


'''simple docstring'''
import argparse

import torch

from transformers import YosoConfig, YosoForMaskedLM


def      a (     __a  )    ->      Optional[int]:



					'''simple docstring'''






					if "model" in orig_key:
										UpperCamelCase__  :Any				   =					orig_key.replace('''model.'''					,   ''''''  )
					if "norm1" in orig_key:
										UpperCamelCase__  :Any				   =					orig_key.replace('''norm1'''					,   '''attention.output.LayerNorm'''  )
					if "norm2" in orig_key:
										UpperCamelCase__  :int				   =					orig_key.replace('''norm2'''					,   '''output.LayerNorm'''  )
					if "norm" in orig_key:
										UpperCamelCase__  :List[Any]				   =					orig_key.replace('''norm'''					,   '''LayerNorm'''  )
					if "transformer" in orig_key:
										UpperCamelCase__  :List[str]				   =					orig_key.split('''.'''  )[0].split('''_'''  )[-1]
										UpperCamelCase__  :Dict				   =					orig_key.replace(f'''transformer_{layer_num}'''					,   f'''encoder.layer.{layer_num}'''  )
					if "mha.attn" in orig_key:
										UpperCamelCase__  :List[str]				   =					orig_key.replace('''mha.attn'''					,   '''attention.self'''  )
					if "mha" in orig_key:
										UpperCamelCase__  :Any				   =					orig_key.replace('''mha'''					,   '''attention'''  )
					if "W_q" in orig_key:
										UpperCamelCase__  :Optional[int]				   =					orig_key.replace('''W_q'''					,   '''self.query'''  )
					if "W_k" in orig_key:
										UpperCamelCase__  :Any				   =					orig_key.replace('''W_k'''					,   '''self.key'''  )
					if "W_v" in orig_key:
										UpperCamelCase__  :Optional[Any]				   =					orig_key.replace('''W_v'''					,   '''self.value'''  )
					if "ff1" in orig_key:
										UpperCamelCase__  :Union[str, Any]				   =					orig_key.replace('''ff1'''					,   '''intermediate.dense'''  )
					if "ff2" in orig_key:
										UpperCamelCase__  :Optional[Any]				   =					orig_key.replace('''ff2'''					,   '''output.dense'''  )
					if "ff" in orig_key:
										UpperCamelCase__  :List[Any]				   =					orig_key.replace('''ff'''					,   '''output.dense'''  )
					if "mlm_class" in orig_key:
										UpperCamelCase__  :str				   =					orig_key.replace('''mlm.mlm_class'''					,   '''cls.predictions.decoder'''  )
					if "mlm" in orig_key:
										UpperCamelCase__  :List[str]				   =					orig_key.replace('''mlm'''					,   '''cls.predictions.transform'''  )
					if "cls" not in orig_key:
										UpperCamelCase__  :Union[str, Any]				   =					'''yoso.''' + orig_key

					return orig_key


def      a (     __a					,   __a  )    ->      Union[str, Any]:



					'''simple docstring'''






					for key in orig_state_dict.copy().keys():
										UpperCamelCase__  :List[Any]				   =					orig_state_dict.pop(__a  )

										if ("pooler" in key) or ("sen_class" in key):
															continue
										else:
															UpperCamelCase__  :List[Any]				   =					val

					UpperCamelCase__  :int				   =					orig_state_dict['''cls.predictions.decoder.bias''']
					UpperCamelCase__  :Union[str, Any]				   =					torch.arange(__a  ).expand((1, -1)  ) + 2

					return orig_state_dict


def      a (     __a					,   __a					,   __a  )    ->      List[str]:



					'''simple docstring'''






					UpperCamelCase__  :int				   =					torch.load(__a					,   map_location='''cpu'''  )['''model_state_dict''']
					UpperCamelCase__  :List[str]				   =					YosoConfig.from_json_file(__a  )
					UpperCamelCase__  :Optional[int]				   =					YosoForMaskedLM(__a  )

					UpperCamelCase__  :Union[str, Any]				   =					convert_checkpoint_helper(config.max_position_embeddings					,   __a  )

					print(model.load_state_dict(__a  )  )
					model.eval()
					model.save_pretrained(__a  )

					print(f'''Checkpoint successfuly converted. Model saved at {pytorch_dump_path}'''  )


if __name__ == "__main__":
		__snake_case				 =	argparse.ArgumentParser()
		# Required parameters
		parser.add_argument(
		    '''--pytorch_model_path''', default=None, type=str, required=True, help='''Path to YOSO pytorch checkpoint.'''
		)
		parser.add_argument(
		    '''--config_file''',
		    default=None,
		    type=str,
		    required=True,
		    help='''The json file for YOSO model config.''',
		)
		parser.add_argument(
		    '''--pytorch_dump_path''', default=None, type=str, required=True, help='''Path to the output PyTorch model.'''
		)
		__snake_case				 =	parser.parse_args()
		convert_yoso_checkpoint(args.pytorch_model_path, args.config_file, args.pytorch_dump_path)



'''simple docstring'''
import importlib
import os
import sys


# This is required to make the module import works (when the python process is running from the root of the repo)
sys.path.append('''.''')


def      a (     __a  )    ->      List[str]:



					'''simple docstring'''






					UpperCamelCase__  :int				   =					test_file.split(os.path.sep  )
					if components[0:2] != ["tests", "models"]:
										raise ValueError(
										    '''`test_file` should start with `tests/models/` (with `/` being the OS specific path separator). Got '''
										    f'''{test_file} instead.'''  )
					UpperCamelCase__  :List[Any]				   =					components[-1]
					if not test_fn.endswith('''py'''  ):
										raise ValueError(f'''`test_file` should be a python file. Got {test_fn} instead.'''  )
					if not test_fn.startswith('''test_modeling_'''  ):
										raise ValueError(
										    f'''`test_file` should point to a file name of the form `test_modeling_*.py`. Got {test_fn} instead.'''  )

					UpperCamelCase__  :Optional[Any]				   =					components[:-1] + [test_fn.replace('''.py'''					,   ''''''  )]
					UpperCamelCase__  :str				   =					'''.'''.join(__a  )

					return test_module_path


def      a (     __a  )    ->      Tuple:



					'''simple docstring'''






					UpperCamelCase__  :Dict				   =					get_module_path(__a  )
					UpperCamelCase__  :List[str]				   =					importlib.import_module(__a  )

					return test_module


def      a (     __a  )    ->      int:



					'''simple docstring'''






					UpperCamelCase__  :Dict				   =					[]
					UpperCamelCase__  :Optional[Any]				   =					get_test_module(__a  )
					for attr in dir(__a  ):
										if attr.endswith('''ModelTester'''  ):
															tester_classes.append(getattr(__a					,   __a  )  )

    # sort with class names
					return sorted(__a					,   key=lambda __a  : x.__name__  )


def      a (     __a  )    ->      List[Any]:



					'''simple docstring'''






					UpperCamelCase__  :List[Any]				   =					[]
					UpperCamelCase__  :Dict				   =					get_test_module(__a  )
					for attr in dir(__a  ):
										UpperCamelCase__  :Dict				   =					getattr(__a					,   __a  )
										# (TF/Flax)ModelTesterMixin is also an attribute in specific model test module. Let's exclude them by checking
										# `all_model_classes` is not empty (which also excludes other special classes).
										UpperCamelCase__  :Optional[int]				   =					getattr(__a					,   '''all_model_classes'''					,   []  )
										if len(__a  ) > 0:
															test_classes.append(__a  )

    # sort with class names
					return sorted(__a					,   key=lambda __a  : x.__name__  )


def      a (     __a  )    ->      Union[str, Any]:



					'''simple docstring'''






					UpperCamelCase__  :int				   =					get_test_classes(__a  )
					UpperCamelCase__  :Any				   =					set()
					for test_class in test_classes:
										model_classes.update(test_class.all_model_classes  )

					# sort with class names
					return sorted(__a					,   key=lambda __a  : x.__name__  )


def      a (     __a  )    ->      Dict:



					'''simple docstring'''






					UpperCamelCase__  :Optional[Any]				   =					test_class()
					if hasattr(__a					,   '''setUp'''  ):
										test.setUp()

					UpperCamelCase__  :Union[str, Any]				   =					None
					if hasattr(__a					,   '''model_tester'''  ):
										# `(TF/Flax)ModelTesterMixin` has this attribute default to `None`. Let's skip this case.
										if test.model_tester is not None:
															UpperCamelCase__  :List[str]				   =					test.model_tester.__class__

					return model_tester


def      a (     __a					,   __a  )    ->      Any:



					'''simple docstring'''






					UpperCamelCase__  :str				   =					get_test_classes(__a  )

					UpperCamelCase__  :List[str]				   =					[]
					for test_class in test_classes:
										if model_class in test_class.all_model_classes:
															target_test_classes.append(__a  )

    # sort with class names
					return sorted(__a					,   key=lambda __a  : x.__name__  )


def      a (     __a					,   __a  )    ->      Union[str, Any]:



					'''simple docstring'''






					UpperCamelCase__  :Optional[int]				   =					get_test_classes_for_model(__a					,   __a  )

					UpperCamelCase__  :List[str]				   =					[]
					for test_class in test_classes:
										UpperCamelCase__  :int				   =					get_model_tester_from_test_class(__a  )
										if tester_class is not None:
															tester_classes.append(__a  )

    # sort with class names
					return sorted(__a					,   key=lambda __a  : x.__name__  )


def      a (     __a  )    ->      int:



					'''simple docstring'''






					UpperCamelCase__  :Any				   =					get_test_classes(__a  )
					UpperCamelCase__  :Dict				   =					{test_class: get_model_tester_from_test_class(__a  ) for test_class in test_classes}
					return test_tester_mapping


def      a (     __a  )    ->      List[str]:



					'''simple docstring'''






					UpperCamelCase__  :Any				   =					get_model_classes(__a  )
					UpperCamelCase__  :Tuple				   =					{
					    model_class: get_test_classes_for_model(__a					,   __a  ) for model_class in model_classes
					}
					return model_test_mapping


def      a (     __a  )    ->      Tuple:



					'''simple docstring'''






					UpperCamelCase__  :List[str]				   =					get_model_classes(__a  )
					UpperCamelCase__  :Union[str, Any]				   =					{
					    model_class: get_tester_classes_for_model(__a					,   __a  ) for model_class in model_classes
					}
					return model_to_tester_mapping







def      a (     __a  )    ->      List[Any]:



					'''simple docstring'''






					if isinstance(__a					,   __a  ):
										return o
					elif isinstance(__a					,   __a  ):
										return o.__name__
					elif isinstance(__a					,   (list, tuple)  ):
										return [to_json(__a  ) for x in o]
					elif isinstance(__a					,   __a  ):
										return {to_json(__a  ): to_json(__a  ) for k, v in o.items()}
					else:
										return o