



'''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


__lowerCAmelCase		     =  get_tests_dir('''fixtures/test_sentencepiece.model''')


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

__lowerCAmelCase		     =  50_003
__lowerCAmelCase		     =  50_002

@require_sentencepiece
@require_tokenizers
class       __magic_name__		(       _UpperCamelCase     ,		unittest.TestCase  ):
							lowerCAmelCase			:       List[str]  							=   PLBartTokenizer
							lowerCAmelCase			:       List[str]  							=   None
							lowerCAmelCase			:       List[str]  							=   False







							def 				__lowercase     (				self   :			Tuple						):
									super().setUp()

									# We have a SentencePiece fixture for testing
									_a	: Dict								=				PLBartTokenizer(_UpperCAmelCase      ,language_codes='base'      ,keep_accents=_UpperCAmelCase						)
									tokenizer.save_pretrained(self.tmpdirname						)







							def 				__lowercase     (				self   :			List[Any]						):
									_a	: str								=				PLBartTokenizer(_UpperCAmelCase      ,language_codes='base'      ,keep_accents=_UpperCAmelCase						)

									_a	: int								=				tokenizer.tokenize('This is a test'						)
									self.assertListEqual(_UpperCAmelCase      ,['▁This', '▁is', '▁a', '▁t', 'est']						)

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

									_a	: Dict								=				tokenizer.tokenize('I was born in 92000, and this is falsé.'						)
									self.assertListEqual(
									    _UpperCAmelCase      ,[
									        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	: List[Any]								=				tokenizer.convert_tokens_to_ids(_UpperCAmelCase						)
									self.assertListEqual(
									    _UpperCAmelCase      ,[
									        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	: str								=				tokenizer.convert_ids_to_tokens(_UpperCAmelCase						)
									self.assertListEqual(
									    _UpperCAmelCase      ,[
									        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	: Tuple								=				tokenizer.vocab_size
									_a	: Union[str, Any]								=				[tokenizer.convert_ids_to_tokens(_UpperCAmelCase						) for x in range(end - 4      ,_UpperCAmelCase						)]

									self.assertListEqual(_UpperCAmelCase      ,['__java__', '__python__', '__en_XX__', '<mask>']						)

									_a	: Optional[Any]								=				'java.lang.Exception, python.lang.Exception, javascript, php, ruby, go'
									_a	: str								=				tokenizer(_UpperCAmelCase						).input_ids
									self.assertEqual(
									    tokenizer.decode(_UpperCAmelCase      ,skip_special_tokens=_UpperCAmelCase      ,clean_up_tokenization_spaces=_UpperCAmelCase						)      ,_UpperCAmelCase      ,)







							def 				__lowercase     (				self   :			List[Any]						):
									_a	: List[str]								=				PLBartTokenizer(_UpperCAmelCase      ,language_codes='multi'      ,keep_accents=_UpperCAmelCase						)

									_a	: List[str]								=				tokenizer.tokenize('This is a test'						)
									self.assertListEqual(_UpperCAmelCase      ,['▁This', '▁is', '▁a', '▁t', 'est']						)

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

									_a	: Optional[int]								=				tokenizer.tokenize('I was born in 92000, and this is falsé.'						)
									self.assertListEqual(
									    _UpperCAmelCase      ,[
									        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	: Dict								=				tokenizer.convert_tokens_to_ids(_UpperCAmelCase						)
									self.assertListEqual(
									    _UpperCAmelCase      ,[
									        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	: Optional[Any]								=				tokenizer.convert_ids_to_tokens(_UpperCAmelCase						)
									self.assertListEqual(
									    _UpperCAmelCase      ,[
									        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	: Tuple								=				tokenizer.vocab_size
									_a	: Any								=				[tokenizer.convert_ids_to_tokens(_UpperCAmelCase						) for x in range(end - 7      ,_UpperCAmelCase						)]

									self.assertListEqual(
									    _UpperCAmelCase      ,['__java__', '__python__', '__en_XX__', '__javascript__', '__php__', '__ruby__', '__go__']						)
									_a	: Dict								=				'java.lang.Exception, python.lang.Exception, javascript, php, ruby, go'
									_a	: Union[str, Any]								=				tokenizer(_UpperCAmelCase						).input_ids
									self.assertEqual(
									    tokenizer.decode(_UpperCAmelCase      ,skip_special_tokens=_UpperCAmelCase      ,clean_up_tokenization_spaces=_UpperCAmelCase						)      ,_UpperCAmelCase      ,)

@require_torch
@require_sentencepiece
@require_tokenizers
class       __magic_name__		(       unittest.TestCase  ):
							lowerCAmelCase			:       List[Any]  							=   'uclanlp/plbart-python-en_XX'
							lowerCAmelCase			:       Any  							=   [
							    '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			:       str  							=   [
							    'Returns the maximum value of a b c.',
							    'Sums the values of a b c.',
							]
							lowerCAmelCase			:       Optional[Any]  							=   [
							    1_3_4,
							    5_4_5_2,
							    3_3_4_6_0,
							    3_3_4_4_1,
							    3_3_4_6_3,
							    3_3_4_6_5,
							    3_3_4_6_3,
							    3_3_4_4_9,
							    9_8_8,
							    2_0,
							    3_3_4_5_6,
							    1_9,
							    3_3_4_5_6,
							    7_7_1,
							    3_9,
							    4_2_5_8,
							    8_8_9,
							    3_3_1_8,
							    3_3_4_4_1,
							    3_3_4_6_3,
							    3_3_4_6_5,
							    3_3_4_6_3,
							    3_3_4_4_9,
							    2_4_7_1,
							    2,
							    PYTHON_CODE,
							]







							@classmethod
							def 				__lowercase     (				cls   :			str						):
									_a	: PLBartTokenizer								=				PLBartTokenizer.from_pretrained(
									    cls.checkpoint_name      ,language_codes='base'      ,src_lang='python'      ,tgt_lang='en_XX'						)
									_a	: Tuple								=				1
									return cls







							def 				__lowercase     (				self   :			Any						):
									self.assertEqual(self.tokenizer.fairseq_tokens_to_ids['__java__']      ,50001						)
									self.assertEqual(self.tokenizer.fairseq_tokens_to_ids['__python__']      ,50002						)
									self.assertEqual(self.tokenizer.fairseq_tokens_to_ids['__en_XX__']      ,50003						)







							def 				__lowercase     (				self   :			List[Any]						):
									_a	: str								=				self.tokenizer.batch_encode_plus(self.src_text						).input_ids[0]
									self.assertListEqual(self.expected_src_tokens      ,_UpperCAmelCase						)







							def 				__lowercase     (				self   :			Union[str, Any]						):
									self.assertIn(_UpperCAmelCase      ,self.tokenizer.all_special_ids						)
									_a	: Any								=				[EN_CODE, 9037, 33442, 57, 752, 153, 14, 56, 18, 9, 2]
									_a	: Dict								=				self.tokenizer.decode(_UpperCAmelCase      ,skip_special_tokens=_UpperCAmelCase						)
									_a	: Union[str, Any]								=				self.tokenizer.decode(generated_ids[1:]      ,skip_special_tokens=_UpperCAmelCase						)
									self.assertEqual(_UpperCAmelCase      ,_UpperCAmelCase						)
									self.assertNotIn(self.tokenizer.eos_token      ,_UpperCAmelCase						)







							def 				__lowercase     (				self   :			int						):
									_a	: Optional[int]								=				['def sum(a,b,c):NEW_LINE_INDENTreturn sum([a,b,c])' * 20]
									self.assertIsInstance(src_text[0]      ,_UpperCAmelCase						)
									_a	: List[str]								=				10
									_a	: Dict								=				self.tokenizer(_UpperCAmelCase      ,max_length=_UpperCAmelCase      ,truncation=_UpperCAmelCase						).input_ids[0]
									self.assertEqual(ids[-2]      ,2						)
									self.assertEqual(ids[-1]      ,_UpperCAmelCase						)
									self.assertEqual(len(_UpperCAmelCase						)      ,_UpperCAmelCase						)







							def 				__lowercase     (				self   :			Optional[int]						):
									self.assertListEqual(self.tokenizer.convert_tokens_to_ids(['<mask>', '__java__']						)      ,[50004, 50001]						)







							def 				__lowercase     (				self   :			Optional[Any]						):
									_a	: Dict								=				tempfile.mkdtemp()
									_a	: List[Any]								=				self.tokenizer.fairseq_tokens_to_ids
									self.tokenizer.save_pretrained(_UpperCAmelCase						)
									_a	: Any								=				PLBartTokenizer.from_pretrained(_UpperCAmelCase						)
									self.assertDictEqual(new_tok.fairseq_tokens_to_ids      ,_UpperCAmelCase						)







							@require_torch
							def 				__lowercase     (				self   :			Dict						):
									_a	: List[str]								=				self.tokenizer(self.src_text      ,text_target=self.tgt_text      ,padding=_UpperCAmelCase      ,return_tensors='pt'						)
									_a	: Tuple								=				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]      ,_UpperCAmelCase						)
									self.assertEqual(batch.decoder_input_ids[1][-1]      ,2						)
									self.assertEqual(batch.labels[1][-2:].tolist()      ,[2, EN_CODE]						)







							@require_torch
							def 				__lowercase     (				self   :			Optional[Any]						):
									_a	: List[str]								=				self.tokenizer(
									    self.src_text      ,text_target=self.tgt_text      ,padding=_UpperCAmelCase      ,truncation=_UpperCAmelCase      ,max_length=len(self.expected_src_tokens						)      ,return_tensors='pt'      ,)
									_a	: Any								=				shift_tokens_right(batch['labels']      ,self.tokenizer.pad_token_id						)

									self.assertIsInstance(_UpperCAmelCase      ,_UpperCAmelCase						)

									self.assertEqual((2, 26)      ,batch.input_ids.shape						)
									self.assertEqual((2, 26)      ,batch.attention_mask.shape						)
									_a	: Optional[int]								=				batch.input_ids.tolist()[0]
									self.assertListEqual(self.expected_src_tokens      ,_UpperCAmelCase						)
									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 				__lowercase     (				self   :			Optional[Any]						):
									_a	: Optional[int]								=				self.tokenizer(self.src_text      ,padding=_UpperCAmelCase      ,truncation=_UpperCAmelCase      ,max_length=3      ,return_tensors='pt'						)
									_a	: str								=				self.tokenizer(
									    text_target=self.tgt_text      ,padding=_UpperCAmelCase      ,truncation=_UpperCAmelCase      ,max_length=10      ,return_tensors='pt'						)
									_a	: Optional[Any]								=				targets['input_ids']
									_a	: List[Any]								=				shift_tokens_right(_UpperCAmelCase      ,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 				__lowercase     (				self   :			Optional[int]						):
									_a	: int								=				self.tokenizer._build_translation_inputs(
									    'A test'      ,return_tensors='pt'      ,src_lang='en_XX'      ,tgt_lang='java'						)

									self.assertEqual(
									    nested_simplify(_UpperCAmelCase						)      ,{
									        # A, test, EOS, en_XX
									        'input_ids': [[150, 242, 2, 50003]],
									        'attention_mask': [[1, 1, 1, 1]],
									        # java
									        'forced_bos_token_id': 50001,
									    }      ,)









'''simple docstring'''

import argparse

from transformers import BigBirdConfig, BigBirdForPreTraining, BigBirdForQuestionAnswering, load_tf_weights_in_big_bird
from transformers.utils import logging


logging.set_verbosity_info()



def 	__lowerCamelCase	( lowerCAmelCase_		,     lowerCAmelCase_		,     lowerCAmelCase_		,     lowerCAmelCase_    )     -> Any:
		# Initialise PyTorch model
		_a	: int								=				BigBirdConfig.from_json_file(lowerCAmelCase_    )
		print(f"""Building PyTorch model from configuration: {config}"""    )

		if is_trivia_qa:
				_a	: Union[str, Any]								=				BigBirdForQuestionAnswering(lowerCAmelCase_    )
		else:
				_a	: Any								=				BigBirdForPreTraining(lowerCAmelCase_    )

		# Load weights from tf checkpoint
		load_tf_weights_in_big_bird(lowerCAmelCase_		,     lowerCAmelCase_		,     is_trivia_qa=lowerCAmelCase_    )

		# Save pytorch-model
		print(f"""Save PyTorch model to {pytorch_dump_path}"""    )
		model.save_pretrained(lowerCAmelCase_    )


if __name__ == "__main__":
							__lowerCAmelCase		     =  argparse.ArgumentParser()
							# Required parameters
							parser.add_argument(
							    '''--tf_checkpoint_path''', default=None, type=str, required=True, help='''Path to the TensorFlow checkpoint path.'''
							)
							parser.add_argument(
							    '''--big_bird_config_file''',
							    default=None,
							    type=str,
							    required=True,
							    help=(
							        '''The config json file corresponding to the pre-trained BERT model. \n'''
							        '''This specifies the model architecture.'''
							    ),
							)
							parser.add_argument(
							    '''--pytorch_dump_path''', default=None, type=str, required=True, help='''Path to the output PyTorch model.'''
							)
							parser.add_argument(
							    '''--is_trivia_qa''', action='''store_true''', help='''Whether to convert a model with a trivia_qa head.'''
							)
							__lowerCAmelCase		     =  parser.parse_args()
							convert_tf_checkpoint_to_pytorch(
							    args.tf_checkpoint_path, args.big_bird_config_file, args.pytorch_dump_path, args.is_trivia_qa
							)




