
'''simple docstring'''



# limitations under the License.


from typing import Optional, Tuple, Union

import torch

from diffusers import DiffusionPipeline, ImagePipelineOutput




class     UpperCAmelCase_	(						_SCREAMING_SNAKE_CASE					):






						'''simple docstring'''






						def __init__(   self       ,  _lowercase       ,  _lowercase ):

												"""simple docstring"""



												super().__init__()
												self.register_modules(unet=_lowercase       ,  scheduler=_lowercase )




						@torch.no_grad()
						def __call__(   self       ,  _lowercase = 1       ,  _lowercase = None       ,  _lowercase = 50       ,  _lowercase = "pil"       ,  _lowercase = True       ,  **_lowercase       ,  ):

												"""simple docstring"""



												_lowerCAmelCase    		=					torch.randn(
												    (batch_size, self.unet.config.in_channels, self.unet.config.sample_size, self.unet.config.sample_size)       ,  generator=_lowercase       ,  )
												_lowerCAmelCase    		=					image.to(self.device )

												# set step values
												self.scheduler.set_timesteps(_lowercase )

												for t in self.progress_bar(self.scheduler.timesteps ):
																		# 1. predict noise model_output
																		_lowerCAmelCase    		=					self.unet(_lowercase       ,  _lowercase ).sample

																		# 2. predict previous mean of image x_t-1 and add variance depending on eta
																		# eta corresponds to η in paper and should be between [0, 1]
																		# do x_t -> x_t-1
																		_lowerCAmelCase    		=					self.scheduler.step(_lowercase       ,  _lowercase       ,  _lowercase ).prev_sample

												_lowerCAmelCase    		=					(image / 2 + 0.5).clamp(0       ,  1 )
												_lowerCAmelCase    		=					image.cpu().permute(0       ,  2       ,  3       ,  1 ).numpy()
												if output_type == "pil":
																		_lowerCAmelCase    		=					self.numpy_to_pil(_lowercase )

												if not return_dict:
																		return (image,), "This is a local test"

												return ImagePipelineOutput(images=_lowercase ), "This is a local test"


'''simple docstring'''



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


_lowercase          =						logging.get_logger(__name__)

_lowercase          =						{
    """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     UpperCAmelCase_	(						_SCREAMING_SNAKE_CASE					):






						'''simple docstring'''






						_lowercase						: str										=  '''dpr'''




						def __init__(   self       ,  _lowercase=30_522       ,  _lowercase=768       ,  _lowercase=12       ,  _lowercase=12       ,  _lowercase=3_072       ,  _lowercase="gelu"       ,  _lowercase=0.1       ,  _lowercase=0.1       ,  _lowercase=512       ,  _lowercase=2       ,  _lowercase=0.02       ,  _lowercase=1e-12       ,  _lowercase=0       ,  _lowercase="absolute"       ,  _lowercase = 0       ,  **_lowercase       ,  ):

												"""simple docstring"""



												super().__init__(pad_token_id=_lowercase       ,  **_lowercase )

												_lowerCAmelCase    		=					vocab_size
												_lowerCAmelCase    		=					hidden_size
												_lowerCAmelCase    		=					num_hidden_layers
												_lowerCAmelCase    		=					num_attention_heads
												_lowerCAmelCase    		=					hidden_act
												_lowerCAmelCase    		=					intermediate_size
												_lowerCAmelCase    		=					hidden_dropout_prob
												_lowerCAmelCase    		=					attention_probs_dropout_prob
												_lowerCAmelCase    		=					max_position_embeddings
												_lowerCAmelCase    		=					type_vocab_size
												_lowerCAmelCase    		=					initializer_range
												_lowerCAmelCase    		=					layer_norm_eps
												_lowerCAmelCase    		=					projection_dim
												_lowerCAmelCase    		=					position_embedding_type
