


from queue import PriorityQueue
from typing import Any

import numpy as np

def 						_UpperCAmelCase				(			SCREAMING_SNAKE_CASE__			:					dict			,     SCREAMING_SNAKE_CASE__			:					str			,     SCREAMING_SNAKE_CASE__			:					set			,     SCREAMING_SNAKE_CASE__			:					set			,     SCREAMING_SNAKE_CASE__			:					dict			,     SCREAMING_SNAKE_CASE__			:					dict			,     SCREAMING_SNAKE_CASE__			:					PriorityQueue			,     SCREAMING_SNAKE_CASE__			:					dict			,     SCREAMING_SNAKE_CASE__			:					float | int			,     ):
     for nxt, d in graph[v]:
          if nxt in visited_forward:
               continue
          __UpperCamelCase    							=cst_fwd.get(SCREAMING_SNAKE_CASE__			,     np.inf				)
          __UpperCamelCase    							=cst_fwd[v] + d
          if new_cost_f < old_cost_f:
               queue.put((new_cost_f, nxt)				)
               __UpperCamelCase    							=new_cost_f
               __UpperCamelCase    							=v
          if nxt in visited_backward:
               if cst_fwd[v] + d + cst_bwd[nxt] < shortest_distance:
                    __UpperCamelCase    							=cst_fwd[v] + d + cst_bwd[nxt]
     return shortest_distance

def 						_UpperCAmelCase				(			SCREAMING_SNAKE_CASE__			:					str			,     SCREAMING_SNAKE_CASE__			:					str			,     SCREAMING_SNAKE_CASE__			:					dict			,     SCREAMING_SNAKE_CASE__			:					dict				):
     __UpperCamelCase    							=-1

     __UpperCamelCase    							=set()
     __UpperCamelCase    							=set()
     __UpperCamelCase    							={source: 0}
     __UpperCamelCase    							={destination: 0}
     __UpperCamelCase    							={source: None}
     __UpperCamelCase    							={destination: None}
     __UpperCamelCase    							=PriorityQueue()
     __UpperCamelCase    							=PriorityQueue()

     __UpperCamelCase    							=np.inf

     queue_forward.put((0, source)				)
     queue_backward.put((0, destination)				)

     if source == destination:
          return 0

     while not queue_forward.empty() and not queue_backward.empty():
          __UpperCamelCase							,      __UpperCamelCase    							=queue_forward.get()
          visited_forward.add(SCREAMING_SNAKE_CASE__				)

          __UpperCamelCase							,      __UpperCamelCase    							=queue_backward.get()
          visited_backward.add(SCREAMING_SNAKE_CASE__				)

          __UpperCamelCase    							=pass_and_relaxation(
              SCREAMING_SNAKE_CASE__			,     SCREAMING_SNAKE_CASE__			,     SCREAMING_SNAKE_CASE__			,     SCREAMING_SNAKE_CASE__			,     SCREAMING_SNAKE_CASE__			,     SCREAMING_SNAKE_CASE__			,     SCREAMING_SNAKE_CASE__			,     SCREAMING_SNAKE_CASE__			,     SCREAMING_SNAKE_CASE__			,     )

          __UpperCamelCase    							=pass_and_relaxation(
              SCREAMING_SNAKE_CASE__			,     SCREAMING_SNAKE_CASE__			,     SCREAMING_SNAKE_CASE__			,     SCREAMING_SNAKE_CASE__			,     SCREAMING_SNAKE_CASE__			,     SCREAMING_SNAKE_CASE__			,     SCREAMING_SNAKE_CASE__			,     SCREAMING_SNAKE_CASE__			,     SCREAMING_SNAKE_CASE__			,     )

          if cst_fwd[v_fwd] + cst_bwd[v_bwd] >= shortest_distance:
               break

     if shortest_distance != np.inf:
          __UpperCamelCase    							=shortest_distance
     return shortest_path_distance


_A		       =						{
    'B': [['C', 1]],
    'C': [['D', 1]],
    'D': [['F', 1]],
    'E': [['B', 1], ['G', 2]],
    'F': [],
    'G': [['F', 1]],
}
_A		       =						{
    'B': [['E', 1]],
    'C': [['B', 1]],
    'D': [['C', 1]],
    'F': [['D', 1], ['G', 1]],
    'E': [[None, np.inf]],
    'G': [['E', 2]],
}

if __name__ == "__main__":
   import doctest

   doctest.testmod()










"""simple docstring"""

import os
import tempfile
import unittest
import uuid
from pathlib import Path

from transformers.testing_utils import get_tests_dir, require_soundfile, require_torch, require_vision
from transformers.tools.agent_types import AgentAudio, AgentImage, AgentText
from transformers.utils import is_soundfile_availble, is_torch_available, is_vision_available


if is_torch_available():
     import torch

if is_soundfile_availble():
     import soundfile as sf

if is_vision_available():
     from PIL import Image




def __lowercase			(							_a=""    ):
    snake_case_ :     List[str]				=	tempfile.mkdtemp()
    return os.path.join(_a		,			str(uuid.uuida()    ) + suffix    )




@require_soundfile
@require_torch
class        _UpperCAmelCase       (			unittest.TestCase):

 def 						_snake_case					(     self		:       str				):
     snake_case_ :     int				=	torch.rand(12  ,     dtype=torch.floataa				) - 0.5
     snake_case_ :     Optional[int]				=	AgentAudio(lowercase_				)
     snake_case_ :     List[str]				=	str(agent_type.to_string()				)

     # Ensure that the tensor and the agent_type's tensor are the same
     self.assertTrue(torch.allclose(lowercase_  ,     agent_type.to_raw()  ,     atol=1E-4				)				)

     del agent_type

     # Ensure the path remains even after the object deletion
     self.assertTrue(os.path.exists(lowercase_				)				)

     # Ensure that the file contains the same value as the original tensor
     snake_case_,	snake_case_ :     int				=	sf.read(lowercase_				)
     self.assertTrue(torch.allclose(lowercase_  ,     torch.tensor(lowercase_				)  ,     atol=1E-4				)				)






 def 						_snake_case					(     self		:       Optional[int]				):
     snake_case_ :     Any				=	torch.rand(12  ,     dtype=torch.floataa				) - 0.5
     snake_case_ :     List[str]				=	get_new_path(suffix='''.wav'''				)
     sf.write(lowercase_  ,     lowercase_  ,     16000				)

     snake_case_ :     Tuple				=	AgentAudio(lowercase_				)

     self.assertTrue(torch.allclose(lowercase_  ,     agent_type.to_raw()  ,     atol=1E-4				)				)
     self.assertEqual(agent_type.to_string()  ,     lowercase_				)





@require_vision
@require_torch
class        _UpperCAmelCase       (			unittest.TestCase):

 def 						_snake_case					(     self		:       Tuple				):
     snake_case_ :     List[Any]				=	torch.randint(0  ,     256  ,     (64, 64, 3)				)
     snake_case_ :     str				=	AgentImage(lowercase_				)
     snake_case_ :     Union[str, Any]				=	str(agent_type.to_string()				)

     # Ensure that the tensor and the agent_type's tensor are the same
     self.assertTrue(torch.allclose(lowercase_  ,     agent_type._tensor  ,     atol=1E-4				)				)

     self.assertIsInstance(agent_type.to_raw()  ,     Image.Image				)

     # Ensure the path remains even after the object deletion
     del agent_type
     self.assertTrue(os.path.exists(lowercase_				)				)

 def 						_snake_case					(     self		:       str				):
     snake_case_ :     Any				=	Path(get_tests_dir('''fixtures/tests_samples/COCO'''				)				) / '''000000039769.png'''
     snake_case_ :     Optional[int]				=	Image.open(lowercase_				)
     snake_case_ :     Tuple				=	AgentImage(lowercase_				)

     self.assertTrue(path.samefile(agent_type.to_string()				)				)
     self.assertTrue(image == agent_type.to_raw()				)

     # Ensure the path remains even after the object deletion
     del agent_type
     self.assertTrue(os.path.exists(lowercase_				)				)






 def 						_snake_case					(     self		:       str				):
     snake_case_ :     int				=	Path(get_tests_dir('''fixtures/tests_samples/COCO'''				)				) / '''000000039769.png'''
     snake_case_ :     Dict				=	Image.open(lowercase_				)
     snake_case_ :     List[str]				=	AgentImage(lowercase_				)

     self.assertFalse(path.samefile(agent_type.to_string()				)				)
     self.assertTrue(image == agent_type.to_raw()				)

     # Ensure the path remains even after the object deletion
     del agent_type
     self.assertTrue(os.path.exists(lowercase_				)				)





class        _UpperCAmelCase       (			unittest.TestCase):

 def 						_snake_case					(     self		:       Any				):
     snake_case_ :     Tuple				=	'''Hey!'''
     snake_case_ :     Optional[Any]				=	AgentText(lowercase_				)

     self.assertEqual(lowercase_  ,     agent_type.to_string()				)
     self.assertEqual(lowercase_  ,     agent_type.to_raw()				)
     self.assertEqual(lowercase_  ,     lowercase_				)





