
"""simple docstring"""
import argparse

import torch

from ...utils import logging
from . import AlbertConfig, AlbertForPreTraining, load_tf_weights_in_albert


logging.set_verbosity_info()

def  lowercase     (_lowerCAmelCase ,    _lowerCAmelCase ,    _lowerCAmelCase						):
						# Initialise PyTorch model
						__lowerCAmelCase     =  AlbertConfig.from_json_file(_lowerCAmelCase						)
						print(f"""Building PyTorch model from configuration: {config}"""						)
						__lowerCAmelCase     =  AlbertForPreTraining(_lowerCAmelCase						)

						# Load weights from tf checkpoint
						load_tf_weights_in_albert(_lowerCAmelCase ,    _lowerCAmelCase ,    _lowerCAmelCase						)

						# Save pytorch-model
						print(f"""Save PyTorch model to {pytorch_dump_path}"""						)
						torch.save(model.state_dict() ,    _lowerCAmelCase						)


if __name__ == "__main__":
			SCREAMING_SNAKE_CASE_					     =	argparse.ArgumentParser()
			# Required parameters
			parser.add_argument(
			    '''--tf_checkpoint_path''', default=None, type=str, required=True, help='''Path to the TensorFlow checkpoint path.'''
			)
			parser.add_argument(
			    '''--albert_config_file''',
			    default=None,
			    type=str,
			    required=True,
			    help=(
			        '''The config json file corresponding to the pre-trained ALBERT model. \n'''
			        '''This specifies the model architecture.'''
			    ),
			)
			parser.add_argument(
			    '''--pytorch_dump_path''', default=None, type=str, required=True, help='''Path to the output PyTorch model.'''
			)
			SCREAMING_SNAKE_CASE_					     =	parser.parse_args()
			convert_tf_checkpoint_to_pytorch(args.tf_checkpoint_path, args.albert_config_file, args.pytorch_dump_path)


"""simple docstring"""
from typing import List

from .keymap import KEYMAP, get_character

def  lowercase     (_lowerCAmelCase						):

						def decorator(_lowerCAmelCase						):
												__lowerCAmelCase     =  getattr(_lowerCAmelCase ,    """handle_key""" ,    []						)
												handle += [key]
												setattr(_lowerCAmelCase ,    """handle_key""" ,    _lowerCAmelCase						)
												return func

						return decorator

def  lowercase     (*_lowerCAmelCase						):

						def decorator(_lowerCAmelCase						):
												__lowerCAmelCase     =  getattr(_lowerCAmelCase ,    """handle_key""" ,    []						)
												handle += keys
												setattr(_lowerCAmelCase ,    """handle_key""" ,    _lowerCAmelCase						)
												return func

						return decorator
class       lowerCAmelCase_		(				A__ ):



							'''simple docstring'''





							def __new__( cls    ,				snake_case_    ,				snake_case_    ,				snake_case_				)       ->  Any:
													__lowerCAmelCase     =  super().__new__(cls    ,				snake_case_    ,				snake_case_    ,				snake_case_				)
													if not hasattr(snake_case_    ,				"""key_handler"""				):
																			setattr(snake_case_    ,				"""key_handler"""    ,				{}				)
													setattr(snake_case_    ,				"""handle_input"""    ,				KeyHandler.handle_input				)

													for value in attrs.values():
																			__lowerCAmelCase     =  getattr(snake_case_    ,				"""handle_key"""    ,				[]				)
																			for key in handled_keys:
																									__lowerCAmelCase     =  value
													return new_cls




							@staticmethod
							def    A__						( cls				)       ->  Tuple:
													__lowerCAmelCase     =  get_character()
													if char != KEYMAP["undefined"]:
																			__lowerCAmelCase     =  ord(snake_case_				)
													__lowerCAmelCase     =  cls.key_handler.get(snake_case_				)
													if handler:
																			__lowerCAmelCase     =  char
																			return handler(cls				)
													else:
																			return None

def  lowercase     (cls						):
						return KeyHandler(cls.__name__ ,    cls.__bases__ ,    cls.__dict__.copy()						)
