





import re

import jax.numpy as jnp
from flax.traverse_util import flatten_dict, unflatten_dict
from jax.random import PRNGKey

from ..utils import logging


UpperCamelCase__											= logging.get_logger(__name__)





def     _UpperCamelCase     (a__   :Optional[Any]       ):






							"""simple docstring"""





							UpperCamelCase__				     =			r"""\w+[.]\d+"""
							UpperCamelCase__				     =			re.findall(a__   ,			a__       )
							for pat in pats:
														UpperCamelCase__				     =			key.replace(a__   ,			"""_""".join(pat.split("""."""       )       )       )
							return key





def     _UpperCamelCase     (a__   :List[str]   ,			a__   :int   ,			a__   :Any       ):






							"""simple docstring"""





							UpperCamelCase__				     =			pt_tuple_key[:-1] + ("""scale""",)
							if (
							    any("""norm""" in str_ for str_ in pt_tuple_key       )
							    and (pt_tuple_key[-1] == "bias")
							    and (pt_tuple_key[:-1] + ("bias",) not in random_flax_state_dict)
							    and (pt_tuple_key[:-1] + ("scale",) in random_flax_state_dict)
							):
														UpperCamelCase__				     =			pt_tuple_key[:-1] + ("""scale""",)
														return renamed_pt_tuple_key, pt_tensor
							elif pt_tuple_key[-1] in ["weight", "gamma"] and pt_tuple_key[:-1] + ("scale",) in random_flax_state_dict:
														UpperCamelCase__				     =			pt_tuple_key[:-1] + ("""scale""",)
														return renamed_pt_tuple_key, pt_tensor

							# embedding
							if pt_tuple_key[-1] == "weight" and pt_tuple_key[:-1] + ("embedding",) in random_flax_state_dict:
														UpperCamelCase__				     =			pt_tuple_key[:-1] + ("""embedding""",)
														return renamed_pt_tuple_key, pt_tensor

							# conv layer
							UpperCamelCase__				     =			pt_tuple_key[:-1] + ("""kernel""",)
							if pt_tuple_key[-1] == "weight" and pt_tensor.ndim == 4:
														UpperCamelCase__				     =			pt_tensor.transpose(2   ,			3   ,			1   ,			0       )
														return renamed_pt_tuple_key, pt_tensor

							# linear layer
							UpperCamelCase__				     =			pt_tuple_key[:-1] + ("""kernel""",)
							if pt_tuple_key[-1] == "weight":
														UpperCamelCase__				     =			pt_tensor.T
														return renamed_pt_tuple_key, pt_tensor

							# old PyTorch layer norm weight
							UpperCamelCase__				     =			pt_tuple_key[:-1] + ("""weight""",)
							if pt_tuple_key[-1] == "gamma":
														return renamed_pt_tuple_key, pt_tensor

							# old PyTorch layer norm bias
							UpperCamelCase__				     =			pt_tuple_key[:-1] + ("""bias""",)
							if pt_tuple_key[-1] == "beta":
														return renamed_pt_tuple_key, pt_tensor

							return pt_tuple_key, pt_tensor





def     _UpperCamelCase     (a__   :Any   ,			a__   :Optional[Any]   ,			a__   :Tuple=42       ):






							"""simple docstring"""





							UpperCamelCase__				     =			{k: v.numpy() for k, v in pt_state_dict.items()}

							# Step 2: Since the model is stateless, get random Flax params
							UpperCamelCase__				     =			flax_model.init_weights(PRNGKey(a__       )       )

							UpperCamelCase__				     =			flatten_dict(a__       )
							UpperCamelCase__				     =			{}

							# Need to change some parameters name to match Flax names
							for pt_key, pt_tensor in pt_state_dict.items():
														UpperCamelCase__				     =			rename_key(a__       )
														UpperCamelCase__				     =			tuple(renamed_pt_key.split("""."""       )       )

														# Correctly rename weight parameters
														UpperCamelCase__     ,     UpperCamelCase__				     =			rename_key_and_reshape_tensor(a__   ,			a__   ,			a__       )

														if flax_key in random_flax_state_dict:
																					if flax_tensor.shape != random_flax_state_dict[flax_key].shape:
																												raise ValueError(
																												    f"""PyTorch checkpoint seems to be incorrect. Weight {pt_key} was expected to be of shape """
																												    f"""{random_flax_state_dict[flax_key].shape}, but is {flax_tensor.shape}."""       )

        # also add unexpected weight so that warning is thrown
														UpperCamelCase__				     =			jnp.asarray(a__       )

							return unflatten_dict(a__       )











from __future__ import annotations

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

@dataclass
class        __SCREAMING_SNAKE_CASE					:
							snake_case     :      int
							snake_case     :      Node | None						     =       None
							snake_case     :      Node | None						     =       None






def     _UpperCamelCase     ():






							"""simple docstring"""





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





def     _UpperCamelCase     (a__   :Node | None       ):






							"""simple docstring"""





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





def     _UpperCamelCase     (a__   :Node | None       ):






							"""simple docstring"""





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





def     _UpperCamelCase     (a__   :Node | None       ):






							"""simple docstring"""





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





def     _UpperCamelCase     (a__   :Node | None       ):






							"""simple docstring"""





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





def     _UpperCamelCase     (a__   :Node | None       ):






							"""simple docstring"""





							UpperCamelCase__				     =			[]

							if root is None:
														return output

							UpperCamelCase__				     =			deque([root]       )

							while process_queue:
														UpperCamelCase__				     =			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     (a__   :Node | None   ,			a__   :int       ):






							"""simple docstring"""





							UpperCamelCase__				     =			[]

							def populate_output(a__   :Node | None   ,			a__   :int       ) -> 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(a__   ,			a__       )
							return output





def     _UpperCamelCase     (a__   :Node | None   ,			a__   :int       ):






							"""simple docstring"""





							UpperCamelCase__				     =			[]

							def populate_output(a__   :Node | None   ,			a__   :int       ) -> 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(a__   ,			a__       )
							return output





def     _UpperCamelCase     (a__   :Node | None       ):






							"""simple docstring"""





							if root is None:
														return []

							UpperCamelCase__				     =			[]

							UpperCamelCase__				     =			0
							UpperCamelCase__				     =			height(a__       )

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

							return output





def     _UpperCamelCase     ():  # Main function for testing.






							"""simple docstring"""





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

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

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

							print("""Level-wise order Traversal: """       )

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

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


if __name__ == "__main__":
					import doctest

					doctest.testmod()
					main()




