code stringlengths 81 54k | code_codestyle int64 0 721 | style_context stringlengths 91 41.9k | style_context_codestyle int64 0 699 | label int64 0 1 |
|---|---|---|---|---|
'''simple docstring'''
def _UpperCAmelCase ( a : str ) -> list:
"""simple docstring"""
lowercase_ : List[Any] = [0] * len(a )
for i in range(1 , len(a ) ):
# use last results for better performance - dynamic programming... | 703 |
'''simple docstring'''
from typing import List, Optional, Union
import numpy as np
import PIL
import torch
from PIL import Image
from ...models import UNetaDConditionModel, VQModel
from ...pipelines import DiffusionPipeline
from ...pipelines.pipeline_utils import ImagePipelineOutput
from ...schedulers import ... | 7 | 0 |
'''simple docstring'''
def _UpperCAmelCase ( a : int = 1_0 ) -> str:
"""simple docstring"""
if not isinstance(a , a ) or n < 0:
raise ValueError('Invalid input' )
lowercase_ : List[str] = 1_0**n
lowercase_ : Optio... | 704 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ..utils import _LazyModule
A: int = {
"config": [
"EXTERNAL_DATA_FORMAT_SIZE_LIMIT",
"OnnxConfig",
"OnnxConfigWithPast",
"OnnxSeq2SeqConfigWithPast",
"PatchingSpec",
],
"convert": ["e... | 7 | 0 |
'''simple docstring'''
import unittest
from transformers import AutoConfig, AutoTokenizer, BertConfig, TensorType, is_flax_available
from transformers.testing_utils import DUMMY_UNKNOWN_IDENTIFIER, require_flax, slow
if is_flax_available():
import jax
from transformers.models.auto.modeling_fla... | 705 |
'''simple docstring'''
import io
import json
import unittest
from parameterized import parameterized
from transformers import FSMTForConditionalGeneration, FSMTTokenizer
from transformers.testing_utils import get_tests_dir, require_torch, slow, torch_device
from utils import calculate_bleu
A: Any ... | 7 | 0 |
'''simple docstring'''
from math import cos, sin, sqrt, tau
from audio_filters.iir_filter import IIRFilter
def _UpperCAmelCase ( a : int , a : int , a : float = 1 / sqrt(2 ) ) -> IIRFilter:
"""simple docstring"""
lowercase_ : str = ta... | 706 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ....utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
A: int = {
"configuration_trajectory_transformer": [
"TRAJECTORY_TRANSFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP",
"TrajectoryTransformerCon... | 7 | 0 |
'''simple docstring'''
def _UpperCAmelCase ( a : int , a : int ) -> int:
"""simple docstring"""
while a != 0:
lowercase_ : int = b % a, a
return b
def _UpperCAmelCase ( a : int , a : int ) -> int:
... | 707 |
'''simple docstring'''
def _UpperCAmelCase ( a : str ) -> str:
"""simple docstring"""
lowercase_ : Dict = 0
# if input_string is "aba" than new_input_string become "a|b|a"
lowercase_ : Dict = ''
lowercase_ : Any = ... | 7 | 0 |
'''simple docstring'''
from __future__ import annotations
import unittest
from transformers import XGLMConfig, XGLMTokenizer, is_tf_available
from transformers.testing_utils import require_tf, slow
from ...test_configuration_common import ConfigTester
from ...test_modeling_tf_common import TFModelTesterMixin... | 708 |
'''simple docstring'''
from pathlib import PurePosixPath
from typing import Optional
import fsspec
from fsspec import AbstractFileSystem
from huggingface_hub.hf_api import DatasetInfo
from ..utils.file_utils import get_authentication_headers_for_url
from ..utils.hub import hf_hub_url
class __magi... | 7 | 0 |
'''simple docstring'''
from collections import OrderedDict
from typing import Mapping
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
A: Optional[Any] = {
"albert-base-v1": "https://huggingface.co/albert-base-v1/resolve/main/config.json",
"albert-large-... | 709 |
'''simple docstring'''
import argparse
import json
from pathlib import Path
import requests
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from transformers import (
BertTokenizer,
ViltConfig,
ViltForImageAndTextRetrieval,
ViltForImagesAndTextClassification,
... | 7 | 0 |
'''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,
resize,
... | 710 |
'''simple docstring'''
def _UpperCAmelCase ( a : list ) -> list:
"""simple docstring"""
for i in range(len(a ) - 1 , 0 , -1 ):
lowercase_ : Any = False
for j in range(a , 0 , -1 ):
... | 7 | 0 |
'''simple docstring'''
import io
import json
import unittest
from parameterized import parameterized
from transformers import FSMTForConditionalGeneration, FSMTTokenizer
from transformers.testing_utils import get_tests_dir, require_torch, slow, torch_device
from utils import calculate_bleu
A: Any ... | 711 |
'''simple docstring'''
from ..utils import DummyObject, requires_backends
class __magic_name__ ( metaclass=UpperCAmelCase_ ):
"""simple docstring"""
SCREAMING_SNAKE_CASE_ : str = ['transformers', 'torch', 'note_seq']
def __init__( self , *_lowercase ... | 7 | 0 |
import argparse
from ...utils.dataclasses import (
ComputeEnvironment,
DistributedType,
DynamoBackend,
PrecisionType,
SageMakerDistributedType,
)
from ..menu import BulletMenu
A: Optional[int] = [
"EAGER",
"AOT_EAGER",
"INDUCTOR",
"NVFUSER",
"AOT_NVFUSER",
... | 712 |
'''simple docstring'''
def _UpperCAmelCase ( a : str , a : str ) -> float:
"""simple docstring"""
def get_matched_characters(a : str , a : str ) -> str:
lowercase_ : Union[str, Any] = []
lowercase_ : Tuple ... | 7 | 0 |
import unittest
from transformers import load_tool
from .test_tools_common import ToolTesterMixin
class __magic_name__ ( unittest.TestCase, UpperCAmelCase_ ):
"""simple docstring"""
def lowerCamelCase__ ( self ) -> Union[str, Any]:
lowercase... | 713 |
'''simple docstring'''
from __future__ import annotations
def _UpperCAmelCase ( a : int = 4 ) -> list[list[int]]:
"""simple docstring"""
lowercase_ : Tuple = abs(a ) or 4
return [[1 + x + y * row_size for x in range(a )] for y in range(a ... | 7 | 0 |
'''simple docstring'''
import json
import logging
import os
import socket
import git
import numpy as np
import torch
logging.basicConfig(
format="%(asctime)s - %(levelname)s - %(name)s - PID: %(process)d - %(message)s",
datefmt="%m/%d/%Y %H:%M:%S",
level=logging.INFO,
)
A: Tuple = l... | 714 |
'''simple docstring'''
# Usage:
# ./gen-card-facebook-wmt19.py
import os
from pathlib import Path
def _UpperCAmelCase ( a : Dict , a : Optional[int] , a : Tuple ) -> Optional[int]:
"""simple docstring"""
lowercase_ : Any = {
'en':... | 7 | 0 |
def _UpperCAmelCase ( a : float , a : float ) -> float:
"""simple docstring"""
return price * (1 + tax_rate)
if __name__ == "__main__":
print(f"""{price_plus_tax(1_0_0, 0.25) = }""")
print(f"""{price_plus_tax(125.50, 0.05) = }""")
| 715 |
'''simple docstring'''
import json
import logging
import os
import socket
import git
import numpy as np
import torch
logging.basicConfig(
format="%(asctime)s - %(levelname)s - %(name)s - PID: %(process)d - %(message)s",
datefmt="%m/%d/%Y %H:%M:%S",
level=logging.INFO,
)
A: Tuple = l... | 7 | 0 |
'''simple docstring'''
import os
import numpy
import onnx
def _UpperCAmelCase ( a : Optional[Any] , a : Any ) -> List[str]:
"""simple docstring"""
lowercase_ : Optional[Any] = a.name
lowercase_ : List[str] = b.name
lowe... | 716 |
'''simple docstring'''
import os
from distutils.util import strtobool
def _UpperCAmelCase ( a : Any , a : int ) -> Any:
"""simple docstring"""
for e in env_keys:
lowercase_ : Optional[Any] = int(os.environ.get(a , -1 ) ... | 7 | 0 |
'''simple docstring'''
import unittest
from diffusers.pipelines.pipeline_utils import is_safetensors_compatible
class __magic_name__ ( unittest.TestCase ):
"""simple docstring"""
def lowerCamelCase__ ( self ) -> Optional[An... | 717 |
'''simple docstring'''
from typing import Dict, Optional
import numpy as np
import datasets
A: int = "\nIoU is the area of overlap between the predicted segmentation and the ground truth divided by the area of union\nbetween the predicted segmentation and the ground truth. For binary (two class... | 7 | 0 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_sentencepiece_available
A: int = {}
try:
if not is_sentencepiece_available():
raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailab... | 718 |
'''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
A: Dict = logging.get_logger(__name__)
A: Optional[Any] ... | 7 | 0 |
import math
def _UpperCAmelCase ( a : float , a : float ) -> float:
"""simple docstring"""
if (
not isinstance(a , (int, float) )
or power_factor < -1
or power_factor > 1
):
raise ValueError('power_factor ... | 719 |
'''simple docstring'''
from ...configuration_utils import PretrainedConfig
from ...utils import logging
A: int = logging.get_logger(__name__)
A: int = {
"bigcode/gpt_bigcode-santacoder": "https://huggingface.co/bigcode/gpt_bigcode-santacoder/resolve/main/config.json",
}
cl... | 7 | 0 |
'''simple docstring'''
from __future__ import annotations
import unittest
from transformers import EsmConfig, is_tf_available
from transformers.testing_utils import require_tf, slow
from ...test_configuration_common import ConfigTester
from ...test_modeling_tf_common import TFModelTesterMixin, floats_tensor,... | 720 |
'''simple docstring'''
import unittest
from diffusers.pipelines.pipeline_utils import is_safetensors_compatible
class __magic_name__ ( unittest.TestCase ):
"""simple docstring"""
def lowerCamelCase__ ( self ) -> Optional[Any]:
lowercase_ : ... | 7 | 0 |
'''simple docstring'''
def _UpperCAmelCase ( a : str ) -> str:
"""simple docstring"""
if not all(char in '01' for char in bin_string ):
raise ValueError('Non-binary value was passed to the function' )
if not bin_string:
raise ValueError(... | 721 |
'''simple docstring'''
import argparse
A: List[Any] = "docs/source/_static/js/custom.js"
def _UpperCAmelCase ( a : Optional[Any] ) -> Optional[Any]:
"""simple docstring"""
with open(a , encoding='utf-8' , newline='\n' ) as f:
... | 7 | 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_torc... | 8 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tokenizers_available, is_torch_available
SCREAMING_SNAKE_CASE = {
'configuration_m2m_100': ['M2M_100_PRETRAINED_CONFIG_ARCHIVE_MAP', 'M2M100Config', 'M2M100OnnxConfig'],
... | 8 | 1 |
'''simple docstring'''
import unittest
from diffusers import FlaxAutoencoderKL
from diffusers.utils import is_flax_available
from diffusers.utils.testing_utils import require_flax
from .test_modeling_common_flax import FlaxModelTesterMixin
if is_flax_available():
import jax
@require_flax
class Upper... | 8 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_torch_available,
)
SCREAMING_SNAKE_CASE = {
'configuration_mega': ['MEGA_PRETRAINED_CONFIG_ARCHIVE_MAP', 'MegaConfig', 'MegaOnnxConfig'],
}
try:
if not ... | 8 | 1 |
'''simple docstring'''
from ...configuration_utils import PretrainedConfig
from ...utils import logging
SCREAMING_SNAKE_CASE = logging.get_logger(__name__)
SCREAMING_SNAKE_CASE = {
'SCUT-DLVCLab/lilt-roberta-en-base': (
'https://huggingface.co/SCUT-DLVCLab/lilt-roberta-en-base/resolve... | 8 |
'''simple docstring'''
from typing import List, Optional, Tuple
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import logging
from .tokenization_herbert import HerbertTokenizer
SCREAMING_SNAKE_CASE = logging.get_logger(__name__)
SCREAMING_SNAKE_CASE = {'vocab_file':... | 8 | 1 |
'''simple docstring'''
def lowercase_ ( __A : Tuple ) -> Dict:
"""simple docstring"""
lowercase : Tuple =0
lowercase : Optional[int] =len(__A )
for i in range(n - 1 ):
for j in range(i + 1 , __A ):
if arr[i] > arr[j]:
nu... | 8 |
'''simple docstring'''
import subprocess
import sys
from transformers import BertConfig, BertModel, BertTokenizer, pipeline
from transformers.testing_utils import TestCasePlus, require_torch
class UpperCAmelCase_ ( __A ):
"""simple docstring"""
@require_torch
def A__ ... | 8 | 1 |
'''simple docstring'''
from dataclasses import dataclass
from typing import Optional, Tuple, Union
import torch
import torch.nn as nn
from ..configuration_utils import ConfigMixin, register_to_config
from ..utils import BaseOutput
from .embeddings import GaussianFourierProjection, TimestepEmbedding, Timeste... | 8 |
'''simple docstring'''
SCREAMING_SNAKE_CASE = 'Alexander Joslin'
import operator as op
from .stack import Stack
def lowercase_ ( __A : str ) -> int:
"""simple docstring"""
lowercase : int ={'''*''': op.mul, '''/''': op.truediv, '''+''': op.add, '''-... | 8 | 1 |
'''simple docstring'''
def lowercase_ ( __A : int ) -> list:
"""simple docstring"""
if bit_count < 0:
raise ValueError('''The given input must be positive''' )
# get the generated string sequence
lowercase : int =gray_code_sequence_string(__A )
#
... | 8 |
'''simple docstring'''
import re
def lowercase_ ( __A : str ) -> bool:
"""simple docstring"""
lowercase : Any =re.compile(R'''^(\+91[\-\s]?)?[0]?(91)?[789]\d{9}$''' )
if match := re.search(__A , __A ):
return match.string == phone
return F... | 8 | 1 |
'''simple docstring'''
import argparse
import requests
import torch
from PIL import Image
from transformers import SwinConfig, SwinForMaskedImageModeling, ViTImageProcessor
def lowercase_ ( __A : Union[str, Any] ) -> Union[str, Any]:
"""simple docstring"""
lowercas... | 8 |
'''simple docstring'''
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_ten... | 8 | 1 |
'''simple docstring'''
import os
import shutil
import tempfile
from unittest import TestCase
from unittest.mock import patch
import numpy as np
from datasets import Dataset
from transformers.models.realm.configuration_realm import RealmConfig
from transformers.models.realm.retrieval_realm import _REALM_BLOC... | 8 |
'''simple docstring'''
import warnings
from typing import List, Optional, Union
from ...processing_utils import ProcessorMixin
from ...tokenization_utils_base import BatchEncoding, PaddingStrategy, PreTokenizedInput, TextInput, TruncationStrategy
from ...utils import TensorType
class UpperCAmelCase_ ( ... | 8 | 1 |
'''simple docstring'''
import argparse
import os
import pickle
import sys
import torch
from transformers import TransfoXLConfig, TransfoXLLMHeadModel, load_tf_weights_in_transfo_xl
from transformers.models.transfo_xl import tokenization_transfo_xl as data_utils
from transformers.models.transfo_xl.tokenizati... | 8 |
'''simple docstring'''
def lowercase_ ( __A : int = 6_0_0_8_5_1_4_7_5_1_4_3 ) -> int:
"""simple docstring"""
try:
lowercase : Any =int(__A )
except (TypeError, ValueError):
raise TypeError('''Parameter n must be int or castable to int.''' )
if n <=... | 8 | 1 |
'''simple docstring'''
import math
import sys
def lowercase_ ( __A : int ) -> int:
"""simple docstring"""
if number != int(__A ):
raise ValueError('''the value of input must be a natural number''' )
if number < 0:
raise ValueError('''the value of input must ... | 8 |
'''simple docstring'''
from __future__ import annotations
import math
def lowercase_ ( __A : float , __A : int ) -> float:
"""simple docstring"""
lowercase : str =u
for i in range(1 , __A ):
lowercase : Any =temp * ... | 8 | 1 |
'''simple docstring'''
import requests
SCREAMING_SNAKE_CASE = 'https://newsapi.org/v1/articles?source=bbc-news&sortBy=top&apiKey='
def lowercase_ ( __A : str ) -> None:
"""simple docstring"""
lowercase : Tuple =requests.get(_NEWS_API + bbc_news_api_k... | 8 |
'''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 transformers.testing_ut... | 8 | 1 |
'''simple docstring'''
import unittest
import numpy as np
from transformers.testing_utils import require_pytesseract, require_torch
from transformers.utils import is_pytesseract_available, is_torch_available
from ...test_image_processing_common import ImageProcessingSavingTestMixin, prepare_image_inputs
... | 8 |
'''simple docstring'''
from __future__ import annotations
SCREAMING_SNAKE_CASE = 8.988E9 # units = N * m^s * C^-2
def lowercase_ ( __A : float , __A : float , __A : float , __A : float ) -> dict[str, float]:
"""simple do... | 8 | 1 |
'''simple docstring'''
import unittest
from transformers import AutoConfig, AutoTokenizer, BertConfig, TensorType, is_flax_available
from transformers.testing_utils import DUMMY_UNKNOWN_IDENTIFIER, require_flax, slow
if is_flax_available():
import jax
from transformers.models.auto.modeling_fla... | 8 |
'''simple docstring'''
import json
import os
from functools import lru_cache
from typing import Dict, List, Optional, Tuple, Union
import regex as re
from ...tokenization_utils import AddedToken, PreTrainedTokenizer
from ...tokenization_utils_base import BatchEncoding, EncodedInput
from ...utils import Padd... | 8 | 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 ... | 8 |
'''simple docstring'''
import mpmath # for roots of unity
import numpy as np
class UpperCAmelCase_ :
"""simple docstring"""
def __init__( self : List[Any] , UpperCAmelCase : Dict=None , UpperCAmelCase : Optional[int]=None ) -> Optional[Any]:
'''s... | 8 | 1 |
'''simple docstring'''
import argparse
from transformers import (
TapasConfig,
TapasForMaskedLM,
TapasForQuestionAnswering,
TapasForSequenceClassification,
TapasModel,
TapasTokenizer,
load_tf_weights_in_tapas,
)
from transformers.utils import logging
logging.set_verbosity_info()... | 8 |
'''simple docstring'''
def lowercase_ ( __A : int , __A : int ) -> str:
"""simple docstring"""
if number < 0 or shift_amount < 0:
raise ValueError('''both inputs must be positive integers''' )
lowercase : List[Any] =str(bin(__A ) )
... | 8 | 1 |
'''simple docstring'''
def lowercase_ ( __A : list , __A : int , __A : int = 0 , __A : int = 0 ) -> int:
"""simple docstring"""
lowercase : List[Any] =right or len(__A ) - 1
if left > right:
return -1
elif l... | 8 |
'''simple docstring'''
import unittest
from transformers import MODEL_FOR_DOCUMENT_QUESTION_ANSWERING_MAPPING, AutoTokenizer, is_vision_available
from transformers.pipelines import pipeline
from transformers.pipelines.document_question_answering import apply_tesseract
from transformers.testing_utils import (... | 8 | 1 |
'''simple docstring'''
import warnings
from ...processing_utils import ProcessorMixin
from ...tokenization_utils_base import BatchEncoding
class UpperCAmelCase_ ( __A ):
"""simple docstring"""
UpperCamelCase_ = ['''image_processor''', '''tokenizer''']
UpperCamelCa... | 8 |
'''simple docstring'''
def lowercase_ ( __A : float , __A : int ) -> float:
"""simple docstring"""
if digit_amount > 0:
return round(number - int(__A ) , __A )
return number - int(__A )
if __name__ == "__main__":
print(decimal_i... | 8 | 1 |
'''simple docstring'''
def lowercase_ ( __A : list ) -> list:
"""simple docstring"""
if len(__A ) <= 1:
return [tuple(__A )]
lowercase : List[str] =[]
def generate(__A : int , __A : list ):
lowercase : Any =[0] *... | 8 |
'''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 ... | 8 | 1 |
'''simple docstring'''
def lowercase_ ( __A : int ) -> bool:
"""simple docstring"""
return sum(i for i in range(1 , number // 2 + 1 ) if number % i == 0 ) == number
if __name__ == "__main__":
print('Program to check whether a number is a Perfect nu... | 8 |
'''simple docstring'''
from __future__ import annotations
import unittest
from transformers import DistilBertConfig, 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_t... | 8 | 1 |
'''simple docstring'''
def lowercase_ ( __A : Optional[Any] ) -> int:
"""simple docstring"""
lowercase : Optional[int] =[0] * len(__A )
lowercase : List[str] =[]
lowercase : List[str] =[1] * len(__A )
for values in graph.values(... | 8 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_sentencepiece_available,
is_tf_available,
is_tokenizers_available,
is_torch_available,
)
SCREAMING_SNAKE_CASE = {
'configuration_rembert': ['REMBER... | 8 | 1 |
'''simple docstring'''
import logging
import os
from .state import PartialState
class UpperCAmelCase_ ( logging.LoggerAdapter ):
"""simple docstring"""
@staticmethod
def A__ ( UpperCAmelCase : List[str] ) -> Optional[int]:
'''simple docstring'''
... | 8 |
'''simple docstring'''
import importlib.metadata
from typing import Union
from packaging.version import Version, parse
from .constants import STR_OPERATION_TO_FUNC
SCREAMING_SNAKE_CASE = parse(importlib.metadata.version('torch'))
def lowercase_ ( __A : Union[str, Version] , ... | 8 | 1 |
'''simple docstring'''
import argparse
import torch
from huggingface_hub import hf_hub_download
from transformers import AutoTokenizer, RobertaPreLayerNormConfig, RobertaPreLayerNormForMaskedLM
from transformers.utils import logging
logging.set_verbosity_info()
SCREAMING_SNAKE_CASE = logging.get_logg... | 8 |
'''simple docstring'''
from __future__ import annotations
from collections.abc import Generator
import requests
from bsa import BeautifulSoup
SCREAMING_SNAKE_CASE = 'https://www.indeed.co.in/jobs?q=mobile+app+development&l='
def lowercase_ ( __A : str = "mumbai" ) -> ... | 8 | 1 |
'''simple docstring'''
import numpy as np
# Importing the Keras libraries and packages
import tensorflow as tf
from tensorflow.keras import layers, models
if __name__ == "__main__":
# Initialising the CNN
# (Sequential- Building the model layer by layer)
SCREAMING_SNAKE_CASE = models.... | 8 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tokenizers_available, is_torch_available
SCREAMING_SNAKE_CASE = {
'configuration_m2m_100': ['M2M_100_PRETRAINED_CONFIG_ARCHIVE_MAP', 'M2M100Config', 'M2M100OnnxConfig'],
... | 8 | 1 |
'''simple docstring'''
from dataclasses import dataclass, field
from typing import Optional
@dataclass
class UpperCAmelCase_ :
"""simple docstring"""
UpperCamelCase_ = field(
default='''codeparrot/codeparrot''' , metadata={'''help''': '''Model name or path o... | 8 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_torch_available,
)
SCREAMING_SNAKE_CASE = {
'configuration_mega': ['MEGA_PRETRAINED_CONFIG_ARCHIVE_MAP', 'MegaConfig', 'MegaOnnxConfig'],
}
try:
if not ... | 8 | 1 |
'''simple docstring'''
import numpy as np
import datasets
SCREAMING_SNAKE_CASE = '\nCompute the Mahalanobis Distance\n\nMahalonobis distance is the distance between a point and a distribution.\nAnd not between two distinct points. It is effectively a multivariate equivalent of the Euclidean distance.\... | 8 |
'''simple docstring'''
from typing import List, Optional, Tuple
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import logging
from .tokenization_herbert import HerbertTokenizer
SCREAMING_SNAKE_CASE = logging.get_logger(__name__)
SCREAMING_SNAKE_CASE = {'vocab_file':... | 8 | 1 |
'''simple docstring'''
import os
from pathlib import Path
from unittest.mock import patch
import pytest
import zstandard as zstd
from datasets.download.download_config import DownloadConfig
from datasets.utils.file_utils import (
OfflineModeIsEnabled,
cached_path,
fsspec_get,
fsspec_head,
... | 8 |
'''simple docstring'''
import subprocess
import sys
from transformers import BertConfig, BertModel, BertTokenizer, pipeline
from transformers.testing_utils import TestCasePlus, require_torch
class UpperCAmelCase_ ( __A ):
"""simple docstring"""
@require_torch
def A__ ... | 8 | 1 |
'''simple docstring'''
import argparse
import json
from collections import OrderedDict
from functools import partial
from pathlib import Path
import timm
import torch
from huggingface_hub import hf_hub_download
from transformers import LevitConfig, LevitForImageClassificationWithTeacher, LevitImageProcessor... | 8 |
'''simple docstring'''
SCREAMING_SNAKE_CASE = 'Alexander Joslin'
import operator as op
from .stack import Stack
def lowercase_ ( __A : str ) -> int:
"""simple docstring"""
lowercase : int ={'''*''': op.mul, '''/''': op.truediv, '''+''': op.add, '''-... | 8 | 1 |
'''simple docstring'''
import argparse
import torch
from transformers import (
EncodecConfig,
EncodecFeatureExtractor,
EncodecModel,
logging,
)
# checkpoints downloaded from:
# https://dl.fbaipublicfiles.com/encodec/v0/encodec_24khz-d7cc33bc.th
# https://huggingface.co/facebook/musicgen-sm... | 8 |
'''simple docstring'''
import re
def lowercase_ ( __A : str ) -> bool:
"""simple docstring"""
lowercase : Any =re.compile(R'''^(\+91[\-\s]?)?[0]?(91)?[789]\d{9}$''' )
if match := re.search(__A , __A ):
return match.string == phone
return F... | 8 | 1 |
'''simple docstring'''
class UpperCAmelCase_ :
"""simple docstring"""
def __init__( self : List[str] ) -> None:
'''simple docstring'''
lowercase : dict[str, TrieNode] ={} # Mapping from char to TrieNode
lowercase : Optional[int] =Fal... | 8 |
'''simple docstring'''
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_ten... | 8 | 1 |
'''simple docstring'''
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_ten... | 8 |
'''simple docstring'''
import warnings
from typing import List, Optional, Union
from ...processing_utils import ProcessorMixin
from ...tokenization_utils_base import BatchEncoding, PaddingStrategy, PreTokenizedInput, TextInput, TruncationStrategy
from ...utils import TensorType
class UpperCAmelCase_ ( ... | 8 | 1 |
'''simple docstring'''
import argparse
import json
from pathlib import Path
import requests
import timm
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from transformers import DeiTImageProcessor, ViTConfig, ViTForImageClassification, ViTImageProcessor, ViTModel
from transform... | 8 |
'''simple docstring'''
def lowercase_ ( __A : int = 6_0_0_8_5_1_4_7_5_1_4_3 ) -> int:
"""simple docstring"""
try:
lowercase : Any =int(__A )
except (TypeError, ValueError):
raise TypeError('''Parameter n must be int or castable to int.''' )
if n <=... | 8 | 1 |
'''simple docstring'''
import numpy as np
import torch
import tqdm
from ...models.unet_ad import UNetaDModel
from ...pipelines import DiffusionPipeline
from ...utils import randn_tensor
from ...utils.dummy_pt_objects import DDPMScheduler
class UpperCAmelCase_ ( __A ):
"""simple docstring"... | 8 |
'''simple docstring'''
from __future__ import annotations
import math
def lowercase_ ( __A : float , __A : int ) -> float:
"""simple docstring"""
lowercase : str =u
for i in range(1 , __A ):
lowercase : Any =temp * ... | 8 | 1 |
'''simple docstring'''
import re
from flax.core.frozen_dict import freeze
from flax.traverse_util import flatten_dict, unflatten_dict
from jax.experimental import PartitionSpec as P
# Sentinels
SCREAMING_SNAKE_CASE = object()
# For specifying empty leaf dict `{}`
SCREAMING_SNAKE_CASE = object()
... | 8 |
'''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 transformers.testing_ut... | 8 | 1 |
'''simple docstring'''
import warnings
from ..trainer import Trainer
from ..utils import logging
SCREAMING_SNAKE_CASE = logging.get_logger(__name__)
class UpperCAmelCase_ ( __A ):
"""simple docstring"""
def __init__( self : Any , UpperCAmelCase : Any=None ... | 8 |
'''simple docstring'''
from __future__ import annotations
SCREAMING_SNAKE_CASE = 8.988E9 # units = N * m^s * C^-2
def lowercase_ ( __A : float , __A : float , __A : float , __A : float ) -> dict[str, float]:
"""simple do... | 8 | 1 |
'''simple docstring'''
import argparse
import os
from pathlib import Path
from typing import Dict
import tensorflow as tf
import torch
from tqdm import tqdm
from transformers import PegasusConfig, PegasusForConditionalGeneration, PegasusTokenizer
from transformers.models.pegasus.configuration_pegasus import... | 8 |
'''simple docstring'''
import json
import os
from functools import lru_cache
from typing import Dict, List, Optional, Tuple, Union
import regex as re
from ...tokenization_utils import AddedToken, PreTrainedTokenizer
from ...tokenization_utils_base import BatchEncoding, EncodedInput
from ...utils import Padd... | 8 | 1 |
'''simple docstring'''
import sys
import tempfile
import unittest
import unittest.mock as mock
from pathlib import Path
from huggingface_hub import HfFolder, delete_repo
from requests.exceptions import HTTPError
from transformers import AutoFeatureExtractor, WavaVecaFeatureExtractor
from transformers.testin... | 8 |
'''simple docstring'''
import mpmath # for roots of unity
import numpy as np
class UpperCAmelCase_ :
"""simple docstring"""
def __init__( self : List[Any] , UpperCAmelCase : Dict=None , UpperCAmelCase : Optional[int]=None ) -> Optional[Any]:
'''s... | 8 | 1 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tf_available, is_torch_available
SCREAMING_SNAKE_CASE = {
'configuration_data2vec_audio': ['DATA2VEC_AUDIO_PRETRAINED_CONFIG_ARCHIVE_MAP', 'Data2VecAudioConfig'],
'confi... | 8 |
'''simple docstring'''
def lowercase_ ( __A : int , __A : int ) -> str:
"""simple docstring"""
if number < 0 or shift_amount < 0:
raise ValueError('''both inputs must be positive integers''' )
lowercase : List[Any] =str(bin(__A ) )
... | 8 | 1 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tensorflow_text_available, is_torch_available
SCREAMING_SNAKE_CASE = {
'configuration_ernie': ['ERNIE_PRETRAINED_CONFIG_ARCHIVE_MAP', 'ErnieConfig', 'ErnieOnnxConfig'],
}
t... | 8 |
'''simple docstring'''
import unittest
from transformers import MODEL_FOR_DOCUMENT_QUESTION_ANSWERING_MAPPING, AutoTokenizer, is_vision_available
from transformers.pipelines import pipeline
from transformers.pipelines.document_question_answering import apply_tesseract
from transformers.testing_utils import (... | 8 | 1 |
'''simple docstring'''
from typing import List, Optional, Tuple
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import logging
from .tokenization_herbert import HerbertTokenizer
SCREAMING_SNAKE_CASE = logging.get_logger(__name__)
SCREAMING_SNAKE_CASE = {'vocab_file':... | 8 |
'''simple docstring'''
def lowercase_ ( __A : float , __A : int ) -> float:
"""simple docstring"""
if digit_amount > 0:
return round(number - int(__A ) , __A )
return number - int(__A )
if __name__ == "__main__":
print(decimal_i... | 8 | 1 |
'''simple docstring'''
from __future__ import annotations
import math
def lowercase_ ( __A : list , __A : list ) -> list:
"""simple docstring"""
if len(__A ) != 2 or len(a[0] ) != 2 or len(__A ) != 2 or len(b[0] ) != 2:
raise Exception('''Ma... | 8 |
'''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 ... | 8 | 1 |
'''simple docstring'''
import argparse
import json
from dataclasses import dataclass, field
from functools import partial
from pathlib import Path
from typing import Callable, Dict, List, Tuple
import timm
import torch
import torch.nn as nn
from classy_vision.models.regnet import RegNet, RegNetParams, RegNet... | 8 |
'''simple docstring'''
from __future__ import annotations
import unittest
from transformers import DistilBertConfig, 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_t... | 8 | 1 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tf_available,
is_tokenizers_available,
is_torch_available,
)
SCREAMING_SNAKE_CASE = {
'configuration_roformer': ['ROFORMER_PRETR... | 8 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_sentencepiece_available,
is_tf_available,
is_tokenizers_available,
is_torch_available,
)
SCREAMING_SNAKE_CASE = {
'configuration_rembert': ['REMBER... | 8 | 1 |
'''simple docstring'''
import os
import sys
import tempfile
import unittest
import unittest.mock as mock
from pathlib import Path
from huggingface_hub import HfFolder, delete_repo
from huggingface_hub.file_download import http_get
from requests.exceptions import HTTPError
from transformers import (
Albe... | 8 |
'''simple docstring'''
import importlib.metadata
from typing import Union
from packaging.version import Version, parse
from .constants import STR_OPERATION_TO_FUNC
SCREAMING_SNAKE_CASE = parse(importlib.metadata.version('torch'))
def lowercase_ ( __A : Union[str, Version] , ... | 8 | 1 |
'''simple docstring'''
from ...utils import (
OptionalDependencyNotAvailable,
is_torch_available,
is_transformers_available,
is_transformers_version,
)
try:
if not (is_transformers_available() and is_torch_available()):
raise OptionalDependencyNotAvailable()
except Optional... | 8 |
'''simple docstring'''
from __future__ import annotations
from collections.abc import Generator
import requests
from bsa import BeautifulSoup
SCREAMING_SNAKE_CASE = 'https://www.indeed.co.in/jobs?q=mobile+app+development&l='
def lowercase_ ( __A : str = "mumbai" ) -> ... | 8 | 1 |
'''simple docstring'''
from manim import *
class UpperCAmelCase_ ( __A ):
"""simple docstring"""
def A__ ( self : List[Any] ) -> int:
'''simple docstring'''
lowercase : Tuple =Rectangle(height=0.5 , width=0.5 )
lowercase... | 8 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tokenizers_available, is_torch_available
SCREAMING_SNAKE_CASE = {
'configuration_m2m_100': ['M2M_100_PRETRAINED_CONFIG_ARCHIVE_MAP', 'M2M100Config', 'M2M100OnnxConfig'],
... | 8 | 1 |
'''simple docstring'''
from .integrations import (
is_optuna_available,
is_ray_available,
is_sigopt_available,
is_wandb_available,
run_hp_search_optuna,
run_hp_search_ray,
run_hp_search_sigopt,
run_hp_search_wandb,
)
from .trainer_utils import (
HPSearchBackend,
default... | 8 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_torch_available,
)
SCREAMING_SNAKE_CASE = {
'configuration_mega': ['MEGA_PRETRAINED_CONFIG_ARCHIVE_MAP', 'MegaConfig', 'MegaOnnxConfig'],
}
try:
if not ... | 8 | 1 |
'''simple docstring'''
from __future__ import annotations
from typing import Any
class UpperCAmelCase_ ( __A ):
"""simple docstring"""
pass
class UpperCAmelCase_ :
"""simple docstring"""
def __init__( self : Union[str, Any] , UpperCAmelCa... | 8 |
'''simple docstring'''
from typing import List, Optional, Tuple
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import logging
from .tokenization_herbert import HerbertTokenizer
SCREAMING_SNAKE_CASE = logging.get_logger(__name__)
SCREAMING_SNAKE_CASE = {'vocab_file':... | 8 | 1 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_torch_available,
)
SCREAMING_SNAKE_CASE = {
'configuration_mega': ['MEGA_PRETRAINED_CONFIG_ARCHIVE_MAP', 'MegaConfig', 'MegaOnnxConfig'],
}
try:
if not ... | 8 |
'''simple docstring'''
import subprocess
import sys
from transformers import BertConfig, BertModel, BertTokenizer, pipeline
from transformers.testing_utils import TestCasePlus, require_torch
class UpperCAmelCase_ ( __A ):
"""simple docstring"""
@require_torch
def A__ ... | 8 | 1 |
'''simple docstring'''
from collections import OrderedDict
from typing import Mapping
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
SCREAMING_SNAKE_CASE = logging.get_logger(__name__)
SCREAMING_SNAKE_CASE = {
'xlm-mlm-en-2048'... | 8 |
'''simple docstring'''
SCREAMING_SNAKE_CASE = 'Alexander Joslin'
import operator as op
from .stack import Stack
def lowercase_ ( __A : str ) -> int:
"""simple docstring"""
lowercase : int ={'''*''': op.mul, '''/''': op.truediv, '''+''': op.add, '''-... | 8 | 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 ImageProcessingSavingTestMixin, ... | 8 |
'''simple docstring'''
import re
def lowercase_ ( __A : str ) -> bool:
"""simple docstring"""
lowercase : Any =re.compile(R'''^(\+91[\-\s]?)?[0]?(91)?[789]\d{9}$''' )
if match := re.search(__A , __A ):
return match.string == phone
return F... | 8 | 1 |
'''simple docstring'''
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():
f... | 8 |
'''simple docstring'''
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_ten... | 8 | 1 |
'''simple docstring'''
import numpy as np
from transformers import BatchFeature
from transformers.testing_utils import require_tf, require_torch
from .test_feature_extraction_common import FeatureExtractionSavingTestMixin
class UpperCAmelCase_ ( __A ):
"""simple docstring"""
Up... | 8 |
'''simple docstring'''
import warnings
from typing import List, Optional, Union
from ...processing_utils import ProcessorMixin
from ...tokenization_utils_base import BatchEncoding, PaddingStrategy, PreTokenizedInput, TextInput, TruncationStrategy
from ...utils import TensorType
class UpperCAmelCase_ ( ... | 8 | 1 |
'''simple docstring'''
from __future__ import annotations
import numpy as np
def lowercase_ ( __A : list[float] ) -> Any:
"""simple docstring"""
return np.maximum(0 , __A )
if __name__ == "__main__":
print(np.array(relu([-1, 0, 5]))) # --> [0, 0,... | 8 |
'''simple docstring'''
def lowercase_ ( __A : int = 6_0_0_8_5_1_4_7_5_1_4_3 ) -> int:
"""simple docstring"""
try:
lowercase : Any =int(__A )
except (TypeError, ValueError):
raise TypeError('''Parameter n must be int or castable to int.''' )
if n <=... | 8 | 1 |
'''simple docstring'''
from __future__ import annotations
from functools import lru_cache
from math import ceil
SCREAMING_SNAKE_CASE = 100
SCREAMING_SNAKE_CASE = set(range(3, NUM_PRIMES, 2))
primes.add(2)
SCREAMING_SNAKE_CASE = 42
for prime in range(3, ceil(NUM_PRIMES**0.5), 2):
if pr... | 8 |
'''simple docstring'''
from __future__ import annotations
import math
def lowercase_ ( __A : float , __A : int ) -> float:
"""simple docstring"""
lowercase : str =u
for i in range(1 , __A ):
lowercase : Any =temp * ... | 8 | 1 |
'''simple docstring'''
def lowercase_ ( __A : list ) -> list:
"""simple docstring"""
lowercase : str =False
while is_sorted is False: # Until all the indices are traversed keep looping
lowercase : Optional[Any] =True
for i in range(0 , ... | 8 |
'''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 transformers.testing_ut... | 8 | 1 |
'''simple docstring'''
import argparse
import os
# New Code #
import evaluate
import torch
from datasets import load_dataset
from torch.optim import AdamW
from torch.utils.data import DataLoader
from transformers import AutoModelForSequenceClassification, AutoTokenizer, get_linear_schedule_with_warmup, set_s... | 8 |
'''simple docstring'''
from __future__ import annotations
SCREAMING_SNAKE_CASE = 8.988E9 # units = N * m^s * C^-2
def lowercase_ ( __A : float , __A : float , __A : float , __A : float ) -> dict[str, float]:
"""simple do... | 8 | 1 |
'''simple docstring'''
import inspect
import os
import sys
import unittest
import accelerate
from accelerate.test_utils import execute_subprocess_async, require_tpu
class UpperCAmelCase_ ( unittest.TestCase ):
"""simple docstring"""
def A__ ( self : Dict ) -> int:... | 8 |
'''simple docstring'''
import json
import os
from functools import lru_cache
from typing import Dict, List, Optional, Tuple, Union
import regex as re
from ...tokenization_utils import AddedToken, PreTrainedTokenizer
from ...tokenization_utils_base import BatchEncoding, EncodedInput
from ...utils import Padd... | 8 | 1 |
'''simple docstring'''
def lowercase_ ( __A : float , __A : int ) -> float:
"""simple docstring"""
if digit_amount > 0:
return round(number - int(__A ) , __A )
return number - int(__A )
if __name__ == "__main__":
print(decimal_i... | 8 |
'''simple docstring'''
import mpmath # for roots of unity
import numpy as np
class UpperCAmelCase_ :
"""simple docstring"""
def __init__( self : List[Any] , UpperCAmelCase : Dict=None , UpperCAmelCase : Optional[int]=None ) -> Optional[Any]:
'''s... | 8 | 1 |
'''simple docstring'''
import unittest
from transformers import MODEL_FOR_DOCUMENT_QUESTION_ANSWERING_MAPPING, AutoTokenizer, is_vision_available
from transformers.pipelines import pipeline
from transformers.pipelines.document_question_answering import apply_tesseract
from transformers.testing_utils import (... | 8 |
'''simple docstring'''
def lowercase_ ( __A : int , __A : int ) -> str:
"""simple docstring"""
if number < 0 or shift_amount < 0:
raise ValueError('''both inputs must be positive integers''' )
lowercase : List[Any] =str(bin(__A ) )
... | 8 | 1 |
'''simple docstring'''
# limitations under the License.
from typing import Optional, Tuple, Union
import torch
from diffusers import DiffusionPipeline, ImagePipelineOutput
class UpperCAmelCase_ ( __A ):
"""simple docstring"""
def __init__( self : Optional[Any] , U... | 8 |
'''simple docstring'''
import unittest
from transformers import MODEL_FOR_DOCUMENT_QUESTION_ANSWERING_MAPPING, AutoTokenizer, is_vision_available
from transformers.pipelines import pipeline
from transformers.pipelines.document_question_answering import apply_tesseract
from transformers.testing_utils import (... | 8 | 1 |
'''simple docstring'''
from __future__ import annotations
from collections.abc import Sequence
from typing import Literal
def lowercase_ ( __A : str , __A : str ) -> str | Literal[False]:
"""simple docstring"""
lowercase : str =list(__A )... | 8 |
'''simple docstring'''
def lowercase_ ( __A : float , __A : int ) -> float:
"""simple docstring"""
if digit_amount > 0:
return round(number - int(__A ) , __A )
return number - int(__A )
if __name__ == "__main__":
print(decimal_i... | 8 | 1 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_sentencepiece_available,
is_tf_available,
is_tokenizers_available,
is_torch_available,
)
SCREAMING_SNAKE_CASE = {'configuration_... | 8 |
'''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 ... | 8 | 1 |
'''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_fast import BertTokenizerFast
from .tokenization_dpr import ... | 8 |
'''simple docstring'''
from __future__ import annotations
import unittest
from transformers import DistilBertConfig, 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_t... | 8 | 1 |
'''simple docstring'''
def lowercase_ ( __A : int = 1_0_0_0 ) -> int:
"""simple docstring"""
lowercase : List[str] =-1
lowercase : Optional[int] =0
for a in range(1 , n // 3 ):
# Solving the two equations a**2+b**2=c**2 and a+b+c=N ... | 8 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_sentencepiece_available,
is_tf_available,
is_tokenizers_available,
is_torch_available,
)
SCREAMING_SNAKE_CASE = {
'configuration_rembert': ['REMBER... | 8 | 1 |
'''simple docstring'''
class UpperCAmelCase_ :
"""simple docstring"""
def __init__( self : List[Any] , UpperCAmelCase : list ) -> None:
'''simple docstring'''
lowercase : Union[str, Any] =set_counts
lowercase : Any =max(Up... | 8 |
'''simple docstring'''
import importlib.metadata
from typing import Union
from packaging.version import Version, parse
from .constants import STR_OPERATION_TO_FUNC
SCREAMING_SNAKE_CASE = parse(importlib.metadata.version('torch'))
def lowercase_ ( __A : Union[str, Version] , ... | 8 | 1 |
'''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
from ..auto import CONFIG_MAPPING
SCREAMING_SNAKE_CASE = logging.get_logg... | 8 |
'''simple docstring'''
from __future__ import annotations
from collections.abc import Generator
import requests
from bsa import BeautifulSoup
SCREAMING_SNAKE_CASE = 'https://www.indeed.co.in/jobs?q=mobile+app+development&l='
def lowercase_ ( __A : str = "mumbai" ) -> ... | 8 | 1 |
'''simple docstring'''
from tempfile import TemporaryDirectory
from unittest import TestCase
from unittest.mock import MagicMock, patch
from transformers import AutoModel, TFAutoModel
from transformers.onnx import FeaturesManager
from transformers.testing_utils import SMALL_MODEL_IDENTIFIER, require_tf, requ... | 8 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tokenizers_available, is_torch_available
SCREAMING_SNAKE_CASE = {
'configuration_m2m_100': ['M2M_100_PRETRAINED_CONFIG_ARCHIVE_MAP', 'M2M100Config', 'M2M100OnnxConfig'],
... | 8 | 1 |
'''simple docstring'''
from dataclasses import dataclass, field
from typing import ClassVar, Dict
from ..features import Features, Value
from .base import TaskTemplate
@dataclass(frozen=__A )
class UpperCAmelCase_ ( __A ):
"""simple docstring"""
UpperCamelCase_ = fie... | 8 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_torch_available,
)
SCREAMING_SNAKE_CASE = {
'configuration_mega': ['MEGA_PRETRAINED_CONFIG_ARCHIVE_MAP', 'MegaConfig', 'MegaOnnxConfig'],
}
try:
if not ... | 8 | 1 |
'''simple docstring'''
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, ... | 8 |
'''simple docstring'''
from typing import List, Optional, Tuple
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import logging
from .tokenization_herbert import HerbertTokenizer
SCREAMING_SNAKE_CASE = logging.get_logger(__name__)
SCREAMING_SNAKE_CASE = {'vocab_file':... | 8 | 1 |
'''simple docstring'''
from __future__ import annotations
import unittest
from transformers import DistilBertConfig, 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_t... | 8 |
'''simple docstring'''
import subprocess
import sys
from transformers import BertConfig, BertModel, BertTokenizer, pipeline
from transformers.testing_utils import TestCasePlus, require_torch
class UpperCAmelCase_ ( __A ):
"""simple docstring"""
@require_torch
def A__ ... | 8 | 1 |
'''simple docstring'''
import gc
import random
import unittest
import numpy as np
import torch
from transformers import (
CLIPImageProcessor,
CLIPTextConfig,
CLIPTextModel,
CLIPTokenizer,
CLIPVisionConfig,
CLIPVisionModelWithProjection,
)
from diffusers import AutoencoderKL, DDIMSche... | 8 |
'''simple docstring'''
SCREAMING_SNAKE_CASE = 'Alexander Joslin'
import operator as op
from .stack import Stack
def lowercase_ ( __A : str ) -> int:
"""simple docstring"""
lowercase : int ={'''*''': op.mul, '''/''': op.truediv, '''+''': op.add, '''-... | 8 | 1 |
'''simple docstring'''
import sys
SCREAMING_SNAKE_CASE = (
'73167176531330624919225119674426574742355349194934'
'96983520312774506326239578318016984801869478851843'
'85861560789112949495459501737958331952853208805511'
'12540698747158523863050715693290963295227443043557'
'668966489504... | 8 |
'''simple docstring'''
import re
def lowercase_ ( __A : str ) -> bool:
"""simple docstring"""
lowercase : Any =re.compile(R'''^(\+91[\-\s]?)?[0]?(91)?[789]\d{9}$''' )
if match := re.search(__A , __A ):
return match.string == phone
return F... | 8 | 1 |
'''simple docstring'''
from typing import List, Union
import numpy as np
from ..utils import add_end_docstrings, is_torch_available, is_vision_available, logging, requires_backends
from .base import PIPELINE_INIT_ARGS, Pipeline
if is_vision_available():
from PIL import Image
from ..image_util... | 8 |
'''simple docstring'''
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_ten... | 8 | 1 |
'''simple docstring'''
import pytest
from datasets.utils.sharding import _distribute_shards, _number_of_shards_in_gen_kwargs, _split_gen_kwargs
@pytest.mark.parametrize(
'''kwargs, expected''' , [
({'''num_shards''': 0, '''max_num_jobs''': 1}, []),
({'''num_shards''': 1_0, '''m... | 8 |
'''simple docstring'''
import warnings
from typing import List, Optional, Union
from ...processing_utils import ProcessorMixin
from ...tokenization_utils_base import BatchEncoding, PaddingStrategy, PreTokenizedInput, TextInput, TruncationStrategy
from ...utils import TensorType
class UpperCAmelCase_ ( ... | 8 | 1 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tokenizers_available, is_torch_available
SCREAMING_SNAKE_CASE = {
'configuration_m2m_100': ['M2M_100_PRETRAINED_CONFIG_ARCHIVE_MAP', 'M2M100Config', 'M2M100OnnxConfig'],
... | 8 |
'''simple docstring'''
def lowercase_ ( __A : int = 6_0_0_8_5_1_4_7_5_1_4_3 ) -> int:
"""simple docstring"""
try:
lowercase : Any =int(__A )
except (TypeError, ValueError):
raise TypeError('''Parameter n must be int or castable to int.''' )
if n <=... | 8 | 1 |
'''simple docstring'''
import json
import os
import re
import shutil
import tempfile
import unittest
from typing import Tuple
from transformers import AddedToken, BatchEncoding, ByTaTokenizer
from transformers.utils import cached_property, is_tf_available, is_torch_available
from ...test_tokenization_common... | 8 |
'''simple docstring'''
from __future__ import annotations
import math
def lowercase_ ( __A : float , __A : int ) -> float:
"""simple docstring"""
lowercase : str =u
for i in range(1 , __A ):
lowercase : Any =temp * ... | 8 | 1 |
'''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
from ...utils.backbone_utils import BackboneConfigMixin, get_aligned_output_feat... | 8 |
'''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 transformers.testing_ut... | 8 | 1 |
'''simple docstring'''
class UpperCAmelCase_ :
"""simple docstring"""
def __init__( self : Dict , UpperCAmelCase : Any ) -> Dict:
'''simple docstring'''
lowercase : str =val
lowercase : Tuple =None
lowercase : ... | 8 |
'''simple docstring'''
from __future__ import annotations
SCREAMING_SNAKE_CASE = 8.988E9 # units = N * m^s * C^-2
def lowercase_ ( __A : float , __A : float , __A : float , __A : float ) -> dict[str, float]:
"""simple do... | 8 | 1 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_sentencepiece_available,
is_tf_available,
is_tokenizers_available,
is_torch_available,
)
SCREAMING_SNAKE_CASE = {
'configuration_rembert': ['REMBER... | 8 |
'''simple docstring'''
import json
import os
from functools import lru_cache
from typing import Dict, List, Optional, Tuple, Union
import regex as re
from ...tokenization_utils import AddedToken, PreTrainedTokenizer
from ...tokenization_utils_base import BatchEncoding, EncodedInput
from ...utils import Padd... | 8 | 1 |
'''simple docstring'''
from dataclasses import dataclass
from typing import Optional, Tuple, Union
import torch
import torch.nn as nn
from ..configuration_utils import ConfigMixin, register_to_config
from ..utils import BaseOutput, apply_forward_hook
from .modeling_utils import ModelMixin
from .vae import D... | 8 |
'''simple docstring'''
import mpmath # for roots of unity
import numpy as np
class UpperCAmelCase_ :
"""simple docstring"""
def __init__( self : List[Any] , UpperCAmelCase : Dict=None , UpperCAmelCase : Optional[int]=None ) -> Optional[Any]:
'''s... | 8 | 1 |
'''simple docstring'''
# Copyright 2023 The HuggingFace Inc. team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENS... | 8 |
'''simple docstring'''
def lowercase_ ( __A : int , __A : int ) -> str:
"""simple docstring"""
if number < 0 or shift_amount < 0:
raise ValueError('''both inputs must be positive integers''' )
lowercase : List[Any] =str(bin(__A ) )
... | 8 | 1 |
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