deepy.networks.ComputationalGraph.__init__() - Code Metrics - Inspection of "Big refactoring" - zomux/deepy - Measure and Improve Code Quality continuously with Scrutinizer

Completed

Push — master ( 8f7ec7...957d47 )

by Raphael

created 2016-02-02 01:21 UTC

deepy.networks.ComputationalGraph.init() F

↳ Parent: deepy.networks.ComputationalGraph

Complexity

Conditions

Size

Total Lines

Duplication

Lines	0
Ratio	0 %

Metric	Value
cc	9
dl	0
loc	24
rs	3.4838

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

from . import NeuralNetwork


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

    def __init__(self, input_dim=0, model=None, input_tensor=None,
                 cost=None, output=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(ComputationalGraph, self).__init__(input_dim, input_tensor=input_tensor)
        if model:
            self.stack(model)
        if output:
            self.stack(output)
        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

1			#!/usr/bin/env python
2			# -- coding: utf-8 --
3
4			from . import NeuralNetwork
5
6
7			class ComputationalGraph(NeuralNetwork):
8			"""
9			A simple neural network that the last layer outputs cost.
10			"""
11
12			def __init__(self, input_dim=0, model=None, input_tensor=None,
13			cost=None, output=None, blocks=None, input_vars=None, target_vars=None):
14			"""
15			Create a basic network.
16
17			Parameters:
18			input_dim - dimension of input variable
19			model - a short hand to specify the model
20			config - network configuration
21			input_tensor - specify the tensor of input if it's special
22			"""
23			super(ComputationalGraph, self).__init__(input_dim, input_tensor=input_tensor)
24			if model:
25			self.stack(model)
26			if output:
27			self.stack(output)
28			if cost:
29			self.stack(cost)
30			if blocks:
31			self.register(*blocks)
32			if input_vars:
33			self.input_variables = [t.tensor for t in input_vars]
34			if target_vars:
35			self.target_variables = [t.tensor for t in target_vars]
36
37
38			@property
39			def cost(self):
40			return self.output
41
42			@property
43			def test_cost(self):
44			return self.test_output

zomux / deepy

Push — master ( 8f7ec7...957d47 )

deepy.networks.ComputationalGraph.__init__() F

Complexity

Size

Duplication

Duplication Side-by-Side

Filter issues like

deepy.networks.ComputationalGraph.init() F