parameters: (self, inputs, outputs, batch_size=1, iteration=1)
return_statement: return result
docstring: Run predict using the supplied 'inputs' to calculate the outputs specified by 'outputs'.
          :param inputs: Dictionary from input name to the value(s) for that input.
              An input value is specified as a numpy array. Each input in the dictionary
              maps to a list of values (i.e. a list of numpy array objects), where the length
              of the list must equal the 'batch_size'.
          :param outputs: list of string or dictionary of name: type indicating the output names should be returned
          :param batch_size: The batch size of the prediction. Each input must provide
              an appropriately sized batch of inputs.
          :param iteration: iteration times for send request, just for evaluating time of server process request
          :return: A dictionary from output name to the list of values for
              that output (one list element for each entry of the
              batch).
docstring_summary: Run predict using the supplied 'inputs' to calculate the outputs specified by 'outputs'.
          :param inputs: Dictionary from input name to the value(s) for that input.
              An input value is specified as a numpy array. Each input in the dictionary
              maps to a list of values (i.e. a list of numpy array objects), where the length
              of the list must equal the 'batch_size'.
          :param outputs: list of string or dictionary of name: type indicating the output names should be returned
          :param batch_size: The batch size of the prediction. Each input must provide
              an appropriately sized batch of inputs.
          :param iteration: iteration times for send request, just for evaluating time of server process request
          :return: A dictionary from output name to the list of values for
              that output (one list element for each entry of the
              batch).
docstring_tokens: Run predict using the supplied inputs to calculate the outputs specified by outputs . : param inputs : Dictionary from input name to the value ( s ) for that input . An input value is specified as a numpy array . Each input in the dictionary maps to a list of values ( i . e . a list of numpy array objects ) where the length of the list must equal the batch_size . : param outputs : list of string or dictionary of name : type indicating the output names should be returned : param batch_size : The batch size of the prediction . Each input must provide an appropriately sized batch of inputs . : param iteration : iteration times for send request just for evaluating time of server process request : return : A dictionary from output name to the list of values for that output ( one list element for each entry of the batch ) .
function: def run(self, inputs, outputs, batch_size=1, iteration=1):
          """
          Run predict using the supplied 'inputs' to calculate the outputs specified by 'outputs'.
          :param inputs: Dictionary from input name to the value(s) for that input.
              An input value is specified as a numpy array. Each input in the dictionary
              maps to a list of values (i.e. a list of numpy array objects), where the length
              of the list must equal the 'batch_size'.
          :param outputs: list of string or dictionary of name: type indicating the output names should be returned
          :param batch_size: The batch size of the prediction. Each input must provide
              an appropriately sized batch of inputs.
          :param iteration: iteration times for send request, just for evaluating time of server process request
          :return: A dictionary from output name to the list of values for
              that output (one list element for each entry of the
              batch).
          """
          request = self._prepare_request(inputs, outputs, batch_size)
          response = None
          start = time.time()
          for i in range(iteration):
              response = self._runner.predict(request)
          end = time.time()
          if self._verbose:
              print('Run model {} predict (batch size={}) use {} ms'.format(
                  self._model_name, batch_size, (end - start) * 1000 / iteration))
          result = self.process_response(outputs, response)
          return result
function_tokens: def run ( self , inputs , outputs , batch_size = 1 , iteration = 1 ) : request = self . _prepare_request ( inputs , outputs , batch_size ) response = None start = time . time ( ) for i in range ( iteration ) : response = self . _runner . predict ( request ) end = time . time ( ) if self . _verbose : print ( 'Run model {} predict (batch size={}) use {} ms' . format ( self . _model_name , batch_size , ( end - start ) * 1000 / iteration ) ) result = self . process_response ( outputs , response ) return result