





"""simple docstring"""





def    a__       (       _SCREAMING_SNAKE_CASE	,						_SCREAMING_SNAKE_CASE	,						_SCREAMING_SNAKE_CASE	,						_SCREAMING_SNAKE_CASE	,						_SCREAMING_SNAKE_CASE	,						_SCREAMING_SNAKE_CASE	,						):




		"""simple docstring"""


		UpperCamelCase =						list(_SCREAMING_SNAKE_CASE     )
		UpperCamelCase =						list(_SCREAMING_SNAKE_CASE     )
		UpperCamelCase =						len(_SCREAMING_SNAKE_CASE     )
		UpperCamelCase =						len(_SCREAMING_SNAKE_CASE     )

		UpperCamelCase =						[
		    [0 for _ in range(len_destination_seq + 1     )] for _ in range(len_source_seq + 1     )
		]
		UpperCamelCase =						[
		    ["0" for _ in range(len_destination_seq + 1     )] for _ in range(len_source_seq + 1     )
		]

		for i in range(1	,						len_source_seq + 1     ):
				UpperCamelCase =						i * delete_cost
				UpperCamelCase =						F"D{source_seq[i - 1]:c}"

		for i in range(1	,						len_destination_seq + 1     ):
				UpperCamelCase =						i * insert_cost
				UpperCamelCase =						F"I{destination_seq[i - 1]:c}"

		for i in range(1	,						len_source_seq + 1     ):
				for j in range(1	,						len_destination_seq + 1     ):
						if source_seq[i - 1] == destination_seq[j - 1]:
								UpperCamelCase =						costs[i - 1][j - 1] + copy_cost
								UpperCamelCase =						F"C{source_seq[i - 1]:c}"
						else:
								UpperCamelCase =						costs[i - 1][j - 1] + replace_cost
								UpperCamelCase =						F"R{source_seq[i - 1]:c}" + str(destination_seq[j - 1]     )

						if costs[i - 1][j] + delete_cost < costs[i][j]:
								UpperCamelCase =						costs[i - 1][j] + delete_cost
								UpperCamelCase =						F"D{source_seq[i - 1]:c}"

						if costs[i][j - 1] + insert_cost < costs[i][j]:
								UpperCamelCase =						costs[i][j - 1] + insert_cost
								UpperCamelCase =						F"I{destination_seq[j - 1]:c}"

		return costs, ops


def    a__       (       _SCREAMING_SNAKE_CASE	,						_SCREAMING_SNAKE_CASE	,						_SCREAMING_SNAKE_CASE     ):




		"""simple docstring"""


		if i == 0 and j == 0:
				return []
		else:
				if ops[i][j][0] == "C" or ops[i][j][0] == "R":
						UpperCamelCase =						assemble_transformation(_SCREAMING_SNAKE_CASE	,						i - 1	,						j - 1     )
						seq.append(ops[i][j]     )
						return seq
				elif ops[i][j][0] == "D":
						UpperCamelCase =						assemble_transformation(_SCREAMING_SNAKE_CASE	,						i - 1	,						_SCREAMING_SNAKE_CASE     )
						seq.append(ops[i][j]     )
						return seq
				else:
						UpperCamelCase =						assemble_transformation(_SCREAMING_SNAKE_CASE	,						_SCREAMING_SNAKE_CASE	,						j - 1     )
						seq.append(ops[i][j]     )
						return seq


if __name__ == "__main__":
						lowerCAmelCase__      ,  lowerCAmelCase__        =      compute_transform_tables('''Python''', '''Algorithms''', -1, 1, 2, 2)

						lowerCAmelCase__        =      len(operations)
						lowerCAmelCase__        =      len(operations[0])
						lowerCAmelCase__        =      assemble_transformation(operations, m - 1, n - 1)

						lowerCAmelCase__        =      list('''Python''')
						lowerCAmelCase__        =      0
						lowerCAmelCase__        =      0

						with open('''min_cost.txt''', '''w''') as file:
												for op in sequence:
																		print(''''''.join(string))

																		if op[0] == "C":
																								file.write('''%-16s''' % '''Copy %c''' % op[1])
																								file.write('''\t\t\t''' + ''''''.join(string))
																								file.write('''\r\n''')

																								cost -= 1
																		elif op[0] == "R":
																								lowerCAmelCase__        =      op[2]

																								file.write('''%-16s''' % ('''Replace %c''' % op[1] + ''' with ''' + str(op[2])))
																								file.write('''\t\t''' + ''''''.join(string))
																								file.write('''\r\n''')

																								cost += 1
																		elif op[0] == "D":
																								string.pop(i)

																								file.write('''%-16s''' % '''Delete %c''' % op[1])
																								file.write('''\t\t\t''' + ''''''.join(string))
																								file.write('''\r\n''')

																								cost += 2
																		else:
																								string.insert(i, op[1])

																								file.write('''%-16s''' % '''Insert %c''' % op[1])
																								file.write('''\t\t\t''' + ''''''.join(string))
																								file.write('''\r\n''')

																								cost += 2

																		i += 1

												print(''''''.join(string))
												print('''Cost: ''', cost)

												file.write('''\r\nMinimum cost: ''' + str(cost))













"""simple docstring"""





import argparse
import logging

import datasets
from tokenizers import Tokenizer, decoders, normalizers, pre_tokenizers, processors
from tokenizers.models import Unigram
from tokenizers.trainers import UnigramTrainer

from transformers import AlbertTokenizerFast


lowerCAmelCase__        =      logging.getLogger(__name__)


def    a__       (       ):




		"""simple docstring"""


		UpperCamelCase =						argparse.ArgumentParser(description="Train a unigram tokenizer on the wikitext dataset."     )
		parser.add_argument(
		    "--dataset_name"	,						type=_SCREAMING_SNAKE_CASE	,						default="wikitext"	,						help="Name of the training. Explore datasets at: hf.co/datasets."	,						)
		parser.add_argument(
		    "--dataset_config"	,						type=_SCREAMING_SNAKE_CASE	,						default="wikitext-103-raw-v1"	,						help="Configuration name of the dataset."     )
		parser.add_argument(
		    "--batch_size"	,						type=_SCREAMING_SNAKE_CASE	,						default=1_000	,						help="Batch size during training."	,						)
		parser.add_argument(
		    "--vocab_size"	,						type=_SCREAMING_SNAKE_CASE	,						default=10_048	,						help="Size of the desired vocabulary."	,						)
		parser.add_argument(
		    "--limit"	,						default=_SCREAMING_SNAKE_CASE	,						type=_SCREAMING_SNAKE_CASE	,						help="Limit the number of shards (used for debugging)."	,						)
		parser.add_argument(
		    "--export_to_hub"	,						action="store_true"	,						)

		UpperCamelCase =						parser.parse_args()
		return args


def    a__       (       _SCREAMING_SNAKE_CASE     ):




		"""simple docstring"""


		UpperCamelCase =						datasets.load_dataset(args.dataset_name	,						args.dataset_config	,						split="train"     )

		if args.limit is not None:
				UpperCamelCase =						min(len(_SCREAMING_SNAKE_CASE     )	,						args.limit     )
				UpperCamelCase =						dataset.select(range(_SCREAMING_SNAKE_CASE     )     )
				logger.info(F"Limiting the dataset to {args.limit} entries."     )

		def batch_iterator():
				for i in range(0	,						len(_SCREAMING_SNAKE_CASE     )	,						args.batch_size     ):
						yield dataset[i : i + args.batch_size]["text"]

    # Prepare the tokenizer.
		UpperCamelCase =						Tokenizer(Unigram()     )
		UpperCamelCase =						normalizers.Sequence([normalizers.Replace("``"	,						"\""     ), normalizers.Replace("''"	,						"\""     )]     )
		UpperCamelCase =						pre_tokenizers.Metaspace()

		# Prepare the trainer.
		UpperCamelCase =						UnigramTrainer(
		    unk_token="<unk>"	,						special_tokens=["[CLS]", "[SEP]", "<unk>", "<pad>", "[MASK]"]	,						vocab_size=args.vocab_size	,						)

		logger.info("Training the tokenizer."     )
		tokenizer.train_from_iterator(batch_iterator()	,						trainer=_SCREAMING_SNAKE_CASE     )
		logger.info("Tokenizer training complete!"     )

		UpperCamelCase =						tokenizer.token_to_id("[CLS]"     )
		UpperCamelCase =						tokenizer.token_to_id("[SEP]"     )
		UpperCamelCase =						processors.TemplateProcessing(
		    single="[CLS]:0 $A:0 [SEP]:0"	,						pair="[CLS]:0 $A:0 [SEP]:0 $B:1 [SEP]:1"	,						special_tokens=[
		        ("[CLS]", cls_token_id),
		        ("[SEP]", sep_token_id),
		    ]	,						)
		UpperCamelCase =						decoders.Metaspace()

		if args.export_to_hub:
				logger.info("Exporting the trained tokenzier to Hub."     )
				UpperCamelCase =						AlbertTokenizerFast(tokenizer_object=_SCREAMING_SNAKE_CASE     )
				new_tokenizer.push_to_hub("unigram-tokenizer-dataset"     )


if __name__ == "__main__":
						lowerCAmelCase__        =      parse_args()
						main(args)






