


import unittest

import numpy as np

from transformers.testing_utils import require_flax, require_tf, require_torch
from transformers.utils import (
    expand_dims,
    flatten_dict,
    is_flax_available,
    is_tf_available,
    is_torch_available,
    reshape,
    squeeze,
    transpose,
)


if is_flax_available():
    import jax.numpy as jnp

if is_tf_available():
    import tensorflow as tf

if is_torch_available():
    import torch







class 			_lowercase (							unittest.TestCase):


       """simple docstring"""




       def 						lowerCAmelCase     (   self							:			List[Any]       ):


             '''simple docstring'''



             lowerCamelCase__		:				str    =  {
                 "task_specific_params": {
                     "summarization": {"length_penalty": 1.0, "max_length": 128, "min_length": 12, "num_beams": 4},
                     "summarization_cnn": {"length_penalty": 2.0, "max_length": 142, "min_length": 56, "num_beams": 4},
                     "summarization_xsum": {"length_penalty": 1.0, "max_length": 62, "min_length": 11, "num_beams": 6},
                 }
             }
             lowerCamelCase__		:				int    =  {
                 "task_specific_params.summarization.length_penalty": 1.0,
                 "task_specific_params.summarization.max_length": 128,
                 "task_specific_params.summarization.min_length": 12,
                 "task_specific_params.summarization.num_beams": 4,
                 "task_specific_params.summarization_cnn.length_penalty": 2.0,
                 "task_specific_params.summarization_cnn.max_length": 142,
                 "task_specific_params.summarization_cnn.min_length": 56,
                 "task_specific_params.summarization_cnn.num_beams": 4,
                 "task_specific_params.summarization_xsum.length_penalty": 1.0,
                 "task_specific_params.summarization_xsum.max_length": 62,
                 "task_specific_params.summarization_xsum.min_length": 11,
                 "task_specific_params.summarization_xsum.num_beams": 6,
             }

             self.assertEqual(flatten_dict(__lowerCamelCase       )					,      __lowerCamelCase       )





       def 						lowerCAmelCase     (   self							:			Tuple       ):


             '''simple docstring'''



             lowerCamelCase__		:				Dict    =  np.random.randn(3					,      4       )
             self.assertTrue(np.allclose(transpose(__lowerCamelCase       )					,      x.transpose()       )       )

             lowerCamelCase__		:				List[str]    =  np.random.randn(3					,      4					,      5       )
             self.assertTrue(np.allclose(transpose(__lowerCamelCase					,      axes=(1, 2, 0)       )					,      x.transpose((1, 2, 0)       )       )       )





       @require_torch
       def 						lowerCAmelCase     (   self							:			str       ):


             '''simple docstring'''



             lowerCamelCase__		:				Optional[Any]    =  np.random.randn(3					,      4       )
             lowerCamelCase__		:				List[Any]    =  torch.tensor(__lowerCamelCase       )
             self.assertTrue(np.allclose(transpose(__lowerCamelCase       )					,      transpose(__lowerCamelCase       ).numpy()       )       )

             lowerCamelCase__		:				Any    =  np.random.randn(3					,      4					,      5       )
             lowerCamelCase__		:				List[str]    =  torch.tensor(__lowerCamelCase       )
             self.assertTrue(np.allclose(transpose(__lowerCamelCase					,      axes=(1, 2, 0)       )					,      transpose(__lowerCamelCase					,      axes=(1, 2, 0)       ).numpy()       )       )





       @require_tf
       def 						lowerCAmelCase     (   self							:			Tuple       ):


             '''simple docstring'''



             lowerCamelCase__		:				List[str]    =  np.random.randn(3					,      4       )
             lowerCamelCase__		:				Optional[int]    =  tf.constant(__lowerCamelCase       )
             self.assertTrue(np.allclose(transpose(__lowerCamelCase       )					,      transpose(__lowerCamelCase       ).numpy()       )       )

             lowerCamelCase__		:				Optional[Any]    =  np.random.randn(3					,      4					,      5       )
             lowerCamelCase__		:				Optional[int]    =  tf.constant(__lowerCamelCase       )
             self.assertTrue(np.allclose(transpose(__lowerCamelCase					,      axes=(1, 2, 0)       )					,      transpose(__lowerCamelCase					,      axes=(1, 2, 0)       ).numpy()       )       )





       @require_flax
       def 						lowerCAmelCase     (   self							:			List[Any]       ):


             '''simple docstring'''



             lowerCamelCase__		:				Optional[int]    =  np.random.randn(3					,      4       )
             lowerCamelCase__		:				Optional[Any]    =  jnp.array(__lowerCamelCase       )
             self.assertTrue(np.allclose(transpose(__lowerCamelCase       )					,      np.asarray(transpose(__lowerCamelCase       )       )       )       )

             lowerCamelCase__		:				int    =  np.random.randn(3					,      4					,      5       )
             lowerCamelCase__		:				str    =  jnp.array(__lowerCamelCase       )
             self.assertTrue(np.allclose(transpose(__lowerCamelCase					,      axes=(1, 2, 0)       )					,      np.asarray(transpose(__lowerCamelCase					,      axes=(1, 2, 0)       )       )       )       )





       def 						lowerCAmelCase     (   self							:			Tuple       ):


             '''simple docstring'''



             lowerCamelCase__		:				str    =  np.random.randn(3					,      4       )
             self.assertTrue(np.allclose(reshape(__lowerCamelCase					,      (4, 3)       )					,      np.reshape(__lowerCamelCase					,      (4, 3)       )       )       )

             lowerCamelCase__		:				int    =  np.random.randn(3					,      4					,      5       )
             self.assertTrue(np.allclose(reshape(__lowerCamelCase					,      (12, 5)       )					,      np.reshape(__lowerCamelCase					,      (12, 5)       )       )       )





       @require_torch
       def 						lowerCAmelCase     (   self							:			Union[str, Any]       ):


             '''simple docstring'''



             lowerCamelCase__		:				Dict    =  np.random.randn(3					,      4       )
             lowerCamelCase__		:				Tuple    =  torch.tensor(__lowerCamelCase       )
             self.assertTrue(np.allclose(reshape(__lowerCamelCase					,      (4, 3)       )					,      reshape(__lowerCamelCase					,      (4, 3)       ).numpy()       )       )

             lowerCamelCase__		:				Optional[int]    =  np.random.randn(3					,      4					,      5       )
             lowerCamelCase__		:				Tuple    =  torch.tensor(__lowerCamelCase       )
             self.assertTrue(np.allclose(reshape(__lowerCamelCase					,      (12, 5)       )					,      reshape(__lowerCamelCase					,      (12, 5)       ).numpy()       )       )





       @require_tf
       def 						lowerCAmelCase     (   self							:			Optional[int]       ):


             '''simple docstring'''



             lowerCamelCase__		:				Union[str, Any]    =  np.random.randn(3					,      4       )
             lowerCamelCase__		:				List[Any]    =  tf.constant(__lowerCamelCase       )
             self.assertTrue(np.allclose(reshape(__lowerCamelCase					,      (4, 3)       )					,      reshape(__lowerCamelCase					,      (4, 3)       ).numpy()       )       )

             lowerCamelCase__		:				int    =  np.random.randn(3					,      4					,      5       )
             lowerCamelCase__		:				List[str]    =  tf.constant(__lowerCamelCase       )
             self.assertTrue(np.allclose(reshape(__lowerCamelCase					,      (12, 5)       )					,      reshape(__lowerCamelCase					,      (12, 5)       ).numpy()       )       )





       @require_flax
       def 						lowerCAmelCase     (   self							:			Optional[int]       ):


             '''simple docstring'''



             lowerCamelCase__		:				Tuple    =  np.random.randn(3					,      4       )
             lowerCamelCase__		:				List[str]    =  jnp.array(__lowerCamelCase       )
             self.assertTrue(np.allclose(reshape(__lowerCamelCase					,      (4, 3)       )					,      np.asarray(reshape(__lowerCamelCase					,      (4, 3)       )       )       )       )

             lowerCamelCase__		:				Union[str, Any]    =  np.random.randn(3					,      4					,      5       )
             lowerCamelCase__		:				Tuple    =  jnp.array(__lowerCamelCase       )
             self.assertTrue(np.allclose(reshape(__lowerCamelCase					,      (12, 5)       )					,      np.asarray(reshape(__lowerCamelCase					,      (12, 5)       )       )       )       )





       def 						lowerCAmelCase     (   self							:			List[Any]       ):


             '''simple docstring'''



             lowerCamelCase__		:				int    =  np.random.randn(1					,      3					,      4       )
             self.assertTrue(np.allclose(squeeze(__lowerCamelCase       )					,      np.squeeze(__lowerCamelCase       )       )       )

             lowerCamelCase__		:				List[str]    =  np.random.randn(1					,      4					,      1					,      5       )
             self.assertTrue(np.allclose(squeeze(__lowerCamelCase					,      axis=2       )					,      np.squeeze(__lowerCamelCase					,      axis=2       )       )       )





       @require_torch
       def 						lowerCAmelCase     (   self							:			List[Any]       ):


             '''simple docstring'''



             lowerCamelCase__		:				Optional[Any]    =  np.random.randn(1					,      3					,      4       )
             lowerCamelCase__		:				str    =  torch.tensor(__lowerCamelCase       )
             self.assertTrue(np.allclose(squeeze(__lowerCamelCase       )					,      squeeze(__lowerCamelCase       ).numpy()       )       )

             lowerCamelCase__		:				Tuple    =  np.random.randn(1					,      4					,      1					,      5       )
             lowerCamelCase__		:				List[Any]    =  torch.tensor(__lowerCamelCase       )
             self.assertTrue(np.allclose(squeeze(__lowerCamelCase					,      axis=2       )					,      squeeze(__lowerCamelCase					,      axis=2       ).numpy()       )       )





       @require_tf
       def 						lowerCAmelCase     (   self							:			Optional[int]       ):


             '''simple docstring'''



             lowerCamelCase__		:				str    =  np.random.randn(1					,      3					,      4       )
             lowerCamelCase__		:				List[Any]    =  tf.constant(__lowerCamelCase       )
             self.assertTrue(np.allclose(squeeze(__lowerCamelCase       )					,      squeeze(__lowerCamelCase       ).numpy()       )       )

             lowerCamelCase__		:				Dict    =  np.random.randn(1					,      4					,      1					,      5       )
             lowerCamelCase__		:				str    =  tf.constant(__lowerCamelCase       )
             self.assertTrue(np.allclose(squeeze(__lowerCamelCase					,      axis=2       )					,      squeeze(__lowerCamelCase					,      axis=2       ).numpy()       )       )





       @require_flax
       def 						lowerCAmelCase     (   self							:			List[str]       ):


             '''simple docstring'''



             lowerCamelCase__		:				Any    =  np.random.randn(1					,      3					,      4       )
             lowerCamelCase__		:				str    =  jnp.array(__lowerCamelCase       )
             self.assertTrue(np.allclose(squeeze(__lowerCamelCase       )					,      np.asarray(squeeze(__lowerCamelCase       )       )       )       )

             lowerCamelCase__		:				Dict    =  np.random.randn(1					,      4					,      1					,      5       )
             lowerCamelCase__		:				Tuple    =  jnp.array(__lowerCamelCase       )
             self.assertTrue(np.allclose(squeeze(__lowerCamelCase					,      axis=2       )					,      np.asarray(squeeze(__lowerCamelCase					,      axis=2       )       )       )       )





       def 						lowerCAmelCase     (   self							:			Dict       ):


             '''simple docstring'''



             lowerCamelCase__		:				int    =  np.random.randn(3					,      4       )
             self.assertTrue(np.allclose(expand_dims(__lowerCamelCase					,      axis=1       )					,      np.expand_dims(__lowerCamelCase					,      axis=1       )       )       )





       @require_torch
       def 						lowerCAmelCase     (   self							:			Dict       ):


             '''simple docstring'''



             lowerCamelCase__		:				int    =  np.random.randn(3					,      4       )
             lowerCamelCase__		:				Union[str, Any]    =  torch.tensor(__lowerCamelCase       )
             self.assertTrue(np.allclose(expand_dims(__lowerCamelCase					,      axis=1       )					,      expand_dims(__lowerCamelCase					,      axis=1       ).numpy()       )       )





       @require_tf
       def 						lowerCAmelCase     (   self							:			Dict       ):


             '''simple docstring'''



             lowerCamelCase__		:				List[Any]    =  np.random.randn(3					,      4       )
             lowerCamelCase__		:				List[Any]    =  tf.constant(__lowerCamelCase       )
             self.assertTrue(np.allclose(expand_dims(__lowerCamelCase					,      axis=1       )					,      expand_dims(__lowerCamelCase					,      axis=1       ).numpy()       )       )





       @require_flax
       def 						lowerCAmelCase     (   self							:			Any       ):


             '''simple docstring'''



             lowerCamelCase__		:				Dict    =  np.random.randn(3					,      4       )
             lowerCamelCase__		:				Any    =  jnp.array(__lowerCamelCase       )
             self.assertTrue(np.allclose(expand_dims(__lowerCamelCase					,      axis=1       )					,      np.asarray(expand_dims(__lowerCamelCase					,      axis=1       )       )       )       )






from __future__ import annotations

A      :    Union[str, Any]		=					{
    "A": ["B", "C", "E"],
    "B": ["A", "D", "E"],
    "C": ["A", "F", "G"],
    "D": ["B"],
    "E": ["A", "B", "D"],
    "F": ["C"],
    "G": ["C"],
}







class 			_lowercase :


       """simple docstring"""




       def __init__(   self							:			Tuple					,      __lowerCamelCase							:			dict[str, list[str]]					,      __lowerCamelCase							:			str       ):


             '''simple docstring'''



             lowerCamelCase__		:				Union[str, Any]    =  graph
             # mapping node to its parent in resulting breadth first tree
             lowerCamelCase__		:				dict[str, str | None]    =  {}
             lowerCamelCase__		:				Dict    =  source_vertex





       def 						lowerCAmelCase     (   self							:			Any       ):


             '''simple docstring'''



             lowerCamelCase__		:				int    =  {self.source_vertex}
             lowerCamelCase__		:				Optional[int]    =  None
             lowerCamelCase__		:				Dict    =  [self.source_vertex]  # first in first out queue

             while queue:
                   lowerCamelCase__		:				Optional[int]    =  queue.pop(0       )
                   for adjacent_vertex in self.graph[vertex]:
                         if adjacent_vertex not in visited:
                               visited.add(__lowerCamelCase       )
                               lowerCamelCase__		:				List[str]    =  vertex
                               queue.append(__lowerCamelCase       )





       def 						lowerCAmelCase     (   self							:			Optional[Any]					,      __lowerCamelCase							:			str       ):


             '''simple docstring'''



             if target_vertex == self.source_vertex:
                   return self.source_vertex

             lowerCamelCase__		:				Tuple    =  self.parent.get(__lowerCamelCase       )
             if target_vertex_parent is None:
                   lowerCamelCase__		:				Tuple    =  (
                       f"No path from vertex: {self.source_vertex} to vertex: {target_vertex}"
                   )
                   raise ValueError(__lowerCamelCase       )

             return self.shortest_path(__lowerCamelCase       ) + f"->{target_vertex}"


if __name__ == "__main__":
    A      :    List[str]		=					Graph(graph, "G")
    g.breath_first_search()
    print(g.shortest_path("D"))
    print(g.shortest_path("G"))
    print(g.shortest_path("Foo"))


