


"""simple docstring"""



import copy
import json
import os
import tempfile

from transformers import is_torch_available

from .test_configuration_utils import config_common_kwargs
class 					__magic_name__		(			__UpperCAmelCase     ):






       def __init__(   self  :    str  ,     snake_case__  :    Any  ,     snake_case__  :    str=None  ,     snake_case__  :    Optional[Any]=True  ,     snake_case__  :    List[str]=None  ,     **snake_case__  :    Union[str, Any]				):

              '''simple docstring'''






              lowercase		:List[Any]       							=				parent
              lowercase		:str       							=				config_class
              lowercase		:int       							=				has_text_modality
              lowercase		:Dict       							=				kwargs
              lowercase		:str       							=				common_properties






       def  __snake_case						(   self  :    int				):

              '''simple docstring'''






              lowercase		:int       							=				self.config_class(**self.inputs_dict				)
              lowercase		:Optional[Any]       							=				(
                  ['''hidden_size''', '''num_attention_heads''', '''num_hidden_layers''']
                  if self.common_properties is None
                  else self.common_properties
              )

              # Add common fields for text models
              if self.has_text_modality:
                     common_properties.extend(['''vocab_size''']				)

              # Test that config has the common properties as getters
              for prop in common_properties:
                     self.parent.assertTrue(hasattr(snake_case__  ,     snake_case__				)  ,     msg=f"""`{prop}` does not exist"""				)

              # Test that config has the common properties as setter
              for idx, name in enumerate(snake_case__				):
                     try:
                            setattr(snake_case__  ,     snake_case__  ,     snake_case__				)
                            self.parent.assertEqual(
                                getattr(snake_case__  ,     snake_case__				)  ,     snake_case__  ,     msg=f"""`{name} value {idx} expected, but was {getattr(snake_case__  ,     snake_case__				)}"""				)
                     except NotImplementedError:
                            # Some models might not be able to implement setters for common_properties
                            # In that case, a NotImplementedError is raised
                            pass

        # Test if config class can be called with Config(prop_name=..)
              for idx, name in enumerate(snake_case__				):
                     try:
                            lowercase		:int       							=				self.config_class(**{name: idx}				)
                            self.parent.assertEqual(
                                getattr(snake_case__  ,     snake_case__				)  ,     snake_case__  ,     msg=f"""`{name} value {idx} expected, but was {getattr(snake_case__  ,     snake_case__				)}"""				)
                     except NotImplementedError:
                            # Some models might not be able to implement setters for common_properties
                            # In that case, a NotImplementedError is raised
                            pass






       def  __snake_case						(   self  :    str				):

              '''simple docstring'''






              lowercase		:Tuple       							=				self.config_class(**self.inputs_dict				)
              lowercase		:Union[str, Any]       							=				json.loads(config.to_json_string()				)
              for key, value in self.inputs_dict.items():
                     self.parent.assertEqual(obj[key]  ,     snake_case__				)






       def  __snake_case						(   self  :    Any				):

              '''simple docstring'''






              lowercase		:int       							=				self.config_class(**self.inputs_dict				)

              with tempfile.TemporaryDirectory() as tmpdirname:
                     lowercase		:List[Any]       							=				os.path.join(snake_case__  ,     '''config.json'''				)
                     config_first.to_json_file(snake_case__				)
                     lowercase		:Optional[int]       							=				self.config_class.from_json_file(snake_case__				)

              self.parent.assertEqual(config_second.to_dict()  ,     config_first.to_dict()				)






       def  __snake_case						(   self  :    Dict				):

              '''simple docstring'''






              lowercase		:Any       							=				self.config_class(**self.inputs_dict				)

              with tempfile.TemporaryDirectory() as tmpdirname:
                     config_first.save_pretrained(snake_case__				)
                     lowercase		:Any       							=				self.config_class.from_pretrained(snake_case__				)

              self.parent.assertEqual(config_second.to_dict()  ,     config_first.to_dict()				)






       def  __snake_case						(   self  :    str				):

              '''simple docstring'''






              lowercase		:Any       							=				self.config_class(**self.inputs_dict				)

              lowercase		:Dict       							=				'''test'''
              with tempfile.TemporaryDirectory() as tmpdirname:
                     lowercase		:Dict       							=				os.path.join(snake_case__  ,     snake_case__				)
                     config_first.save_pretrained(snake_case__				)
                     lowercase		:Optional[int]       							=				self.config_class.from_pretrained(snake_case__  ,     subfolder=snake_case__				)

              self.parent.assertEqual(config_second.to_dict()  ,     config_first.to_dict()				)






       def  __snake_case						(   self  :    Tuple				):

              '''simple docstring'''






              lowercase		:Dict       							=				self.config_class(**self.inputs_dict  ,     num_labels=5				)
              self.parent.assertEqual(len(config.idalabel				)  ,     5				)
              self.parent.assertEqual(len(config.labelaid				)  ,     5				)

              lowercase		:int       							=				3
              self.parent.assertEqual(len(config.idalabel				)  ,     3				)
              self.parent.assertEqual(len(config.labelaid				)  ,     3				)






       def  __snake_case						(   self  :    Any				):

              '''simple docstring'''






              if self.config_class.is_composition:
                     return
              lowercase		:List[Any]       							=				self.config_class()
              self.parent.assertIsNotNone(snake_case__				)






       def  __snake_case						(   self  :    Dict				):

              '''simple docstring'''






              lowercase		:List[str]       							=				copy.deepcopy(snake_case__				)
              lowercase		:Dict       							=				self.config_class(**snake_case__				)
              lowercase		:List[str]       							=				[]
              for key, value in config_common_kwargs.items():
                     if key == "torch_dtype":
                            if not is_torch_available():
                                   continue
                            else:
                                   import torch

                                   if config.torch_dtype != torch.floataa:
                                          wrong_values.append(('''torch_dtype''', config.torch_dtype, torch.floataa)				)
                     elif getattr(snake_case__  ,     snake_case__				) != value:
                            wrong_values.append((key, getattr(snake_case__  ,     snake_case__				), value)				)

              if len(snake_case__				) > 0:
                     lowercase		:List[str]       							=				'''\n'''.join([f"""- {v[0]}: got {v[1]} instead of {v[2]}""" for v in wrong_values]				)
                     raise ValueError(f"""The following keys were not properly set in the config:\n{errors}"""				)







       def  __snake_case						(   self  :    int				):

              '''simple docstring'''






              self.create_and_test_config_common_properties()
              self.create_and_test_config_to_json_string()
              self.create_and_test_config_to_json_file()
              self.create_and_test_config_from_and_save_pretrained()
              self.create_and_test_config_from_and_save_pretrained_subfolder()
              self.create_and_test_config_with_num_labels()
              self.check_config_can_be_init_without_params()
              self.check_config_arguments_init()





"""simple docstring"""



import argparse

import torch
from torch import nn

from transformers import MBartConfig, MBartForConditionalGeneration






def       lowerCamelCase					(a_						:Dict)     ->							Dict:
       lowercase		:Tuple       							=				[
           '''encoder.version''',
           '''decoder.version''',
           '''model.encoder.version''',
           '''model.decoder.version''',
           '''_float_tensor''',
           '''decoder.output_projection.weight''',
       ]
       for k in ignore_keys:
              state_dict.pop(a_				,				a_)






def       lowerCamelCase					(a_						:Union[str, Any])     ->							str:
       lowercase							,  lowercase		:Tuple       							=				emb.weight.shape
       lowercase		:List[str]       							=				nn.Linear(a_				,				a_				,				bias=a_)
       lowercase		:List[str]       							=				emb.weight.data
       return lin_layer






def       lowerCamelCase					(a_						:int				,				a_						:Union[str, Any]="facebook/mbart-large-en-ro"				,				a_						:Union[str, Any]=False				,				a_						:List[Any]=False)     ->							List[Any]:
       lowercase		:List[Any]       							=				torch.load(a_				,				map_location='''cpu''')['''model''']
       remove_ignore_keys_(a_)
       lowercase		:Dict       							=				state_dict['''encoder.embed_tokens.weight'''].shape[0]

       lowercase		:Tuple       							=				MBartConfig.from_pretrained(a_				,				vocab_size=a_)
       if mbart_aa and finetuned:
              lowercase		:List[Any]       							=				'''relu'''

       lowercase		:Optional[int]       							=				state_dict['''decoder.embed_tokens.weight''']
       lowercase		:Union[str, Any]       							=				MBartForConditionalGeneration(a_)
       model.model.load_state_dict(a_)

       if finetuned:
              lowercase		:Dict       							=				make_linear_from_emb(model.model.shared)

       return model


if __name__ == "__main__":
 UpperCAmelCase      		=			argparse.ArgumentParser()
 # Required parameters
 parser.add_argument(
     '''fairseq_path''', type=str, help='''bart.large, bart.large.cnn or a path to a model.pt on local filesystem.'''
 )
 parser.add_argument('''pytorch_dump_folder_path''', default=None, type=str, help='''Path to the output PyTorch model.''')
 parser.add_argument(
     '''--hf_config''',
     default='''facebook/mbart-large-cc25''',
     type=str,
     help='''Which huggingface architecture to use: mbart-large''',
 )
 parser.add_argument('''--mbart_50''', action='''store_true''', help='''whether the model is mMART-50 checkpoint''')
 parser.add_argument('''--finetuned''', action='''store_true''', help='''whether the model is a fine-tuned checkpoint''')
 UpperCAmelCase      		=			parser.parse_args()
 UpperCAmelCase      		=			convert_fairseq_mbart_checkpoint_from_disk(
     args.fairseq_path, hf_config_path=args.hf_config, finetuned=args.finetuned, mbart_aa=args.mbart_aa
 )
 model.save_pretrained(args.pytorch_dump_folder_path)

