"""simple docstring"""





import os
import unittest

from transformers import LxmertTokenizer, LxmertTokenizerFast
from transformers.models.bert.tokenization_bert import VOCAB_FILES_NAMES
from transformers.testing_utils import require_tokenizers

from ...test_tokenization_common import TokenizerTesterMixin
@require_tokenizers
class  _snake_case     (					a__				, unittest.TestCase		):
						snake_case__			  =			LxmertTokenizer
						snake_case__			  =			LxmertTokenizerFast
						snake_case__			  =			True
						snake_case__			  =			True






						def       lowerCamelCase__     (       self      :			List[str]    ):
													super().setUp()

													__lowerCamelCase					:		Union[str, Any]		   =     [
													    "[UNK]",
													    "[CLS]",
													    "[SEP]",
													    "want",
													    "##want",
													    "##ed",
													    "wa",
													    "un",
													    "runn",
													    "##ing",
													    ",",
													    "low",
													    "lowest",
													]
													__lowerCamelCase					:		int		   =     os.path.join(self.tmpdirname							,					VOCAB_FILES_NAMES["vocab_file"]    )
													with open(self.vocab_file							,					"w"							,					encoding="utf-8"    ) as vocab_writer:
																				vocab_writer.write("".join([x + "\n" for x in vocab_tokens]    )    )






						def       lowerCamelCase__     (       self      :			str							,					UpperCAmelCase      :			str    ):
													__lowerCamelCase					:		int		   =     "UNwant\u00E9d,running"
													__lowerCamelCase					:		Union[str, Any]		   =     "unwanted, running"
													return input_text, output_text






						def       lowerCamelCase__     (       self      :			int    ):
													__lowerCamelCase					:		List[str]		   =     self.tokenizer_class(self.vocab_file    )

													__lowerCamelCase					:		List[str]		   =     tokenizer.tokenize("UNwant\u00E9d,running"    )
													self.assertListEqual(UpperCAmelCase							,					["un", "##want", "##ed", ",", "runn", "##ing"]    )
													self.assertListEqual(tokenizer.convert_tokens_to_ids(UpperCAmelCase    )							,					[7, 4, 5, 10, 8, 9]    )







						def       lowerCamelCase__     (       self      :			Union[str, Any]    ):
													if not self.test_rust_tokenizer:
																				return

													__lowerCamelCase					:		str		   =     self.get_tokenizer()
													__lowerCamelCase					:		Union[str, Any]		   =     self.get_rust_tokenizer()

													__lowerCamelCase					:		Optional[Any]		   =     "I was born in 92000, and this is falsé."

													__lowerCamelCase					:		Union[str, Any]		   =     tokenizer.tokenize(UpperCAmelCase    )
													__lowerCamelCase					:		Dict		   =     rust_tokenizer.tokenize(UpperCAmelCase    )
													self.assertListEqual(UpperCAmelCase							,					UpperCAmelCase    )

													__lowerCamelCase					:		List[Any]		   =     tokenizer.encode(UpperCAmelCase							,					add_special_tokens=UpperCAmelCase    )
													__lowerCamelCase					:		Dict		   =     rust_tokenizer.encode(UpperCAmelCase							,					add_special_tokens=UpperCAmelCase    )
													self.assertListEqual(UpperCAmelCase							,					UpperCAmelCase    )

													__lowerCamelCase					:		Optional[int]		   =     self.get_rust_tokenizer()
													__lowerCamelCase					:		Any		   =     tokenizer.encode(UpperCAmelCase    )
													__lowerCamelCase					:		Tuple		   =     rust_tokenizer.encode(UpperCAmelCase    )
													self.assertListEqual(UpperCAmelCase							,					UpperCAmelCase    )
"""simple docstring"""





import os
from argparse import ArgumentParser
from typing import List

import torch.utils.data

from datasets import Dataset, IterableDataset
from datasets.distributed import split_dataset_by_node


__A  =				4
__A  =				3
class  _snake_case     (					a__		):
						pass


def    lowercase_   (   _lowerCamelCase:	List[str]      ) ->      List[str]:



							'''simple docstring'''

							for shard in shards:
														for i in range(_lowerCamelCase      ):
																					yield {"i": i, "shard": shard}


def    lowercase_   (   ) ->      List[Any]:



							'''simple docstring'''

							__lowerCamelCase					:		List[Any]		   =     int(os.environ["RANK"]      )
							__lowerCamelCase					:		Optional[int]		   =     int(os.environ["WORLD_SIZE"]      )

							__lowerCamelCase					:		Any		   =     ArgumentParser()
							parser.add_argument("--streaming"						,   type=_lowerCamelCase      )
							parser.add_argument("--local_rank"						,   type=_lowerCamelCase      )
							parser.add_argument("--num_workers"						,   type=_lowerCamelCase						,   default=0      )
							__lowerCamelCase					:		Dict		   =     parser.parse_args()
							__lowerCamelCase					:		str		   =     args.streaming
							__lowerCamelCase					:		List[Any]		   =     args.num_workers

							__lowerCamelCase					:		Optional[Any]		   =     {"shards": [F"""shard_{shard_idx}""" for shard_idx in range(_lowerCamelCase      )]}
							__lowerCamelCase					:		int		   =     IterableDataset.from_generator(_lowerCamelCase						,   gen_kwargs=_lowerCamelCase      )
							if not streaming:
														__lowerCamelCase					:		Optional[int]		   =     Dataset.from_list(list(_lowerCamelCase      )      )

							__lowerCamelCase					:		Union[str, Any]		   =     split_dataset_by_node(_lowerCamelCase						,   rank=_lowerCamelCase						,   world_size=_lowerCamelCase      )
							__lowerCamelCase					:		Optional[Any]		   =     torch.utils.data.DataLoader(_lowerCamelCase						,   num_workers=_lowerCamelCase      )

							__lowerCamelCase					:		List[Any]		   =     NUM_SHARDS * NUM_ITEMS_PER_SHARD
							__lowerCamelCase					:		Optional[Any]		   =     full_size // world_size
							expected_local_size += int(rank < (full_size % world_size)      )

							__lowerCamelCase					:		Optional[Any]		   =     sum(1 for _ in dataloader      )
							if local_size != expected_local_size:
														raise FailedTestError(F"""local_size {local_size} != expected_local_size {expected_local_size}"""      )


if __name__ == "__main__":
				main()