





import json
import os
import tempfile

import datasets
from utils import generate_example_dataset, get_duration


snake_case_				=      5_0_0_0_0_0

snake_case_,							snake_case_				=      os.path.split(__file__)
snake_case_				=      os.path.join(RESULTS_BASEPATH, '''results''', RESULTS_FILENAME.replace('''.py''', '''.json'''))


@get_duration
def        A__						(							SCREAMING_SNAKE_CASE_		) ->  int:
		lowerCamelCase :			Optional[Any]    		=dataset.select(range(0				,							len(SCREAMING_SNAKE_CASE_		)				,							2		)		)


@get_duration
def        A__						(							SCREAMING_SNAKE_CASE_		) ->  int:
		lowerCamelCase :			Dict    		=dataset.sort('''numbers'''		)


@get_duration
def        A__						(							SCREAMING_SNAKE_CASE_		) ->  List[Any]:
		lowerCamelCase :			int    		=dataset.shuffle()


@get_duration
def        A__						(							SCREAMING_SNAKE_CASE_		) ->  List[Any]:
		lowerCamelCase :			Tuple    		=dataset.train_test_split(0.1		)


@get_duration
def        A__						(							SCREAMING_SNAKE_CASE_				,							SCREAMING_SNAKE_CASE_=1_0		) ->  str:
		for shard_id in range(SCREAMING_SNAKE_CASE_		):
				lowerCamelCase :			Optional[int]    		=dataset.shard(SCREAMING_SNAKE_CASE_				,							SCREAMING_SNAKE_CASE_		)


def        A__						(							) ->  Union[str, Any]:
		lowerCamelCase :			int    		={'''num examples''': SPEED_TEST_N_EXAMPLES}
		lowerCamelCase :			List[str]    		=(select, sort, shuffle, train_test_split, shard)
		with tempfile.TemporaryDirectory() as tmp_dir:
				print('''generating dataset'''		)
				lowerCamelCase :			List[Any]    		=datasets.Features({'''text''': datasets.Value('''string'''		), '''numbers''': datasets.Value('''float32'''		)}		)
				lowerCamelCase :			Dict    		=generate_example_dataset(
				    os.path.join(SCREAMING_SNAKE_CASE_				,							'''dataset.arrow'''		)				,							SCREAMING_SNAKE_CASE_				,							num_examples=SCREAMING_SNAKE_CASE_		)
				print('''Functions'''		)
				for func in functions:
						print(func.__name__		)
						lowerCamelCase :			Dict    		=func(SCREAMING_SNAKE_CASE_		)

		with open(SCREAMING_SNAKE_CASE_				,							'''wb'''		) as f:
				f.write(json.dumps(SCREAMING_SNAKE_CASE_		).encode('''utf-8'''		)		)


if __name__ == "__main__":  # useful to run the profiler
				benchmark_indices_mapping()








import sys

from transformers import AutoTokenizer


snake_case_				=      sys.argv[1]
snake_case_				=      sys.argv[2]
snake_case_				=      int(sys.argv[3])

snake_case_				=      0

snake_case_				=      AutoTokenizer.from_pretrained(model_name_or_path)
max_len -= tokenizer.num_special_tokens_to_add()

with open(dataset, '''rt''') as f_p:
				for line in f_p:
								snake_case_				=      line.rstrip()

								if not line:
												print(line)
												snake_case_				=      0
												continue

								snake_case_				=      line.split()[0]

								snake_case_				=      len(tokenizer.tokenize(token))

								# Token contains strange control characters like \x96 or \x95
								# Just filter out the complete line
								if current_subwords_len == 0:
												continue

								if (subword_len_counter + current_subwords_len) > max_len:
												print('''''')
												print(line)
												snake_case_				=      current_subwords_len
												continue

								subword_len_counter += current_subwords_len

								print(line)

