





"""simple docstring"""




import tempfile
import unittest

from transformers import SPIECE_UNDERLINE, BatchEncoding, PLBartTokenizer, is_torch_available
from transformers.testing_utils import (
    get_tests_dir,
    nested_simplify,
    require_sentencepiece,
    require_tokenizers,
    require_torch,
)

from ...test_tokenization_common import TokenizerTesterMixin


a		:				str  			=    get_tests_dir('''fixtures/test_sentencepiece.model''')


if is_torch_available():
		from transformers.models.plbart.modeling_plbart import shift_tokens_right

a		:				List[Any]  			=    50003
a		:				Union[str, Any]  			=    50002


@require_sentencepiece
@require_tokenizers
class  __UpperCamelCase       (		a__	, unittest.TestCase		):
							lowerCamelCase     :      List[Any]         =PLBartTokenizer
							lowerCamelCase     :      List[Any]         =None
							lowerCamelCase     :      Union[str, Any]         =False






							def 					__a     (     self   )			->				Union[str, Any]:
								super().setUp()

								# We have a SentencePiece fixture for testing
								a   :	List[str]			=       PLBartTokenizer(lowerCAmelCase__   ,      language_codes="base"   ,      keep_accents=lowerCAmelCase__   )
								tokenizer.save_pretrained(self.tmpdirname   )






							def 					__a     (     self   )			->				Dict:
								a   :	Optional[int]			=       PLBartTokenizer(lowerCAmelCase__   ,      language_codes="base"   ,      keep_accents=lowerCAmelCase__   )

								a   :	Optional[int]			=       tokenizer.tokenize("This is a test"   )
								self.assertListEqual(lowerCAmelCase__   ,      ["▁This", "▁is", "▁a", "▁t", "est"]   )

								self.assertListEqual(
								    tokenizer.convert_tokens_to_ids(lowerCAmelCase__   )   ,      [value + tokenizer.fairseq_offset for value in [285, 46, 10, 170, 382]]   ,      )

								a   :	List[Any]			=       tokenizer.tokenize("I was born in 92000, and this is falsé."   )
								self.assertListEqual(
								    lowerCAmelCase__   ,      [
								        SPIECE_UNDERLINE + "I",
								        SPIECE_UNDERLINE + "was",
								        SPIECE_UNDERLINE + "b",
								        "or",
								        "n",
								        SPIECE_UNDERLINE + "in",
								        SPIECE_UNDERLINE + "",
								        "9",
								        "2",
								        "0",
								        "0",
								        "0",
								        ",",
								        SPIECE_UNDERLINE + "and",
								        SPIECE_UNDERLINE + "this",
								        SPIECE_UNDERLINE + "is",
								        SPIECE_UNDERLINE + "f",
								        "al",
								        "s",
								        "é",
								        ".",
								    ]   ,      )
								a   :	Union[str, Any]			=       tokenizer.convert_tokens_to_ids(lowerCAmelCase__   )
								self.assertListEqual(
								    lowerCAmelCase__   ,      [
								        value + tokenizer.fairseq_offset
								        for value in [8, 21, 84, 55, 24, 19, 7, 2, 602, 347, 347, 347, 3, 12, 66, 46, 72, 80, 6, 2, 4]
								    ]   ,      )

								a   :	Tuple			=       tokenizer.convert_ids_to_tokens(lowerCAmelCase__   )
								self.assertListEqual(
								    lowerCAmelCase__   ,      [
								        SPIECE_UNDERLINE + "I",
								        SPIECE_UNDERLINE + "was",
								        SPIECE_UNDERLINE + "b",
								        "or",
								        "n",
								        SPIECE_UNDERLINE + "in",
								        SPIECE_UNDERLINE + "",
								        "<unk>",
								        "2",
								        "0",
								        "0",
								        "0",
								        ",",
								        SPIECE_UNDERLINE + "and",
								        SPIECE_UNDERLINE + "this",
								        SPIECE_UNDERLINE + "is",
								        SPIECE_UNDERLINE + "f",
								        "al",
								        "s",
								        "<unk>",
								        ".",
								    ]   ,      )

								a   :	Optional[int]			=       tokenizer.vocab_size
								a   :	Any			=       [tokenizer.convert_ids_to_tokens(lowerCAmelCase__   ) for x in range(end - 4   ,      lowerCAmelCase__   )]

								self.assertListEqual(lowerCAmelCase__   ,      ["__java__", "__python__", "__en_XX__", "<mask>"]   )

								a   :	Any			=       "java.lang.Exception, python.lang.Exception, javascript, php, ruby, go"
								a   :	Optional[int]			=       tokenizer(lowerCAmelCase__   ).input_ids
								self.assertEqual(
								    tokenizer.decode(lowerCAmelCase__   ,      skip_special_tokens=lowerCAmelCase__   ,      clean_up_tokenization_spaces=lowerCAmelCase__   )   ,      lowerCAmelCase__   ,      )






							def 					__a     (     self   )			->				Tuple:
								a   :	Any			=       PLBartTokenizer(lowerCAmelCase__   ,      language_codes="multi"   ,      keep_accents=lowerCAmelCase__   )

								a   :	Dict			=       tokenizer.tokenize("This is a test"   )
								self.assertListEqual(lowerCAmelCase__   ,      ["▁This", "▁is", "▁a", "▁t", "est"]   )

								self.assertListEqual(
								    tokenizer.convert_tokens_to_ids(lowerCAmelCase__   )   ,      [value + tokenizer.fairseq_offset for value in [285, 46, 10, 170, 382]]   ,      )

								a   :	int			=       tokenizer.tokenize("I was born in 92000, and this is falsé."   )
								self.assertListEqual(
								    lowerCAmelCase__   ,      [
								        SPIECE_UNDERLINE + "I",
								        SPIECE_UNDERLINE + "was",
								        SPIECE_UNDERLINE + "b",
								        "or",
								        "n",
								        SPIECE_UNDERLINE + "in",
								        SPIECE_UNDERLINE + "",
								        "9",
								        "2",
								        "0",
								        "0",
								        "0",
								        ",",
								        SPIECE_UNDERLINE + "and",
								        SPIECE_UNDERLINE + "this",
								        SPIECE_UNDERLINE + "is",
								        SPIECE_UNDERLINE + "f",
								        "al",
								        "s",
								        "é",
								        ".",
								    ]   ,      )
								a   :	str			=       tokenizer.convert_tokens_to_ids(lowerCAmelCase__   )
								self.assertListEqual(
								    lowerCAmelCase__   ,      [
								        value + tokenizer.fairseq_offset
								        for value in [8, 21, 84, 55, 24, 19, 7, 2, 602, 347, 347, 347, 3, 12, 66, 46, 72, 80, 6, 2, 4]
								    ]   ,      )

								a   :	Union[str, Any]			=       tokenizer.convert_ids_to_tokens(lowerCAmelCase__   )
								self.assertListEqual(
								    lowerCAmelCase__   ,      [
								        SPIECE_UNDERLINE + "I",
								        SPIECE_UNDERLINE + "was",
								        SPIECE_UNDERLINE + "b",
								        "or",
								        "n",
								        SPIECE_UNDERLINE + "in",
								        SPIECE_UNDERLINE + "",
								        "<unk>",
								        "2",
								        "0",
								        "0",
								        "0",
								        ",",
								        SPIECE_UNDERLINE + "and",
								        SPIECE_UNDERLINE + "this",
								        SPIECE_UNDERLINE + "is",
								        SPIECE_UNDERLINE + "f",
								        "al",
								        "s",
								        "<unk>",
								        ".",
								    ]   ,      )
								a   :	Dict			=       tokenizer.vocab_size
								a   :	List[Any]			=       [tokenizer.convert_ids_to_tokens(lowerCAmelCase__   ) for x in range(end - 7   ,      lowerCAmelCase__   )]

								self.assertListEqual(
								    lowerCAmelCase__   ,      ["__java__", "__python__", "__en_XX__", "__javascript__", "__php__", "__ruby__", "__go__"]   )
								a   :	List[str]			=       "java.lang.Exception, python.lang.Exception, javascript, php, ruby, go"
								a   :	int			=       tokenizer(lowerCAmelCase__   ).input_ids
								self.assertEqual(
								    tokenizer.decode(lowerCAmelCase__   ,      skip_special_tokens=lowerCAmelCase__   ,      clean_up_tokenization_spaces=lowerCAmelCase__   )   ,      lowerCAmelCase__   ,      )


@require_torch
@require_sentencepiece
@require_tokenizers
class  __UpperCamelCase       (		unittest.TestCase		):
							lowerCamelCase     :      int         ="""uclanlp/plbart-python-en_XX"""
							lowerCamelCase     :      Tuple         =[
							    """def maximum(a,b,c):NEW_LINE_INDENTreturn max([a,b,c])""",
							    """def sum(a,b,c):NEW_LINE_INDENTreturn sum([a,b,c])""",
							]
							lowerCamelCase     :      List[Any]         =[
							    """Returns the maximum value of a b c.""",
							    """Sums the values of a b c.""",
							]
							lowerCamelCase     :      List[Any]         =[
							    134,
							    5452,
							    3_3460,
							    3_3441,
							    3_3463,
							    3_3465,
							    3_3463,
							    3_3449,
							    988,
							    20,
							    3_3456,
							    19,
							    3_3456,
							    771,
							    39,
							    4258,
							    889,
							    3318,
							    3_3441,
							    3_3463,
							    3_3465,
							    3_3463,
							    3_3449,
							    2471,
							    2,
							    PYTHON_CODE,
							]






							@classmethod
							def 					__a     (     cls   )			->				List[Any]:
								a   :	PLBartTokenizer			=       PLBartTokenizer.from_pretrained(
								    cls.checkpoint_name   ,      language_codes="base"   ,      src_lang="python"   ,      tgt_lang="en_XX"   )
								a   :	Optional[Any]			=       1
								return cls






							def 					__a     (     self   )			->				List[str]:
								self.assertEqual(self.tokenizer.fairseq_tokens_to_ids["__java__"]   ,      5_0001   )
								self.assertEqual(self.tokenizer.fairseq_tokens_to_ids["__python__"]   ,      5_0002   )
								self.assertEqual(self.tokenizer.fairseq_tokens_to_ids["__en_XX__"]   ,      5_0003   )






							def 					__a     (     self   )			->				int:
								a   :	List[str]			=       self.tokenizer.batch_encode_plus(self.src_text   ).input_ids[0]
								self.assertListEqual(self.expected_src_tokens   ,      lowerCAmelCase__   )






							def 					__a     (     self   )			->				int:
								self.assertIn(lowerCAmelCase__   ,      self.tokenizer.all_special_ids   )
								a   :	List[str]			=       [EN_CODE, 9037, 3_3442, 57, 752, 153, 14, 56, 18, 9, 2]
								a   :	List[Any]			=       self.tokenizer.decode(lowerCAmelCase__   ,      skip_special_tokens=lowerCAmelCase__   )
								a   :	Dict			=       self.tokenizer.decode(generated_ids[1:]   ,      skip_special_tokens=lowerCAmelCase__   )
								self.assertEqual(lowerCAmelCase__   ,      lowerCAmelCase__   )
								self.assertNotIn(self.tokenizer.eos_token   ,      lowerCAmelCase__   )






							def 					__a     (     self   )			->				List[Any]:
								a   :	Union[str, Any]			=       ["def sum(a,b,c):NEW_LINE_INDENTreturn sum([a,b,c])" * 20]
								self.assertIsInstance(src_text[0]   ,      lowerCAmelCase__   )
								a   :	Optional[Any]			=       10
								a   :	Tuple			=       self.tokenizer(lowerCAmelCase__   ,      max_length=lowerCAmelCase__   ,      truncation=lowerCAmelCase__   ).input_ids[0]
								self.assertEqual(ids[-2]   ,      2   )
								self.assertEqual(ids[-1]   ,      lowerCAmelCase__   )
								self.assertEqual(len(lowerCAmelCase__   )   ,      lowerCAmelCase__   )






							def 					__a     (     self   )			->				Tuple:
								self.assertListEqual(self.tokenizer.convert_tokens_to_ids(["<mask>", "__java__"]   )   ,      [5_0004, 5_0001]   )






							def 					__a     (     self   )			->				Tuple:
								a   :	str			=       tempfile.mkdtemp()
								a   :	int			=       self.tokenizer.fairseq_tokens_to_ids
								self.tokenizer.save_pretrained(lowerCAmelCase__   )
								a   :	List[str]			=       PLBartTokenizer.from_pretrained(lowerCAmelCase__   )
								self.assertDictEqual(new_tok.fairseq_tokens_to_ids   ,      lowerCAmelCase__   )






							@require_torch
							def 					__a     (     self   )			->				Optional[int]:
								a   :	List[Any]			=       self.tokenizer(self.src_text   ,      text_target=self.tgt_text   ,      padding=lowerCAmelCase__   ,      return_tensors="pt"   )
								a   :	str			=       shift_tokens_right(batch["labels"]   ,      self.tokenizer.pad_token_id   )

								# fairseq batch: https://gist.github.com/sshleifer/cba08bc2109361a74ac3760a7e30e4f4
								self.assertEqual(batch.input_ids[1][-2:].tolist()   ,      [2, PYTHON_CODE]   )
								self.assertEqual(batch.decoder_input_ids[1][0]   ,      lowerCAmelCase__   )
								self.assertEqual(batch.decoder_input_ids[1][-1]   ,      2   )
								self.assertEqual(batch.labels[1][-2:].tolist()   ,      [2, EN_CODE]   )






							@require_torch
							def 					__a     (     self   )			->				Dict:
								a   :	Optional[int]			=       self.tokenizer(
								    self.src_text   ,      text_target=self.tgt_text   ,      padding=lowerCAmelCase__   ,      truncation=lowerCAmelCase__   ,      max_length=len(self.expected_src_tokens   )   ,      return_tensors="pt"   ,      )
								a   :	Optional[int]			=       shift_tokens_right(batch["labels"]   ,      self.tokenizer.pad_token_id   )

								self.assertIsInstance(lowerCAmelCase__   ,      lowerCAmelCase__   )

								self.assertEqual((2, 26)   ,      batch.input_ids.shape   )
								self.assertEqual((2, 26)   ,      batch.attention_mask.shape   )
								a   :	Union[str, Any]			=       batch.input_ids.tolist()[0]
								self.assertListEqual(self.expected_src_tokens   ,      lowerCAmelCase__   )
								self.assertEqual(2   ,      batch.decoder_input_ids[0, -1]   )  # EOS
								# Test that special tokens are reset
								self.assertEqual(self.tokenizer.prefix_tokens   ,      []   )
								self.assertEqual(self.tokenizer.suffix_tokens   ,      [self.tokenizer.eos_token_id, PYTHON_CODE]   )






							def 					__a     (     self   )			->				Any:
								a   :	Optional[Any]			=       self.tokenizer(self.src_text   ,      padding=lowerCAmelCase__   ,      truncation=lowerCAmelCase__   ,      max_length=3   ,      return_tensors="pt"   )
								a   :	List[str]			=       self.tokenizer(
								    text_target=self.tgt_text   ,      padding=lowerCAmelCase__   ,      truncation=lowerCAmelCase__   ,      max_length=10   ,      return_tensors="pt"   )
								a   :	List[Any]			=       targets["input_ids"]
								a   :	Tuple			=       shift_tokens_right(lowerCAmelCase__   ,      self.tokenizer.pad_token_id   )

								self.assertEqual(batch.input_ids.shape[1]   ,      3   )
								self.assertEqual(batch.decoder_input_ids.shape[1]   ,      10   )






							@require_torch
							def 					__a     (     self   )			->				List[Any]:
								a   :	List[Any]			=       self.tokenizer._build_translation_inputs(
								    "A test"   ,      return_tensors="pt"   ,      src_lang="en_XX"   ,      tgt_lang="java"   )

								self.assertEqual(
								    nested_simplify(lowerCAmelCase__   )   ,      {
								        # A, test, EOS, en_XX
								        "input_ids": [[150, 242, 2, 5_0003]],
								        "attention_mask": [[1, 1, 1, 1]],
								        # java
								        "forced_bos_token_id": 5_0001,
								    }   ,      )









"""simple docstring"""




import multiprocessing
import time

from arguments import PretokenizationArguments
from datasets import load_dataset

from transformers import AutoTokenizer, HfArgumentParser






def    _SCREAMING_SNAKE_CASE	(			_lowercase		:					List[str]      )				->int:






	'''simple docstring'''






	a   :	int			=       {}
	a   :	Union[str, Any]			=       tokenizer(example["content"]					, truncation=_lowercase      )["input_ids"]
	a   :	Any			=       len(example["content"]      ) / len(output["input_ids"]      )
	return output


a		:				int  			=    HfArgumentParser(PretokenizationArguments)
a		:				Optional[int]  			=    parser.parse_args()
if args.num_workers is None:
		a		:				Tuple  			=    multiprocessing.cpu_count()
a		:				Optional[int]  			=    AutoTokenizer.from_pretrained(args.tokenizer_dir)

a		:				Dict  			=    time.time()
a		:				Tuple  			=    load_dataset(args.dataset_name, split='''train''')
print(F'''Dataset loaded in {time.time()-t_start:.2f}s''')

a		:				Dict  			=    time.time()
a		:				Tuple  			=    ds.map(
    tokenize,
    num_proc=args.num_workers,
    remove_columns=[
        '''repo_name''',
        '''path''',
        '''copies''',
        '''size''',
        '''content''',
        '''license''',
        '''hash''',
        '''line_mean''',
        '''line_max''',
        '''alpha_frac''',
        '''autogenerated''',
    ],
)
print(F'''Dataset tokenized in {time.time()-t_start:.2f}s''')

a		:				Tuple  			=    time.time()
ds.push_to_hub(args.tokenized_data_repo)







print(F'''Data pushed to the hub in {time.time()-t_start:.2f}s''')


