"""simple docstring"""


import argparse

import torch
from torch import nn

from transformers import MBartConfig, MBartForConditionalGeneration







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







def 					UpperCAmelCase    (		UpperCAmelCase					)				->      Dict:
     snake_case_       ,	snake_case_					       =					emb.weight.shape
     snake_case_					       =					nn.Linear(UpperCAmelCase						,					UpperCAmelCase						,					bias=UpperCAmelCase					)
     snake_case_					       =					emb.weight.data
     return lin_layer







def 					UpperCAmelCase    (		UpperCAmelCase						,					UpperCAmelCase="facebook/mbart-large-en-ro"						,					UpperCAmelCase=False						,					UpperCAmelCase=False					)				->      Optional[int]:
     snake_case_					       =					torch.load(UpperCAmelCase						,					map_location='cpu'					)['model']
     remove_ignore_keys_(UpperCAmelCase					)
     snake_case_					       =					state_dict['encoder.embed_tokens.weight'].shape[0]

     snake_case_					       =					MBartConfig.from_pretrained(UpperCAmelCase						,					vocab_size=UpperCAmelCase					)
     if mbart_aa and finetuned:
          snake_case_					       =					'relu'

     snake_case_					       =					state_dict['decoder.embed_tokens.weight']
     snake_case_					       =					MBartForConditionalGeneration(UpperCAmelCase					)
     model.model.load_state_dict(UpperCAmelCase					)

     if finetuned:
          snake_case_					       =					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)









"""simple docstring"""






import copy
import tempfile
import unittest

from huggingface_hub import HfFolder, delete_repo
from parameterized import parameterized
from requests.exceptions import HTTPError

from transformers import AutoConfig, GenerationConfig
from transformers.testing_utils import TOKEN, USER, is_staging_test




class 							lowerCAmelCase__				(			unittest.TestCase ):






      '''simple docstring'''

      @parameterized.expand([(None,), ('''foo.json''',)])
      def _SCREAMING_SNAKE_CASE (						self     :  Dict						,	lowercase_     :  Union[str, Any]):




          '''simple docstring'''


          SCREAMING_SNAKE_CASE_      :  List[str]    						=		GenerationConfig(
              do_sample=lowercase_						,	temperature=0.7						,	length_penalty=1.0						,	bad_words_ids=[[1, 2, 3], [4, 5]]						,	)
          with tempfile.TemporaryDirectory() as tmp_dir:
              config.save_pretrained(lowercase_						,	config_name=lowercase_)
              SCREAMING_SNAKE_CASE_      :  Tuple    						=		GenerationConfig.from_pretrained(lowercase_						,	config_name=lowercase_)

          # Checks parameters that were specified
          self.assertEqual(loaded_config.do_sample						,	lowercase_)
          self.assertEqual(loaded_config.temperature						,	0.7)
          self.assertEqual(loaded_config.length_penalty						,	1.0)
          self.assertEqual(loaded_config.bad_words_ids						,	[[1, 2, 3], [4, 5]])

          # Checks parameters that were not specified (defaults)
          self.assertEqual(loaded_config.top_k						,	50)
          self.assertEqual(loaded_config.max_length						,	20)
          self.assertEqual(loaded_config.max_time						,	lowercase_)
      def _SCREAMING_SNAKE_CASE (						self     :  Optional[Any]):




          '''simple docstring'''


          SCREAMING_SNAKE_CASE_      :  Optional[Any]    						=		AutoConfig.from_pretrained('''gpt2''')
          SCREAMING_SNAKE_CASE_      :  int    						=		GenerationConfig.from_model_config(lowercase_)
          SCREAMING_SNAKE_CASE_      :  int    						=		GenerationConfig()

          # The generation config has loaded a few non-default parameters from the model config
          self.assertNotEqual(lowercase_						,	lowercase_)

          # One of those parameters is eos_token_id -- check if it matches
          self.assertNotEqual(generation_config_from_model.eos_token_id						,	default_generation_config.eos_token_id)
          self.assertEqual(generation_config_from_model.eos_token_id						,	model_config.eos_token_id)
      def _SCREAMING_SNAKE_CASE (						self     :  Dict):




          '''simple docstring'''


          SCREAMING_SNAKE_CASE_      :  str    						=		GenerationConfig()
          SCREAMING_SNAKE_CASE_      :  Any    						=		{
              '''max_new_tokens''': 1024,
              '''foo''': '''bar''',
          }
          SCREAMING_SNAKE_CASE_      :  str    						=		copy.deepcopy(lowercase_)
          SCREAMING_SNAKE_CASE_      :  Tuple    						=		generation_config.update(**lowercase_)

          # update_kwargs was not modified (no side effects)
          self.assertEqual(lowercase_						,	lowercase_)

          # update_kwargs was used to update the config on valid attributes
          self.assertEqual(generation_config.max_new_tokens						,	1024)

          # `.update()` returns a dictionary of unused kwargs
          self.assertEqual(lowercase_						,	{'''foo''': '''bar'''})
      def _SCREAMING_SNAKE_CASE (						self     :  Any):




          '''simple docstring'''


          SCREAMING_SNAKE_CASE_      :  Optional[Any]    						=		GenerationConfig()
          SCREAMING_SNAKE_CASE_      :  List[str]    						=		'''bar'''

          with tempfile.TemporaryDirectory('''test-generation-config''') as tmp_dir:
              generation_config.save_pretrained(lowercase_)

              SCREAMING_SNAKE_CASE_      :  List[Any]    						=		GenerationConfig.from_pretrained(lowercase_)
          # update_kwargs was used to update the config on valid attributes
          self.assertEqual(new_config.foo						,	'''bar''')

          SCREAMING_SNAKE_CASE_      :  Optional[Any]    						=		GenerationConfig.from_model_config(lowercase_)
          assert not hasattr(lowercase_						,	'''foo''')  # no new kwargs should be initialized if from config



      def _SCREAMING_SNAKE_CASE (						self     :  Tuple):




          '''simple docstring'''


          SCREAMING_SNAKE_CASE_      :  Tuple    						=		GenerationConfig()
          self.assertEqual(default_config.temperature						,	1.0)
          self.assertEqual(default_config.do_sample						,	lowercase_)
          self.assertEqual(default_config.num_beams						,	1)

          SCREAMING_SNAKE_CASE_      :  Dict    						=		GenerationConfig(
              do_sample=lowercase_						,	temperature=0.7						,	length_penalty=1.0						,	bad_words_ids=[[1, 2, 3], [4, 5]]						,	)
          self.assertEqual(config.temperature						,	0.7)
          self.assertEqual(config.do_sample						,	lowercase_)
          self.assertEqual(config.num_beams						,	1)

          with tempfile.TemporaryDirectory() as tmp_dir:
              config.save_pretrained(lowercase_)
              SCREAMING_SNAKE_CASE_      :  Tuple    						=		GenerationConfig.from_pretrained(lowercase_						,	temperature=1.0)

          self.assertEqual(loaded_config.temperature						,	1.0)
          self.assertEqual(loaded_config.do_sample						,	lowercase_)
          self.assertEqual(loaded_config.num_beams						,	1)  # default value




@is_staging_test
class 							lowerCAmelCase__				(			unittest.TestCase ):






      '''simple docstring'''

      @classmethod
      def _SCREAMING_SNAKE_CASE (						cls     :  Any):




          '''simple docstring'''


          SCREAMING_SNAKE_CASE_      :  str    						=		TOKEN
          HfFolder.save_token(lowercase_)
      @classmethod
      def _SCREAMING_SNAKE_CASE (						cls     :  List[str]):




          '''simple docstring'''


          try:
              delete_repo(token=cls._token						,	repo_id='''test-generation-config''')
          except HTTPError:
              pass

          try:
              delete_repo(token=cls._token						,	repo_id='''valid_org/test-generation-config-org''')
          except HTTPError:
              pass
      def _SCREAMING_SNAKE_CASE (						self     :  Dict):




          '''simple docstring'''


          SCREAMING_SNAKE_CASE_      :  Tuple    						=		GenerationConfig(
              do_sample=lowercase_						,	temperature=0.7						,	length_penalty=1.0						,	)
          config.push_to_hub('''test-generation-config'''						,	use_auth_token=self._token)

          SCREAMING_SNAKE_CASE_      :  int    						=		GenerationConfig.from_pretrained(F'{USER}/test-generation-config')
          for k, v in config.to_dict().items():
              if k != "transformers_version":
                  self.assertEqual(lowercase_						,	getattr(lowercase_						,	lowercase_))

        # Reset repo
          delete_repo(token=self._token						,	repo_id='''test-generation-config''')

          # Push to hub via save_pretrained
          with tempfile.TemporaryDirectory() as tmp_dir:
              config.save_pretrained(
                  lowercase_						,	repo_id='''test-generation-config'''						,	push_to_hub=lowercase_						,	use_auth_token=self._token)

          SCREAMING_SNAKE_CASE_      :  Optional[int]    						=		GenerationConfig.from_pretrained(F'{USER}/test-generation-config')
          for k, v in config.to_dict().items():
              if k != "transformers_version":
                  self.assertEqual(lowercase_						,	getattr(lowercase_						,	lowercase_))



      def _SCREAMING_SNAKE_CASE (						self     :  Union[str, Any]):




          '''simple docstring'''


          SCREAMING_SNAKE_CASE_      :  Dict    						=		GenerationConfig(
              do_sample=lowercase_						,	temperature=0.7						,	length_penalty=1.0						,	)
          config.push_to_hub('''valid_org/test-generation-config-org'''						,	use_auth_token=self._token)

          SCREAMING_SNAKE_CASE_      :  Any    						=		GenerationConfig.from_pretrained('''valid_org/test-generation-config-org''')
          for k, v in config.to_dict().items():
              if k != "transformers_version":
                  self.assertEqual(lowercase_						,	getattr(lowercase_						,	lowercase_))

        # Reset repo
          delete_repo(token=self._token						,	repo_id='''valid_org/test-generation-config-org''')

          # Push to hub via save_pretrained
          with tempfile.TemporaryDirectory() as tmp_dir:
              config.save_pretrained(
                  lowercase_						,	repo_id='''valid_org/test-generation-config-org'''						,	push_to_hub=lowercase_						,	use_auth_token=self._token)

          SCREAMING_SNAKE_CASE_      :  Any    						=		GenerationConfig.from_pretrained('''valid_org/test-generation-config-org''')
          for k, v in config.to_dict().items():
              if k != "transformers_version":
                  self.assertEqual(lowercase_						,	getattr(lowercase_						,	lowercase_))


