



"""simple docstring"""

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    __lowercase     (					_UpperCAmelCase					,    _UpperCAmelCase					,    unittest.TestCase):







						"""simple docstring"""







						_A		:							Union[str, Any]							       =		IFInpaintingPipeline
						_A		:							Optional[Any]							       =		TEXT_GUIDED_IMAGE_INPAINTING_PARAMS - {"""width""", """height"""}
						_A		:							Optional[int]							       =		TEXT_GUIDED_IMAGE_INPAINTING_BATCH_PARAMS
						_A		:							str							       =		PipelineTesterMixin.required_optional_params - {"""latents"""}







						def 						__UpperCamelCase							(self       ):
											return self._get_dummy_components()







						def 						__UpperCamelCase							(self   ,		lowercase__   ,		lowercase__=0       ):
											if str(lowercase__       ).startswith("""mps"""       ):
																snake_case_					:		Optional[Any] 					=					torch.manual_seed(lowercase__       )
											else:
																snake_case_					:		Optional[Any] 					=					torch.Generator(device=lowercase__       ).manual_seed(lowercase__       )

											snake_case_					:		Dict 					=					floats_tensor((1, 3, 32, 32)   ,		rng=random.Random(lowercase__       )       ).to(lowercase__       )
											snake_case_					:		Tuple 					=					floats_tensor((1, 3, 32, 32)   ,		rng=random.Random(lowercase__       )       ).to(lowercase__       )

											snake_case_					:		Tuple 					=					{
											    """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 						__UpperCamelCase							(self       ):
											self._test_xformers_attention_forwardGenerator_pass(expected_max_diff=1e-3       )







						def 						__UpperCamelCase							(self       ):
											self._test_save_load_optional_components()







						@unittest.skipIf(torch_device != """cuda"""   ,		reason="""float16 requires CUDA"""       )
						def 						__UpperCamelCase							(self       ):
											# Due to non-determinism in save load of the hf-internal-testing/tiny-random-t5 text encoder
											super().test_save_load_floataa(expected_max_diff=1e-1       )







						def 						__UpperCamelCase							(self       ):
											self._test_attention_slicing_forward_pass(expected_max_diff=1e-2       )







						def 						__UpperCamelCase							(self       ):
											self._test_save_load_local()







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








"""simple docstring"""

from ...configuration_utils import PretrainedConfig
from ...utils import logging


a_			   =					logging.get_logger(__name__)

a_			   =					{
    '''facebook/dpr-ctx_encoder-single-nq-base''': (
        '''https://huggingface.co/facebook/dpr-ctx_encoder-single-nq-base/resolve/main/config.json'''
    ),
    '''facebook/dpr-question_encoder-single-nq-base''': (
        '''https://huggingface.co/facebook/dpr-question_encoder-single-nq-base/resolve/main/config.json'''
    ),
    '''facebook/dpr-reader-single-nq-base''': (
        '''https://huggingface.co/facebook/dpr-reader-single-nq-base/resolve/main/config.json'''
    ),
    '''facebook/dpr-ctx_encoder-multiset-base''': (
        '''https://huggingface.co/facebook/dpr-ctx_encoder-multiset-base/resolve/main/config.json'''
    ),
    '''facebook/dpr-question_encoder-multiset-base''': (
        '''https://huggingface.co/facebook/dpr-question_encoder-multiset-base/resolve/main/config.json'''
    ),
    '''facebook/dpr-reader-multiset-base''': (
        '''https://huggingface.co/facebook/dpr-reader-multiset-base/resolve/main/config.json'''
    ),
}







class    __lowercase     (					_UpperCAmelCase):







						"""simple docstring"""







						_A		:							Optional[int]							       =		"""dpr"""







						def __init__(self   ,		lowercase__=3_05_22   ,		lowercase__=7_68   ,		lowercase__=12   ,		lowercase__=12   ,		lowercase__=30_72   ,		lowercase__="gelu"   ,		lowercase__=0.1   ,		lowercase__=0.1   ,		lowercase__=5_12   ,		lowercase__=2   ,		lowercase__=0.02   ,		lowercase__=1e-12   ,		lowercase__=0   ,		lowercase__="absolute"   ,		lowercase__ = 0   ,		**lowercase__   ,		):
											super().__init__(pad_token_id=lowercase__   ,		**lowercase__       )

											snake_case_					:		List[Any] 					=					vocab_size
											snake_case_					:		List[str] 					=					hidden_size
											snake_case_					:		Tuple 					=					num_hidden_layers
											snake_case_					:		List[Any] 					=					num_attention_heads
											snake_case_					:		int 					=					hidden_act
											snake_case_					:		Dict 					=					intermediate_size
											snake_case_					:		int 					=					hidden_dropout_prob
											snake_case_					:		Any 					=					attention_probs_dropout_prob
											snake_case_					:		str 					=					max_position_embeddings
											snake_case_					:		List[str] 					=					type_vocab_size
											snake_case_					:		List[str] 					=					initializer_range
											snake_case_					:		Optional[int] 					=					layer_norm_eps
											snake_case_					:		Union[str, Any] 					=					projection_dim
											snake_case_					:		str 					=					position_embedding_type




