| # -*- coding: utf8 -*- |
| import torch |
| from .Module import Module |
| |
| |
| class ELU(Module): |
| """ |
| Djork-Arné Clevert, Thomas Unterthiner, Sepp Hochreiter |
| Fast and Accurate Deep Network Learning by Exponential Linear Units (ELUs) |
| http.//arxiv.org/pdf/1511.07289.pdf |
| """ |
| |
| def __init__(self, alpha=1., inplace=False): |
| assert type(alpha) == float |
| super(ELU, self).__init__() |
| self.alpha = alpha |
| self.inplace = inplace |
| |
| def updateOutput(self, input): |
| self._backend.ELU_updateOutput( |
| self._backend.library_state, |
| input, |
| self.output, |
| self.alpha, |
| 1.0, |
| 1.0, |
| self.inplace |
| ) |
| return self.output |
| |
| def updateGradInput(self, input, gradOutput): |
| self._backend.ELU_updateGradInput( |
| self._backend.library_state, |
| gradOutput, |
| self.gradInput, |
| self.output, |
| self.alpha, |
| 1.0, |
| 1.0 |
| ) |
| return self.gradInput |
| |
| def __repr__(self): |
| return '{}(alpha={:.3f})'.format(str(type(self)), self.alpha) |
