





'''simple docstring'''


from __future__ import annotations

from sys import maxsize
from typing import Generic, TypeVar

lowerCAmelCase_   :   int       =					TypeVar("T")







def    _lowerCamelCase  (__lowerCamelCase  :     int     )   ->    int:
			return (position - 1) // 2







def    _lowerCamelCase  (__lowerCamelCase  :     int     )   ->    int:
			return (2 * position) + 1







def    _lowerCamelCase  (__lowerCamelCase  :     int     )   ->    int:
			return (2 * position) + 2






class       UpperCamelCase__  (		Generic[T]     ):







	def __init__(				self			:   Union[str, Any]		):




				'''simple docstring'''
				a__     = []
				a__     = {}
				a__     = 0







	def __len__(				self			:   List[str]		):




				'''simple docstring'''
				return self.elements







	def __repr__(				self			:   str		):




				'''simple docstring'''
				return str(self.heap		)







	def 						__a   (				self			:   List[Any]		):




				'''simple docstring'''
				# Check if the priority queue is empty
				return self.elements == 0







	def 						__a   (				self			:   Tuple , lowerCamelCase			:   T , lowerCamelCase			:   int		):




				'''simple docstring'''
				# Add an element with given priority to the queue
				self.heap.append((elem, weight)		)
				a__     = self.elements
				self.elements += 1
				self._bubble_up(lowerCamelCase		)







	def 						__a   (				self			:   Any		):




				'''simple docstring'''
				# Remove and return the element with lowest weight (highest priority)
				if self.elements > 1:
							self._swap_nodes(0 , self.elements - 1		)
				a__   ,				a__     = self.heap.pop()
				del self.position_map[elem]
				self.elements -= 1
				if self.elements > 0:
							a__   ,				a__     = self.heap[0]
							self._bubble_down(lowerCamelCase		)
				return elem







	def 						__a   (				self			:   Dict , lowerCamelCase			:   T , lowerCamelCase			:   int		):




				'''simple docstring'''
				# Update the weight of the given key
				a__     = self.position_map[elem]
				a__     = (elem, weight)
				if position > 0:
							a__     = get_parent_position(lowerCamelCase		)
							a__   ,				a__     = self.heap[parent_position]
							if parent_weight > weight:
										self._bubble_up(lowerCamelCase		)
							else:
										self._bubble_down(lowerCamelCase		)
				else:
							self._bubble_down(lowerCamelCase		)







	def 						__a   (				self			:   Optional[int] , lowerCamelCase			:   T		):




				'''simple docstring'''
				# Place a node at the proper position (upward movement) [to be used internally
				# only]
				a__     = self.position_map[elem]
				if curr_pos == 0:
							return None
				a__     = get_parent_position(lowerCamelCase		)
				a__   ,				a__     = self.heap[curr_pos]
				a__   ,				a__     = self.heap[parent_position]
				if parent_weight > weight:
							self._swap_nodes(lowerCamelCase , lowerCamelCase		)
							return self._bubble_up(lowerCamelCase		)
				return None







	def 						__a   (				self			:   Optional[int] , lowerCamelCase			:   T		):




				'''simple docstring'''
				# Place a node at the proper position (downward movement) [to be used
				# internally only]
				a__     = self.position_map[elem]
				a__   ,				a__     = self.heap[curr_pos]
				a__     = get_child_left_position(lowerCamelCase		)
				a__     = get_child_right_position(lowerCamelCase		)
				if child_left_position < self.elements and child_right_position < self.elements:
							a__   ,				a__     = self.heap[child_left_position]
							a__   ,				a__     = self.heap[child_right_position]
							if child_right_weight < child_left_weight and child_right_weight < weight:
										self._swap_nodes(lowerCamelCase , lowerCamelCase		)
										return self._bubble_down(lowerCamelCase		)
				if child_left_position < self.elements:
							a__   ,				a__     = self.heap[child_left_position]
							if child_left_weight < weight:
										self._swap_nodes(lowerCamelCase , lowerCamelCase		)
										return self._bubble_down(lowerCamelCase		)
				else:
							return None
				if child_right_position < self.elements:
							a__   ,				a__     = self.heap[child_right_position]
							if child_right_weight < weight:
										self._swap_nodes(lowerCamelCase , lowerCamelCase		)
										return self._bubble_down(lowerCamelCase		)
				return None







	def 						__a   (				self			:   Tuple , lowerCamelCase			:   int , lowerCamelCase			:   int		):




				'''simple docstring'''
				# Swap the nodes at the given positions
				a__     = self.heap[nodea_pos][0]
				a__     = self.heap[nodea_pos][0]
				a__   ,				a__     = (
				    self.heap[nodea_pos],
				    self.heap[nodea_pos],
				)
				a__     = nodea_pos
				a__     = nodea_pos






class       UpperCamelCase__  (		Generic[T]     ):







	def __init__(				self			:   Optional[Any]		):




				'''simple docstring'''
				a__     = {}
				a__     = 0







	def __repr__(				self			:   int		):




				'''simple docstring'''
				return str(self.connections		)







	def __len__(				self			:   str		):




				'''simple docstring'''
				return self.nodes







	def 						__a   (				self			:   Optional[Any] , lowerCamelCase			:   T		):




				'''simple docstring'''
				# Add a node in the graph if it is not in the graph
				if node not in self.connections:
							a__     = {}
							self.nodes += 1







	def 						__a   (				self			:   List[str] , lowerCamelCase			:   T , lowerCamelCase			:   T , lowerCamelCase			:   int		):




				'''simple docstring'''
				# Add an edge between 2 nodes in the graph
				self.add_node(lowerCamelCase		)
				self.add_node(lowerCamelCase		)
				a__     = weight
				a__     = weight







def    _lowerCamelCase  (__lowerCamelCase  :     GraphUndirectedWeighted[T]					,  )   ->    tuple[dict[T, int], dict[T, T | None]]:
			a__     = {node: maxsize for node in graph.connections}
			a__     = {node: None for node in graph.connections}

			a__     = MinPriorityQueue()
			for node, weight in dist.items():
						priority_queue.push(__lowerCamelCase					,  __lowerCamelCase     )

			if priority_queue.is_empty():
						return dist, parent

			# initialization
			a__     = priority_queue.extract_min()
			a__     = 0
			for neighbour in graph.connections[node]:
						if dist[neighbour] > dist[node] + graph.connections[node][neighbour]:
									a__     = dist[node] + graph.connections[node][neighbour]
									priority_queue.update_key(__lowerCamelCase					,  dist[neighbour]     )
									a__     = node

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










'''simple docstring'''


import importlib
import os
import sys


# This is required to make the module import works (when the python process is running from the root of the repo)
sys.path.append(".")







def    _lowerCamelCase  (__lowerCamelCase  :     List[str]     )   ->    List[str]:
			a__     = test_file.split(os.path.sep     )
			if components[0:2] != ["tests", "models"]:
						raise ValueError(
						    "`test_file` should start with `tests/models/` (with `/` being the OS specific path separator). Got "
						    f'''{test_file} instead.'''     )
			a__     = components[-1]
			if not test_fn.endswith("py"     ):
						raise ValueError(f'''`test_file` should be a python file. Got {test_fn} instead.'''     )
			if not test_fn.startswith("test_modeling_"     ):
						raise ValueError(
						    f'''`test_file` should point to a file name of the form `test_modeling_*.py`. Got {test_fn} instead.'''     )

			a__     = components[:-1] + [test_fn.replace(".py"					,  ""     )]
			a__     = ".".join(__lowerCamelCase     )

			return test_module_path







def    _lowerCamelCase  (__lowerCamelCase  :     Union[str, Any]     )   ->    Optional[Any]:
			a__     = get_module_path(__lowerCamelCase     )
			a__     = importlib.import_module(__lowerCamelCase     )

			return test_module







def    _lowerCamelCase  (__lowerCamelCase  :     Optional[int]     )   ->    Union[str, Any]:
			a__     = []
			a__     = get_test_module(__lowerCamelCase     )
			for attr in dir(__lowerCamelCase     ):
						if attr.endswith("ModelTester"     ):
									tester_classes.append(getattr(__lowerCamelCase					,  __lowerCamelCase     )     )

    # sort with class names
			return sorted(__lowerCamelCase					,  key=lambda __lowerCamelCase     : x.__name__     )







def    _lowerCamelCase  (__lowerCamelCase  :     Tuple     )   ->    Tuple:
			a__     = []
			a__     = get_test_module(__lowerCamelCase     )
			for attr in dir(__lowerCamelCase     ):
						a__     = getattr(__lowerCamelCase					,  __lowerCamelCase     )
						# (TF/Flax)ModelTesterMixin is also an attribute in specific model test module. Let's exclude them by checking
						# `all_model_classes` is not empty (which also excludes other special classes).
						a__     = getattr(__lowerCamelCase					,  "all_model_classes"					,  []     )
						if len(__lowerCamelCase     ) > 0:
									test_classes.append(__lowerCamelCase     )

    # sort with class names
			return sorted(__lowerCamelCase					,  key=lambda __lowerCamelCase     : x.__name__     )







def    _lowerCamelCase  (__lowerCamelCase  :     List[Any]     )   ->    List[Any]:
			a__     = get_test_classes(__lowerCamelCase     )
			a__     = set()
			for test_class in test_classes:
						model_classes.update(test_class.all_model_classes     )

			# sort with class names
			return sorted(__lowerCamelCase					,  key=lambda __lowerCamelCase     : x.__name__     )







def    _lowerCamelCase  (__lowerCamelCase  :     str     )   ->    Dict:
			a__     = test_class()
			if hasattr(__lowerCamelCase					,  "setUp"     ):
						test.setUp()

			a__     = None
			if hasattr(__lowerCamelCase					,  "model_tester"     ):
						# `(TF/Flax)ModelTesterMixin` has this attribute default to `None`. Let's skip this case.
						if test.model_tester is not None:
									a__     = test.model_tester.__class__

			return model_tester







def    _lowerCamelCase  (__lowerCamelCase  :     Dict					,  __lowerCamelCase  :     Optional[int]     )   ->    List[Any]:
			a__     = get_test_classes(__lowerCamelCase     )

			a__     = []
			for test_class in test_classes:
						if model_class in test_class.all_model_classes:
									target_test_classes.append(__lowerCamelCase     )

    # sort with class names
			return sorted(__lowerCamelCase					,  key=lambda __lowerCamelCase     : x.__name__     )







def    _lowerCamelCase  (__lowerCamelCase  :     Any					,  __lowerCamelCase  :     Tuple     )   ->    Dict:
			a__     = get_test_classes_for_model(__lowerCamelCase					,  __lowerCamelCase     )

			a__     = []
			for test_class in test_classes:
						a__     = get_model_tester_from_test_class(__lowerCamelCase     )
						if tester_class is not None:
									tester_classes.append(__lowerCamelCase     )

    # sort with class names
			return sorted(__lowerCamelCase					,  key=lambda __lowerCamelCase     : x.__name__     )







def    _lowerCamelCase  (__lowerCamelCase  :     List[str]     )   ->    int:
			a__     = get_test_classes(__lowerCamelCase     )
			a__     = {test_class: get_model_tester_from_test_class(__lowerCamelCase     ) for test_class in test_classes}
			return test_tester_mapping







def    _lowerCamelCase  (__lowerCamelCase  :     Any     )   ->    List[Any]:
			a__     = get_model_classes(__lowerCamelCase     )
			a__     = {
			    model_class: get_test_classes_for_model(__lowerCamelCase					,  __lowerCamelCase     ) for model_class in model_classes
			}
			return model_test_mapping







def    _lowerCamelCase  (__lowerCamelCase  :     Tuple     )   ->    Tuple:
			a__     = get_model_classes(__lowerCamelCase     )
			a__     = {
			    model_class: get_tester_classes_for_model(__lowerCamelCase					,  __lowerCamelCase     ) for model_class in model_classes
			}
			return model_to_tester_mapping







def    _lowerCamelCase  (__lowerCamelCase  :     str     )   ->    Dict:
			if isinstance(__lowerCamelCase					,  __lowerCamelCase     ):
						return o
			elif isinstance(__lowerCamelCase					,  __lowerCamelCase     ):
						return o.__name__
			elif isinstance(__lowerCamelCase					,  (list, tuple)     ):
						return [to_json(__lowerCamelCase     ) for x in o]
			elif isinstance(__lowerCamelCase					,  __lowerCamelCase     ):
						return {to_json(__lowerCamelCase     ): to_json(__lowerCamelCase     ) for k, v in o.items()}
			else:
						return o



