





from collections import UserDict
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_torch_available():
			from ..models.auto.modeling_auto import MODEL_FOR_ZERO_SHOT_IMAGE_CLASSIFICATION_MAPPING

if is_tf_available():
			from ..models.auto.modeling_tf_auto import TF_MODEL_FOR_ZERO_SHOT_IMAGE_CLASSIFICATION_MAPPING
			from ..tf_utils import stable_softmax

__lowerCamelCase : int											=			logging.get_logger(__name__)

@add_end_docstrings(_lowercase  )
class       UpperCAmelCase (						_lowercase  ):




		def __init__(self      :	List[Any]							,			**A__      :	int				)					-> List[Any]:
						super().__init__(**A__				)

						requires_backends(self							,			"vision"				)
						self.check_model_type(
						    TF_MODEL_FOR_ZERO_SHOT_IMAGE_CLASSIFICATION_MAPPING
						    if self.framework == "tf"
						    else MODEL_FOR_ZERO_SHOT_IMAGE_CLASSIFICATION_MAPPING				)




		def __call__(self      :	Dict							,			A__      :	Tuple							,			**A__      :	Tuple				)					-> Tuple:
						return super().__call__(A__							,			**A__				)




		def 				UpperCAmelCase__   (self      :	Union[str, Any]							,			**A__      :	List[str]				)					-> str:
						lowercase         = {}
						if "candidate_labels" in kwargs:
										lowercase         = kwargs["candidate_labels"]
						if "hypothesis_template" in kwargs:
										lowercase         = kwargs["hypothesis_template"]

						return preprocess_params, {}, {}




		def 				UpperCAmelCase__   (self      :	List[str]							,			A__      :	Any							,			A__      :	Optional[int]=None							,			A__      :	List[Any]="This is a photo of {}."				)					-> int:
						lowercase         = load_image(A__				)
						lowercase         = self.image_processor(images=[image]							,			return_tensors=self.framework				)
						lowercase         = candidate_labels
						lowercase         = [hypothesis_template.format(A__				) for x in candidate_labels]
						lowercase         = self.tokenizer(A__							,			return_tensors=self.framework							,			padding=A__				)
						lowercase         = [text_inputs]
						return inputs




		def 				UpperCAmelCase__   (self      :	List[Any]							,			A__      :	Optional[Any]				)					-> Optional[int]:
						lowercase         = model_inputs.pop("candidate_labels"				)
						lowercase         = model_inputs.pop("text_inputs"				)
						if isinstance(text_inputs[0]							,			A__				):
										lowercase         = text_inputs[0]
						else:
										# Batching case.
										lowercase         = text_inputs[0][0]

						lowercase         = self.model(**A__							,			**A__				)

						lowercase         = {
						    "candidate_labels": candidate_labels,
						    "logits": outputs.logits_per_image,
						}
						return model_outputs





		def 				UpperCAmelCase__   (self      :	Any							,			A__      :	List[str]				)					-> Optional[int]:
						lowercase         = model_outputs.pop("candidate_labels"				)
						lowercase         = model_outputs["logits"][0]
						if self.framework == "pt":
										lowercase         = logits.softmax(dim=-1				).squeeze(-1				)
										lowercase         = probs.tolist()
										if not isinstance(A__							,			A__				):
														lowercase         = [scores]
						elif self.framework == "tf":
										lowercase         = stable_softmax(A__							,			axis=-1				)
										lowercase         = probs.numpy().tolist()
						else:
										raise ValueError(f'Unsupported framework: {self.framework}'				)

						lowercase         = [
						    {"score": score, "label": candidate_label}
						    for score, candidate_label in sorted(zip(A__							,			A__				)							,			key=lambda A__				: -x[0]				)
						]
						return result











'''simple docstring'''

from __future__ import annotations

from collections import deque
from collections.abc import Sequence
from dataclasses import dataclass
from typing import Any

@dataclass
class       UpperCAmelCase :
		UpperCAmelCase					:	int
		UpperCAmelCase					:	Node | None 			=		None
		UpperCAmelCase					:	Node | None 			=		None







def 							UpperCAmelCase_    (	):

				"""simple docstring"""






				lowercase         = Node(1							)
				lowercase         = Node(2							)
				lowercase         = Node(3							)
				lowercase         = Node(4							)
				lowercase         = Node(5							)
				return tree







def 							UpperCAmelCase_    (	lowerCAmelCase_							):

				"""simple docstring"""






				return [root.data, *preorder(root.left							), *preorder(root.right							)] if root else []







def 							UpperCAmelCase_    (	lowerCAmelCase_							):

				"""simple docstring"""






				return postorder(root.left							) + postorder(root.right							) + [root.data] if root else []







def 							UpperCAmelCase_    (	lowerCAmelCase_							):

				"""simple docstring"""






				return [*inorder(root.left							), root.data, *inorder(root.right							)] if root else []







def 							UpperCAmelCase_    (	lowerCAmelCase_							):

				"""simple docstring"""






				return (max(height(root.left							)		,							height(root.right							)							) + 1) if root else 0







def 							UpperCAmelCase_    (	lowerCAmelCase_							):

				"""simple docstring"""






				lowercase         = []

				if root is None:
								return output

				lowercase         = deque([root]							)

				while process_queue:
								lowercase         = process_queue.popleft()
								output.append(node.data							)

								if node.left:
												process_queue.append(node.left							)
								if node.right:
												process_queue.append(node.right							)
				return output







def 							UpperCAmelCase_    (	lowerCAmelCase_		,							lowerCAmelCase_							):

				"""simple docstring"""






				lowercase         = []

				def populate_output(lowerCAmelCase_		,							lowerCAmelCase_							) -> None:
								if not root:
												return
								if level == 1:
												output.append(root.data							)
								elif level > 1:
												populate_output(root.left		,							level - 1							)
												populate_output(root.right		,							level - 1							)

				populate_output(lowerCAmelCase_		,							lowerCAmelCase_							)
				return output







def 							UpperCAmelCase_    (	lowerCAmelCase_		,							lowerCAmelCase_							):

				"""simple docstring"""






				lowercase         = []

				def populate_output(lowerCAmelCase_		,							lowerCAmelCase_							) -> None:
								if root is None:
												return
								if level == 1:
												output.append(root.data							)
								elif level > 1:
												populate_output(root.right		,							level - 1							)
												populate_output(root.left		,							level - 1							)

				populate_output(lowerCAmelCase_		,							lowerCAmelCase_							)
				return output







def 							UpperCAmelCase_    (	lowerCAmelCase_							):

				"""simple docstring"""






				if root is None:
								return []

				lowercase         = []

				lowercase         = 0
				lowercase         = height(lowerCAmelCase_							)

				for h in range(1		,							height_tree + 1							):
								if not flag:
												output.append(get_nodes_from_left_to_right(lowerCAmelCase_		,							lowerCAmelCase_							)							)
												lowercase         = 1
								else:
												output.append(get_nodes_from_right_to_left(lowerCAmelCase_		,							lowerCAmelCase_							)							)
												lowercase         = 0

				return output







def 							UpperCAmelCase_    (	):  # Main function for testing.

				"""simple docstring"""






				lowercase         = make_tree()
				print(f'In-order Traversal: {inorder(lowerCAmelCase_							)}'							)
				print(f'Pre-order Traversal: {preorder(lowerCAmelCase_							)}'							)
				print(f'Post-order Traversal: {postorder(lowerCAmelCase_							)}'		,							"\n"							)

				print(f'Height of Tree: {height(lowerCAmelCase_							)}'		,							"\n"							)

				print("Complete Level Order Traversal: "							)
				print(level_order(lowerCAmelCase_							)		,							"\n"							)

				print("Level-wise order Traversal: "							)

				for level in range(1		,							height(lowerCAmelCase_							) + 1							):
								print(f'Level {level}:'		,							get_nodes_from_left_to_right(lowerCAmelCase_		,							level=lowerCAmelCase_							)							)

				print("\nZigZag order Traversal: "							)
				print(zigzag(lowerCAmelCase_							)							)


if __name__ == "__main__":
			import doctest

			doctest.testmod()
			main()




