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#!/usr/bin/env python
# -*- coding: utf-8 -*-
from . import NeuralLayer
from conv import Convolution
class PRelu(NeuralLayer):
"""
Probabilistic ReLU.
- http://arxiv.org/pdf/1502.01852v1.pdf
def __init__(self, input_tensor=2):
super(PRelu, self).__init__("prelu")
self.input_tensor = input_tensor
def prepare(self):
self.alphas = self.create_bias(self.output_dim, "alphas")
self.register_parameters(self.alphas)
if self.input_tensor == 3:
self.alphas = self.alphas.dimshuffle('x', 0, 'x')
elif self.input_tensor == 4:
self.alphas = self.alphas.dimshuffle('x', 0, 'x', 'x')
def compute_tensor(self, x):
positive_vector = x * (x >= 0)
negative_vector = self.alphas * (x * (x < 0))
return positive_vector + negative_vector
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