


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 				A       (			unittest.TestCase				):
					'''simple docstring'''






					@parameterized.expand([(None,), ("""foo.json""",)]						)
					def     lowerCamelCase__	(self       :		Optional[Any] ,   _UpperCAmelCase       :		Optional[Any]						)		->  Optional[Any]:




							"""simple docstring"""


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

							# Checks parameters that were specified
							self.assertEqual(loaded_config.do_sample ,   _UpperCAmelCase						)
							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 ,   _UpperCAmelCase						)

					def     lowerCamelCase__	(self       :		Any						)		->  List[Any]:




							"""simple docstring"""


							lowercase__	     =						AutoConfig.from_pretrained("""gpt2"""						)
							lowercase__	     =						GenerationConfig.from_model_config(_UpperCAmelCase						)
							lowercase__	     =						GenerationConfig()

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

							# 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     lowerCamelCase__	(self       :		List[Any]						)		->  str:




							"""simple docstring"""


							lowercase__	     =						GenerationConfig()
							lowercase__	     =						{
							    """max_new_tokens""": 1024,
							    """foo""": """bar""",
							}
							lowercase__	     =						copy.deepcopy(_UpperCAmelCase						)
							lowercase__	     =						generation_config.update(**_UpperCAmelCase						)

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

							# 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(_UpperCAmelCase ,   {"""foo""": """bar"""}						)

					def     lowerCamelCase__	(self       :		str						)		->  Optional[int]:




							"""simple docstring"""


							lowercase__	     =						GenerationConfig()
							lowercase__	     =						"""bar"""

							with tempfile.TemporaryDirectory("""test-generation-config"""						) as tmp_dir:
									generation_config.save_pretrained(_UpperCAmelCase						)

									lowercase__	     =						GenerationConfig.from_pretrained(_UpperCAmelCase						)
							# update_kwargs was used to update the config on valid attributes
							self.assertEqual(new_config.foo ,   """bar"""						)

							lowercase__	     =						GenerationConfig.from_model_config(_UpperCAmelCase						)
							assert not hasattr(_UpperCAmelCase ,   """foo"""						)  # no new kwargs should be initialized if from config


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




							"""simple docstring"""


							lowercase__	     =						GenerationConfig()
							self.assertEqual(default_config.temperature ,   1.0						)
							self.assertEqual(default_config.do_sample ,   _UpperCAmelCase						)
							self.assertEqual(default_config.num_beams ,   1						)

							lowercase__	     =						GenerationConfig(
							    do_sample=_UpperCAmelCase ,   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 ,   _UpperCAmelCase						)
							self.assertEqual(config.num_beams ,   1						)

							with tempfile.TemporaryDirectory() as tmp_dir:
									config.save_pretrained(_UpperCAmelCase						)
									lowercase__	     =						GenerationConfig.from_pretrained(_UpperCAmelCase ,   temperature=1.0						)

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






@is_staging_test
class 				A       (			unittest.TestCase				):
					'''simple docstring'''






					@classmethod
					def     lowerCamelCase__	(cls       :		int						)		->  Optional[Any]:




							"""simple docstring"""


							lowercase__	     =						TOKEN
							HfFolder.save_token(_UpperCAmelCase						)

					@classmethod
					def     lowerCamelCase__	(cls       :		Tuple						)		->  List[Any]:




							"""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     lowerCamelCase__	(self       :		Dict						)		->  str:




							"""simple docstring"""


							lowercase__	     =						GenerationConfig(
							    do_sample=_UpperCAmelCase ,   temperature=0.7 ,   length_penalty=1.0 ,   )
							config.push_to_hub("""test-generation-config""" ,   use_auth_token=self._token						)

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

        # 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(
									    _UpperCAmelCase ,   repo_id="""test-generation-config""" ,   push_to_hub=_UpperCAmelCase ,   use_auth_token=self._token						)

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


					def     lowerCamelCase__	(self       :		int						)		->  Any:




							"""simple docstring"""


							lowercase__	     =						GenerationConfig(
							    do_sample=_UpperCAmelCase ,   temperature=0.7 ,   length_penalty=1.0 ,   )
							config.push_to_hub("""valid_org/test-generation-config-org""" ,   use_auth_token=self._token						)

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

        # 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(
									    _UpperCAmelCase ,   repo_id="""valid_org/test-generation-config-org""" ,   push_to_hub=_UpperCAmelCase ,   use_auth_token=self._token						)

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





import argparse

import torch
from torch import nn

from transformers import MBartConfig, MBartForConditionalGeneration






def 					UpperCamelCase   (      __magic_name__	:				Optional[Any]	)  ->    Tuple:
		"""simple docstring"""




		lowercase__	     =						[
		    """encoder.version""",
		    """decoder.version""",
		    """model.encoder.version""",
		    """model.decoder.version""",
		    """_float_tensor""",
		    """decoder.output_projection.weight""",
		]
		for k in ignore_keys:
				state_dict.pop(__magic_name__       ,       __magic_name__	)






def 					UpperCamelCase   (      __magic_name__	:				int	)  ->    Union[str, Any]:
		"""simple docstring"""




		lowercase__     ,      lowercase__	     =						emb.weight.shape
		lowercase__	     =						nn.Linear(__magic_name__       ,       __magic_name__       ,       bias=__magic_name__	)
		lowercase__	     =						emb.weight.data
		return lin_layer






def 					UpperCamelCase   (      __magic_name__	:				str       ,       __magic_name__	:				str="facebook/mbart-large-en-ro"       ,       __magic_name__	:				Any=False       ,       __magic_name__	:				int=False	)  ->    Optional[int]:
		"""simple docstring"""




		lowercase__	     =						torch.load(__magic_name__       ,       map_location="""cpu"""	)["""model"""]
		remove_ignore_keys_(__magic_name__	)
		lowercase__	     =						state_dict["""encoder.embed_tokens.weight"""].shape[0]

		lowercase__	     =						MBartConfig.from_pretrained(__magic_name__       ,       vocab_size=__magic_name__	)
		if mbart_aa and finetuned:
				lowercase__	     =						"""relu"""

		lowercase__	     =						state_dict["""decoder.embed_tokens.weight"""]
		lowercase__	     =						MBartForConditionalGeneration(__magic_name__	)
		model.model.load_state_dict(__magic_name__	)

		if finetuned:
				lowercase__	     =						make_linear_from_emb(model.model.shared	)

		return model


if __name__ == "__main__":
	A			:						Optional[Any]        =  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')
	A			:						Any        =  parser.parse_args()
	A			:						str        =  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)

