

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

_UpperCAmelCase		:   Any										=       logging.get_logger(__name__)







@add_end_docstrings(SCREAMING_SNAKE_CASE_			)
class  lowercase				(       SCREAMING_SNAKE_CASE_			):




				def __init__(					self      ,   *snake_case      ,   **snake_case       ):
											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     a							(					self      ,   snake_case=None       ):
											snake_case_							=    {}
											if top_k is not None:
																		snake_case_							=    top_k
											return {}, {}, postprocess_params




				def __call__(					self      ,   snake_case      ,   **snake_case       ):
											return super().__call__(__UpperCAmelCase      ,   **__UpperCAmelCase       )




				def     a							(					self      ,   snake_case       ):
											snake_case_							=    load_image(__UpperCAmelCase       )
											snake_case_							=    self.image_processor(images=__UpperCAmelCase      ,   return_tensors=self.framework       )
											return model_inputs




				def     a							(					self      ,   snake_case       ):
											snake_case_							=    self.model(**__UpperCAmelCase       )
											return model_outputs




				def     a							(					self      ,   snake_case      ,   snake_case=5       ):
											if top_k > self.model.config.num_labels:
																		snake_case_							=    self.model.config.num_labels

											if self.framework == "pt":
																		snake_case_							=    model_outputs.logits.softmax(-1       )[0]
																		snake_case_							=    probs.topk(__UpperCAmelCase       )
											elif self.framework == "tf":
																		snake_case_							=    stable_softmax(model_outputs.logits      ,   axis=-1       )[0]
																		snake_case_							=    tf.math.top_k(__UpperCAmelCase      ,   k=__UpperCAmelCase       )
																		snake_case_							=    topk.values.numpy(), topk.indices.numpy()
											else:
																		raise ValueError(F'''Unsupported framework: {self.framework}'''       )

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









'''simple docstring'''





def    _SCREAMING_SNAKE_CASE  (       UpperCamelCase = "The quick brown fox jumps over the lazy dog"							,    ):



    """simple docstring"""





    lowerCAmelCase__ :  str							      =					set()

    # Replace all the whitespace in our sentence
    lowerCAmelCase__ :  Tuple							      =					input_str.replace(""" """							,    """"""			)
    for alpha in input_str:
        if "a" <= alpha.lower() <= "z":
            frequency.add(alpha.lower()			)
    return len(UpperCamelCase			) == 26
def    _SCREAMING_SNAKE_CASE  (       UpperCamelCase = "The quick brown fox jumps over the lazy dog"							,    ):



    """simple docstring"""





    lowerCAmelCase__ :  Any							      =					[False] * 26
    for char in input_str:
        if char.islower():
            lowerCAmelCase__ :  Optional[Any]							      =					True
        elif char.isupper():
            lowerCAmelCase__ :  Any							      =					True
    return all(UpperCamelCase			)
def    _SCREAMING_SNAKE_CASE  (       UpperCamelCase = "The quick brown fox jumps over the lazy dog"							,    ):



    """simple docstring"""





    return len({char for char in input_str.lower() if char.isalpha()}			) == 26
def    _SCREAMING_SNAKE_CASE  (       ):



    """simple docstring"""





    from timeit import timeit

    lowerCAmelCase__ :  Union[str, Any]							      =					"""from __main__ import is_pangram, is_pangram_faster, is_pangram_fastest"""
    print(timeit("""is_pangram()"""							,    setup=UpperCamelCase			)			)
    print(timeit("""is_pangram_faster()"""							,    setup=UpperCamelCase			)			)
    print(timeit("""is_pangram_fastest()"""							,    setup=UpperCamelCase			)			)
    # 5.348480500048026, 2.6477354579837993, 1.8470395830227062
    # 5.036091582966037, 2.644472333951853,  1.8869528750656173


if __name__ == "__main__":
 import doctest

 doctest.testmod()
 benchmark()


