




import unittest

from transformers import AlbertTokenizer, AlbertTokenizerFast
from transformers.testing_utils import get_tests_dir, require_sentencepiece, require_tokenizers, slow

from ...test_tokenization_common import TokenizerTesterMixin


_lowerCamelCase			:	str							 =     get_tests_dir("""fixtures/spiece.model""")


@require_sentencepiece
@require_tokenizers
class        UpperCamelCase_					(				UpperCAmelCase__	,      unittest.TestCase  ):

				'''simple docstring'''






				UpperCAmelCase__													=   AlbertTokenizer
				UpperCAmelCase__													=   AlbertTokenizerFast
				UpperCAmelCase__													=   True
				UpperCAmelCase__													=   True
				UpperCAmelCase__													=   True


				def  SCREAMING_SNAKE_CASE							(    self   :			Tuple)		->Optional[int]:





											'''simple docstring'''

											super().setUp()

											# We have a SentencePiece fixture for testing
											A__   				=					AlbertTokenizer(UpperCAmelCase__)
											tokenizer.save_pretrained(self.tmpdirname)


				def  SCREAMING_SNAKE_CASE							(    self   :			int      ,				UpperCAmelCase__   :			Union[str, Any])		->List[Any]:





											'''simple docstring'''

											A__   				=					'''this is a test'''
											A__   				=					'''this is a test'''
											return input_text, output_text


				def  SCREAMING_SNAKE_CASE							(    self   :			Optional[int])		->str:





											'''simple docstring'''

											A__   				=					'''<pad>'''
											A__   				=					0

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


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





											'''simple docstring'''

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

											self.assertEqual(vocab_keys[0]      ,				'''<pad>''')
											self.assertEqual(vocab_keys[1]      ,				'''<unk>''')
											self.assertEqual(vocab_keys[-1]      ,				'''▁eloquent''')
											self.assertEqual(len(UpperCAmelCase__)      ,				30_000)


				def  SCREAMING_SNAKE_CASE							(    self   :			str)		->List[Any]:





											'''simple docstring'''

											self.assertEqual(self.get_tokenizer().vocab_size      ,				30_000)


				def  SCREAMING_SNAKE_CASE							(    self   :			Optional[Any])		->List[str]:





											'''simple docstring'''

											if not self.test_rust_tokenizer:
																		return

											A__   				=					self.get_tokenizer()
											A__   				=					self.get_rust_tokenizer()

											A__   				=					'''I was born in 92000, and this is falsé.'''

											A__   				=					tokenizer.tokenize(UpperCAmelCase__)
											A__   				=					rust_tokenizer.tokenize(UpperCAmelCase__)
											self.assertListEqual(UpperCAmelCase__      ,				UpperCAmelCase__)

											A__   				=					tokenizer.encode(UpperCAmelCase__      ,				add_special_tokens=UpperCAmelCase__)
											A__   				=					rust_tokenizer.encode(UpperCAmelCase__      ,				add_special_tokens=UpperCAmelCase__)
											self.assertListEqual(UpperCAmelCase__      ,				UpperCAmelCase__)

											A__   				=					self.get_rust_tokenizer()
											A__   				=					tokenizer.encode(UpperCAmelCase__)
											A__   				=					rust_tokenizer.encode(UpperCAmelCase__)
											self.assertListEqual(UpperCAmelCase__      ,				UpperCAmelCase__)


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





											'''simple docstring'''

											A__   				=					AlbertTokenizer(UpperCAmelCase__      ,				keep_accents=UpperCAmelCase__)

											A__   				=					tokenizer.tokenize('''This is a test''')
											self.assertListEqual(UpperCAmelCase__      ,				['''▁this''', '''▁is''', '''▁a''', '''▁test'''])

											self.assertListEqual(tokenizer.convert_tokens_to_ids(UpperCAmelCase__)      ,				[48, 25, 21, 1_289])

											A__   				=					tokenizer.tokenize('''I was born in 92000, and this is falsé.''')
											self.assertListEqual(
											    UpperCAmelCase__      ,				['''▁i''', '''▁was''', '''▁born''', '''▁in''', '''▁9''', '''2000''', ''',''', '''▁and''', '''▁this''', '''▁is''', '''▁fal''', '''s''', '''é''', '''.'''])
											A__   				=					tokenizer.convert_tokens_to_ids(UpperCAmelCase__)
											self.assertListEqual(UpperCAmelCase__      ,				[31, 23, 386, 19, 561, 3_050, 15, 17, 48, 25, 8_256, 18, 1, 9])

											A__   				=					tokenizer.convert_ids_to_tokens(UpperCAmelCase__)
											self.assertListEqual(
											    UpperCAmelCase__      ,				['''▁i''', '''▁was''', '''▁born''', '''▁in''', '''▁9''', '''2000''', ''',''', '''▁and''', '''▁this''', '''▁is''', '''▁fal''', '''s''', '''<unk>''', '''.''']      ,				)


				def  SCREAMING_SNAKE_CASE							(    self   :			Optional[Any])		->Dict:





											'''simple docstring'''

											A__   				=					AlbertTokenizer(UpperCAmelCase__)

											A__   				=					tokenizer.encode('''sequence builders''')
											A__   				=					tokenizer.encode('''multi-sequence build''')

											A__   				=					tokenizer.build_inputs_with_special_tokens(UpperCAmelCase__)
											A__   				=					tokenizer.build_inputs_with_special_tokens(UpperCAmelCase__      ,				UpperCAmelCase__)

											assert encoded_sentence == [tokenizer.cls_token_id] + text + [tokenizer.sep_token_id]
											assert encoded_pair == [tokenizer.cls_token_id] + text + [tokenizer.sep_token_id] + text_a + [
											    tokenizer.sep_token_id
											]





				@slow
				def  SCREAMING_SNAKE_CASE							(    self   :			List[Any])		->Optional[int]:





											'''simple docstring'''

											A__   				=					{'''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, 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, 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, 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, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0]], '''input_ids''': [[2, 21_970, 13, 5, 6_092, 167, 28, 7_103, 2_153, 673, 8, 7_028, 12_051, 18, 17, 7_103, 2_153, 673, 8, 3_515, 18_684, 8, 4_461, 6, 1_927, 297, 8, 12_060, 2_607, 18, 13, 5, 4_461, 15, 10_538, 38, 8, 135, 15, 822, 58, 15, 993, 10_363, 15, 1_460, 8_005, 4_461, 15, 993, 255, 2_328, 9, 9, 9, 6, 26, 1_112, 816, 3_260, 13, 5, 103, 2_377, 6, 17, 1_112, 816, 2_782, 13, 5, 103, 10_641, 6, 29, 84, 2_512, 2_430, 782, 18_684, 2_761, 19, 808, 2_430, 2_556, 17, 855, 1_480, 9_477, 4_091, 128, 11_712, 15, 7_103, 2_153, 673, 17, 24_883, 9_990, 9, 3], [2, 11_502, 25, 1_006, 20, 782, 8, 11_809, 855, 1_732, 19_393, 18_667, 37, 367, 21_018, 69, 1_854, 34, 11_860, 19_124, 27, 156, 225, 17, 193, 4_141, 19, 65, 9_124, 9, 3, 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], [2, 14, 2_231, 886, 2_385, 17_659, 84, 14, 16_792, 1_952, 9, 3, 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, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0]], '''token_type_ids''': [[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, 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, 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, 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, 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=UpperCAmelCase__      ,				model_name='''albert-base-v2'''      ,				revision='''6b6560eaf5ff2e250b00c50f380c5389a9c2d82e'''      ,				)








import random
import unittest

import torch

from diffusers import IFInpaintingPipeline
from diffusers.utils import floats_tensor
from diffusers.utils.import_utils import is_xformers_available
from diffusers.utils.testing_utils import skip_mps, torch_device

from ..pipeline_params import (
    TEXT_GUIDED_IMAGE_INPAINTING_BATCH_PARAMS,
    TEXT_GUIDED_IMAGE_INPAINTING_PARAMS,
)
from ..test_pipelines_common import PipelineTesterMixin
from . import IFPipelineTesterMixin


@skip_mps
class        UpperCamelCase_					(				UpperCAmelCase__	,      UpperCAmelCase__	,      unittest.TestCase  ):

    '''simple docstring'''






    UpperCAmelCase__													=   IFInpaintingPipeline
    UpperCAmelCase__													=   TEXT_GUIDED_IMAGE_INPAINTING_PARAMS - {'''width''', '''height'''}
    UpperCAmelCase__													=   TEXT_GUIDED_IMAGE_INPAINTING_BATCH_PARAMS
    UpperCAmelCase__													=   PipelineTesterMixin.required_optional_params - {'''latents'''}


    def  SCREAMING_SNAKE_CASE							(    self   :			Any)		->Dict:





           '''simple docstring'''

           return self._get_dummy_components()


    def  SCREAMING_SNAKE_CASE							(    self   :			int      ,				UpperCAmelCase__   :			Dict      ,				UpperCAmelCase__   :			int=0)		->int:





           '''simple docstring'''

           if str(UpperCAmelCase__).startswith('''mps'''):
                  A__   				=					torch.manual_seed(UpperCAmelCase__)
           else:
                  A__   				=					torch.Generator(device=UpperCAmelCase__).manual_seed(UpperCAmelCase__)

           A__   				=					floats_tensor((1, 3, 32, 32)      ,				rng=random.Random(UpperCAmelCase__)).to(UpperCAmelCase__)
           A__   				=					floats_tensor((1, 3, 32, 32)      ,				rng=random.Random(UpperCAmelCase__)).to(UpperCAmelCase__)

           A__   				=					{
               '''prompt''': '''A painting of a squirrel eating a burger''',
               '''image''': image,
               '''mask_image''': mask_image,
               '''generator''': generator,
               '''num_inference_steps''': 2,
               '''output_type''': '''numpy''',
           }

           return inputs


    @unittest.skipIf(
        torch_device != '''cuda''' or not is_xformers_available()      ,				reason='''XFormers attention is only available with CUDA and `xformers` installed'''      ,				)
    def  SCREAMING_SNAKE_CASE							(    self   :			List[str])		->List[Any]:





           '''simple docstring'''

           self._test_xformers_attention_forwardGenerator_pass(expected_max_diff=1e-3)


    def  SCREAMING_SNAKE_CASE							(    self   :			Dict)		->int:





           '''simple docstring'''

           self._test_save_load_optional_components()


    @unittest.skipIf(torch_device != '''cuda'''      ,				reason='''float16 requires CUDA''')
    def  SCREAMING_SNAKE_CASE							(    self   :			Optional[Any])		->List[str]:





           '''simple docstring'''

           super().test_save_load_floataa(expected_max_diff=1e-1)


    def  SCREAMING_SNAKE_CASE							(    self   :			int)		->List[Any]:





           '''simple docstring'''

           self._test_attention_slicing_forward_pass(expected_max_diff=1e-2)


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





           '''simple docstring'''

           self._test_save_load_local()





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





           '''simple docstring'''

           self._test_inference_batch_single_identical(
               expected_max_diff=1e-2      ,				)


