ATL_CIKM-2019/ElasticNodes.py

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2019-12-04 14:18:56 +08:00
# Marcus Vinicius Sousa Leite de Carvalho
# marcus.decarvalho@ntu.edu.sg
# ivsucram@gmail.com
#
# NANYANG TECHNOLOGICAL UNIVERSITY - NTUITIVE PTE LTD Dual License Agreement
# Non-Commercial Use Only
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# Copyright (c) NTUITIVE. All rights reserved.
import numpy as np
class ElasticNodes:
###### Elastic Nodes ######
growable = None
prunable = None
data_mean = 0
data_standard_deviation = 0
data_variance = 0
number_samples_feed = 0
number_samples_layer = None
bias_mean = None
bias_variance = None
bias_standard_deviation = None
minimum_bias_mean = None
minimum_bias_standard_deviation = None
bias = None
var_mean = None
var_variance = None
var_standard_deviation = None
minimum_var_mean = None
minimum_var_standard_deviation = None
var = None
node_evolution = None
bias_gradient = None
bias_mean_net = None
var_mean_net = None
######
def __init__(self, number_hidden_layers=1):
nhl = number_hidden_layers #readability
self.number_samples_layer = np.zeros(nhl)
self.bias_mean = np.zeros(nhl)
self.bias_variance = np.zeros(nhl)
self.bias_standard_deviation = np.zeros(nhl)
self.minimum_bias_mean = np.ones(nhl) * np.inf
self.minimum_bias_standard_deviation = np.ones(nhl) * np.inf
self.BIAS = []
self.var_mean = np.zeros(nhl)
self.var_variance = np.zeros(nhl)
self.var_standard_deviation = np.zeros(nhl)
self.minimum_var_mean = np.ones(nhl) * np.inf
self.minimum_var_standard_deviation = np.ones(nhl) * np.inf
self.VAR = []
self.growable = np.ones(nhl) * False
self.prunable = []
for i in range(nhl):
self.prunable.append([-1])