NeuralRegressor.__init__() - Code Metrics - zomux/deepy - Measure and Improve Code Quality continuously with Scrutinizer

NeuralRegressor.init() A
last analyzed 2017-01-17 00:28 UTC

↳ Parent: NeuralRegressor

Complexity

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Size

Total Lines

Duplication

Lines	0
Ratio	0 %

Importance

Changes

Metric	Value
cc	2
dl	0
loc	4
rs	10
c	0
b	0
f	0

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

from theano import tensor as T
import deepy.tensor as DT
from . import NeuralNetwork
from deepy.utils import dim_to_var


class NeuralRegressor(NeuralNetwork):
    """
    A class of defining stacked neural network regressors.
    """
    def __init__(self, input_dim, target_tensor=2, clip_value=None, input_tensor=None):
        self.target_tensor = dim_to_var(target_tensor, "k") if type(target_tensor) == int else target_tensor
        self.clip_value = clip_value
        super(NeuralRegressor, self).__init__(input_dim, input_tensor=input_tensor)

    def setup_variables(self):
        super(NeuralRegressor, self).setup_variables()
        self.k = self.target_tensor
        self.target_variables.append(self.k)

    def _cost_func(self, y):
        if self.clip_value:
            y = T.clip(y, -self.clip_value, self.clip_value)
        return DT.costs.least_squares(y, self.k)

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

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

1			#!/usr/bin/env python
2			# -- coding: utf-8 --
3
4			from theano import tensor as T
5			import deepy.tensor as DT
6			from . import NeuralNetwork
7			from deepy.utils import dim_to_var
8
9
10			class NeuralRegressor(NeuralNetwork):
11			"""
12			A class of defining stacked neural network regressors.
13			"""
14			def __init__(self, input_dim, target_tensor=2, clip_value=None, input_tensor=None):
15			self.target_tensor = dim_to_var(target_tensor, "k") if type(target_tensor) == int else target_tensor
16			self.clip_value = clip_value
17			super(NeuralRegressor, self).__init__(input_dim, input_tensor=input_tensor)
18
19			def setup_variables(self):
20			super(NeuralRegressor, self).setup_variables()
21			self.k = self.target_tensor
22			self.target_variables.append(self.k)
23
24			def _cost_func(self, y):
25			if self.clip_value:
26			y = T.clip(y, -self.clip_value, self.clip_value)
27			return DT.costs.least_squares(y, self.k)
28
29			@property
30			def cost(self):
31			return self._cost_func(self.output)
32
33			@property
34			def test_cost(self):
35			return self._cost_func(self.test_output)

zomux / deepy

NeuralRegressor.__init__() A last analyzed 2017-01-17 00:28 UTC

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NeuralRegressor.init() A
last analyzed 2017-01-17 00:28 UTC