'''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 				_lowercase     (				unittest.TestCase			):


 '''simple docstring'''






 @parameterized.expand([(None,), ("""foo.json""",)]							)
 def a					(      self   :	int      ,       SCREAMING_SNAKE_CASE__   :	Optional[Any]							)  ->    Union[str, Any]:
  __lowerCAmelCase											=						GenerationConfig(
      do_sample=SCREAMING_SNAKE_CASE__      ,       temperature=0.7      ,       length_penalty=1.0      ,       bad_words_ids=[[1, 2, 3], [4, 5]]      ,       )
  with tempfile.TemporaryDirectory() as tmp_dir:
   config.save_pretrained(SCREAMING_SNAKE_CASE__      ,       config_name=SCREAMING_SNAKE_CASE__							)
   __lowerCAmelCase											=						GenerationConfig.from_pretrained(SCREAMING_SNAKE_CASE__      ,       config_name=SCREAMING_SNAKE_CASE__							)

  # Checks parameters that were specified
  self.assertEqual(loaded_config.do_sample      ,       SCREAMING_SNAKE_CASE__							)
  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      ,       SCREAMING_SNAKE_CASE__							)
 def a					(      self   :	List[str]							)  ->    Union[str, Any]:
  __lowerCAmelCase											=						AutoConfig.from_pretrained("""gpt2"""							)
  __lowerCAmelCase											=						GenerationConfig.from_model_config(SCREAMING_SNAKE_CASE__							)
  __lowerCAmelCase											=						GenerationConfig()

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

  # 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 a					(      self   :	str							)  ->    List[str]:
  __lowerCAmelCase											=						GenerationConfig()
  __lowerCAmelCase											=						{
      """max_new_tokens""": 10_24,
      """foo""": """bar""",
  }
  __lowerCAmelCase											=						copy.deepcopy(SCREAMING_SNAKE_CASE__							)
  __lowerCAmelCase											=						generation_config.update(**SCREAMING_SNAKE_CASE__							)

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

  # update_kwargs was used to update the config on valid attributes
  self.assertEqual(generation_config.max_new_tokens      ,       10_24							)

  # `.update()` returns a dictionary of unused kwargs
  self.assertEqual(SCREAMING_SNAKE_CASE__      ,       {"""foo""": """bar"""}							)
 def a					(      self   :	str							)  ->    int:
  __lowerCAmelCase											=						GenerationConfig()
  __lowerCAmelCase											=						"""bar"""

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

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

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





 def a					(      self   :	List[Any]							)  ->    Any:
  __lowerCAmelCase											=						GenerationConfig()
  self.assertEqual(default_config.temperature      ,       1.0							)
  self.assertEqual(default_config.do_sample      ,       SCREAMING_SNAKE_CASE__							)
  self.assertEqual(default_config.num_beams      ,       1							)

  __lowerCAmelCase											=						GenerationConfig(
      do_sample=SCREAMING_SNAKE_CASE__      ,       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      ,       SCREAMING_SNAKE_CASE__							)
  self.assertEqual(config.num_beams      ,       1							)

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

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







@is_staging_test
class 				_lowercase     (				unittest.TestCase			):


 '''simple docstring'''






 @classmethod
 def a					(      cls   :	Union[str, Any]							)  ->    Tuple:
  __lowerCAmelCase											=						TOKEN
  HfFolder.save_token(SCREAMING_SNAKE_CASE__							)
 @classmethod
 def a					(      cls   :	Optional[int]							)  ->    int:
  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 a					(      self   :	Optional[int]							)  ->    Any:
  __lowerCAmelCase											=						GenerationConfig(
      do_sample=SCREAMING_SNAKE_CASE__      ,       temperature=0.7      ,       length_penalty=1.0      ,       )
  config.push_to_hub("""test-generation-config"""      ,       use_auth_token=self._token							)

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

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

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





 def a					(      self   :	List[Any]							)  ->    Union[str, Any]:
  __lowerCAmelCase											=						GenerationConfig(
      do_sample=SCREAMING_SNAKE_CASE__      ,       temperature=0.7      ,       length_penalty=1.0      ,       )
  config.push_to_hub("""valid_org/test-generation-config-org"""      ,       use_auth_token=self._token							)

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

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

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







'''simple docstring'''

import argparse

import torch

from transformers import BlenderbotConfig, BlenderbotForConditionalGeneration
from transformers.utils import logging


logging.set_verbosity_info()
_A			:      str					      =				logging.get_logger(__name__)

_A			:      str					      =				[
    ['''attention''', '''attn'''],
    ['''encoder_attention''', '''encoder_attn'''],
    ['''q_lin''', '''q_proj'''],
    ['''k_lin''', '''k_proj'''],
    ['''v_lin''', '''v_proj'''],
    ['''out_lin''', '''out_proj'''],
    ['''norm_embeddings''', '''layernorm_embedding'''],
    ['''position_embeddings''', '''embed_positions'''],
    ['''embeddings''', '''embed_tokens'''],
    ['''ffn.lin''', '''fc'''],
]







def      UpperCamelCase_						(					snake_case_       :       Tuple      )					->     Optional[int]:






 '''simple docstring'''

 if k == "embeddings.weight":
  return "shared.weight"

 for parlai_name, hf_name in PATTERNS:
  __lowerCAmelCase											=						k.replace(snake_case_						,		snake_case_      )

 if k.startswith("""encoder"""      ):
  __lowerCAmelCase											=						k.replace(""".attn"""						,		""".self_attn"""      )
  __lowerCAmelCase											=						k.replace("""norm1"""						,		"""self_attn_layer_norm"""      )
  __lowerCAmelCase											=						k.replace("""norm2"""						,		"""final_layer_norm"""      )
 elif k.startswith("""decoder"""      ):
  __lowerCAmelCase											=						k.replace("""norm1"""						,		"""self_attn_layer_norm"""      )
  __lowerCAmelCase											=						k.replace("""norm2"""						,		"""encoder_attn_layer_norm"""      )
  __lowerCAmelCase											=						k.replace("""norm3"""						,		"""final_layer_norm"""      )
 return k







def      UpperCamelCase_						(					snake_case_       :       List[str]      )					->     Dict:






 '''simple docstring'''

 __lowerCAmelCase											=						[
     """model.encoder.layernorm_embedding.weight""",
     """model.encoder.layernorm_embedding.bias""",
     """model.decoder.layernorm_embedding.weight""",
     """model.decoder.layernorm_embedding.bias""",
 ]
 for k in keys:
  __lowerCAmelCase											=						sd.pop(snake_case_      )
  __lowerCAmelCase											=						k.replace("""layernorm_embedding"""						,		"""layer_norm"""      )
  assert new_k not in sd
  __lowerCAmelCase											=						v


_A			:      int					      =				['''START''']







@torch.no_grad()
def      UpperCamelCase_						(					snake_case_       :       List[Any]						,		snake_case_       :       Any						,		snake_case_       :       Optional[int]      )					->     Optional[Any]:






 '''simple docstring'''

 __lowerCAmelCase											=						torch.load(snake_case_						,		map_location="""cpu"""      )
 __lowerCAmelCase											=						model["""model"""]
 __lowerCAmelCase											=						BlenderbotConfig.from_json_file(snake_case_      )
 __lowerCAmelCase											=						BlenderbotForConditionalGeneration(snake_case_      )
 __lowerCAmelCase											=						m.model.state_dict().keys()
 __lowerCAmelCase											=						[]
 __lowerCAmelCase											=						{}
 for k, v in sd.items():
  if k in IGNORE_KEYS:
   continue

  __lowerCAmelCase											=						rename_state_dict_key(snake_case_      )
  if new_k not in valid_keys:
   failures.append([k, new_k]      )
  else:
   __lowerCAmelCase											=						v
 if cfg.normalize_before:  # Blenderbot-3B checkpoints. Rename layernorm_embedding -> layer_norm
  rename_layernorm_keys(snake_case_      )
 m.model.load_state_dict(snake_case_						,		strict=snake_case_      )
 m.half()
 m.save_pretrained(snake_case_      )


if __name__ == "__main__":
 _A			:      Optional[Any]					      =				argparse.ArgumentParser()
 # Required parameters
 parser.add_argument('''--src_path''', type=str, help='''like blenderbot-model.bin''')
 parser.add_argument('''--save_dir''', default='''hf_blenderbot''', type=str, help='''Where to save converted model.''')
 parser.add_argument(
     '''--hf_config_json''', default='''blenderbot-3b-config.json''', type=str, help='''Path to config to use'''
 )
 _A			:      Tuple					      =				parser.parse_args()
 convert_parlai_checkpoint(args.src_path, args.save_dir, args.hf_config_json)






