




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__					    =    logging.get_logger(__name__)
@add_end_docstrings(snake_case__   )
class     a__					(      snake_case__   ):






						def __init__(     self	,    *_A	,    **_A    ):




											"""simple docstring"""



											super().__init__(*_A	,    **_A    )
											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        __SCREAMING_SNAKE_CASE(     self	,    _A=None    ):




											"""simple docstring"""



											__lowerCAmelCase            = {}
											if top_k is not None:
																__lowerCAmelCase            = top_k
											return {}, {}, postprocess_params






						def __call__(     self	,    _A	,    **_A    ):




											"""simple docstring"""



											return super().__call__(_A	,    **_A    )






						def        __SCREAMING_SNAKE_CASE(     self	,    _A    ):




											"""simple docstring"""



											__lowerCAmelCase            = load_image(_A    )
											__lowerCAmelCase            = self.image_processor(images=_A	,    return_tensors=self.framework    )
											return model_inputs






						def        __SCREAMING_SNAKE_CASE(     self	,    _A    ):




											"""simple docstring"""



											__lowerCAmelCase            = self.model(**_A    )
											return model_outputs






						def        __SCREAMING_SNAKE_CASE(     self	,    _A	,    _A=5    ):




											"""simple docstring"""



											if top_k > self.model.config.num_labels:
																__lowerCAmelCase            = self.model.config.num_labels

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

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










import os


# All paths are set with the intent you should run this script from the root of the repo with the command
# python utils/check_doctest_list.py
UpperCamelCase__					    =    """."""


if __name__ == "__main__":
					UpperCamelCase__					    =    os.path.join(REPO_PATH, """utils/documentation_tests.txt""")
					UpperCamelCase__					    =    []
					UpperCamelCase__					    =    []
					with open(doctest_file_path) as fp:
										for line in fp:
															UpperCamelCase__					    =    line.strip()
															UpperCamelCase__					    =    os.path.join(REPO_PATH, line)
															if not (os.path.isfile(path) or os.path.isdir(path)):
																				non_existent_paths.append(line)
															all_paths.append(path)
					if len(non_existent_paths) > 0:
										UpperCamelCase__					    =    """\n""".join(non_existent_paths)
										raise ValueError(f'''`utils/documentation_tests.txt` contains non-existent paths:\n{non_existent_paths}''')
					if all_paths != sorted(all_paths):
										raise ValueError("""Files in `utils/documentation_tests.txt` are not in alphabetical order.""")




