Source code for pacman.executor.algorithm_classes.abstract_python_algorithm

# Copyright (c) 2017-2019 The University of Manchester
#
# This program is free software: you can redistribute it and/or modify
# it under the terms of the GNU General Public License as published by
# the Free Software Foundation, either version 3 of the License, or
# (at your option) any later version.
#
# This program is distributed in the hope that it will be useful,
# but WITHOUT ANY WARRANTY; without even the implied warranty of
# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the
# GNU General Public License for more details.
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# You should have received a copy of the GNU General Public License
# along with this program.  If not, see <http://www.gnu.org/licenses/>.

from abc import abstractmethod
from spinn_utilities.overrides import overrides
from pacman.exceptions import PacmanAlgorithmFailedToGenerateOutputsException
from .abstract_algorithm import AbstractAlgorithm


[docs]class AbstractPythonAlgorithm(AbstractAlgorithm): """ An algorithm written in Python. """ __slots__ = [ # The module containing the python code to execute "_python_module" ] def __init__( self, algorithm_id, required_inputs, optional_inputs, outputs, required_input_tokens, optional_input_tokens, generated_output_tokens, python_module): """ :param python_module: The module containing the python code to execute """ # pylint: disable=too-many-arguments super(AbstractPythonAlgorithm, self).__init__( algorithm_id, required_inputs, optional_inputs, outputs, required_input_tokens, optional_input_tokens, generated_output_tokens) self._python_module = python_module
[docs] @abstractmethod def call_python(self, inputs): """ Call the algorithm :param inputs: A dict of parameter name -> value :return: The result of calling the python algorithm """
[docs] @overrides(AbstractAlgorithm.call) def call(self, inputs): # Get the inputs to pass to the function method_inputs = self._get_inputs(inputs) # Run the algorithm and get the results results = self.call_python(method_inputs) if results is not None and not isinstance(results, tuple): results = (results,) # If there are no results and there are not meant to be, return if results is None and not self._outputs: return None # Check the results are valid if ((results is None and self._outputs) or len(self._outputs) != len(results)): raise PacmanAlgorithmFailedToGenerateOutputsException( "Algorithm {} returned {} but specified {} output types" .format(self._algorithm_id, results, len(self._outputs))) # Return the results processed into a dict return self._get_outputs(inputs, results)