


'''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


_UpperCAmelCase				: Optional[int]							    =				get_tests_dir("""fixtures/test_sentencepiece.model""")


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

_UpperCAmelCase				: Dict							    =				5_0_0_0_3
_UpperCAmelCase				: List[Any]							    =				5_0_0_0_2


@require_sentencepiece
@require_tokenizers
class       a__				( __lowercase							,						unittest.TestCase      ):







				"""simple docstring"""



				__UpperCamelCase    :		Any		=	PLBartTokenizer
				__UpperCamelCase    :		Any		=	None
				__UpperCamelCase    :		Union[str, Any]		=	False




				def 					_snake_case  (self		):
										super().setUp()

										# We have a SentencePiece fixture for testing
										__lowerCAmelCase							       =				PLBartTokenizer(_A       ,			language_codes='''base'''       ,			keep_accents=_A		)
										tokenizer.save_pretrained(self.tmpdirname		)




				def 					_snake_case  (self		):
										__lowerCAmelCase							       =				PLBartTokenizer(_A       ,			language_codes='''base'''       ,			keep_accents=_A		)

										__lowerCAmelCase							       =				tokenizer.tokenize('''This is a test'''		)
										self.assertListEqual(_A       ,			['''▁This''', '''▁is''', '''▁a''', '''▁t''', '''est''']		)

										self.assertListEqual(
										    tokenizer.convert_tokens_to_ids(_A		)       ,			[value + tokenizer.fairseq_offset for value in [2_85, 46, 10, 1_70, 3_82]]       ,			)

										__lowerCAmelCase							       =				tokenizer.tokenize('''I was born in 92000, and this is falsé.'''		)
										self.assertListEqual(
										    _A       ,			[
										        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''',
										        '''.''',
										    ]       ,			)
										__lowerCAmelCase							       =				tokenizer.convert_tokens_to_ids(_A		)
										self.assertListEqual(
										    _A       ,			[
										        value + tokenizer.fairseq_offset
										        for value in [8, 21, 84, 55, 24, 19, 7, 2, 6_02, 3_47, 3_47, 3_47, 3, 12, 66, 46, 72, 80, 6, 2, 4]
										    ]       ,			)

										__lowerCAmelCase							       =				tokenizer.convert_ids_to_tokens(_A		)
										self.assertListEqual(
										    _A       ,			[
										        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>''',
										        '''.''',
										    ]       ,			)

										__lowerCAmelCase							       =				tokenizer.vocab_size
										__lowerCAmelCase							       =				[tokenizer.convert_ids_to_tokens(_A		) for x in range(end - 4       ,			_A		)]

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

										__lowerCAmelCase							       =				'''java.lang.Exception, python.lang.Exception, javascript, php, ruby, go'''
										__lowerCAmelCase							       =				tokenizer(_A		).input_ids
										self.assertEqual(
										    tokenizer.decode(_A       ,			skip_special_tokens=_A       ,			clean_up_tokenization_spaces=_A		)       ,			_A       ,			)




				def 					_snake_case  (self		):
										__lowerCAmelCase							       =				PLBartTokenizer(_A       ,			language_codes='''multi'''       ,			keep_accents=_A		)

										__lowerCAmelCase							       =				tokenizer.tokenize('''This is a test'''		)
										self.assertListEqual(_A       ,			['''▁This''', '''▁is''', '''▁a''', '''▁t''', '''est''']		)

										self.assertListEqual(
										    tokenizer.convert_tokens_to_ids(_A		)       ,			[value + tokenizer.fairseq_offset for value in [2_85, 46, 10, 1_70, 3_82]]       ,			)

										__lowerCAmelCase							       =				tokenizer.tokenize('''I was born in 92000, and this is falsé.'''		)
										self.assertListEqual(
										    _A       ,			[
										        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''',
										        '''.''',
										    ]       ,			)
										__lowerCAmelCase							       =				tokenizer.convert_tokens_to_ids(_A		)
										self.assertListEqual(
										    _A       ,			[
										        value + tokenizer.fairseq_offset
										        for value in [8, 21, 84, 55, 24, 19, 7, 2, 6_02, 3_47, 3_47, 3_47, 3, 12, 66, 46, 72, 80, 6, 2, 4]
										    ]       ,			)

										__lowerCAmelCase							       =				tokenizer.convert_ids_to_tokens(_A		)
										self.assertListEqual(
										    _A       ,			[
										        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>''',
										        '''.''',
										    ]       ,			)
										__lowerCAmelCase							       =				tokenizer.vocab_size
										__lowerCAmelCase							       =				[tokenizer.convert_ids_to_tokens(_A		) for x in range(end - 7       ,			_A		)]

										self.assertListEqual(
										    _A       ,			['''__java__''', '''__python__''', '''__en_XX__''', '''__javascript__''', '''__php__''', '''__ruby__''', '''__go__''']		)
										__lowerCAmelCase							       =				'''java.lang.Exception, python.lang.Exception, javascript, php, ruby, go'''
										__lowerCAmelCase							       =				tokenizer(_A		).input_ids
										self.assertEqual(
										    tokenizer.decode(_A       ,			skip_special_tokens=_A       ,			clean_up_tokenization_spaces=_A		)       ,			_A       ,			)


@require_torch
@require_sentencepiece
@require_tokenizers
class       a__				( unittest.TestCase      ):







				"""simple docstring"""



				__UpperCamelCase    :		List[str]		=	'uclanlp/plbart-python-en_XX'
				__UpperCamelCase    :		int		=	[
				    'def maximum(a,b,c):NEW_LINE_INDENTreturn max([a,b,c])',
				    'def sum(a,b,c):NEW_LINE_INDENTreturn sum([a,b,c])',
				]
				__UpperCamelCase    :		str		=	[
				    'Returns the maximum value of a b c.',
				    'Sums the values of a b c.',
				]
				__UpperCamelCase    :		Dict		=	[
				    134,
				    5_452,
				    33_460,
				    33_441,
				    33_463,
				    33_465,
				    33_463,
				    33_449,
				    988,
				    20,
				    33_456,
				    19,
				    33_456,
				    771,
				    39,
				    4_258,
				    889,
				    3_318,
				    33_441,
				    33_463,
				    33_465,
				    33_463,
				    33_449,
				    2_471,
				    2,
				    PYTHON_CODE,
				]




				@classmethod
				def 					_snake_case  (cls		):
										__lowerCAmelCase							       =				PLBartTokenizer.from_pretrained(
										    cls.checkpoint_name       ,			language_codes='''base'''       ,			src_lang='''python'''       ,			tgt_lang='''en_XX'''		)
										__lowerCAmelCase							       =				1
										return cls




				def 					_snake_case  (self		):
										self.assertEqual(self.tokenizer.fairseq_tokens_to_ids['''__java__''']       ,			5_00_01		)
										self.assertEqual(self.tokenizer.fairseq_tokens_to_ids['''__python__''']       ,			5_00_02		)
										self.assertEqual(self.tokenizer.fairseq_tokens_to_ids['''__en_XX__''']       ,			5_00_03		)




				def 					_snake_case  (self		):
										__lowerCAmelCase							       =				self.tokenizer.batch_encode_plus(self.src_text		).input_ids[0]
										self.assertListEqual(self.expected_src_tokens       ,			_A		)




				def 					_snake_case  (self		):
										self.assertIn(_A       ,			self.tokenizer.all_special_ids		)
										__lowerCAmelCase							       =				[EN_CODE, 90_37, 3_34_42, 57, 7_52, 1_53, 14, 56, 18, 9, 2]
										__lowerCAmelCase							       =				self.tokenizer.decode(_A       ,			skip_special_tokens=_A		)
										__lowerCAmelCase							       =				self.tokenizer.decode(generated_ids[1:]       ,			skip_special_tokens=_A		)
										self.assertEqual(_A       ,			_A		)
										self.assertNotIn(self.tokenizer.eos_token       ,			_A		)




				def 					_snake_case  (self		):
										__lowerCAmelCase							       =				['''def sum(a,b,c):NEW_LINE_INDENTreturn sum([a,b,c])''' * 20]
										self.assertIsInstance(src_text[0]       ,			_A		)
										__lowerCAmelCase							       =				10
										__lowerCAmelCase							       =				self.tokenizer(_A       ,			max_length=_A       ,			truncation=_A		).input_ids[0]
										self.assertEqual(ids[-2]       ,			2		)
										self.assertEqual(ids[-1]       ,			_A		)
										self.assertEqual(len(_A		)       ,			_A		)




				def 					_snake_case  (self		):
										self.assertListEqual(self.tokenizer.convert_tokens_to_ids(['''<mask>''', '''__java__''']		)       ,			[5_00_04, 5_00_01]		)




				def 					_snake_case  (self		):
										__lowerCAmelCase							       =				tempfile.mkdtemp()
										__lowerCAmelCase							       =				self.tokenizer.fairseq_tokens_to_ids
										self.tokenizer.save_pretrained(_A		)
										__lowerCAmelCase							       =				PLBartTokenizer.from_pretrained(_A		)
										self.assertDictEqual(new_tok.fairseq_tokens_to_ids       ,			_A		)




				@require_torch
				def 					_snake_case  (self		):
										__lowerCAmelCase							       =				self.tokenizer(self.src_text       ,			text_target=self.tgt_text       ,			padding=_A       ,			return_tensors='''pt'''		)
										__lowerCAmelCase							       =				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]       ,			_A		)
										self.assertEqual(batch.decoder_input_ids[1][-1]       ,			2		)
										self.assertEqual(batch.labels[1][-2:].tolist()       ,			[2, EN_CODE]		)




				@require_torch
				def 					_snake_case  (self		):
										__lowerCAmelCase							       =				self.tokenizer(
										    self.src_text       ,			text_target=self.tgt_text       ,			padding=_A       ,			truncation=_A       ,			max_length=len(self.expected_src_tokens		)       ,			return_tensors='''pt'''       ,			)
										__lowerCAmelCase							       =				shift_tokens_right(batch['''labels''']       ,			self.tokenizer.pad_token_id		)

										self.assertIsInstance(_A       ,			_A		)

										self.assertEqual((2, 26)       ,			batch.input_ids.shape		)
										self.assertEqual((2, 26)       ,			batch.attention_mask.shape		)
										__lowerCAmelCase							       =				batch.input_ids.tolist()[0]
										self.assertListEqual(self.expected_src_tokens       ,			_A		)
										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 					_snake_case  (self		):
										__lowerCAmelCase							       =				self.tokenizer(self.src_text       ,			padding=_A       ,			truncation=_A       ,			max_length=3       ,			return_tensors='''pt'''		)
										__lowerCAmelCase							       =				self.tokenizer(
										    text_target=self.tgt_text       ,			padding=_A       ,			truncation=_A       ,			max_length=10       ,			return_tensors='''pt'''		)
										__lowerCAmelCase							       =				targets['''input_ids''']
										__lowerCAmelCase							       =				shift_tokens_right(_A       ,			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 					_snake_case  (self		):
										__lowerCAmelCase							       =				self.tokenizer._build_translation_inputs(
										    '''A test'''       ,			return_tensors='''pt'''       ,			src_lang='''en_XX'''       ,			tgt_lang='''java'''		)

										self.assertEqual(
										    nested_simplify(_A		)       ,			{
										        # A, test, EOS, en_XX
										        '''input_ids''': [[1_50, 2_42, 2, 5_00_03]],
										        '''attention_mask''': [[1, 1, 1, 1]],
										        # java
										        '''forced_bos_token_id''': 5_00_01,
										    }       ,			)





'''simple docstring'''

import unittest
from pathlib import Path
from tempfile import TemporaryDirectory

from transformers import AutoConfig, TFGPTaLMHeadModel, is_keras_nlp_available, is_tf_available
from transformers.models.gpta.tokenization_gpta import GPTaTokenizer
from transformers.testing_utils import require_keras_nlp, require_tf, slow


if is_tf_available():
	import tensorflow as tf

if is_keras_nlp_available():
	from transformers.models.gpta import TFGPTaTokenizer


_UpperCAmelCase				: str							    =				["""gpt2"""]
_UpperCAmelCase				: Optional[int]							    =				"""gpt2"""

if is_tf_available():


	class       a__				( tf.Module      ):







					"""simple docstring"""



					def __init__(self       ,			__lowercase		):
											super().__init__()
											__lowerCAmelCase							       =				tokenizer
											__lowerCAmelCase							       =				AutoConfig.from_pretrained(__lowercase		)
											__lowerCAmelCase							       =				TFGPTaLMHeadModel.from_config(__lowercase		)




					@tf.function(input_signature=(tf.TensorSpec((None,)       ,			tf.string       ,			name='''text'''		),)		)
					def 					_snake_case  (self       ,			__lowercase		):
											__lowerCAmelCase							       =				self.tokenizer(__lowercase		)
											__lowerCAmelCase							       =				tokenized['''input_ids'''].to_tensor()

											__lowerCAmelCase							       =				tf.cast(input_ids_dense > 0       ,			tf.intaa		)
											# input_mask = tf.reshape(input_mask, [-1, MAX_SEQ_LEN])

											__lowerCAmelCase							       =				self.model(input_ids=__lowercase       ,			attention_mask=__lowercase		)['''logits''']

											return outputs


@require_tf
@require_keras_nlp
class       a__				( unittest.TestCase      ):







				"""simple docstring"""



				def 					_snake_case  (self		):
										super().setUp()

										__lowerCAmelCase							       =				[GPTaTokenizer.from_pretrained(__lowercase		) for checkpoint in (TOKENIZER_CHECKPOINTS)]
										__lowerCAmelCase							       =				[TFGPTaTokenizer.from_pretrained(__lowercase		) for checkpoint in TOKENIZER_CHECKPOINTS]
										assert len(self.tokenizers		) == len(self.tf_tokenizers		)

										__lowerCAmelCase							       =				[
										    '''This is a straightforward English test sentence.''',
										    '''This one has some weird characters\rto\nsee\r\nif  those\u00E9break things.''',
										    '''Now we\'re going to add some Chinese: 一 二 三 一二三''',
										    '''And some much more rare Chinese: 齉 堃 齉堃''',
										    '''Je vais aussi écrire en français pour tester les accents''',
										    '''Classical Irish also has some unusual characters, so in they go: Gaelaċ, ꝼ''',
										]
										__lowerCAmelCase							       =				list(zip(self.test_sentences       ,			self.test_sentences[::-1]		)		)




				def 					_snake_case  (self		):
										for tokenizer, tf_tokenizer in zip(self.tokenizers       ,			self.tf_tokenizers		):
																for test_inputs in self.test_sentences:
																						__lowerCAmelCase							       =				tokenizer([test_inputs]       ,			return_tensors='''tf'''		)
																						__lowerCAmelCase							       =				tf_tokenizer([test_inputs]		)

																						for key in python_outputs.keys():
																												# convert them to numpy to avoid messing with ragged tensors
																												__lowerCAmelCase							       =				python_outputs[key].numpy()
																												__lowerCAmelCase							       =				tf_outputs[key].numpy()

																												self.assertTrue(tf.reduce_all(python_outputs_values.shape == tf_outputs_values.shape		)		)
																												self.assertTrue(tf.reduce_all(tf.cast(__lowercase       ,			tf.intaa		) == tf_outputs_values		)		)




				@slow
				def 					_snake_case  (self		):
										for tf_tokenizer in self.tf_tokenizers:
																__lowerCAmelCase							       =				tf.function(__lowercase		)
																for test_inputs in self.test_sentences:
																						__lowerCAmelCase							       =				tf.constant(__lowercase		)
																						__lowerCAmelCase							       =				compiled_tokenizer(__lowercase		)
																						__lowerCAmelCase							       =				tf_tokenizer(__lowercase		)

																						for key in eager_outputs.keys():
																												self.assertTrue(tf.reduce_all(eager_outputs[key] == compiled_outputs[key]		)		)




				@slow
				def 					_snake_case  (self		):
										for tf_tokenizer in self.tf_tokenizers:
																__lowerCAmelCase							       =				ModelToSave(tokenizer=__lowercase		)
																__lowerCAmelCase							       =				tf.convert_to_tensor([self.test_sentences[0]]		)
																__lowerCAmelCase							       =				model.serving(__lowercase		)  # Build model with some sample inputs
																with TemporaryDirectory() as tempdir:
																						__lowerCAmelCase							       =				Path(__lowercase		) / '''saved.model'''
																						tf.saved_model.save(__lowercase       ,			__lowercase       ,			signatures={'''serving_default''': model.serving}		)
																						__lowerCAmelCase							       =				tf.saved_model.load(__lowercase		)
																__lowerCAmelCase							       =				loaded_model.signatures['''serving_default'''](__lowercase		)['''output_0''']
																# We may see small differences because the loaded model is compiled, so we need an epsilon for the test
																self.assertTrue(tf.reduce_all(out == loaded_output		)		)




				@slow
				def 					_snake_case  (self		):
										for tf_tokenizer in self.tf_tokenizers:
																__lowerCAmelCase							       =				tf.convert_to_tensor([self.test_sentences[0]]		)
																__lowerCAmelCase							       =				tf_tokenizer(__lowercase		)  # Build model with some sample inputs

																__lowerCAmelCase							       =				tf_tokenizer.get_config()
																__lowerCAmelCase							       =				TFGPTaTokenizer.from_config(__lowercase		)
																__lowerCAmelCase							       =				model_from_config(__lowercase		)

																for key in from_config_output.keys():
																						self.assertTrue(tf.reduce_all(from_config_output[key] == out[key]		)		)




				@slow
				def 					_snake_case  (self		):
										for tf_tokenizer in self.tf_tokenizers:
																# for the test to run
																__lowerCAmelCase							       =				12_31_23

																for max_length in [3, 5, 10_24]:
																						__lowerCAmelCase							       =				tf.convert_to_tensor([self.test_sentences[0]]		)
																						__lowerCAmelCase							       =				tf_tokenizer(__lowercase       ,			max_length=__lowercase		)

																						__lowerCAmelCase							       =				out['''input_ids'''].numpy().shape[1]

																						assert out_length == max_length

