code stringlengths 86 54.5k | code_codestyle int64 0 371 | style_context stringlengths 87 49.2k | style_context_codestyle int64 0 349 | label int64 0 1 |
|---|---|---|---|---|
"""simple docstring"""
import json
import pathlib
import unittest
import numpy as np
from transformers.testing_utils import require_torch, require_vision, slow
from transformers.utils import is_torch_available, is_vision_available
from ...test_image_processing_common import ImageProcessin... | 249 |
'''simple docstring'''
class _lowercase :
def __init__( self: Tuple , UpperCamelCase__: list[int] ):
lowerCamelCase__ : Union[str, Any] = len(UpperCamelCase__ )
lowerCamelCase__ : Union[str, Any]... | 41 | 0 |
"""simple docstring"""
from __future__ import annotations
def _a ( _snake_case ):
"""simple docstring"""
create_state_space_tree(UpperCamelCase__ , [] , 0 , [0 for i in range(len(UpperCamelCase__ ) )] )
def _a ( _snake_case , _snake_case... | 363 |
"""simple docstring"""
import argparse
import torch
from transformers import (
SpeechTaConfig,
SpeechTaFeatureExtractor,
SpeechTaForSpeechToSpeech,
SpeechTaForSpeechToText,
SpeechTaForTextToSpeech,
SpeechTaProcessor,
SpeechTaTokenizer,
logging,
)
from transformers.tokeniz... | 234 | 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 d... | 45 |
from heapq import heappop, heappush
import numpy as np
def _SCREAMING_SNAKE_CASE ( a , a , a , a , ) -> tuple[float | int, list[tuple[int, int]]]:
__A , __A : int = grid.shape
__A : Any = [-1, 1, 0, 0]
__A... | 280 | 0 |
"""simple docstring"""
from ...configuration_utils import PretrainedConfig
from ...utils import logging
lowerCAmelCase : Union[str, Any] = logging.get_logger(__name__)
lowerCAmelCase : Any = {
"""microsoft/trocr-base-handwritten""": (
"""https://hugging... | 358 |
import doctest
from collections import deque
import numpy as np
class __lowercase :
"""simple docstring"""
def __init__( self : Union[str, Any]):
SCREAMING_SNAKE_CASE_: int = [2, 1, 2, -1]
SCREAMING_SNAKE_CASE_: Optional[Any] = [1, 2, 3, 4]
def _SCR... | 127 | 0 |
from PIL import Image
def _SCREAMING_SNAKE_CASE ( _lowerCamelCase : Image , _lowerCamelCase : float) -> Optional[int]:
'''simple docstring'''
def brightness(_lowerCamelCase : int) -> float:
return 128 + level + (c - 128)
... | 232 |
'''simple docstring'''
import json
import os
from functools import lru_cache
from typing import List, Optional, Tuple
import regex as re
from ...tokenization_utils import AddedToken, PreTrainedTokenizer
from ...utils import logging
UpperCamelCase__ : Optional[int] = logging.get_logger(__name__)
U... | 112 | 0 |
"""simple docstring"""
import os
import unittest
from transformers import LxmertTokenizer, LxmertTokenizerFast
from transformers.models.bert.tokenization_bert import VOCAB_FILES_NAMES
from transformers.testing_utils import require_tokenizers
from ...test_tokenization_common import TokenizerTesterMixin
@... | 202 |
"""simple docstring"""
import os
import zipfile
import requests
from get_ci_error_statistics import download_artifact, get_artifacts_links
def __snake_case ( SCREAMING_SNAKE_CASE__ : Tuple , SCREAMING_SNAKE_CASE__ : List[str]=7 ) -> Tuple:
'''simple do... | 202 | 1 |
'''simple docstring'''
import baseaa
def SCREAMING_SNAKE_CASE_ ( _UpperCAmelCase : str ) -> bytes:
return baseaa.baaencode(string.encode("""utf-8""" ) )
def SCREAMING_SNAKE_CASE_ ( _UpperCAmelCase : bytes ) -> str:
return baseaa.baadecode(_UpperCAmelC... | 276 |
import warnings
from typing import List, Optional, Union
from ...processing_utils import ProcessorMixin
from ...tokenization_utils_base import BatchEncoding, PaddingStrategy, PreTokenizedInput, TextInput, TruncationStrategy
from ...utils import TensorType
class A_ ( snake_case__ ):
... | 322 | 0 |
import importlib
import os
import fsspec
import pytest
from fsspec import register_implementation
from fsspec.registry import _registry as _fsspec_registry
from datasets.filesystems import COMPRESSION_FILESYSTEMS, HfFileSystem, extract_path_from_uri, is_remote_filesystem
from .utils import require_lza, require_zstan... | 284 | def snake_case (__lowercase ) -> bool:
'''simple docstring'''
_snake_case : Dict = 0
for ch in input_str:
_snake_case : int = ord(__lowercase )
_snake_case : List[Any] = pow(2 , __lowercase )
#... | 284 | 1 |
"""simple docstring"""
import os
import re
import shutil
import sys
import tempfile
import unittest
import black
__SCREAMING_SNAKE_CASE : Dict = os.path.abspath(os.path.dirname(os.path.dirname(os.path.dirname(__file__))))
sys.path.append(os.path.join(git_repo_path, 'utils'))
import check_copies #... | 347 |
'''simple docstring'''
def SCREAMING_SNAKE_CASE__ ( __A ) -> bool:
return number & 1 == 0
if __name__ == "__main__":
import doctest
doctest.testmod()
| 42 | 0 |
"""simple docstring"""
import unittest
from dataclasses import dataclass
import pytest
from accelerate.commands.config.config_args import SageMakerConfig
from accelerate.utils import ComputeEnvironment
from accelerate.utils.launch import _convert_nargs_to_dict
@dataclass
class UpperCAmelCase_ ( _low... | 360 | """simple docstring"""
import unittest
from huggingface_hub import hf_hub_download
from transformers import MODEL_FOR_VIDEO_CLASSIFICATION_MAPPING, VideoMAEFeatureExtractor
from transformers.pipelines import VideoClassificationPipeline, pipeline
from transformers.testing_utils import (
is_pipeline_test,
nest... | 54 | 0 |
import argparse
import os
import re
# All paths are set with the intent you should run this script from the root of the repo with the command
# python utils/check_dummies.py
_UpperCAmelCase : Optional[Any] ="""src/diffusers"""
# Matches is_xxx_available()
_UpperCAmelCase : Dict =re.compile(R"""is\_([a... | 262 |
from .glue import glue_convert_examples_to_features, glue_output_modes, glue_processors, glue_tasks_num_labels
from .squad import SquadExample, SquadFeatures, SquadVaProcessor, SquadVaProcessor, squad_convert_examples_to_features
from .utils import DataProcessor, InputExample, InputFeatures, SingleSentenceClassifica... | 262 | 1 |
import os
# Precomputes a list of the 100 first triangular numbers
UpperCamelCase__ =[int(0.5 * n * (n + 1)) for n in range(1, 101)]
def lowerCamelCase__ ():
_SCREAMING_SNAKE_CASE : Union[str, Any] = os.path.dirname(os.path.realpath(__lowerCamelCase ) )
_SCREAM... | 325 |
from maths.prime_check import is_prime
def lowerCamelCase__ (__lowerCamelCase ):
if not isinstance(__lowerCamelCase, __lowerCamelCase ):
_SCREAMING_SNAKE_CASE : List[str] = f"""Input value of [number={number}] must be an integer"""
raise TypeError(__l... | 325 | 1 |
import json
import os
from typing import Optional
import numpy as np
from ...feature_extraction_utils import BatchFeature
from ...processing_utils import ProcessorMixin
from ...utils import logging
from ...utils.hub import get_file_from_repo
from ..auto import AutoTokenizer
a_ = logging.get_logger(__name__)... | 76 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tf_available,
is_tokenizers_available,
is_torch_available,
)
SCREAMING_SNAKE_CASE_ = {
'''configuration_roberta''': ['''... | 301 | 0 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tf_available,
is_tokenizers_available,
is_torch_available,
)
_snake_case = {
"configuration_blenderbot": [
... | 371 | 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 (
MobileViTConfig,
MobileViTForImageClassification,
MobileViTForSemanticSegmentation,
MobileViTImageProcessor,
)
f... | 342 | 0 |
'''simple docstring'''
from __future__ import annotations
import inspect
import unittest
from math import floor
import numpy as np
from transformers import CvtConfig
from transformers.testing_utils import require_tf, require_vision, slow
from transformers.utils import cached_property, is_tf_available, is_vision_... | 239 |
'''simple docstring'''
from typing import Mapping
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxSeqaSeqConfigWithPast
from ...utils import logging
__lowercase : Dict = logging.get_logger(__name__)
__lowercase : Optional[Any] = {
'google/umt5-small': 'htt... | 27 | 0 |
'''simple docstring'''
import argparse
import os
import platform
import numpy as np
import psutil
import torch
from accelerate import __version__ as version
from accelerate.commands.config import default_config_file, load_config_from_file
from ..utils import is_npu_available, is_xpu_available
def lower... | 365 |
'''simple docstring'''
from __future__ import annotations
def lowerCamelCase__ ( __lowerCamelCase : list[int] ):
'''simple docstring'''
if not nums:
return 0
_UpperCAmelCase : Tuple =nums[0]
_UpperCAmelCase : int ... | 242 | 0 |
"""simple docstring"""
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
lowercase__ = datasets.uti... | 241 |
from ....configuration_utils import PretrainedConfig
from ....utils import logging
UpperCAmelCase_ : List[str] = logging.get_logger(__name__)
UpperCAmelCase_ : int = {
'''CarlCochet/trajectory-transformer-halfcheetah-medium-v2''': (
'''https://huggingface.co/CarlCoche... | 38 | 0 |
"""simple docstring"""
from typing import Optional, Tuple, Union
import tensorflow as tf
from ...activations_tf import ACTaFN
from ...file_utils import add_code_sample_docstrings, add_start_docstrings, add_start_docstrings_to_model_forward
from ...modeling_tf_outputs import (
TFBaseModelOutputWithNoAttention,
... | 364 | """simple docstring"""
from itertools import product
def __UpperCAmelCase ( lowercase ,lowercase ):
"""simple docstring"""
_UpperCAmelCase = sides_number
_UpperCAmelCase = max_face_number * dice_number
_UpperCAmelCase = [0] * (max_total + 1)
_UpperCAmelCase = 1
_U... | 30 | 0 |
from __future__ import annotations
import time
import numpy as np
__a : Optional[Any] = [8, 5, 9, 7]
__a : Optional[Any] = [
[2, 0, 1, 1],
[0, 1, 2, 1],
[4, 0, 0, 3],
[0, 2, 1, 0],
[1, 0, 3, 0],
]
__a : List[Any] = [
[3, 2, 1, 4],
[0, 2, 5, 2],
[5, ... | 210 | import os
import pickle
import unittest
from transformers import AutoTokenizer
from transformers.models.bert.tokenization_bert import BertTokenizer
from transformers.models.bert_japanese.tokenization_bert_japanese import (
VOCAB_FILES_NAMES,
BertJapaneseTokenizer,
CharacterTokenizer,
JumanppTokenizer,
... | 210 | 1 |
'''simple docstring'''
import argparse
import logging
import sys
from unittest.mock import patch
import run_glue_deebert
from transformers.testing_utils import TestCasePlus, get_gpu_count, require_torch_non_multi_gpu, slow
logging.basicConfig(level=logging.DEBUG)
lowercase =logging.getLogger()
... | 352 |
'''simple docstring'''
from __future__ import annotations
from random import choice
def lowerCamelCase__ ( __lowerCamelCase : Optional[int] ):
'''simple docstring'''
return choice(__lowerCamelCase )
def lowerCamelCase__ ( __lowerCamelCase : ... | 242 | 0 |
"""simple docstring"""
def UpperCamelCase__ ( lowercase__ : str , lowercase__ : str = " " ):
snake_case : List[str] = []
snake_case : List[Any] = 0
for index, char in enumerate(lowercase__ ):
if char == separator:
split_words... | 148 |
"""simple docstring"""
from typing import Any
class lowerCamelCase__ :
def __init__( self , SCREAMING_SNAKE_CASE ):
"""simple docstring"""
snake_case : Tuple = data
snake_case : Union[str, Any] = None
class ... | 148 | 1 |
import requests
from bsa import BeautifulSoup
def __UpperCamelCase ( lowercase__ : str = "AAPL" ) -> str:
'''simple docstring'''
lowerCAmelCase_ : Optional[Any] = f'https://in.finance.yahoo.com/quote/{symbol}?s={symbol}'
lowerCAmelCase_ : Tuple = B... | 28 |
import argparse
import numpy as np
import torch
from transformers import SpeechTaHifiGan, SpeechTaHifiGanConfig, logging
logging.set_verbosity_info()
__UpperCAmelCase = logging.get_logger('transformers.models.speecht5')
def __UpperCamelCase ( lowercase__ : Optional[Any] , lowe... | 28 | 1 |
'''simple docstring'''
import unittest
import torch
from torch import nn
from diffusers.models.activations import get_activation
class _UpperCamelCase ( unittest.TestCase ):
'''simple docstring'''
def __lowerCamelCase ( self : int):
'''simpl... | 166 |
'''simple docstring'''
import os
from shutil import copyfile
from typing import Any, Dict, List, Optional, Tuple
import sentencepiece as spm
from ...tokenization_utils import PreTrainedTokenizer
from ...utils import logging
lowerCamelCase = logging.get_logger(__name__)
lowerCamelCase = ... | 166 | 1 |
"""simple docstring"""
import json
import os
import unittest
from transformers.models.ctrl.tokenization_ctrl import VOCAB_FILES_NAMES, CTRLTokenizer
from ...test_tokenization_common import TokenizerTesterMixin
class UpperCamelCase ( _UpperCAmelCase , unittest.TestCase ):
lower... | 350 |
from .dependency_versions_table import deps
from .utils.versions import require_version, require_version_core
# define which module versions we always want to check at run time
# (usually the ones defined in `install_requires` in setup.py)
#
# order specific notes:
# - tqdm must be checked before tokenizers
Uppe... | 198 | 0 |
def __snake_case ( _UpperCAmelCase = 4000000 ):
__a = [0, 1]
__a = 0
while fib[i] <= n:
fib.append(fib[i] + fib[i + 1] )
if fib[i + 2] > n:
break
i += 1
__a = 0
for j in range(len(_UpperCAmelCase ) -... | 49 |
import functools
from typing import Any
def UpperCamelCase ( snake_case__ : str , snake_case__ : list[str] ) -> bool:
# Validation
if not isinstance(snake_case__ , snake_case__ ) or len(snake_case__ ) == 0:
raise ValueError('the string should be not empty s... | 119 | 0 |
'''simple docstring'''
import baseaa
def __magic_name__( lowerCamelCase):
return baseaa.baaencode(string.encode('''utf-8'''))
def __magic_name__( lowerCamelCase):
return baseaa.baadecode(lowerCamelCase).decode('''utf-8''')
if __name__ == "__main__":
_UpperCAmelCase ... | 353 |
'''simple docstring'''
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 a__ ( _... | 9 | 0 |
"""simple docstring"""
from __future__ import annotations
__SCREAMING_SNAKE_CASE =[]
def lowercase__( __SCREAMING_SNAKE_CASE : list[list[int]] , __SCREAMING_SNAKE_CASE : int , __SCREAMING_SNAKE_CASE : int ):
for i in range(len(__SCREAMING_SNAKE... | 213 | """simple docstring"""
import inspect
import unittest
import numpy as np
from transformers import ViTConfig, is_flax_available
from transformers.testing_utils import require_flax, slow
from ...test_configuration_common import ConfigTester
from ...test_modeling_flax_common import FlaxModelTesterMixin, floats_t... | 213 | 1 |
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... | 353 |
from math import factorial
def lowerCAmelCase__ ( lowerCamelCase_ : int = 100):
'''simple docstring'''
return sum(map(lowerCamelCase_ ,str(factorial(lowerCamelCase_))))
if __name__ == "__main__":
print(solution(int(input('Enter the Number: ').strip())))
| 94 | 0 |
import os
import time
from dataclasses import dataclass, field
from enum import Enum
from typing import Dict, List, Optional, Union
import torch
from filelock import FileLock
from torch.utils.data import Dataset
from ...models.auto.modeling_auto import MODEL_FOR_QUESTION_ANSWERING_MAPPING
from ...tokenization_util... | 94 |
import json
import pathlib
import unittest
import numpy as np
from transformers.testing_utils import require_torch, require_vision, slow
from transformers.utils import is_torch_available, is_vision_available
from ...test_image_processing_common import ImageProcessingSavingTestMixin, prepare_image_inpu... | 184 | 0 |
from __future__ import annotations
import unittest
from transformers import RoFormerConfig, is_tf_available
from transformers.testing_utils import require_tf, slow
from ...test_configuration_common import ConfigTester
from ...test_modeling_tf_common import TFModelTesterMixin, ids_tensor, random_attention_mas... | 367 | import warnings
from ...utils import logging
from .image_processing_clip import CLIPImageProcessor
lowercase = logging.get_logger(__name__)
class __lowercase ( A ):
'''simple docstring'''
def __init__( self : Any , *_a : Optional[A... | 35 | 0 |
"""simple docstring"""
import json
import sys
import tempfile
import unittest
from pathlib import Path
import transformers
from transformers import (
CONFIG_MAPPING,
IMAGE_PROCESSOR_MAPPING,
AutoConfig,
AutoImageProcessor,
CLIPConfig,
CLIPImageProcessor,
)
from transform... | 217 |
"""simple docstring"""
from ...configuration_utils import PretrainedConfig
from ...utils import logging
__A = logging.get_logger(__name__)
__A = {
"google/switch-base-8": "https://huggingface.co/google/switch-base-8/blob/main/config.json",
}
class snake_case ( ... | 217 | 1 |
from math import sqrt
def UpperCAmelCase_ (_lowerCAmelCase : int = 1_00_00_00 ):
__UpperCamelCase : int = 0
__UpperCamelCase : int = 0
__UpperCamelCase : int
while num_cuboids <= limit:
max_cuboid_size += 1
for sum_shortest_si... | 171 |
def UpperCAmelCase_ (_lowerCAmelCase : int = 1_00 ):
__UpperCamelCase : Tuple = n * (n + 1) * (2 * n + 1) / 6
__UpperCamelCase : List[str] = (n * (n + 1) / 2) ** 2
return int(square_of_sum - sum_of_squares )
if __name__ == "__main__":
print(F"""{s... | 171 | 1 |
import gc
import threading
import time
import psutil
import torch
class A_ :
def __init__( self : List[str]):
__lowerCamelCase : str = psutil.Process()
__lowerCamelCase : Tuple = False
def lowerCAmelCase ( se... | 73 | import copy
from ...configuration_utils import PretrainedConfig
from ...utils import logging
from ..auto import CONFIG_MAPPING
__a : int = logging.get_logger(__name__)
__a : str = {
"""ut/deta""": """https://huggingface.co/ut/deta/resolve/main/config.json""",
}
class _UpperCamelCa... | 210 | 0 |
"""simple docstring"""
import gc
import unittest
from transformers import CTRLConfig, 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... | 128 |
"""simple docstring"""
from ..utils import is_flax_available, is_torch_available
if is_torch_available():
from .autoencoder_kl import AutoencoderKL
from .controlnet import ControlNetModel
from .dual_transformer_ad import DualTransformeraDModel
from .modeling_utils i... | 128 | 1 |
"""simple docstring"""
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 ... | 220 |
import requests
from bsa import BeautifulSoup
def UpperCAmelCase_ ( _A = "AAPL" ):
'''simple docstring'''
SCREAMING_SNAKE_CASE__ = F'''https://in.finance.yahoo.com/quote/{symbol}?s={symbol}'''
SCREAMING_SNAKE_CASE__ = BeautifulSoup(requests.get(_A ).text , ''... | 314 | 0 |
"""simple docstring"""
import math
import qiskit
def _A (__a = 1 , __a = 1 , __a = 1 ) -> qiskit.result.counts.Counts:
"""simple docstring"""
if (
isinstance(__a , __a )
or isinstance(__a , __a )
or isinstance(__a , ... | 318 |
"""simple docstring"""
from collections import defaultdict
def _A (__a , __a ) -> bool:
"""simple docstring"""
SCREAMING_SNAKE_CASE_ : Dict = first_str.lower().strip()
SCREAMING_SNAKE_CASE_ : List[Any] = second_str.lower().strip()
# Rem... | 318 | 1 |
'''simple docstring'''
import collections
import os
from typing import List, Optional, Tuple
from transformers.utils import is_jieba_available, requires_backends
if is_jieba_available():
import jieba
from ...tokenization_utils import PreTrainedTokenizer
from ...utils import logging
... | 168 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_tf_available,
is_tokenizers_available,
is_torch_available,
is_vision_available,
)
a_ : Union[str, Any] = {
"config... | 168 | 1 |
import os
from typing import Any, Callable, Dict, List, Optional, Tuple, Union
import torch
from torch import nn
from ...models.controlnet import ControlNetModel, ControlNetOutput
from ...models.modeling_utils import ModelMixin
from ...utils import logging
snake_case : Any = logging.get_logger(__nam... | 281 |
from typing import TYPE_CHECKING
from ....utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available, is_vision_available
snake_case : Any = {'''configuration_van''': ['''VAN_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''VanConfig''']}
try:
if not is_torch_available():
raise... | 281 | 1 |
import re
def UpperCamelCase( __UpperCamelCase : str ):
lowerCAmelCase_ : str = re.compile(R'''^(\+91[\-\s]?)?[0]?(91)?[789]\d{9}$''' )
if match := re.search(__UpperCamelCase ,__UpperCamelCase ):
return match.string == phone
return False
if __name__ == "__main__":
pr... | 103 |
from typing import Any
import numpy as np
def __SCREAMING_SNAKE_CASE ( snake_case_ ):
'''simple docstring'''
return np.array_equal(snake_case_ , matrix.conjugate().T )
def __SCREAMING_SNAKE_CASE ( snake_case_ , snake_case_ ):
'''simple docstring''... | 133 | 0 |
'''simple docstring'''
# NOTE: This file is deprecated and will be removed in a future version.
# It only exists so that temporarely `from diffusers.pipelines import DiffusionPipeline` works
from ...utils import deprecate
from ..controlnet.multicontrolnet import MultiControlNetModel # noqa: F401
from ..cont... | 363 |
'''simple docstring'''
from collections import defaultdict
from math import gcd
def __lowercase ( __lowercase = 150_0000 ) -> int:
'''simple docstring'''
_A = defaultdict(__lowercase )
_A = 2
while 2 * euclid_m * (euclid_m + 1) <= limit:... | 174 | 0 |
"""simple docstring"""
# this script reports modified .py files under the desired list of top-level sub-dirs passed as a list of arguments, e.g.:
# python ./utils/get_modified_files.py utils src tests examples
#
# it uses git to find the forking point and which files were modified - i.e. files not under git won... | 292 |
"""simple docstring"""
from __future__ import annotations
import unittest
from transformers import AutoTokenizer, PegasusConfig, is_tf_available
from transformers.testing_utils import require_sentencepiece, require_tf, require_tokenizers, slow
from transformers.utils import cached_property
from ...test_configu... | 292 | 1 |
"""simple docstring"""
from __future__ import annotations
def lowercase ( _snake_case : list[int] ) ->list[int]: # This function is recursive
"""simple docstring"""
__snake_case : int = len(_snake_case )
# If the array contains only one element, we retu... | 24 |
"""simple docstring"""
import itertools
from dataclasses import dataclass
from typing import List, Optional
import pyarrow as pa
import pyarrow.parquet as pq
import datasets
from datasets.table import table_cast
SCREAMING_SNAKE_CASE : int = datasets.utils.logging.get_logger(__name__)
@dataclass
cla... | 24 | 1 |
import math_equivalence # From: git+https://github.com/hendrycks/math.git
import datasets
UpperCAmelCase__ : List[Any] = """\
@article{hendrycksmath2021,
title={Measuring Mathematical Problem Solving With the MATH Dataset},
author={Dan Hendrycks
and Collin Burns
and Saurav Kadavath... | 245 |
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 ..... | 245 | 1 |
'''simple docstring'''
from __future__ import annotations
def __snake_case( _lowerCAmelCase ) -> int:
if not nums:
return 0
snake_case__ : List[str] = nums[0]
snake_case__ : Tuple = 0
for num in nums[1:]:
snake_cas... | 370 |
'''simple docstring'''
import collections
from typing import List, Optional, Union
from ...tokenization_utils_base import BatchEncoding
from ...utils import TensorType, add_end_docstrings, add_start_docstrings, logging
from ..bert.tokenization_bert import BertTokenizer
__a = logging.get_logger(__nam... | 43 | 0 |
def __lowercase ( _UpperCamelCase, _UpperCamelCase ) ->Tuple:
"""simple docstring"""
while b:
lowercase , lowercase : Any = b, a % b
return a
def __lowercase ( _UpperCamelCase, _UpperCamelCase ) ->Dict:
"""simple docstri... | 337 | """simple docstring"""
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tokenizers_available, is_torch_available
lowerCAmelCase__ : str = {
'configuration_roc_bert': ['ROC_BERT_PRETRAINED_CONFIG_ARCHIVE_MAP', 'RoCBertConfig'],
'tokenizati... | 98 | 0 |
'''simple docstring'''
import os
from collections import deque
import torch
from torch.utils.data import Dataset
class _a ( SCREAMING_SNAKE_CASE ):
'''simple docstring'''
def __init__( self, A="", A="train" ):
... | 246 |
'''simple docstring'''
import copy
from dataclasses import dataclass, field
from typing import ClassVar, Dict
from ..features import ClassLabel, Features, Value
from .base import TaskTemplate
@dataclass(frozen=SCREAMING_SNAKE_CASE )
class _a ( SCREAMING_SNAKE_CASE ):... | 246 | 1 |
import warnings
from typing import List, Optional, Union
from ...processing_utils import ProcessorMixin
from ...tokenization_utils_base import BatchEncoding, PaddingStrategy, PreTokenizedInput, TextInput, TruncationStrategy
from ...utils import TensorType
class lowercase ( UpperCamelCase__ )... | 26 |
from __future__ import annotations
import numpy as np
def lowerCAmelCase_ ( snake_case_ ):
return np.maximum(0,snake_case_ )
if __name__ == "__main__":
print(np.array(relu([-1, 0, 5]))) # --> [0, 0, 5]
| 26 | 1 |
"""simple docstring"""
from typing import Optional, Union
import torch
from torch import nn
from ...configuration_utils import ConfigMixin, register_to_config
from ...models.modeling_utils import ModelMixin
class A ( _UpperCAmelCase , _UpperCAmelCase ):
... | 361 |
def _snake_case( SCREAMING_SNAKE_CASE__ : int = 1000 ) -> int:
'''simple docstring'''
A__ = 3
A__ = 0
while a < n:
if a % 3 == 0 or a % 5 == 0:
result += a
elif a % 15 == 0:
res... | 282 | 0 |
'''simple docstring'''
from typing import List, Optional, Union
from ...configuration_utils import PretrainedConfig
from ...utils import logging
__lowerCamelCase = logging.get_logger(__name__)
__lowerCamelCase = {
'''huggingface/time-series-transformer-tourism-monthly''': (
... | 162 |
'''simple docstring'''
import gc
import unittest
import numpy as np
import torch
from transformers import CLIPTextConfig, CLIPTextModelWithProjection, CLIPTokenizer
from diffusers import HeunDiscreteScheduler, PriorTransformer, ShapEPipeline
from diffusers.pipelines.shap_e import ShapERenderer
from diffusers... | 162 | 1 |
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 BartTokenizer
_lowerCam... | 99 |
import logging
import os
from .state import PartialState
class __UpperCAmelCase ( logging.LoggerAdapter ):
@staticmethod
def __magic_name__ ( __A : str ):
UpperCAmelCase : Dict = PartialState()
return not main_process_only or (main_process_only a... | 99 | 1 |
import json
import os
import tempfile
import datasets
from utils import generate_example_dataset, get_duration
lowerCamelCase : Optional[Any] = 50_000
lowerCamelCase : Dict = 5_000
lowerCamelCase , lowerCamelCase : Optional[Any] = os.path.split(__file__)
low... | 204 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tokenizers_available, is_torch_available
lowerCamelCase : str = {
"configuration_nezha": ["NEZHA_PRETRAINED_CONFIG_ARCHIVE_MAP", "NezhaConfig"],
}
try:
if not is_torch_available()... | 204 | 1 |
'''simple docstring'''
import argparse
import torch
from transformers import BertConfig, BertForPreTraining, load_tf_weights_in_bert
from transformers.utils import logging
logging.set_verbosity_info()
def _lowerCAmelCase ( lowercase , lowercase , lowercase ) -> List[str]:
... | 358 |
'''simple docstring'''
import numpy as np
from transformers import Pipeline
def _lowerCAmelCase ( lowercase ) -> List[str]:
__lowerCAmelCase = np.max(lowercase , axis=-1 , keepdims=lowercase )
__lowerCAmelCase = np.exp(outputs - maxes )
... | 46 | 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,
WavaVecaFeatureExtr... | 55 |
'''simple docstring'''
import inspect
import unittest
import numpy as np
from tests.test_modeling_common import floats_tensor
from transformers import DetrConfig, MaskFormerConfig, SwinConfig, is_torch_available, is_vision_available
from transformers.testing_utils import require_torch, require_torch_multi_gp... | 37 | 0 |
"""simple docstring"""
import warnings
from ...processing_utils import ProcessorMixin
from ...tokenization_utils_base import BatchEncoding
class lowerCamelCase__ ( SCREAMING_SNAKE_CASE ):
'''simple docstring'''
_lowerCamelCase = ['''image_processor''', '''tokeniz... | 371 |
"""simple docstring"""
import argparse
from transformers import CLIPImageProcessor, CLIPVisionModelWithProjection
from diffusers import UnCLIPImageVariationPipeline, UnCLIPPipeline
if __name__ == "__main__":
UpperCAmelCase =argparse.ArgumentParser()
parser.add_argument("--dump_path", de... | 77 | 0 |
'''simple docstring'''
import unittest
import numpy as np
from transformers.testing_utils import require_torch, require_vision
from transformers.utils import is_torch_available, is_vision_available
from ...test_image_processing_common import ImageProcessingSavingTestMixin, prepare_image_inputs
if is_torch_... | 112 |
from __future__ import annotations
import math
lowercase : Any = '2020.9.26'
lowercase : Union[str, Any] = 'xcodz-dot, cclaus, dhruvmanila'
def _SCREAMING_SNAKE_CASE ( _lowerCamelCase : float , _lowerCamelCase : float , _lowerCamelCas... | 232 | 0 |
from math import factorial
lowerCAmelCase_ = {str(d): factorial(d) for d in range(10)}
def snake_case( __magic_name__ ) -> int:
'''simple docstring'''
return sum(DIGIT_FACTORIAL[d] for d in str(__magic_name__ ) )
def snake_case( ... | 116 |
import re
from typing import Callable, List, Optional, Union
import tensorflow as tf
try:
from tensorflow.keras.optimizers.legacy import Adam
except ImportError:
from tensorflow.keras.optimizers import Adam
class _A ( tf.keras.optimizers.schedules.LearningRateSchedule ):
... | 116 | 1 |
import inspect
import unittest
from transformers import DPTConfig
from transformers.file_utils import is_torch_available, is_vision_available
from transformers.models.auto import get_values
from transformers.testing_utils import require_torch, require_vision, slow, torch_device
from ...test_configuration_common imp... | 214 |
def snake_case__ ( SCREAMING_SNAKE_CASE_ : str , SCREAMING_SNAKE_CASE_ : str ):
'''simple docstring'''
if len(SCREAMING_SNAKE_CASE_ ) != len(SCREAMING_SNAKE_CASE_ ):
raise ValueError('String lengths must match!' )
lowercase__ : Union[str, Any] = ... | 214 | 1 |
from math import log
from scipy.constants import Boltzmann, physical_constants
lowercase : List[Any] = 3_0_0 # TEMPERATURE (unit = K)
def A_ ( A__ , A__ , A__ , ) -> float:
if donor_conc <= 0:
raise ValueError('Donor concentration should be positive' ... | 364 |
import glob
import os
import random
from string import ascii_lowercase, digits
import cva
lowercase : Optional[Any] = """"""
lowercase : int = """"""
lowercase : List[Any] = """"""
lowercase : Optional[int] = 1 # (0 is vertical, 1 is horizontal)
def... | 225 | 0 |
from __future__ import annotations
def snake_case__ ( SCREAMING_SNAKE_CASE_ : list[int] ):
'''simple docstring'''
lowercase__ : Optional[Any] = len(UpperCAmelCase_ ) // 2
# choose the middle 3 elements
lowercase__ : Dict = lst[m - 1 : m + 2]
... | 214 |
from collections import OrderedDict
from typing import Any, Mapping, Optional
from ... import PreTrainedTokenizer
from ...configuration_utils import PretrainedConfig
from ...file_utils import TensorType, is_torch_available
from ...onnx import OnnxConfig, OnnxConfigWithPast, OnnxSeqaSeqConfigWithPast
from ...onnx.ut... | 94 | 0 |
"""simple docstring"""
from unittest import TestCase
from datasets import Dataset
from minhash_deduplication import deduplicate_dataset, make_duplicate_clusters
def UpperCamelCase_ ( ) -> Optional[int]:
"""simple docstring"""
lowerCAmelCase_ : Tu... | 350 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_sentencepiece_available,
is_speech_available,
is_torch_available,
)
lowercase__ : Optional[int] = {
"""configuration_... | 289 | 0 |
"""simple docstring"""
import numpy as np
import torch
from torch.utils.data import Dataset
from utils import logger
class _UpperCAmelCase ( snake_case__ ):
'''simple docstring'''
def __init__(self , a_ , a_ ):
'''simple docstring'''
__snake_case : An... | 102 |
"""simple docstring"""
from ..utils import DummyObject, requires_backends
class __A (metaclass=snake_case__):
'''simple docstring'''
__lowercase: List[Any] = ["""sentencepiece"""]
def __init__( self : int , *UpperCAmelCase_ : Any ... | 347 | 0 |
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
a ="""src/transformers"""
a ="""docs/source/en"""
... | 358 |
# Copyright 2021 The HuggingFace Team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required ... | 113 | 0 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available, is_vision_available
UpperCAmelCase_ : Dict = {"""configuration_glpn""": ["""GLPN_PRETRAINED_CONFIG_ARCHIVE_MAP""", """GLPNConfig"""]}
try:
if not is_vis... | 91 |
from typing import Union
import fire
import torch
from tqdm import tqdm
def SCREAMING_SNAKE_CASE__ ( lowercase ,lowercase = "cpu" ,lowercase = None ) -> None:
snake_case : int = torch.load(lowercase ,map_location=lowercase )
for k, v in tqdm(state_... | 124 | 0 |
'''simple docstring'''
from __future__ import annotations
import unittest
from transformers import is_tf_available, is_torch_available
from transformers.testing_utils import DUMMY_UNKNOWN_IDENTIFIER, SMALL_MODEL_IDENTIFIER, is_pt_tf_cross_test, slow
if is_tf_available():
from transformers... | 358 |
'''simple docstring'''
import json
import os
import unittest
from transformers import DebertaTokenizer, DebertaTokenizerFast
from transformers.models.deberta.tokenization_deberta import VOCAB_FILES_NAMES
from transformers.testing_utils import slow
from ...test_tokenization_common import TokenizerTest... | 9 | 0 |
from __future__ import annotations
from collections import deque
from collections.abc import Sequence
from dataclasses import dataclass
from typing import Any
@dataclass
class A__ :
lowerCAmelCase__ : int
lowerCAmelCase__ : Node | None = None
lowerCAmelCase__ : No... | 325 |
import os
import string
import sys
lowerCamelCase = 1 << 8
lowerCamelCase = {
'''tab''': ord('''\t'''),
'''newline''': ord('''\r'''),
'''esc''': 27,
'''up''': 65 + ARROW_KEY_FLAG,
'''down''': 66 + ARROW_KEY_FLAG,
'''right''': 67 + ARROW_KEY_FLAG,
'''left''': ... | 188 | 0 |
'''simple docstring'''
import unittest
from transformers import DonutProcessor
lowerCAmelCase: Optional[int] = 'naver-clova-ix/donut-base'
class a__( unittest.TestCase ):
def lowercase_ ( self : Union[str, Any] ):
a : Dict = DonutP... | 357 |
'''simple docstring'''
import copy
import os
import cva
import numpy as np
from matplotlib import pyplot as plt
class a__:
def __init__( self : Optional[int] ):
a : int = ''
a : List[str] = ''
a : int = ... | 96 | 0 |
'''simple docstring'''
import pickle
import shutil
import tempfile
import unittest
from transformers import SPIECE_UNDERLINE, XLMRobertaTokenizer, XLMRobertaTokenizerFast
from transformers.testing_utils import get_tests_dir, require_sentencepiece, require_tokenizers, slow
from transformers.utils import cached_... | 258 | '''simple docstring'''
import copy
from typing import Any, Dict, List, Optional, Union
import numpy as np
from ...audio_utils import mel_filter_bank, spectrogram, window_function
from ...feature_extraction_sequence_utils import SequenceFeatureExtractor
from ...feature_extraction_utils import BatchFeature
from ...... | 272 | 0 |
'''simple docstring'''
import warnings
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 Tens... | 365 |
'''simple docstring'''
import warnings
from ...utils import logging
from .image_processing_mobilevit import MobileViTImageProcessor
__A : Optional[int] = logging.get_logger(__name__)
class __UpperCamelCase ( lowercase__ ):
def __init__( self :List[str] ,*_Upp... | 8 | 0 |
from copy import deepcopy
class __snake_case :
def __init__( self : List[str] , _snake_case : list[int] | None = None , _snake_case : int | None = None):
"""simple docstring"""
if arr is None and size is not No... | 51 |
'''simple docstring'''
import os
import sys
from contextlib import contextmanager
# Windows only
if os.name == "nt":
import ctypes
import msvcrt # noqa
class lowercase__ ( ctypes.Structure ):
'''simple docstring'''
A_ : Optional[Any] =... | 200 | 0 |
'''simple docstring'''
import argparse
from transformers import CLIPImageProcessor, CLIPVisionModelWithProjection
from diffusers import UnCLIPImageVariationPipeline, UnCLIPPipeline
if __name__ == "__main__":
__snake_case : str = argparse.ArgumentParser()
parser.add_argument('--dump... | 354 |
'''simple docstring'''
import torch
from diffusers import CMStochasticIterativeScheduler
from .test_schedulers import SchedulerCommonTest
class lowerCamelCase ( lowercase_ ):
'''simple docstring'''
__snake_case = (CMStochasticIterativeScheduler,)
__snake_case = 10
... | 136 | 0 |
def lowerCAmelCase_ ( __A ) -> str:
'''simple docstring'''
return " ".join(input_str.split()[::-1] )
if __name__ == "__main__":
import doctest
doctest.testmod()
| 65 | """simple docstring"""
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_tf_available,
is_tokenizers_available,
is_torch_available,
is_vision_available,
)
__A = {
'''configuration_layoutlmv3''': [
'''LAYOUTLMV3_PRETRAI... | 135 | 0 |
"""simple docstring"""
from __future__ import annotations
def _A ( lowercase ):
"""simple docstring"""
a =[True] * limit
a =False
a =False
a =True
for i in range(3 , int(limit**0.5 + 1 ) , 2 ):
a =i * 2
... | 215 |
"""simple docstring"""
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.testi... | 215 | 1 |
import copy
from ...configuration_utils import PretrainedConfig
from ...utils import logging
__lowerCAmelCase : Union[str, Any] = logging.get_logger(__name__)
class snake_case__ (_UpperCamelCase ):
"""simple docstring"""
SCREAMING_SNAKE_CASE_ : Union[str, Any... | 107 |
import pickle
import shutil
import tempfile
import unittest
from transformers import SPIECE_UNDERLINE, XLMRobertaTokenizer, XLMRobertaTokenizerFast
from transformers.testing_utils import get_tests_dir, require_sentencepiece, require_tokenizers, slow
from transformers.utils import cached_property
from ...test_tok... | 107 | 1 |
from abc import ABC, abstractmethod
from argparse import ArgumentParser
class a__ ( __snake_case ):
@staticmethod
@abstractmethod
def __SCREAMING_SNAKE_CASE ( UpperCAmelCase ) -> Any:
raise NotImplementedError()
@abstractmethod
de... | 370 | import copy
import json
import os
import tempfile
from transformers import is_torch_available
from .test_configuration_utils import config_common_kwargs
class a__ ( __snake_case ):
def __init__( self , UpperCAmelCase , UpperCAmelCase=None , UpperCA... | 197 | 0 |
'''simple docstring'''
import math
import random
from typing import Any
from .hill_climbing import SearchProblem
def lowerCamelCase ( __lowerCamelCase : Dict , __lowerCamelCase : bool = True , __lowerCamelCase : float = math.inf , __lowerCamelCase : float ... | 58 |
def __UpperCAmelCase ( __a : int ,__a : list[int] ,__a : int ) -> int:
"""simple docstring"""
def count_of_possible_combinations(__a : int ) -> int:
if target < 0:
return 0
if target == 0:
return 1
... | 235 | 0 |
"""simple docstring"""
import logging
import os
from dataclasses import dataclass, field
from typing import Dict, Optional
import datasets
import numpy as np
import tensorflow as tf
from transformers import (
AutoConfig,
AutoTokenizer,
EvalPrediction,
HfArgumentParser,
PreTrainedTokenizer... | 340 |
"""simple docstring"""
import os
from typing import BinaryIO, Optional, Union
import numpy as np
import pyarrow.parquet as pq
from .. import Audio, Dataset, Features, Image, NamedSplit, Value, config
from ..features.features import FeatureType, _visit
from ..formatting import query_table
from ..packaged_modu... | 340 | 1 |
'''simple docstring'''
import bza
import gzip
import lzma
import os
import shutil
import struct
import tarfile
import warnings
import zipfile
from abc import ABC, abstractmethod
from pathlib import Path
from typing import Dict, List, Optional, Type, Union
from .. import config
from .filelock import FileLock
from .log... | 198 | '''simple docstring'''
import os
import re
import warnings
from shutil import copyfile
from typing import List, Optional, Tuple
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import is_sentencepiece_available, logging
if is_sentencepiece_available():
from .tokenization_ta import TaTo... | 198 | 1 |
def lowercase_ ( A__ ) -> List[Any]:
"""simple docstring"""
snake_case = len(A__ )
for i in range(length - 1 ):
snake_case = i
for k in range(i + 1 , A__ ):
if collection[k] < collection[least]:
snake_ca... | 137 |
def lowercase_ ( A__ = 1000 ) -> int:
"""simple docstring"""
return sum(2 * a * ((a - 1) // 2) for a in range(3 , n + 1 ) )
if __name__ == "__main__":
print(solution())
| 137 | 1 |
from collections import OrderedDict
from typing import Mapping
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
__UpperCAmelCase : Optional[Any] = logging.get_logger(__name__)
__UpperCAmelCase : Tuple = ... | 111 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
_lowerCamelCase =logging.get_logger(__name__)
_lowerCamelCase ={
"facebook/vit-mae-base": "https://huggingface.co/facebook/vit-mae-base/resolve/main/config.json",
# See all ViT MAE models at https://h... | 334 | 0 |
from typing import Dict, List, Optional, Union
import numpy as np
from .feature_extraction_utils import BatchFeature, FeatureExtractionMixin
from .utils import PaddingStrategy, TensorType, is_tf_tensor, is_torch_tensor, logging, to_numpy
__magic_name__ = logging.get_logger(__name__)
... | 355 |
import operator as op
def _lowerCAmelCase ( A__: List[str] ):
'''simple docstring'''
UpperCAmelCase = []
UpperCAmelCase = lambda A__ , A__ : int(x / y ) # noqa: E731 integer division operation
UpperCAmelCase = {
... | 152 | 0 |
import argparse
import os
from io import BytesIO
from pathlib import Path
import requests
from clip_retrieval.clip_client import ClipClient
from PIL import Image
from tqdm import tqdm
def a ( snake_case__: Dict , snake_case__: str , snake_case__: List[str] ... | 30 |
"""simple docstring"""
import pickle
import unittest
import torch
from accelerate import Accelerator
from accelerate.state import AcceleratorState
from accelerate.test_utils import require_cpu
@require_cpu
class lowerCAmelCase_ (unittest.TestCase ):
"""simple docstring"""
... | 25 | 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_mvp impo... | 362 |
'''simple docstring'''
def UpperCAmelCase_ ( __lowercase : str = "The quick brown fox jumps over the lazy dog" , ) -> bool:
'''simple docstring'''
_UpperCAmelCase = set()
# Replace all the whitespace in our sentence
_UpperCAmelCase ... | 156 | 0 |
lowercase : Union[str, Any] = {
"""A""": ["""B""", """C""", """E"""],
"""B""": ["""A""", """D""", """E"""],
"""C""": ["""A""", """F""", """G"""],
"""D""": ["""B"""],
"""E""": ["""A""", """B""", """D"""],
"""F""": ["""C"""],
"""G""": ["""C"""],
}
def A_ ( A__ , ... | 99 |
def lowerCAmelCase_ ( __UpperCAmelCase: int ) -> int:
if not isinstance(__UpperCAmelCase , __UpperCAmelCase ) or number < 0:
raise ValueError('''Input must be a non-negative integer''' )
UpperCamelCase__ : Optional[Any] = 0
whil... | 201 | 0 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tf_available,
is_tokenizers_available,
is_torch_available,
)
__lowercase : Tuple = {
'configuration_distilbert': [
'... | 352 |
'''simple docstring'''
from dataclasses import dataclass
from typing import Optional, Tuple
import torch
from torch import nn
from transformers import RobertaPreTrainedModel, XLMRobertaConfig, XLMRobertaModel
from transformers.utils import ModelOutput
@dataclass
class __UpperCamelCase ( lowerCAme... | 294 | 0 |
import os
from shutil import copyfile
from typing import Any, Dict, List, Optional, Tuple
import sentencepiece as spm
from ...tokenization_utils import AddedToken, PreTrainedTokenizer
from ...utils import logging
__lowerCAmelCase : str =logging.get_logger(__name__)
__lowerCAmelCase : Optional[int] ={'... | 9 |
import json
from typing import TYPE_CHECKING, List, Optional, Tuple
from tokenizers import pre_tokenizers
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import logging
if TYPE_CHECKING:
from transformers.pipelines.conversational import Conversation
__lowerCAmelCase : Optiona... | 9 | 1 |
"""simple docstring"""
import json
import os
import shutil
import tempfile
from unittest import TestCase
from transformers import BartTokenizer, BartTokenizerFast, DPRQuestionEncoderTokenizer, DPRQuestionEncoderTokenizerFast
from transformers.models.bart.configuration_bart import BartConfig
from t... | 326 |
"""simple docstring"""
import argparse
import json
import os
from collections import OrderedDict
import torch
from transformers import LukeConfig, LukeForMaskedLM, MLukeTokenizer, XLMRobertaTokenizer
from transformers.tokenization_utils_base import AddedToken
@torch.no_grad()
def ... | 326 | 1 |
'''simple docstring'''
import requests
def __lowercase ( __lowercase , __lowercase ) -> None:
'''simple docstring'''
_A = {"Content-Type": "application/json"}
_A = requests.post(__lowercase , json={"text": message_body} , headers=__low... | 79 |
'''simple docstring'''
from __future__ import annotations
import unittest
from transformers import AutoTokenizer, PegasusConfig, is_tf_available
from transformers.testing_utils import require_sentencepiece, require_tf, require_tokenizers, slow
from transformers.utils import cached_property
fro... | 349 | 0 |
"""simple docstring"""
from ...configuration_utils import PretrainedConfig
from ...utils import logging
lowercase__ : int = logging.get_logger(__name__)
lowercase__ : Union[str, Any] = {
"""sayakpaul/vit-msn-base""": """https://huggingface.co/sayakpau... | 364 |
"""simple docstring"""
from diffusers.utils.testing_utils import require_onnxruntime
@require_onnxruntime
class UpperCamelCase__ :
"""simple docstring"""
pass
| 289 | 0 |
import os
from shutil import copyfile
from typing import List, Optional, Tuple
from ...tokenization_utils import AddedToken
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import is_sentencepiece_available, logging
if is_sentencepiece_available():
from .tokenization_big_bird import ... | 348 | from functools import lru_cache
@lru_cache
def _snake_case ( lowerCAmelCase : int ):
"""simple docstring"""
if num < 0:
raise ValueError("Number should not be negative." )
return 1 if num in (0, 1) else num * factorial(num - 1 )
if __name__ == "__main__":
import doctest
doct... | 18 | 0 |
import importlib.metadata
import operator
import re
import sys
from typing import Optional
from packaging import version
snake_case : List[str] = {
'''<''': operator.lt,
'''<=''': operator.le,
'''==''': operator.eq,
'''!=''': operator.ne,
'''>=''': operator.ge,
'''>''': ... | 109 |
from __future__ import annotations
def __lowercase ( __lowerCAmelCase : List[Any] , __lowerCAmelCase : Optional[Any] , __lowerCAmelCase : str , __lowerCAmelCase : List[str] ): # noqa: E741
while r - l > 1:
a__ = (l + r... | 109 | 1 |
from __future__ import annotations
from typing import Dict
from ...configuration_utils import PretrainedConfig
A__ = {
'''susnato/ernie-m-base_pytorch''': '''https://huggingface.co/susnato/ernie-m-base_pytorch/blob/main/config.json''',
'''susnato/ernie-m-large_pytorch''': '''htt... | 230 |
from collections import OrderedDict
from typing import TYPE_CHECKING, Any, Mapping, Optional
from packaging import version
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...onnx.utils import compute_effective_axis_dimension
from ...utils import logging
if TYPE_CHECKING:
... | 345 | 0 |
from ..utils import DummyObject, requires_backends
class UpperCamelCase ( metaclass=lowercase__ ):
'''simple docstring'''
lowercase : Optional[int] =["""flax""", """transformers"""]
def __init__( self , *UpperCamelCase_ , ... | 365 |
from __future__ import annotations
from random import random
class UpperCamelCase :
'''simple docstring'''
def __init__( self , UpperCamelCase_ = None ):
lowercase_ :Tuple = value
lowercase_ :Tuple = r... | 252 | 0 |
from __future__ import annotations
UpperCAmelCase__ = list[list[int]]
# assigning initial values to the grid
UpperCAmelCase__ = [
[3, 0, 6, 5, 0, 8, 4, 0, 0],
[5, 2, 0, 0, 0, 0, 0, 0, 0],
[0, 8, 7, 0, 0, 0, 0, 3, 1],
[0, 0, 3, 0, 1, 0, 0, 8, 0],
[9, 0, 0, 8, 6... | 0 |
"""simple docstring"""
import numpy as np
import pandas as pd
from sklearn.preprocessing import MinMaxScaler
from tensorflow.keras.layers import LSTM, Dense
from tensorflow.keras.models import Sequential
if __name__ == "__main__":
__a = pd.read_csv("sample_data.csv", header=None)
__a = ... | 66 | 0 |
'''simple docstring'''
def SCREAMING_SNAKE_CASE__ ( snake_case : int , snake_case : int ) -> str:
"""simple docstring"""
if a < 0 or b < 0:
raise ValueError('the value of both inputs must be positive' )
a : List[str] = ... | 345 | '''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_sentencepiece_available,
is_tokenizers_available,
is_torch_available,
is_vision_available,
)
UpperCamelCase : List[str] = {"""processing_layout... | 345 | 1 |
'''simple docstring'''
from ...configuration_utils import PretrainedConfig
from ...utils import logging
a : Optional[int] = logging.get_logger(__name__)
a : Union[str, Any] = {
'sayakpaul/vit-msn-base': 'https://huggingface.co/sayakpaul/vit-msn-base/resolve/main/config.json',
# See... | 311 |
"""simple docstring"""
from argparse import ArgumentParser
from .env import EnvironmentCommand
def _SCREAMING_SNAKE_CASE ( ):
'''simple docstring'''
lowercase = ArgumentParser('Diffusers CLI tool' , usage='diffusers-cli <command> [<args>]' )
lowercase ... | 220 | 0 |
'''simple docstring'''
import argparse
import os.path as osp
import re
import torch
from safetensors.torch import load_file, save_file
# =================#
# UNet Conversion #
# =================#
UpperCAmelCase = [
# (stable-diffusion, HF Diffusers)
('time_embed.0.weight', 'time_em... | 365 |
'''simple docstring'''
from __future__ import annotations
import os
import tempfile
import unittest
from transformers import ConvBertConfig, is_tf_available
from transformers.testing_utils import require_tf, slow
from ...test_configuration_common import ConfigTester
from ...test_modeling_tf_comm... | 187 | 0 |
'''simple docstring'''
import warnings
from ...utils import logging
from .image_processing_deformable_detr import DeformableDetrImageProcessor
lowerCAmelCase: List[str] = logging.get_logger(__name__)
class a__( UpperCamelCase_ ):
def __init__( self : str ... | 297 | import unittest
from transformers import EsmConfig, is_torch_available
from transformers.testing_utils import TestCasePlus, require_torch, slow, torch_device
from ...test_configuration_common import ConfigTester
from ...test_modeling_common import ModelTesterMixin, ids_tensor, random_attention_mask
from ...tes... | 338 | 0 |
'''simple docstring'''
import unittest
from accelerate import debug_launcher
from accelerate.test_utils import require_cpu, test_ops, test_script
@require_cpu
class UpperCamelCase__( unittest.TestCase ):
def a__( self : List[str] )-> Union[str, Any]:
"""simple... | 353 |
'''simple docstring'''
from __future__ import annotations
from typing import Any
class UpperCamelCase__:
def __init__( self : Any , lowerCAmelCase : int , lowerCAmelCase : int , lowerCAmelCase : float = 0 )-> None:
"""simple docstring""... | 91 | 0 |
"""simple docstring"""
# using dfs for finding eulerian path traversal
def UpperCAmelCase__ (snake_case__ : List[str] , snake_case__ : Tuple , snake_case__ : int , snake_case__ : List[str]=None ):
"""simple docstring"""
_snake_ca... | 64 |
"""simple docstring"""
from math import factorial
A_ = {str(d): factorial(d) for d in range(10)}
def UpperCAmelCase__ (snake_case__ : int ):
"""simple docstring"""
return sum(DIGIT_FACTORIAL[d] for d in str(snake_case__ ) )
def UpperCAmelCas... | 64 | 1 |
# Copyright 2023 The HuggingFace Inc. team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by a... | 134 |
from __future__ import annotations
_snake_case : Union[str, Any] = []
def lowerCAmelCase_ ( __lowerCamelCase , __lowerCamelCase , __lowerCamelCase ):
for i in range(len(__lowerCamelCase ) ):
if board[row][i] == 1:
... | 134 | 1 |
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