import argparse
import json
import os

import torch
from transformers.file_utils import has_file

from diffusers import UNetaDConditionModel, UNetaDModel


UpperCAmelCase_           =				False
UpperCAmelCase_           =				True
UpperCAmelCase_           =				False


if __name__ == "__main__":
  UpperCAmelCase_           =				argparse.ArgumentParser()

  parser.add_argument(
      '''--repo_path''',
      default=None,
      type=str,
      required=True,
      help='''The config json file corresponding to the architecture.''',
  )

  parser.add_argument('''--dump_path''', default=None, type=str, required=True, help='''Path to the output model.''')

  UpperCAmelCase_           =				parser.parse_args()

  UpperCAmelCase_           =				{
      '''image_size''': '''sample_size''',
      '''num_res_blocks''': '''layers_per_block''',
      '''block_channels''': '''block_out_channels''',
      '''down_blocks''': '''down_block_types''',
      '''up_blocks''': '''up_block_types''',
      '''downscale_freq_shift''': '''freq_shift''',
      '''resnet_num_groups''': '''norm_num_groups''',
      '''resnet_act_fn''': '''act_fn''',
      '''resnet_eps''': '''norm_eps''',
      '''num_head_channels''': '''attention_head_dim''',
  }

  UpperCAmelCase_           =				{
      '''time_steps''': '''time_proj''',
      '''mid''': '''mid_block''',
      '''downsample_blocks''': '''down_blocks''',
      '''upsample_blocks''': '''up_blocks''',
  }

  UpperCAmelCase_           =				'''''' if has_file(args.repo_path, '''config.json''') else '''unet'''

  with open(os.path.join(args.repo_path, subfolder, '''config.json'''), '''r''', encoding='''utf-8''') as reader:
    UpperCAmelCase_           =				reader.read()
    UpperCAmelCase_           =				json.loads(text)

  if do_only_config:
    for key in config_parameters_to_change.keys():
      config.pop(key, None)

  if has_file(args.repo_path, '''config.json'''):
    UpperCAmelCase_           =				UNetaDModel(**config)
  else:
    UpperCAmelCase_           =				UNetaDConditionModel if '''ldm-text2im-large-256''' in args.repo_path else UNetaDModel
    UpperCAmelCase_           =				class_name(**config)

  if do_only_config:
    model.save_config(os.path.join(args.repo_path, subfolder))

  UpperCAmelCase_           =				dict(model.config)

  if do_only_renaming:
    for key, value in config_parameters_to_change.items():
      if key in config:
        UpperCAmelCase_           =				config[key]
        del config[key]

    UpperCAmelCase_           =				[k.replace('''UNetRes''', '''''') for k in config['''down_block_types''']]
    UpperCAmelCase_           =				[k.replace('''UNetRes''', '''''') for k in config['''up_block_types''']]

  if do_only_weights:
    UpperCAmelCase_           =				torch.load(os.path.join(args.repo_path, subfolder, '''diffusion_pytorch_model.bin'''))

    UpperCAmelCase_           =				{}
    for param_key, param_value in state_dict.items():
      if param_key.endswith('''.op.bias''') or param_key.endswith('''.op.weight'''):
        continue
      UpperCAmelCase_           =				False
      for key, new_key in key_parameters_to_change.items():
        if not has_changed and param_key.split('''.''')[0] == key:
          UpperCAmelCase_           =				param_value
          UpperCAmelCase_           =				True
      if not has_changed:
        UpperCAmelCase_           =				param_value

    model.load_state_dict(new_state_dict)
    model.save_pretrained(os.path.join(args.repo_path, subfolder))
def    lowerCAmelCase_  (		lowercase:				Dict		)     ->					Any:







 '''simple docstring'''
 _UpperCamelCase:  int    						=			[]
 _UpperCamelCase:  Dict    						=			set({'''(''', '''[''', '''{'''}		)
 _UpperCamelCase:  int    						=			set({''')''', ''']''', '''}'''}		)
 _UpperCamelCase:  Dict    						=			{'''{''': '''}''', '''[''': ''']''', '''(''': ''')'''}

 for i in range(len(lowercase		)		):
  if s[i] in open_brackets:
   stack.append(s[i]		)

  elif s[i] in closed_brackets and (
      len(lowercase		) == 0 or (len(lowercase		) > 0 and open_to_closed[stack.pop()] != s[i])
  ):
   return False

 return len(lowercase		) == 0




def    lowerCAmelCase_  (		)     ->					int:







 '''simple docstring'''
 _UpperCamelCase:  List[str]    						=			input('''Enter sequence of brackets: '''		)
 if is_balanced(lowercase		):
  print(lowercase	,       '''is balanced'''		)
 else:
  print(lowercase	,       '''is not balanced'''		)


if __name__ == "__main__":
  main()