
"""simple docstring"""







import unittest

from datasets import load_dataset

from transformers import BloomTokenizerFast
from transformers.testing_utils import require_tokenizers

from ...test_tokenization_common import TokenizerTesterMixin




@require_tokenizers
class 			A__	(     _lowerCamelCase	,					unittest.TestCase):
		A_						:	List[Any]           =     None
		A_						:	Optional[Any]           =     BloomTokenizerFast
		A_						:	List[Any]           =     BloomTokenizerFast
		A_						:	Tuple           =     True
		A_						:	Tuple           =     False
		A_						:	Optional[Any]           =     'tokenizer_file'
		A_						:	List[Any]           =     {'bos_token': '<s>', 'eos_token': '</s>', 'unk_token': '<unk>', 'pad_token': '<pad>'}

		def 							__lowerCamelCase							(				self			):
			super().setUp()
			__lowerCAmelCase      :						List[str]						      =				BloomTokenizerFast.from_pretrained('bigscience/tokenizer'			)
			tokenizer.save_pretrained(self.tmpdirname			)

		def 							__lowerCamelCase							(				self	,		**_SCREAMING_SNAKE_CASE			):
			kwargs.update(self.special_tokens_map			)
			return BloomTokenizerFast.from_pretrained(self.tmpdirname	,		**_SCREAMING_SNAKE_CASE			)

		def 							__lowerCamelCase							(				self			):
			__lowerCAmelCase      :						int						      =				self.get_rust_tokenizer()

			__lowerCAmelCase      :						List[Any]						      =				['The quick brown fox</s>', 'jumps over the lazy dog</s>']
			__lowerCAmelCase      :						str						      =				[[21_75, 2_37_14, 7_31_73, 14_42_52, 2], [77, 13_26_19, 34_78, 3_68, 10_95_86, 3_54_33, 2]]

			__lowerCAmelCase      :						Tuple						      =				tokenizer.batch_encode_plus(_SCREAMING_SNAKE_CASE			)['input_ids']
			self.assertListEqual(_SCREAMING_SNAKE_CASE	,		_SCREAMING_SNAKE_CASE			)

			__lowerCAmelCase      :						Optional[int]						      =				tokenizer.batch_decode(_SCREAMING_SNAKE_CASE			)
			self.assertListEqual(_SCREAMING_SNAKE_CASE	,		_SCREAMING_SNAKE_CASE			)

		def 							__lowerCamelCase							(				self	,		_SCREAMING_SNAKE_CASE=6			):
			for tokenizer, pretrained_name, kwargs in self.tokenizers_list:
				with self.subTest(f"{tokenizer.__class__.__name__} ({pretrained_name})"			):
					__lowerCAmelCase      :						Tuple						      =				self.rust_tokenizer_class.from_pretrained(_SCREAMING_SNAKE_CASE	,		**_SCREAMING_SNAKE_CASE			)
					# tokenizer_r.pad_token = None # Hotfixing padding = None
					# Simple input
					__lowerCAmelCase      :						List[str]						      =				'This is a simple input'
					__lowerCAmelCase      :						Optional[Any]						      =				['This is a simple input 1', 'This is a simple input 2']
					__lowerCAmelCase      :						Union[str, Any]						      =				('This is a simple input', 'This is a pair')
					__lowerCAmelCase      :						List[Any]						      =				[
					    ('This is a simple input 1', 'This is a simple input 2'),
					    ('This is a simple pair 1', 'This is a simple pair 2'),
					]

					# Simple input tests
					try:
						tokenizer_r.encode(_SCREAMING_SNAKE_CASE	,		max_length=_SCREAMING_SNAKE_CASE			)
						tokenizer_r.encode_plus(_SCREAMING_SNAKE_CASE	,		max_length=_SCREAMING_SNAKE_CASE			)

						tokenizer_r.batch_encode_plus(_SCREAMING_SNAKE_CASE	,		max_length=_SCREAMING_SNAKE_CASE			)
						tokenizer_r.encode(_SCREAMING_SNAKE_CASE	,		max_length=_SCREAMING_SNAKE_CASE			)
						tokenizer_r.batch_encode_plus(_SCREAMING_SNAKE_CASE	,		max_length=_SCREAMING_SNAKE_CASE			)
					except ValueError:
						self.fail('Bloom Tokenizer should be able to deal with padding'			)

					__lowerCAmelCase      :						Dict						      =				None  # Hotfixing padding = None
					self.assertRaises(_SCREAMING_SNAKE_CASE	,		tokenizer_r.encode	,		_SCREAMING_SNAKE_CASE	,		max_length=_SCREAMING_SNAKE_CASE	,		padding='max_length'			)

					# Simple input
					self.assertRaises(_SCREAMING_SNAKE_CASE	,		tokenizer_r.encode_plus	,		_SCREAMING_SNAKE_CASE	,		max_length=_SCREAMING_SNAKE_CASE	,		padding='max_length'			)

					# Simple input
					self.assertRaises(
					    _SCREAMING_SNAKE_CASE	,		tokenizer_r.batch_encode_plus	,		_SCREAMING_SNAKE_CASE	,		max_length=_SCREAMING_SNAKE_CASE	,		padding='max_length'	,		)

					# Pair input
					self.assertRaises(_SCREAMING_SNAKE_CASE	,		tokenizer_r.encode	,		_SCREAMING_SNAKE_CASE	,		max_length=_SCREAMING_SNAKE_CASE	,		padding='max_length'			)

					# Pair input
					self.assertRaises(_SCREAMING_SNAKE_CASE	,		tokenizer_r.encode_plus	,		_SCREAMING_SNAKE_CASE	,		max_length=_SCREAMING_SNAKE_CASE	,		padding='max_length'			)

					# Pair input
					self.assertRaises(
					    _SCREAMING_SNAKE_CASE	,		tokenizer_r.batch_encode_plus	,		_SCREAMING_SNAKE_CASE	,		max_length=_SCREAMING_SNAKE_CASE	,		padding='max_length'	,		)

		def 							__lowerCamelCase							(				self			):
			__lowerCAmelCase      :						str						      =				self.get_rust_tokenizer()
			__lowerCAmelCase      :						Dict						      =				load_dataset('xnli'	,		'all_languages'	,		split='test'	,		streaming=_SCREAMING_SNAKE_CASE			)

			__lowerCAmelCase      :						Any						      =				next(iter(_SCREAMING_SNAKE_CASE			)			)['premise']  # pick up one data
			__lowerCAmelCase      :						List[Any]						      =				list(sample_data.values()			)

			__lowerCAmelCase      :						Union[str, Any]						      =				list(map(tokenizer.encode	,		_SCREAMING_SNAKE_CASE			)			)
			__lowerCAmelCase      :						str						      =				[tokenizer.decode(_SCREAMING_SNAKE_CASE	,		clean_up_tokenization_spaces=_SCREAMING_SNAKE_CASE			) for x in output_tokens]
			self.assertListEqual(_SCREAMING_SNAKE_CASE	,		_SCREAMING_SNAKE_CASE			)







		def 							__lowerCamelCase							(				self			):
			# The test has to be overriden because BLOOM uses ALiBi positional embeddings that does not have
			# any sequence length constraints. This test of the parent class will fail since it relies on the
			# maximum sequence length of the positoonal embeddings.
			self.assertGreaterEqual(len(self.tokenizer_class.pretrained_vocab_files_map			)	,		1			)
			self.assertGreaterEqual(len(list(self.tokenizer_class.pretrained_vocab_files_map.values()			)[0]			)	,		1			)

"""simple docstring"""







import os
def    __lowerCAmelCase    (_UpperCamelCase = "input.txt"		):

	with open(os.path.join(os.path.dirname(_UpperCamelCase		)	,  _UpperCamelCase		)		) as input_file:
		__lowerCAmelCase      :						Optional[Any]						      =				[
		    [int(_UpperCamelCase		) for element in line.split(','		)]
		    for line in input_file.readlines()
		]

	__lowerCAmelCase      :						List[str]						      =				len(_UpperCamelCase		)
	__lowerCAmelCase      :						Tuple						      =				len(matrix[0]		)

	__lowerCAmelCase      :						int						      =				[[-1 for _ in range(_UpperCamelCase		)] for _ in range(_UpperCamelCase		)]
	for i in range(_UpperCamelCase		):
		__lowerCAmelCase      :						Any						      =				matrix[i][0]

	for j in range(1	,  _UpperCamelCase		):
		for i in range(_UpperCamelCase		):
			__lowerCAmelCase      :						Optional[Any]						      =				minimal_path_sums[i][j - 1] + matrix[i][j]

		for i in range(1	,  _UpperCamelCase		):
			__lowerCAmelCase      :						Optional[Any]						      =				min(
			    minimal_path_sums[i][j]	,  minimal_path_sums[i - 1][j] + matrix[i][j]		)

		for i in range(rows - 2	,  -1	,  -1		):
			__lowerCAmelCase      :						List[str]						      =				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() = }')