




"""simple docstring"""







import argparse

import requests
import torch
from PIL import Image

from transformers import ViTMAEConfig, ViTMAEForPreTraining, ViTMAEImageProcessor





def      __snake_case (				_lowercase    ):


    """simple docstring"""







    if "cls_token" in name:
        UpperCamelCase              =	name.replace('''cls_token'''			,'''vit.embeddings.cls_token'''    )
    if "mask_token" in name:
        UpperCamelCase              =	name.replace('''mask_token'''			,'''decoder.mask_token'''    )
    if "decoder_pos_embed" in name:
        UpperCamelCase              =	name.replace('''decoder_pos_embed'''			,'''decoder.decoder_pos_embed'''    )
    if "pos_embed" in name and "decoder" not in name:
        UpperCamelCase              =	name.replace('''pos_embed'''			,'''vit.embeddings.position_embeddings'''    )
    if "patch_embed.proj" in name:
        UpperCamelCase              =	name.replace('''patch_embed.proj'''			,'''vit.embeddings.patch_embeddings.projection'''    )
    if "patch_embed.norm" in name:
        UpperCamelCase              =	name.replace('''patch_embed.norm'''			,'''vit.embeddings.norm'''    )
    if "decoder_blocks" in name:
        UpperCamelCase              =	name.replace('''decoder_blocks'''			,'''decoder.decoder_layers'''    )
    if "blocks" in name:
        UpperCamelCase              =	name.replace('''blocks'''			,'''vit.encoder.layer'''    )
    if "attn.proj" in name:
        UpperCamelCase              =	name.replace('''attn.proj'''			,'''attention.output.dense'''    )
    if "attn" in name:
        UpperCamelCase              =	name.replace('''attn'''			,'''attention.self'''    )
    if "norm1" in name:
        UpperCamelCase              =	name.replace('''norm1'''			,'''layernorm_before'''    )
    if "norm2" in name:
        UpperCamelCase              =	name.replace('''norm2'''			,'''layernorm_after'''    )
    if "mlp.fc1" in name:
        UpperCamelCase              =	name.replace('''mlp.fc1'''			,'''intermediate.dense'''    )
    if "mlp.fc2" in name:
        UpperCamelCase              =	name.replace('''mlp.fc2'''			,'''output.dense'''    )
    if "decoder_embed" in name:
        UpperCamelCase              =	name.replace('''decoder_embed'''			,'''decoder.decoder_embed'''    )
    if "decoder_norm" in name:
        UpperCamelCase              =	name.replace('''decoder_norm'''			,'''decoder.decoder_norm'''    )
    if "decoder_pred" in name:
        UpperCamelCase              =	name.replace('''decoder_pred'''			,'''decoder.decoder_pred'''    )
    if "norm.weight" in name and "decoder" not in name:
        UpperCamelCase              =	name.replace('''norm.weight'''			,'''vit.layernorm.weight'''    )
    if "norm.bias" in name and "decoder" not in name:
        UpperCamelCase              =	name.replace('''norm.bias'''			,'''vit.layernorm.bias'''    )

    return name





def      __snake_case (				_lowercase			,_lowercase    ):


    """simple docstring"""







    for key in orig_state_dict.copy().keys():
        UpperCamelCase              =	orig_state_dict.pop(_lowercase    )

        if "qkv" in key:
            UpperCamelCase              =	key.split('''.'''    )
            UpperCamelCase              =	int(key_split[1]    )
            if "decoder_blocks" in key:
                UpperCamelCase              =	config.decoder_hidden_size
                UpperCamelCase              =	'''decoder.decoder_layers.'''
                if "weight" in key:
                    UpperCamelCase              =	val[:dim, :]
                    UpperCamelCase              =	val[dim : dim * 2, :]
                    UpperCamelCase              =	val[-dim:, :]
                elif "bias" in key:
                    UpperCamelCase              =	val[:dim]
                    UpperCamelCase              =	val[dim : dim * 2]
                    UpperCamelCase              =	val[-dim:]
            else:
                UpperCamelCase              =	config.hidden_size
                UpperCamelCase              =	'''vit.encoder.layer.'''
                if "weight" in key:
                    UpperCamelCase              =	val[:dim, :]
                    UpperCamelCase              =	val[dim : dim * 2, :]
                    UpperCamelCase              =	val[-dim:, :]
                elif "bias" in key:
                    UpperCamelCase              =	val[:dim]
                    UpperCamelCase              =	val[dim : dim * 2]
                    UpperCamelCase              =	val[-dim:]

        else:
            UpperCamelCase              =	val

    return orig_state_dict





def      __snake_case (				_lowercase			,_lowercase    ):


    """simple docstring"""







    UpperCamelCase              =	ViTMAEConfig()
    if "large" in checkpoint_url:
        UpperCamelCase              =	1024
        UpperCamelCase              =	4096
        UpperCamelCase              =	24
        UpperCamelCase              =	16
    elif "huge" in checkpoint_url:
        UpperCamelCase              =	14
        UpperCamelCase              =	1280
        UpperCamelCase              =	5120
        UpperCamelCase              =	32
        UpperCamelCase              =	16

    UpperCamelCase              =	ViTMAEForPreTraining(_lowercase    )

    UpperCamelCase              =	torch.hub.load_state_dict_from_url(_lowercase			,map_location='''cpu'''    )['''model''']

    UpperCamelCase              =	ViTMAEImageProcessor(size=config.image_size    )

    UpperCamelCase              =	convert_state_dict(_lowercase			,_lowercase    )

    model.load_state_dict(_lowercase    )
    model.eval()

    UpperCamelCase              =	'''https://user-images.githubusercontent.com/11435359/147738734-196fd92f-9260-48d5-ba7e-bf103d29364d.jpg'''

    UpperCamelCase              =	Image.open(requests.get(_lowercase			,stream=_lowercase    ).raw    )
    UpperCamelCase              =	ViTMAEImageProcessor(size=config.image_size    )
    UpperCamelCase              =	image_processor(images=_lowercase			,return_tensors='''pt'''    )

    # forward pass
    torch.manual_seed(2    )
    UpperCamelCase              =	model(**_lowercase    )
    UpperCamelCase              =	outputs.logits

    if "large" in checkpoint_url:
        UpperCamelCase              =	torch.tensor(
            [[-0.7309, -0.7128, -1.0169], [-1.0161, -0.9058, -1.1878], [-1.0478, -0.9411, -1.1911]]    )
    elif "huge" in checkpoint_url:
        UpperCamelCase              =	torch.tensor(
            [[-1.1599, -0.9199, -1.2221], [-1.1952, -0.9269, -1.2307], [-1.2143, -0.9337, -1.2262]]    )
    else:
        UpperCamelCase              =	torch.tensor(
            [[-0.9192, -0.8481, -1.1259], [-1.1349, -1.0034, -1.2599], [-1.1757, -1.0429, -1.2726]]    )

    # verify logits
    assert torch.allclose(logits[0, :3, :3]			,_lowercase			,atol=1e-4    )

    print(f'Saving model to {pytorch_dump_folder_path}'    )
    model.save_pretrained(_lowercase    )

    print(f'Saving image processor to {pytorch_dump_folder_path}'    )
    image_processor.save_pretrained(_lowercase    )


if __name__ == "__main__":
  SCREAMING_SNAKE_CASE_	     =       argparse.ArgumentParser()
  # Required parameters
  parser.add_argument(
      '--checkpoint_url',
      default='https://dl.fbaipublicfiles.com/mae/visualize/mae_visualize_vit_base.pth',
      type=str,
      help='URL of the checkpoint you\'d like to convert.',
  )
  parser.add_argument(
      '--pytorch_dump_folder_path', default=None, type=str, help='Path to the output PyTorch model directory.'
  )

  SCREAMING_SNAKE_CASE_	     =       parser.parse_args()
  convert_vit_mae_checkpoint(args.checkpoint_url, args.pytorch_dump_folder_path)



'''simple docstring'''

import os
import unicodedata
from shutil import copyfile
from typing import Any, Dict, List, Optional, Tuple

import sentencepiece as spm

from ...tokenization_utils import AddedToken, PreTrainedTokenizer
from ...utils import SPIECE_UNDERLINE, logging


lowerCamelCase				:  str    		=      logging.get_logger(__name__)

lowerCamelCase				:  str    		=      {'vocab_file': 'spiece.model'}

lowerCamelCase				:  int    		=      {
    'vocab_file': {
        'TsinghuaAI/CPM-Generate': 'https://huggingface.co/TsinghuaAI/CPM-Generate/resolve/main/spiece.model',
    }
}
class     __lowerCAmelCase		(lowercase_	):





      '''simple docstring'''






      def __init__(self       :       List[Any]  ,		UpperCamelCase       :       Optional[Any]  ,		UpperCamelCase       :       Any=False  ,		UpperCamelCase       :       Dict=True  ,		UpperCamelCase       :       int=False  ,		UpperCamelCase       :       Optional[Any]="<s>"  ,		UpperCamelCase       :       Union[str, Any]="</s>"  ,		UpperCamelCase       :       Optional[int]="<unk>"  ,		UpperCamelCase       :       List[Any]="<sep>"  ,		UpperCamelCase       :       Dict="<pad>"  ,		UpperCamelCase       :       int="<cls>"  ,		UpperCamelCase       :       int="<mask>"  ,		UpperCamelCase       :       str=["<eop>", "<eod>"]  ,		UpperCamelCase       :       Optional[Dict[str, Any]] = None  ,		**UpperCamelCase       :       Dict  ,		):

             '''simple docstring'''







             lowercase__      =					AddedToken(UpperCamelCase  ,		lstrip=UpperCamelCase  ,		rstrip=UpperCamelCase					) if isinstance(UpperCamelCase  ,		UpperCamelCase					) else mask_token

             lowercase__      =					{} if sp_model_kwargs is None else sp_model_kwargs

             super().__init__(
                 do_lower_case=UpperCamelCase  ,		remove_space=UpperCamelCase  ,		keep_accents=UpperCamelCase  ,		bos_token=UpperCamelCase  ,		eos_token=UpperCamelCase  ,		unk_token=UpperCamelCase  ,		sep_token=UpperCamelCase  ,		pad_token=UpperCamelCase  ,		cls_token=UpperCamelCase  ,		mask_token=UpperCamelCase  ,		additional_special_tokens=UpperCamelCase  ,		sp_model_kwargs=self.sp_model_kwargs  ,		**UpperCamelCase  ,		)

             lowercase__      =					3

             lowercase__      =					do_lower_case
             lowercase__      =					remove_space
             lowercase__      =					keep_accents
             lowercase__      =					vocab_file

             lowercase__      =					spm.SentencePieceProcessor(**self.sp_model_kwargs					)
             self.sp_model.Load(UpperCamelCase					)

             try:
                    import jieba
             except ModuleNotFoundError as error:
                    raise error.__class__(
                        '''You need to install jieba to use CpmTokenizer or CpmTokenizerFast. '''
                        '''See https://pypi.org/project/jieba/ for installation.'''					)
             lowercase__      =					jieba
             lowercase__      =					str.maketrans(''' \n'''  ,		'''\u2582\u2583'''					)



      @property
      # Copied from transformers.models.xlnet.tokenization_xlnet.XLNetTokenizer.vocab_size
      def  UpperCamelCase__						(self       :       List[str]					):

             '''simple docstring'''







             return len(self.sp_model					)



      def  UpperCamelCase__						(self       :       List[Any]					):

             '''simple docstring'''







             lowercase__      =					{self.convert_ids_to_tokens(UpperCamelCase					): i for i in range(self.vocab_size					)}
             vocab.update(self.added_tokens_encoder					)
             return vocab



      def __getstate__(self       :       Union[str, Any]					):

             '''simple docstring'''







             lowercase__      =					self.__dict__.copy()
             lowercase__      =					None
             return state



      def __setstate__(self       :       Dict  ,		UpperCamelCase       :       int					):

             '''simple docstring'''







             lowercase__      =					d

             # for backward compatibility
             if not hasattr(self  ,		'''sp_model_kwargs'''					):
                    lowercase__      =					{}

             lowercase__      =					spm.SentencePieceProcessor(**self.sp_model_kwargs					)
             self.sp_model.Load(self.vocab_file					)



      def  UpperCamelCase__						(self       :       Optional[int]  ,		UpperCamelCase       :       Dict					):

             '''simple docstring'''







             if self.remove_space:
                    lowercase__      =					''' '''.join(inputs.strip().split()					)
             else:
                    lowercase__      =					inputs
             lowercase__      =					outputs.replace('''``'''  ,		'''"'''					).replace('''\'\''''  ,		'''"'''					)

             if not self.keep_accents:
                    lowercase__      =					unicodedata.normalize('''NFKD'''  ,		UpperCamelCase					)
                    lowercase__      =					''''''.join([c for c in outputs if not unicodedata.combining(UpperCamelCase					)]					)
             if self.do_lower_case:
                    lowercase__      =					outputs.lower()

             return outputs



      def  UpperCamelCase__						(self       :       List[Any]  ,		UpperCamelCase       :       str					):

             '''simple docstring'''







             lowercase__      =					self.preprocess_text(UpperCamelCase					)
             lowercase__      =					self.sp_model.encode(UpperCamelCase  ,		out_type=UpperCamelCase					)
             lowercase__      =					[]
             for piece in pieces:
                    if len(UpperCamelCase					) > 1 and piece[-1] == str(''','''					) and piece[-2].isdigit():
                           lowercase__      =					self.sp_model.EncodeAsPieces(piece[:-1].replace(UpperCamelCase  ,		''''''					)					)
                           if piece[0] != SPIECE_UNDERLINE and cur_pieces[0][0] == SPIECE_UNDERLINE:
                                  if len(cur_pieces[0]					) == 1:
                                         lowercase__      =					cur_pieces[1:]
                                  else:
                                         lowercase__      =					cur_pieces[0][1:]
                           cur_pieces.append(piece[-1]					)
                           new_pieces.extend(UpperCamelCase					)
                    else:
                           new_pieces.append(UpperCamelCase					)

             return new_pieces



      def  UpperCamelCase__						(self       :       int  ,		UpperCamelCase       :       str					):

             '''simple docstring'''







             return self.sp_model.PieceToId(UpperCamelCase					)



      def  UpperCamelCase__						(self       :       str  ,		UpperCamelCase       :       Optional[Any]					):

             '''simple docstring'''







             return self.sp_model.IdToPiece(UpperCamelCase					)



      def  UpperCamelCase__						(self       :       Union[str, Any]  ,		UpperCamelCase       :       str					):

             '''simple docstring'''







             lowercase__      =					''''''.join(UpperCamelCase					).replace(UpperCamelCase  ,		''' '''					).strip()
             return out_string



      def  UpperCamelCase__						(self       :       Any  ,		UpperCamelCase       :       List[int]  ,		UpperCamelCase       :       Optional[List[int]] = None					):

             '''simple docstring'''







             lowercase__      =					[self.sep_token_id]
             lowercase__      =					[self.cls_token_id]
             if token_ids_a is None:
                    return token_ids_a + sep + cls
             return token_ids_a + sep + token_ids_a + sep + cls



      def  UpperCamelCase__						(self       :       Tuple  ,		UpperCamelCase       :       List[int]  ,		UpperCamelCase       :       Optional[List[int]] = None  ,		UpperCamelCase       :       bool = False					):

             '''simple docstring'''







             if already_has_special_tokens:
                    return super().get_special_tokens_mask(
                        token_ids_a=UpperCamelCase  ,		token_ids_a=UpperCamelCase  ,		already_has_special_tokens=UpperCamelCase					)

             if token_ids_a is not None:
                    return ([0] * len(UpperCamelCase					)) + [1] + ([0] * len(UpperCamelCase					)) + [1, 1]
             return ([0] * len(UpperCamelCase					)) + [1, 1]



      def  UpperCamelCase__						(self       :       str  ,		UpperCamelCase       :       List[int]  ,		UpperCamelCase       :       Optional[List[int]] = None					):

             '''simple docstring'''







             lowercase__      =					[self.sep_token_id]
             lowercase__      =					[2]

             if token_ids_a is None:
                    return len(token_ids_a + sep					) * [0] + cls_segment_id
             return len(token_ids_a + sep					) * [0] + len(token_ids_a + sep					) * [1] + cls_segment_id



      def  UpperCamelCase__						(self       :       Tuple  ,		UpperCamelCase       :       str  ,		UpperCamelCase       :       Optional[str] = None					):

             '''simple docstring'''







             if not os.path.isdir(UpperCamelCase					):
                    logger.error(f"Vocabulary path ({save_directory}) should be a directory"					)
                    return
             lowercase__      =					os.path.join(
                 UpperCamelCase  ,		(filename_prefix + '''-''' if filename_prefix else '''''') + VOCAB_FILES_NAMES['''vocab_file''']					)

             if os.path.abspath(self.vocab_file					) != os.path.abspath(UpperCamelCase					) and os.path.isfile(self.vocab_file					):
                    copyfile(self.vocab_file  ,		UpperCamelCase					)
             elif not os.path.isfile(self.vocab_file					):
                    with open(UpperCamelCase  ,		'''wb'''					) as fi:
                           lowercase__      =					self.sp_model.serialized_model_proto()
                           fi.write(UpperCamelCase					)

             return (out_vocab_file,)






      def  UpperCamelCase__						(self       :       List[str]  ,		*UpperCamelCase       :       List[Any]  ,		**UpperCamelCase       :       Union[str, Any]					):

             '''simple docstring'''







             lowercase__      =					super()._decode(*UpperCamelCase  ,		**UpperCamelCase					)
             lowercase__      =					text.replace(''' '''  ,		''''''					).replace('''\u2582'''  ,		''' '''					).replace('''\u2583'''  ,		'''\n'''					)
             return text




