
"""simple docstring"""
import string
from math import logaa
def 				a__   (   a   :				str       ,     a   :				str		):

		"""simple docstring"""







		_snake_case     :						str						=   document.translate(
		    str.maketrans(""       ,     ""       ,     string.punctuation		)		).replace("\n"       ,     ""		)
		_snake_case     :						int						=   document_without_punctuation.split(" "		)  # word tokenization
		return len([word for word in tokenize_document if word.lower() == term.lower()]		)
def 				a__   (   a   :				str       ,     a   :				str		):

		"""simple docstring"""







		_snake_case     :						int						=   corpus.lower().translate(
		    str.maketrans(""       ,     ""       ,     string.punctuation		)		)  # strip all punctuation and replace it with ''
		_snake_case     :						Optional[Any]						=   corpus_without_punctuation.split("\n"		)
		_snake_case     :						Any						=   term.lower()
		return (len([doc for doc in docs if term in doc]		), len(UpperCamelCase__		))
def 				a__   (   a   :				int       ,     a   :				int       ,     a   :				Any=False		):

		"""simple docstring"""







		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__   (   a   :				int       ,     a   :				int		):

		"""simple docstring"""







		return round(tf * idf       ,     3		)



"""simple docstring"""
from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available, is_vision_available


_a      :			Optional[int]					=							{
    """configuration_pix2struct""": [
        """PIX2STRUCT_PRETRAINED_CONFIG_ARCHIVE_MAP""",
        """Pix2StructConfig""",
        """Pix2StructTextConfig""",
        """Pix2StructVisionConfig""",
    ],
    """processing_pix2struct""": ["""Pix2StructProcessor"""],
}

try:
    if not is_vision_available():
        raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
    pass
else:
    _a      :			List[Any]					=							["""Pix2StructImageProcessor"""]


try:
    if not is_torch_available():
        raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
    pass
else:
    _a      :			Dict					=							[
        """PIX2STRUCT_PRETRAINED_MODEL_ARCHIVE_LIST""",
        """Pix2StructPreTrainedModel""",
        """Pix2StructForConditionalGeneration""",
        """Pix2StructVisionModel""",
        """Pix2StructTextModel""",
    ]

if TYPE_CHECKING:
    from .configuration_pixastruct import (
        PIX2STRUCT_PRETRAINED_CONFIG_ARCHIVE_MAP,
        PixaStructConfig,
        PixaStructTextConfig,
        PixaStructVisionConfig,
    )
    from .processing_pixastruct import PixaStructProcessor

    try:
        if not is_vision_available():
            raise OptionalDependencyNotAvailable()
    except OptionalDependencyNotAvailable:
        pass
    else:
        from .image_processing_pixastruct import PixaStructImageProcessor

    try:
        if not is_torch_available():
            raise OptionalDependencyNotAvailable()
    except OptionalDependencyNotAvailable:
        pass
    else:
        from .modeling_pixastruct import (
            PIX2STRUCT_PRETRAINED_MODEL_ARCHIVE_LIST,
            PixaStructForConditionalGeneration,
            PixaStructPreTrainedModel,
            PixaStructTextModel,
            PixaStructVisionModel,
        )

else:
    import sys

    _a      :			Optional[int]					=							_LazyModule(__name__, globals()["""__file__"""], _import_structure, module_spec=__spec__)

