





import argparse
import os
import re

import packaging.version


UpperCAmelCase_ 							=       """examples/"""
UpperCAmelCase_ 							=       {
    """examples""": (re.compile(R"""^check_min_version\(\"[^\"]+\"\)\s*$""", re.MULTILINE), """check_min_version(\"VERSION\")\n"""),
    """init""": (re.compile(R"""^__version__\s+=\s+\"([^\"]+)\"\s*$""", re.MULTILINE), """__version__ = \"VERSION\"\n"""),
    """setup""": (re.compile(R"""^(\s*)version\s*=\s*\"[^\"]+\",""", re.MULTILINE), R"""\1version=\"VERSION\","""),
    """doc""": (re.compile(R"""^(\s*)release\s*=\s*\"[^\"]+\"$""", re.MULTILINE), """release = \"VERSION\"\n"""),
}
UpperCAmelCase_ 							=       {
    """init""": """src/transformers/__init__.py""",
    """setup""": """setup.py""",
}
UpperCAmelCase_ 							=       """README.md"""





def   lowerCamelCase__       (       UpperCamelCase__     :    Optional[int]    ,      UpperCamelCase__     :    Dict    ,      UpperCamelCase__     :    Union[str, Any]  )     ->	Union[str, Any]:



					'''simple docstring'''




					with open(UpperCamelCase__    ,      'r'    ,      encoding='utf-8'    ,      newline='\n'  ) as f:
										_snake_case													=			f.read()
					_snake_case							,       _snake_case													=			REPLACE_PATTERNS[pattern]
					_snake_case													=			replace.replace('VERSION'    ,      UpperCamelCase__  )
					_snake_case													=			re_pattern.sub(UpperCamelCase__    ,      UpperCamelCase__  )
					with open(UpperCamelCase__    ,      'w'    ,      encoding='utf-8'    ,      newline='\n'  ) as f:
										f.write(UpperCamelCase__  )





def   lowerCamelCase__       (       UpperCamelCase__     :    Any  )     ->	Optional[Any]:



					'''simple docstring'''




					for folder, directories, fnames in os.walk(UpperCamelCase__  ):
										# Removing some of the folders with non-actively maintained examples from the walk
										if "research_projects" in directories:
															directories.remove('research_projects'  )
										if "legacy" in directories:
															directories.remove('legacy'  )
										for fname in fnames:
															if fname.endswith('.py'  ):
																				update_version_in_file(os.path.join(UpperCamelCase__    ,      UpperCamelCase__  )    ,      UpperCamelCase__    ,      pattern='examples'  )





def   lowerCamelCase__       (       UpperCamelCase__     :    int    ,      UpperCamelCase__     :    Dict=False  )     ->	List[str]:



					'''simple docstring'''




					for pattern, fname in REPLACE_FILES.items():
										update_version_in_file(UpperCamelCase__    ,      UpperCamelCase__    ,      UpperCamelCase__  )
					if not patch:
										update_version_in_examples(UpperCamelCase__  )





def   lowerCamelCase__       (       )     ->	Tuple:



					'''simple docstring'''




					_snake_case													=			'🤗 Transformers currently provides the following architectures'
					_snake_case													=			'1. Want to contribute a new model?'
					with open(UpperCamelCase__    ,      'r'    ,      encoding='utf-8'    ,      newline='\n'  ) as f:
										_snake_case													=			f.readlines()

					# Find the start of the list.
					_snake_case													=			0
					while not lines[start_index].startswith(_start_prompt  ):
										start_index += 1
					start_index += 1

					_snake_case													=			start_index
					# Update the lines in the model list.
					while not lines[index].startswith(_end_prompt  ):
										if lines[index].startswith('1.'  ):
															_snake_case													=			lines[index].replace(
															    'https://huggingface.co/docs/transformers/main/model_doc'    ,      'https://huggingface.co/docs/transformers/model_doc'    ,      )
										index += 1

					with open(UpperCamelCase__    ,      'w'    ,      encoding='utf-8'    ,      newline='\n'  ) as f:
										f.writelines(UpperCamelCase__  )





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



					'''simple docstring'''




					with open(REPLACE_FILES['init']    ,      'r'  ) as f:
										_snake_case													=			f.read()
					_snake_case													=			REPLACE_PATTERNS['init'][0].search(UpperCamelCase__  ).groups()[0]
					return packaging.version.parse(UpperCamelCase__  )





def   lowerCamelCase__       (       UpperCamelCase__     :    List[str]=False  )     ->	int:



					'''simple docstring'''




					_snake_case													=			get_version()
					if patch and default_version.is_devrelease:
										raise ValueError('Can\'t create a patch version from the dev branch, checkout a released version!'  )
					if default_version.is_devrelease:
										_snake_case													=			default_version.base_version
					elif patch:
										_snake_case													=			F'''{default_version.major}.{default_version.minor}.{default_version.micro + 1}'''
					else:
										_snake_case													=			F'''{default_version.major}.{default_version.minor + 1}.0'''

					# Now let's ask nicely if that's the right one.
					_snake_case													=			input(F'''Which version are you releasing? [{default_version}]'''  )
					if len(UpperCamelCase__  ) == 0:
										_snake_case													=			default_version

					print(F'''Updating version to {version}.'''  )
					global_version_update(UpperCamelCase__    ,      patch=UpperCamelCase__  )
					if not patch:
										print('Cleaning main README, don\'t forget to run `make fix-copies`.'  )
										clean_main_ref_in_model_list()





def   lowerCamelCase__       (       )     ->	Any:



					'''simple docstring'''




					_snake_case													=			get_version()
					_snake_case													=			F'''{current_version.major}.{current_version.minor + 1}.0.dev0'''
					_snake_case													=			current_version.base_version

					# Check with the user we got that right.
					_snake_case													=			input(F'''Which version are we developing now? [{dev_version}]'''  )
					if len(UpperCamelCase__  ) == 0:
										_snake_case													=			dev_version

					print(F'''Updating version to {version}.'''  )
					global_version_update(UpperCamelCase__  )
					print('Cleaning main README, don\'t forget to run `make fix-copies`.'  )
					clean_main_ref_in_model_list()


if __name__ == "__main__":
					UpperCAmelCase_ 							=       argparse.ArgumentParser()
					parser.add_argument("""--post_release""", action="""store_true""", help="""Whether this is pre or post release.""")
					parser.add_argument("""--patch""", action="""store_true""", help="""Whether or not this is a patch release.""")
					UpperCAmelCase_ 							=       parser.parse_args()
					if not args.post_release:
										pre_release_work(patch=args.patch)
					elif args.patch:
										print("""Nothing to do after a patch :-)""")
					else:
										post_release_work()










import argparse

from torch import nn

# transformers_old should correspond to branch `save_old_prophetnet_model_structure` here
# original prophetnet_checkpoints are saved under `patrickvonplaten/..._old` respectively
from transformers_old.modeling_prophetnet import (
    ProphetNetForConditionalGeneration as ProphetNetForConditionalGenerationOld,
)
from transformers_old.modeling_xlm_prophetnet import (
    XLMProphetNetForConditionalGeneration as XLMProphetNetForConditionalGenerationOld,
)

from transformers import ProphetNetForConditionalGeneration, XLMProphetNetForConditionalGeneration, logging


UpperCAmelCase_ 							=       logging.get_logger(__name__)
logging.set_verbosity_info()





def   lowerCamelCase__       (       UpperCamelCase__     :    str    ,      UpperCamelCase__     :    str  )     ->	Union[str, Any]:



					'''simple docstring'''




					if "xprophetnet" in prophetnet_checkpoint_path:
										_snake_case													=			XLMProphetNetForConditionalGenerationOld.from_pretrained(UpperCamelCase__  )
										_snake_case							,       _snake_case													=			XLMProphetNetForConditionalGeneration.from_pretrained(
										    UpperCamelCase__    ,      output_loading_info=UpperCamelCase__  )
					else:
										_snake_case													=			ProphetNetForConditionalGenerationOld.from_pretrained(UpperCamelCase__  )
										_snake_case							,       _snake_case													=			ProphetNetForConditionalGeneration.from_pretrained(
										    UpperCamelCase__    ,      output_loading_info=UpperCamelCase__  )

					_snake_case													=			['key_proj', 'value_proj', 'query_proj']

					_snake_case													=			{
					    'self_attn': 'ngram_self_attn',
					    'cross_attn': 'encoder_attn',
					    'cross_attn_layer_norm': 'encoder_attn_layer_norm',
					    'feed_forward_layer_norm': 'final_layer_norm',
					    'feed_forward': '',
					    'intermediate': 'fc1',
					    'output': 'fc2',
					    'key_proj': 'k_proj',
					    'query_proj': 'q_proj',
					    'value_proj': 'v_proj',
					    'word_embeddings': 'embed_tokens',
					    'embeddings_layer_norm': 'emb_layer_norm',
					    'relative_pos_embeddings': 'relative_linear',
					    'ngram_embeddings': 'ngram_input_embed',
					    'position_embeddings': 'embed_positions',
					}

					for key in loading_info["missing_keys"]:
										_snake_case													=			key.split('.'  )

										if attributes[0] == "lm_head":
															_snake_case													=			prophet
															_snake_case													=			prophet_old
										else:
															_snake_case													=			prophet.prophetnet
															_snake_case													=			prophet_old.model

										_snake_case													=			False
										for attribute in attributes:
															if attribute in mapping:
																				_snake_case													=			mapping[attribute]
																				if not hasattr(UpperCamelCase__    ,      UpperCamelCase__  ) and len(UpperCamelCase__  ) > 0:
																									_snake_case													=			attribute
															elif hasattr(UpperCamelCase__    ,      UpperCamelCase__  ):
																				_snake_case													=			attribute

															if attribute == "weight":
																				assert old_model.weight.shape == model.weight.shape, "Shapes have to match!"
																				_snake_case													=			old_model.weight
																				logger.info(F'''{attribute} is initialized.'''  )
																				_snake_case													=			True
																				break
															elif attribute == "bias":
																				assert old_model.bias.shape == model.bias.shape, "Shapes have to match!"
																				_snake_case													=			old_model.bias
																				logger.info(F'''{attribute} is initialized'''  )
																				_snake_case													=			True
																				break
															elif attribute in special_keys and hasattr(UpperCamelCase__    ,      'in_proj_weight'  ):
																				_snake_case													=			old_model.in_proj_weight.shape[0] // 3
																				_snake_case													=			getattr(UpperCamelCase__    ,      UpperCamelCase__  )
																				param.weight.shape == old_model.in_proj_weight[:embed_dim, :].shape, "Shapes have to match"
																				param.bias.shape == old_model.in_proj_bias[:embed_dim].shape, "Shapes have to match"
																				if attribute == "query_proj":
																									_snake_case													=			nn.Parameter(old_model.in_proj_weight[:embed_dim, :]  )
																									_snake_case													=			nn.Parameter(old_model.in_proj_bias[:embed_dim]  )

																				elif attribute == "key_proj":
																									_snake_case													=			nn.Parameter(old_model.in_proj_weight[embed_dim : 2 * embed_dim, :]  )
																									_snake_case													=			nn.Parameter(old_model.in_proj_bias[embed_dim : 2 * embed_dim]  )
																				elif attribute == "value_proj":
																									_snake_case													=			nn.Parameter(old_model.in_proj_weight[2 * embed_dim :, :]  )
																									_snake_case													=			nn.Parameter(old_model.in_proj_bias[2 * embed_dim :]  )
																				_snake_case													=			True
																				break
															elif attribute == "position_embeddings":
																				assert (
																				    model.position_embeddings.weight.shape[-1] == old_model.embed_positions.weight.shape[-1]
																				), "Hidden size has to match"
																				assert model.position_embeddings.weight.shape[0] == 512, "We want 512 position_embeddings."
																				_snake_case													=			nn.Parameter(old_model.embed_positions.weight[:512, :]  )
																				_snake_case													=			True
																				break

															if attribute.isdigit():
																				_snake_case													=			model[int(UpperCamelCase__  )]
																				_snake_case													=			old_model[int(UpperCamelCase__  )]
															else:
																				_snake_case													=			getattr(UpperCamelCase__    ,      UpperCamelCase__  )

																				if old_attribute == "":
																									_snake_case													=			old_model
																				else:
																									if not hasattr(UpperCamelCase__    ,      UpperCamelCase__  ):
																														raise ValueError(F'''{old_model} does not have {old_attribute}'''  )
																									_snake_case													=			getattr(UpperCamelCase__    ,      UpperCamelCase__  )

										if not is_key_init:
															raise ValueError(F'''{key} was not correctly initialized!'''  )

					print(F'''Saving model to {pytorch_dump_folder_path}'''  )
					prophet.save_pretrained(UpperCamelCase__  )


if __name__ == "__main__":
					UpperCAmelCase_ 							=       argparse.ArgumentParser()
					# Required parameters
					parser.add_argument(
					    """--prophetnet_checkpoint_path""", default=None, type=str, required=True, help="""Path the official PyTorch dump."""
					)
					parser.add_argument(
					    """--pytorch_dump_folder_path""", default=None, type=str, required=True, help="""Path to the output PyTorch model."""
					)
					UpperCAmelCase_ 							=       parser.parse_args()
					convert_prophetnet_checkpoint_to_pytorch(args.prophetnet_checkpoint_path, args.pytorch_dump_folder_path)



