





import heapq
import sys

import numpy as np

UpperCamelCase__											= tuple[int, int]

class        __SCREAMING_SNAKE_CASE					:






							def __init__(						self  ):
														UpperCamelCase__				     =			[]
														UpperCamelCase__				     =			set()






							def 				_lowerCamelCase		(						self  ):
														if not self.empty():
																					return self.elements[0][0]
														else:
																					return float("""inf"""  )






							def 				_lowerCamelCase		(						self  ):
														return len(self.elements  ) == 0






							def 				_lowerCamelCase		(						self  , __lowerCAmelCase  , __lowerCAmelCase  ):
														if item not in self.set:
																					heapq.heappush(self.elements  , (priority, item)  )
																					self.set.add(__lowerCAmelCase  )
														else:
																					# update
																					# print("update", item)
																					UpperCamelCase__				     =			[]
																					((UpperCamelCase__)     ,     (UpperCamelCase__))				     =			heapq.heappop(self.elements  )
																					while x != item:
																												temp.append((pri, x)  )
																												((UpperCamelCase__)     ,     (UpperCamelCase__))				     =			heapq.heappop(self.elements  )
																					temp.append((priority, item)  )
																					for pro, xxx in temp:
																												heapq.heappush(self.elements  , (pro, xxx)  )






							def 				_lowerCamelCase		(						self  , __lowerCAmelCase  ):
														if item in self.set:
																					self.set.remove(__lowerCAmelCase  )
																					UpperCamelCase__				     =			[]
																					((UpperCamelCase__)     ,     (UpperCamelCase__))				     =			heapq.heappop(self.elements  )
																					while x != item:
																												temp.append((pro, x)  )
																												((UpperCamelCase__)     ,     (UpperCamelCase__))				     =			heapq.heappop(self.elements  )
																					for prito, yyy in temp:
																												heapq.heappush(self.elements  , (prito, yyy)  )






							def 				_lowerCamelCase		(						self  ):
														return self.elements[0][1]







							def 				_lowerCamelCase		(						self  ):
														((UpperCamelCase__)     ,     (UpperCamelCase__))				     =			heapq.heappop(self.elements  )
														self.set.remove(__lowerCAmelCase  )
														return (priority, item)






def     _UpperCamelCase     (a__   :TPos   ,			a__   :TPos       ):






							"""simple docstring"""





							UpperCamelCase__				     =			np.array(a__       )
							UpperCamelCase__				     =			np.array(a__       )
							return np.linalg.norm(a - b       )





def     _UpperCamelCase     (a__   :TPos   ,			a__   :TPos       ):






							"""simple docstring"""





							return consistent_heuristic(a__   ,			a__       ) // t





def     _UpperCamelCase     (a__   :TPos   ,			a__   :TPos       ):






							"""simple docstring"""





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





def     _UpperCamelCase     (a__   :TPos   ,			a__   :int   ,			a__   :TPos   ,			a__   :dict[TPos, float]       ):






							"""simple docstring"""





							UpperCamelCase__				     =			g_function[start] + Wa * heuristics[i](a__   ,			a__       )
							return ans





def     _UpperCamelCase     (a__   :Optional[Any]   ,			a__   :Union[str, Any]   ,			a__   :int       ):






							"""simple docstring"""





							UpperCamelCase__				     =			np.chararray((n, n)       )
							for i in range(a__       ):
														for j in range(a__       ):
																					UpperCamelCase__				     =			"""*"""

							for i in range(a__       ):
														for j in range(a__       ):
																					if (j, (n - 1) - i) in blocks:
																												UpperCamelCase__				     =			"""#"""

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

							for i in range(a__       ):
														for j in range(a__       ):
																					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:-"""       )
							UpperCamelCase__				     =			back_pointer[goal]
							while x != start:
														print(a__   ,			end=""" """       )
														UpperCamelCase__				     =			back_pointer[x]
							print(a__       )
							sys.exit()





def     _UpperCamelCase     (a__   :TPos       ):






							"""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     _UpperCamelCase     (a__   :List[Any]   ,			a__   :Tuple   ,			a__   :Union[str, Any]   ,			a__   :Any   ,			a__   :str   ,			a__   :Optional[Any]   ,			a__   :List[Any]   ,			a__   :List[str]   ,			):






							"""simple docstring"""





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

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

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





def     _UpperCamelCase     ():






							"""simple docstring"""





							UpperCamelCase__				     =			[]
							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


UpperCamelCase__											= {0: consistent_heuristic, 1: heuristic_a, 2: heuristic_a}

UpperCamelCase__											= [
    (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),
]
UpperCamelCase__											= make_common_ground()


UpperCamelCase__											= blocks_blk
# hyper parameters
UpperCamelCase__											= 1
UpperCamelCase__											= 1
UpperCamelCase__											= 20
UpperCamelCase__											= 3  # one consistent and two other inconsistent

# start and end destination
UpperCamelCase__											= (0, 0)
UpperCamelCase__											= (n - 1, n - 1)

UpperCamelCase__											= 1





def     _UpperCamelCase     (a__   :TPos   ,			a__   :TPos   ,			a__   :int       ):






							"""simple docstring"""





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

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

							UpperCamelCase__				     =			[]
							UpperCamelCase__				     =			[]
							while open_list[0].minkey() < float("""inf"""       ):
														for i in range(1   ,			a__       ):
																					# 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(a__   ,			a__   ,			a__       )
																												else:
																																			UpperCamelCase__     ,     UpperCamelCase__				     =			open_list[i].top_show()
																																			visited.add(a__       )
																																			expand_state(
																																			    a__   ,			a__   ,			a__   ,			a__   ,			a__   ,			a__   ,			a__   ,			a__   ,			)
																																			close_list_inad.append(a__       )
																					else:
																												if g_function[goal] <= open_list[0].minkey():
																																			if g_function[goal] < float("""inf"""       ):
																																										do_something(a__   ,			a__   ,			a__       )
																												else:
																																			UpperCamelCase__				     =			open_list[0].top_show()
																																			visited.add(a__       )
																																			expand_state(
																																			    a__   ,			0   ,			a__   ,			a__   ,			a__   ,			a__   ,			a__   ,			a__   ,			)
																																			close_list_anchor.append(a__       )
							print("""No path found to goal"""       )
							print()
							for i in range(n - 1   ,			-1   ,			-1       ):
														for j in range(a__       ):
																					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)











import gc
import unittest

from transformers import MODEL_FOR_MASKED_LM_MAPPING, TF_MODEL_FOR_MASKED_LM_MAPPING, FillMaskPipeline, pipeline
from transformers.pipelines import PipelineException
from transformers.testing_utils import (
    is_pipeline_test,
    is_torch_available,
    nested_simplify,
    require_tf,
    require_torch,
    require_torch_gpu,
    slow,
)

from .test_pipelines_common import ANY

@is_pipeline_test
class        __SCREAMING_SNAKE_CASE					(     unittest.TestCase       ):
							snake_case     :      Any						     =       MODEL_FOR_MASKED_LM_MAPPING
							snake_case     :      Dict						     =       TF_MODEL_FOR_MASKED_LM_MAPPING






							def 				_lowerCamelCase		(						self  ):
														super().tearDown()
														# clean-up as much as possible GPU memory occupied by PyTorch
														gc.collect()
														if is_torch_available():
																					import torch

																					torch.cuda.empty_cache()






							@require_tf
							def 				_lowerCamelCase		(						self  ):
														UpperCamelCase__				     =			pipeline(task="""fill-mask"""  , model="""sshleifer/tiny-distilroberta-base"""  , top_k=2  , framework="""tf"""  )
														UpperCamelCase__				     =			unmasker("""My name is <mask>"""  )
														self.assertEqual(
														    nested_simplify(__lowerCAmelCase  , decimals=6  )  , [
														        {"""sequence""": """My name is grouped""", """score""": 2.1E-05, """token""": 38015, """token_str""": """ grouped"""},
														        {"""sequence""": """My name is accuser""", """score""": 2.1E-05, """token""": 25506, """token_str""": """ accuser"""},
														    ]  , )

														UpperCamelCase__				     =			unmasker("""The largest city in France is <mask>"""  )
														self.assertEqual(
														    nested_simplify(__lowerCAmelCase  , decimals=6  )  , [
														        {
														            """sequence""": """The largest city in France is grouped""",
														            """score""": 2.1E-05,
														            """token""": 38015,
														            """token_str""": """ grouped""",
														        },
														        {
														            """sequence""": """The largest city in France is accuser""",
														            """score""": 2.1E-05,
														            """token""": 25506,
														            """token_str""": """ accuser""",
														        },
														    ]  , )

														UpperCamelCase__				     =			unmasker("""My name is <mask>"""  , targets=[""" Patrick""", """ Clara""", """ Teven"""]  , top_k=3  )
														self.assertEqual(
														    nested_simplify(__lowerCAmelCase  , decimals=6  )  , [
														        {"""sequence""": """My name is Clara""", """score""": 2E-05, """token""": 13606, """token_str""": """ Clara"""},
														        {"""sequence""": """My name is Patrick""", """score""": 2E-05, """token""": 3499, """token_str""": """ Patrick"""},
														        {"""sequence""": """My name is Te""", """score""": 1.9E-05, """token""": 2941, """token_str""": """ Te"""},
														    ]  , )






							@require_torch
							def 				_lowerCamelCase		(						self  ):
														UpperCamelCase__				     =			pipeline(task="""fill-mask"""  , model="""sshleifer/tiny-distilroberta-base"""  , top_k=2  , framework="""pt"""  )

														UpperCamelCase__				     =			unmasker("""My name is <mask>"""  )
														self.assertEqual(
														    nested_simplify(__lowerCAmelCase  , decimals=6  )  , [
														        {"""sequence""": """My name is Maul""", """score""": 2.2E-05, """token""": 35676, """token_str""": """ Maul"""},
														        {"""sequence""": """My name isELS""", """score""": 2.2E-05, """token""": 16416, """token_str""": """ELS"""},
														    ]  , )

														UpperCamelCase__				     =			unmasker("""The largest city in France is <mask>"""  )
														self.assertEqual(
														    nested_simplify(__lowerCAmelCase  , decimals=6  )  , [
														        {
														            """sequence""": """The largest city in France is Maul""",
														            """score""": 2.2E-05,
														            """token""": 35676,
														            """token_str""": """ Maul""",
														        },
														        {"""sequence""": """The largest city in France isELS""", """score""": 2.2E-05, """token""": 16416, """token_str""": """ELS"""},
														    ]  , )

														UpperCamelCase__				     =			unmasker("""My name is <mask>"""  , targets=[""" Patrick""", """ Clara""", """ Teven"""]  , top_k=3  )
														self.assertEqual(
														    nested_simplify(__lowerCAmelCase  , decimals=6  )  , [
														        {"""sequence""": """My name is Patrick""", """score""": 2.1E-05, """token""": 3499, """token_str""": """ Patrick"""},
														        {"""sequence""": """My name is Te""", """score""": 2E-05, """token""": 2941, """token_str""": """ Te"""},
														        {"""sequence""": """My name is Clara""", """score""": 2E-05, """token""": 13606, """token_str""": """ Clara"""},
														    ]  , )

														UpperCamelCase__				     =			unmasker("""My name is <mask> <mask>"""  , top_k=2  )

														self.assertEqual(
														    nested_simplify(__lowerCAmelCase  , decimals=6  )  , [
														        [
														            {
														                """score""": 2.2E-05,
														                """token""": 35676,
														                """token_str""": """ Maul""",
														                """sequence""": """<s>My name is Maul<mask></s>""",
														            },
														            {"""score""": 2.2E-05, """token""": 16416, """token_str""": """ELS""", """sequence""": """<s>My name isELS<mask></s>"""},
														        ],
														        [
														            {
														                """score""": 2.2E-05,
														                """token""": 35676,
														                """token_str""": """ Maul""",
														                """sequence""": """<s>My name is<mask> Maul</s>""",
														            },
														            {"""score""": 2.2E-05, """token""": 16416, """token_str""": """ELS""", """sequence""": """<s>My name is<mask>ELS</s>"""},
														        ],
														    ]  , )






							@require_torch_gpu
							def 				_lowerCamelCase		(						self  ):
														UpperCamelCase__				     =			pipeline("""fill-mask"""  , model="""hf-internal-testing/tiny-random-distilbert"""  , device=0  , framework="""pt"""  )

														# convert model to fp16
														pipe.model.half()

														UpperCamelCase__				     =			pipe("""Paris is the [MASK] of France."""  )
														# We actually don't care about the result, we just want to make sure
														# it works, meaning the float16 tensor got casted back to float32
														# for postprocessing.
														self.assertIsInstance(__lowerCAmelCase  , __lowerCAmelCase  )






							@slow
							@require_torch
							def 				_lowerCamelCase		(						self  ):
														UpperCamelCase__				     =			pipeline(task="""fill-mask"""  , model="""distilroberta-base"""  , top_k=2  , framework="""pt"""  )
														self.run_large_test(__lowerCAmelCase  )






							@slow
							@require_tf
							def 				_lowerCamelCase		(						self  ):
														UpperCamelCase__				     =			pipeline(task="""fill-mask"""  , model="""distilroberta-base"""  , top_k=2  , framework="""tf"""  )
														self.run_large_test(__lowerCAmelCase  )






							def 				_lowerCamelCase		(						self  , __lowerCAmelCase  ):
														UpperCamelCase__				     =			unmasker("""My name is <mask>"""  )
														self.assertEqual(
														    nested_simplify(__lowerCAmelCase  )  , [
														        {"""sequence""": """My name is John""", """score""": 0.008, """token""": 610, """token_str""": """ John"""},
														        {"""sequence""": """My name is Chris""", """score""": 0.007, """token""": 1573, """token_str""": """ Chris"""},
														    ]  , )
														UpperCamelCase__				     =			unmasker("""The largest city in France is <mask>"""  )
														self.assertEqual(
														    nested_simplify(__lowerCAmelCase  )  , [
														        {
														            """sequence""": """The largest city in France is Paris""",
														            """score""": 0.251,
														            """token""": 2201,
														            """token_str""": """ Paris""",
														        },
														        {
														            """sequence""": """The largest city in France is Lyon""",
														            """score""": 0.214,
														            """token""": 12790,
														            """token_str""": """ Lyon""",
														        },
														    ]  , )

														UpperCamelCase__				     =			unmasker("""My name is <mask>"""  , targets=[""" Patrick""", """ Clara""", """ Teven"""]  , top_k=3  )
														self.assertEqual(
														    nested_simplify(__lowerCAmelCase  )  , [
														        {"""sequence""": """My name is Patrick""", """score""": 0.005, """token""": 3499, """token_str""": """ Patrick"""},
														        {"""sequence""": """My name is Clara""", """score""": 0.000, """token""": 13606, """token_str""": """ Clara"""},
														        {"""sequence""": """My name is Te""", """score""": 0.000, """token""": 2941, """token_str""": """ Te"""},
														    ]  , )






							@require_torch
							def 				_lowerCamelCase		(						self  ):
														UpperCamelCase__				     =			pipeline(task="""fill-mask"""  , model="""sshleifer/tiny-distilroberta-base"""  , framework="""pt"""  )
														UpperCamelCase__				     =			None
														UpperCamelCase__				     =			None
														self.run_pipeline_test(__lowerCAmelCase  , []  )






							@require_tf
							def 				_lowerCamelCase		(						self  ):
														UpperCamelCase__				     =			pipeline(task="""fill-mask"""  , model="""sshleifer/tiny-distilroberta-base"""  , framework="""tf"""  )
														UpperCamelCase__				     =			None
														UpperCamelCase__				     =			None
														self.run_pipeline_test(__lowerCAmelCase  , []  )






							def 				_lowerCamelCase		(						self  , __lowerCAmelCase  , __lowerCAmelCase  , __lowerCAmelCase  ):
														if tokenizer is None or tokenizer.mask_token_id is None:
																					self.skipTest("""The provided tokenizer has no mask token, (probably reformer or wav2vec2)"""  )

														UpperCamelCase__				     =			FillMaskPipeline(model=__lowerCAmelCase  , tokenizer=__lowerCAmelCase  )
														UpperCamelCase__				     =			[
														    f"""This is another {tokenizer.mask_token} test""",
														]
														return fill_masker, examples






							def 				_lowerCamelCase		(						self  , __lowerCAmelCase  , __lowerCAmelCase  ):
														UpperCamelCase__				     =			fill_masker.tokenizer
														UpperCamelCase__				     =			fill_masker.model

														UpperCamelCase__				     =			fill_masker(
														    f"""This is a {tokenizer.mask_token}"""  , )
														self.assertEqual(
														    __lowerCAmelCase  , [
														        {"""sequence""": ANY(__lowerCAmelCase  ), """score""": ANY(__lowerCAmelCase  ), """token""": ANY(__lowerCAmelCase  ), """token_str""": ANY(__lowerCAmelCase  )},
														        {"""sequence""": ANY(__lowerCAmelCase  ), """score""": ANY(__lowerCAmelCase  ), """token""": ANY(__lowerCAmelCase  ), """token_str""": ANY(__lowerCAmelCase  )},
														        {"""sequence""": ANY(__lowerCAmelCase  ), """score""": ANY(__lowerCAmelCase  ), """token""": ANY(__lowerCAmelCase  ), """token_str""": ANY(__lowerCAmelCase  )},
														        {"""sequence""": ANY(__lowerCAmelCase  ), """score""": ANY(__lowerCAmelCase  ), """token""": ANY(__lowerCAmelCase  ), """token_str""": ANY(__lowerCAmelCase  )},
														        {"""sequence""": ANY(__lowerCAmelCase  ), """score""": ANY(__lowerCAmelCase  ), """token""": ANY(__lowerCAmelCase  ), """token_str""": ANY(__lowerCAmelCase  )},
														    ]  , )

														UpperCamelCase__				     =			fill_masker([f"""This is a {tokenizer.mask_token}"""]  )
														self.assertEqual(
														    __lowerCAmelCase  , [
														        {"""sequence""": ANY(__lowerCAmelCase  ), """score""": ANY(__lowerCAmelCase  ), """token""": ANY(__lowerCAmelCase  ), """token_str""": ANY(__lowerCAmelCase  )},
														        {"""sequence""": ANY(__lowerCAmelCase  ), """score""": ANY(__lowerCAmelCase  ), """token""": ANY(__lowerCAmelCase  ), """token_str""": ANY(__lowerCAmelCase  )},
														        {"""sequence""": ANY(__lowerCAmelCase  ), """score""": ANY(__lowerCAmelCase  ), """token""": ANY(__lowerCAmelCase  ), """token_str""": ANY(__lowerCAmelCase  )},
														        {"""sequence""": ANY(__lowerCAmelCase  ), """score""": ANY(__lowerCAmelCase  ), """token""": ANY(__lowerCAmelCase  ), """token_str""": ANY(__lowerCAmelCase  )},
														        {"""sequence""": ANY(__lowerCAmelCase  ), """score""": ANY(__lowerCAmelCase  ), """token""": ANY(__lowerCAmelCase  ), """token_str""": ANY(__lowerCAmelCase  )},
														    ]  , )

														UpperCamelCase__				     =			fill_masker([f"""This is a {tokenizer.mask_token}""", f"""Another {tokenizer.mask_token} great test."""]  )
														self.assertEqual(
														    __lowerCAmelCase  , [
														        [
														            {"""sequence""": ANY(__lowerCAmelCase  ), """score""": ANY(__lowerCAmelCase  ), """token""": ANY(__lowerCAmelCase  ), """token_str""": ANY(__lowerCAmelCase  )},
														            {"""sequence""": ANY(__lowerCAmelCase  ), """score""": ANY(__lowerCAmelCase  ), """token""": ANY(__lowerCAmelCase  ), """token_str""": ANY(__lowerCAmelCase  )},
														            {"""sequence""": ANY(__lowerCAmelCase  ), """score""": ANY(__lowerCAmelCase  ), """token""": ANY(__lowerCAmelCase  ), """token_str""": ANY(__lowerCAmelCase  )},
														            {"""sequence""": ANY(__lowerCAmelCase  ), """score""": ANY(__lowerCAmelCase  ), """token""": ANY(__lowerCAmelCase  ), """token_str""": ANY(__lowerCAmelCase  )},
														            {"""sequence""": ANY(__lowerCAmelCase  ), """score""": ANY(__lowerCAmelCase  ), """token""": ANY(__lowerCAmelCase  ), """token_str""": ANY(__lowerCAmelCase  )},
														        ],
														        [
														            {"""sequence""": ANY(__lowerCAmelCase  ), """score""": ANY(__lowerCAmelCase  ), """token""": ANY(__lowerCAmelCase  ), """token_str""": ANY(__lowerCAmelCase  )},
														            {"""sequence""": ANY(__lowerCAmelCase  ), """score""": ANY(__lowerCAmelCase  ), """token""": ANY(__lowerCAmelCase  ), """token_str""": ANY(__lowerCAmelCase  )},
														            {"""sequence""": ANY(__lowerCAmelCase  ), """score""": ANY(__lowerCAmelCase  ), """token""": ANY(__lowerCAmelCase  ), """token_str""": ANY(__lowerCAmelCase  )},
														            {"""sequence""": ANY(__lowerCAmelCase  ), """score""": ANY(__lowerCAmelCase  ), """token""": ANY(__lowerCAmelCase  ), """token_str""": ANY(__lowerCAmelCase  )},
														            {"""sequence""": ANY(__lowerCAmelCase  ), """score""": ANY(__lowerCAmelCase  ), """token""": ANY(__lowerCAmelCase  ), """token_str""": ANY(__lowerCAmelCase  )},
														        ],
														    ]  , )

														with self.assertRaises(__lowerCAmelCase  ):
																					fill_masker([None]  )
														# No mask_token is not supported
														with self.assertRaises(__lowerCAmelCase  ):
																					fill_masker("""This is"""  )

														self.run_test_top_k(__lowerCAmelCase  , __lowerCAmelCase  )
														self.run_test_targets(__lowerCAmelCase  , __lowerCAmelCase  )
														self.run_test_top_k_targets(__lowerCAmelCase  , __lowerCAmelCase  )
														self.fill_mask_with_duplicate_targets_and_top_k(__lowerCAmelCase  , __lowerCAmelCase  )
														self.fill_mask_with_multiple_masks(__lowerCAmelCase  , __lowerCAmelCase  )






							def 				_lowerCamelCase		(						self  , __lowerCAmelCase  , __lowerCAmelCase  ):
														UpperCamelCase__				     =			tokenizer.get_vocab()
														UpperCamelCase__				     =			sorted(vocab.keys()  )[:2]
														# Pipeline argument
														UpperCamelCase__				     =			FillMaskPipeline(model=__lowerCAmelCase  , tokenizer=__lowerCAmelCase  , targets=__lowerCAmelCase  )
														UpperCamelCase__				     =			fill_masker(f"""This is a {tokenizer.mask_token}"""  )
														self.assertEqual(
														    __lowerCAmelCase  , [
														        {"""sequence""": ANY(__lowerCAmelCase  ), """score""": ANY(__lowerCAmelCase  ), """token""": ANY(__lowerCAmelCase  ), """token_str""": ANY(__lowerCAmelCase  )},
														        {"""sequence""": ANY(__lowerCAmelCase  ), """score""": ANY(__lowerCAmelCase  ), """token""": ANY(__lowerCAmelCase  ), """token_str""": ANY(__lowerCAmelCase  )},
														    ]  , )
														UpperCamelCase__				     =			{vocab[el] for el in targets}
														self.assertEqual({el["""token"""] for el in outputs}  , __lowerCAmelCase  )
														UpperCamelCase__				     =			[tokenizer.decode([x]  ) for x in target_ids]
														self.assertEqual({el["""token_str"""] for el in outputs}  , set(__lowerCAmelCase  )  )

														# Call argument
														UpperCamelCase__				     =			FillMaskPipeline(model=__lowerCAmelCase  , tokenizer=__lowerCAmelCase  )
														UpperCamelCase__				     =			fill_masker(f"""This is a {tokenizer.mask_token}"""  , targets=__lowerCAmelCase  )
														self.assertEqual(
														    __lowerCAmelCase  , [
														        {"""sequence""": ANY(__lowerCAmelCase  ), """score""": ANY(__lowerCAmelCase  ), """token""": ANY(__lowerCAmelCase  ), """token_str""": ANY(__lowerCAmelCase  )},
														        {"""sequence""": ANY(__lowerCAmelCase  ), """score""": ANY(__lowerCAmelCase  ), """token""": ANY(__lowerCAmelCase  ), """token_str""": ANY(__lowerCAmelCase  )},
														    ]  , )
														UpperCamelCase__				     =			{vocab[el] for el in targets}
														self.assertEqual({el["""token"""] for el in outputs}  , __lowerCAmelCase  )
														UpperCamelCase__				     =			[tokenizer.decode([x]  ) for x in target_ids]
														self.assertEqual({el["""token_str"""] for el in outputs}  , set(__lowerCAmelCase  )  )

														# Score equivalence
														UpperCamelCase__				     =			fill_masker(f"""This is a {tokenizer.mask_token}"""  , targets=__lowerCAmelCase  )
														UpperCamelCase__				     =			[top_mask["""token_str"""] for top_mask in outputs]
														UpperCamelCase__				     =			[top_mask["""score"""] for top_mask in outputs]

														# For some BPE tokenizers, `</w>` is removed during decoding, so `token_str` won't be the same as in `targets`.
														if set(__lowerCAmelCase  ) == set(__lowerCAmelCase  ):
																					UpperCamelCase__				     =			fill_masker(f"""This is a {tokenizer.mask_token}"""  , targets=__lowerCAmelCase  )
																					UpperCamelCase__				     =			[top_mask["""score"""] for top_mask in unmasked_targets]
																					self.assertEqual(nested_simplify(__lowerCAmelCase  )  , nested_simplify(__lowerCAmelCase  )  )

														# Raises with invalid
														with self.assertRaises(__lowerCAmelCase  ):
																					UpperCamelCase__				     =			fill_masker(f"""This is a {tokenizer.mask_token}"""  , targets=[]  )
														# For some tokenizers, `""` is actually in the vocabulary and the expected error won't raised
														if "" not in tokenizer.get_vocab():
																					with self.assertRaises(__lowerCAmelCase  ):
																												UpperCamelCase__				     =			fill_masker(f"""This is a {tokenizer.mask_token}"""  , targets=[""""""]  )
																					with self.assertRaises(__lowerCAmelCase  ):
																												UpperCamelCase__				     =			fill_masker(f"""This is a {tokenizer.mask_token}"""  , targets=""""""  )






							def 				_lowerCamelCase		(						self  , __lowerCAmelCase  , __lowerCAmelCase  ):
														UpperCamelCase__				     =			FillMaskPipeline(model=__lowerCAmelCase  , tokenizer=__lowerCAmelCase  , top_k=2  )
														UpperCamelCase__				     =			fill_masker(f"""This is a {tokenizer.mask_token}"""  )
														self.assertEqual(
														    __lowerCAmelCase  , [
														        {"""sequence""": ANY(__lowerCAmelCase  ), """score""": ANY(__lowerCAmelCase  ), """token""": ANY(__lowerCAmelCase  ), """token_str""": ANY(__lowerCAmelCase  )},
														        {"""sequence""": ANY(__lowerCAmelCase  ), """score""": ANY(__lowerCAmelCase  ), """token""": ANY(__lowerCAmelCase  ), """token_str""": ANY(__lowerCAmelCase  )},
														    ]  , )

														UpperCamelCase__				     =			FillMaskPipeline(model=__lowerCAmelCase  , tokenizer=__lowerCAmelCase  )
														UpperCamelCase__				     =			fill_masker(f"""This is a {tokenizer.mask_token}"""  , top_k=2  )
														self.assertEqual(
														    __lowerCAmelCase  , [
														        {"""sequence""": ANY(__lowerCAmelCase  ), """score""": ANY(__lowerCAmelCase  ), """token""": ANY(__lowerCAmelCase  ), """token_str""": ANY(__lowerCAmelCase  )},
														        {"""sequence""": ANY(__lowerCAmelCase  ), """score""": ANY(__lowerCAmelCase  ), """token""": ANY(__lowerCAmelCase  ), """token_str""": ANY(__lowerCAmelCase  )},
														    ]  , )
														self.assertEqual(nested_simplify(__lowerCAmelCase  )  , nested_simplify(__lowerCAmelCase  )  )






							def 				_lowerCamelCase		(						self  , __lowerCAmelCase  , __lowerCAmelCase  ):
														UpperCamelCase__				     =			tokenizer.get_vocab()
														UpperCamelCase__				     =			FillMaskPipeline(model=__lowerCAmelCase  , tokenizer=__lowerCAmelCase  )

														# top_k=2, ntargets=3
														UpperCamelCase__				     =			sorted(vocab.keys()  )[:3]
														UpperCamelCase__				     =			fill_masker(f"""This is a {tokenizer.mask_token}"""  , top_k=2  , targets=__lowerCAmelCase  )

														# If we use the most probably targets, and filter differently, we should still
														# have the same results
														UpperCamelCase__				     =			[el["""token_str"""] for el in sorted(__lowerCAmelCase  , key=lambda __lowerCAmelCase  : x["score"]  , reverse=__lowerCAmelCase  )]
														# For some BPE tokenizers, `</w>` is removed during decoding, so `token_str` won't be the same as in `targets`.
														if set(__lowerCAmelCase  ).issubset(__lowerCAmelCase  ):
																					UpperCamelCase__				     =			fill_masker(f"""This is a {tokenizer.mask_token}"""  , top_k=3  , targets=__lowerCAmelCase  )
																					# They should yield exactly the same result
																					self.assertEqual(nested_simplify(__lowerCAmelCase  )  , nested_simplify(__lowerCAmelCase  )  )






							def 				_lowerCamelCase		(						self  , __lowerCAmelCase  , __lowerCAmelCase  ):
														UpperCamelCase__				     =			FillMaskPipeline(model=__lowerCAmelCase  , tokenizer=__lowerCAmelCase  )
														UpperCamelCase__				     =			tokenizer.get_vocab()
														# String duplicates + id duplicates
														UpperCamelCase__				     =			sorted(vocab.keys()  )[:3]
														UpperCamelCase__				     =			[targets[0], targets[1], targets[0], targets[2], targets[1]]
														UpperCamelCase__				     =			fill_masker(f"""My name is {tokenizer.mask_token}"""  , targets=__lowerCAmelCase  , top_k=10  )

														# The target list contains duplicates, so we can't output more
														# than them
														self.assertEqual(len(__lowerCAmelCase  )  , 3  )







							def 				_lowerCamelCase		(						self  , __lowerCAmelCase  , __lowerCAmelCase  ):
														UpperCamelCase__				     =			FillMaskPipeline(model=__lowerCAmelCase  , tokenizer=__lowerCAmelCase  )

														UpperCamelCase__				     =			fill_masker(
														    f"""This is a {tokenizer.mask_token} {tokenizer.mask_token} {tokenizer.mask_token}"""  , top_k=2  )
														self.assertEqual(
														    __lowerCAmelCase  , [
														        [
														            {"""sequence""": ANY(__lowerCAmelCase  ), """score""": ANY(__lowerCAmelCase  ), """token""": ANY(__lowerCAmelCase  ), """token_str""": ANY(__lowerCAmelCase  )},
														            {"""sequence""": ANY(__lowerCAmelCase  ), """score""": ANY(__lowerCAmelCase  ), """token""": ANY(__lowerCAmelCase  ), """token_str""": ANY(__lowerCAmelCase  )},
														        ],
														        [
														            {"""sequence""": ANY(__lowerCAmelCase  ), """score""": ANY(__lowerCAmelCase  ), """token""": ANY(__lowerCAmelCase  ), """token_str""": ANY(__lowerCAmelCase  )},
														            {"""sequence""": ANY(__lowerCAmelCase  ), """score""": ANY(__lowerCAmelCase  ), """token""": ANY(__lowerCAmelCase  ), """token_str""": ANY(__lowerCAmelCase  )},
														        ],
														        [
														            {"""sequence""": ANY(__lowerCAmelCase  ), """score""": ANY(__lowerCAmelCase  ), """token""": ANY(__lowerCAmelCase  ), """token_str""": ANY(__lowerCAmelCase  )},
														            {"""sequence""": ANY(__lowerCAmelCase  ), """score""": ANY(__lowerCAmelCase  ), """token""": ANY(__lowerCAmelCase  ), """token_str""": ANY(__lowerCAmelCase  )},
														        ],
														    ]  , )




