



"""simple docstring"""






import importlib
import json
import os
import sys
import tempfile
import unittest
from pathlib import Path

import transformers
import transformers.models.auto
from transformers.models.auto.configuration_auto import CONFIG_MAPPING, AutoConfig
from transformers.models.bert.configuration_bert import BertConfig
from transformers.models.roberta.configuration_roberta import RobertaConfig
from transformers.testing_utils import DUMMY_UNKNOWN_IDENTIFIER, get_tests_dir


sys.path.append(str(Path(__file__).parent.parent.parent.parent / '''utils'''))

from test_module.custom_configuration import CustomConfig  # noqa E402


snake_case   					=				get_tests_dir('''fixtures/dummy-config.json''')



class     UpperCAmelCase    (	unittest.TestCase  ):



   def    __UpperCAmelCase    (       self    :	Any				):



     """simple docstring"""
     _snake_case   	=      0



   def    __UpperCAmelCase    (       self    :	Optional[Any]				):



     """simple docstring"""
     self.assertIsNotNone(transformers.models.auto.__spec__				)
     self.assertIsNotNone(importlib.util.find_spec('''transformers.models.auto'''				)				)



   def    __UpperCAmelCase    (       self    :	List[str]				):



     """simple docstring"""
     _snake_case   	=      AutoConfig.from_pretrained('''bert-base-uncased'''				)
     self.assertIsInstance(__lowerCamelCase							,       __lowerCamelCase				)



   def    __UpperCAmelCase    (       self    :	Union[str, Any]				):



     """simple docstring"""
     _snake_case   	=      AutoConfig.from_pretrained(__lowerCamelCase				)
     self.assertIsInstance(__lowerCamelCase							,       __lowerCamelCase				)



   def    __UpperCAmelCase    (       self    :	int				):



     """simple docstring"""
     _snake_case   	=      AutoConfig.from_pretrained(__lowerCamelCase				)
     self.assertIsInstance(__lowerCamelCase							,       __lowerCamelCase				)



   def    __UpperCAmelCase    (       self    :	Union[str, Any]				):



     """simple docstring"""
     _snake_case   	=      AutoConfig.for_model('''roberta'''				)
     self.assertIsInstance(__lowerCamelCase							,       __lowerCamelCase				)



   def    __UpperCAmelCase    (       self    :	Dict				):



     """simple docstring"""
     with tempfile.TemporaryDirectory() as tmp_dir:
       # This model name contains bert and roberta, but roberta ends up being picked.
       _snake_case   	=      os.path.join(__lowerCamelCase							,       '''fake-roberta'''				)
       os.makedirs(__lowerCamelCase							,       exist_ok=__lowerCamelCase				)
       with open(os.path.join(__lowerCamelCase							,       '''config.json'''				)							,       '''w'''				) as f:
         f.write(json.dumps({}				)				)
       _snake_case   	=      AutoConfig.from_pretrained(__lowerCamelCase				)
       self.assertEqual(type(__lowerCamelCase				)							,       __lowerCamelCase				)



   def    __UpperCAmelCase    (       self    :	Optional[Any]				):



     """simple docstring"""
     try:
       AutoConfig.register('''custom'''							,       __lowerCamelCase				)
       # Wrong model type will raise an error
       with self.assertRaises(__lowerCamelCase				):
         AutoConfig.register('''model'''							,       __lowerCamelCase				)
       # Trying to register something existing in the Transformers library will raise an error
       with self.assertRaises(__lowerCamelCase				):
         AutoConfig.register('''bert'''							,       __lowerCamelCase				)

       # Now that the config is registered, it can be used as any other config with the auto-API
       _snake_case   	=      CustomConfig()
       with tempfile.TemporaryDirectory() as tmp_dir:
         config.save_pretrained(__lowerCamelCase				)
         _snake_case   	=      AutoConfig.from_pretrained(__lowerCamelCase				)
         self.assertIsInstance(__lowerCamelCase							,       __lowerCamelCase				)

     finally:
       if "custom" in CONFIG_MAPPING._extra_content:
         del CONFIG_MAPPING._extra_content["custom"]



   def    __UpperCAmelCase    (       self    :	Optional[int]				):



     """simple docstring"""
     with self.assertRaisesRegex(
         __lowerCamelCase							,       '''bert-base is not a local folder and is not a valid model identifier'''				):
       _snake_case   	=      AutoConfig.from_pretrained('''bert-base'''				)



   def    __UpperCAmelCase    (       self    :	Dict				):



     """simple docstring"""
     with self.assertRaisesRegex(
         __lowerCamelCase							,       R'''aaaaaa is not a valid git identifier \(branch name, tag name or commit id\)'''				):
       _snake_case   	=      AutoConfig.from_pretrained(__lowerCamelCase							,       revision='''aaaaaa'''				)



   def    __UpperCAmelCase    (       self    :	Dict				):



     """simple docstring"""
     with self.assertRaisesRegex(
         __lowerCamelCase							,       '''hf-internal-testing/no-config-test-repo does not appear to have a file named config.json.'''							,       ):
       _snake_case   	=      AutoConfig.from_pretrained('''hf-internal-testing/no-config-test-repo'''				)



   def    __UpperCAmelCase    (       self    :	str				):



     """simple docstring"""
     # If remote code is not set, we will time out when asking whether to load the model.
     with self.assertRaises(__lowerCamelCase				):
       _snake_case   	=      AutoConfig.from_pretrained('''hf-internal-testing/test_dynamic_model'''				)
     # If remote code is disabled, we can't load this config.
     with self.assertRaises(__lowerCamelCase				):
       _snake_case   	=      AutoConfig.from_pretrained('''hf-internal-testing/test_dynamic_model'''							,       trust_remote_code=__lowerCamelCase				)

     _snake_case   	=      AutoConfig.from_pretrained('''hf-internal-testing/test_dynamic_model'''							,       trust_remote_code=__lowerCamelCase				)
     self.assertEqual(config.__class__.__name__							,       '''NewModelConfig'''				)

     # Test config can be reloaded.
     with tempfile.TemporaryDirectory() as tmp_dir:
       config.save_pretrained(__lowerCamelCase				)
       _snake_case   	=      AutoConfig.from_pretrained(__lowerCamelCase							,       trust_remote_code=__lowerCamelCase				)
     self.assertEqual(reloaded_config.__class__.__name__							,       '''NewModelConfig'''				)





   def    __UpperCAmelCase    (       self    :	Union[str, Any]				):



     """simple docstring"""



     class     UpperCAmelCase    (	__SCREAMING_SNAKE_CASE  ):
        A__		:	List[Any]           =  '''new-model'''

     try:
       AutoConfig.register('''new-model'''							,       __lowerCamelCase				)
       # If remote code is not set, the default is to use local
       _snake_case   	=      AutoConfig.from_pretrained('''hf-internal-testing/test_dynamic_model'''				)
       self.assertEqual(config.__class__.__name__							,       '''NewModelConfigLocal'''				)

       # If remote code is disabled, we load the local one.
       _snake_case   	=      AutoConfig.from_pretrained('''hf-internal-testing/test_dynamic_model'''							,       trust_remote_code=__lowerCamelCase				)
       self.assertEqual(config.__class__.__name__							,       '''NewModelConfigLocal'''				)

       # If remote is enabled, we load from the Hub
       _snake_case   	=      AutoConfig.from_pretrained('''hf-internal-testing/test_dynamic_model'''							,       trust_remote_code=__lowerCamelCase				)
       self.assertEqual(config.__class__.__name__							,       '''NewModelConfig'''				)

     finally:
       if "new-model" in CONFIG_MAPPING._extra_content:
         del CONFIG_MAPPING._extra_content["new-model"]








import argparse
from pathlib import Path

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

from diffusers import AutoencoderKL


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







def 						lowerCamelCase__      ( __A    :Any	,__A    :tuple	,__A    :Path	,__A    :int	,__A    :Union[str, Any]	,__A    :Optional[Any]	,__A    :Optional[Any]	,__A    :List[Any]=False	,):


       """simple docstring"""




       output_path.parent.mkdir(parents=__A	,exist_ok=__A		)
       # 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(
                  __A	,__A	,f=output_path.as_posix()	,input_names=__A	,output_names=__A	,dynamic_axes=__A	,do_constant_folding=__A	,use_external_data_format=__A	,enable_onnx_checker=__A	,opset_version=__A	,)
       else:
              export(
                  __A	,__A	,f=output_path.as_posix()	,input_names=__A	,output_names=__A	,dynamic_axes=__A	,do_constant_folding=__A	,opset_version=__A	,)







@torch.no_grad()
def 						lowerCamelCase__      ( __A    :str	,__A    :str	,__A    :int	,__A    :bool = False		):


       """simple docstring"""




       __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(__A		)

       # 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(
           __A	,model_args=(
               torch.randn(1	,__A	,2_5	,2_5		).to(device=__A	,dtype=__A		),
               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=__A	,)
       del vae_decoder


if __name__ == "__main__":
    UpperCamelCase__		 =     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''')

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

