deepy.networks.BasicNetwork

Complexity

Total Complexity

10

Size/Duplication

Total Lines	36
Duplicated Lines	0 %

3 Methods

Rating	Name	Duplication	Size	Complexity
C	__init__()	0	22	8
A	cost()	0	3	1
A	test_cost()	0	3	1

#!/usr/bin/env python
# -*- coding: utf-8 -*-

from . import NeuralNetwork


class BasicNetwork(NeuralNetwork):
    """
    A simple neural network that the last layer outputs cost.
    """

    def __init__(self, input_dim=0, model=None, config=None, input_tensor=None,
                 cost=None, blocks=None, input_vars=None, target_vars=None):
        """
        Create a basic network.

        Parameters:
            input_dim - dimension of input variable
            model - a short hand to specify the model
            config - network configuration
            input_tensor - specify the tensor of input if it's special
        """
        super(BasicNetwork, self).__init__(input_dim, config=config, input_tensor=input_tensor)
        if model:
            self.stack(model)
        if cost:
            self.stack(cost)
        if blocks:
            self.register(*blocks)
        if input_vars:
            self.input_variables = [t.tensor for t in input_vars]
        if target_vars:
            self.target_variables = [t.tensor for t in target_vars]


    @property
    def cost(self):
        return self.output

    @property
    def test_cost(self):
        return self.test_output