
from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available


lowerCamelCase      ={
    "configuration_clipseg": [
        "CLIPSEG_PRETRAINED_CONFIG_ARCHIVE_MAP",
        "CLIPSegConfig",
        "CLIPSegTextConfig",
        "CLIPSegVisionConfig",
    ],
    "processing_clipseg": ["CLIPSegProcessor"],
}

try:
    if not is_torch_available():
        raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
    pass
else:
    lowerCamelCase      =[
        "CLIPSEG_PRETRAINED_MODEL_ARCHIVE_LIST",
        "CLIPSegModel",
        "CLIPSegPreTrainedModel",
        "CLIPSegTextModel",
        "CLIPSegVisionModel",
        "CLIPSegForImageSegmentation",
    ]

if TYPE_CHECKING:
    from .configuration_clipseg import (
        CLIPSEG_PRETRAINED_CONFIG_ARCHIVE_MAP,
        CLIPSegConfig,
        CLIPSegTextConfig,
        CLIPSegVisionConfig,
    )
    from .processing_clipseg import CLIPSegProcessor

    try:
        if not is_torch_available():
            raise OptionalDependencyNotAvailable()
    except OptionalDependencyNotAvailable:
        pass
    else:
        from .modeling_clipseg import (
            CLIPSEG_PRETRAINED_MODEL_ARCHIVE_LIST,
            CLIPSegForImageSegmentation,
            CLIPSegModel,
            CLIPSegPreTrainedModel,
            CLIPSegTextModel,
            CLIPSegVisionModel,
        )

else:
    import sys

    lowerCamelCase      =_LazyModule(__name__, globals()["__file__"], _import_structure, module_spec=__spec__)




import doctest
from collections import deque

import numpy as np




class 				_lowerCamelCase :





     """simple docstring"""







     def __init__(							self  )  ->   None:




           """simple docstring"""







           UpperCamelCase__    :   Tuple					=				[2, 1, 2, -1]
           UpperCamelCase__    :   Union[str, Any]					=				[1, 2, 3, 4]






     def    __SCREAMING_SNAKE_CASE			(							self  )  ->   list[float]:




           """simple docstring"""







           UpperCamelCase__    :   List[str]					=				len(self.first_signal  )
           UpperCamelCase__    :   Any					=				len(self.second_signal  )

           UpperCamelCase__    :   Dict					=				max(__SCREAMING_SNAKE_CASE						,						__SCREAMING_SNAKE_CASE  )

           # create a zero matrix of max_length x max_length
           UpperCamelCase__    :   List[Any]					=				[[0] * max_length for i in range(__SCREAMING_SNAKE_CASE  )]

           # fills the smaller signal with zeros to make both signals of same length
           if length_first_signal < length_second_signal:
                 self.first_signal += [0] * (max_length - length_first_signal)
           elif length_first_signal > length_second_signal:
                 self.second_signal += [0] * (max_length - length_second_signal)
           for i in range(__SCREAMING_SNAKE_CASE  ):
                 UpperCamelCase__    :   Optional[int]					=				deque(self.second_signal  )
                 rotated_signal.rotate(__SCREAMING_SNAKE_CASE  )
                 for j, item in enumerate(__SCREAMING_SNAKE_CASE  ):
                       matrix[i][j] += item

        # multiply the matrix with the first signal
           UpperCamelCase__    :   Optional[Any]					=				np.matmul(np.transpose(__SCREAMING_SNAKE_CASE  )						,						np.transpose(self.first_signal  )  )

           # rounding-off to two decimal places
           return [round(__SCREAMING_SNAKE_CASE						,						2  ) for i in final_signal]


if __name__ == "__main__":
    doctest.testmod()


