


"""simple docstring"""







import argparse
import hashlib  # hashlib is only used inside the Test class
import struct


class  SCREAMING_SNAKE_CASE__							:
       """simple docstring"""


       def __init__(		self						,	snake_case__		):






         """simple docstring"""





         lowerCAmelCase	:	Dict								=				data
         lowerCAmelCase	:	List[str]								=				[0x67_452_301, 0xef_cda_b89, 0x98_bad_cfe, 0x10_325_476, 0xc3_d2e_1f0]

       @staticmethod
       def 			lowercase__				(		snake_case__						,	snake_case__		):






         """simple docstring"""





         return ((n << b) | (n >> (32 - b))) & 0xff_fff_fff

       def 			lowercase__				(		self		):






         """simple docstring"""





         lowerCAmelCase	:	Any								=				B"\x80" + B"\x00" * (63 - (len(self.data		) + 8) % 64)
         lowerCAmelCase	:	Tuple								=				self.data + padding + struct.pack(">Q"						,	8 * len(self.data		)		)
         return padded_data

       def 			lowercase__				(		self		):






         """simple docstring"""





         return [
             self.padded_data[i : i + 64] for i in range(0						,	len(self.padded_data		)						,	64		)
         ]

       def 			lowercase__				(		self						,	snake_case__		):






         """simple docstring"""





         lowerCAmelCase	:	Optional[Any]								=				list(struct.unpack(">16L"						,	a__		)		) + [0] * 64
         for i in range(16						,	80		):
           lowerCAmelCase	:	Any								=				self.rotate((w[i - 3] ^ w[i - 8] ^ w[i - 14] ^ w[i - 16])						,	1		)
         return w







       def 			lowercase__				(		self		):






         """simple docstring"""





         lowerCAmelCase	:	Union[str, Any]								=				self.padding()
         lowerCAmelCase	:	List[str]								=				self.split_blocks()
         for block in self.blocks:
           lowerCAmelCase	:	int								=				self.expand_block(a__		)
           lowerCAmelCase		,    lowerCAmelCase		,    lowerCAmelCase		,    lowerCAmelCase		,    lowerCAmelCase	:	Any								=				self.h
           for i in range(0						,	80		):
             if 0 <= i < 20:
               lowerCAmelCase	:	Tuple								=				(b & c) | ((~b) & d)
               lowerCAmelCase	:	Dict								=				0x5a_827_999
             elif 20 <= i < 40:
               lowerCAmelCase	:	Any								=				b ^ c ^ d
               lowerCAmelCase	:	Optional[Any]								=				0x6e_d9e_ba1
             elif 40 <= i < 60:
               lowerCAmelCase	:	Union[str, Any]								=				(b & c) | (b & d) | (c & d)
               lowerCAmelCase	:	Dict								=				0x8f_1bb_cdc
             elif 60 <= i < 80:
               lowerCAmelCase	:	Dict								=				b ^ c ^ d
               lowerCAmelCase	:	str								=				0xca_62c_1d6
             lowerCAmelCase		,    lowerCAmelCase		,    lowerCAmelCase		,    lowerCAmelCase		,    lowerCAmelCase	:	Any								=				(
                 self.rotate(a__						,	5		) + f + e + k + expanded_block[i] & 0xff_fff_fff,
                 a,
                 self.rotate(a__						,	30		),
                 c,
                 d,
             )
           lowerCAmelCase	:	int								=				(
               self.h[0] + a & 0xff_fff_fff,
               self.h[1] + b & 0xff_fff_fff,
               self.h[2] + c & 0xff_fff_fff,
               self.h[3] + d & 0xff_fff_fff,
               self.h[4] + e & 0xff_fff_fff,
           )
         return ("{:08x}" * 5).format(*self.h		)

def    a__     (							):


  '''simple docstring'''







  lowerCAmelCase	:	List[Any]								=				B"Test String"
  assert SHAaHash(UpperCamelCase__							).final_hash() == hashlib.shaa(UpperCamelCase__							).hexdigest()  # noqa: S324
def    a__     (							):


  '''simple docstring'''







  lowerCAmelCase	:	List[Any]								=				argparse.ArgumentParser(description="Process some strings or files"							)
  parser.add_argument(
      "--string"							, dest="input_string"							, default="Hello World!! Welcome to Cryptography"							, help="Hash the string"							, )
  parser.add_argument("--file"							, dest="input_file"							, help="Hash contents of a file"							)
  lowerCAmelCase	:	List[str]								=				parser.parse_args()
  lowerCAmelCase	:	Any								=				args.input_string
  # In any case hash input should be a bytestring
  if args.input_file:
    with open(args.input_file							, "rb"							) as f:
      lowerCAmelCase	:	List[Any]								=				f.read()
  else:
    lowerCAmelCase	:	Tuple								=				bytes(UpperCamelCase__							, "utf-8"							)
  print(SHAaHash(UpperCamelCase__							).final_hash()							)


if __name__ == "__main__":
     main()
     import doctest

     doctest.testmod()









import argparse

import torch

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


logging.set_verbosity_info()
_lowercase							:   List[str]						=						logging.get_logger(__name__)

_lowercase							:   int						=						[
    ["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					( UpperCamelCase__:  str    )			-> int:





	"""simple docstring"""







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

	for parlai_name, hf_name in PATTERNS:
		A             =					k.replace(UpperCamelCase__				,       UpperCamelCase__    )

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





def 	_lowerCAmelCase					( UpperCamelCase__:  Tuple    )			-> str:





	"""simple docstring"""







	A             =					[
	    """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             =					sd.pop(UpperCamelCase__    )
		A             =					k.replace("""layernorm_embedding"""				,       """layer_norm"""    )
		assert new_k not in sd
		A             =					v


_lowercase							:   List[Any]						=						["START"]





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





	"""simple docstring"""







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

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


if __name__ == "__main__":
				_lowercase							:   str						=						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							:   List[str]						=						parser.parse_args()
				convert_parlai_checkpoint(args.src_path, args.save_dir, args.hf_config_json)



