





'''simple docstring'''







# Copyright 2023 The HuggingFace Team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
#     http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
from typing import TYPE_CHECKING

from ...utils import (
    OptionalDependencyNotAvailable,
    _LazyModule,
    is_torch_available,
    is_vision_available,
)


_a      :				int											=					{
    """configuration_tvlt""": ["""TVLT_PRETRAINED_CONFIG_ARCHIVE_MAP""", """TvltConfig"""],
    """feature_extraction_tvlt""": ["""TvltFeatureExtractor"""],
    """processing_tvlt""": ["""TvltProcessor"""],
}

try:
	if not is_torch_available():
		raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
	pass
else:
	_a      :				Union[str, Any]											=					[
	    """TVLT_PRETRAINED_MODEL_ARCHIVE_LIST""",
	    """TvltModel""",
	    """TvltForPreTraining""",
	    """TvltForAudioVisualClassification""",
	    """TvltPreTrainedModel""",
	]

try:
	if not is_vision_available():
		raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
	pass
else:
	_a      :				str											=					["""TvltImageProcessor"""]


if TYPE_CHECKING:
	from .configuration_tvlt import TVLT_PRETRAINED_CONFIG_ARCHIVE_MAP, TvltConfig
	from .processing_tvlt import TvltProcessor
	from .feature_extraction_tvlt import TvltFeatureExtractor

	try:
		if not is_torch_available():
			raise OptionalDependencyNotAvailable()
	except OptionalDependencyNotAvailable:
		pass
	else:
		from .modeling_tvlt import (
		    TVLT_PRETRAINED_MODEL_ARCHIVE_LIST,
		    TvltForAudioVisualClassification,
		    TvltForPreTraining,
		    TvltModel,
		    TvltPreTrainedModel,
		)

	try:
		if not is_vision_available():
			raise OptionalDependencyNotAvailable()
	except OptionalDependencyNotAvailable:
		pass
	else:
		from .image_processing_tvlt import TvltImageProcessor


else:
	import sys

	_a      :				Tuple											=					_LazyModule(__name__, globals()["""__file__"""], _import_structure, module_spec=__spec__)








'''simple docstring'''







import math
import sys





class 					_UpperCAmelCase							:
		def __init__(						self    ):



					'''simple docstring'''

					__lowerCAmelCase      		=       0
					__lowerCAmelCase      		=       []
					__lowerCAmelCase      		=       {}  # To store the pos of node in array
		def 						lowerCamelCase__    (						self    ):



					'''simple docstring'''

					return self.cur_size == 0
		def 						lowerCamelCase__    (						self,__SCREAMING_SNAKE_CASE    ):



					'''simple docstring'''

					__lowerCAmelCase      		=       self.left(__SCREAMING_SNAKE_CASE    )
					__lowerCAmelCase      		=       self.right(__SCREAMING_SNAKE_CASE    )
					if lc < self.cur_size and self.array(__SCREAMING_SNAKE_CASE    )[0] < self.array(__SCREAMING_SNAKE_CASE    )[0]:
								__lowerCAmelCase      		=       lc
					else:
								__lowerCAmelCase      		=       idx
					if rc < self.cur_size and self.array(__SCREAMING_SNAKE_CASE    )[0] < self.array(__SCREAMING_SNAKE_CASE    )[0]:
								__lowerCAmelCase      		=       rc
					if smallest != idx:
								self.swap(__SCREAMING_SNAKE_CASE,__SCREAMING_SNAKE_CASE    )
								self.min_heapify(__SCREAMING_SNAKE_CASE    )
		def 						lowerCamelCase__    (						self,__SCREAMING_SNAKE_CASE    ):



					'''simple docstring'''

					__lowerCAmelCase      		=       self.cur_size
					self.cur_size += 1
					self.array.append((sys.maxsize, tup[1])    )
					self.decrease_key((sys.maxsize, tup[1]),tup[0]    )
		def 						lowerCamelCase__    (						self    ):



					'''simple docstring'''

					__lowerCAmelCase      		=       self.array[0][1]
					__lowerCAmelCase      		=       self.array[self.cur_size - 1]
					self.cur_size -= 1
					self.min_heapify(1    )
					del self.pos[min_node]
					return min_node
		def 						lowerCamelCase__    (						self,__SCREAMING_SNAKE_CASE    ):



					'''simple docstring'''

					return 2 * i + 1
		def 						lowerCamelCase__    (						self,__SCREAMING_SNAKE_CASE    ):



					'''simple docstring'''

					return 2 * i + 2
		def 						lowerCamelCase__    (						self,__SCREAMING_SNAKE_CASE    ):



					'''simple docstring'''

					return math.floor(i / 2    )
		def 						lowerCamelCase__    (						self,__SCREAMING_SNAKE_CASE,__SCREAMING_SNAKE_CASE    ):



					'''simple docstring'''

					__lowerCAmelCase      		=       j
					__lowerCAmelCase      		=       i
					__lowerCAmelCase      		=       self.array[i]
					__lowerCAmelCase      		=       self.array[j]
					__lowerCAmelCase      		=       temp







		def 						lowerCamelCase__    (						self,__SCREAMING_SNAKE_CASE,__SCREAMING_SNAKE_CASE    ):



					'''simple docstring'''

					__lowerCAmelCase      		=       self.pos[tup[1]]
					# assuming the new_d is atmost old_d
					__lowerCAmelCase      		=       (new_d, tup[1])
					while idx > 0 and self.array[self.par(__SCREAMING_SNAKE_CASE    )][0] > self.array[idx][0]:
								self.swap(__SCREAMING_SNAKE_CASE,self.par(__SCREAMING_SNAKE_CASE    )    )
								__lowerCAmelCase      		=       self.par(__SCREAMING_SNAKE_CASE    )





class 					_UpperCAmelCase							:
		def __init__(						self,__SCREAMING_SNAKE_CASE    ):



					'''simple docstring'''

					__lowerCAmelCase      		=       {}  # To store graph: u -> (v,w)
					__lowerCAmelCase      		=       num  # Number of nodes in graph
					# To store the distance from source vertex
					__lowerCAmelCase      		=       [0] * self.num_nodes
					__lowerCAmelCase      		=       [-1] * self.num_nodes  # To store the path
		def 						lowerCamelCase__    (						self,__SCREAMING_SNAKE_CASE,__SCREAMING_SNAKE_CASE,__SCREAMING_SNAKE_CASE    ):



					'''simple docstring'''

					if u in self.adjList:
								self.adjList[u].append((v, w)    )
					else:
								__lowerCAmelCase      		=       [(v, w)]

					# Assuming undirected graph
					if v in self.adjList:
								self.adjList[v].append((u, w)    )
					else:
								__lowerCAmelCase      		=       [(u, w)]
		def 						lowerCamelCase__    (						self    ):



					'''simple docstring'''

					for u in self.adjList:
								print(__SCREAMING_SNAKE_CASE,"""->""",""" -> """.join(str(f'{v}({w})'    ) for v, w in self.adjList[u]    )    )
		def 						lowerCamelCase__    (						self,__SCREAMING_SNAKE_CASE    ):



					'''simple docstring'''

					__lowerCAmelCase      		=       [-1] * self.num_nodes
					# src is the source node
					__lowerCAmelCase      		=       0
					__lowerCAmelCase      		=       PriorityQueue()
					q.insert((0, src)    )  # (dist from src, node)
					for u in self.adjList:
								if u != src:
											__lowerCAmelCase      		=       sys.maxsize  # Infinity
											__lowerCAmelCase      		=       -1

					while not q.is_empty():
								__lowerCAmelCase      		=       q.extract_min()  # Returns node with the min dist from source
								# Update the distance of all the neighbours of u and
								# if their prev dist was INFINITY then push them in Q
								for v, w in self.adjList[u]:
											__lowerCAmelCase      		=       self.dist[u] + w
											if self.dist[v] > new_dist:
														if self.dist[v] == sys.maxsize:
																	q.insert((new_dist, v)    )
														else:
																	q.decrease_key((self.dist[v], v),__SCREAMING_SNAKE_CASE    )
														__lowerCAmelCase      		=       new_dist
														__lowerCAmelCase      		=       u

        # Show the shortest distances from src
					self.show_distances(__SCREAMING_SNAKE_CASE    )
		def 						lowerCamelCase__    (						self,__SCREAMING_SNAKE_CASE    ):



					'''simple docstring'''

					print(f'Distance from node: {src}'    )
					for u in range(self.num_nodes    ):
								print(f'Node {u} has distance: {self.dist[u]}'    )







		def 						lowerCamelCase__    (						self,__SCREAMING_SNAKE_CASE,__SCREAMING_SNAKE_CASE    ):



					'''simple docstring'''

					__lowerCAmelCase      		=       []
					__lowerCAmelCase      		=       0
					__lowerCAmelCase      		=       dest
					# Backtracking from dest to src
					while self.par[temp] != -1:
								path.append(__SCREAMING_SNAKE_CASE    )
								if temp != src:
											for v, w in self.adjList[temp]:
														if v == self.par[temp]:
																	cost += w
																	break
								__lowerCAmelCase      		=       self.par[temp]
					path.append(__SCREAMING_SNAKE_CASE    )
					path.reverse()

					print(f'----Path to reach {dest} from {src}----'    )
					for u in path:
								print(f'{u}',end=""" """    )
								if u != dest:
											print("""-> """,end=""""""    )

					print("""\nTotal cost of path: """,__SCREAMING_SNAKE_CASE    )


if __name__ == "__main__":
	_a      :				str											=					Graph(9)
	graph.add_edge(0, 1, 4)
	graph.add_edge(0, 7, 8)
	graph.add_edge(1, 2, 8)
	graph.add_edge(1, 7, 1_1)
	graph.add_edge(2, 3, 7)
	graph.add_edge(2, 8, 2)
	graph.add_edge(2, 5, 4)
	graph.add_edge(3, 4, 9)
	graph.add_edge(3, 5, 1_4)
	graph.add_edge(4, 5, 1_0)
	graph.add_edge(5, 6, 2)
	graph.add_edge(6, 7, 1)
	graph.add_edge(6, 8, 6)
	graph.add_edge(7, 8, 7)
	graph.show_graph()
	graph.dijkstra(0)
	graph.show_path(0, 4)

# OUTPUT
# 0 -> 1(4) -> 7(8)
# 1 -> 0(4) -> 2(8) -> 7(11)
# 7 -> 0(8) -> 1(11) -> 6(1) -> 8(7)
# 2 -> 1(8) -> 3(7) -> 8(2) -> 5(4)
# 3 -> 2(7) -> 4(9) -> 5(14)
# 8 -> 2(2) -> 6(6) -> 7(7)
# 5 -> 2(4) -> 3(14) -> 4(10) -> 6(2)
# 4 -> 3(9) -> 5(10)
# 6 -> 5(2) -> 7(1) -> 8(6)
# Distance from node: 0
# Node 0 has distance: 0
# Node 1 has distance: 4
# Node 2 has distance: 12
# Node 3 has distance: 19
# Node 4 has distance: 21
# Node 5 has distance: 11
# Node 6 has distance: 9
# Node 7 has distance: 8
# Node 8 has distance: 14
# ----Path to reach 4 from 0----
# 0 -> 7 -> 6 -> 5 -> 4
# Total cost of path:  21

