





'''simple docstring'''




import os
from typing import Optional

import fsspec
from fsspec.archive import AbstractArchiveFileSystem
from fsspec.utils import DEFAULT_BLOCK_SIZE






class 				__snake_case     (					__magic_name__							):
	__lowerCAmelCase       						=  ''''''
	__lowerCAmelCase       						=  (
	    None  # protocol passed in prefix to the url. ex: "gzip", for gzip://file.txt::http://foo.bar/file.txt.gz
	)
	__lowerCAmelCase       						=  None  # compression type in fsspec. ex: "gzip"
	__lowerCAmelCase       						=  None  # extension of the filename to strip. ex: "".gz" to get file.txt from file.txt.gz





	def __init__(		self      ,       UpperCamelCase_ = ""      ,       UpperCamelCase_ = None      ,       UpperCamelCase_ = None      ,       **UpperCamelCase_		)      ->		Tuple:
		super().__init__(self      ,       **UpperCamelCase_		)
		# always open as "rb" since fsspec can then use the TextIOWrapper to make it work for "r" mode
		snake_case__	       =   fsspec.open(
		    UpperCamelCase_      ,       mode='rb'      ,       protocol=UpperCamelCase_      ,       compression=self.compression      ,       client_kwargs={
		        'requote_redirect_url': False,  # see https://github.com/huggingface/datasets/pull/5459
		        'trust_env': True,  # Enable reading proxy env variables.
		        **(target_options or {}).pop('client_kwargs'      ,       {}		),  # To avoid issues if it was already passed.
		    }      ,       **(target_options or {})      ,       )
		snake_case__	       =   os.path.basename(self.file.path.split('::'		)[0]		)
		snake_case__	       =   (
		    self.compressed_name[: self.compressed_name.rindex('.'		)]
		    if '.' in self.compressed_name
		    else self.compressed_name
		)
		snake_case__	       =   None





	@classmethod
	def   _snake_case   (		cls      ,       UpperCamelCase_		)      ->		Tuple:
		# compressed file paths are always relative to the archive root
		return super()._strip_protocol(UpperCamelCase_		).lstrip('/'		)





	def   _snake_case   (		self		)      ->		str:
		if self.dir_cache is None:
			snake_case__	       =   {**self.file.fs.info(self.file.path		), 'name': self.uncompressed_name}
			snake_case__	       =   {f['name']: f}





	def   _snake_case   (		self      ,       UpperCamelCase_		)      ->		int:
		return self.file.open().read()





	def   _snake_case   (		self      ,       UpperCamelCase_      ,       UpperCamelCase_ = "rb"      ,       UpperCamelCase_=None      ,       UpperCamelCase_=True      ,       UpperCamelCase_=None      ,       **UpperCamelCase_      ,       )      ->		List[str]:
		snake_case__	       =   self._strip_protocol(UpperCamelCase_		)
		if mode != "rb":
			raise ValueError(F'''Tried to read with mode {mode} on file {self.file.path} opened with mode \'rb\''''		)
		return self.file.open()






class 				__snake_case     (					__magic_name__							):
	__lowerCAmelCase       						=  '''bz2'''
	__lowerCAmelCase       						=  '''bz2'''
	__lowerCAmelCase       						=  '''.bz2'''






class 				__snake_case     (					__magic_name__							):
	__lowerCAmelCase       						=  '''gzip'''
	__lowerCAmelCase       						=  '''gzip'''
	__lowerCAmelCase       						=  '''.gz'''






class 				__snake_case     (					__magic_name__							):
	__lowerCAmelCase       						=  '''lz4'''
	__lowerCAmelCase       						=  '''lz4'''
	__lowerCAmelCase       						=  '''.lz4'''






class 				__snake_case     (					__magic_name__							):
	__lowerCAmelCase       						=  '''xz'''
	__lowerCAmelCase       						=  '''xz'''
	__lowerCAmelCase       						=  '''.xz'''






class 				__snake_case     (					__magic_name__							):
	__lowerCAmelCase       						=  '''zstd'''
	__lowerCAmelCase       						=  '''zstd'''
	__lowerCAmelCase       						=  '''.zst'''





	def __init__(		self      ,       UpperCamelCase_      ,       UpperCamelCase_ = "rb"      ,       UpperCamelCase_ = None      ,       UpperCamelCase_ = None      ,       UpperCamelCase_ = DEFAULT_BLOCK_SIZE      ,       **UpperCamelCase_      ,       )      ->		List[Any]:
		super().__init__(
		    fo=UpperCamelCase_      ,       mode=UpperCamelCase_      ,       target_protocol=UpperCamelCase_      ,       target_options=UpperCamelCase_      ,       block_size=UpperCamelCase_      ,       **UpperCamelCase_      ,       )
		# We need to wrap the zstd decompressor to avoid this error in fsspec==2021.7.0 and zstandard==0.15.2:
		#
		# File "/Users/user/.virtualenvs/hf-datasets/lib/python3.7/site-packages/fsspec/core.py", line 145, in open
		#     out.close = close
		# AttributeError: 'zstd.ZstdDecompressionReader' object attribute 'close' is read-only
		#
		# see https://github.com/intake/filesystem_spec/issues/725
		snake_case__	       =   self.file.__enter__






		class 				__snake_case     :





			def __init__(		self      ,       UpperCamelCase_		)      ->		List[str]:
				snake_case__	       =   file_





			def __enter__(		self		)      ->		Union[str, Any]:
				self._file.__enter__()
				return self





			def __exit__(		self      ,       *UpperCamelCase_      ,       **UpperCamelCase_		)      ->		Union[str, Any]:
				self._file.__exit__(*UpperCamelCase_      ,       **UpperCamelCase_		)





			def __iter__(		self		)      ->		List[Any]:
				return iter(self._file		)





			def   _snake_case   (		self		)      ->		str:
				return next(self._file		)





			def __getattr__(		self      ,       UpperCamelCase_		)      ->		Dict:
				return getattr(self._file      ,       UpperCamelCase_		)

		def fixed_enter(*UpperCamelCase_      ,       **UpperCamelCase_		):
			return WrappedFile(_enter(*UpperCamelCase_      ,       **UpperCamelCase_		)		)

		snake_case__	       =   fixed_enter










'''simple docstring'''




import argparse
from pathlib import Path

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

from diffusers import AutoencoderKL


a__					:			Optional[int]          =     version.parse(version.parse(torch.__version__).base_version) < version.parse('''1.11''')




def 						__lowerCamelCase			(	UpperCAmelCase_					,				UpperCAmelCase_					,				UpperCAmelCase_					,				UpperCAmelCase_					,				UpperCAmelCase_					,				UpperCAmelCase_					,				UpperCAmelCase_					,				UpperCAmelCase_=False					,				)   ->Optional[int]:
	output_path.parent.mkdir(parents=UpperCAmelCase_					,				exist_ok=UpperCAmelCase_							)
	# 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(
		    UpperCAmelCase_					,				UpperCAmelCase_					,				f=output_path.as_posix()					,				input_names=UpperCAmelCase_					,				output_names=UpperCAmelCase_					,				dynamic_axes=UpperCAmelCase_					,				do_constant_folding=UpperCAmelCase_					,				use_external_data_format=UpperCAmelCase_					,				enable_onnx_checker=UpperCAmelCase_					,				opset_version=UpperCAmelCase_					,				)
	else:
		export(
		    UpperCAmelCase_					,				UpperCAmelCase_					,				f=output_path.as_posix()					,				input_names=UpperCAmelCase_					,				output_names=UpperCAmelCase_					,				dynamic_axes=UpperCAmelCase_					,				do_constant_folding=UpperCAmelCase_					,				opset_version=UpperCAmelCase_					,				)




@torch.no_grad()
def 						__lowerCamelCase			(	UpperCAmelCase_					,				UpperCAmelCase_					,				UpperCAmelCase_					,				UpperCAmelCase_ = False							)   ->Union[str, Any]:
	snake_case__	       =   torch.floataa if fpaa else torch.floataa
	if fpaa and torch.cuda.is_available():
		snake_case__	       =   'cuda'
	elif fpaa and not torch.cuda.is_available():
		raise ValueError('`float16` model export is only supported on GPUs with CUDA'							)
	else:
		snake_case__	       =   'cpu'
	snake_case__	       =   Path(UpperCAmelCase_							)

	# VAE DECODER
	snake_case__	       =   AutoencoderKL.from_pretrained(model_path + '/vae'							)
	snake_case__	       =   vae_decoder.config.latent_channels
	# forward only through the decoder part
	snake_case__	       =   vae_decoder.decode
	onnx_export(
	    UpperCAmelCase_					,				model_args=(
	        torch.randn(1					,				UpperCAmelCase_					,				25					,				25							).to(device=UpperCAmelCase_					,				dtype=UpperCAmelCase_							),
	        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=UpperCAmelCase_					,				)
	del vae_decoder


if __name__ == "__main__":
			a__					:			Optional[int]          =     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=14,
			    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__					:			List[str]          =     parser.parse_args()
			print(args.output_path)
			convert_models(args.model_path, args.output_path, args.opset, args.fpaa)
			print('''SD: Done: ONNX''')



