'''simple docstring'''




import json
import os
import unittest

from transformers import BatchEncoding, LEDTokenizer, LEDTokenizerFast
from transformers.models.led.tokenization_led import VOCAB_FILES_NAMES
from transformers.testing_utils import require_tokenizers, require_torch
from transformers.utils import cached_property

from ...test_tokenization_common import TokenizerTesterMixin





@require_tokenizers
class     __magic_name__						(    _UpperCAmelCase,     unittest.TestCase):
			UpperCamelCase__				=       LEDTokenizer
			UpperCamelCase__				=       LEDTokenizerFast
			UpperCamelCase__				=       True







			def 	SCREAMING_SNAKE_CASE_     (	self				:  Dict    ):
										super().setUp()
										lowercase_					:			str										=       [
										    """l""",
										    """o""",
										    """w""",
										    """e""",
										    """r""",
										    """s""",
										    """t""",
										    """i""",
										    """d""",
										    """n""",
										    """\u0120""",
										    """\u0120l""",
										    """\u0120n""",
										    """\u0120lo""",
										    """\u0120low""",
										    """er""",
										    """\u0120lowest""",
										    """\u0120newer""",
										    """\u0120wider""",
										    """<unk>""",
										]
										lowercase_					:			Tuple										=       dict(zip(lowercase_				,			range(len(lowercase_    )    )    )    )
										lowercase_					:			Dict										=       ["""#version: 0.2""", """\u0120 l""", """\u0120l o""", """\u0120lo w""", """e r""", """"""]
										lowercase_					:			List[str]										=       {"""unk_token""": """<unk>"""}

										lowercase_					:			Union[str, Any]										=       os.path.join(self.tmpdirname				,			VOCAB_FILES_NAMES["""vocab_file"""]    )
										lowercase_					:			Any										=       os.path.join(self.tmpdirname				,			VOCAB_FILES_NAMES["""merges_file"""]    )
										with open(self.vocab_file				,			"""w"""				,			encoding="""utf-8"""    ) as fp:
																	fp.write(json.dumps(lowercase_    ) + """\n"""    )
										with open(self.merges_file				,			"""w"""				,			encoding="""utf-8"""    ) as fp:
																	fp.write("""\n""".join(lowercase_    )    )







			def 	SCREAMING_SNAKE_CASE_     (	self				:  Dict				,			**lowercase_				:  str    ):
										kwargs.update(self.special_tokens_map    )
										return self.tokenizer_class.from_pretrained(self.tmpdirname				,			**lowercase_    )







			def 	SCREAMING_SNAKE_CASE_     (	self				:  List[Any]				,			**lowercase_				:  Tuple    ):
										kwargs.update(self.special_tokens_map    )
										return self.rust_tokenizer_class.from_pretrained(self.tmpdirname				,			**lowercase_    )







			def 	SCREAMING_SNAKE_CASE_     (	self				:  int				,			lowercase_				:  Optional[int]    ):
										return "lower newer", "lower newer"







			@cached_property
			def 	SCREAMING_SNAKE_CASE_     (	self				:  Any    ):
										return LEDTokenizer.from_pretrained("""allenai/led-base-16384"""    )







			@cached_property
			def 	SCREAMING_SNAKE_CASE_     (	self				:  Union[str, Any]    ):
										return LEDTokenizerFast.from_pretrained("""allenai/led-base-16384"""    )







			@require_torch
			def 	SCREAMING_SNAKE_CASE_     (	self				:  Optional[int]    ):
										lowercase_					:			Any										=       ["""A long paragraph for summarization.""", """Another paragraph for summarization."""]
										lowercase_					:			Any										=       [0, 250, 251, 17818, 13, 39186, 1938, 4, 2]

										for tokenizer in [self.default_tokenizer, self.default_tokenizer_fast]:
																	lowercase_					:			str										=       tokenizer(lowercase_				,			max_length=len(lowercase_    )				,			padding=lowercase_				,			return_tensors="""pt"""    )
																	self.assertIsInstance(lowercase_				,			lowercase_    )

																	self.assertEqual((2, 9)				,			batch.input_ids.shape    )
																	self.assertEqual((2, 9)				,			batch.attention_mask.shape    )
																	lowercase_					:			Union[str, Any]										=       batch.input_ids.tolist()[0]
																	self.assertListEqual(lowercase_				,			lowercase_    )







			@require_torch
			def 	SCREAMING_SNAKE_CASE_     (	self				:  Optional[int]    ):
										lowercase_					:			Tuple										=       ["""A long paragraph for summarization.""", """Another paragraph for summarization."""]
										for tokenizer in [self.default_tokenizer, self.default_tokenizer_fast]:
																	lowercase_					:			Union[str, Any]										=       tokenizer(lowercase_				,			padding=lowercase_				,			return_tensors="""pt"""    )
																	self.assertIn("""input_ids"""				,			lowercase_    )
																	self.assertIn("""attention_mask"""				,			lowercase_    )
																	self.assertNotIn("""labels"""				,			lowercase_    )
																	self.assertNotIn("""decoder_attention_mask"""				,			lowercase_    )







			@require_torch
			def 	SCREAMING_SNAKE_CASE_     (	self				:  List[Any]    ):
										lowercase_					:			int										=       [
										    """Summary of the text.""",
										    """Another summary.""",
										]
										for tokenizer in [self.default_tokenizer, self.default_tokenizer_fast]:
																	lowercase_					:			Optional[Any]										=       tokenizer(text_target=lowercase_				,			max_length=32				,			padding="""max_length"""				,			return_tensors="""pt"""    )
																	self.assertEqual(32				,			targets["""input_ids"""].shape[1]    )







			@require_torch
			def 	SCREAMING_SNAKE_CASE_     (	self				:  Union[str, Any]    ):
										for tokenizer in [self.default_tokenizer, self.default_tokenizer_fast]:
																	lowercase_					:			Dict										=       tokenizer(
																	    ["""I am a small frog""" * 1024, """I am a small frog"""]				,			padding=lowercase_				,			truncation=lowercase_				,			return_tensors="""pt"""    )
																	self.assertIsInstance(lowercase_				,			lowercase_    )
																	self.assertEqual(batch.input_ids.shape				,			(2, 5122)    )







			@require_torch
			def 	SCREAMING_SNAKE_CASE_     (	self				:  Dict    ):
										lowercase_					:			List[str]										=       ["""A long paragraph for summarization."""]
										lowercase_					:			Optional[Any]										=       [
										    """Summary of the text.""",
										]
										for tokenizer in [self.default_tokenizer, self.default_tokenizer_fast]:
																	lowercase_					:			str										=       tokenizer(lowercase_				,			return_tensors="""pt"""    )
																	lowercase_					:			Union[str, Any]										=       tokenizer(text_target=lowercase_				,			return_tensors="""pt"""    )
																	lowercase_					:			Tuple										=       inputs["""input_ids"""]
																	lowercase_					:			str										=       targets["""input_ids"""]
																	self.assertTrue((input_ids[:, 0] == tokenizer.bos_token_id).all().item()    )
																	self.assertTrue((labels[:, 0] == tokenizer.bos_token_id).all().item()    )
																	self.assertTrue((input_ids[:, -1] == tokenizer.eos_token_id).all().item()    )
																	self.assertTrue((labels[:, -1] == tokenizer.eos_token_id).all().item()    )







			@require_torch
			def 	SCREAMING_SNAKE_CASE_     (	self				:  Union[str, Any]    ):
										for tokenizer in [self.default_tokenizer, self.default_tokenizer_fast]:
																	lowercase_					:			Optional[Any]										=       ["""Summary of the text.""", """Another summary."""]
																	lowercase_					:			int										=       [[0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, -1, -1]]

																	lowercase_					:			List[str]										=       tokenizer(lowercase_				,			padding=lowercase_    )
																	lowercase_					:			Tuple										=       [[0] * len(lowercase_    ) for x in encoded_output["""input_ids"""]]
																	lowercase_					:			Tuple										=       tokenizer.pad(lowercase_    )
																	self.assertSequenceEqual(outputs["""global_attention_mask"""]				,			lowercase_    )







			def 	SCREAMING_SNAKE_CASE_     (	self				:  List[Any]    ):
										pass







			def 	SCREAMING_SNAKE_CASE_     (	self				:  List[str]    ):
										for tokenizer, pretrained_name, kwargs in self.tokenizers_list:
																	with self.subTest(f'''{tokenizer.__class__.__name__} ({pretrained_name})'''    ):
																								lowercase_					:			str										=       self.rust_tokenizer_class.from_pretrained(lowercase_				,			**lowercase_    )
																								lowercase_					:			Optional[Any]										=       self.tokenizer_class.from_pretrained(lowercase_				,			**lowercase_    )
																								lowercase_					:			Union[str, Any]										=       """A, <mask> AllenNLP sentence."""
																								lowercase_					:			Dict										=       tokenizer_r.encode_plus(lowercase_				,			add_special_tokens=lowercase_				,			return_token_type_ids=lowercase_    )
																								lowercase_					:			List[Any]										=       tokenizer_p.encode_plus(lowercase_				,			add_special_tokens=lowercase_				,			return_token_type_ids=lowercase_    )
																								self.assertEqual(sum(tokens_r["""token_type_ids"""]    )				,			sum(tokens_p["""token_type_ids"""]    )    )
																								self.assertEqual(
																								    sum(tokens_r["""attention_mask"""]    ) / len(tokens_r["""attention_mask"""]    )				,			sum(tokens_p["""attention_mask"""]    ) / len(tokens_p["""attention_mask"""]    )				,			)

																								lowercase_					:			Optional[Any]										=       tokenizer_r.convert_ids_to_tokens(tokens_r["""input_ids"""]    )
																								lowercase_					:			List[str]										=       tokenizer_p.convert_ids_to_tokens(tokens_p["""input_ids"""]    )
																								self.assertSequenceEqual(tokens_p["""input_ids"""]				,			[0, 250, 6, 50264, 3823, 487, 21992, 3645, 4, 2]    )
																								self.assertSequenceEqual(tokens_r["""input_ids"""]				,			[0, 250, 6, 50264, 3823, 487, 21992, 3645, 4, 2]    )

																								self.assertSequenceEqual(
																								    lowercase_				,			["""<s>""", """A""", """,""", """<mask>""", """ĠAllen""", """N""", """LP""", """Ġsentence""", """.""", """</s>"""]    )
																								self.assertSequenceEqual(
																								    lowercase_				,			["""<s>""", """A""", """,""", """<mask>""", """ĠAllen""", """N""", """LP""", """Ġsentence""", """.""", """</s>"""]    )






'''simple docstring'''




import operator as op




def 							lowerCamelCase	(      UpperCAmelCase__       :					Optional[Any] )			->      int:
							lowercase_					:			Optional[Any]										=       []
							lowercase_					:			str										=       lambda UpperCAmelCase__      ,      UpperCAmelCase__ : int(x / y )  # noqa: E731 integer division operation
							lowercase_					:			Optional[Any]										=       {
							    """^""": op.pow,
							    """*""": op.mul,
							    """/""": div,
							    """+""": op.add,
							    """-""": op.sub,
							}  # operators & their respective operation

							# print table header
							print("""Symbol""".center(8 )      ,      """Action""".center(12 )      ,      """Stack"""      ,      sep=""" | """ )
							print("""-""" * (30 + len(UpperCAmelCase__ )) )

							for x in post_fix:
														if x.isdigit():  # if x in digit
																					stack.append(UpperCAmelCase__ )  # append x to stack
																					# output in tabular format
																					print(x.rjust(8 )      ,      ("""push(""" + x + """)""").ljust(12 )      ,      """,""".join(UpperCAmelCase__ )      ,      sep=""" | """ )
														else:
																					lowercase_					:			str										=       stack.pop()  # pop stack
																					# output in tabular format
																					print("""""".rjust(8 )      ,      ("""pop(""" + b + """)""").ljust(12 )      ,      """,""".join(UpperCAmelCase__ )      ,      sep=""" | """ )

																					lowercase_					:			Optional[int]										=       stack.pop()  # pop stack
																					# output in tabular format
																					print("""""".rjust(8 )      ,      ("""pop(""" + a + """)""").ljust(12 )      ,      """,""".join(UpperCAmelCase__ )      ,      sep=""" | """ )

																					stack.append(
																					    str(opr[x](int(UpperCAmelCase__ )      ,      int(UpperCAmelCase__ ) ) ) )  # evaluate the 2 values popped from stack & push result to stack
																					# output in tabular format
																					print(
																					    x.rjust(8 )      ,      ("""push(""" + a + x + b + """)""").ljust(12 )      ,      """,""".join(UpperCAmelCase__ )      ,      sep=""" | """      ,      )

							return int(stack[0] )


if __name__ == "__main__":
						_lowercase						: Tuple						=						input("\n\nEnter a Postfix Equation (space separated) = ").split(" ")
						print("\n\tResult = ", solve(Postfix))





