



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 		a__			(		_UpperCamelCase			: List[str] ,_UpperCamelCase			: tuple ,_UpperCamelCase			: Path ,_UpperCamelCase			: Tuple ,_UpperCamelCase			: Optional[int] ,_UpperCamelCase			: Optional[int] ,_UpperCamelCase			: Optional[Any] ,_UpperCamelCase			: List[str]=False ,):
			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 		a__			(		_UpperCamelCase			: str ,_UpperCamelCase			: str ,_UpperCamelCase			: int ,_UpperCamelCase			: bool = False							):
			__lowerCamelCase													=    torch.floataa if fpaa else torch.floataa
			if fpaa and torch.cuda.is_available():
						__lowerCamelCase													=    """cuda"""
			elif fpaa and not torch.cuda.is_available():
						raise ValueError('''`float16` model export is only supported on GPUs with CUDA'''							)
			else:
						__lowerCamelCase													=    """cpu"""
			__lowerCamelCase													=    Path(UpperCAmelCase__							)

			# VAE DECODER
			__lowerCamelCase													=    AutoencoderKL.from_pretrained(model_path + '''/vae'''							)
			__lowerCamelCase													=    vae_decoder.config.latent_channels
			# forward only through the decoder part
			__lowerCamelCase													=    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_			=					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_			=					parser.parse_args()
		print(args.output_path)
		convert_models(args.model_path, args.output_path, args.opset, args.fpaa)
		print("""SD: Done: ONNX""")











import unittest

from transformers import RoFormerTokenizer, RoFormerTokenizerFast
from transformers.testing_utils import require_rjieba, require_tokenizers

from ...test_tokenization_common import TokenizerTesterMixin



@require_rjieba
@require_tokenizers
class  __lowerCAmelCase     (	lowerCAmelCase__  ,	unittest.TestCase   ):
 lowerCAmelCase__       					=  RoFormerTokenizer
 lowerCAmelCase__       					=  RoFormerTokenizerFast
 lowerCAmelCase__       					=  True
 lowerCAmelCase__       					=  True




 def        lowerCamelCase      (						self				):



    '''simple docstring'''
    super().setUp()




 def        lowerCamelCase      (						self	,				**__UpperCAmelCase				):



    '''simple docstring'''
    return self.tokenizer_class.from_pretrained('''junnyu/roformer_chinese_base'''	,				**__UpperCAmelCase				)




 def        lowerCamelCase      (						self	,				**__UpperCAmelCase				):



    '''simple docstring'''
    return self.rust_tokenizer_class.from_pretrained('''junnyu/roformer_chinese_base'''	,				**__UpperCAmelCase				)




 def        lowerCamelCase      (						self				):



    '''simple docstring'''
    __lowerCamelCase													=    '''永和服装饰品有限公司,今天天气非常好'''
    __lowerCamelCase													=    '''永和 服装 饰品 有限公司 , 今 天 天 气 非常 好'''
    return input_text, output_text




 def        lowerCamelCase      (						self				):



    '''simple docstring'''
    __lowerCamelCase													=    self.get_tokenizer()
    __lowerCamelCase							,__lowerCamelCase													=    self.get_chinese_input_output_texts()
    __lowerCamelCase													=    tokenizer.tokenize(__UpperCAmelCase				)

    self.assertListEqual(__UpperCAmelCase	,				output_text.split()				)

    __lowerCamelCase													=    tokens + [tokenizer.unk_token]
    __lowerCamelCase													=    [22943, 21332, 34431, 45904, 117, 306, 1231, 1231, 2653, 33994, 1266, 100]
    self.assertListEqual(tokenizer.convert_tokens_to_ids(__UpperCAmelCase				)	,				__UpperCAmelCase				)




 def        lowerCamelCase      (						self				):



    '''simple docstring'''
    __lowerCamelCase													=    self.get_rust_tokenizer()
    __lowerCamelCase							,__lowerCamelCase													=    self.get_chinese_input_output_texts()
    __lowerCamelCase													=    tokenizer.tokenize(__UpperCAmelCase				)
    self.assertListEqual(__UpperCAmelCase	,				output_text.split()				)
    __lowerCamelCase													=    tokens + [tokenizer.unk_token]
    __lowerCamelCase													=    [22943, 21332, 34431, 45904, 117, 306, 1231, 1231, 2653, 33994, 1266, 100]
    self.assertListEqual(tokenizer.convert_tokens_to_ids(__UpperCAmelCase				)	,				__UpperCAmelCase				)




 def        lowerCamelCase      (						self				):



    '''simple docstring'''
    pass




 def        lowerCamelCase      (						self				):



    '''simple docstring'''
    pass




 def        lowerCamelCase      (						self				):



    '''simple docstring'''
    pass






