





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
from ...utils.backbone_utils import BackboneConfigMixin, get_aligned_output_features_output_indices


__A       : Tuple						    = logging.get_logger(__name__)

__A       : List[str]						    = {
    "facebook/convnext-tiny-224": "https://huggingface.co/facebook/convnext-tiny-224/resolve/main/config.json",
    # See all ConvNeXT models at https://huggingface.co/models?filter=convnext
}







class     lowerCamelCase(	__snake_case ,   __snake_case  ):
     '''simple docstring'''


     __magic_name__        = 'convnext'




     def __init__(						self							,    snake_case_=3							,    snake_case_=4							,    snake_case_=4							,    snake_case_=None							,    snake_case_=None							,    snake_case_="gelu"							,    snake_case_=0.02							,    snake_case_=1E-12							,    snake_case_=1E-6							,    snake_case_=0.0							,    snake_case_=224							,    snake_case_=None							,    snake_case_=None							,    **snake_case_							,    ):
         super().__init__(**snake_case_       )

         _A    =       num_channels
         _A    =       patch_size
         _A    =       num_stages
         _A    =       [96, 192, 384, 768] if hidden_sizes is None else hidden_sizes
         _A    =       [3, 3, 9, 3] if depths is None else depths
         _A    =       hidden_act
         _A    =       initializer_range
         _A    =       layer_norm_eps
         _A    =       layer_scale_init_value
         _A    =       drop_path_rate
         _A    =       image_size
         _A    =       ['stem'] + [F"stage{idx}" for idx in range(1							,    len(self.depths       ) + 1       )]
         _A, _A    =       get_aligned_output_features_output_indices(
             out_features=snake_case_							,    out_indices=snake_case_							,    stage_names=self.stage_names       )







class     lowerCamelCase(	__snake_case  ):
     '''simple docstring'''


     __magic_name__        = version.parse('1.11'  )




     @property
     def 					lowerCAmelCase__		(						self       ):
         return OrderedDict(
             [
                 ('pixel_values', {0: 'batch', 1: 'num_channels', 2: 'height', 3: 'width'}),
             ]       )




     @property
     def 					lowerCAmelCase__		(						self       ):
         return 1E-5












import unittest

import numpy as np
import PIL
import torch

from diffusers.image_processor import VaeImageProcessor







class     lowerCamelCase(	unittest.TestCase  ):
     '''simple docstring'''


     @property
     def 					lowerCAmelCase__		(						self       ):
         _A    =       1
         _A    =       3
         _A    =       8
         _A    =       8

         _A    =       torch.rand((batch_size, num_channels, height, width)       )

         return sample




     def 					lowerCAmelCase__		(						self							,    snake_case_       ):
         if isinstance(image[0]							,    PIL.Image.Image       ):
             return np.stack([np.array(snake_case_       ) for i in image]							,    axis=0       )
         elif isinstance(snake_case_							,    torch.Tensor       ):
             return image.cpu().numpy().transpose(0							,    2							,    3							,    1       )
         return image




     def 					lowerCAmelCase__		(						self       ):
         _A    =       VaeImageProcessor(do_resize=snake_case_							,    do_normalize=snake_case_       )

         _A    =       self.dummy_sample
         _A    =       self.to_np(snake_case_       )

         for output_type in ["pt", "np", "pil"]:
             _A    =       image_processor.postprocess(
                 image_processor.preprocess(snake_case_       )							,    output_type=snake_case_							,    )
             _A    =       self.to_np(snake_case_       )
             _A    =       (input_np * 255).round() if output_type == 'pil' else input_np
             assert (
                 np.abs(in_np - out_np       ).max() < 1E-6
             ), F"decoded output does not match input for output_type {output_type}"




     def 					lowerCAmelCase__		(						self       ):
         _A    =       VaeImageProcessor(do_resize=snake_case_							,    do_normalize=snake_case_       )
         _A    =       self.dummy_sample.cpu().numpy().transpose(0							,    2							,    3							,    1       )

         for output_type in ["pt", "np", "pil"]:
             _A    =       image_processor.postprocess(image_processor.preprocess(snake_case_       )							,    output_type=snake_case_       )

             _A    =       self.to_np(snake_case_       )
             _A    =       (input_np * 255).round() if output_type == 'pil' else input_np
             assert (
                 np.abs(in_np - out_np       ).max() < 1E-6
             ), F"decoded output does not match input for output_type {output_type}"




     def 					lowerCAmelCase__		(						self       ):
         _A    =       VaeImageProcessor(do_resize=snake_case_							,    do_normalize=snake_case_       )

         _A    =       self.dummy_sample.cpu().numpy().transpose(0							,    2							,    3							,    1       )
         _A    =       image_processor.numpy_to_pil(snake_case_       )

         for output_type in ["pt", "np", "pil"]:
             _A    =       image_processor.postprocess(image_processor.preprocess(snake_case_       )							,    output_type=snake_case_       )
             for i, o in zip(snake_case_							,    snake_case_       ):
                 _A    =       np.array(snake_case_       )
                 _A    =       self.to_np(snake_case_       ) if output_type == 'pil' else (self.to_np(snake_case_       ) * 255).round()
                 assert (
                     np.abs(in_np - out_np       ).max() < 1E-6
                 ), F"decoded output does not match input for output_type {output_type}"




     def 					lowerCAmelCase__		(						self       ):
         _A    =       VaeImageProcessor(do_resize=snake_case_							,    do_normalize=snake_case_       )

         _A    =       self.dummy_sample
         _A    =       input_pt_ad.squeeze(0       )

         _A    =       image_processor.postprocess(
             image_processor.preprocess(snake_case_       )							,    output_type='np'							,    )
         _A    =       image_processor.postprocess(
             image_processor.preprocess(snake_case_       )							,    output_type='np'							,    )

         _A    =       self.to_np(self.dummy_sample       )
         _A    =       input_np_ad.squeeze(0       )

         _A    =       image_processor.postprocess(
             image_processor.preprocess(snake_case_       )							,    output_type='np'							,    )
         _A    =       image_processor.postprocess(
             image_processor.preprocess(snake_case_       )							,    output_type='np'							,    )

         assert np.abs(out_pt_ad - out_pt_ad       ).max() < 1E-6
         assert np.abs(out_np_ad - out_np_ad       ).max() < 1E-6




     def 					lowerCAmelCase__		(						self       ):
         _A    =       VaeImageProcessor(do_resize=snake_case_							,    do_normalize=snake_case_       )

         _A    =       self.dummy_sample
         _A    =       list(snake_case_       )

         _A    =       image_processor.postprocess(
             image_processor.preprocess(snake_case_       )							,    output_type='np'							,    )

         _A    =       image_processor.postprocess(
             image_processor.preprocess(snake_case_       )							,    output_type='np'							,    )

         _A    =       self.to_np(self.dummy_sample       )
         list(snake_case_       )

         _A    =       image_processor.postprocess(
             image_processor.preprocess(snake_case_       )							,    output_type='np'							,    )

         _A    =       image_processor.postprocess(
             image_processor.preprocess(snake_case_       )							,    output_type='np'							,    )

         assert np.abs(out_pt_ad - out_pt_list       ).max() < 1E-6
         assert np.abs(out_np_ad - out_np_list       ).max() < 1E-6





