import functools
import logging
import os
import sys
import threading
from logging import (
    CRITICAL,  # NOQA
    DEBUG,  # NOQA
    ERROR,  # NOQA
    FATAL,  # NOQA
    INFO,  # NOQA
    NOTSET,  # NOQA
    WARN,  # NOQA
    WARNING,  # NOQA
)
from typing import Optional

import huggingface_hub.utils as hf_hub_utils
from tqdm import auto as tqdm_lib


lowerCAmelCase_ : List[str]						  =      threading.Lock()
lowerCAmelCase_ : Dict						  =      None

lowerCAmelCase_ : Optional[int]						  =      {
    "debug": logging.DEBUG,
    "info": logging.INFO,
    "warning": logging.WARNING,
    "error": logging.ERROR,
    "critical": logging.CRITICAL,
}

lowerCAmelCase_ : Tuple						  =      logging.WARNING

lowerCAmelCase_ : str						  =      True


def __a (	)	->							str:
      '''simple docstring'''


      lowercase_     =      os.getenv("TRANSFORMERS_VERBOSITY" ,		snake_case__				)
      if env_level_str:
            if env_level_str in log_levels:
                  return log_levels[env_level_str]
            else:
                  logging.getLogger().warning(
                      f'Unknown option TRANSFORMERS_VERBOSITY={env_level_str}, '
                      f'has to be one of: { ", ".join(log_levels.keys()				) }'				)
      return _default_log_level


def __a (	)	->							Any:
      '''simple docstring'''


      return __name__.split("."				)[0]


def __a (	)	->							Any:
      '''simple docstring'''


      return logging.getLogger(_get_library_name()				)


def __a (	)	->							Optional[int]:
      '''simple docstring'''


      global _default_handler

      with _lock:
            if _default_handler:
                  # This library has already configured the library root logger.
                  return
            lowercase_     =      logging.StreamHandler()  # Set sys.stderr as stream.
            lowercase_     =      sys.stderr.flush

            # Apply our default configuration to the library root logger.
            lowercase_     =      _get_library_root_logger()
            library_root_logger.addHandler(_default_handler				)
            library_root_logger.setLevel(_get_default_logging_level()				)
            lowercase_     =      False


def __a (	)	->							Any:
      '''simple docstring'''


      global _default_handler

      with _lock:
            if not _default_handler:
                  return

            lowercase_     =      _get_library_root_logger()
            library_root_logger.removeHandler(_default_handler				)
            library_root_logger.setLevel(logging.NOTSET				)
            lowercase_     =      None


def __a (	)	->							Optional[int]:
      '''simple docstring'''


      return log_levels


def __a (	__lowerCamelCase			:						Optional[str] = None				)	->							str:
      '''simple docstring'''


      if name is None:
            lowercase_     =      _get_library_name()

      _configure_library_root_logger()
      return logging.getLogger(snake_case__				)


def __a (	)	->							List[str]:
      '''simple docstring'''


      _configure_library_root_logger()
      return _get_library_root_logger().getEffectiveLevel()


def __a (	__lowerCamelCase			:						int				)	->							List[str]:
      '''simple docstring'''


      _configure_library_root_logger()
      _get_library_root_logger().setLevel(snake_case__				)


def __a (	)	->							Optional[Any]:
      '''simple docstring'''


      return set_verbosity(snake_case__				)


def __a (	)	->							str:
      '''simple docstring'''


      return set_verbosity(snake_case__				)


def __a (	)	->							Union[str, Any]:
      '''simple docstring'''


      return set_verbosity(snake_case__				)


def __a (	)	->							Any:
      '''simple docstring'''


      return set_verbosity(snake_case__				)


def __a (	)	->							str:
      '''simple docstring'''


      _configure_library_root_logger()

      assert _default_handler is not None
      _get_library_root_logger().removeHandler(_default_handler				)


def __a (	)	->							Dict:
      '''simple docstring'''


      _configure_library_root_logger()

      assert _default_handler is not None
      _get_library_root_logger().addHandler(_default_handler				)


def __a (	__lowerCamelCase			:						logging.Handler				)	->							Union[str, Any]:
      '''simple docstring'''


      _configure_library_root_logger()

      assert handler is not None
      _get_library_root_logger().addHandler(snake_case__				)


def __a (	__lowerCamelCase			:						logging.Handler				)	->							Optional[int]:
      '''simple docstring'''


      _configure_library_root_logger()

      assert handler is not None and handler not in _get_library_root_logger().handlers
      _get_library_root_logger().removeHandler(snake_case__				)


def __a (	)	->							List[str]:
      '''simple docstring'''


      _configure_library_root_logger()
      lowercase_     =      False


def __a (	)	->							int:
      '''simple docstring'''


      _configure_library_root_logger()
      lowercase_     =      True


def __a (	)	->							Union[str, Any]:
      '''simple docstring'''


      lowercase_     =      _get_library_root_logger().handlers

      for handler in handlers:
            lowercase_     =      logging.Formatter("[%(levelname)s|%(filename)s:%(lineno)s] %(asctime)s >> %(message)s"				)
            handler.setFormatter(snake_case__				)


def __a (	)	->							Optional[Any]:
      '''simple docstring'''


      lowercase_     =      _get_library_root_logger().handlers

      for handler in handlers:
            handler.setFormatter(snake_case__				)


def __a (	self			:						str ,		*__lowerCamelCase			:						int ,		**__lowerCamelCase			:						Tuple				)	->							Union[str, Any]:
      '''simple docstring'''


      lowercase_     =      os.getenv("TRANSFORMERS_NO_ADVISORY_WARNINGS" ,		snake_case__				)
      if no_advisory_warnings:
            return
      self.warning(*snake_case__ ,		**snake_case__				)


lowerCAmelCase_ : Union[str, Any]						  =      warning_advice


@functools.lru_cache(snake_case__				)
def __a (	self			:						Optional[Any] ,		*__lowerCamelCase			:						List[Any] ,		**__lowerCamelCase			:						Union[str, Any]				)	->							Dict:
      '''simple docstring'''


      self.warning(*snake_case__ ,		**snake_case__				)


lowerCAmelCase_ : Any						  =      warning_once





class 							lowercase						:


   def __init__(   self				:	str   ,		*__lowerCAmelCase				:	List[str]   ,		**__lowerCAmelCase				:	Union[str, Any])      ->					Dict:  # pylint: disable=unused-argument
         lowercase_     =      args[0] if args else None


   def __iter__(   self				:	List[Any])      ->					Union[str, Any]:
         return iter(self._iterator)


   def __getattr__(   self				:	Dict   ,		__lowerCAmelCase				:	Dict)      ->					str:

         def empty_fn(*__lowerCAmelCase				:	Dict   ,		**__lowerCAmelCase				:	Optional[Any]):  # pylint: disable=unused-argument
               return

         return empty_fn


   def __enter__(   self				:	int)      ->					Union[str, Any]:
         return self


   def __exit__(   self				:	int   ,		__lowerCAmelCase				:	List[str]   ,		__lowerCAmelCase				:	Optional[int]   ,		__lowerCAmelCase				:	Dict)      ->					Tuple:
         return





class 							lowercase						:


   def __call__(   self				:	Optional[int]   ,		*__lowerCAmelCase				:	Any   ,		**__lowerCAmelCase				:	Dict)      ->					List[str]:
         if _tqdm_active:
               return tqdm_lib.tqdm(*A_   ,		**A_)
         else:
               return EmptyTqdm(*A_   ,		**A_)


   def __UpperCAmelCase       (   self				:	Optional[int]   ,		*__lowerCAmelCase				:	Optional[int]   ,		**__lowerCAmelCase				:	Tuple)      ->					Any:
         lowercase_     =      None
         if _tqdm_active:
               return tqdm_lib.tqdm.set_lock(*A_   ,		**A_)


   def __UpperCAmelCase       (   self				:	Dict)      ->					List[Any]:
         if _tqdm_active:
               return tqdm_lib.tqdm.get_lock()




lowerCAmelCase_ : List[str]						  =      _tqdm_cls()


def __a (	)	->							str:
      '''simple docstring'''


      global _tqdm_active
      return bool(_tqdm_active				)


def __a (	)	->							Any:
      '''simple docstring'''


      global _tqdm_active
      lowercase_     =      True
      hf_hub_utils.enable_progress_bars()






def __a (	)	->							Optional[Any]:
      '''simple docstring'''


      global _tqdm_active
      lowercase_     =      False
      hf_hub_utils.disable_progress_bars()







'''simple docstring'''

import argparse
import os

import torch

from transformers import FlavaConfig, FlavaForPreTraining
from transformers.models.flava.convert_dalle_to_flava_codebook import convert_dalle_checkpoint


def __a (	__lowerCamelCase			:						List[Any]				)	->							Tuple:
      '''simple docstring'''


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


def __a (	__lowerCamelCase			:						str ,		__lowerCamelCase			:						str				)	->							List[str]:
      '''simple docstring'''


      lowercase_     =      {}

      for key, value in state_dict.items():
            if "text_encoder.embeddings" in key or "image_encoder.embeddings" in key:
                  continue

            lowercase_     =      key.replace("heads.cmd.mim_head.cls.predictions" ,		"mmm_image_head"				)
            lowercase_     =      key.replace("heads.cmd.mlm_head.cls.predictions" ,		"mmm_text_head"				)
            lowercase_     =      key.replace("heads.cmd.itm_head.cls" ,		"itm_head"				)
            lowercase_     =      key.replace("heads.cmd.itm_head.pooler" ,		"itm_head.pooler"				)
            lowercase_     =      key.replace("heads.cmd.clip_head.logit_scale" ,		"flava.logit_scale"				)
            lowercase_     =      key.replace("heads.fairseq_mlm.cls.predictions" ,		"mlm_head"				)
            lowercase_     =      key.replace("heads.imagenet.mim_head.cls.predictions" ,		"mim_head"				)
            lowercase_     =      key.replace("mm_text_projection" ,		"flava.text_to_mm_projection"				)
            lowercase_     =      key.replace("mm_image_projection" ,		"flava.image_to_mm_projection"				)
            lowercase_     =      key.replace("image_encoder.module" ,		"flava.image_model"				)
            lowercase_     =      key.replace("text_encoder.module" ,		"flava.text_model"				)
            lowercase_     =      key.replace("mm_encoder.module.encoder.cls_token" ,		"flava.multimodal_model.cls_token"				)
            lowercase_     =      key.replace("mm_encoder.module" ,		"flava.multimodal_model"				)
            lowercase_     =      key.replace("text_projection" ,		"flava.text_projection"				)
            lowercase_     =      key.replace("image_projection" ,		"flava.image_projection"				)

            lowercase_     =      value.float()

      for key, value in codebook_state_dict.items():
            lowercase_     =      value

      return upgrade


@torch.no_grad()
def __a (	__lowerCamelCase			:						Dict ,		__lowerCamelCase			:						List[Any] ,		__lowerCamelCase			:						List[str] ,		__lowerCamelCase			:						Tuple=None				)	->							Optional[int]:
      '''simple docstring'''


      if config_path is not None:
            lowercase_     =      FlavaConfig.from_pretrained(__lowerCamelCase				)
      else:
            lowercase_     =      FlavaConfig()

      lowercase_     =      FlavaForPreTraining(__lowerCamelCase				).eval()

      lowercase_     =      convert_dalle_checkpoint(__lowerCamelCase ,		__lowerCamelCase ,		save_checkpoint=__lowerCamelCase				)

      if os.path.exists(__lowerCamelCase				):
            lowercase_     =      torch.load(__lowerCamelCase ,		map_location="cpu"				)
      else:
            lowercase_     =      torch.hub.load_state_dict_from_url(__lowerCamelCase ,		map_location="cpu"				)

      lowercase_     =      upgrade_state_dict(__lowerCamelCase ,		__lowerCamelCase				)
      hf_model.load_state_dict(__lowerCamelCase				)
      lowercase_     =      hf_model.state_dict()
      lowercase_     =      count_parameters(__lowerCamelCase				)
      lowercase_     =      count_parameters(__lowerCamelCase				) + count_parameters(__lowerCamelCase				)

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

      hf_model.save_pretrained(__lowerCamelCase				)


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("--codebook_path", default=None, type=str, help="Path to flava codebook checkpoint")
       parser.add_argument("--config_path", default=None, type=str, help="Path to hf config.json of model to convert")
       lowerCAmelCase_ : List[Any]						  =      parser.parse_args()

       convert_flava_checkpoint(args.checkpoint_path, args.codebook_path, args.pytorch_dump_folder_path, args.config_path)






