





import unittest

from transformers import PegasusTokenizer, PegasusTokenizerFast
from transformers.testing_utils import get_tests_dir, require_sentencepiece, require_tokenizers, require_torch, slow
from transformers.utils import cached_property

from ...test_tokenization_common import TokenizerTesterMixin


_SCREAMING_SNAKE_CASE   =      get_tests_dir('''fixtures/test_sentencepiece_no_bos.model''')






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







	'''simple docstring'''

	a      :			Optional[Any]     =    PegasusTokenizer
	a      :			Optional[int]     =    PegasusTokenizerFast
	a      :			Union[str, Any]     =    True
	a      :			Dict     =    True


	def   _UpperCAmelCase       (self	)							->							str:







				'''simple docstring'''





				super().setUp()

				# We have a SentencePiece fixture for testing
				__lowercase			  =							PegasusTokenizer(_lowerCamelCase	)
				tokenizer.save_pretrained(self.tmpdirname	)


	@cached_property
	def   _UpperCAmelCase       (self	)							->							Optional[int]:







				'''simple docstring'''





				return PegasusTokenizer.from_pretrained('''google/pegasus-large'''	)


	def   _UpperCAmelCase       (self       ,**_lowerCamelCase	)							->							PegasusTokenizer:







				'''simple docstring'''





				return PegasusTokenizer.from_pretrained(self.tmpdirname       ,**_lowerCamelCase	)


	def   _UpperCAmelCase       (self       ,_lowerCamelCase	)							->							Union[str, Any]:







				'''simple docstring'''





				return ("This is a test", "This is a test")


	def   _UpperCAmelCase       (self	)							->							Optional[int]:







				'''simple docstring'''





				__lowercase			  =							'''</s>'''
				__lowercase			  =							1

				self.assertEqual(self.get_tokenizer()._convert_token_to_id(_lowerCamelCase	)       ,_lowerCamelCase	)
				self.assertEqual(self.get_tokenizer()._convert_id_to_token(_lowerCamelCase	)       ,_lowerCamelCase	)


	def   _UpperCAmelCase       (self	)							->							List[Any]:







				'''simple docstring'''





				__lowercase			  =							list(self.get_tokenizer().get_vocab().keys()	)

				self.assertEqual(vocab_keys[0]       ,'''<pad>'''	)
				self.assertEqual(vocab_keys[1]       ,'''</s>'''	)
				self.assertEqual(vocab_keys[-1]       ,'''v'''	)
				self.assertEqual(len(_lowerCamelCase	)       ,1103	)


	def   _UpperCAmelCase       (self	)							->							Tuple:







				'''simple docstring'''





				self.assertEqual(self.get_tokenizer().vocab_size       ,1103	)


	def   _UpperCAmelCase       (self	)							->							Optional[Any]:







				'''simple docstring'''





				__lowercase			  =							self.rust_tokenizer_class.from_pretrained(self.tmpdirname	)
				__lowercase			  =							self.tokenizer_class.from_pretrained(self.tmpdirname	)
				__lowercase			  =							(
				    '''Let\'s see which <unk> is the better <unk_token_11> one <mask_1> It seems like this <mask_2> was important'''
				    ''' </s> <pad> <pad> <pad>'''
				)
				__lowercase			  =							rust_tokenizer([raw_input_str]       ,return_tensors=_lowerCamelCase       ,add_special_tokens=_lowerCamelCase	).input_ids[0]
				__lowercase			  =							py_tokenizer([raw_input_str]       ,return_tensors=_lowerCamelCase       ,add_special_tokens=_lowerCamelCase	).input_ids[0]
				self.assertListEqual(_lowerCamelCase       ,_lowerCamelCase	)


	def   _UpperCAmelCase       (self	)							->							List[str]:







				'''simple docstring'''





				__lowercase			  =							self._large_tokenizer
				# <mask_1> masks whole sentence while <mask_2> masks single word
				__lowercase			  =							'''<mask_1> To ensure a <mask_2> flow of bank resolutions.'''
				__lowercase			  =							[2, 413, 615, 114, 3, 1971, 113, 1679, 10710, 107, 1]
				__lowercase			  =							tokenizer([raw_input_str]       ,return_tensors=_lowerCamelCase	).input_ids[0]
				self.assertListEqual(_lowerCamelCase       ,_lowerCamelCase	)


	def   _UpperCAmelCase       (self	)							->							Union[str, Any]:







				'''simple docstring'''





				__lowercase			  =							self._large_tokenizer
				# The tracebacks for the following asserts are **better** without messages or self.assertEqual
				assert tokenizer.vocab_size == 96103
				assert tokenizer.pad_token_id == 0
				assert tokenizer.eos_token_id == 1
				assert tokenizer.offset == 103
				assert tokenizer.unk_token_id == tokenizer.offset + 2 == 105
				assert tokenizer.unk_token == "<unk>"
				assert tokenizer.model_max_length == 1024
				__lowercase			  =							'''To ensure a smooth flow of bank resolutions.'''
				__lowercase			  =							[413, 615, 114, 2291, 1971, 113, 1679, 10710, 107, 1]
				__lowercase			  =							tokenizer([raw_input_str]       ,return_tensors=_lowerCamelCase	).input_ids[0]
				self.assertListEqual(_lowerCamelCase       ,_lowerCamelCase	)
				assert tokenizer.convert_ids_to_tokens([0, 1, 2, 3]	) == ["<pad>", "</s>", "<mask_1>", "<mask_2>"]


	@require_torch
	def   _UpperCAmelCase       (self	)							->							str:







				'''simple docstring'''





				__lowercase			  =							['''This is going to be way too long.''' * 150, '''short example''']
				__lowercase			  =							['''not super long but more than 5 tokens''', '''tiny''']
				__lowercase			  =							self._large_tokenizer(_lowerCamelCase       ,padding=_lowerCamelCase       ,truncation=_lowerCamelCase       ,return_tensors='''pt'''	)
				__lowercase			  =							self._large_tokenizer(
				    text_target=_lowerCamelCase       ,max_length=5       ,padding=_lowerCamelCase       ,truncation=_lowerCamelCase       ,return_tensors='''pt'''	)

				assert batch.input_ids.shape == (2, 1024)
				assert batch.attention_mask.shape == (2, 1024)
				assert targets["input_ids"].shape == (2, 5)
				assert len(_lowerCamelCase	) == 2  # input_ids, attention_mask.


	@slow
	def   _UpperCAmelCase       (self	)							->							int:







				'''simple docstring'''





				__lowercase			  =							{'''input_ids''': [[38979, 143, 18485, 606, 130, 26669, 87686, 121, 54189, 1129, 111, 26669, 87686, 121, 9114, 14787, 121, 13249, 158, 592, 956, 121, 14621, 31576, 143, 62613, 108, 9688, 930, 43430, 11562, 62613, 304, 108, 11443, 897, 108, 9314, 17415, 63399, 108, 11443, 7614, 18316, 118, 4284, 7148, 12430, 143, 1400, 25703, 158, 111, 4284, 7148, 11772, 143, 21297, 1064, 158, 122, 204, 3506, 1754, 1133, 14787, 1581, 115, 33224, 4482, 111, 1355, 110, 29173, 317, 50833, 108, 20147, 94665, 111, 77198, 107, 1], [110, 62613, 117, 638, 112, 1133, 121, 20098, 1355, 79050, 13872, 135, 1596, 53541, 1352, 141, 13039, 5542, 124, 302, 518, 111, 268, 2956, 115, 149, 4427, 107, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [139, 1235, 2799, 18289, 17780, 204, 109, 9474, 1296, 107, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0]], '''attention_mask''': [[1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1], [1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0]]}  # noqa: E501
				# fmt: on

				self.tokenizer_integration_test_util(
				    expected_encoding=_lowerCamelCase       ,model_name='''google/bigbird-pegasus-large-arxiv'''       ,revision='''ba85d0851d708441f91440d509690f1ab6353415'''       ,)






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







	'''simple docstring'''

	a      :			List[str]     =    PegasusTokenizer
	a      :			Tuple     =    PegasusTokenizerFast
	a      :			Optional[int]     =    True
	a      :			str     =    True


	def   _UpperCAmelCase       (self	)							->							Optional[int]:







				'''simple docstring'''





				super().setUp()

				# We have a SentencePiece fixture for testing
				__lowercase			  =							PegasusTokenizer(_lowerCamelCase       ,offset=0       ,mask_token_sent=_lowerCamelCase       ,mask_token='''[MASK]'''	)
				tokenizer.save_pretrained(self.tmpdirname	)


	@cached_property
	def   _UpperCAmelCase       (self	)							->							Tuple:







				'''simple docstring'''





				return PegasusTokenizer.from_pretrained('''google/bigbird-pegasus-large-arxiv'''	)


	def   _UpperCAmelCase       (self       ,**_lowerCamelCase	)							->							PegasusTokenizer:







				'''simple docstring'''





				return PegasusTokenizer.from_pretrained(self.tmpdirname       ,**_lowerCamelCase	)


	def   _UpperCAmelCase       (self       ,_lowerCamelCase	)							->							int:







				'''simple docstring'''





				return ("This is a test", "This is a test")


	def   _UpperCAmelCase       (self	)							->							Union[str, Any]:







				'''simple docstring'''





				__lowercase			  =							self.rust_tokenizer_class.from_pretrained(self.tmpdirname	)
				__lowercase			  =							self.tokenizer_class.from_pretrained(self.tmpdirname	)
				__lowercase			  =							(
				    '''Let\'s see which <unk> is the better <unk_token> one [MASK] It seems like this [MASK] was important </s>'''
				    ''' <pad> <pad> <pad>'''
				)
				__lowercase			  =							rust_tokenizer([raw_input_str]       ,return_tensors=_lowerCamelCase       ,add_special_tokens=_lowerCamelCase	).input_ids[0]
				__lowercase			  =							py_tokenizer([raw_input_str]       ,return_tensors=_lowerCamelCase       ,add_special_tokens=_lowerCamelCase	).input_ids[0]
				self.assertListEqual(_lowerCamelCase       ,_lowerCamelCase	)


	@require_torch
	def   _UpperCAmelCase       (self	)							->							Tuple:







				'''simple docstring'''





				__lowercase			  =							['''This is going to be way too long.''' * 1000, '''short example''']
				__lowercase			  =							['''not super long but more than 5 tokens''', '''tiny''']
				__lowercase			  =							self._large_tokenizer(_lowerCamelCase       ,padding=_lowerCamelCase       ,truncation=_lowerCamelCase       ,return_tensors='''pt'''	)
				__lowercase			  =							self._large_tokenizer(
				    text_target=_lowerCamelCase       ,max_length=5       ,padding=_lowerCamelCase       ,truncation=_lowerCamelCase       ,return_tensors='''pt'''	)

				assert batch.input_ids.shape == (2, 4096)
				assert batch.attention_mask.shape == (2, 4096)
				assert targets["input_ids"].shape == (2, 5)
				assert len(_lowerCamelCase	) == 2  # input_ids, attention_mask.


	def   _UpperCAmelCase       (self	)							->							List[Any]:







				'''simple docstring'''





				__lowercase			  =							(
				    '''This is an example string that is used to test the original TF implementation against the HF'''
				    ''' implementation'''
				)

				__lowercase			  =							self._large_tokenizer(_lowerCamelCase	).input_ids

				self.assertListEqual(
				    _lowerCamelCase       ,[182, 117, 142, 587, 4211, 120, 117, 263, 112, 804, 109, 856, 25016, 3137, 464, 109, 26955, 3137, 1]       ,)












'''simple docstring'''



# NOTE: This file is deprecated and will be removed in a future version.
# It only exists so that temporarely `from diffusers.pipelines import DiffusionPipeline` works

from ...utils import deprecate
from ..controlnet.pipeline_flax_controlnet import FlaxStableDiffusionControlNetPipeline  # noqa: F401


deprecate(
    '''stable diffusion controlnet''',
    '''0.22.0''',
    '''Importing `FlaxStableDiffusionControlNetPipeline` from diffusers.pipelines.stable_diffusion.flax_pipeline_stable_diffusion_controlnet is deprecated. Please import `from diffusers import FlaxStableDiffusionControlNetPipeline` instead.''',
    standard_warn=False,
    stacklevel=3,
)





