





'''simple docstring'''




import argparse

import torch
from safetensors.torch import load_file

from diffusers import StableDiffusionPipeline







def _lowerCAmelCase     (      _lowerCAmelCase       ,    _lowerCAmelCase       ,    _lowerCAmelCase       ,    _lowerCAmelCase       ,    _lowerCAmelCase    )->     Dict:
 # load base model
 __UpperCAmelCase					=   StableDiffusionPipeline.from_pretrained(__lowerCAmelCase       ,    torch_dtype=torch.floataa    )

 # load LoRA weight from .safetensors
 __UpperCAmelCase					=   load_file(__lowerCAmelCase    )

 __UpperCAmelCase					=   []

 # directly update weight in diffusers model
 for key in state_dict:
  # it is suggested to print out the key, it usually will be something like below
  # "lora_te_text_model_encoder_layers_0_self_attn_k_proj.lora_down.weight"

  # as we have set the alpha beforehand, so just skip
  if ".alpha" in key or key in visited:
   continue

  if "text" in key:
   __UpperCAmelCase					=   key.split('.'    )[0].split(LORA_PREFIX_TEXT_ENCODER + '_'    )[-1].split('_'    )
   __UpperCAmelCase					=   pipeline.text_encoder
  else:
   __UpperCAmelCase					=   key.split('.'    )[0].split(LORA_PREFIX_UNET + '_'    )[-1].split('_'    )
   __UpperCAmelCase					=   pipeline.unet

  # find the target layer
  __UpperCAmelCase					=   layer_infos.pop(0    )
  while len(__lowerCAmelCase    ) > -1:
   try:
    __UpperCAmelCase					=   curr_layer.__getattr__(__lowerCAmelCase    )
    if len(__lowerCAmelCase    ) > 0:
     __UpperCAmelCase					=   layer_infos.pop(0    )
    elif len(__lowerCAmelCase    ) == 0:
     break
   except Exception:
    if len(__lowerCAmelCase    ) > 0:
     temp_name += "_" + layer_infos.pop(0    )
    else:
     __UpperCAmelCase					=   layer_infos.pop(0    )

  __UpperCAmelCase					=   []
  if "lora_down" in key:
   pair_keys.append(key.replace('lora_down'       ,    'lora_up'    )    )
   pair_keys.append(__lowerCAmelCase    )
  else:
   pair_keys.append(__lowerCAmelCase    )
   pair_keys.append(key.replace('lora_up'       ,    'lora_down'    )    )

  # update weight
  if len(state_dict[pair_keys[0]].shape    ) == 4:
   __UpperCAmelCase					=   state_dict[pair_keys[0]].squeeze(3    ).squeeze(2    ).to(torch.floataa    )
   __UpperCAmelCase					=   state_dict[pair_keys[1]].squeeze(3    ).squeeze(2    ).to(torch.floataa    )
   curr_layer.weight.data += alpha * torch.mm(__lowerCAmelCase       ,    __lowerCAmelCase    ).unsqueeze(2    ).unsqueeze(3    )
  else:
   __UpperCAmelCase					=   state_dict[pair_keys[0]].to(torch.floataa    )
   __UpperCAmelCase					=   state_dict[pair_keys[1]].to(torch.floataa    )
   curr_layer.weight.data += alpha * torch.mm(__lowerCAmelCase       ,    __lowerCAmelCase    )

  # update visited list
  for item in pair_keys:
   visited.append(__lowerCAmelCase    )

 return pipeline


if __name__ == "__main__":
    _A:					Optional[Any]							=				argparse.ArgumentParser()

    parser.add_argument(
        """--base_model_path""", default=None, type=str, required=True, help="""Path to the base model in diffusers format."""
    )
    parser.add_argument(
        """--checkpoint_path""", default=None, type=str, required=True, help="""Path to the checkpoint to convert."""
    )
    parser.add_argument("""--dump_path""", default=None, type=str, required=True, help="""Path to the output model.""")
    parser.add_argument(
        """--lora_prefix_unet""", default="""lora_unet""", type=str, help="""The prefix of UNet weight in safetensors"""
    )
    parser.add_argument(
        """--lora_prefix_text_encoder""",
        default="""lora_te""",
        type=str,
        help="""The prefix of text encoder weight in safetensors""",
    )
    parser.add_argument("""--alpha""", default=0.75, type=float, help="""The merging ratio in W = W0 + alpha * deltaW""")
    parser.add_argument(
        """--to_safetensors""", action="""store_true""", help="""Whether to store pipeline in safetensors format or not."""
    )
    parser.add_argument("""--device""", type=str, help="""Device to use (e.g. cpu, cuda:0, cuda:1, etc.)""")

    _A:					int							=				parser.parse_args()

    _A:					List[Any]							=				args.base_model_path
    _A:					Dict							=				args.checkpoint_path
    _A:					List[str]							=				args.dump_path
    _A:					List[Any]							=				args.lora_prefix_unet
    _A:					Optional[Any]							=				args.lora_prefix_text_encoder
    _A:					Optional[Any]							=				args.alpha

    _A:					Optional[int]							=				convert(base_model_path, checkpoint_path, lora_prefix_unet, lora_prefix_text_encoder, alpha)

    _A:					Tuple							=				pipe.to(args.device)
    pipe.save_pretrained(args.dump_path, safe_serialization=args.to_safetensors)







'''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 UpperCAmelCase							(		UpperCAmelCase_					,			unittest.TestCase							):
    _A :			List[str]						   =       MgpstrTokenizer
    _A :			Any						   =       False
    _A :			List[Any]						   =       {}
    _A :			int						   =       False



    def 					__lowerCamelCase						(  self					):
     super().setUp()

     # fmt: off
     __UpperCAmelCase					=   ['[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
     __UpperCAmelCase					=   dict(zip(__A     ,			range(len(__A					)					)					)					)

     __UpperCAmelCase					=   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(__A					) + '\n'					)



    def 					__lowerCamelCase						(  self     ,			**__A					):
     return MgpstrTokenizer.from_pretrained(self.tmpdirname     ,			**__A					)



    def 					__lowerCamelCase						(  self     ,			__A					):
     __UpperCAmelCase					=   'tester'
     __UpperCAmelCase					=   'tester'
     return input_text, output_text



    @unittest.skip('MGP-STR always lower cases letters.'					)
    def 					__lowerCamelCase						(  self					):
     pass



    def 					__lowerCamelCase						(  self					):
     __UpperCAmelCase					=   self.get_tokenizers(do_lower_case=__A					)
     for tokenizer in tokenizers:
      with self.subTest(f'{tokenizer.__class__.__name__}'					):
       __UpperCAmelCase					=   '[SPECIAL_TOKEN]'

       tokenizer.add_special_tokens({'cls_token': special_token}					)
       __UpperCAmelCase					=   tokenizer.encode([special_token]     ,			add_special_tokens=__A					)
       self.assertEqual(len(__A					)     ,			1					)

       __UpperCAmelCase					=   tokenizer.decode(__A     ,			skip_special_tokens=__A					)
       self.assertTrue(special_token not in decoded					)



    def 					__lowerCamelCase						(  self					):
     __UpperCAmelCase					=   self.get_tokenizers()
     for tokenizer in tokenizers:
      with self.subTest(f'{tokenizer.__class__.__name__}'					):
       __UpperCAmelCase					,    __UpperCAmelCase					=   self.get_input_output_texts(__A					)

       __UpperCAmelCase					=   tokenizer.tokenize(__A					)
       __UpperCAmelCase					=   tokenizer.convert_tokens_to_ids(__A					)
       __UpperCAmelCase					=   tokenizer.encode(__A     ,			add_special_tokens=__A					)
       self.assertListEqual(__A     ,			__A					)

       __UpperCAmelCase					=   tokenizer.convert_ids_to_tokens(__A					)
       self.assertNotEqual(len(__A					)     ,			0					)
       __UpperCAmelCase					=   tokenizer.decode(__A					)
       self.assertIsInstance(__A     ,			__A					)

       self.assertEqual(text_a.replace(' '     ,			''					)     ,			__A					)



    @unittest.skip('MGP-STR tokenizer only handles one sequence.'					)
    def 					__lowerCamelCase						(  self					):
     pass




    @unittest.skip('inputs cannot be pretokenized in MgpstrTokenizer'					)
    def 					__lowerCamelCase						(  self					):
     pass





