'''simple docstring'''
import argparse
import os

import torch

from transformers import FlavaImageCodebook, FlavaImageCodebookConfig



def  __lowerCamelCase       (      _UpperCamelCase  :  Any							,    _UpperCamelCase  :  List[str]							,    _UpperCamelCase  :  List[Any]							,    _UpperCamelCase  :  int					):


      '''simple docstring'''


      UpperCAmelCase_            =  s.rsplit(_UpperCamelCase							,    _UpperCamelCase					)
      return new.join(_UpperCamelCase					)



def  __lowerCamelCase       (      _UpperCamelCase  :  int					):


      '''simple docstring'''


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



def  __lowerCamelCase       (      _UpperCamelCase  :  str					):


      '''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(_UpperCamelCase							,    '''.w'''							,    '''.weight'''							,    1					)
            if key.endswith('''.b'''					):
                  UpperCAmelCase_            =  rreplace(_UpperCamelCase							,    '''.b'''							,    '''.bias'''							,    1					)

            UpperCAmelCase_            =  value.float()

      return upgrade



@torch.no_grad()
def  __lowerCamelCase       (      _UpperCamelCase  :  Union[str, Any]							,    _UpperCamelCase  :  Dict							,    _UpperCamelCase  :  int=None							,    _UpperCamelCase  :  List[Any]=True					):


      '''simple docstring'''


      from dall_e import Encoder

      UpperCAmelCase_            =  Encoder()
      if os.path.exists(_UpperCamelCase					):
            UpperCAmelCase_            =  torch.load(_UpperCamelCase					)
      else:
            UpperCAmelCase_            =  torch.hub.load_state_dict_from_url(_UpperCamelCase					)

      if isinstance(_UpperCamelCase							,    _UpperCamelCase					):
            UpperCAmelCase_            =  ckpt.state_dict()
      encoder.load_state_dict(_UpperCamelCase					)

      if config_path is not None:
            UpperCAmelCase_            =  FlavaImageCodebookConfig.from_pretrained(_UpperCamelCase					)
      else:
            UpperCAmelCase_            =  FlavaImageCodebookConfig()

      UpperCAmelCase_            =  FlavaImageCodebook(_UpperCamelCase					).eval()
      UpperCAmelCase_            =  encoder.state_dict()

      UpperCAmelCase_            =  upgrade_state_dict(_UpperCamelCase					)
      hf_model.load_state_dict(_UpperCamelCase					)
      UpperCAmelCase_            =  hf_model.state_dict()
      UpperCAmelCase_            =  count_parameters(_UpperCamelCase					)
      UpperCAmelCase_            =  count_parameters(_UpperCamelCase					)

      assert torch.allclose(_UpperCamelCase							,    _UpperCamelCase							,    atol=1E-3					)

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


if __name__ == "__main__":
      lowercase__  :      List[Any]        =					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")
      lowercase__  :      Tuple        =					parser.parse_args()

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






'''simple docstring'''
import os

import pytest

from datasets import (
    get_dataset_config_info,
    get_dataset_config_names,
    get_dataset_infos,
    get_dataset_split_names,
    inspect_dataset,
    inspect_metric,
)


lowercase__  :      Tuple        =					pytest.mark.integration



@pytest.mark.parametrize('''path'''							,    ['''paws''', '''csv''']					)
def  __lowerCamelCase       (      _UpperCamelCase  :  Optional[Any]							,    _UpperCamelCase  :  int					):


      '''simple docstring'''


      inspect_dataset(_UpperCamelCase							,    _UpperCamelCase					)
      UpperCAmelCase_            =  path + '''.py'''
      assert script_name in os.listdir(_UpperCamelCase					)
      assert "__pycache__" not in os.listdir(_UpperCamelCase					)



@pytest.mark.filterwarnings('''ignore:inspect_metric is deprecated:FutureWarning'''					)
@pytest.mark.filterwarnings('''ignore:metric_module_factory is deprecated:FutureWarning'''					)
@pytest.mark.parametrize('''path'''							,    ['''accuracy''']					)
def  __lowerCamelCase       (      _UpperCamelCase  :  Tuple							,    _UpperCamelCase  :  Optional[Any]					):


      '''simple docstring'''


      inspect_metric(_UpperCamelCase							,    _UpperCamelCase					)
      UpperCAmelCase_            =  path + '''.py'''
      assert script_name in os.listdir(_UpperCamelCase					)
      assert "__pycache__" not in os.listdir(_UpperCamelCase					)



@pytest.mark.parametrize(
    '''path, config_name, expected_splits'''							,    [
        ('''squad''', '''plain_text''', ['''train''', '''validation''']),
        ('''dalle-mini/wit''', '''dalle-mini--wit''', ['''train''']),
        ('''paws''', '''labeled_final''', ['''train''', '''test''', '''validation''']),
    ]							,    )
def  __lowerCamelCase       (      _UpperCamelCase  :  Optional[Any]							,    _UpperCamelCase  :  Any							,    _UpperCamelCase  :  int					):


      '''simple docstring'''


      UpperCAmelCase_            =  get_dataset_config_info(_UpperCamelCase							,    config_name=_UpperCamelCase					)
      assert info.config_name == config_name
      assert list(info.splits.keys()					) == expected_splits



@pytest.mark.parametrize(
    '''path, config_name, expected_exception'''							,    [
        ('''paws''', None, ValueError),
    ]							,    )
def  __lowerCamelCase       (      _UpperCamelCase  :  Any							,    _UpperCamelCase  :  List[str]							,    _UpperCamelCase  :  Union[str, Any]					):


      '''simple docstring'''


      with pytest.raises(_UpperCamelCase					):
            get_dataset_config_info(_UpperCamelCase							,    config_name=_UpperCamelCase					)



@pytest.mark.parametrize(
    '''path, expected'''							,    [
        ('''squad''', '''plain_text'''),
        ('''acronym_identification''', '''default'''),
        ('''lhoestq/squad''', '''plain_text'''),
        ('''lhoestq/test''', '''default'''),
        ('''lhoestq/demo1''', '''lhoestq--demo1'''),
        ('''dalle-mini/wit''', '''dalle-mini--wit'''),
    ]							,    )
def  __lowerCamelCase       (      _UpperCamelCase  :  Any							,    _UpperCamelCase  :  Optional[Any]					):


      '''simple docstring'''


      UpperCAmelCase_            =  get_dataset_config_names(_UpperCamelCase					)
      assert expected in config_names



@pytest.mark.parametrize(
    '''path, expected_configs, expected_splits_in_first_config'''							,    [
        ('''squad''', ['''plain_text'''], ['''train''', '''validation''']),
        ('''dalle-mini/wit''', ['''dalle-mini--wit'''], ['''train''']),
        ('''paws''', ['''labeled_final''', '''labeled_swap''', '''unlabeled_final'''], ['''train''', '''test''', '''validation''']),
    ]							,    )
def  __lowerCamelCase       (      _UpperCamelCase  :  str							,    _UpperCamelCase  :  Optional[int]							,    _UpperCamelCase  :  int					):


      '''simple docstring'''


      UpperCAmelCase_            =  get_dataset_infos(_UpperCamelCase					)
      assert list(infos.keys()					) == expected_configs
      UpperCAmelCase_            =  expected_configs[0]
      assert expected_config in infos
      UpperCAmelCase_            =  infos[expected_config]
      assert info.config_name == expected_config
      assert list(info.splits.keys()					) == expected_splits_in_first_config



@pytest.mark.parametrize(
    '''path, expected_config, expected_splits'''							,    [
        ('''squad''', '''plain_text''', ['''train''', '''validation''']),
        ('''dalle-mini/wit''', '''dalle-mini--wit''', ['''train''']),
        ('''paws''', '''labeled_final''', ['''train''', '''test''', '''validation''']),
    ]							,    )
def  __lowerCamelCase       (      _UpperCamelCase  :  str							,    _UpperCamelCase  :  int							,    _UpperCamelCase  :  str					):


      '''simple docstring'''


      UpperCAmelCase_            =  get_dataset_infos(_UpperCamelCase					)
      assert expected_config in infos
      UpperCAmelCase_            =  infos[expected_config]
      assert info.config_name == expected_config
      assert list(info.splits.keys()					) == expected_splits





@pytest.mark.parametrize(
    '''path, config_name, expected_exception'''							,    [
        ('''paws''', None, ValueError),
    ]							,    )
def  __lowerCamelCase       (      _UpperCamelCase  :  Any							,    _UpperCamelCase  :  Optional[int]							,    _UpperCamelCase  :  Optional[int]					):


      '''simple docstring'''


      with pytest.raises(_UpperCamelCase					):
            get_dataset_split_names(_UpperCamelCase							,    config_name=_UpperCamelCase					)





