
'''simple docstring'''


import argparse
import json
import os

import torch
from transformers.file_utils import has_file

from diffusers import UNetaDConditionModel, UNetaDModel


__lowercase				: Union[str, Any]											=  False
__lowercase				: Optional[int]											=  True
__lowercase				: Optional[Any]											=  False


if __name__ == "__main__":
					__lowercase				: Union[str, Any]											=  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.''')

					__lowercase				: Union[str, Any]											=  parser.parse_args()

					__lowercase				: Dict											=  {
					    '''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''',
					}

					__lowercase				: List[str]											=  {
					    '''time_steps''': '''time_proj''',
					    '''mid''': '''mid_block''',
					    '''downsample_blocks''': '''down_blocks''',
					    '''upsample_blocks''': '''up_blocks''',
					}

					__lowercase				: Optional[int]											=  '''''' 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:
										__lowercase				: Tuple											=  reader.read()
										__lowercase				: str											=  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'''):
										__lowercase				: List[str]											=  UNetaDModel(**config)
					else:
										__lowercase				: int											=  UNetaDConditionModel if '''ldm-text2im-large-256''' in args.repo_path else UNetaDModel
										__lowercase				: Tuple											=  class_name(**config)

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

					__lowercase				: int											=  dict(model.config)

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

										__lowercase				: List[Any]											=  [k.replace('''UNetRes''', '''''') for k in config['''down_block_types''']]
										__lowercase				: Union[str, Any]											=  [k.replace('''UNetRes''', '''''') for k in config['''up_block_types''']]

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

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

										model.load_state_dict(new_state_dict)
										model.save_pretrained(os.path.join(args.repo_path, subfolder))







"""simple docstring"""







A		=						8.31_4462  # Unit - J mol-1 K-1

def  __SCREAMING_SNAKE_CASE		(			lowerCamelCase_:							float     ,		lowerCamelCase_:							float     ,		lowerCamelCase_:							float ):
						"""simple docstring"""






						if moles < 0 or kelvin < 0 or volume < 0:
												raise ValueError("Invalid inputs. Enter positive value." )
						return moles * kelvin * UNIVERSAL_GAS_CONSTANT / volume

def  __SCREAMING_SNAKE_CASE		(			lowerCamelCase_:							float     ,		lowerCamelCase_:							float     ,		lowerCamelCase_:							float ):
						"""simple docstring"""






						if moles < 0 or kelvin < 0 or pressure < 0:
												raise ValueError("Invalid inputs. Enter positive value." )
						return moles * kelvin * UNIVERSAL_GAS_CONSTANT / pressure


if __name__ == "__main__":
			from doctest import testmod

			testmod()



