from __future__ import annotations

from sys import maxsize
from typing import Generic, TypeVar

__lowercase							 =					TypeVar('''T''')



def lowerCamelCase  (   SCREAMING_SNAKE_CASE	):
    '''simple docstring'''







    return (position - 1) // 2



def lowerCamelCase  (   SCREAMING_SNAKE_CASE	):
    '''simple docstring'''







    return (2 * position) + 1



def lowerCamelCase  (   SCREAMING_SNAKE_CASE	):
    '''simple docstring'''







    return (2 * position) + 2


class 	lowerCamelCase_     (   Generic[T] ):






    '''simple docstring'''






    def __init__(	self)       ->	None:
        __UpperCamelCase     :list[tuple[T, int]]			  =		[]
        __UpperCamelCase     :dict[T, int]			  =		{}
        __UpperCamelCase     :int			  =		0







    def __len__(	self)       ->	int:
        return self.elements







    def __repr__(	self)       ->	str:
        return str(self.heap)







    def 			UpperCamelCase__   (	self)       ->	bool:
        # Check if the priority queue is empty
        return self.elements == 0







    def 			UpperCamelCase__   (	self , __lowercase , __lowercase)       ->	None:
        # Add an element with given priority to the queue
        self.heap.append((elem, weight))
        __UpperCamelCase     :Optional[Any]			  =		self.elements
        self.elements += 1
        self._bubble_up(__lowercase)







    def 			UpperCamelCase__   (	self)       ->	T:
        # Remove and return the element with lowest weight (highest priority)
        if self.elements > 1:
            self._swap_nodes(0 , self.elements - 1)
        __UpperCamelCase  ,       __UpperCamelCase     :Dict			  =		self.heap.pop()
        del self.position_map[elem]
        self.elements -= 1
        if self.elements > 0:
            __UpperCamelCase  ,       __UpperCamelCase     :Optional[int]			  =		self.heap[0]
            self._bubble_down(__lowercase)
        return elem







    def 			UpperCamelCase__   (	self , __lowercase , __lowercase)       ->	None:
        # Update the weight of the given key
        __UpperCamelCase     :List[str]			  =		self.position_map[elem]
        __UpperCamelCase     :List[str]			  =		(elem, weight)
        if position > 0:
            __UpperCamelCase     :str			  =		get_parent_position(__lowercase)
            __UpperCamelCase  ,       __UpperCamelCase     :Tuple			  =		self.heap[parent_position]
            if parent_weight > weight:
                self._bubble_up(__lowercase)
            else:
                self._bubble_down(__lowercase)
        else:
            self._bubble_down(__lowercase)







    def 			UpperCamelCase__   (	self , __lowercase)       ->	None:
        # Place a node at the proper position (upward movement) [to be used internally
        # only]
        __UpperCamelCase     :Any			  =		self.position_map[elem]
        if curr_pos == 0:
            return None
        __UpperCamelCase     :List[str]			  =		get_parent_position(__lowercase)
        __UpperCamelCase  ,       __UpperCamelCase     :List[Any]			  =		self.heap[curr_pos]
        __UpperCamelCase  ,       __UpperCamelCase     :int			  =		self.heap[parent_position]
        if parent_weight > weight:
            self._swap_nodes(__lowercase , __lowercase)
            return self._bubble_up(__lowercase)
        return None







    def 			UpperCamelCase__   (	self , __lowercase)       ->	None:
        # Place a node at the proper position (downward movement) [to be used
        # internally only]
        __UpperCamelCase     :int			  =		self.position_map[elem]
        __UpperCamelCase  ,       __UpperCamelCase     :List[Any]			  =		self.heap[curr_pos]
        __UpperCamelCase     :int			  =		get_child_left_position(__lowercase)
        __UpperCamelCase     :Optional[Any]			  =		get_child_right_position(__lowercase)
        if child_left_position < self.elements and child_right_position < self.elements:
            __UpperCamelCase  ,       __UpperCamelCase     :Optional[Any]			  =		self.heap[child_left_position]
            __UpperCamelCase  ,       __UpperCamelCase     :Optional[int]			  =		self.heap[child_right_position]
            if child_right_weight < child_left_weight and child_right_weight < weight:
                self._swap_nodes(__lowercase , __lowercase)
                return self._bubble_down(__lowercase)
        if child_left_position < self.elements:
            __UpperCamelCase  ,       __UpperCamelCase     :int			  =		self.heap[child_left_position]
            if child_left_weight < weight:
                self._swap_nodes(__lowercase , __lowercase)
                return self._bubble_down(__lowercase)
        else:
            return None
        if child_right_position < self.elements:
            __UpperCamelCase  ,       __UpperCamelCase     :Optional[Any]			  =		self.heap[child_right_position]
            if child_right_weight < weight:
                self._swap_nodes(__lowercase , __lowercase)
                return self._bubble_down(__lowercase)
        return None







    def 			UpperCamelCase__   (	self , __lowercase , __lowercase)       ->	None:
        # Swap the nodes at the given positions
        __UpperCamelCase     :Union[str, Any]			  =		self.heap[nodea_pos][0]
        __UpperCamelCase     :Dict			  =		self.heap[nodea_pos][0]
        __UpperCamelCase  ,       __UpperCamelCase     :int			  =		(
            self.heap[nodea_pos],
            self.heap[nodea_pos],
        )
        __UpperCamelCase     :Any			  =		nodea_pos
        __UpperCamelCase     :Tuple			  =		nodea_pos


class 	lowerCamelCase_     (   Generic[T] ):






    '''simple docstring'''






    def __init__(	self)       ->	None:
        __UpperCamelCase     :dict[T, dict[T, int]]			  =		{}
        __UpperCamelCase     :int			  =		0







    def __repr__(	self)       ->	str:
        return str(self.connections)







    def __len__(	self)       ->	int:
        return self.nodes







    def 			UpperCamelCase__   (	self , __lowercase)       ->	None:
        # Add a node in the graph if it is not in the graph
        if node not in self.connections:
            __UpperCamelCase     :List[str]			  =		{}
            self.nodes += 1







    def 			UpperCamelCase__   (	self , __lowercase , __lowercase , __lowercase)       ->	None:
        # Add an edge between 2 nodes in the graph
        self.add_node(__lowercase)
        self.add_node(__lowercase)
        __UpperCamelCase     :Dict			  =		weight
        __UpperCamelCase     :Union[str, Any]			  =		weight



def lowerCamelCase  (   SCREAMING_SNAKE_CASE  ,			):
    '''simple docstring'''







    __UpperCamelCase     :dict[T, int]			  =		{node: maxsize for node in graph.connections}
    __UpperCamelCase     :dict[T, T | None]			  =		{node: None for node in graph.connections}

    __UpperCamelCase     :MinPriorityQueue[T]			  =		MinPriorityQueue()
    for node, weight in dist.items():
        priority_queue.push(SCREAMING_SNAKE_CASE  ,			SCREAMING_SNAKE_CASE	)

    if priority_queue.is_empty():
        return dist, parent

    # initialization
    __UpperCamelCase     :Optional[int]			  =		priority_queue.extract_min()
    __UpperCamelCase     :Any			  =		0
    for neighbour in graph.connections[node]:
        if dist[neighbour] > dist[node] + graph.connections[node][neighbour]:
            __UpperCamelCase     :Optional[Any]			  =		dist[node] + graph.connections[node][neighbour]
            priority_queue.update_key(SCREAMING_SNAKE_CASE  ,			dist[neighbour]	)
            __UpperCamelCase     :Any			  =		node

    # running prim's algorithm
    while not priority_queue.is_empty():
        __UpperCamelCase     :str			  =		priority_queue.extract_min()
        for neighbour in graph.connections[node]:
            if dist[neighbour] > dist[node] + graph.connections[node][neighbour]:
                __UpperCamelCase     :List[str]			  =		dist[node] + graph.connections[node][neighbour]
                priority_queue.update_key(SCREAMING_SNAKE_CASE  ,			dist[neighbour]	)
                __UpperCamelCase     :Union[str, Any]			  =		node
    return dist, parent






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


__lowercase							 =					logging.get_logger(__name__)



def lowerCamelCase  (   SCREAMING_SNAKE_CASE	):
    '''simple docstring'''







    __UpperCamelCase     :Tuple			  =		R'''\w+[.]\d+'''
    __UpperCamelCase     :List[str]			  =		re.findall(SCREAMING_SNAKE_CASE  ,			SCREAMING_SNAKE_CASE	)
    for pat in pats:
        __UpperCamelCase     :int			  =		key.replace(SCREAMING_SNAKE_CASE  ,			'''_'''.join(pat.split('''.'''	)	)	)
    return key



def lowerCamelCase  (   SCREAMING_SNAKE_CASE  ,			SCREAMING_SNAKE_CASE  ,			SCREAMING_SNAKE_CASE	):
    '''simple docstring'''







    __UpperCamelCase     :Tuple			  =		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     :str			  =		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     :Any			  =		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     :str			  =		pt_tuple_key[:-1] + ('''embedding''',)
        return renamed_pt_tuple_key, pt_tensor

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

    # linear layer
    __UpperCamelCase     :List[str]			  =		pt_tuple_key[:-1] + ('''kernel''',)
    if pt_tuple_key[-1] == "weight":
        __UpperCamelCase     :Any			  =		pt_tensor.T
        return renamed_pt_tuple_key, pt_tensor

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

    # old PyTorch layer norm bias
    __UpperCamelCase     :int			  =		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 lowerCamelCase  (   SCREAMING_SNAKE_CASE  ,			SCREAMING_SNAKE_CASE  ,			SCREAMING_SNAKE_CASE=42	):
    '''simple docstring'''







    __UpperCamelCase     :Union[str, Any]			  =		{k: v.numpy() for k, v in pt_state_dict.items()}

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

    __UpperCamelCase     :int			  =		flatten_dict(SCREAMING_SNAKE_CASE	)
    __UpperCamelCase     :List[Any]			  =		{}

    # Need to change some parameters name to match Flax names
    for pt_key, pt_tensor in pt_state_dict.items():
        __UpperCamelCase     :List[Any]			  =		rename_key(SCREAMING_SNAKE_CASE	)
        __UpperCamelCase     :List[Any]			  =		tuple(renamed_pt_key.split('''.'''	)	)

        # Correctly rename weight parameters
        __UpperCamelCase  ,       __UpperCamelCase     :Any			  =		rename_key_and_reshape_tensor(SCREAMING_SNAKE_CASE  ,			SCREAMING_SNAKE_CASE  ,			SCREAMING_SNAKE_CASE	)

        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     :str			  =		jnp.asarray(SCREAMING_SNAKE_CASE	)

    return unflatten_dict(SCREAMING_SNAKE_CASE	)





