'''simple docstring'''




import json
import os
import re
import shutil
import tempfile
import unittest
from typing import Tuple

from transformers import AddedToken, BatchEncoding, ByTaTokenizer
from transformers.utils import cached_property, is_tf_available, is_torch_available

from ...test_tokenization_common import TokenizerTesterMixin


if is_torch_available():
						_lowercase						: Union[str, Any]						=						"pt"
elif is_tf_available():
						_lowercase						: str						=						"tf"
else:
						_lowercase						: Any						=						"jax"





class     __magic_name__						(    _UpperCAmelCase,     unittest.TestCase):
			UpperCamelCase__				=       ByTaTokenizer
			UpperCamelCase__				=       False







			def 	SCREAMING_SNAKE_CASE_     (	self				:  Tuple    ):
										super().setUp()
										lowercase_					:			Tuple										=       ByTaTokenizer()
										tokenizer.save_pretrained(self.tmpdirname    )







			@cached_property
			def 	SCREAMING_SNAKE_CASE_     (	self				:  Tuple    ):
										return ByTaTokenizer.from_pretrained("""google/byt5-small"""    )







			def 	SCREAMING_SNAKE_CASE_     (	self				:  Dict				,			**lowercase_				:  Dict    ):
										return self.tokenizer_class.from_pretrained(self.tmpdirname				,			**lowercase_    )







			def 	SCREAMING_SNAKE_CASE_     (	self				:  Any				,			lowercase_				:  Optional[int]				,			lowercase_				:  List[str]=False				,			lowercase_				:  Optional[int]=20				,			lowercase_				:  List[str]=5    ):
										# XXX The default common tokenizer tests assume that every ID is decodable on its own.
										# This assumption is invalid for ByT5 because single bytes might not be
										# valid utf-8 (byte 128 for instance).
										# Here we're overriding the smallest possible method to provide
										# a clean sequence without making the same assumption.

										lowercase_					:			Optional[int]										=       []
										for i in range(len(lowercase_    )    ):
																	try:
																								lowercase_					:			Tuple										=       tokenizer.decode([i]				,			clean_up_tokenization_spaces=lowercase_    )
																	except UnicodeDecodeError:
																								pass
																	toks.append((i, tok)    )

										lowercase_					:			Tuple										=       list(filter(lambda lowercase_    : re.match(r"""^[ a-zA-Z]+$"""				,			t[1]    )				,			lowercase_    )    )
										lowercase_					:			Dict										=       list(filter(lambda lowercase_    : [t[0]] == tokenizer.encode(t[1]				,			add_special_tokens=lowercase_    )				,			lowercase_    )    )
										if max_length is not None and len(lowercase_    ) > max_length:
																	lowercase_					:			str										=       toks[:max_length]
										if min_length is not None and len(lowercase_    ) < min_length and len(lowercase_    ) > 0:
																	while len(lowercase_    ) < min_length:
																								lowercase_					:			Optional[Any]										=       toks + toks
        # toks_str = [t[1] for t in toks]
										lowercase_					:			Union[str, Any]										=       [t[0] for t in toks]

										# Ensure consistency
										lowercase_					:			Dict										=       tokenizer.decode(lowercase_				,			clean_up_tokenization_spaces=lowercase_    )
										if " " not in output_txt and len(lowercase_    ) > 1:
																	lowercase_					:			Dict										=       (
																	    tokenizer.decode([toks_ids[0]]				,			clean_up_tokenization_spaces=lowercase_    )
																	    + """ """
																	    + tokenizer.decode(toks_ids[1:]				,			clean_up_tokenization_spaces=lowercase_    )
																	)
										if with_prefix_space:
																	lowercase_					:			int										=       """ """ + output_txt
										lowercase_					:			List[str]										=       tokenizer.encode(lowercase_				,			add_special_tokens=lowercase_    )
										return output_txt, output_ids







			def 	SCREAMING_SNAKE_CASE_     (	self				:  Optional[int]    ):
										lowercase_					:			Dict										=       self.ta_base_tokenizer
										lowercase_					:			Any										=       tokenizer(["""hi</s>""", """I went to the gym</s>""", """</s>"""]    )
										lowercase_					:			Dict										=       tokenizer(["""hi""", """I went to the gym""", """"""]    )
										self.assertListEqual(batch_with_eos_added["""input_ids"""]				,			batch_without_eos_added["""input_ids"""]    )







			def 	SCREAMING_SNAKE_CASE_     (	self				:  List[str]    ):
										lowercase_					:			Optional[Any]										=       self.ta_base_tokenizer
										lowercase_					:			int										=       """Unicode €."""
										lowercase_					:			Any										=       tokenizer(lowercase_    )
										lowercase_					:			int										=       [88, 113, 108, 102, 114, 103, 104, 35, 229, 133, 175, 49, 1]
										self.assertEqual(encoded["""input_ids"""]				,			lowercase_    )

										# decoding
										lowercase_					:			Dict										=       tokenizer.decode(lowercase_    )
										self.assertEqual(lowercase_				,			"""Unicode €.</s>"""    )

										lowercase_					:			Any										=       tokenizer("""e è é ê ë"""    )
										lowercase_					:			List[str]										=       [104, 35, 198, 171, 35, 198, 172, 35, 198, 173, 35, 198, 174, 1]
										self.assertEqual(encoded["""input_ids"""]				,			lowercase_    )
										# decoding
										lowercase_					:			List[str]										=       tokenizer.decode(lowercase_    )
										self.assertEqual(lowercase_				,			"""e è é ê ë</s>"""    )

										# encode/decode, but with `encode` instead of `__call__`
										self.assertEqual(tokenizer.decode(tokenizer.encode("""e è é ê ë"""    )    )				,			"""e è é ê ë</s>"""    )







			def 	SCREAMING_SNAKE_CASE_     (	self				:  Any    ):
										lowercase_					:			Tuple										=       self.ta_base_tokenizer
										lowercase_					:			Any										=       ["""A long paragraph for summarization.""", """Another paragraph for summarization."""]
										# fmt: off
										lowercase_					:			List[Any]										=       [68, 35, 111, 114, 113, 106, 35, 115, 100, 117, 100, 106, 117, 100, 115, 107, 35, 105, 114, 117, 35, 118, 120, 112, 112, 100, 117, 108, 125, 100, 119, 108, 114, 113, 49, 1, 0]
										# fmt: on
										lowercase_					:			Dict										=       tokenizer(lowercase_				,			padding=lowercase_				,			return_tensors=lowercase_    )
										self.assertIsInstance(lowercase_				,			lowercase_    )

										if FRAMEWORK != "jax":
																	lowercase_					:			Optional[Any]										=       list(batch.input_ids.numpy()[0]    )
										else:
																	lowercase_					:			Optional[int]										=       list(batch.input_ids.tolist()[0]    )

										self.assertListEqual(lowercase_				,			lowercase_    )

										self.assertEqual((2, 37)				,			batch.input_ids.shape    )
										self.assertEqual((2, 37)				,			batch.attention_mask.shape    )







			def 	SCREAMING_SNAKE_CASE_     (	self				:  Optional[int]    ):
										lowercase_					:			Dict										=       self.ta_base_tokenizer
										lowercase_					:			Optional[Any]										=       ["""A long paragraph for summarization.""", """Another paragraph for summarization."""]
										lowercase_					:			Optional[int]										=       tokenizer(lowercase_				,			padding=lowercase_				,			return_tensors=lowercase_    )
										# check if input_ids are returned and no decoder_input_ids
										self.assertIn("""input_ids"""				,			lowercase_    )
										self.assertIn("""attention_mask"""				,			lowercase_    )
										self.assertNotIn("""decoder_input_ids"""				,			lowercase_    )
										self.assertNotIn("""decoder_attention_mask"""				,			lowercase_    )







			def 	SCREAMING_SNAKE_CASE_     (	self				:  Any    ):
										lowercase_					:			List[str]										=       self.ta_base_tokenizer
										lowercase_					:			Dict										=       [
										    """Summary of the text.""",
										    """Another summary.""",
										]
										lowercase_					:			int										=       tokenizer(
										    text_target=lowercase_				,			max_length=32				,			padding="""max_length"""				,			truncation=lowercase_				,			return_tensors=lowercase_    )
										self.assertEqual(32				,			targets["""input_ids"""].shape[1]    )







			def 	SCREAMING_SNAKE_CASE_     (	self				:  Optional[int]    ):
										lowercase_					:			str										=       self.ta_base_tokenizer
										lowercase_					:			Dict										=       ["""A long paragraph for summarization. </s>"""]
										lowercase_					:			int										=       ["""Summary of the text. </s>"""]
										# fmt: off
										lowercase_					:			Any										=       [68, 35, 111, 114, 113, 106, 35, 115, 100, 117, 100, 106, 117, 100, 115, 107, 35, 105, 114, 117, 35, 118, 120, 112, 112, 100, 117, 108, 125, 100, 119, 108, 114, 113, 49, 35, 1]
										lowercase_					:			List[Any]										=       [86, 120, 112, 112, 100, 117, 124, 35, 114, 105, 35, 119, 107, 104, 35, 119, 104, 123, 119, 49, 35, 1]
										# fmt: on

										lowercase_					:			Optional[int]										=       tokenizer(lowercase_				,			text_target=lowercase_    )

										self.assertEqual(lowercase_				,			batch["""input_ids"""][0]    )
										self.assertEqual(lowercase_				,			batch["""labels"""][0]    )







			def 	SCREAMING_SNAKE_CASE_     (	self				:  int    ):
										# safety check on max_len default value so we are sure the test works
										lowercase_					:			Dict										=       self.get_tokenizers()
										for tokenizer in tokenizers:
																	with self.subTest(f'''{tokenizer.__class__.__name__}'''    ):
																								self.assertNotEqual(tokenizer.model_max_length				,			42    )

        # Now let's start the test
										lowercase_					:			Any										=       self.get_tokenizers()
										for tokenizer in tokenizers:
																	with self.subTest(f'''{tokenizer.__class__.__name__}'''    ):
																								# Isolate this from the other tests because we save additional tokens/etc
																								lowercase_					:			str										=       tempfile.mkdtemp()

																								lowercase_					:			str										=       """ He is very happy, UNwant\u00E9d,running"""
																								lowercase_					:			Union[str, Any]										=       tokenizer.encode(lowercase_				,			add_special_tokens=lowercase_    )
																								tokenizer.save_pretrained(lowercase_    )

																								lowercase_					:			Optional[int]										=       tokenizer.__class__.from_pretrained(lowercase_    )
																								lowercase_					:			Any										=       after_tokenizer.encode(lowercase_				,			add_special_tokens=lowercase_    )
																								self.assertListEqual(lowercase_				,			lowercase_    )

																								shutil.rmtree(lowercase_    )

										lowercase_					:			List[str]										=       self.get_tokenizers(model_max_length=42    )
										for tokenizer in tokenizers:
																	with self.subTest(f'''{tokenizer.__class__.__name__}'''    ):
																								# Isolate this from the other tests because we save additional tokens/etc
																								lowercase_					:			str										=       tempfile.mkdtemp()

																								lowercase_					:			Dict										=       """ He is very happy, UNwant\u00E9d,running"""
																								tokenizer.add_tokens(["""bim""", """bambam"""]    )
																								lowercase_					:			Optional[Any]										=       tokenizer.additional_special_tokens
																								additional_special_tokens.append("""new_additional_special_token"""    )
																								tokenizer.add_special_tokens({"""additional_special_tokens""": additional_special_tokens}    )
																								lowercase_					:			Optional[Any]										=       tokenizer.encode(lowercase_				,			add_special_tokens=lowercase_    )
																								tokenizer.save_pretrained(lowercase_    )

																								lowercase_					:			List[Any]										=       tokenizer.__class__.from_pretrained(lowercase_    )
																								lowercase_					:			Any										=       after_tokenizer.encode(lowercase_				,			add_special_tokens=lowercase_    )
																								self.assertListEqual(lowercase_				,			lowercase_    )
																								self.assertIn("""new_additional_special_token"""				,			after_tokenizer.additional_special_tokens    )
																								self.assertEqual(after_tokenizer.model_max_length				,			42    )

																								lowercase_					:			Optional[Any]										=       tokenizer.__class__.from_pretrained(lowercase_				,			model_max_length=43    )
																								self.assertEqual(tokenizer.model_max_length				,			43    )

																								shutil.rmtree(lowercase_    )







			def 	SCREAMING_SNAKE_CASE_     (	self				:  Dict    ):
										lowercase_					:			str										=       []
										if self.test_slow_tokenizer:
																	tokenizer_list.append((self.tokenizer_class, self.get_tokenizer())    )

										if self.test_rust_tokenizer:
																	tokenizer_list.append((self.rust_tokenizer_class, self.get_rust_tokenizer())    )

										for tokenizer_class, tokenizer_utils in tokenizer_list:
																	with tempfile.TemporaryDirectory() as tmp_dir:
																								tokenizer_utils.save_pretrained(lowercase_    )

																								with open(os.path.join(lowercase_				,			"""special_tokens_map.json"""    )				,			encoding="""utf-8"""    ) as json_file:
																															lowercase_					:			List[str]										=       json.load(lowercase_    )

																								with open(os.path.join(lowercase_				,			"""tokenizer_config.json"""    )				,			encoding="""utf-8"""    ) as json_file:
																															lowercase_					:			List[Any]										=       json.load(lowercase_    )

																								lowercase_					:			Optional[Any]										=       [f'''<extra_id_{i}>''' for i in range(125    )]

																								lowercase_					:			Union[str, Any]										=       added_tokens_extra_ids + [
																								    """an_additional_special_token"""
																								]
																								lowercase_					:			List[Any]										=       added_tokens_extra_ids + [
																								    """an_additional_special_token"""
																								]

																								with open(os.path.join(lowercase_				,			"""special_tokens_map.json"""    )				,			"""w"""				,			encoding="""utf-8"""    ) as outfile:
																															json.dump(lowercase_				,			lowercase_    )
																								with open(os.path.join(lowercase_				,			"""tokenizer_config.json"""    )				,			"""w"""				,			encoding="""utf-8"""    ) as outfile:
																															json.dump(lowercase_				,			lowercase_    )

																								# the following checks allow us to verify that our test works as expected, i.e. that the tokenizer takes
																								# into account the new value of additional_special_tokens given in the "tokenizer_config.json" and
																								# "special_tokens_map.json" files
																								lowercase_					:			Optional[Any]										=       tokenizer_class.from_pretrained(
																								    lowercase_				,			)
																								self.assertIn(
																								    """an_additional_special_token"""				,			tokenizer_without_change_in_init.additional_special_tokens    )
																								# self.assertIn("an_additional_special_token",tokenizer_without_change_in_init.get_vocab()) # ByT5Tokenization no vocab
																								self.assertEqual(
																								    ["""an_additional_special_token"""]				,			tokenizer_without_change_in_init.convert_ids_to_tokens(
																								        tokenizer_without_change_in_init.convert_tokens_to_ids(["""an_additional_special_token"""]    )    )				,			)

																								# Now we test that we can change the value of additional_special_tokens in the from_pretrained
																								lowercase_					:			Optional[int]										=       added_tokens_extra_ids + [AddedToken("""a_new_additional_special_token"""				,			lstrip=lowercase_    )]
																								lowercase_					:			Optional[int]										=       tokenizer_class.from_pretrained(
																								    lowercase_				,			additional_special_tokens=lowercase_				,			)

																								self.assertIn("""a_new_additional_special_token"""				,			tokenizer.additional_special_tokens    )
																								self.assertEqual(
																								    ["""a_new_additional_special_token"""]				,			tokenizer.convert_ids_to_tokens(
																								        tokenizer.convert_tokens_to_ids(["""a_new_additional_special_token"""]    )    )				,			)







			def 	SCREAMING_SNAKE_CASE_     (	self				:  List[str]    ):
										lowercase_					:			Optional[int]										=       []
										if self.test_slow_tokenizer:
																	tokenizer_list.append((self.tokenizer_class, self.get_tokenizer())    )

										if self.test_rust_tokenizer:
																	tokenizer_list.append((self.rust_tokenizer_class, self.get_rust_tokenizer())    )

										for tokenizer_class, tokenizer_utils in tokenizer_list:
																	with tempfile.TemporaryDirectory() as tmp_dir:
																								tokenizer_utils.save_pretrained(lowercase_    )

																								lowercase_					:			int										=       tokenizer_class.from_pretrained(lowercase_    )

																								self.assertTrue(tokenizer.decode([255]    ) == """"""    )







			def 	SCREAMING_SNAKE_CASE_     (	self				:  Any    ):
										pass







			def 	SCREAMING_SNAKE_CASE_     (	self				:  Union[str, Any]    ):
										pass







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







			def 	SCREAMING_SNAKE_CASE_     (	self				:  Dict    ):
										pass







			def 	SCREAMING_SNAKE_CASE_     (	self				:  List[Any]    ):
										# The default common tokenizer tests uses invalid tokens for ByT5 that can only accept one-character strings
										# and special added tokens as tokens
										lowercase_					:			List[Any]										=       self.get_tokenizers(fast=lowercase_				,			do_lower_case=lowercase_    )
										for tokenizer in tokenizers:
																	with self.subTest(f'''{tokenizer.__class__.__name__}'''    ):
																								lowercase_					:			str										=       ["""t""", """h""", """i""", """s""", """ """, """i""", """s""", """ """, """a""", """ """, """t""", """e""", """x""", """t""", """</s>"""]
																								lowercase_					:			str										=       tokenizer.convert_tokens_to_string(lowercase_    )

																								self.assertIsInstance(lowercase_				,			lowercase_    )







			def 	SCREAMING_SNAKE_CASE_     (	self				:  int    ):
										lowercase_					:			List[str]										=       self.get_tokenizers()
										for tokenizer in tokenizers:
																	with self.subTest(f'''{tokenizer.__class__.__name__}'''    ):
																								lowercase_					:			Any										=       [
																								    """bos_token""",
																								    """eos_token""",
																								    """unk_token""",
																								    """sep_token""",
																								    """pad_token""",
																								    """cls_token""",
																								    """mask_token""",
																								]

																								lowercase_					:			Union[str, Any]										=       0
																								lowercase_					:			Any										=       tokenizer.convert_ids_to_tokens(
																								    lowercase_				,			skip_special_tokens=lowercase_    )

																								for attr in attributes_list:
																															setattr(lowercase_				,			attr + """_id"""				,			lowercase_    )
																															self.assertEqual(getattr(lowercase_				,			lowercase_    )				,			lowercase_    )
																															self.assertEqual(getattr(lowercase_				,			attr + """_id"""    )				,			lowercase_    )

																															setattr(lowercase_				,			attr + """_id"""				,			lowercase_    )
																															self.assertEqual(getattr(lowercase_				,			lowercase_    )				,			lowercase_    )
																															self.assertEqual(getattr(lowercase_				,			attr + """_id"""    )				,			lowercase_    )

																								setattr(lowercase_				,			"""additional_special_tokens_ids"""				,			[]    )
																								self.assertListEqual(getattr(lowercase_				,			"""additional_special_tokens"""    )				,			[]    )
																								self.assertListEqual(getattr(lowercase_				,			"""additional_special_tokens_ids"""    )				,			[]    )

																								setattr(lowercase_				,			"""additional_special_tokens_ids"""				,			[token_id_to_test_setters]    )
																								self.assertListEqual(getattr(lowercase_				,			"""additional_special_tokens"""    )				,			[token_to_test_setters]    )
																								self.assertListEqual(getattr(lowercase_				,			"""additional_special_tokens_ids"""    )				,			[token_id_to_test_setters]    )






'''simple docstring'''




import os




def 							lowerCamelCase	(      UpperCAmelCase__       :					str = "input.txt" )			->      int:

							with open(os.path.join(os.path.dirname(UpperCAmelCase__ )      ,      UpperCAmelCase__ ) ) as input_file:
														lowercase_					:			str										=       [
														    [int(UpperCAmelCase__ ) for element in line.split(""",""" )]
														    for line in input_file.readlines()
														]

							lowercase_					:			Optional[Any]										=       len(UpperCAmelCase__ )
							lowercase_					:			Any										=       len(matrix[0] )

							lowercase_					:			Union[str, Any]										=       [[-1 for _ in range(UpperCAmelCase__ )] for _ in range(UpperCAmelCase__ )]
							for i in range(UpperCAmelCase__ ):
														lowercase_					:			int										=       matrix[i][0]

							for j in range(1      ,      UpperCAmelCase__ ):
														for i in range(UpperCAmelCase__ ):
																					lowercase_					:			Union[str, Any]										=       minimal_path_sums[i][j - 1] + matrix[i][j]

														for i in range(1      ,      UpperCAmelCase__ ):
																					lowercase_					:			Tuple										=       min(
																					    minimal_path_sums[i][j]      ,      minimal_path_sums[i - 1][j] + matrix[i][j] )

														for i in range(rows - 2      ,      -1      ,      -1 ):
																					lowercase_					:			Dict										=       min(
																					    minimal_path_sums[i][j]      ,      minimal_path_sums[i + 1][j] + matrix[i][j] )

							return min(minimal_path_sums_row[-1] for minimal_path_sums_row in minimal_path_sums )


if __name__ == "__main__":
						print(f"""{solution() = }""")





