import unittest

from transformers import DebertaVaTokenizer, DebertaVaTokenizerFast
from transformers.testing_utils import get_tests_dir, require_sentencepiece, require_tokenizers, slow

from ...test_tokenization_common import TokenizerTesterMixin


UpperCAmelCase_			    =							get_tests_dir('''fixtures/spiece.model''')




@require_sentencepiece
@require_tokenizers
class  __magic_name__  (		__a      ,	unittest.TestCase    ):





   """simple docstring"""




   lowerCAmelCase      :    Optional[int]  			=   DebertaVaTokenizer
   lowerCAmelCase      :    Tuple  			=   DebertaVaTokenizerFast
   lowerCAmelCase      :    Any  			=   True
   lowerCAmelCase      :    int  			=   True



   def   lowerCAmelCase						(	self					:  Optional[Any]							):



    """simple docstring"""



    super().setUp()

    # We have a SentencePiece fixture for testing
    _UpperCamelCase:     int							= DebertaVaTokenizer(__a		,  unk_token='''<unk>'''							)
    tokenizer.save_pretrained(self.tmpdirname							)



   def   lowerCAmelCase						(	self					:  Any		,  _lowercase					:  List[Any]							):



    """simple docstring"""



    _UpperCamelCase:     Dict							= '''this is a test'''
    _UpperCamelCase:     List[str]							= '''this is a test'''
    return input_text, output_text



   def   lowerCAmelCase						(	self					:  Optional[int]							):



    """simple docstring"""



    _UpperCamelCase:     Dict							= '''<pad>'''
    _UpperCamelCase:     Optional[int]							= 0

    self.assertEqual(self.get_tokenizer()._convert_token_to_id(__a							)		,  __a							)
    self.assertEqual(self.get_tokenizer()._convert_id_to_token(__a							)		,  __a							)



   def   lowerCAmelCase						(	self					:  Tuple							):



    """simple docstring"""



    _UpperCamelCase:     List[str]							= list(self.get_tokenizer().get_vocab().keys()							)
    self.assertEqual(vocab_keys[0]		,  '''<pad>'''							)
    self.assertEqual(vocab_keys[1]		,  '''<unk>'''							)
    self.assertEqual(vocab_keys[-1]		,  '''[PAD]'''							)
    self.assertEqual(len(__a							)		,  30_001							)



   def   lowerCAmelCase						(	self					:  int							):



    """simple docstring"""



    self.assertEqual(self.get_tokenizer().vocab_size		,  30_000							)



   def   lowerCAmelCase						(	self					:  List[Any]							):



    """simple docstring"""



    _UpperCamelCase:     List[Any]							= ''' \tHeLLo!how  \n Are yoU?  '''
    _UpperCamelCase:     Any							= ['''▁hello''', '''!''', '''how''', '''▁are''', '''▁you''', '''?''']
    # fmt: on

    _UpperCamelCase:     Union[str, Any]							= DebertaVaTokenizer(__a		,  do_lower_case=__a							)
    _UpperCamelCase:     Tuple							= tokenizer.convert_ids_to_tokens(tokenizer.encode(__a		,  add_special_tokens=__a							)							)

    self.assertListEqual(__a		,  __a							)

    _UpperCamelCase:     List[Any]							= DebertaVaTokenizerFast(__a		,  do_lower_case=__a							)
    _UpperCamelCase:     Optional[int]							= rust_tokenizer.convert_ids_to_tokens(rust_tokenizer.encode(__a		,  add_special_tokens=__a							)							)

    self.assertListEqual(__a		,  __a							)



   @unittest.skip('''There is an inconsistency between slow and fast tokenizer due to a bug in the fast one.'''							)
   def   lowerCAmelCase						(	self					:  Tuple							):



    """simple docstring"""



    pass



   @unittest.skip('''There is an inconsistency between slow and fast tokenizer due to a bug in the fast one.'''							)
   def   lowerCAmelCase						(	self					:  List[str]							):



    """simple docstring"""



    pass



   def   lowerCAmelCase						(	self					:  Optional[Any]							):



    """simple docstring"""



    _UpperCamelCase:     Any							= '''I was born in 92000, and this is falsé.'''
    _UpperCamelCase:     Optional[Any]							= ['''▁''', '''<unk>''', '''▁was''', '''▁born''', '''▁in''', '''▁9''', '''2000''', '''▁''', ''',''', '''▁and''', '''▁this''', '''▁is''', '''▁fal''', '''s''', '''<unk>''', '''▁''', '''.''', ]
    # fmt: on

    _UpperCamelCase:     int							= DebertaVaTokenizer(__a		,  split_by_punct=__a							)
    _UpperCamelCase:     Union[str, Any]							= tokenizer.convert_ids_to_tokens(tokenizer.encode(__a		,  add_special_tokens=__a							)							)

    self.assertListEqual(__a		,  __a							)

    _UpperCamelCase:     str							= DebertaVaTokenizerFast(__a		,  split_by_punct=__a							)
    _UpperCamelCase:     Dict							= rust_tokenizer.convert_ids_to_tokens(rust_tokenizer.encode(__a		,  add_special_tokens=__a							)							)

    self.assertListEqual(__a		,  __a							)



   def   lowerCAmelCase						(	self					:  Any							):



    """simple docstring"""



    _UpperCamelCase:     Any							= '''I was born in 92000, and this is falsé.'''
    _UpperCamelCase:     int							= ['''▁i''', '''▁was''', '''▁born''', '''▁in''', '''▁9''', '''2000''', '''▁''', ''',''', '''▁and''', '''▁this''', '''▁is''', '''▁fal''', '''s''', '''<unk>''', '''▁''', '''.''', ]
    # fmt: on

    _UpperCamelCase:     Optional[Any]							= DebertaVaTokenizer(__a		,  do_lower_case=__a		,  split_by_punct=__a							)
    _UpperCamelCase:     int							= tokenizer.convert_ids_to_tokens(tokenizer.encode(__a		,  add_special_tokens=__a							)							)
    self.assertListEqual(__a		,  __a							)

    _UpperCamelCase:     str							= DebertaVaTokenizerFast(__a		,  do_lower_case=__a		,  split_by_punct=__a							)
    _UpperCamelCase:     List[str]							= rust_tokenizer.convert_ids_to_tokens(rust_tokenizer.encode(__a		,  add_special_tokens=__a							)							)
    self.assertListEqual(__a		,  __a							)



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



    """simple docstring"""



    _UpperCamelCase:     Optional[Any]							= '''I was born in 92000, and this is falsé.'''
    _UpperCamelCase:     Optional[int]							= ['''▁i''', '''▁was''', '''▁born''', '''▁in''', '''▁9''', '''2000''', ''',''', '''▁and''', '''▁this''', '''▁is''', '''▁fal''', '''s''', '''<unk>''', '''.''', ]
    # fmt: on

    _UpperCamelCase:     Dict							= DebertaVaTokenizer(__a		,  do_lower_case=__a		,  split_by_punct=__a							)
    _UpperCamelCase:     Any							= tokenizer.convert_ids_to_tokens(tokenizer.encode(__a		,  add_special_tokens=__a							)							)

    self.assertListEqual(__a		,  __a							)

    _UpperCamelCase:     str							= DebertaVaTokenizerFast(__a		,  do_lower_case=__a		,  split_by_punct=__a							)
    _UpperCamelCase:     List[str]							= rust_tokenizer.convert_ids_to_tokens(rust_tokenizer.encode(__a		,  add_special_tokens=__a							)							)

    self.assertListEqual(__a		,  __a							)



   def   lowerCAmelCase						(	self					:  Optional[int]							):



    """simple docstring"""



    _UpperCamelCase:     Optional[Any]							= '''I was born in 92000, and this is falsé.'''
    _UpperCamelCase:     Dict							= ['''▁''', '''<unk>''', '''▁was''', '''▁born''', '''▁in''', '''▁9''', '''2000''', '''▁''', ''',''', '''▁and''', '''▁this''', '''▁is''', '''▁fal''', '''s''', '''<unk>''', '''▁''', '''.''', ]
    # fmt: on

    _UpperCamelCase:     List[Any]							= DebertaVaTokenizer(__a		,  do_lower_case=__a		,  split_by_punct=__a							)
    _UpperCamelCase:     List[str]							= tokenizer.convert_ids_to_tokens(tokenizer.encode(__a		,  add_special_tokens=__a							)							)

    self.assertListEqual(__a		,  __a							)

    _UpperCamelCase:     List[str]							= DebertaVaTokenizerFast(__a		,  do_lower_case=__a		,  split_by_punct=__a							)
    _UpperCamelCase:     Optional[int]							= rust_tokenizer.convert_ids_to_tokens(rust_tokenizer.encode(__a		,  add_special_tokens=__a							)							)

    self.assertListEqual(__a		,  __a							)



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



    """simple docstring"""



    _UpperCamelCase:     List[Any]							= ''' \tHeLLo!how  \n Are yoU?  '''
    _UpperCamelCase:     Optional[int]							= ['''▁''', '''<unk>''', '''e''', '''<unk>''', '''o''', '''!''', '''how''', '''▁''', '''<unk>''', '''re''', '''▁yo''', '''<unk>''', '''?''']
    # fmt: on

    _UpperCamelCase:     Optional[Any]							= DebertaVaTokenizer(__a		,  do_lower_case=__a		,  split_by_punct=__a							)
    _UpperCamelCase:     str							= tokenizer.convert_ids_to_tokens(tokenizer.encode(__a		,  add_special_tokens=__a							)							)

    self.assertListEqual(__a		,  __a							)

    _UpperCamelCase:     Dict							= DebertaVaTokenizerFast(__a		,  do_lower_case=__a		,  split_by_punct=__a							)
    _UpperCamelCase:     Dict							= rust_tokenizer.convert_ids_to_tokens(rust_tokenizer.encode(__a		,  add_special_tokens=__a							)							)

    self.assertListEqual(__a		,  __a							)



   def   lowerCAmelCase						(	self					:  Dict							):



    """simple docstring"""



    _UpperCamelCase:     Optional[int]							= self.get_tokenizer()
    _UpperCamelCase:     Optional[int]							= self.get_rust_tokenizer()

    _UpperCamelCase:     Optional[int]							= '''I was born in 92000, and this is falsé.'''

    _UpperCamelCase:     List[Any]							= tokenizer.convert_ids_to_tokens(tokenizer.encode(__a		,  add_special_tokens=__a							)							)
    _UpperCamelCase:     Tuple							= rust_tokenizer.convert_ids_to_tokens(rust_tokenizer.encode(__a		,  add_special_tokens=__a							)							)
    self.assertListEqual(__a		,  __a							)

    _UpperCamelCase:     Any							= tokenizer.encode(__a		,  add_special_tokens=__a							)
    _UpperCamelCase:     List[str]							= rust_tokenizer.encode(__a		,  add_special_tokens=__a							)
    self.assertListEqual(__a		,  __a							)

    _UpperCamelCase:     Dict							= self.get_rust_tokenizer()
    _UpperCamelCase:     int							= tokenizer.encode(__a							)
    _UpperCamelCase:     str							= rust_tokenizer.encode(__a							)
    self.assertListEqual(__a		,  __a							)



   def   lowerCAmelCase						(	self					:  Dict							):



    """simple docstring"""



    _UpperCamelCase:     int							= '''This is a test'''
    _UpperCamelCase:     List[str]							= [13, 1, 4_398, 25, 21, 1_289]
    _UpperCamelCase:     List[str]							= ['''▁''', '''T''', '''his''', '''▁is''', '''▁a''', '''▁test''']
    _UpperCamelCase:     Tuple							= ['''▁''', '''<unk>''', '''his''', '''▁is''', '''▁a''', '''▁test''']

    _UpperCamelCase:     str							= DebertaVaTokenizer(__a		,  keep_accents=__a							)
    _UpperCamelCase:     Dict							= DebertaVaTokenizerFast(__a		,  keep_accents=__a							)

    _UpperCamelCase:     Dict							= tokenizer.encode(__a		,  add_special_tokens=__a							)
    self.assertListEqual(__a		,  __a							)
    _UpperCamelCase:     Optional[int]							= tokenizer.tokenize(__a							)
    self.assertListEqual(__a		,  __a							)
    _UpperCamelCase:     Tuple							= tokenizer.convert_ids_to_tokens(__a							)
    self.assertListEqual(__a		,  __a							)

    _UpperCamelCase:     List[Any]							= rust_tokenizer.encode(__a		,  add_special_tokens=__a							)
    self.assertListEqual(__a		,  __a							)
    _UpperCamelCase:     Optional[Any]							= rust_tokenizer.tokenize(__a							)
    self.assertListEqual(__a		,  __a							)
    _UpperCamelCase:     Union[str, Any]							= rust_tokenizer.convert_ids_to_tokens(__a							)
    self.assertListEqual(__a		,  __a							)

    # fmt: off
    _UpperCamelCase:     str							= '''I was born in 92000, and this is falsé.'''
    _UpperCamelCase:     Optional[int]							= [13, 1, 23, 386, 19, 561, 3_050, 15, 17, 48, 25, 8_256, 18, 1, 9]
    _UpperCamelCase:     List[Any]							= ['''▁''', '''I''', '''▁was''', '''▁born''', '''▁in''', '''▁9''', '''2000''', ''',''', '''▁and''', '''▁this''', '''▁is''', '''▁fal''', '''s''', '''é''', '''.''', ]
    _UpperCamelCase:     str							= ['''▁''', '''<unk>''', '''▁was''', '''▁born''', '''▁in''', '''▁9''', '''2000''', ''',''', '''▁and''', '''▁this''', '''▁is''', '''▁fal''', '''s''', '''<unk>''', '''.''', ]
    # fmt: on

    _UpperCamelCase:     Tuple							= tokenizer.encode(__a		,  add_special_tokens=__a							)
    self.assertListEqual(__a		,  __a							)
    _UpperCamelCase:     Tuple							= tokenizer.tokenize(__a							)
    self.assertListEqual(__a		,  __a							)
    _UpperCamelCase:     Optional[Any]							= tokenizer.convert_ids_to_tokens(__a							)
    self.assertListEqual(__a		,  __a							)

    _UpperCamelCase:     str							= rust_tokenizer.encode(__a		,  add_special_tokens=__a							)
    self.assertListEqual(__a		,  __a							)
    _UpperCamelCase:     List[Any]							= rust_tokenizer.tokenize(__a							)
    self.assertListEqual(__a		,  __a							)
    _UpperCamelCase:     Optional[Any]							= rust_tokenizer.convert_ids_to_tokens(__a							)
    self.assertListEqual(__a		,  __a							)



   def   lowerCAmelCase						(	self					:  Any							):



    """simple docstring"""



    _UpperCamelCase:     Optional[int]							= DebertaVaTokenizer(__a							)

    _UpperCamelCase:     List[str]							= tokenizer.encode('''sequence builders'''							)
    _UpperCamelCase:     Dict							= tokenizer.encode('''multi-sequence build'''							)

    _UpperCamelCase:     Union[str, Any]							= tokenizer.build_inputs_with_special_tokens(__a							)
    _UpperCamelCase:     Tuple							= tokenizer.build_inputs_with_special_tokens(__a		,  __a							)

    self.assertEqual([tokenizer.cls_token_id] + text + [tokenizer.sep_token_id]		,  __a							)
    self.assertEqual(
        [tokenizer.cls_token_id] + text + [tokenizer.sep_token_id] + text_a + [tokenizer.sep_token_id]		,  __a		,  )



   @slow
   def   lowerCAmelCase						(	self					:  int							):



    """simple docstring"""



    _UpperCamelCase:     str							= {'''input_ids''': [[1, 39_867, 36, 19_390, 486, 27, 35_052, 81_436, 18, 60_685, 1_225, 7, 35_052, 81_436, 18, 9_367, 16_899, 18, 15_937, 53, 594, 773, 18, 16_287, 30_465, 36, 15_937, 6, 41_139, 38, 36_979, 60_763, 191, 6, 34_132, 99, 6, 50_538, 390, 43_230, 6, 34_132, 2_779, 20_850, 14, 699, 1_072, 1_194, 36, 382, 10_901, 53, 7, 699, 1_072, 2_084, 36, 20_422, 630, 53, 19, 105, 3_049, 1_896, 1_053, 16_899, 1_506, 11, 37_978, 4_243, 7, 1_237, 31_869, 200, 16_566, 654, 6, 35_052, 81_436, 7, 55_630, 13_593, 4, 2], [1, 26, 15_011, 13, 667, 8, 1_053, 18, 23_611, 1_237, 72_356, 12_820, 34, 104_134, 1_209, 35, 13_313, 6_627, 21, 202, 347, 7, 164, 2_399, 11, 46, 4_485, 4, 2, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [1, 5, 1_232, 2_864, 15_785, 14_951, 105, 5, 8_581, 1_250, 4, 2, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0]], '''token_type_ids''': [[0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0]], '''attention_mask''': [[1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1], [1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0]]}  # noqa: E501
    # fmt: on

    self.tokenizer_integration_test_util(
        expected_encoding=__a		,  model_name='''microsoft/deberta-v2-xlarge'''		,  revision='''ad6e42c1532ddf3a15c39246b63f5559d558b670'''		,  )
import argparse

import torch
from safetensors.torch import load_file

from diffusers import StableDiffusionPipeline




def       lowerCAmelCase_     (		lowercase:							Optional[int]  ,					lowercase:							Any  ,					lowercase:							str  ,					lowercase:							List[str]  ,					lowercase:							Optional[int]		)    ->				int:







 '''simple docstring'''
 # load base model
 _UpperCamelCase:     Optional[int]							= StableDiffusionPipeline.from_pretrained(lowercase  ,					torch_dtype=torch.floataa		)

 # load LoRA weight from .safetensors
 _UpperCamelCase:     List[str]							= load_file(lowercase		)

 _UpperCamelCase:     Optional[int]							= []

 # 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:     int							= key.split('''.'''		)[0].split(LORA_PREFIX_TEXT_ENCODER + '''_'''		)[-1].split('''_'''		)
   _UpperCamelCase:     str							= pipeline.text_encoder
  else:
   _UpperCamelCase:     Optional[Any]							= key.split('''.'''		)[0].split(LORA_PREFIX_UNET + '''_'''		)[-1].split('''_'''		)
   _UpperCamelCase:     Any							= pipeline.unet

  # find the target layer
  _UpperCamelCase:     Union[str, Any]							= layer_infos.pop(0		)
  while len(lowercase		) > -1:
   try:
    _UpperCamelCase:     Union[str, Any]							= curr_layer.__getattr__(lowercase		)
    if len(lowercase		) > 0:
     _UpperCamelCase:     Tuple							= layer_infos.pop(0		)
    elif len(lowercase		) == 0:
     break
   except Exception:
    if len(lowercase		) > 0:
     temp_name += "_" + layer_infos.pop(0		)
    else:
     _UpperCamelCase:     List[Any]							= layer_infos.pop(0		)

  _UpperCamelCase:     Any							= []
  if "lora_down" in key:
   pair_keys.append(key.replace('''lora_down'''  ,					'''lora_up'''		)		)
   pair_keys.append(lowercase		)
  else:
   pair_keys.append(lowercase		)
   pair_keys.append(key.replace('''lora_up'''  ,					'''lora_down'''		)		)

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

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

 return pipeline


if __name__ == "__main__":
  UpperCAmelCase_			    =							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=0.7_5, 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.)''')

  UpperCAmelCase_			    =							parser.parse_args()

  UpperCAmelCase_			    =							args.base_model_path
  UpperCAmelCase_			    =							args.checkpoint_path
  UpperCAmelCase_			    =							args.dump_path
  UpperCAmelCase_			    =							args.lora_prefix_unet
  UpperCAmelCase_			    =							args.lora_prefix_text_encoder
  UpperCAmelCase_			    =							args.alpha

  UpperCAmelCase_			    =							convert(base_model_path, checkpoint_path, lora_prefix_unet, lora_prefix_text_encoder, alpha)

  UpperCAmelCase_			    =							pipe.to(args.device)
  pipe.save_pretrained(args.dump_path, safe_serialization=args.to_safetensors)