"""simple docstring"""





import gc
import tempfile
import unittest

import numpy as np
import torch

from diffusers import VersatileDiffusionTextToImagePipeline
from diffusers.utils.testing_utils import nightly, require_torch_gpu, torch_device


__A	=					False
class 			_snake_case  (       unittest.TestCase		):
						pass

@nightly
@require_torch_gpu
class 			_snake_case  (       unittest.TestCase		):






						def    lowerCamelCase__  (							self   :      Optional[Any]     ):
													super().tearDown()
													gc.collect()
													torch.cuda.empty_cache()






						def    lowerCamelCase__  (							self   :      Tuple     ):
													__lowerCamelCase       :		Tuple		 =  VersatileDiffusionTextToImagePipeline.from_pretrained("shi-labs/versatile-diffusion"     )
													# remove text_unet
													pipe.remove_unused_weights()
													pipe.to(_UpperCAmelCase     )
													pipe.set_progress_bar_config(disable=_UpperCAmelCase     )

													__lowerCamelCase       :		List[Any]		 =  "A painting of a squirrel eating a burger "
													__lowerCamelCase       :		Optional[Any]		 =  torch.manual_seed(0     )
													__lowerCamelCase       :		List[str]		 =  pipe(
													    prompt=_UpperCAmelCase				,       generator=_UpperCAmelCase				,       guidance_scale=7.5				,       num_inference_steps=2				,       output_type="numpy"     ).images

													with tempfile.TemporaryDirectory() as tmpdirname:
																				pipe.save_pretrained(_UpperCAmelCase     )
																				__lowerCamelCase       :		List[str]		 =  VersatileDiffusionTextToImagePipeline.from_pretrained(_UpperCAmelCase     )
													pipe.to(_UpperCAmelCase     )
													pipe.set_progress_bar_config(disable=_UpperCAmelCase     )

													__lowerCamelCase       :		str		 =  generator.manual_seed(0     )
													__lowerCamelCase       :		List[Any]		 =  pipe(
													    prompt=_UpperCAmelCase				,       generator=_UpperCAmelCase				,       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    lowerCamelCase__  (							self   :      List[str]     ):
													__lowerCamelCase       :		Tuple		 =  VersatileDiffusionTextToImagePipeline.from_pretrained(
													    "shi-labs/versatile-diffusion"				,       torch_dtype=torch.floataa     )
													pipe.to(_UpperCAmelCase     )
													pipe.set_progress_bar_config(disable=_UpperCAmelCase     )

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

													__lowerCamelCase       :		Optional[Any]		 =  image[0, 253:256, 253:256, -1]

													assert image.shape == (1, 512, 512, 3)
													__lowerCamelCase       :		int		 =  np.array([0.3_3_6_7, 0.3_1_6_9, 0.2_6_5_6, 0.3_8_7_0, 0.4_7_9_0, 0.3_7_9_6, 0.4_0_0_9, 0.4_8_7_8, 0.4_7_7_8]     )

													assert np.abs(image_slice.flatten() - expected_slice     ).max() < 1E-2



from collections import OrderedDict
from typing import Mapping

from packaging import version

from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging


A			:						Any        =  logging.get_logger(__name__)

A			:						Tuple        =  {
    'sail/poolformer_s12': 'https://huggingface.co/sail/poolformer_s12/resolve/main/config.json',
    # See all PoolFormer models at https://huggingface.co/models?filter=poolformer
}



class 				A       (			UpperCAmelCase__				):
					'''simple docstring'''






					A__     =					'''poolformer'''

					def __init__(self       :		Dict ,   _UpperCAmelCase       :		Union[str, Any]=3 ,   _UpperCAmelCase       :		str=16 ,   _UpperCAmelCase       :		Any=16 ,   _UpperCAmelCase       :		Union[str, Any]=3 ,   _UpperCAmelCase       :		Union[str, Any]=4.0 ,   _UpperCAmelCase       :		str=[2, 2, 6, 2] ,   _UpperCAmelCase       :		int=[64, 128, 320, 512] ,   _UpperCAmelCase       :		Union[str, Any]=[7, 3, 3, 3] ,   _UpperCAmelCase       :		List[Any]=[4, 2, 2, 2] ,   _UpperCAmelCase       :		Union[str, Any]=[2, 1, 1, 1] ,   _UpperCAmelCase       :		Optional[Any]=4 ,   _UpperCAmelCase       :		Dict=0.0 ,   _UpperCAmelCase       :		Union[str, Any]="gelu" ,   _UpperCAmelCase       :		Optional[Any]=True ,   _UpperCAmelCase       :		Tuple=1E-5 ,   _UpperCAmelCase       :		Tuple=0.02 ,   **_UpperCAmelCase       :		Union[str, Any] ,   )		->  Optional[int]:




							"""simple docstring"""


							lowercase__	     =						num_channels
							lowercase__	     =						patch_size
							lowercase__	     =						stride
							lowercase__	     =						padding
							lowercase__	     =						pool_size
							lowercase__	     =						hidden_sizes
							lowercase__	     =						mlp_ratio
							lowercase__	     =						depths
							lowercase__	     =						patch_sizes
							lowercase__	     =						strides
							lowercase__	     =						num_encoder_blocks
							lowercase__	     =						drop_path_rate
							lowercase__	     =						hidden_act
							lowercase__	     =						use_layer_scale
							lowercase__	     =						layer_scale_init_value
							lowercase__	     =						initializer_range
							super().__init__(**_UpperCAmelCase						)






class 				A       (			UpperCAmelCase__				):
					'''simple docstring'''






					A__     =					version.parse('''1.11'''				)

					@property
					def     lowerCamelCase__	(self       :		List[str]						)		->  Mapping[str, Mapping[int, str]]:




							"""simple docstring"""


							return OrderedDict(
							    [
							        ("""pixel_values""", {0: """batch""", 1: """num_channels""", 2: """height""", 3: """width"""}),
							    ]						)


					@property
					def     lowerCamelCase__	(self       :		Dict						)		->  float:




							"""simple docstring"""


							return 2E-3

