import string
from math import logaa
def       A	(    _lowercase		,  _lowercase						):
						SCREAMING_SNAKE_CASE							:    Dict							=							document.translate(
						    str.maketrans(''''''		,  ''''''		,  string.punctuation						)						).replace('''\n'''		,  ''''''						)
						SCREAMING_SNAKE_CASE							:    Any							=							document_without_punctuation.split(''' '''						)  # word tokenization
						return len([word for word in tokenize_document if word.lower() == term.lower()]						)
def       A	(    _lowercase		,  _lowercase						):
						SCREAMING_SNAKE_CASE							:    List[Any]							=							corpus.lower().translate(
						    str.maketrans(''''''		,  ''''''		,  string.punctuation						)						)  # strip all punctuation and replace it with ''
						SCREAMING_SNAKE_CASE							:    Dict							=							corpus_without_punctuation.split('''\n'''						)
						SCREAMING_SNAKE_CASE							:    int							=							term.lower()
						return (len([doc for doc in docs if term in doc]						), len(_lowercase						))
def       A	(    _lowercase		,  _lowercase		,  _lowercase=False						):
						if smoothing:
												if n == 0:
																		raise ValueError('''log10(0) is undefined.'''						)
												return round(1 + logaa(n / (1 + df)						)		,  3						)

						if df == 0:
												raise ZeroDivisionError('''df must be > 0'''						)
						elif n == 0:
												raise ValueError('''log10(0) is undefined.'''						)
						return round(logaa(n / df						)		,  3						)



def       A	(    _lowercase		,  _lowercase						):
						return round(tf * idf		,  3						)






from typing import TYPE_CHECKING

from ...utils import (
    OptionalDependencyNotAvailable,
    _LazyModule,
    is_torch_available,
)


__UpperCamelCase		:       Tuple									=     {
    'configuration_swiftformer': [
        'SWIFTFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP',
        'SwiftFormerConfig',
        'SwiftFormerOnnxConfig',
    ]
}

try:
					if not is_torch_available():
										raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
					pass
else:
					__UpperCamelCase		:       Optional[Any]									=     [
					    'SWIFTFORMER_PRETRAINED_MODEL_ARCHIVE_LIST',
					    'SwiftFormerForImageClassification',
					    'SwiftFormerModel',
					    'SwiftFormerPreTrainedModel',
					]

if TYPE_CHECKING:
					from .configuration_swiftformer import (
					    SWIFTFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP,
					    SwiftFormerConfig,
					    SwiftFormerOnnxConfig,
					)

					try:
										if not is_torch_available():
															raise OptionalDependencyNotAvailable()
					except OptionalDependencyNotAvailable:
										pass
					else:
										from .modeling_swiftformer import (
										    SWIFTFORMER_PRETRAINED_MODEL_ARCHIVE_LIST,
										    SwiftFormerForImageClassification,
										    SwiftFormerModel,
										    SwiftFormerPreTrainedModel,
										)

else:
					import sys

					__UpperCamelCase		:       List[Any]									=     _LazyModule(__name__, globals()['__file__'], _import_structure, module_spec=__spec__)





