




import argparse
import os

import torch

from transformers import FlavaImageCodebook, FlavaImageCodebookConfig




def        _SCREAMING_SNAKE_CASE      (		snake_case			,     snake_case			,     snake_case			,     snake_case       )						->				Tuple:
						_UpperCAmelCase      =			s.rsplit(snake_case			,     snake_case       )
						return new.join(snake_case       )




def        _SCREAMING_SNAKE_CASE      (		snake_case       )						->				Union[str, Any]:
						# encoder.embeddings are double copied in original FLAVA
						return sum(param.float().sum() if """encoder.embeddings""" not in key else 0 for key, param in state_dict.items()       )




def        _SCREAMING_SNAKE_CASE      (		snake_case       )						->				int:
						_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(snake_case			,     """.w"""			,     """.weight"""			,     1       )
												if key.endswith(""".b"""       ):
																		_UpperCAmelCase      =			rreplace(snake_case			,     """.b"""			,     """.bias"""			,     1       )

												_UpperCAmelCase      =			value.float()

						return upgrade




@torch.no_grad()
def        _SCREAMING_SNAKE_CASE      (		snake_case			,     snake_case			,     snake_case=None			,     snake_case=True       )						->				str:
						from dall_e import Encoder

						_UpperCAmelCase      =			Encoder()
						if os.path.exists(snake_case       ):
												_UpperCAmelCase      =			torch.load(snake_case       )
						else:
												_UpperCAmelCase      =			torch.hub.load_state_dict_from_url(snake_case       )

						if isinstance(snake_case			,     snake_case       ):
												_UpperCAmelCase      =			ckpt.state_dict()
						encoder.load_state_dict(snake_case       )

						if config_path is not None:
												_UpperCAmelCase      =			FlavaImageCodebookConfig.from_pretrained(snake_case       )
						else:
												_UpperCAmelCase      =			FlavaImageCodebookConfig()

						_UpperCAmelCase      =			FlavaImageCodebook(snake_case       ).eval()
						_UpperCAmelCase      =			encoder.state_dict()

						_UpperCAmelCase      =			upgrade_state_dict(snake_case       )
						hf_model.load_state_dict(snake_case       )
						_UpperCAmelCase      =			hf_model.state_dict()
						_UpperCAmelCase      =			count_parameters(snake_case       )
						_UpperCAmelCase      =			count_parameters(snake_case       )

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

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


if __name__ == "__main__":
				a													=			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")
				a													=			parser.parse_args()

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





import itertools
import string
from collections.abc import Generator, Iterable




def        _SCREAMING_SNAKE_CASE      (		snake_case			,     snake_case       )						->				Generator[tuple[str, ...], None, None]:
						_UpperCAmelCase      =			iter(snake_case       )
						while True:
												_UpperCAmelCase      =			tuple(itertools.islice(snake_case			,     snake_case       )       )
												if not chunk:
																		return
												yield chunk




def        _SCREAMING_SNAKE_CASE      (		snake_case       )						->				str:
						_UpperCAmelCase      =			"""""".join([c.upper() for c in dirty if c in string.ascii_letters]       )
						_UpperCAmelCase      =			""""""

						if len(snake_case       ) < 2:
												return dirty

						for i in range(len(snake_case       ) - 1       ):
												clean += dirty[i]

												if dirty[i] == dirty[i + 1]:
																		clean += "X"

						clean += dirty[-1]

						if len(snake_case       ) & 1:
												clean += "X"

						return clean




def        _SCREAMING_SNAKE_CASE      (		snake_case       )						->				list[str]:
						# I and J are used interchangeably to allow
						# us to use a 5x5 table (25 letters)
						_UpperCAmelCase      =			"""ABCDEFGHIKLMNOPQRSTUVWXYZ"""
						# we're using a list instead of a '2d' array because it makes the math
						# for setting up the table and doing the actual encoding/decoding simpler
						_UpperCAmelCase      =			[]

						# copy key chars into the table if they are in `alphabet` ignoring duplicates
						for char in key.upper():
												if char not in table and char in alphabet:
																		table.append(snake_case       )

    # fill the rest of the table in with the remaining alphabet chars
						for char in alphabet:
												if char not in table:
																		table.append(snake_case       )

						return table




def        _SCREAMING_SNAKE_CASE      (		snake_case			,     snake_case       )						->				str:
						_UpperCAmelCase      =			generate_table(snake_case       )
						_UpperCAmelCase      =			prepare_input(snake_case       )
						_UpperCAmelCase      =			""""""

						# https://en.wikipedia.org/wiki/Playfair_cipher#Description
						for chara, chara in chunker(snake_case			,     2       ):
												_UpperCAmelCase    ,					_UpperCAmelCase      =			divmod(table.index(snake_case       )			,     5       )
												_UpperCAmelCase    ,					_UpperCAmelCase      =			divmod(table.index(snake_case       )			,     5       )

												if rowa == rowa:
																		ciphertext += table[rowa * 5 + (cola + 1) % 5]
																		ciphertext += table[rowa * 5 + (cola + 1) % 5]
												elif cola == cola:
																		ciphertext += table[((rowa + 1) % 5) * 5 + cola]
																		ciphertext += table[((rowa + 1) % 5) * 5 + cola]
												else:  # rectangle
																		ciphertext += table[rowa * 5 + cola]
																		ciphertext += table[rowa * 5 + cola]

						return ciphertext




def        _SCREAMING_SNAKE_CASE      (		snake_case			,     snake_case       )						->				str:
						_UpperCAmelCase      =			generate_table(snake_case       )
						_UpperCAmelCase      =			""""""

						# https://en.wikipedia.org/wiki/Playfair_cipher#Description
						for chara, chara in chunker(snake_case			,     2       ):
												_UpperCAmelCase    ,					_UpperCAmelCase      =			divmod(table.index(snake_case       )			,     5       )
												_UpperCAmelCase    ,					_UpperCAmelCase      =			divmod(table.index(snake_case       )			,     5       )

												if rowa == rowa:
																		plaintext += table[rowa * 5 + (cola - 1) % 5]
																		plaintext += table[rowa * 5 + (cola - 1) % 5]
												elif cola == cola:
																		plaintext += table[((rowa - 1) % 5) * 5 + cola]
																		plaintext += table[((rowa - 1) % 5) * 5 + cola]
												else:  # rectangle
																		plaintext += table[rowa * 5 + cola]
																		plaintext += table[rowa * 5 + cola]

						return plaintext