import argparse
import os

import torch

from transformers import FlavaImageCodebook, FlavaImageCodebookConfig




def    lowerCAmelCase_ (     __A,  __A,  __A,  __A							)     ->				Optional[Any]:







      '''simple docstring'''


      UpperCAmelCase__								=  s.rsplit(__A,  __A							)
      return new.join(__A							)




def    lowerCAmelCase_ (     __A							)     ->				Tuple:







      '''simple docstring'''


      return sum(param.float().sum() if "encoder.embeddings" not in key else 0 for key, param in state_dict.items()							)




def    lowerCAmelCase_ (     __A							)     ->				Optional[Any]:







      '''simple docstring'''


      UpperCAmelCase__								=  {}

      UpperCAmelCase__								=  ["group_1", "group_2", "group_3", "group_4"]
      for key, value in state_dict.items():
            for group_key in group_keys:
                  if group_key in key:
                        UpperCAmelCase__								=  key.replace(f"""{group_key}.""",  f"""{group_key}.group."""							)

            if "res_path" in key:
                  UpperCAmelCase__								=  key.replace("res_path.",  "res_path.path."							)

            if key.endswith(".w"							):
                  UpperCAmelCase__								=  rreplace(__A,  ".w",  ".weight",  1							)
            if key.endswith(".b"							):
                  UpperCAmelCase__								=  rreplace(__A,  ".b",  ".bias",  1							)

            UpperCAmelCase__								=  value.float()

      return upgrade




@torch.no_grad()
def    lowerCAmelCase_ (     __A,  __A,  __A=None,  __A=True							)     ->				List[str]:







      '''simple docstring'''


      from dall_e import Encoder

      UpperCAmelCase__								=  Encoder()
      if os.path.exists(__A							):
            UpperCAmelCase__								=  torch.load(__A							)
      else:
            UpperCAmelCase__								=  torch.hub.load_state_dict_from_url(__A							)

      if isinstance(__A,  __A							):
            UpperCAmelCase__								=  ckpt.state_dict()
      encoder.load_state_dict(__A							)

      if config_path is not None:
            UpperCAmelCase__								=  FlavaImageCodebookConfig.from_pretrained(__A							)
      else:
            UpperCAmelCase__								=  FlavaImageCodebookConfig()

      UpperCAmelCase__								=  FlavaImageCodebook(__A							).eval()
      UpperCAmelCase__								=  encoder.state_dict()

      UpperCAmelCase__								=  upgrade_state_dict(__A							)
      hf_model.load_state_dict(__A							)
      UpperCAmelCase__								=  hf_model.state_dict()
      UpperCAmelCase__								=  count_parameters(__A							)
      UpperCAmelCase__								=  count_parameters(__A							)

      assert torch.allclose(__A,  __A,  atol=1e-3							)

      if save_checkpoint:
            hf_model.save_pretrained(__A							)
      else:
            return hf_state_dict


if __name__ == "__main__":
      UpperCamelCase__											=					argparse.ArgumentParser()
      parser.add_argument('--pytorch_dump_folder_path', default=None, type=str, help='Path to the output PyTorch model.')
      parser.add_argument('--checkpoint_path', default=None, type=str, help='Path to flava checkpoint')
      parser.add_argument('--config_path', default=None, type=str, help='Path to hf config.json of model to convert')
      UpperCamelCase__											=					parser.parse_args()

      convert_dalle_checkpoint(args.checkpoint_path, args.pytorch_dump_folder_path, args.config_path)







from __future__ import annotations


def        _UpperCamelCase							(      lowercase__      ):
						__SCREAMING_SNAKE_CASE						:     Dict					=		0.00
						__SCREAMING_SNAKE_CASE						:     List[str]					=		0
						for resistor in resistors:
												if resistor <= 0:
																		__SCREAMING_SNAKE_CASE						:     Any					=		F'''Resistor at index {index} has a negative or zero value!'''
																		raise ValueError(lowercase__      )
												first_sum += 1 / float(lowercase__      )
												index += 1
						return 1 / first_sum


def        _UpperCamelCase							(      lowercase__      ):
						__SCREAMING_SNAKE_CASE						:     Tuple					=		0.00
						__SCREAMING_SNAKE_CASE						:     int					=		0
						for resistor in resistors:
												sum_r += resistor
												if resistor < 0:
																		__SCREAMING_SNAKE_CASE						:     Tuple					=		F'''Resistor at index {index} has a negative value!'''
																		raise ValueError(lowercase__      )
												index += 1
						return sum_r


if __name__ == "__main__":
						import doctest

						doctest.testmod()
