
'''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       _lowerCAmelCase   (   __snake_case					,							unittest.TestCase				):







							'''simple docstring'''

							lowerCAmelCase_ 						=						PLBartTokenizer
							lowerCAmelCase_ 						=						None
							lowerCAmelCase_ 						=						False

							def 	lowercase							(self  )					->       str:
														super().setUp()

														# We have a SentencePiece fixture for testing
														_snake_case       =  PLBartTokenizer(UpperCAmelCase  ,  language_codes="""base"""  ,  keep_accents=UpperCAmelCase  )
														tokenizer.save_pretrained(self.tmpdirname  )

							def 	lowercase							(self  )					->       Any:
														_snake_case       =  PLBartTokenizer(UpperCAmelCase  ,  language_codes="""base"""  ,  keep_accents=UpperCAmelCase  )

														_snake_case       =  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]]  ,  )

														_snake_case       =  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""",
														        """.""",
														    ]  ,  )
														_snake_case       =  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]
														    ]  ,  )

														_snake_case       =  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>""",
														        """.""",
														    ]  ,  )

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

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

														_snake_case       =  """java.lang.Exception, python.lang.Exception, javascript, php, ruby, go"""
														_snake_case       =  tokenizer(UpperCAmelCase  ).input_ids
														self.assertEqual(
														    tokenizer.decode(UpperCAmelCase  ,  skip_special_tokens=UpperCAmelCase  ,  clean_up_tokenization_spaces=UpperCAmelCase  )  ,  UpperCAmelCase  ,  )





							def 	lowercase							(self  )					->       Any:
														_snake_case       =  PLBartTokenizer(UpperCAmelCase  ,  language_codes="""multi"""  ,  keep_accents=UpperCAmelCase  )

														_snake_case       =  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]]  ,  )

														_snake_case       =  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""",
														        """.""",
														    ]  ,  )
														_snake_case       =  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]
														    ]  ,  )

														_snake_case       =  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>""",
														        """.""",
														    ]  ,  )
														_snake_case       =  tokenizer.vocab_size
														_snake_case       =  [tokenizer.convert_ids_to_tokens(UpperCAmelCase  ) for x in range(end - 7  ,  UpperCAmelCase  )]

														self.assertListEqual(
														    UpperCAmelCase  ,  ["""__java__""", """__python__""", """__en_XX__""", """__javascript__""", """__php__""", """__ruby__""", """__go__"""]  )
														_snake_case       =  """java.lang.Exception, python.lang.Exception, javascript, php, ruby, go"""
														_snake_case       =  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       _lowerCAmelCase   (   unittest.TestCase				):







							'''simple docstring'''

							lowerCAmelCase_ 						=						"uclanlp/plbart-python-en_XX"
							lowerCAmelCase_ 						=						[
							    "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_ 						=						[
							    "Returns the maximum value of a b c.",
							    "Sums the values of a b c.",
							]
							lowerCAmelCase_ 						=						[
							    1_34,
							    54_52,
							    3_34_60,
							    3_34_41,
							    3_34_63,
							    3_34_65,
							    3_34_63,
							    3_34_49,
							    9_88,
							    20,
							    3_34_56,
							    19,
							    3_34_56,
							    7_71,
							    39,
							    42_58,
							    8_89,
							    33_18,
							    3_34_41,
							    3_34_63,
							    3_34_65,
							    3_34_63,
							    3_34_49,
							    24_71,
							    2,
							    PYTHON_CODE,
							]

							@classmethod
							def 	lowercase							(cls  )					->       Optional[int]:
														_snake_case       =  PLBartTokenizer.from_pretrained(
														    cls.checkpoint_name  ,  language_codes="""base"""  ,  src_lang="""python"""  ,  tgt_lang="""en_XX"""  )
														_snake_case       =  1
														return cls

							def 	lowercase							(self  )					->       List[str]:
														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  )					->       Dict:
														_snake_case       =  self.tokenizer.batch_encode_plus(self.src_text  ).input_ids[0]
														self.assertListEqual(self.expected_src_tokens  ,  UpperCAmelCase  )

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

							def 	lowercase							(self  )					->       Any:
														_snake_case       =  ["""def sum(a,b,c):NEW_LINE_INDENTreturn sum([a,b,c])""" * 20]
														self.assertIsInstance(src_text[0]  ,  UpperCAmelCase  )
														_snake_case       =  10
														_snake_case       =  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  )					->       Dict:
														self.assertListEqual(self.tokenizer.convert_tokens_to_ids(["""<mask>""", """__java__"""]  )  ,  [50004, 50001]  )

							def 	lowercase							(self  )					->       int:
														_snake_case       =  tempfile.mkdtemp()
														_snake_case       =  self.tokenizer.fairseq_tokens_to_ids
														self.tokenizer.save_pretrained(UpperCAmelCase  )
														_snake_case       =  PLBartTokenizer.from_pretrained(UpperCAmelCase  )
														self.assertDictEqual(new_tok.fairseq_tokens_to_ids  ,  UpperCAmelCase  )

							@require_torch
							def 	lowercase							(self  )					->       List[str]:
														_snake_case       =  self.tokenizer(self.src_text  ,  text_target=self.tgt_text  ,  padding=UpperCAmelCase  ,  return_tensors="""pt"""  )
														_snake_case       =  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  )					->       Tuple:
														_snake_case       =  self.tokenizer(
														    self.src_text  ,  text_target=self.tgt_text  ,  padding=UpperCAmelCase  ,  truncation=UpperCAmelCase  ,  max_length=len(self.expected_src_tokens  )  ,  return_tensors="""pt"""  ,  )
														_snake_case       =  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  )
														_snake_case       =  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  )					->       str:
														_snake_case       =  self.tokenizer(self.src_text  ,  padding=UpperCAmelCase  ,  truncation=UpperCAmelCase  ,  max_length=3  ,  return_tensors="""pt"""  )
														_snake_case       =  self.tokenizer(
														    text_target=self.tgt_text  ,  padding=UpperCAmelCase  ,  truncation=UpperCAmelCase  ,  max_length=10  ,  return_tensors="""pt"""  )
														_snake_case       =  targets["""input_ids"""]
														_snake_case       =  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  )					->       List[Any]:
														_snake_case       =  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'''
from ...utils import (
    OptionalDependencyNotAvailable,
    is_flax_available,
    is_torch_available,
    is_transformers_available,
)


try:
				if not (is_transformers_available() and is_torch_available()):
								raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
				from ...utils.dummy_torch_and_transformers_objects import *  # noqa F403
else:
				from .multicontrolnet import MultiControlNetModel
				from .pipeline_controlnet import StableDiffusionControlNetPipeline
				from .pipeline_controlnet_imgaimg import StableDiffusionControlNetImgaImgPipeline
				from .pipeline_controlnet_inpaint import StableDiffusionControlNetInpaintPipeline


if is_transformers_available() and is_flax_available():
				from .pipeline_flax_controlnet import FlaxStableDiffusionControlNetPipeline