 545 |
'''simple docstring'''
from typing import Dict, Iterable, List, Optional, Union
import numpy as np
from ...image_processing_utils import BaseImageProcessor, BatchFeature, get_size_dict
from ...image_transforms import (
center_crop,
get_resize_output_image_size,
normalize,
rescale,
... | 75 | 0 |
import warnings
from ...utils import logging
from .image_processing_flava import FlavaImageProcessor
UpperCamelCase = logging.get_logger(__name__)
class __lowerCamelCase ( __a ):
"""simple docstring"""
def __init__( self : Union[str, Any] , ... | 61 |
'''simple docstring'''
import math
def a__ ( ) -> None:
UpperCAmelCase__ : List[str] = input('''Enter message: ''' )
UpperCAmelCase__ : Any = int(input(F"""Enter key [2-{len(lowerCAmelCase__ ) - 1}]: """ ) )
UpperCAmelCase__ ... | 75 | 0 |
'''simple docstring'''
from collections.abc import Callable
import numpy as np
def __lowerCamelCase ( SCREAMING_SNAKE_CASE_ : Union[str, Any] , SCREAMING_SNAKE_CASE_ : List[Any] , SCREAMING_SNAKE_CASE_ : Dict , SCREAMING_SNAKE_CASE_ : Dict , SC... | 421 |
'''simple docstring'''
class lowerCamelCase_ :
def __init__( self : str , _A : Union[str, Any] , _A : Optional[int] ):
'''simple docstring'''
UpperCAmelCase__ : Optional[Any] = name
... | 75 | 0 |
'''simple docstring'''
import numpy as np
from nltk.translate import meteor_score
import datasets
from datasets.config import importlib_metadata, version
__magic_name__ = version.parse(importlib_metadata.version('nltk'))
if NLTK_VERSION >= version.Version('3.6.4'):
from nltk import word_tokenize
... | 665 |
'''simple docstring'''
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
UpperCamelCase__ = '''src/transformers'... | 75 | 0 |
import gc
import unittest
import numpy as np
import torch
from torch.backends.cuda import sdp_kernel
from diffusers import (
CMStochasticIterativeScheduler,
ConsistencyModelPipeline,
UNetaDModel,
)
from diffusers.utils import randn_tensor, slow, torch_device
from diffusers.utils.testing_uti... | 443 |
'''simple docstring'''
from ..utils import DummyObject, requires_backends
class lowerCamelCase_ ( metaclass=__a ):
lowerCAmelCase__ = ['torch', 'torchsde']
def __init__( self : Tuple , *_A : Any , **_A : Optional[Any] ... | 75 | 0 |
import inspect
import unittest
from transformers import YolosConfig
from transformers.testing_utils import require_torch, require_vision, slow, torch_device
from transformers.utils import cached_property, is_torch_available, is_vision_available
from ...test_configuration_common import ConfigTester
from ... | 99 |
'''simple docstring'''
from ...configuration_utils import PretrainedConfig
from ...utils import logging
UpperCamelCase__ = logging.get_logger(__name__)
UpperCamelCase__ = {'''ctrl''': '''https://huggingface.co/ctrl/resolve/main/config.json'''}
class lowerCamelCase_ ( ... | 75 | 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 di... | 211 |
'''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, TrainingJobAna... | 75 | 0 |
from multiprocessing import Lock, Pipe, Process
# lock used to ensure that two processes do not access a pipe at the same time
_UpperCamelCase = Lock()
def lowerCAmelCase__( lowercase : List[Any] , lowercase : Optional[Any] , lowercase : Tuple , lowercase ... | 243 |
'''simple docstring'''
import math_equivalence # From: git+https://github.com/hendrycks/math.git
import datasets
UpperCamelCase__ = '''\
@article{hendrycksmath2021,
title={Measuring Mathematical Problem Solving With the MATH Dataset},
author={Dan Hendrycks
and Collin Burns
and Saura... | 75 | 0 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_sentencepiece_available,
is_tokenizers_available,
is_torch_available,
)
__A = {'''configuration_reformer''': ['''REFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''Re... | 646 |
'''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_b... | 75 | 0 |
'''simple docstring'''
import functools
from typing import Any
def __UpperCAmelCase ( a_: int, a_: Tuple ):
# Validation
if not isinstance(lowerCAmelCase__, lowerCAmelCase__ ) or len(lowerCAmelCase__ ) == 0:
raise ValueError("the string should be not empty string" )... | 494 |
'''simple docstring'''
import random
from typing import Any
def a__ ( lowerCAmelCase__ ) -> list[Any]:
for _ in range(len(lowerCAmelCase__ ) ):
UpperCAmelCase__ : int = random.randint(0 , len(lowerCAmelCase__ ) - 1 )
UpperCAmelCas... | 75 | 0 |
"""simple docstring"""
from sklearn.metrics import fa_score, matthews_corrcoef
import datasets
from .record_evaluation import evaluate as evaluate_record
_lowerCAmelCase : Optional[Any] = "\\n@article{wang2019superglue,\n title={SuperGLUE: A Stickier Benchmark for General-Purpose Language Und... | 289 |
'''simple docstring'''
import math
def a__ ( lowerCAmelCase__ ) -> list[int]:
UpperCAmelCase__ : List[Any] = []
UpperCAmelCase__ : Dict = 2
UpperCAmelCase__ : Optional[Any] = int(math.sqrt(lowerCAmelCase__ )... | 75 | 0 |
"""simple docstring"""
from collections import OrderedDict
from typing import Mapping
from packaging import version
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
snake_case : List[Any] = logging.get_logger(__name__)
... | 545 |
'''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 diff... | 75 | 0 |
from ...configuration_utils import PretrainedConfig
UpperCamelCase = {
'google/tapas-base-finetuned-sqa': (
'https://huggingface.co/google/tapas-base-finetuned-sqa/resolve/main/config.json'
),
'google/tapas-base-finetuned-wtq': (
'https://huggingface.co/google/tapa... | 61 |
'''simple docstring'''
import unittest
import numpy as np
import timeout_decorator # noqa
from transformers import BlenderbotConfig, is_flax_available
from transformers.testing_utils import jax_device, require_flax, slow
from ...generation.test_flax_utils import FlaxGenerationTesterMixin
from ...tes... | 75 | 0 |
'''simple docstring'''
from typing import Dict, List, Optional, Union
import numpy as np
from ...image_processing_utils import BaseImageProcessor, BatchFeature, get_size_dict
from ...image_transforms import (
center_crop,
convert_to_rgb,
get_resize_output_image_size,
normaliz... | 421 |
'''simple docstring'''
import os
import tempfile
from functools import partial
from unittest import TestCase
from unittest.mock import patch
import datasets
import datasets.config
from .utils import require_beam
class lowerCamelCase_ ( datasets.BeamBasedBuilder ):
... | 75 | 0 |
'''simple docstring'''
from __future__ import annotations
import numpy as np
def lowerCamelCase ( lowerCamelCase : str):
return np.maximum(0 , lowerCAmelCase__)
if __name__ == "__main__":
print(np.array(relu([-1, 0, 5]))) # --> [0, 0, 5]
| 665 |
'''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-... | 75 | 0 |
import numpy as np
import torch
from torch.utils.data import DataLoader
from accelerate.utils.dataclasses import DistributedType
class lowercase_ :
def __init__( self , __A=2 , __A=3 , __A=64 , __A=None ) -> Optional[Any]:
... | 443 |
'''simple docstring'''
import argparse
import torch
from transformers import GPTaConfig, GPTaModel, load_tf_weights_in_gpta
from transformers.utils import CONFIG_NAME, WEIGHTS_NAME, logging
logging.set_verbosity_info()
def a__ ( lowerCAmelCase__ , lowerCAmelCase__ , lowerC... | 75 | 0 |
import json
import os
import shutil
import tempfile
import unittest
import numpy as np
import pytest
from transformers import BertTokenizer, BertTokenizerFast
from transformers.models.bert.tokenization_bert import VOCAB_FILES_NAMES
from transformers.testing_utils import require_vision
from transform... | 99 |
'''simple docstring'''
from __future__ import annotations
import copy
import inspect
import unittest
import numpy as np
from transformers import is_tf_available, is_vision_available
from transformers.models.auto import get_values
from transformers.testing_utils import require_tf, slow
from transfor... | 75 | 0 |
'''simple docstring'''
import enum
import warnings
from ..tokenization_utils import TruncationStrategy
from ..utils import add_end_docstrings, is_tf_available, is_torch_available, logging
from .base import PIPELINE_INIT_ARGS, Pipeline
if is_tf_available():
import tensorflow as tf
from ... | 211 |
'''simple docstring'''
import webbrowser
from sys import argv
from urllib.parse import parse_qs, quote
import requests
from bsa import BeautifulSoup
from fake_useragent import UserAgent
if __name__ == "__main__":
UpperCamelCase__ = '''%20'''.join(argv[1:]) if len(argv) > 1 else quote(str(in... | 75 | 0 |
import os
from dataclasses import dataclass, field
from io import BytesIO
from typing import TYPE_CHECKING, Any, ClassVar, Dict, Optional, Union
import numpy as np
import pyarrow as pa
from .. import config
from ..download.streaming_download_manager import xopen, xsplitext
from ..table import array_cast
from ..... | 243 |
'''simple docstring'''
from pathlib import Path
import cva
import numpy as np
from matplotlib import pyplot as plt
def a__ ( lowerCAmelCase__ , lowerCAmelCase__ , lowerCAmelCase__ , lowerCAmelCase__ , lowerCAmelCase__ ) -> np.ndarray:
UpperCAmelCase__ ... | 75 | 0 |
"""simple docstring"""
import unittest
from transformers import BarthezTokenizer, BarthezTokenizerFast, BatchEncoding
from transformers.testing_utils import require_sentencepiece, require_tokenizers, require_torch, slow
from ...test_tokenization_common import TokenizerTesterMixin
@require_tokenizers
@require_sen... | 646 |
'''simple docstring'''
from datetime import datetime as dt
import os
from github import Github
UpperCamelCase__ = [
'''good first issue''',
'''good second issue''',
'''good difficult issue''',
'''feature request''',
'''new model''',
'''wip''',
]
def ... | 75 | 0 |
'''simple docstring'''
import os
import sys
__a = os.path.join(os.path.dirname(__file__), 'src')
sys.path.append(SRC_DIR)
from transformers import (
AutoConfig,
AutoModel,
AutoModelForCausalLM,
AutoModelForMaskedLM,
AutoModelForQuestionAnswering,
AutoModelForSequenceClassifica... | 494 |
'''simple docstring'''
from typing import List, Optional, Tuple, Union
import torch
from ...utils import logging, randn_tensor
from ..pipeline_utils import AudioPipelineOutput, DiffusionPipeline
UpperCamelCase__ = logging.get_logger(__name__) # pylint: disable=invalid-name
class ... | 75 | 0 |
"""simple docstring"""
import os
import jsonlines
import numpy as np
from tqdm import tqdm
_lowerCAmelCase : List[str] = 20_48
_lowerCAmelCase : Optional[Any] = 40_96
_lowerCAmelCase : Optional[int] = 42
_lowerCAmelCase : int = os.environ.pop("PROCESS_T... | 289 |
'''simple docstring'''
from math import factorial
def a__ ( lowerCAmelCase__ , lowerCAmelCase__ , lowerCAmelCase__ ) -> float:
if successes > trials:
raise ValueError('''successes must be lower or equal to trials''' )
if trials < 0 or successes < 0:
... | 75 | 0 |
"""simple docstring"""
def A ( __snake_case: str = 1_0_0_0_0_0_0 ) -> int:
"""simple docstring"""
__magic_name__ = 1
__magic_name__ = 1
__magic_name__ = {1: 1}
for inputa in range(2 , lowerCA... | 545 |
'''simple docstring'''
from typing import Dict, Iterable, List, Optional, Union
import numpy as np
from ...image_processing_utils import BaseImageProcessor, BatchFeature, get_size_dict
from ...image_transforms import (
center_crop,
get_resize_output_image_size,
normalize,
rescale,
... | 75 | 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
UpperCamelCase = 'src/transformers'
# This is to make su... | 61 |
'''simple docstring'''
import math
def a__ ( ) -> None:
UpperCAmelCase__ : List[str] = input('''Enter message: ''' )
UpperCAmelCase__ : Any = int(input(F"""Enter key [2-{len(lowerCAmelCase__ ) - 1}]: """ ) )
UpperCAmelCase__ ... | 75 | 0 |
'''simple docstring'''
import importlib
import torch
import yaml
from omegaconf import OmegaConf
from taming.models.vqgan import VQModel
def __lowerCamelCase ( SCREAMING_SNAKE_CASE_ : Dict , SCREAMING_SNAKE_CASE_ : Dict=False ) -> List[str]:
"""simple ... | 421 |
'''simple docstring'''
class lowerCamelCase_ :
def __init__( self : str , _A : Union[str, Any] , _A : Optional[int] ):
'''simple docstring'''
UpperCAmelCase__ : Optional[Any] = name
... | 75 | 0 |
'''simple docstring'''
def lowerCamelCase ( lowerCamelCase : List[Any]):
A_ : Optional[int] = [False] * len(lowerCAmelCase__)
A_ : str = [-1] * len(lowerCAmelCase__)
def dfs(lowerCamelCase : List[str] , lowerCamelCase : Union[str, Any]):
... | 665 |
'''simple docstring'''
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
UpperCamelCase__ = '''src/transformers'... | 75 | 0 |
import math
def SCREAMING_SNAKE_CASE_ ( UpperCAmelCase_ : List[str] ) -> list[int]:
SCREAMING_SNAKE_CASE_ : List[Any] =[]
SCREAMING_SNAKE_CASE_ : Dict =2
SCREAMING_SNAKE_CASE_ : Optional[Any] =int(math.sqrt(lowerCAmelCase__ ) ) # S... | 443 |
'''simple docstring'''
from ..utils import DummyObject, requires_backends
class lowerCamelCase_ ( metaclass=__a ):
lowerCAmelCase__ = ['torch', 'torchsde']
def __init__( self : Tuple , *_A : Any , **_A : Optional[Any] ... | 75 | 0 |
import functools
import logging
import os
import sys
import threading
from logging import (
CRITICAL, # NOQA
DEBUG, # NOQA
ERROR, # NOQA
FATAL, # NOQA
INFO, # NOQA
NOTSET, # NOQA
WARN, # NOQA
WARNING, # NOQA
)
from typing import Optional
import huggingface... | 99 |
'''simple docstring'''
from ...configuration_utils import PretrainedConfig
from ...utils import logging
UpperCamelCase__ = logging.get_logger(__name__)
UpperCamelCase__ = {'''ctrl''': '''https://huggingface.co/ctrl/resolve/main/config.json'''}
class lowerCamelCase_ ( ... | 75 | 0 |
'''simple docstring'''
import argparse
import os
from accelerate.utils import ComputeEnvironment
from .cluster import get_cluster_input
from .config_args import cache_dir, default_config_file, default_yaml_config_file, load_config_from_file # noqa: F401
from .config_utils import _ask_field, _ask_opti... | 211 |
'''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, TrainingJobAna... | 75 | 0 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
_UpperCamelCase = logging.get_logger(__name__)
class _lowerCamelCase ( __a ):
"""simple docstring"""
UpperCAmelCase_ : Union[str, Any] ="timm_backbone"
def __in... | 243 |
'''simple docstring'''
import math_equivalence # From: git+https://github.com/hendrycks/math.git
import datasets
UpperCamelCase__ = '''\
@article{hendrycksmath2021,
title={Measuring Mathematical Problem Solving With the MATH Dataset},
author={Dan Hendrycks
and Collin Burns
and Saura... | 75 | 0 |
"""simple docstring"""
import json
import os
import subprocess
import unittest
from ast import literal_eval
import pytest
from parameterized import parameterized, parameterized_class
from . import is_sagemaker_available
if is_sagemaker_available():
from sagemaker import Session, TrainingJobAnalytics
fr... | 646 |
'''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_b... | 75 | 0 |
'''simple docstring'''
__a = 'ABCDEFGHIJKLMNOPQRSTUVWXYZabcdefghijklmnopqrstuvwxyz0123456789+/'
def __UpperCAmelCase ( a_: Dict ):
# Make sure the supplied data is a bytes-like object
if not isinstance(lowerCAmelCase__, lowerCAmelCase__ ):
_UpperCAmelCase : U... | 494 |
'''simple docstring'''
import random
from typing import Any
def a__ ( lowerCAmelCase__ ) -> list[Any]:
for _ in range(len(lowerCAmelCase__ ) ):
UpperCAmelCase__ : int = random.randint(0 , len(lowerCAmelCase__ ) - 1 )
UpperCAmelCas... | 75 | 0 |
"""simple docstring"""
from collections import Counter
from pathlib import Path
from typing import Optional, Tuple
import yaml
class UpperCAmelCase_ ( yaml.SafeLoader ):
def snake_case_ ( self : Optional[Any] , A : List[str] ):
_UpperCAmelCase :... | 289 |
'''simple docstring'''
import math
def a__ ( lowerCAmelCase__ ) -> list[int]:
UpperCAmelCase__ : List[Any] = []
UpperCAmelCase__ : Dict = 2
UpperCAmelCase__ : Optional[Any] = int(math.sqrt(lowerCAmelCase__ )... | 75 | 0 |
"""simple docstring"""
import argparse
import collections
import os
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_table.py
snake_case : Optiona... | 545 |
'''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 diff... | 75 | 0 |
from __future__ import annotations
class __lowerCamelCase :
"""simple docstring"""
def __init__( self : int , SCREAMING_SNAKE_CASE__ : list[list[int]] ) -> Union[str, Any]:
lowerCAmelCase__ = TypeError(
"Matrices must be f... | 61 |
'''simple docstring'''
import unittest
import numpy as np
import timeout_decorator # noqa
from transformers import BlenderbotConfig, is_flax_available
from transformers.testing_utils import jax_device, require_flax, slow
from ...generation.test_flax_utils import FlaxGenerationTesterMixin
from ...tes... | 75 | 0 |
'''simple docstring'''
from ...processing_utils import ProcessorMixin
from ...tokenization_utils_base import BatchEncoding
class SCREAMING_SNAKE_CASE__ ( __a ):
_A = ["image_processor", "tokenizer"]
_A = "AutoImageProcessor"
_A = ... | 421 |
'''simple docstring'''
import os
import tempfile
from functools import partial
from unittest import TestCase
from unittest.mock import patch
import datasets
import datasets.config
from .utils import require_beam
class lowerCamelCase_ ( datasets.BeamBasedBuilder ):
... | 75 | 0 |
'''simple docstring'''
from __future__ import annotations
from math import pi
def lowerCamelCase ( lowerCamelCase : List[Any] , lowerCamelCase : str , lowerCamelCase : Any):
if (inductance, frequency, reactance).count(0) != 1:
raise ValueError("""One and only one... | 665 |
'''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-... | 75 | 0 |
def SCREAMING_SNAKE_CASE_ ( UpperCAmelCase_ : str , UpperCAmelCase_ : List[str] ) -> str:
SCREAMING_SNAKE_CASE_ : list[list[str]] =[[] for _ in range(lowerCAmelCase__ )]
SCREAMING_SNAKE_CASE_ : Union[str, Any] =key - 1
if key <= 0:
... | 443 |
'''simple docstring'''
import argparse
import torch
from transformers import GPTaConfig, GPTaModel, load_tf_weights_in_gpta
from transformers.utils import CONFIG_NAME, WEIGHTS_NAME, logging
logging.set_verbosity_info()
def a__ ( lowerCAmelCase__ , lowerCAmelCase__ , lowerC... | 75 | 0 |
import math_equivalence # From: git+https://github.com/hendrycks/math.git
import datasets
SCREAMING_SNAKE_CASE = '\\n@article{hendrycksmath2021,\n title={Measuring Mathematical Problem Solving With the MATH Dataset},\n author={Dan Hendrycks\n and Collin Burns\n and Saurav Kadavath... | 99 |
'''simple docstring'''
from __future__ import annotations
import copy
import inspect
import unittest
import numpy as np
from transformers import is_tf_available, is_vision_available
from transformers.models.auto import get_values
from transformers.testing_utils import require_tf, slow
from transfor... | 75 | 0 |
'''simple docstring'''
import copy
from ...configuration_utils import PretrainedConfig
from ...utils import logging
from ..auto import CONFIG_MAPPING
lowercase = logging.get_logger(__name__)
lowercase = {
'''ut/deta''': '''https://huggingface.co/ut/deta/resolve/main/config.jso... | 211 |
'''simple docstring'''
import webbrowser
from sys import argv
from urllib.parse import parse_qs, quote
import requests
from bsa import BeautifulSoup
from fake_useragent import UserAgent
if __name__ == "__main__":
UpperCamelCase__ = '''%20'''.join(argv[1:]) if len(argv) > 1 else quote(str(in... | 75 | 0 |
import argparse
import json
import os
import time
import zipfile
from get_ci_error_statistics import download_artifact, get_artifacts_links
from transformers import logging
_UpperCamelCase = logging.get_logger(__name__)
def lowerCAmelCase__( lowercase : Any , lowercase ... | 243 |
'''simple docstring'''
from pathlib import Path
import cva
import numpy as np
from matplotlib import pyplot as plt
def a__ ( lowerCAmelCase__ , lowerCAmelCase__ , lowerCAmelCase__ , lowerCAmelCase__ , lowerCAmelCase__ ) -> np.ndarray:
UpperCAmelCase__ ... | 75 | 0 |
"""simple docstring"""
from collections import deque
from math import floor
from random import random
from time import time
class _snake_case :
def __init__( self : Tuple ):
__lowerCamelCase : Dict = {}
def lowerCamelCase__ ( self : ... | 646 |
'''simple docstring'''
from datetime import datetime as dt
import os
from github import Github
UpperCamelCase__ = [
'''good first issue''',
'''good second issue''',
'''good difficult issue''',
'''feature request''',
'''new model''',
'''wip''',
]
def ... | 75 | 0 |
'''simple docstring'''
import torch
from diffusers import DDPMScheduler
from .test_schedulers import SchedulerCommonTest
class A__ ( __a ):
"""simple docstring"""
UpperCamelCase_ : int = (DDPMScheduler,)
def _lowerCAmelCase ( self : Opt... | 494 |
'''simple docstring'''
from typing import List, Optional, Tuple, Union
import torch
from ...utils import logging, randn_tensor
from ..pipeline_utils import AudioPipelineOutput, DiffusionPipeline
UpperCamelCase__ = logging.get_logger(__name__) # pylint: disable=invalid-name
class ... | 75 | 0 |
"""simple docstring"""
import os
import unittest
from tempfile import TemporaryDirectory
import torch
import torch.nn as nn
from accelerate.utils import (
OffloadedWeightsLoader,
extract_submodules_state_dict,
load_offloaded_weight,
offload_state_dict,
offload_weight,
)
class U... | 289 |
'''simple docstring'''
from math import factorial
def a__ ( lowerCAmelCase__ , lowerCAmelCase__ , lowerCAmelCase__ ) -> float:
if successes > trials:
raise ValueError('''successes must be lower or equal to trials''' )
if trials < 0 or successes < 0:
... | 75 | 0 |
"""simple docstring"""
def A ( __snake_case: str ) -> str:
"""simple docstring"""
if collection == []:
return []
# get some information about the collection
__magic_name__ = len(lowerCAmelCase__ )
__magi... | 545 |
'''simple docstring'''
from typing import Dict, Iterable, List, Optional, Union
import numpy as np
from ...image_processing_utils import BaseImageProcessor, BatchFeature, get_size_dict
from ...image_transforms import (
center_crop,
get_resize_output_image_size,
normalize,
rescale,
... | 75 | 0 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
UpperCamelCase = logging.get_logger(__name__)
UpperCamelCase = {'openai-gpt': 'https://huggingface.co/openai-gpt/resolve/main/config.json'}
class __lowerCamelCase ( __a ):
... | 61 |
'''simple docstring'''
import math
def a__ ( ) -> None:
UpperCAmelCase__ : List[str] = input('''Enter message: ''' )
UpperCAmelCase__ : Any = int(input(F"""Enter key [2-{len(lowerCAmelCase__ ) - 1}]: """ ) )
UpperCAmelCase__ ... | 75 | 0 |
'''simple docstring'''
import string
# frequency taken from https://en.wikipedia.org/wiki/Letter_frequency
snake_case_ = {
'E': 1_2.7_0,
'T': 9.0_6,
'A': 8.1_7,
'O': 7.5_1,
'I': 6.9_7,
'N': 6.7_5,
'S': 6.3_3,
'H': 6.0_9,
'R': 5.9_9,
'D': 4.2_5... | 421 |
'''simple docstring'''
class lowerCamelCase_ :
def __init__( self : str , _A : Union[str, Any] , _A : Optional[int] ):
'''simple docstring'''
UpperCAmelCase__ : Optional[Any] = name
... | 75 | 0 |
'''simple docstring'''
import unittest
import numpy as np
import torch
from diffusers import ScoreSdeVePipeline, ScoreSdeVeScheduler, UNetaDModel
from diffusers.utils.testing_utils import enable_full_determinism, require_torch, slow, torch_device
enable_full_determinism()
class __lowerCAmelCase ( ... | 665 |
'''simple docstring'''
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
UpperCamelCase__ = '''src/transformers'... | 75 | 0 |
from typing import Any
def SCREAMING_SNAKE_CASE_ ( UpperCAmelCase_ : Dict , UpperCAmelCase_ : str , UpperCAmelCase_ : int , UpperCAmelCase_ : Optional[Any] , UpperCAmelCase_ : Dict , ) -> list:
_validation(
lowerCAmelCa... | 443 |
'''simple docstring'''
from ..utils import DummyObject, requires_backends
class lowerCamelCase_ ( metaclass=__a ):
lowerCAmelCase__ = ['torch', 'torchsde']
def __init__( self : Tuple , *_A : Any , **_A : Optional[Any] ... | 75 | 0 |
import argparse
import json
import os
import torch
from torch import nn
from transformers import NllbMoeConfig, NllbMoeModel
from transformers.modeling_utils import dtype_byte_size
from transformers.utils import WEIGHTS_INDEX_NAME, WEIGHTS_NAME
def a (lowerCAmelCase__ ):
__a = [
... | 99 |
'''simple docstring'''
from ...configuration_utils import PretrainedConfig
from ...utils import logging
UpperCamelCase__ = logging.get_logger(__name__)
UpperCamelCase__ = {'''ctrl''': '''https://huggingface.co/ctrl/resolve/main/config.json'''}
class lowerCamelCase_ ( ... | 75 | 0 |
'''simple docstring'''
from math import factorial
def __A ( _SCREAMING_SNAKE_CASE : Optional[Any] , _SCREAMING_SNAKE_CASE : Any , _SCREAMING_SNAKE_CASE : Optional[Any] ):
"""simple docstring"""
if successes > trials:
... | 211 |
'''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, TrainingJobAna... | 75 | 0 |
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
from packaging import version
from torch import nn
... | 243 |
'''simple docstring'''
import math_equivalence # From: git+https://github.com/hendrycks/math.git
import datasets
UpperCamelCase__ = '''\
@article{hendrycksmath2021,
title={Measuring Mathematical Problem Solving With the MATH Dataset},
author={Dan Hendrycks
and Collin Burns
and Saura... | 75 | 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_bart import... | 646 |
'''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_b... | 75 | 0 |
'''simple docstring'''
from binascii import hexlify
from hashlib import shaaaa
from os import urandom
# RFC 3526 - More Modular Exponential (MODP) Diffie-Hellman groups for
# Internet Key Exchange (IKE) https://tools.ietf.org/html/rfc3526
__a = {
# 1536-bit
5: {
'prime': int(
... | 494 |
'''simple docstring'''
import random
from typing import Any
def a__ ( lowerCAmelCase__ ) -> list[Any]:
for _ in range(len(lowerCAmelCase__ ) ):
UpperCAmelCase__ : int = random.randint(0 , len(lowerCAmelCase__ ) - 1 )
UpperCAmelCas... | 75 | 0 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
_lowerCAmelCase : Dict = {
"configuration_timesformer": ["TIMESFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP", "TimesformerConfig"],
}
try:
if not is_torch_a... | 289 |
'''simple docstring'''
import math
def a__ ( lowerCAmelCase__ ) -> list[int]:
UpperCAmelCase__ : List[Any] = []
UpperCAmelCase__ : Dict = 2
UpperCAmelCase__ : Optional[Any] = int(math.sqrt(lowerCAmelCase__ )... | 75 | 0 |
"""simple docstring"""
import collections
import tempfile
import unittest
import numpy as np
from transformers.testing_utils import (
is_pt_flax_cross_test,
require_flax,
require_torch,
require_vision,
slow,
torch_device,
)
from transformers.utils import is_flax_av... | 545 |
'''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 diff... | 75 | 0 |
from typing import Dict, Iterable, Optional, 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, to_pil_image
from ...image_utils import (
IMAGENET_S... | 61 |
'''simple docstring'''
import unittest
import numpy as np
import timeout_decorator # noqa
from transformers import BlenderbotConfig, is_flax_available
from transformers.testing_utils import jax_device, require_flax, slow
from ...generation.test_flax_utils import FlaxGenerationTesterMixin
from ...tes... | 75 | 0 |
'''simple docstring'''
from itertools import product
def __lowerCamelCase ( SCREAMING_SNAKE_CASE_ : str , SCREAMING_SNAKE_CASE_ : Dict ) -> list[int]:
"""simple docstring"""
SCREAMING_SNAKE_CASE_ : Optional[Any] = sides_number
SCREAMING... | 421 |
'''simple docstring'''
import os
import tempfile
from functools import partial
from unittest import TestCase
from unittest.mock import patch
import datasets
import datasets.config
from .utils import require_beam
class lowerCamelCase_ ( datasets.BeamBasedBuilder ):
... | 75 | 0 |
'''simple docstring'''
import re
from ..models.auto import AutoProcessor
from ..models.vision_encoder_decoder import VisionEncoderDecoderModel
from ..utils import is_vision_available
from .base import PipelineTool
if is_vision_available():
from PIL import Image
class __lowerCAmelCase ( __a ... | 665 |
'''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-... | 75 | 0 |
import warnings
from ...utils import logging
from .image_processing_segformer import SegformerImageProcessor
_lowercase = logging.get_logger(__name__)
class lowercase_ ( __a ):
def __init__( self , *__A , **__A ) -> Any:
... | 443 |
'''simple docstring'''
import argparse
import torch
from transformers import GPTaConfig, GPTaModel, load_tf_weights_in_gpta
from transformers.utils import CONFIG_NAME, WEIGHTS_NAME, logging
logging.set_verbosity_info()
def a__ ( lowerCAmelCase__ , lowerCAmelCase__ , lowerC... | 75 | 0 |
from ...utils import is_note_seq_available, is_transformers_available, is_torch_available
from ...utils import OptionalDependencyNotAvailable
try:
if not (is_transformers_available() and is_torch_available()):
raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
from ...... | 99 |
'''simple docstring'''
from __future__ import annotations
import copy
import inspect
import unittest
import numpy as np
from transformers import is_tf_available, is_vision_available
from transformers.models.auto import get_values
from transformers.testing_utils import require_tf, slow
from transfor... | 75 | 0 |
'''simple docstring'''
from typing import Callable, List, Optional, Union
import PIL
import torch
from transformers import (
CLIPImageProcessor,
CLIPSegForImageSegmentation,
CLIPSegProcessor,
CLIPTextModel,
CLIPTokenizer,
)
from diffusers import DiffusionPipeline
from diffuse... | 211 |
'''simple docstring'''
import webbrowser
from sys import argv
from urllib.parse import parse_qs, quote
import requests
from bsa import BeautifulSoup
from fake_useragent import UserAgent
if __name__ == "__main__":
UpperCamelCase__ = '''%20'''.join(argv[1:]) if len(argv) > 1 else quote(str(in... | 75 | 0 |
Subsets and Splits
No community queries yet
The top public SQL queries from the community will appear here once available.