




import json
import os
import tempfile
import unittest
import unittest.mock as mock
from pathlib import Path

from requests.exceptions import HTTPError

from transformers.utils import (
    CONFIG_NAME,
    FLAX_WEIGHTS_NAME,
    TF2_WEIGHTS_NAME,
    TRANSFORMERS_CACHE,
    WEIGHTS_NAME,
    cached_file,
    get_file_from_repo,
    has_file,
)


SCREAMING_SNAKE_CASE__			: Any    =  '''hf-internal-testing/tiny-random-bert'''
SCREAMING_SNAKE_CASE__			: Optional[Any]    =  os.path.join(TRANSFORMERS_CACHE, 'models--hf-internal-testing--tiny-random-bert')
SCREAMING_SNAKE_CASE__			: List[Any]    =  '''9b8c223d42b2188cb49d29af482996f9d0f3e5a6'''




class 						UpperCamelCase__      (unittest.TestCase	):

    '''simple docstring'''



    def        _lowercase	(       self	)	-> Any:
           lowerCamelCase  : List[Any]     					=   cached_file(_UpperCAmelCase	,    _UpperCAmelCase	)
           # Should have downloaded the file in here
           self.assertTrue(os.path.isdir(_UpperCAmelCase	)	)
           # Cache should contain at least those three subfolders:
           for subfolder in ["blobs", "refs", "snapshots"]:
                  self.assertTrue(os.path.isdir(os.path.join(_UpperCAmelCase	,    _UpperCAmelCase	)	)	)
           with open(os.path.join(_UpperCAmelCase	,    "refs"	,    "main"	)	) as f:
                  lowerCamelCase  : Any     					=   f.read()
           self.assertEqual(_UpperCAmelCase	,    os.path.join(_UpperCAmelCase	,    "snapshots"	,    _UpperCAmelCase	,    _UpperCAmelCase	)	)
           self.assertTrue(os.path.isfile(_UpperCAmelCase	)	)

           # File is cached at the same place the second time.
           lowerCamelCase  : Tuple     					=   cached_file(_UpperCAmelCase	,    _UpperCAmelCase	)
           self.assertEqual(_UpperCAmelCase	,    _UpperCAmelCase	)

           # Using a specific revision to test the full commit hash.
           lowerCamelCase  : List[Any]     					=   cached_file(_UpperCAmelCase	,    _UpperCAmelCase	,    revision="9b8c223"	)
           self.assertEqual(_UpperCAmelCase	,    os.path.join(_UpperCAmelCase	,    "snapshots"	,    _UpperCAmelCase	,    _UpperCAmelCase	)	)







    def        _lowercase	(       self	)	-> Dict:






           with self.assertRaisesRegex(_UpperCAmelCase	,    "is not a valid model identifier"	):
                  lowerCamelCase  : Dict     					=   cached_file("tiny-random-bert"	,    _UpperCAmelCase	)

           with self.assertRaisesRegex(_UpperCAmelCase	,    "is not a valid git identifier"	):
                  lowerCamelCase  : Optional[int]     					=   cached_file(_UpperCAmelCase	,    _UpperCAmelCase	,    revision="aaaa"	)

           with self.assertRaisesRegex(_UpperCAmelCase	,    "does not appear to have a file named"	):
                  lowerCamelCase  : int     					=   cached_file(_UpperCAmelCase	,    "conf"	)







    def        _lowercase	(       self	)	-> Optional[int]:






           with self.assertRaisesRegex(_UpperCAmelCase	,    "does not appear to have a file named"	):
                  lowerCamelCase  : Any     					=   cached_file(_UpperCAmelCase	,    "conf"	)

           with open(os.path.join(_UpperCAmelCase	,    "refs"	,    "main"	)	) as f:
                  lowerCamelCase  : Dict     					=   f.read()
           self.assertTrue(os.path.isfile(os.path.join(_UpperCAmelCase	,    ".no_exist"	,    _UpperCAmelCase	,    "conf"	)	)	)

           lowerCamelCase  : List[Any]     					=   cached_file(_UpperCAmelCase	,    "conf"	,    _raise_exceptions_for_missing_entries=_UpperCAmelCase	)
           self.assertIsNone(_UpperCAmelCase	)

           lowerCamelCase  : str     					=   cached_file(_UpperCAmelCase	,    "conf"	,    local_files_only=_UpperCAmelCase	,    _raise_exceptions_for_missing_entries=_UpperCAmelCase	)
           self.assertIsNone(_UpperCAmelCase	)

           lowerCamelCase  : List[str]     					=   mock.Mock()
           lowerCamelCase  : Dict     					=   500
           lowerCamelCase  : List[str]     					=   {}
           lowerCamelCase  : List[Any]     					=   HTTPError
           lowerCamelCase  : Optional[Any]     					=   {}

           # Under the mock environment we get a 500 error when trying to reach the tokenizer.
           with mock.patch("requests.Session.request"	,    return_value=_UpperCAmelCase	) as mock_head:
                  lowerCamelCase  : Dict     					=   cached_file(_UpperCAmelCase	,    "conf"	,    _raise_exceptions_for_connection_errors=_UpperCAmelCase	)
                  self.assertIsNone(_UpperCAmelCase	)
                  # This check we did call the fake head request
                  mock_head.assert_called()







    def        _lowercase	(       self	)	-> Any:
           self.assertTrue(has_file("hf-internal-testing/tiny-bert-pt-only"	,    _UpperCAmelCase	)	)
           self.assertFalse(has_file("hf-internal-testing/tiny-bert-pt-only"	,    _UpperCAmelCase	)	)
           self.assertFalse(has_file("hf-internal-testing/tiny-bert-pt-only"	,    _UpperCAmelCase	)	)







    def        _lowercase	(       self	)	-> Dict:
           self.assertIsNone(get_file_from_repo("bert-base-cased"	,    "ahah.txt"	)	)

           # The function raises if the repository does not exist.
           with self.assertRaisesRegex(_UpperCAmelCase	,    "is not a valid model identifier"	):
                  get_file_from_repo("bert-base-case"	,    _UpperCAmelCase	)

           # The function raises if the revision does not exist.
           with self.assertRaisesRegex(_UpperCAmelCase	,    "is not a valid git identifier"	):
                  get_file_from_repo("bert-base-cased"	,    _UpperCAmelCase	,    revision="ahaha"	)

           lowerCamelCase  : List[str]     					=   get_file_from_repo("bert-base-cased"	,    _UpperCAmelCase	)
           # The name is the cached name which is not very easy to test, so instead we load the content.
           lowerCamelCase  : List[str]     					=   json.loads(open(_UpperCAmelCase	,    "r"	).read()	)
           self.assertEqual(config["hidden_size"]	,    768	)







    def        _lowercase	(       self	)	-> Optional[int]:






           with tempfile.TemporaryDirectory() as tmp_dir:
                  lowerCamelCase  : Tuple     					=   Path(_UpperCAmelCase	) / 'a.txt'
                  filename.touch()
                  self.assertEqual(get_file_from_repo(_UpperCAmelCase	,    "a.txt"	)	,    str(_UpperCAmelCase	)	)

                  self.assertIsNone(get_file_from_repo(_UpperCAmelCase	,    "b.txt"	)	)













'''simple docstring'''




import argparse

import torch

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


logging.set_verbosity_info()
lowercase__       : Tuple         =       logging.get_logger(__name__)

lowercase__       : 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 			_lowerCAmelCase     (    __snake_case    :					List[Any]     )	->	Tuple:
     if k == "embeddings.weight":
          return "shared.weight"

     for parlai_name, hf_name in PATTERNS:
          __A		:					Optional[Any]						=			k.replace(__snake_case					,				__snake_case     )

     if k.startswith('encoder'     ):
          __A		:					Any						=			k.replace('.attn'					,				'.self_attn'     )
          __A		:					Any						=			k.replace('norm1'					,				'self_attn_layer_norm'     )
          __A		:					str						=			k.replace('norm2'					,				'final_layer_norm'     )
     elif k.startswith('decoder'     ):
          __A		:					Tuple						=			k.replace('norm1'					,				'self_attn_layer_norm'     )
          __A		:					str						=			k.replace('norm2'					,				'encoder_attn_layer_norm'     )
          __A		:					int						=			k.replace('norm3'					,				'final_layer_norm'     )
     return k






def 			_lowerCAmelCase     (    __snake_case    :					List[Any]     )	->	Dict:
     __A		:					Optional[int]						=			[
         'model.encoder.layernorm_embedding.weight',
         'model.encoder.layernorm_embedding.bias',
         'model.decoder.layernorm_embedding.weight',
         'model.decoder.layernorm_embedding.bias',
     ]
     for k in keys:
          __A		:					Tuple						=			sd.pop(__snake_case     )
          __A		:					Union[str, Any]						=			k.replace('layernorm_embedding'					,				'layer_norm'     )
          assert new_k not in sd
          __A		:					str						=			v


lowercase__       : Tuple         =       ['''START''']






@torch.no_grad()
def 			_lowerCAmelCase     (    __snake_case    :					Dict					,				__snake_case    :					Any					,				__snake_case    :					List[Any]     )	->	int:
     __A		:					List[str]						=			torch.load(__snake_case					,				map_location='cpu'     )
     __A		:					Tuple						=			model['model']
     __A		:					str						=			BlenderbotConfig.from_json_file(__snake_case     )
     __A		:					int						=			BlenderbotForConditionalGeneration(__snake_case     )
     __A		:					List[Any]						=			m.model.state_dict().keys()
     __A		:					Optional[int]						=			[]
     __A		:					Optional[int]						=			{}
     for k, v in sd.items():
          if k in IGNORE_KEYS:
               continue

          __A		:					Union[str, Any]						=			rename_state_dict_key(__snake_case     )
          if new_k not in valid_keys:
               failures.append([k, new_k]     )
          else:
               __A		:					Optional[Any]						=			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__":
  lowercase__       : Dict         =       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'''
  )
  lowercase__       : Optional[Any]         =       parser.parse_args()
  convert_parlai_checkpoint(args.src_path, args.save_dir, args.hf_config_json)