




import copy
import os
from typing import Union

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


lowerCamelCase__ :   Tuple					=							logging.get_logger(__name__)

lowerCamelCase__ :   int					=							{
    'Salesforce/blip-vqa-base': 'https://huggingface.co/Salesforce/blip-vqa-base/resolve/main/config.json',
    'Salesforce/blip-vqa-capfit-large': (
        'https://huggingface.co/Salesforce/blip-vqa-base-capfit/resolve/main/config.json'
    ),
    'Salesforce/blip-image-captioning-base': (
        'https://huggingface.co/Salesforce/blip-image-captioning-base/resolve/main/config.json'
    ),
    'Salesforce/blip-image-captioning-large': (
        'https://huggingface.co/Salesforce/blip-image-captioning-large/resolve/main/config.json'
    ),
    'Salesforce/blip-itm-base-coco': 'https://huggingface.co/Salesforce/blip-itm-base-coco/resolve/main/config.json',
    'Salesforce/blip-itm-large-coco': 'https://huggingface.co/Salesforce/blip-itm-large-coco/resolve/main/config.json',
    'Salesforce/blip-itm-base-flikr': 'https://huggingface.co/Salesforce/blip-itm-base-flikr/resolve/main/config.json',
    'Salesforce/blip-itm-large-flikr': (
        'https://huggingface.co/Salesforce/blip-itm-large-flikr/resolve/main/config.json'
    ),
}





class        lowerCamelCase_							(      _SCREAMING_SNAKE_CASE					):


 '''simple docstring'''







 lowercase_				    =    "blip_text_model"



 def __init__(							self  :		Optional[Any]				,				_lowerCAmelCase  :		Dict=30_524				,				_lowerCAmelCase  :		int=768				,				_lowerCAmelCase  :		List[str]=768				,				_lowerCAmelCase  :		Any=3_072				,				_lowerCAmelCase  :		Optional[Any]=768				,				_lowerCAmelCase  :		List[str]=12				,				_lowerCAmelCase  :		Dict=8				,				_lowerCAmelCase  :		Optional[int]=512				,				_lowerCAmelCase  :		Union[str, Any]="gelu"				,				_lowerCAmelCase  :		Union[str, Any]=1E-12				,				_lowerCAmelCase  :		int=0.0				,				_lowerCAmelCase  :		List[str]=0.0				,				_lowerCAmelCase  :		Dict=0.02				,				_lowerCAmelCase  :		int=30_522				,				_lowerCAmelCase  :		Optional[int]=2				,				_lowerCAmelCase  :		List[str]=0				,				_lowerCAmelCase  :		List[str]=102				,				_lowerCAmelCase  :		List[Any]=True				,				_lowerCAmelCase  :		Any=True				,				**_lowerCAmelCase  :		int				,				):
       super().__init__(
           pad_token_id=_lowerCAmelCase				,				bos_token_id=_lowerCAmelCase				,				eos_token_id=_lowerCAmelCase				,				sep_token_id=_lowerCAmelCase				,				**_lowerCAmelCase				,				)

       SCREAMING_SNAKE_CASE_							=			vocab_size
       SCREAMING_SNAKE_CASE_							=			hidden_size
       SCREAMING_SNAKE_CASE_							=			encoder_hidden_size
       SCREAMING_SNAKE_CASE_							=			intermediate_size
       SCREAMING_SNAKE_CASE_							=			projection_dim
       SCREAMING_SNAKE_CASE_							=			hidden_dropout_prob
       SCREAMING_SNAKE_CASE_							=			num_hidden_layers
       SCREAMING_SNAKE_CASE_							=			num_attention_heads
       SCREAMING_SNAKE_CASE_							=			max_position_embeddings
       SCREAMING_SNAKE_CASE_							=			layer_norm_eps
       SCREAMING_SNAKE_CASE_							=			hidden_act
       SCREAMING_SNAKE_CASE_							=			initializer_range
       SCREAMING_SNAKE_CASE_							=			attention_probs_dropout_prob
       SCREAMING_SNAKE_CASE_							=			is_decoder
       SCREAMING_SNAKE_CASE_							=			use_cache




 @classmethod
 def       lowerCAmelCase_  (							cls  :		List[str]				,				_lowerCAmelCase  :		Union[str, os.PathLike]				,				**_lowerCAmelCase  :		int						):
       cls._set_token_in_kwargs(_lowerCAmelCase						)

       SCREAMING_SNAKE_CASE_						, SCREAMING_SNAKE_CASE_							=			cls.get_config_dict(_lowerCAmelCase				,				**_lowerCAmelCase						)

       # get the text config dict if we are loading from BlipConfig
       if config_dict.get('model_type'						) == "blip":
             SCREAMING_SNAKE_CASE_							=			config_dict['text_config']

       if "model_type" in config_dict and hasattr(cls				,				'model_type'						) and config_dict["model_type"] != cls.model_type:
             logger.warning(
                 F"You are using a model of type {config_dict['model_type']} to instantiate a model of type "
                 F"{cls.model_type}. This is not supported for all configurations of models and can yield errors."						)

       return cls.from_dict(_lowerCAmelCase				,				**_lowerCAmelCase						)





class        lowerCamelCase_							(      _SCREAMING_SNAKE_CASE					):


 '''simple docstring'''







 lowercase_				    =    "blip_vision_model"



 def __init__(							self  :		Union[str, Any]				,				_lowerCAmelCase  :		Optional[int]=768				,				_lowerCAmelCase  :		Optional[int]=3_072				,				_lowerCAmelCase  :		str=512				,				_lowerCAmelCase  :		Optional[int]=12				,				_lowerCAmelCase  :		Tuple=12				,				_lowerCAmelCase  :		Tuple=384				,				_lowerCAmelCase  :		Optional[int]=16				,				_lowerCAmelCase  :		Dict="gelu"				,				_lowerCAmelCase  :		Dict=1E-5				,				_lowerCAmelCase  :		List[Any]=0.0				,				_lowerCAmelCase  :		Any=1E-10				,				**_lowerCAmelCase  :		List[str]				,				):
       super().__init__(**_lowerCAmelCase						)

       SCREAMING_SNAKE_CASE_							=			hidden_size
       SCREAMING_SNAKE_CASE_							=			intermediate_size
       SCREAMING_SNAKE_CASE_							=			projection_dim
       SCREAMING_SNAKE_CASE_							=			num_hidden_layers
       SCREAMING_SNAKE_CASE_							=			num_attention_heads
       SCREAMING_SNAKE_CASE_							=			patch_size
       SCREAMING_SNAKE_CASE_							=			image_size
       SCREAMING_SNAKE_CASE_							=			initializer_range
       SCREAMING_SNAKE_CASE_							=			attention_dropout
       SCREAMING_SNAKE_CASE_							=			layer_norm_eps
       SCREAMING_SNAKE_CASE_							=			hidden_act




 @classmethod
 def       lowerCAmelCase_  (							cls  :		str				,				_lowerCAmelCase  :		Union[str, os.PathLike]				,				**_lowerCAmelCase  :		Union[str, Any]						):
       cls._set_token_in_kwargs(_lowerCAmelCase						)

       SCREAMING_SNAKE_CASE_						, SCREAMING_SNAKE_CASE_							=			cls.get_config_dict(_lowerCAmelCase				,				**_lowerCAmelCase						)

       # get the vision config dict if we are loading from BlipConfig
       if config_dict.get('model_type'						) == "blip":
             SCREAMING_SNAKE_CASE_							=			config_dict['vision_config']

       if "model_type" in config_dict and hasattr(cls				,				'model_type'						) and config_dict["model_type"] != cls.model_type:
             logger.warning(
                 F"You are using a model of type {config_dict['model_type']} to instantiate a model of type "
                 F"{cls.model_type}. This is not supported for all configurations of models and can yield errors."						)

       return cls.from_dict(_lowerCAmelCase				,				**_lowerCAmelCase						)





class        lowerCamelCase_							(      _SCREAMING_SNAKE_CASE					):


 '''simple docstring'''







 lowercase_				    =    "blip"
 lowercase_				    =    True



 def __init__(							self  :		List[str]				,				_lowerCAmelCase  :		int=None				,				_lowerCAmelCase  :		Optional[int]=None				,				_lowerCAmelCase  :		str=512				,				_lowerCAmelCase  :		List[str]=2.6592				,				_lowerCAmelCase  :		Optional[Any]=256				,				**_lowerCAmelCase  :		Tuple				,				):
       super().__init__(**_lowerCAmelCase						)

       if text_config is None:
             SCREAMING_SNAKE_CASE_							=			{}
             logger.info('`text_config` is `None`. Initializing the `BlipTextConfig` with default values.'						)

       if vision_config is None:
             SCREAMING_SNAKE_CASE_							=			{}
             logger.info('`vision_config` is `None`. Initializing the `BlipVisionConfig` with default values.'						)

       SCREAMING_SNAKE_CASE_							=			BlipTextConfig(**_lowerCAmelCase						)
       SCREAMING_SNAKE_CASE_							=			BlipVisionConfig(**_lowerCAmelCase						)

       SCREAMING_SNAKE_CASE_							=			self.vision_config.hidden_size

       SCREAMING_SNAKE_CASE_							=			projection_dim
       SCREAMING_SNAKE_CASE_							=			logit_scale_init_value
       SCREAMING_SNAKE_CASE_							=			1.0
       SCREAMING_SNAKE_CASE_							=			0.02
       SCREAMING_SNAKE_CASE_							=			image_text_hidden_size



 @classmethod
 def       lowerCAmelCase_  (							cls  :		int				,				_lowerCAmelCase  :		BlipTextConfig				,				_lowerCAmelCase  :		BlipVisionConfig				,				**_lowerCAmelCase  :		Optional[Any]						):
       return cls(text_config=text_config.to_dict()				,				vision_config=vision_config.to_dict()				,				**_lowerCAmelCase						)




 def       lowerCAmelCase_  (							self  :		int						):
       SCREAMING_SNAKE_CASE_							=			copy.deepcopy(self.__dict__						)
       SCREAMING_SNAKE_CASE_							=			self.text_config.to_dict()
       SCREAMING_SNAKE_CASE_							=			self.vision_config.to_dict()
       SCREAMING_SNAKE_CASE_							=			self.__class__.model_type
       return output





import unittest

import numpy as np

from diffusers import OnnxStableDiffusionInpaintPipelineLegacy
from diffusers.utils.testing_utils import (
    is_onnx_available,
    load_image,
    load_numpy,
    nightly,
    require_onnxruntime,
    require_torch_gpu,
)


if is_onnx_available():
   import onnxruntime as ort





@nightly
@require_onnxruntime
@require_torch_gpu
class        lowerCamelCase_							(      unittest.TestCase					):


 '''simple docstring'''







 @property
 def       lowerCAmelCase_  (							self  :		Optional[Any]						):
       return (
           "CUDAExecutionProvider",
           {
               "gpu_mem_limit": "15000000000",  # 15GB
               "arena_extend_strategy": "kSameAsRequested",
           },
       )



 @property
 def       lowerCAmelCase_  (							self  :		str						):
       SCREAMING_SNAKE_CASE_							=			ort.SessionOptions()
       SCREAMING_SNAKE_CASE_							=			False
       return options




 def       lowerCAmelCase_  (							self  :		Tuple						):
       SCREAMING_SNAKE_CASE_							=			load_image(
           'https://huggingface.co/datasets/hf-internal-testing/diffusers-images/resolve/main'
           '/in_paint/overture-creations-5sI6fQgYIuo.png'						)
       SCREAMING_SNAKE_CASE_							=			load_image(
           'https://huggingface.co/datasets/hf-internal-testing/diffusers-images/resolve/main'
           '/in_paint/overture-creations-5sI6fQgYIuo_mask.png'						)
       SCREAMING_SNAKE_CASE_							=			load_numpy(
           'https://huggingface.co/datasets/hf-internal-testing/diffusers-images/resolve/main'
           '/in_paint/red_cat_sitting_on_a_park_bench_onnx.npy'						)

       # using the PNDM scheduler by default
       SCREAMING_SNAKE_CASE_							=			OnnxStableDiffusionInpaintPipelineLegacy.from_pretrained(
           'CompVis/stable-diffusion-v1-4'				,				revision='onnx'				,				safety_checker=_lowerCAmelCase				,				feature_extractor=_lowerCAmelCase				,				provider=self.gpu_provider				,				sess_options=self.gpu_options				,				)
       pipe.set_progress_bar_config(disable=_lowerCAmelCase						)

       SCREAMING_SNAKE_CASE_							=			'A red cat sitting on a park bench'

       SCREAMING_SNAKE_CASE_							=			np.random.RandomState(0						)
       SCREAMING_SNAKE_CASE_							=			pipe(
           prompt=_lowerCAmelCase				,				image=_lowerCAmelCase				,				mask_image=_lowerCAmelCase				,				strength=0.75				,				guidance_scale=7.5				,				num_inference_steps=15				,				generator=_lowerCAmelCase				,				output_type='np'				,				)

       SCREAMING_SNAKE_CASE_							=			output.images[0]

       assert image.shape == (512, 512, 3)
       assert np.abs(expected_image - image						).max() < 1E-2