import shutil
import tempfile
import unittest

import numpy as np
import pytest

from transformers.testing_utils import require_torch, require_vision
from transformers.utils import is_torch_available, is_vision_available


if is_torch_available():
     from transformers.pytorch_utils import is_torch_greater_or_equal_than_1_11
else:
     snake_case__						      =			False

if is_vision_available():
     from PIL import Image

     from transformers import (
         AutoProcessor,
         PixaStructImageProcessor,
         PixaStructProcessor,
         PreTrainedTokenizerFast,
         TaTokenizer,
     )



@unittest.skipIf(
    not is_torch_greater_or_equal_than_1_11 ,	reason='`Pix2StructImageProcessor` requires `torch>=1.11.0`.' ,	)
@require_vision
@require_torch
class 			UpperCamelCase					(			unittest.TestCase			):

     '''simple docstring'''

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






           """simple docstring"""
           _lowerCamelCase           =					tempfile.mkdtemp()

           _lowerCamelCase           =					PixaStructImageProcessor()
           _lowerCamelCase           =					TaTokenizer.from_pretrained('''t5-small'''    )

           _lowerCamelCase           =					PixaStructProcessor(A_					,					A_    )

           processor.save_pretrained(self.tmpdirname    )



     def 		UpperCamelCase_    (       self					,					**A_    )			->					List[str]:






           """simple docstring"""
           return AutoProcessor.from_pretrained(self.tmpdirname					,					**A_    ).tokenizer



     def 		UpperCamelCase_    (       self					,					**A_    )			->					Any:






           """simple docstring"""
           return AutoProcessor.from_pretrained(self.tmpdirname					,					**A_    ).image_processor



     def 		UpperCamelCase_    (       self    )			->					Tuple:






           """simple docstring"""
           shutil.rmtree(self.tmpdirname    )



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






           """simple docstring"""
           _lowerCamelCase           =					[np.random.randint(2_55					,					size=(3, 30, 4_00)					,					dtype=np.uinta    )]

           _lowerCamelCase           =					[Image.fromarray(np.moveaxis(A_					,					0					,					-1    )    ) for x in image_inputs]

           return image_inputs



     def 		UpperCamelCase_    (       self    )			->					Any:






           """simple docstring"""
           _lowerCamelCase           =					PixaStructProcessor(tokenizer=self.get_tokenizer()					,					image_processor=self.get_image_processor()    )
           processor.save_pretrained(self.tmpdirname    )

           _lowerCamelCase           =					self.get_tokenizer(bos_token='''(BOS)'''					,					eos_token='''(EOS)'''    )
           _lowerCamelCase           =					self.get_image_processor(do_normalize=A_					,					padding_value=1.0    )

           _lowerCamelCase           =					PixaStructProcessor.from_pretrained(
               self.tmpdirname					,					bos_token='''(BOS)'''					,					eos_token='''(EOS)'''					,					do_normalize=A_					,					padding_value=1.0    )

           self.assertEqual(processor.tokenizer.get_vocab()					,					tokenizer_add_kwargs.get_vocab()    )
           self.assertIsInstance(processor.tokenizer					,					A_    )

           self.assertEqual(processor.image_processor.to_json_string()					,					image_processor_add_kwargs.to_json_string()    )
           self.assertIsInstance(processor.image_processor					,					A_    )



     def 		UpperCamelCase_    (       self    )			->					int:






           """simple docstring"""
           _lowerCamelCase           =					self.get_image_processor()
           _lowerCamelCase           =					self.get_tokenizer()

           _lowerCamelCase           =					PixaStructProcessor(tokenizer=A_					,					image_processor=A_    )

           _lowerCamelCase           =					self.prepare_image_inputs()

           _lowerCamelCase           =					image_processor(A_					,					return_tensors='''np'''    )
           _lowerCamelCase           =					processor(images=A_					,					return_tensors='''np'''    )

           for key in input_feat_extract.keys():
                 self.assertAlmostEqual(input_feat_extract[key].sum()					,					input_processor[key].sum()					,					delta=1E-2    )



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






           """simple docstring"""
           _lowerCamelCase           =					self.get_image_processor()
           _lowerCamelCase           =					self.get_tokenizer()

           _lowerCamelCase           =					PixaStructProcessor(tokenizer=A_					,					image_processor=A_    )

           _lowerCamelCase           =					'''lower newer'''

           _lowerCamelCase           =					processor(text=A_    )

           _lowerCamelCase           =					tokenizer(A_					,					return_token_type_ids=A_					,					add_special_tokens=A_    )

           for key in encoded_tok.keys():
                 self.assertListEqual(encoded_tok[key]					,					encoded_processor[key]    )



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






           """simple docstring"""
           _lowerCamelCase           =					self.get_image_processor()
           _lowerCamelCase           =					self.get_tokenizer()

           _lowerCamelCase           =					PixaStructProcessor(tokenizer=A_					,					image_processor=A_    )

           _lowerCamelCase           =					'''lower newer'''
           _lowerCamelCase           =					self.prepare_image_inputs()

           _lowerCamelCase           =					processor(text=A_					,					images=A_    )

           self.assertListEqual(
               list(inputs.keys()    )					,					['''flattened_patches''', '''attention_mask''', '''decoder_attention_mask''', '''decoder_input_ids''']    )

           # test if it raises when no input is passed
           with pytest.raises(A_    ):
                 processor()



     def 		UpperCamelCase_    (       self    )			->					str:






           """simple docstring"""
           _lowerCamelCase           =					self.get_image_processor()
           _lowerCamelCase           =					self.get_tokenizer()

           _lowerCamelCase           =					PixaStructProcessor(tokenizer=A_					,					image_processor=A_    )

           _lowerCamelCase           =					'''lower newer'''
           _lowerCamelCase           =					self.prepare_image_inputs()

           _lowerCamelCase           =					processor(text=A_					,					images=A_    )

           _lowerCamelCase           =					[5_12, 10_24, 20_48, 40_96]
           _lowerCamelCase           =					[7_70, 7_70, 7_70, 7_70]
           # with text
           for i, max_patch in enumerate(A_    ):
                 _lowerCamelCase           =					processor(text=A_					,					images=A_					,					max_patches=A_    )
                 self.assertEqual(inputs['''flattened_patches'''][0].shape[0]					,					A_    )
                 self.assertEqual(inputs['''flattened_patches'''][0].shape[1]					,					expected_hidden_size[i]    )

           # without text input
           for i, max_patch in enumerate(A_    ):
                 _lowerCamelCase           =					processor(images=A_					,					max_patches=A_    )
                 self.assertEqual(inputs['''flattened_patches'''][0].shape[0]					,					A_    )
                 self.assertEqual(inputs['''flattened_patches'''][0].shape[1]					,					expected_hidden_size[i]    )



     def 		UpperCamelCase_    (       self    )			->					Dict:






           """simple docstring"""
           _lowerCamelCase           =					self.get_image_processor()
           _lowerCamelCase           =					self.get_tokenizer()

           _lowerCamelCase           =					PixaStructProcessor(tokenizer=A_					,					image_processor=A_    )

           _lowerCamelCase           =					[[1, 4, 5, 8, 1, 0, 8], [3, 4, 3, 1, 1, 8, 9]]

           _lowerCamelCase           =					processor.batch_decode(A_    )
           _lowerCamelCase           =					tokenizer.batch_decode(A_    )

           self.assertListEqual(A_					,					A_    )





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






           """simple docstring"""
           _lowerCamelCase           =					self.get_image_processor()
           _lowerCamelCase           =					self.get_tokenizer()

           _lowerCamelCase           =					PixaStructProcessor(tokenizer=A_					,					image_processor=A_    )

           _lowerCamelCase           =					'''lower newer'''
           _lowerCamelCase           =					self.prepare_image_inputs()

           _lowerCamelCase           =					processor(text=A_					,					images=A_    )

           # For now the processor supports only ["flattened_patches", "input_ids", "attention_mask", "decoder_attention_mask"]
           self.assertListEqual(
               list(inputs.keys()    )					,					['''flattened_patches''', '''attention_mask''', '''decoder_attention_mask''', '''decoder_input_ids''']    )

           _lowerCamelCase           =					processor(text=A_    )

           # For now the processor supports only ["flattened_patches", "input_ids", "attention_mask", "decoder_attention_mask"]
           self.assertListEqual(list(inputs.keys()    )					,					['''input_ids''', '''attention_mask''']    )
from ..utils import deprecate
from .attention_processor import (  # noqa: F401
    Attention,
    AttentionProcessor,
    AttnAddedKVProcessor,
    AttnProcessor2_0,
    LoRAAttnProcessor,
    LoRALinearLayer,
    LoRAXFormersAttnProcessor,
    SlicedAttnAddedKVProcessor,
    SlicedAttnProcessor,
    XFormersAttnProcessor,
)
from .attention_processor import AttnProcessor as AttnProcessorRename  # noqa: F401


deprecate(
    'cross_attention',
    '0.20.0',
    'Importing from cross_attention is deprecated. Please import from diffusers.models.attention_processor instead.',
    standard_warn=False,
)


snake_case__						      =			AttentionProcessor



class 			UpperCamelCase					(			__lowercase			):

     '''simple docstring'''

     def __init__(       self					,					*A_					,					**A_    )			->					Union[str, Any]:






           """simple docstring"""
           _lowerCamelCase           =					F'{self.__class__.__name__} is deprecated and will be removed in `0.20.0`. Please use `from diffusers.models.attention_processor import {"".join(self.__class__.__name__.split("Cross"    )    )} instead.'
           deprecate('''cross_attention'''					,					'''0.20.0'''					,					A_					,					standard_warn=A_    )
           super().__init__(*A_					,					**A_    )





class 			UpperCamelCase					(			__lowercase			):

     '''simple docstring'''

     def __init__(       self					,					*A_					,					**A_    )			->					List[Any]:






           """simple docstring"""
           _lowerCamelCase           =					F'{self.__class__.__name__} is deprecated and will be removed in `0.20.0`. Please use `from diffusers.models.attention_processor import {"".join(self.__class__.__name__.split("Cross"    )    )} instead.'
           deprecate('''cross_attention'''					,					'''0.20.0'''					,					A_					,					standard_warn=A_    )
           super().__init__(*A_					,					**A_    )





class 			UpperCamelCase					(			__lowercase			):

     '''simple docstring'''

     def __init__(       self					,					*A_					,					**A_    )			->					Optional[int]:






           """simple docstring"""
           _lowerCamelCase           =					F'{self.__class__.__name__} is deprecated and will be removed in `0.20.0`. Please use `from diffusers.models.attention_processor import {"".join(self.__class__.__name__.split("Cross"    )    )} instead.'
           deprecate('''cross_attention'''					,					'''0.20.0'''					,					A_					,					standard_warn=A_    )
           super().__init__(*A_					,					**A_    )





class 			UpperCamelCase					(			__lowercase			):

     '''simple docstring'''

     def __init__(       self					,					*A_					,					**A_    )			->					Optional[int]:






           """simple docstring"""
           _lowerCamelCase           =					F'{self.__class__.__name__} is deprecated and will be removed in `0.20.0`. Please use `from diffusers.models.attention_processor import {"".join(self.__class__.__name__.split("Cross"    )    )} instead.'
           deprecate('''cross_attention'''					,					'''0.20.0'''					,					A_					,					standard_warn=A_    )
           super().__init__(*A_					,					**A_    )





class 			UpperCamelCase					(			__lowercase			):

     '''simple docstring'''

     def __init__(       self					,					*A_					,					**A_    )			->					Tuple:






           """simple docstring"""
           _lowerCamelCase           =					F'{self.__class__.__name__} is deprecated and will be removed in `0.20.0`. Please use `from diffusers.models.attention_processor import {"".join(self.__class__.__name__.split("Cross"    )    )} instead.'
           deprecate('''cross_attention'''					,					'''0.20.0'''					,					A_					,					standard_warn=A_    )
           super().__init__(*A_					,					**A_    )





class 			UpperCamelCase					(			__lowercase			):

     '''simple docstring'''

     def __init__(       self					,					*A_					,					**A_    )			->					int:






           """simple docstring"""
           _lowerCamelCase           =					F'{self.__class__.__name__} is deprecated and will be removed in `0.20.0`. Please use `from diffusers.models.attention_processor import {"".join(self.__class__.__name__.split("Cross"    )    )} instead.'
           deprecate('''cross_attention'''					,					'''0.20.0'''					,					A_					,					standard_warn=A_    )
           super().__init__(*A_					,					**A_    )





class 			UpperCamelCase					(			__lowercase			):

     '''simple docstring'''

     def __init__(       self					,					*A_					,					**A_    )			->					Optional[int]:






           """simple docstring"""
           _lowerCamelCase           =					F'{self.__class__.__name__} is deprecated and will be removed in `0.20.0`. Please use `from diffusers.models.attention_processor import {"".join(self.__class__.__name__.split("Cross"    )    )} instead.'
           deprecate('''cross_attention'''					,					'''0.20.0'''					,					A_					,					standard_warn=A_    )
           super().__init__(*A_					,					**A_    )





class 			UpperCamelCase					(			__lowercase			):

     '''simple docstring'''

     def __init__(       self					,					*A_					,					**A_    )			->					Dict:






           """simple docstring"""
           _lowerCamelCase           =					F'{self.__class__.__name__} is deprecated and will be removed in `0.20.0`. Please use `from diffusers.models.attention_processor import {"".join(self.__class__.__name__.split("Cross"    )    )} instead.'
           deprecate('''cross_attention'''					,					'''0.20.0'''					,					A_					,					standard_warn=A_    )
           super().__init__(*A_					,					**A_    )