



'''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							:int       = get_tests_dir('''fixtures/test_sentencepiece.model''')


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

lowerCamelCase							:Optional[Any]       = 5_0_0_0_3
lowerCamelCase							:List[Any]       = 5_0_0_0_2







@require_sentencepiece
@require_tokenizers
class      _lowerCAmelCase							(      __UpperCAmelCase				,      unittest.TestCase			):
	__SCREAMING_SNAKE_CASE       :		Any		      = PLBartTokenizer
	__SCREAMING_SNAKE_CASE       :		List[Any]		      = None
	__SCREAMING_SNAKE_CASE       :		str		      = False


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

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


	def    _a     (self							):
				A_     :						Optional[int]     =					PLBartTokenizer(lowercase	,				language_codes="""base"""	,				keep_accents=lowercase							)

				A_     :						List[str]     =					tokenizer.tokenize("""This is a test"""							)
				self.assertListEqual(lowercase	,				["""▁This""", """▁is""", """▁a""", """▁t""", """est"""]							)

				self.assertListEqual(
				    tokenizer.convert_tokens_to_ids(lowercase							)	,				[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(
				    lowercase	,				[
				        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_     :						Any     =					tokenizer.convert_tokens_to_ids(lowercase							)
				self.assertListEqual(
				    lowercase	,				[
				        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(lowercase							)
				self.assertListEqual(
				    lowercase	,				[
				        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_     :						int     =					tokenizer.vocab_size
				A_     :						Tuple     =					[tokenizer.convert_ids_to_tokens(lowercase							) for x in range(end - 4	,				lowercase							)]

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

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


	def    _a     (self							):
				A_     :						Union[str, Any]     =					PLBartTokenizer(lowercase	,				language_codes="""multi"""	,				keep_accents=lowercase							)

				A_     :						List[str]     =					tokenizer.tokenize("""This is a test"""							)
				self.assertListEqual(lowercase	,				["""▁This""", """▁is""", """▁a""", """▁t""", """est"""]							)

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

				A_     :						Optional[Any]     =					tokenizer.tokenize("""I was born in 92000, and this is falsé."""							)
				self.assertListEqual(
				    lowercase	,				[
				        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(lowercase							)
				self.assertListEqual(
				    lowercase	,				[
				        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_     :						Any     =					tokenizer.convert_ids_to_tokens(lowercase							)
				self.assertListEqual(
				    lowercase	,				[
				        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_     :						Optional[int]     =					[tokenizer.convert_ids_to_tokens(lowercase							) for x in range(end - 7	,				lowercase							)]

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







@require_torch
@require_sentencepiece
@require_tokenizers
class      _lowerCAmelCase							(      unittest.TestCase			):
	__SCREAMING_SNAKE_CASE       :		str		      = 'uclanlp/plbart-python-en_XX'
	__SCREAMING_SNAKE_CASE       :		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])',
	]
	__SCREAMING_SNAKE_CASE       :		List[str]		      = [
	    'Returns the maximum value of a b c.',
	    'Sums the values of a b c.',
	]
	__SCREAMING_SNAKE_CASE       :		Optional[Any]		      = [
	    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    _a     (cls							):
				A_     :						PLBartTokenizer     =					PLBartTokenizer.from_pretrained(
				    cls.checkpoint_name	,				language_codes="""base"""	,				src_lang="""python"""	,				tgt_lang="""en_XX"""							)
				A_     :						int     =					1
				return cls


	def    _a     (self							):
				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    _a     (self							):
				A_     :						str     =					self.tokenizer.batch_encode_plus(self.src_text							).input_ids[0]
				self.assertListEqual(self.expected_src_tokens	,				lowercase							)


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


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


	def    _a     (self							):
				self.assertListEqual(self.tokenizer.convert_tokens_to_ids(["""<mask>""", """__java__"""]							)	,				[50004, 50001]							)


	def    _a     (self							):
				A_     :						Optional[int]     =					tempfile.mkdtemp()
				A_     :						Any     =					self.tokenizer.fairseq_tokens_to_ids
				self.tokenizer.save_pretrained(lowercase							)
				A_     :						Optional[int]     =					PLBartTokenizer.from_pretrained(lowercase							)
				self.assertDictEqual(new_tok.fairseq_tokens_to_ids	,				lowercase							)


	@require_torch
	def    _a     (self							):
				A_     :						Dict     =					self.tokenizer(self.src_text	,				text_target=self.tgt_text	,				padding=lowercase	,				return_tensors="""pt"""							)
				A_     :						Optional[Any]     =					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]	,				lowercase							)
				self.assertEqual(batch.decoder_input_ids[1][-1]	,				2							)
				self.assertEqual(batch.labels[1][-2:].tolist()	,				[2, EN_CODE]							)


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

				self.assertIsInstance(lowercase	,				lowercase							)

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

				self.assertEqual(
				    nested_simplify(lowercase							)	,				{
				        # 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'''




from typing import TYPE_CHECKING

from ....utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available


lowerCamelCase							:Dict       = {'''configuration_mmbt''': ['''MMBTConfig''']}

try:
						if not is_torch_available():
												raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
						pass
else:
						lowerCamelCase							:str       = ['''MMBTForClassification''', '''MMBTModel''', '''ModalEmbeddings''']


if TYPE_CHECKING:
						from .configuration_mmbt import MMBTConfig

						try:
												if not is_torch_available():
																		raise OptionalDependencyNotAvailable()
						except OptionalDependencyNotAvailable:
												pass
						else:
												from .modeling_mmbt import MMBTForClassification, MMBTModel, ModalEmbeddings

else:
						import sys

						lowerCamelCase							:Tuple       = _LazyModule(__name__, globals()['''__file__'''], _import_structure, module_spec=__spec__)