


"""simple docstring"""

from ...configuration_utils import PretrainedConfig
from ...utils import logging


UpperCamelCase     :    Dict       =			logging.get_logger(__name__)

UpperCamelCase     :    str       =			{
    "alibaba-damo/mgp-str-base": "https://huggingface.co/alibaba-damo/mgp-str-base/resolve/main/config.json",
}

class __lowerCAmelCase		(				__SCREAMING_SNAKE_CASE      ):
     lowercase						       =						"mgp-str"





     def __init__(     self     ,					__UpperCAmelCase=[32, 128]     ,					__UpperCAmelCase=4     ,					__UpperCAmelCase=3     ,					__UpperCAmelCase=27     ,					__UpperCAmelCase=38     ,					__UpperCAmelCase=5_0257     ,					__UpperCAmelCase=3_0522     ,					__UpperCAmelCase=768     ,					__UpperCAmelCase=12     ,					__UpperCAmelCase=12     ,					__UpperCAmelCase=4.0     ,					__UpperCAmelCase=True     ,					__UpperCAmelCase=False     ,					__UpperCAmelCase=1E-5     ,					__UpperCAmelCase=0.0     ,					__UpperCAmelCase=0.0     ,					__UpperCAmelCase=0.0     ,					__UpperCAmelCase=False     ,					__UpperCAmelCase=0.0_2     ,					**__UpperCAmelCase     ,					):

      '''simple docstring'''




      super().__init__(**__UpperCAmelCase				)

      __UpperCamelCase      =	image_size
      __UpperCamelCase      =	patch_size
      __UpperCamelCase      =	num_channels
      __UpperCamelCase      =	max_token_length
      __UpperCamelCase      =	num_character_labels
      __UpperCamelCase      =	num_bpe_labels
      __UpperCamelCase      =	num_wordpiece_labels
      __UpperCamelCase      =	hidden_size
      __UpperCamelCase      =	num_hidden_layers
      __UpperCamelCase      =	num_attention_heads
      __UpperCamelCase      =	mlp_ratio
      __UpperCamelCase      =	distilled
      __UpperCamelCase      =	layer_norm_eps
      __UpperCamelCase      =	drop_rate
      __UpperCamelCase      =	qkv_bias
      __UpperCamelCase      =	attn_drop_rate
      __UpperCamelCase      =	drop_path_rate
      __UpperCamelCase      =	output_aa_attentions
      __UpperCamelCase      =	initializer_range





"""simple docstring"""

from typing import Union

import fire
import torch
from tqdm import tqdm






def 							A						(    snake_case				:str    , snake_case				:str = "cpu"    , snake_case				:Union[str, None] = None		)				->     None:
 __UpperCamelCase      =	torch.load(snake_case    , map_location=snake_case		)
 for k, v in tqdm(state_dict.items()		):
  if not isinstance(snake_case    , torch.Tensor		):
   raise TypeError('FP16 conversion only works on paths that are saved state dicts, like pytorch_model.bin'		)
  __UpperCamelCase      =	v.half()
 if save_path is None:  # overwrite src_path
  __UpperCamelCase      =	src_path
 torch.save(snake_case    , snake_case		)


if __name__ == "__main__":
      fire.Fire(convert)



