


"""simple docstring"""
import argparse
import json

from transformers import GPTNeoConfig, GPTNeoForCausalLM, load_tf_weights_in_gpt_neo
from transformers.utils import logging


logging.set_verbosity_info()

def 							_snake_case			(      __snake_case       :			str	,   __snake_case       :			Any	,   __snake_case       :			Optional[Any]      ):




   """simple docstring"""







   _lowerCamelCase  :				List[Any]      =		json.load(open(__snake_case	,   """r"""      )      )
   _lowerCamelCase  :				Tuple      =		GPTNeoConfig(
       hidden_size=config_json["""n_embd"""]	,   num_layers=config_json["""n_layer"""]	,   num_heads=config_json["""n_head"""]	,   attention_types=config_json["""attention_types"""]	,   max_position_embeddings=config_json["""n_positions"""]	,   resid_dropout=config_json["""res_dropout"""]	,   embed_dropout=config_json["""embed_dropout"""]	,   attention_dropout=config_json["""attn_dropout"""]	,   )
   print(F'Building PyTorch model from configuration: {config}'      )
   _lowerCamelCase  :				Tuple      =		GPTNeoForCausalLM(__snake_case      )

   # Load weights from tf checkpoint
   load_tf_weights_in_gpt_neo(__snake_case	,   __snake_case	,   __snake_case      )

   # Save pytorch-model
   print(F'Save PyTorch model to {pytorch_dump_path}'      )
   model.save_pretrained(__snake_case      )


if __name__ == "__main__":
 UpperCAmelCase   =	argparse.ArgumentParser()
 # Required parameters
 parser.add_argument(
     """--tf_checkpoint_path""", default=None, type=str, required=True, help="""Path to the TensorFlow checkpoint path."""
 )
 parser.add_argument(
     """--config_file""",
     default=None,
     type=str,
     required=True,
     help=(
         """The config json file corresponding to the pre-trained mesh-tf model. \n"""
         """This specifies the model architecture."""
     ),
 )
 parser.add_argument(
     """--pytorch_dump_path""", default=None, type=str, required=True, help="""Path to the output PyTorch model."""
 )
 UpperCAmelCase   =	parser.parse_args()
 convert_tf_checkpoint_to_pytorch(args.tf_checkpoint_path, args.config_file, args.pytorch_dump_path)





"""simple docstring"""
def 							_snake_case			(      __snake_case       :			str	,   __snake_case       :			str	,   __snake_case       :			int	,   __snake_case       :			int	,   __snake_case       :			int	,   __snake_case       :			int	,   ):




   """simple docstring"""







   _lowerCamelCase  :				Optional[Any]      =		list(__snake_case      )
   _lowerCamelCase  :				Optional[int]      =		list(__snake_case      )
   _lowerCamelCase  :				Union[str, Any]      =		len(__snake_case      )
   _lowerCamelCase  :				Optional[int]      =		len(__snake_case      )

   _lowerCamelCase  :				List[str]      =		[
       [0 for _ in range(len_destination_seq + 1      )] for _ in range(len_source_seq + 1      )
   ]
   _lowerCamelCase  :				List[Any]      =		[
       ["""0""" for _ in range(len_destination_seq + 1      )] for _ in range(len_source_seq + 1      )
   ]

   for i in range(1	,   len_source_seq + 1      ):
      _lowerCamelCase  :				Optional[Any]      =		i * delete_cost
      _lowerCamelCase  :				Any      =		F'D{source_seq[i - 1]:c}'

   for i in range(1	,   len_destination_seq + 1      ):
      _lowerCamelCase  :				Dict      =		i * insert_cost
      _lowerCamelCase  :				List[str]      =		F'I{destination_seq[i - 1]:c}'

   for i in range(1	,   len_source_seq + 1      ):
      for j in range(1	,   len_destination_seq + 1      ):
         if source_seq[i - 1] == destination_seq[j - 1]:
            _lowerCamelCase  :				Union[str, Any]      =		costs[i - 1][j - 1] + copy_cost
            _lowerCamelCase  :				Tuple      =		F'C{source_seq[i - 1]:c}'
         else:
            _lowerCamelCase  :				Tuple      =		costs[i - 1][j - 1] + replace_cost
            _lowerCamelCase  :				List[str]      =		F'R{source_seq[i - 1]:c}' + str(destination_seq[j - 1]      )

         if costs[i - 1][j] + delete_cost < costs[i][j]:
            _lowerCamelCase  :				Any      =		costs[i - 1][j] + delete_cost
            _lowerCamelCase  :				Any      =		F'D{source_seq[i - 1]:c}'

         if costs[i][j - 1] + insert_cost < costs[i][j]:
            _lowerCamelCase  :				Dict      =		costs[i][j - 1] + insert_cost
            _lowerCamelCase  :				Union[str, Any]      =		F'I{destination_seq[j - 1]:c}'

   return costs, ops

def 							_snake_case			(      __snake_case       :			list[list[str]]	,   __snake_case       :			int	,   __snake_case       :			int      ):




   """simple docstring"""







   if i == 0 and j == 0:
      return []
   else:
      if ops[i][j][0] == "C" or ops[i][j][0] == "R":
         _lowerCamelCase  :				List[Any]      =		assemble_transformation(__snake_case	,   i - 1	,   j - 1      )
         seq.append(ops[i][j]      )
         return seq
      elif ops[i][j][0] == "D":
         _lowerCamelCase  :				Optional[Any]      =		assemble_transformation(__snake_case	,   i - 1	,   __snake_case      )
         seq.append(ops[i][j]      )
         return seq
      else:
         _lowerCamelCase  :				str      =		assemble_transformation(__snake_case	,   __snake_case	,   j - 1      )
         seq.append(ops[i][j]      )
         return seq


if __name__ == "__main__":
 UpperCAmelCase ,     UpperCAmelCase   =	compute_transform_tables("""Python""", """Algorithms""", -1, 1, 2, 2)

 UpperCAmelCase   =	len(operations)
 UpperCAmelCase   =	len(operations[0])
 UpperCAmelCase   =	assemble_transformation(operations, m - 1, n - 1)

 UpperCAmelCase   =	list("""Python""")
 UpperCAmelCase   =	0
 UpperCAmelCase   =	0

 with open("""min_cost.txt""", """w""") as file:
  for op in sequence:
   print("""""".join(string))

   if op[0] == "C":
    file.write("""%-16s""" % """Copy %c""" % op[1])
    file.write("""\t\t\t""" + """""".join(string))
    file.write("""\r\n""")

    cost -= 1
   elif op[0] == "R":
    UpperCAmelCase   =	op[2]

    file.write("""%-16s""" % ("""Replace %c""" % op[1] + """ with """ + str(op[2])))
    file.write("""\t\t""" + """""".join(string))
    file.write("""\r\n""")

    cost += 1
   elif op[0] == "D":
    string.pop(i)

    file.write("""%-16s""" % """Delete %c""" % op[1])
    file.write("""\t\t\t""" + """""".join(string))
    file.write("""\r\n""")

    cost += 2
   else:
    string.insert(i, op[1])

    file.write("""%-16s""" % """Insert %c""" % op[1])
    file.write("""\t\t\t""" + """""".join(string))
    file.write("""\r\n""")

    cost += 2

   i += 1

  print("""""".join(string))
  print("""Cost: """, cost)

  file.write("""\r\nMinimum cost: """ + str(cost))

