





import argparse
from pathlib import Path

from transformers import AutoConfig, AutoTokenizer, RagConfig, RagSequenceForGeneration, RagTokenForGeneration






def 							_lowerCAmelCase (  _a   :					Any					,   _a   :					str					,   _a   :					str					,   _a   :					Path					,   _a   :					str = None					,   _a   :					str = None					,   _a   :					str = None					,   )	->			Union[str, Any]:
     if config_name_or_path is None:
          lowerCAmelCase_					:       Dict    =		"""facebook/rag-token-base""" if model_type == """rag_token""" else """facebook/rag-sequence-base"""

     if generator_tokenizer_name_or_path is None:
          lowerCAmelCase_					:       int    =		generator_name_or_path

     if question_encoder_tokenizer_name_or_path is None:
          lowerCAmelCase_					:       List[Any]    =		question_encoder_name_or_path

     lowerCAmelCase_					:       Optional[Any]    =		RagTokenForGeneration if model_type == """rag_token""" else RagSequenceForGeneration

     # Save model.
     lowerCAmelCase_					:       Dict    =		RagConfig.from_pretrained(_a			)
     lowerCAmelCase_					:       Optional[int]    =		AutoConfig.from_pretrained(_a			)
     lowerCAmelCase_					:       List[Any]    =		AutoConfig.from_pretrained(_a			)

     lowerCAmelCase_					:       Any    =		gen_config
     lowerCAmelCase_					:       List[Any]    =		question_encoder_config

     lowerCAmelCase_					:       int    =		model_class.from_pretrained_question_encoder_generator(
         _a					,   _a					,   config=_a			)
     rag_model.save_pretrained(_a			)

     # Sanity check.
     model_class.from_pretrained(_a			)

     # Save tokenizers.
     lowerCAmelCase_					:       List[str]    =		AutoTokenizer.from_pretrained(_a			)
     gen_tokenizer.save_pretrained(dest_dir / """generator_tokenizer/"""			)
     lowerCAmelCase_					:       Dict    =		AutoTokenizer.from_pretrained(_a			)
     question_encoder_tokenizer.save_pretrained(dest_dir / """question_encoder_tokenizer/"""			)


if __name__ == "__main__":
      UpperCAmelCase_					:   Dict 							=						argparse.ArgumentParser()
      parser.add_argument(
          """--model_type""",
          choices=["""rag_sequence""", """rag_token"""],
          required=True,
          type=str,
          help="""RAG model type: rag_sequence, rag_token""",
      )
      parser.add_argument("""--dest""", type=str, required=True, help="""Path to the output checkpoint directory.""")
      parser.add_argument("""--generator_name_or_path""", type=str, required=True, help="""Generator model identifier""")
      parser.add_argument(
          """--question_encoder_name_or_path""", type=str, required=True, help="""Question encoder model identifier"""
      )

      parser.add_argument(
          """--generator_tokenizer_name_or_path""",
          type=str,
          help="""Generator tokenizer identifier, if not specified, resolves to ``generator_name_or_path``""",
      )
      parser.add_argument(
          """--question_encoder_tokenizer_name_or_path""",
          type=str,
          help="""Question encoder tokenizer identifier, if not specified, resolves to ``question_encoder_name_or_path``""",
      )
      parser.add_argument(
          """--config_name_or_path""",
          type=str,
          help=(
              """Identifier of the model config to use, if not provided, resolves to a base config for a given"""
              """ ``model_type``"""
          ),
      )

      UpperCAmelCase_					:   Tuple 							=						parser.parse_args()

      UpperCAmelCase_					:   str 							=						Path(args.dest)
      dest_dir.mkdir(exist_ok=True)

      consolidate(
          args.model_type,
          args.generator_name_or_path,
          args.question_encoder_name_or_path,
          dest_dir,
          args.config_name_or_path,
          args.generator_tokenizer_name_or_path,
          args.question_encoder_tokenizer_name_or_path,
      )







UpperCAmelCase_					:   str 							=						"""Alexander Joslin"""

import operator as op

from .stack import Stack






def 							_lowerCAmelCase (  _a   :					str			)	->			int:
     lowerCAmelCase_					:       Any    =		{"""*""": op.mul, """/""": op.truediv, """+""": op.add, """-""": op.sub}

     lowerCAmelCase_					:       Stack[int]    =		Stack()
     lowerCAmelCase_					:       Stack[str]    =		Stack()

     for i in equation:
          if i.isdigit():
               # RULE 1
               operand_stack.push(int(_a			)			)
          elif i in operators:
               # RULE 2
               operator_stack.push(_a			)
          elif i == ")":
               # RULE 4
               lowerCAmelCase_					:       Optional[int]    =		operator_stack.peek()
               operator_stack.pop()
               lowerCAmelCase_					:       Union[str, Any]    =		operand_stack.peek()
               operand_stack.pop()
               lowerCAmelCase_					:       List[str]    =		operand_stack.peek()
               operand_stack.pop()

               lowerCAmelCase_					:       Dict    =		operators[opr](_a					,   _a			)
               operand_stack.push(_a			)

    # RULE 5
     return operand_stack.peek()


if __name__ == "__main__":
      UpperCAmelCase_					:   Dict 							=						"""(5 + ((4 * 2) * (2 + 3)))"""
      # answer = 45
      print(F"""{equation} = {dijkstras_two_stack_algorithm(equation)}""")
