'''simple docstring'''




import argparse
from pathlib import Path

import torch
from packaging import version
from torch.onnx import export

from diffusers import AutoencoderKL


_A								=   version.parse(version.parse(torch.__version__).base_version) < version.parse('1.11')

def _UpperCamelCase   (       SCREAMING_SNAKE_CASE_  ,       SCREAMING_SNAKE_CASE_  ,       SCREAMING_SNAKE_CASE_  ,       SCREAMING_SNAKE_CASE_  ,       SCREAMING_SNAKE_CASE_  ,       SCREAMING_SNAKE_CASE_  ,       SCREAMING_SNAKE_CASE_  ,       SCREAMING_SNAKE_CASE_=False  ,       ):
     output_path.parent.mkdir(parents=SCREAMING_SNAKE_CASE_  ,       exist_ok=SCREAMING_SNAKE_CASE_							)
     # PyTorch deprecated the `enable_onnx_checker` and `use_external_data_format` arguments in v1.11,
     # so we check the torch version for backwards compatibility
     if is_torch_less_than_1_11:
          export(
              SCREAMING_SNAKE_CASE_  ,       SCREAMING_SNAKE_CASE_  ,       f=output_path.as_posix()  ,       input_names=SCREAMING_SNAKE_CASE_  ,       output_names=SCREAMING_SNAKE_CASE_  ,       dynamic_axes=SCREAMING_SNAKE_CASE_  ,       do_constant_folding=SCREAMING_SNAKE_CASE_  ,       use_external_data_format=SCREAMING_SNAKE_CASE_  ,       enable_onnx_checker=SCREAMING_SNAKE_CASE_  ,       opset_version=SCREAMING_SNAKE_CASE_  ,       )
     else:
          export(
              SCREAMING_SNAKE_CASE_  ,       SCREAMING_SNAKE_CASE_  ,       f=output_path.as_posix()  ,       input_names=SCREAMING_SNAKE_CASE_  ,       output_names=SCREAMING_SNAKE_CASE_  ,       dynamic_axes=SCREAMING_SNAKE_CASE_  ,       do_constant_folding=SCREAMING_SNAKE_CASE_  ,       opset_version=SCREAMING_SNAKE_CASE_  ,       )

@torch.no_grad()
def _UpperCamelCase   (       SCREAMING_SNAKE_CASE_  ,       SCREAMING_SNAKE_CASE_  ,       SCREAMING_SNAKE_CASE_  ,       SCREAMING_SNAKE_CASE_ = False							):
     lowercase_					:       Tuple     				=					torch.floataa if fpaa else torch.floataa
     if fpaa and torch.cuda.is_available():
          lowercase_					:       str     				=					'cuda'
     elif fpaa and not torch.cuda.is_available():
          raise ValueError('`float16` model export is only supported on GPUs with CUDA'							)
     else:
          lowercase_					:       Tuple     				=					'cpu'
     lowercase_					:       Any     				=					Path(SCREAMING_SNAKE_CASE_							)

     # VAE DECODER
     lowercase_					:       Dict     				=					AutoencoderKL.from_pretrained(model_path + '/vae'							)
     lowercase_					:       Optional[Any]     				=					vae_decoder.config.latent_channels
     # forward only through the decoder part
     lowercase_					:       Dict     				=					vae_decoder.decode
     onnx_export(
         SCREAMING_SNAKE_CASE_  ,       model_args=(
             torch.randn(1  ,       SCREAMING_SNAKE_CASE_  ,       25  ,       25							).to(device=SCREAMING_SNAKE_CASE_  ,       dtype=SCREAMING_SNAKE_CASE_							),
             False,
         )  ,       output_path=output_path / 'vae_decoder' / 'model.onnx'  ,       ordered_input_names=['latent_sample', 'return_dict']  ,       output_names=['sample']  ,       dynamic_axes={
             'latent_sample': {0: 'batch', 1: 'channels', 2: 'height', 3: 'width'},
         }  ,       opset=SCREAMING_SNAKE_CASE_  ,       )
     del vae_decoder


if __name__ == "__main__":
 _A								=   argparse.ArgumentParser()

 parser.add_argument(
     '--model_path',
     type=str,
     required=True,
     help='Path to the `diffusers` checkpoint to convert (either a local directory or on the Hub).',
 )

 parser.add_argument('--output_path', type=str, required=True, help='Path to the output model.')
 parser.add_argument(
     '--opset',
     default=1_4,
     type=int,
     help='The version of the ONNX operator set to use.',
 )
 parser.add_argument('--fp16', action='store_true', default=False, help='Export the models in `float16` mode')

 _A								=   parser.parse_args()
 print(args.output_path)
 convert_models(args.model_path, args.output_path, args.opset, args.fpaa)
 print('SD: Done: ONNX')





'''simple docstring'''




def _UpperCamelCase   (       SCREAMING_SNAKE_CASE_							):
     lowercase_					:       List[Any]     				=					len(SCREAMING_SNAKE_CASE_							)
     for _ in range(SCREAMING_SNAKE_CASE_							):
          for i in range(_ % 2  ,       arr_size - 1  ,       2							):
               if arr[i + 1] < arr[i]:
                    lowercase_				,lowercase_					:       Optional[Any]     				=					arr[i + 1], arr[i]

     return arr


if __name__ == "__main__":
 _A								=   list(range(1_0, 0, -1))
 print(F"""Original: {arr}. Sorted: {odd_even_transposition(arr)}""")




