"""simple docstring"""


import argparse

import OmegaConf
import torch

from diffusers import DDIMScheduler, LDMPipeline, UNetLDMModel, VQModel







def 					__a   (		A    ,				A    ,				A      ):






     '''simple docstring'''



     lowercase__				 =							OmegaConf.load(A      )
     lowercase__				 =							torch.load(A    ,				map_location="cpu"      )["model"]
     lowercase__				 =							list(state_dict.keys()      )

     # extract state_dict for VQVAE
     lowercase__				 =							{}
     lowercase__				 =							"first_stage_model."
     for key in keys:
          if key.startswith(A      ):
               lowercase__				 =							state_dict[key]

    # extract state_dict for UNetLDM
     lowercase__				 =							{}
     lowercase__				 =							"model.diffusion_model."
     for key in keys:
          if key.startswith(A      ):
               lowercase__				 =							state_dict[key]

     lowercase__				 =							config.model.params.first_stage_config.params
     lowercase__				 =							config.model.params.unet_config.params

     lowercase__				 =							VQModel(**A      ).eval()
     vqvae.load_state_dict(A      )

     lowercase__				 =							UNetLDMModel(**A      ).eval()
     unet.load_state_dict(A      )

     lowercase__				 =							DDIMScheduler(
         timesteps=config.model.params.timesteps    ,				beta_schedule="scaled_linear"    ,				beta_start=config.model.params.linear_start    ,				beta_end=config.model.params.linear_end    ,				clip_sample=A    ,				)

     lowercase__				 =							LDMPipeline(A    ,				A    ,				A      )
     pipeline.save_pretrained(A      )


if __name__ == "__main__":
 lowerCAmelCase_:					Optional[Any]     =					argparse.ArgumentParser()
 parser.add_argument("--checkpoint_path", type=str, required=True)
 parser.add_argument("--config_path", type=str, required=True)
 parser.add_argument("--output_path", type=str, required=True)
 lowerCAmelCase_:					Tuple     =					parser.parse_args()

 convert_ldm_original(args.checkpoint_path, args.config_path, args.output_path)





"""simple docstring"""


import json
import os
import unittest

from transformers import MgpstrTokenizer
from transformers.models.mgp_str.tokenization_mgp_str import VOCAB_FILES_NAMES
from transformers.testing_utils import require_tokenizers

from ...test_tokenization_common import TokenizerTesterMixin






@require_tokenizers
class    a__    (   _a					,					unittest.TestCase	):
   snake_case_							=      MgpstrTokenizer
   snake_case_							=      False
   snake_case_							=      {}
   snake_case_							=      False


   def 	snake_case__	(     self  ):
        '''simple docstring'''



        super().setUp()

        # fmt: off
        lowercase__				 =							["[GO]", "[s]", "0", "1", "2", "3", "4", "5", "6", "7", "8", "9", "a", "b", "c", "d", "e", "f", "g", "h", "i", "j", "k", "l", "m", "n", "o", "p", "q", "r", "s", "t", "u", "v", "w", "x", "y", "z"]
        # fmt: on
        lowercase__				 =							dict(zip(_UpperCAmelCase,				range(len(_UpperCAmelCase  )  )  )  )

        lowercase__				 =							os.path.join(self.tmpdirname,				VOCAB_FILES_NAMES["vocab_file"]  )
        with open(self.vocab_file,				"w",				encoding="utf-8"  ) as fp:
             fp.write(json.dumps(_UpperCAmelCase  ) + "\n"  )


   def 	snake_case__	(     self,				**_UpperCAmelCase  ):
        '''simple docstring'''



        return MgpstrTokenizer.from_pretrained(self.tmpdirname,				**_UpperCAmelCase  )


   def 	snake_case__	(     self,				_UpperCAmelCase  ):
        '''simple docstring'''



        lowercase__				 =							"tester"
        lowercase__				 =							"tester"
        return input_text, output_text


   @unittest.skip("MGP-STR always lower cases letters."  )
   def 	snake_case__	(     self  ):
        '''simple docstring'''



        pass


   def 	snake_case__	(     self  ):
        '''simple docstring'''



        lowercase__				 =							self.get_tokenizers(do_lower_case=_UpperCAmelCase  )
        for tokenizer in tokenizers:
             with self.subTest(F'''{tokenizer.__class__.__name__}'''  ):
                  lowercase__				 =							"[SPECIAL_TOKEN]"

                  tokenizer.add_special_tokens({"cls_token": special_token}  )
                  lowercase__				 =							tokenizer.encode([special_token],				add_special_tokens=_UpperCAmelCase  )
                  self.assertEqual(len(_UpperCAmelCase  ),				1  )

                  lowercase__				 =							tokenizer.decode(_UpperCAmelCase,				skip_special_tokens=_UpperCAmelCase  )
                  self.assertTrue(special_token not in decoded  )


   def 	snake_case__	(     self  ):
        '''simple docstring'''



        lowercase__				 =							self.get_tokenizers()
        for tokenizer in tokenizers:
             with self.subTest(F'''{tokenizer.__class__.__name__}'''  ):
                  lowercase__ ,						lowercase__				 =							self.get_input_output_texts(_UpperCAmelCase  )

                  lowercase__				 =							tokenizer.tokenize(_UpperCAmelCase  )
                  lowercase__				 =							tokenizer.convert_tokens_to_ids(_UpperCAmelCase  )
                  lowercase__				 =							tokenizer.encode(_UpperCAmelCase,				add_special_tokens=_UpperCAmelCase  )
                  self.assertListEqual(_UpperCAmelCase,				_UpperCAmelCase  )

                  lowercase__				 =							tokenizer.convert_ids_to_tokens(_UpperCAmelCase  )
                  self.assertNotEqual(len(_UpperCAmelCase  ),				0  )
                  lowercase__				 =							tokenizer.decode(_UpperCAmelCase  )
                  self.assertIsInstance(_UpperCAmelCase,				_UpperCAmelCase  )

                  self.assertEqual(text_a.replace(" ",				""  ),				_UpperCAmelCase  )


   @unittest.skip("MGP-STR tokenizer only handles one sequence."  )
   def 	snake_case__	(     self  ):
        '''simple docstring'''



        pass


   @unittest.skip("inputs cannot be pretokenized in MgpstrTokenizer"  )
   def 	snake_case__	(     self  ):
        '''simple docstring'''



        pass




