
'''simple docstring'''




import unittest
from pathlib import Path
from tempfile import NamedTemporaryFile, TemporaryDirectory

from transformers import BertConfig, BertTokenizerFast, FeatureExtractionPipeline
from transformers.convert_graph_to_onnx import (
    convert,
    ensure_valid_input,
    generate_identified_filename,
    infer_shapes,
    quantize,
)
from transformers.testing_utils import require_tf, require_tokenizers, require_torch, slow





class  A				:





     def 				__lowerCAmelCase							(							self						,			SCREAMING_SNAKE_CASE						,			SCREAMING_SNAKE_CASE						,			SCREAMING_SNAKE_CASE	) ->				Optional[int]:






         """simple docstring"""






         return None





class  A				:





     def 				__lowerCAmelCase							(							self						,			SCREAMING_SNAKE_CASE						,			SCREAMING_SNAKE_CASE						,			SCREAMING_SNAKE_CASE						,			SCREAMING_SNAKE_CASE	) ->				str:






         """simple docstring"""






         return None





class  A				(							unittest.TestCase						):
     __magic_name__						=		[
         # (model_name, model_kwargs)
         ('''bert-base-cased''', {}),
         ('''gpt2''', {'''use_cache''': False}),  # We don't support exporting GPT2 past keys anymore
     ]





     @require_tf
     @slow
     def 				__lowerCAmelCase							(							self	) ->				List[str]:






         """simple docstring"""






         for model, model_kwargs in OnnxExportTestCase.MODEL_TO_TEST:
             self._test_export(_UpperCamelCase						,			'''tf'''						,			12						,			**_UpperCamelCase	)





     @require_torch
     @slow
     def 				__lowerCAmelCase							(							self	) ->				Optional[int]:






         """simple docstring"""






         for model, model_kwargs in OnnxExportTestCase.MODEL_TO_TEST:
             self._test_export(_UpperCamelCase						,			'''pt'''						,			12						,			**_UpperCamelCase	)





     @require_torch
     @slow
     def 				__lowerCAmelCase							(							self	) ->				Optional[Any]:






         """simple docstring"""






         from transformers import BertModel

         A       :   Tuple					=						['''[UNK]''', '''[SEP]''', '''[CLS]''', '''[PAD]''', '''[MASK]''', '''some''', '''other''', '''words''']
         with NamedTemporaryFile(mode='''w+t'''	) as vocab_file:
             vocab_file.write('''\n'''.join(_UpperCamelCase	)	)
             vocab_file.flush()
             A       :   Any					=						BertTokenizerFast(vocab_file.name	)

         with TemporaryDirectory() as bert_save_dir:
             A       :   Optional[Any]					=						BertModel(BertConfig(vocab_size=len(_UpperCamelCase	)	)	)
             model.save_pretrained(_UpperCamelCase	)
             self._test_export(_UpperCamelCase						,			'''pt'''						,			12						,			_UpperCamelCase	)





     @require_tf
     @slow
     def 				__lowerCAmelCase							(							self	) ->				Tuple:






         """simple docstring"""






         for model, model_kwargs in OnnxExportTestCase.MODEL_TO_TEST:
             A       :   List[str]					=						self._test_export(_UpperCamelCase						,			'''tf'''						,			12						,			**_UpperCamelCase	)
             A       :   Optional[int]					=						quantize(Path(_UpperCamelCase	)	)

             # Ensure the actual quantized model is not bigger than the original one
             if quantized_path.stat().st_size >= Path(_UpperCamelCase	).stat().st_size:
                 self.fail('''Quantized model is bigger than initial ONNX model'''	)





     @require_torch
     @slow
     def 				__lowerCAmelCase							(							self	) ->				Tuple:






         """simple docstring"""






         for model, model_kwargs in OnnxExportTestCase.MODEL_TO_TEST:
             A       :   Dict					=						self._test_export(_UpperCamelCase						,			'''pt'''						,			12						,			**_UpperCamelCase	)
             A       :   Optional[int]					=						quantize(_UpperCamelCase	)

             # Ensure the actual quantized model is not bigger than the original one
             if quantized_path.stat().st_size >= Path(_UpperCamelCase	).stat().st_size:
                 self.fail('''Quantized model is bigger than initial ONNX model'''	)





     def 				__lowerCAmelCase							(							self						,			SCREAMING_SNAKE_CASE						,			SCREAMING_SNAKE_CASE						,			SCREAMING_SNAKE_CASE						,			SCREAMING_SNAKE_CASE=None						,			**SCREAMING_SNAKE_CASE	) ->				Any:






         """simple docstring"""






         try:
             # Compute path
             with TemporaryDirectory() as tempdir:
                 A       :   List[str]					=						Path(_UpperCamelCase	).joinpath('''model.onnx'''	)

             # Remove folder if exists
             if path.parent.exists():
                 path.parent.rmdir()

             # Export
             convert(_UpperCamelCase						,			_UpperCamelCase						,			_UpperCamelCase						,			_UpperCamelCase						,			_UpperCamelCase						,			**_UpperCamelCase	)

             return path
         except Exception as e:
             self.fail(_UpperCamelCase	)





     @require_torch
     @require_tokenizers
     @slow
     def 				__lowerCAmelCase							(							self	) ->				Optional[Any]:






         """simple docstring"""






         from transformers import BertModel

         A       :   int					=						BertModel(BertConfig.from_pretrained('''lysandre/tiny-bert-random'''	)	)
         A       :   Optional[Any]					=						BertTokenizerFast.from_pretrained('''lysandre/tiny-bert-random'''	)
         self._test_infer_dynamic_axis(_UpperCamelCase						,			_UpperCamelCase						,			'''pt'''	)





     @require_tf
     @require_tokenizers
     @slow
     def 				__lowerCAmelCase							(							self	) ->				Union[str, Any]:






         """simple docstring"""






         from transformers import TFBertModel

         A       :   int					=						TFBertModel(BertConfig.from_pretrained('''lysandre/tiny-bert-random'''	)	)
         A       :   Optional[int]					=						BertTokenizerFast.from_pretrained('''lysandre/tiny-bert-random'''	)
         self._test_infer_dynamic_axis(_UpperCamelCase						,			_UpperCamelCase						,			'''tf'''	)





     def 				__lowerCAmelCase							(							self						,			SCREAMING_SNAKE_CASE						,			SCREAMING_SNAKE_CASE						,			SCREAMING_SNAKE_CASE	) ->				Any:






         """simple docstring"""






         A       :   Any					=						FeatureExtractionPipeline(_UpperCamelCase						,			_UpperCamelCase	)

         A       :   Optional[Any]					=						['''input_ids''', '''token_type_ids''', '''attention_mask''', '''output_0''', '''output_1''']
         A,  A,  A,  A       :   List[Any]					=						infer_shapes(_UpperCamelCase						,			_UpperCamelCase	)

         # Assert all variables are present
         self.assertEqual(len(_UpperCamelCase	)						,			len(_UpperCamelCase	)	)
         self.assertTrue(all(var_name in shapes for var_name in variable_names	)	)
         self.assertSequenceEqual(variable_names[:3]						,			_UpperCamelCase	)
         self.assertSequenceEqual(variable_names[3:]						,			_UpperCamelCase	)

         # Assert inputs are {0: batch, 1: sequence}
         for var_name in ["input_ids", "token_type_ids", "attention_mask"]:
             self.assertDictEqual(shapes[var_name]						,			{0: '''batch''', 1: '''sequence'''}	)

         # Assert outputs are {0: batch, 1: sequence} and {0: batch}
         self.assertDictEqual(shapes['''output_0''']						,			{0: '''batch''', 1: '''sequence'''}	)
         self.assertDictEqual(shapes['''output_1''']						,			{0: '''batch'''}	)





     def 				__lowerCAmelCase							(							self	) ->				Optional[Any]:






         """simple docstring"""






         A       :   int					=						['''input_ids''', '''attention_mask''', '''token_type_ids''']
         A       :   int					=						{'''input_ids''': [1, 2, 3, 4], '''attention_mask''': [0, 0, 0, 0], '''token_type_ids''': [1, 1, 1, 1]}
         A,  A       :   Optional[int]					=						ensure_valid_input(FuncContiguousArgs()						,			_UpperCamelCase						,			_UpperCamelCase	)

         # Should have exactly the same number of args (all are valid)
         self.assertEqual(len(_UpperCamelCase	)						,			3	)

         # Should have exactly the same input names
         self.assertEqual(set(_UpperCamelCase	)						,			set(_UpperCamelCase	)	)

         # Parameter should be reordered according to their respective place in the function:
         # (input_ids, token_type_ids, attention_mask)
         self.assertEqual(_UpperCamelCase						,			(tokens['''input_ids'''], tokens['''token_type_ids'''], tokens['''attention_mask'''])	)

         # Generated args are interleaved with another args (for instance parameter "past" in GPT2)
         A,  A       :   Dict					=						ensure_valid_input(FuncNonContiguousArgs()						,			_UpperCamelCase						,			_UpperCamelCase	)

         # Should have exactly the one arg (all before the one not provided "some_other_args")
         self.assertEqual(len(_UpperCamelCase	)						,			1	)
         self.assertEqual(len(_UpperCamelCase	)						,			1	)

         # Should have only "input_ids"
         self.assertEqual(inputs_args[0]						,			tokens['''input_ids''']	)
         self.assertEqual(ordered_input_names[0]						,			'''input_ids'''	)





     def 				__lowerCAmelCase							(							self	) ->				List[Any]:






         """simple docstring"""






         A       :   Tuple					=						generate_identified_filename(Path('''/home/something/my_fake_model.onnx'''	)						,			'''-test'''	)
         self.assertEqual('''/home/something/my_fake_model-test.onnx'''						,			generated.as_posix()	)











import heapq
import sys

import numpy as np

snake_case__					:							Tuple													=     tuple[int, int]





class A_					:




   def __init__(self	:Union[str, Any] )->					Union[str, Any]:
         __A          =				[]
         __A          =				set()




   def _lowerCAmelCase      (self	:List[str] )->					str:
         if not self.empty():
               return self.elements[0][0]
         else:
               return float('''inf''' )




   def _lowerCAmelCase      (self	:Any )->					Any:
         return len(self.elements ) == 0




   def _lowerCAmelCase      (self	:List[str]    ,   _UpperCamelCase	:Optional[Any]    ,   _UpperCamelCase	:Optional[int] )->					Optional[int]:
         if item not in self.set:
               heapq.heappush(self.elements    ,   (priority, item) )
               self.set.add(_UpperCamelCase )
         else:
               # update
               # print("update", item)
               __A          =				[]
               ((__A)   ,						(__A))          =				heapq.heappop(self.elements )
               while x != item:
                     temp.append((pri, x) )
                     ((__A)   ,						(__A))          =				heapq.heappop(self.elements )
               temp.append((priority, item) )
               for pro, xxx in temp:
                     heapq.heappush(self.elements    ,   (pro, xxx) )




   def _lowerCAmelCase      (self	:int    ,   _UpperCamelCase	:int )->					int:
         if item in self.set:
               self.set.remove(_UpperCamelCase )
               __A          =				[]
               ((__A)   ,						(__A))          =				heapq.heappop(self.elements )
               while x != item:
                     temp.append((pro, x) )
                     ((__A)   ,						(__A))          =				heapq.heappop(self.elements )
               for prito, yyy in temp:
                     heapq.heappush(self.elements    ,   (prito, yyy) )




   def _lowerCAmelCase      (self	:Optional[Any] )->					int:
         return self.elements[0][1]






   def _lowerCAmelCase      (self	:List[str] )->					List[Any]:
         ((__A)   ,						(__A))          =				heapq.heappop(self.elements )
         self.set.remove(_UpperCamelCase )
         return (priority, item)





def _a				(	lowerCamelCase:   TPos					,				lowerCamelCase:   TPos )	->						Any:







      '''simple docstring'''






      __A          =				np.array(lowerCamelCase )
      __A          =				np.array(lowerCamelCase )
      return np.linalg.norm(a - b )



def _a				(	lowerCamelCase:   TPos					,				lowerCamelCase:   TPos )	->						List[str]:







      '''simple docstring'''






      return consistent_heuristic(lowerCamelCase					,				lowerCamelCase ) // t



def _a				(	lowerCamelCase:   TPos					,				lowerCamelCase:   TPos )	->						Any:







      '''simple docstring'''






      return abs(p[0] - goal[0] ) + abs(p[1] - goal[1] )



def _a				(	lowerCamelCase:   TPos					,				lowerCamelCase:   int					,				lowerCamelCase:   TPos					,				lowerCamelCase:   dict[TPos, float] )	->						Tuple:







      '''simple docstring'''






      __A          =				g_function[start] + Wa * heuristics[i](lowerCamelCase					,				lowerCamelCase )
      return ans



def _a				(	lowerCamelCase:   Tuple					,				lowerCamelCase:   Optional[int]					,				lowerCamelCase:   Optional[int] )	->						Tuple:







      '''simple docstring'''






      __A          =				np.chararray((n, n) )
      for i in range(lowerCamelCase ):
            for j in range(lowerCamelCase ):
                  __A          =				'''*'''

      for i in range(lowerCamelCase ):
            for j in range(lowerCamelCase ):
                  if (j, (n - 1) - i) in blocks:
                        __A          =				'''#'''

      __A          =				'''-'''
      __A          =				back_pointer[goal]
      while x != start:
            ((__A)   ,						(__A))          =				x
            # print(x)
            __A          =				'''-'''
            __A          =				back_pointer[x]
      __A          =				'''-'''

      for i in range(lowerCamelCase ):
            for j in range(lowerCamelCase ):
                  if (i, j) == (0, n - 1):
                        print(grid[i][j]					,				end=''' ''' )
                        print('''<-- End position'''					,				end=''' ''' )
                  else:
                        print(grid[i][j]					,				end=''' ''' )
            print()
      print('''^''' )
      print('''Start position''' )
      print()
      print('''# is an obstacle''' )
      print('''- is the path taken by algorithm''' )
      print('''PATH TAKEN BY THE ALGORITHM IS:-''' )
      __A          =				back_pointer[goal]
      while x != start:
            print(lowerCamelCase					,				end=''' ''' )
            __A          =				back_pointer[x]
      print(lowerCamelCase )
      sys.exit()



def _a				(	lowerCamelCase:   TPos )	->						Optional[Any]:







      '''simple docstring'''






      if p[0] < 0 or p[0] > n - 1:
            return False
      if p[1] < 0 or p[1] > n - 1:
            return False
      return True



def _a				(	lowerCamelCase:   int					,				lowerCamelCase:   Optional[int]					,				lowerCamelCase:   Tuple					,				lowerCamelCase:   Tuple					,				lowerCamelCase:   Optional[int]					,				lowerCamelCase:   str					,				lowerCamelCase:   List[Any]					,				lowerCamelCase:   Dict					,				)	->						Dict:







      '''simple docstring'''






      for itera in range(lowerCamelCase ):
            open_list[itera].remove_element(lowerCamelCase )
      # print("s", s)
      # print("j", j)
      ((__A)   ,						(__A))          =				s
      __A          =				(x - 1, y)
      __A          =				(x + 1, y)
      __A          =				(x, y + 1)
      __A          =				(x, y - 1)

      for neighbours in [left, right, up, down]:
            if neighbours not in blocks:
                  if valid(lowerCamelCase ) and neighbours not in visited:
                        # print("neighbour", neighbours)
                        visited.add(lowerCamelCase )
                        __A          =				-1
                        __A          =				float('''inf''' )

                  if valid(lowerCamelCase ) and g_function[neighbours] > g_function[s] + 1:
                        __A          =				g_function[s] + 1
                        __A          =				s
                        if neighbours not in close_list_anchor:
                              open_list[0].put(lowerCamelCase					,				key(lowerCamelCase					,				0					,				lowerCamelCase					,				lowerCamelCase ) )
                              if neighbours not in close_list_inad:
                                    for var in range(1					,				lowerCamelCase ):
                                          if key(lowerCamelCase					,				lowerCamelCase					,				lowerCamelCase					,				lowerCamelCase ) <= Wa * key(
                                              lowerCamelCase					,				0					,				lowerCamelCase					,				lowerCamelCase ):
                                                open_list[j].put(
                                                    lowerCamelCase					,				key(lowerCamelCase					,				lowerCamelCase					,				lowerCamelCase					,				lowerCamelCase ) )



def _a				(	)	->						str:







      '''simple docstring'''






      __A          =				[]
      for x in range(1					,				5 ):
            for y in range(1					,				6 ):
                  some_list.append((x, y) )

      for x in range(15					,				20 ):
            some_list.append((x, 17) )

      for x in range(10					,				19 ):
            for y in range(1					,				15 ):
                  some_list.append((x, y) )

    # L block
      for x in range(1					,				4 ):
            for y in range(12					,				19 ):
                  some_list.append((x, y) )
      for x in range(3					,				13 ):
            for y in range(16					,				19 ):
                  some_list.append((x, y) )
      return some_list


snake_case__					:							Union[str, Any]													=     {0: consistent_heuristic, 1: heuristic_a, 2: heuristic_a}

snake_case__					:							List[str]													=     [
    (0, 1),
    (1, 1),
    (2, 1),
    (3, 1),
    (4, 1),
    (5, 1),
    (6, 1),
    (7, 1),
    (8, 1),
    (9, 1),
    (10, 1),
    (11, 1),
    (12, 1),
    (13, 1),
    (14, 1),
    (15, 1),
    (16, 1),
    (17, 1),
    (18, 1),
    (19, 1),
]
snake_case__					:							List[str]													=     make_common_ground()


snake_case__					:							int													=     blocks_blk
# hyper parameters
snake_case__					:							Optional[int]													=     1
snake_case__					:							List[Any]													=     1
snake_case__					:							int													=     20
snake_case__					:							Optional[int]													=     3  # one consistent and two other inconsistent

# start and end destination
snake_case__					:							Tuple													=     (0, 0)
snake_case__					:							Any													=     (n - 1, n - 1)

snake_case__					:							List[Any]													=     1



def _a				(	lowerCamelCase:   TPos					,				lowerCamelCase:   TPos					,				lowerCamelCase:   int )	->						Union[str, Any]:







      '''simple docstring'''






      __A          =				{start: 0, goal: float('''inf''' )}
      __A          =				{start: -1, goal: -1}
      __A          =				[]
      __A          =				set()

      for i in range(lowerCamelCase ):
            open_list.append(PriorityQueue() )
            open_list[i].put(lowerCamelCase					,				key(lowerCamelCase					,				lowerCamelCase					,				lowerCamelCase					,				lowerCamelCase ) )

      __A          =				[]
      __A          =				[]
      while open_list[0].minkey() < float('''inf''' ):
            for i in range(1					,				lowerCamelCase ):
                  # print(open_list[0].minkey(), open_list[i].minkey())
                  if open_list[i].minkey() <= Wa * open_list[0].minkey():
                        global t
                        t += 1
                        if g_function[goal] <= open_list[i].minkey():
                              if g_function[goal] < float('''inf''' ):
                                    do_something(lowerCamelCase					,				lowerCamelCase					,				lowerCamelCase )
                        else:
                              __A   ,						__A          =				open_list[i].top_show()
                              visited.add(lowerCamelCase )
                              expand_state(
                                  lowerCamelCase					,				lowerCamelCase					,				lowerCamelCase					,				lowerCamelCase					,				lowerCamelCase					,				lowerCamelCase					,				lowerCamelCase					,				lowerCamelCase					,				)
                              close_list_inad.append(lowerCamelCase )
                  else:
                        if g_function[goal] <= open_list[0].minkey():
                              if g_function[goal] < float('''inf''' ):
                                    do_something(lowerCamelCase					,				lowerCamelCase					,				lowerCamelCase )
                        else:
                              __A          =				open_list[0].top_show()
                              visited.add(lowerCamelCase )
                              expand_state(
                                  lowerCamelCase					,				0					,				lowerCamelCase					,				lowerCamelCase					,				lowerCamelCase					,				lowerCamelCase					,				lowerCamelCase					,				lowerCamelCase					,				)
                              close_list_anchor.append(lowerCamelCase )
      print('''No path found to goal''' )
      print()
      for i in range(n - 1					,				-1					,				-1 ):
            for j in range(lowerCamelCase ):
                  if (j, i) in blocks:
                        print('''#'''					,				end=''' ''' )
                  elif (j, i) in back_pointer:
                        if (j, i) == (n - 1, n - 1):
                              print('''*'''					,				end=''' ''' )
                        else:
                              print('''-'''					,				end=''' ''' )
                  else:
                        print('''*'''					,				end=''' ''' )
                  if (j, i) == (n - 1, n - 1):
                        print('''<-- End position'''					,				end=''' ''' )
            print()
      print('''^''' )
      print('''Start position''' )
      print()
      print('''# is an obstacle''' )
      print('''- is the path taken by algorithm''' )


if __name__ == "__main__":
       multi_a_star(start, goal, n_heuristic)





