

'''simple docstring'''



from typing import List, Union

from ..utils import (
    add_end_docstrings,
    is_tf_available,
    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_utils import load_image

if is_tf_available():
		import tensorflow as tf

		from ..models.auto.modeling_tf_auto import TF_MODEL_FOR_IMAGE_CLASSIFICATION_MAPPING
		from ..tf_utils import stable_softmax

if is_torch_available():
		from ..models.auto.modeling_auto import MODEL_FOR_IMAGE_CLASSIFICATION_MAPPING

__snake_case			:     Optional[Any]										=      logging.get_logger(__name__)



@add_end_docstrings(snake_case__						)
class lowerCamelCase			(  snake_case__						):



			'''simple docstring'''






			def __init__(				self	:						Union[str, Any]		,      *lowerCAmelCase_	:						Dict		,      **lowerCAmelCase_	:						Optional[int]			)      ->		int:





									'''simple docstring'''
									super().__init__(*UpperCAmelCase_		,      **UpperCAmelCase_			)
									requires_backends(self		,      """vision"""			)
									self.check_model_type(
									    TF_MODEL_FOR_IMAGE_CLASSIFICATION_MAPPING
									    if self.framework == """tf"""
									    else MODEL_FOR_IMAGE_CLASSIFICATION_MAPPING			)


			def lowercase__						(				self	:						Dict		,      lowerCAmelCase_	:						List[Any]=None			)      ->		Any:





									'''simple docstring'''
									A__					:       Dict     ={}
									if top_k is not None:
															A__					:       Optional[Any]     =top_k
									return {}, {}, postprocess_params


			def __call__(				self	:						Optional[int]		,      lowerCAmelCase_	:						Union[str, List[str], "Image.Image", List["Image.Image"]]		,      **lowerCAmelCase_	:						int			)      ->		Optional[int]:





									'''simple docstring'''
									return super().__call__(UpperCAmelCase_		,      **UpperCAmelCase_			)


			def lowercase__						(				self	:						Optional[Any]		,      lowerCAmelCase_	:						Tuple			)      ->		Dict:





									'''simple docstring'''
									A__					:       Optional[Any]     =load_image(UpperCAmelCase_			)
									A__					:       List[Any]     =self.image_processor(images=UpperCAmelCase_		,      return_tensors=self.framework			)
									return model_inputs


			def lowercase__						(				self	:						Union[str, Any]		,      lowerCAmelCase_	:						str			)      ->		Union[str, Any]:





									'''simple docstring'''
									A__					:       List[Any]     =self.model(**UpperCAmelCase_			)
									return model_outputs



			def lowercase__						(				self	:						Union[str, Any]		,      lowerCAmelCase_	:						Tuple		,      lowerCAmelCase_	:						List[Any]=5			)      ->		int:





									'''simple docstring'''
									if top_k > self.model.config.num_labels:
															A__					:       Dict     =self.model.config.num_labels

									if self.framework == "pt":
															A__					:       List[Any]     =model_outputs.logits.softmax(-1			)[0]
															A__					:       Any     =probs.topk(UpperCAmelCase_			)
									elif self.framework == "tf":
															A__					:       Union[str, Any]     =stable_softmax(model_outputs.logits		,      axis=-1			)[0]
															A__					:       Optional[int]     =tf.math.top_k(UpperCAmelCase_		,      k=UpperCAmelCase_			)
															A__					:       Union[str, Any]     =topk.values.numpy(), topk.indices.numpy()
									else:
															raise ValueError(f"Unsupported framework: {self.framework}"			)

									A__					:       Dict     =scores.tolist()
									A__					:       Tuple     =ids.tolist()
									return [{"score": score, "label": self.model.config.idalabel[_id]} for score, _id in zip(UpperCAmelCase_		,      UpperCAmelCase_			)]


'''simple docstring'''



from maths.is_square_free import is_square_free
from maths.prime_factors import prime_factors
def 						__lowerCamelCase	(       __snake_case					:		int	)	->							int:






						"""simple docstring"""





						A__					:       List[Any]     =prime_factors(__snake_case	)
						if is_square_free(__snake_case	):
												return -1 if len(__snake_case	) % 2 else 1
						return 0


if __name__ == "__main__":
		import doctest

		doctest.testmod()

