


"""simple docstring"""







import gc
import tempfile
import unittest

import numpy as np
import torch

from diffusers import VersatileDiffusionPipeline
from diffusers.utils.testing_utils import load_image, nightly, require_torch_gpu, torch_device


lowerCAmelCase__      				=   False


class       SCREAMING_SNAKE_CASE__				(		unittest.TestCase				):
       """simple docstring"""


       pass


@nightly
@require_torch_gpu
class       SCREAMING_SNAKE_CASE__				(		unittest.TestCase				):
       """simple docstring"""


       def        lowercase__							(						self						):






         """simple docstring"""





         super().tearDown()
         gc.collect()
         torch.cuda.empty_cache()

       def        lowercase__							(						self						):






         """simple docstring"""





         lowerCAmelCase     :     Tuple								=							VersatileDiffusionPipeline.from_pretrained("shi-labs/versatile-diffusion"		,     torch_dtype=torch.floataa						)
         pipe.to(snake_case__						)
         pipe.set_progress_bar_config(disable=snake_case__						)

         lowerCAmelCase     :     Tuple								=							load_image(
             "https://huggingface.co/datasets/hf-internal-testing/diffusers-images/resolve/main/versatile_diffusion/benz.jpg"						)

         lowerCAmelCase     :     Tuple								=							torch.manual_seed(0						)
         lowerCAmelCase     :     int								=							pipe.dual_guided(
             prompt="first prompt"		,     image=snake_case__		,     text_to_image_strength=0.75		,     generator=snake_case__		,     guidance_scale=7.5		,     num_inference_steps=2		,     output_type="numpy"		,     ).images

         with tempfile.TemporaryDirectory() as tmpdirname:
           pipe.save_pretrained(snake_case__						)
           lowerCAmelCase     :     str								=							VersatileDiffusionPipeline.from_pretrained(snake_case__		,     torch_dtype=torch.floataa						)
         pipe.to(snake_case__						)
         pipe.set_progress_bar_config(disable=snake_case__						)

         lowerCAmelCase     :     List[Any]								=							generator.manual_seed(0						)
         lowerCAmelCase     :     Union[str, Any]								=							pipe.dual_guided(
             prompt="first prompt"		,     image=snake_case__		,     text_to_image_strength=0.75		,     generator=snake_case__		,     guidance_scale=7.5		,     num_inference_steps=2		,     output_type="numpy"		,     ).images

         assert np.abs(image - new_image						).sum() < 1e-5, "Models don't have the same forward pass"







       def        lowercase__							(						self						):






         """simple docstring"""





         lowerCAmelCase     :     Optional[int]								=							VersatileDiffusionPipeline.from_pretrained("shi-labs/versatile-diffusion"		,     torch_dtype=torch.floataa						)
         pipe.to(snake_case__						)
         pipe.set_progress_bar_config(disable=snake_case__						)

         lowerCAmelCase     :     str								=							"cyberpunk 2077"
         lowerCAmelCase     :     Any								=							load_image(
             "https://huggingface.co/datasets/hf-internal-testing/diffusers-images/resolve/main/versatile_diffusion/benz.jpg"						)
         lowerCAmelCase     :     Optional[int]								=							torch.manual_seed(0						)
         lowerCAmelCase     :     List[Any]								=							pipe.dual_guided(
             prompt=snake_case__		,     image=snake_case__		,     text_to_image_strength=0.75		,     generator=snake_case__		,     guidance_scale=7.5		,     num_inference_steps=50		,     output_type="numpy"		,     ).images

         lowerCAmelCase     :     Tuple								=							image[0, 253:256, 253:256, -1]

         assert image.shape == (1, 512, 512, 3)
         lowerCAmelCase     :     Optional[Any]								=							np.array([0.1448, 0.1619, 0.1741, 0.1086, 0.1147, 0.1128, 0.1199, 0.1165, 0.1001]						)

         assert np.abs(image_slice.flatten() - expected_slice						).max() < 1e-1

         lowerCAmelCase     :     Union[str, Any]								=							"A painting of a squirrel eating a burger "
         lowerCAmelCase     :     Any								=							torch.manual_seed(0						)
         lowerCAmelCase     :     Any								=							pipe.text_to_image(
             prompt=snake_case__		,     generator=snake_case__		,     guidance_scale=7.5		,     num_inference_steps=50		,     output_type="numpy"						).images

         lowerCAmelCase     :     Dict								=							image[0, 253:256, 253:256, -1]

         assert image.shape == (1, 512, 512, 3)
         lowerCAmelCase     :     Dict								=							np.array([0.3367, 0.3169, 0.2656, 0.3870, 0.4790, 0.3796, 0.4009, 0.4878, 0.4778]						)

         assert np.abs(image_slice.flatten() - expected_slice						).max() < 1e-1

         lowerCAmelCase     :     Union[str, Any]								=							pipe.image_variation(snake_case__		,     generator=snake_case__		,     output_type="numpy"						).images

         lowerCAmelCase     :     int								=							image[0, 253:256, 253:256, -1]

         assert image.shape == (1, 512, 512, 3)
         lowerCAmelCase     :     Any								=							np.array([0.3076, 0.3123, 0.3284, 0.3782, 0.3770, 0.3894, 0.4297, 0.4331, 0.4456]						)

         assert np.abs(image_slice.flatten() - expected_slice						).max() < 1e-1









"""simple docstring"""







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


lowerCAmelCase__      				=   logging.get_logger(__name__)

lowerCAmelCase__      				=   {
    '''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       SCREAMING_SNAKE_CASE__				(		lowercase				):
       """simple docstring"""


       a  :				int   ="dpr"

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






         """simple docstring"""





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

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





