





import logging
import os
import sys
from pathlib import Path
from unittest.mock import patch

from parameterized import parameterized
from run_eval import run_generate
from run_eval_search import run_search

from transformers.testing_utils import CaptureStdout, TestCasePlus, slow
from utils import ROUGE_KEYS


logging.basicConfig(level=logging.DEBUG)
lowercase    : str    	=  logging.getLogger()


def     SCREAMING_SNAKE_CASE			(      lowerCAmelCase    ,       lowerCAmelCase					):
       _UpperCamelCase              =						'''\n'''.join(__snake_case					)
       Path(__snake_case					).open('''w'''					).writelines(__snake_case					)


lowercase    : Optional[int]    	=  """patrickvonplaten/t5-tiny-random"""
lowercase    : str    	=  """sshleifer/bart-tiny-random"""
lowercase    : int    	=  """sshleifer/tiny-mbart"""

lowercase    : Any    	=  logging.StreamHandler(sys.stdout)
logger.addHandler(stream_handler)
logging.disable(logging.CRITICAL)  # remove noisy download output from tracebacks

class  __A(						__UpperCAmelCase ):

     def 	_UpperCamelCase     (      self,       A      ):





            """simple docstring"""

            _UpperCamelCase              =						Path(self.get_auto_remove_tmp_dir()      ) / '''utest_input.source'''
            _UpperCamelCase              =						input_file_name.parent / '''utest_output.txt'''
            assert not output_file_name.exists()
            _UpperCamelCase              =						[''' New York (CNN)When Liana Barrientos was 23 years old, she got married in Westchester County.''']
            _dump_articles(__a,       __a      )

            _UpperCamelCase              =						str(Path(self.get_auto_remove_tmp_dir()      ) / '''scores.json'''      )
            _UpperCamelCase              =						'''translation_en_to_de''' if model == T5_TINY else '''summarization'''
            _UpperCamelCase              =						F'''
            run_eval_search.py
            {model}
            {input_file_name}
            {output_file_name}
            --score_path {score_path}
            --task {task}
            --num_beams 2
            --length_penalty 2.0
            '''.split()

            with patch.object(__a,       '''argv''',       __a      ):
                   run_generate()
                   assert Path(__a      ).exists()
                   # os.remove(Path(output_file_name))

     def 	_UpperCamelCase     (      self      ):





            """simple docstring"""

            self.run_eval_tester(__a      )

     @parameterized.expand([BART_TINY, MBART_TINY]      )
     @slow
     def 	_UpperCamelCase     (      self,       A      ):





            """simple docstring"""

            self.run_eval_tester(__a      )



     @parameterized.expand([T5_TINY, MBART_TINY]      )
     @slow
     def 	_UpperCamelCase     (      self,       A      ):





            """simple docstring"""

            _UpperCamelCase              =						Path(self.get_auto_remove_tmp_dir()      ) / '''utest_input.source'''
            _UpperCamelCase              =						input_file_name.parent / '''utest_output.txt'''
            assert not output_file_name.exists()

            _UpperCamelCase              =						{
                '''en''': ['''Machine learning is great, isn\'t it?''', '''I like to eat bananas''', '''Tomorrow is another great day!'''],
                '''de''': [
                    '''Maschinelles Lernen ist großartig, oder?''',
                    '''Ich esse gerne Bananen''',
                    '''Morgen ist wieder ein toller Tag!''',
                ],
            }

            _UpperCamelCase              =						Path(self.get_auto_remove_tmp_dir()      )
            _UpperCamelCase              =						str(tmp_dir / '''scores.json'''      )
            _UpperCamelCase              =						str(tmp_dir / '''val.target'''      )
            _dump_articles(__a,       text['''en''']      )
            _dump_articles(__a,       text['''de''']      )
            _UpperCamelCase              =						'''translation_en_to_de''' if model == T5_TINY else '''summarization'''
            _UpperCamelCase              =						F'''
            run_eval_search.py
            {model}
            {str(__a      )}
            {str(__a      )}
            --score_path {score_path}
            --reference_path {reference_path}
            --task {task}
            '''.split()
            testargs.extend(['''--search''', '''num_beams=1:2 length_penalty=0.9:1.0''']      )

            with patch.object(__a,       '''argv''',       __a      ):
                   with CaptureStdout() as cs:
                          run_search()
                   _UpperCamelCase              =						[''' num_beams | length_penalty''', model, '''Best score args''']
                   _UpperCamelCase              =						['''Info''']
                   if "translation" in task:
                          expected_strings.append('''bleu'''      )
                   else:
                          expected_strings.extend(__a      )
                   for w in expected_strings:
                          assert w in cs.out
                   for w in un_expected_strings:
                          assert w not in cs.out
                   assert Path(__a      ).exists()
                   os.remove(Path(__a      )      )













from __future__ import annotations

lowercase    : int    	=  {
    """A""": ["""B""", """C""", """E"""],
    """B""": ["""A""", """D""", """E"""],
    """C""": ["""A""", """F""", """G"""],
    """D""": ["""B"""],
    """E""": ["""A""", """B""", """D"""],
    """F""": ["""C"""],
    """G""": ["""C"""],
}

class  __A:

     def __init__(      self,       A,       A      ):





            """simple docstring"""

            _UpperCamelCase              =						graph
            # mapping node to its parent in resulting breadth first tree
            _UpperCamelCase              =						{}
            _UpperCamelCase              =						source_vertex

     def 	_UpperCamelCase     (      self      ):





            """simple docstring"""

            _UpperCamelCase              =						{self.source_vertex}
            _UpperCamelCase              =						None
            _UpperCamelCase              =						[self.source_vertex]  # first in first out queue

            while queue:
                   _UpperCamelCase              =						queue.pop(0      )
                   for adjacent_vertex in self.graph[vertex]:
                          if adjacent_vertex not in visited:
                                 visited.add(A      )
                                 _UpperCamelCase              =						vertex
                                 queue.append(A      )



     def 	_UpperCamelCase     (      self,       A      ):





            """simple docstring"""

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

            _UpperCamelCase              =						self.parent.get(A      )
            if target_vertex_parent is None:
                   _UpperCamelCase              =						(
                       F'''No path from vertex: {self.source_vertex} to vertex: {target_vertex}'''
                   )
                   raise ValueError(A      )

            return self.shortest_path(A      ) + F'''->{target_vertex}'''


if __name__ == "__main__":
       lowercase    : Tuple    	=  Graph(graph, """G""")
       g.breath_first_search()
       print(g.shortest_path("""D"""))
       print(g.shortest_path("""G"""))
       print(g.shortest_path("""Foo"""))






