
import argparse
import os

import torch

from transformers import FlavaImageCodebook, FlavaImageCodebookConfig

def 		UpperCamelCase						(   lowercase_			,			lowercase_			,			lowercase_			,			lowercase_ )		->						Optional[int]:


  '''simple docstring'''






  lowercase__	: Tuple     		=   s.rsplit(lowercase_			,			lowercase_ )
  return new.join(lowercase_ )

def 		UpperCamelCase						(   lowercase_ )		->						Union[str, Any]:


  '''simple docstring'''






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

def 		UpperCamelCase						(   lowercase_ )		->						int:


  '''simple docstring'''






  lowercase__	: Tuple     		=   {}

  lowercase__	: Tuple     		=   ["""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:
        lowercase__	: Tuple     		=   key.replace(F'{group_key}.'			,			F'{group_key}.group.' )

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

    if key.endswith(""".w""" ):
      lowercase__	: Tuple     		=   rreplace(lowercase_			,			""".w"""			,			""".weight"""			,			1 )
    if key.endswith(""".b""" ):
      lowercase__	: Dict     		=   rreplace(lowercase_			,			""".b"""			,			""".bias"""			,			1 )

    lowercase__	: Any     		=   value.float()

  return upgrade

@torch.no_grad()
def 		UpperCamelCase						(   lowercase_			,			lowercase_			,			lowercase_=None			,			lowercase_=True )		->						Union[str, Any]:


  '''simple docstring'''






  from dall_e import Encoder

  lowercase__	: List[str]     		=   Encoder()
  if os.path.exists(lowercase_ ):
    lowercase__	: str     		=   torch.load(lowercase_ )
  else:
    lowercase__	: Any     		=   torch.hub.load_state_dict_from_url(lowercase_ )

  if isinstance(lowercase_			,			lowercase_ ):
    lowercase__	: Tuple     		=   ckpt.state_dict()
  encoder.load_state_dict(lowercase_ )

  if config_path is not None:
    lowercase__	: List[str]     		=   FlavaImageCodebookConfig.from_pretrained(lowercase_ )
  else:
    lowercase__	: int     		=   FlavaImageCodebookConfig()

  lowercase__	: Tuple     		=   FlavaImageCodebook(lowercase_ ).eval()
  lowercase__	: int     		=   encoder.state_dict()

  lowercase__	: Tuple     		=   upgrade_state_dict(lowercase_ )
  hf_model.load_state_dict(lowercase_ )
  lowercase__	: Tuple     		=   hf_model.state_dict()
  lowercase__	: Any     		=   count_parameters(lowercase_ )
  lowercase__	: Dict     		=   count_parameters(lowercase_ )

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

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


if __name__ == "__main__":
     lowerCamelCase__     :		List[str]        = 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""")
     lowerCamelCase__     :		List[str]        = parser.parse_args()

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











'''simple docstring'''





import unittest

import torch
from torch import nn

from diffusers.models.activations import get_activation







class        UpperCAmelCase_			(			unittest.TestCase      ):
    """simple docstring"""







    def lowerCamelCase			(       self   :	Union[str, Any]		):
          snake_case__    :       int       		= get_activation("""swish"""		)

          self.assertIsInstance(snake_case_					,	nn.SiLU		)

          self.assertEqual(act(torch.tensor(-100					,	dtype=torch.floataa		)		).item()					,	0		)
          self.assertNotEqual(act(torch.tensor(-1					,	dtype=torch.floataa		)		).item()					,	0		)
          self.assertEqual(act(torch.tensor(0					,	dtype=torch.floataa		)		).item()					,	0		)
          self.assertEqual(act(torch.tensor(20					,	dtype=torch.floataa		)		).item()					,	20		)




    def lowerCamelCase			(       self   :	Optional[Any]		):
          snake_case__    :       int       		= get_activation("""silu"""		)

          self.assertIsInstance(snake_case_					,	nn.SiLU		)

          self.assertEqual(act(torch.tensor(-100					,	dtype=torch.floataa		)		).item()					,	0		)
          self.assertNotEqual(act(torch.tensor(-1					,	dtype=torch.floataa		)		).item()					,	0		)
          self.assertEqual(act(torch.tensor(0					,	dtype=torch.floataa		)		).item()					,	0		)
          self.assertEqual(act(torch.tensor(20					,	dtype=torch.floataa		)		).item()					,	20		)




    def lowerCamelCase			(       self   :	Dict		):
          snake_case__    :       Union[str, Any]       		= get_activation("""mish"""		)

          self.assertIsInstance(snake_case_					,	nn.Mish		)

          self.assertEqual(act(torch.tensor(-200					,	dtype=torch.floataa		)		).item()					,	0		)
          self.assertNotEqual(act(torch.tensor(-1					,	dtype=torch.floataa		)		).item()					,	0		)
          self.assertEqual(act(torch.tensor(0					,	dtype=torch.floataa		)		).item()					,	0		)
          self.assertEqual(act(torch.tensor(20					,	dtype=torch.floataa		)		).item()					,	20		)




    def lowerCamelCase			(       self   :	Union[str, Any]		):
          snake_case__    :       int       		= get_activation("""gelu"""		)

          self.assertIsInstance(snake_case_					,	nn.GELU		)

          self.assertEqual(act(torch.tensor(-100					,	dtype=torch.floataa		)		).item()					,	0		)
          self.assertNotEqual(act(torch.tensor(-1					,	dtype=torch.floataa		)		).item()					,	0		)
          self.assertEqual(act(torch.tensor(0					,	dtype=torch.floataa		)		).item()					,	0		)
          self.assertEqual(act(torch.tensor(20					,	dtype=torch.floataa		)		).item()					,	20		)
