69e3319c4bffaa78823be2267f036d3d3fdf286e,tensorlayer/layers/activation.py,PTRelu6,forward,#PTRelu6#,237

Before Change

        // self.add_weights([self.alpha_low, self.alpha_high])

    def forward(self, inputs):
        outputs = self._apply_activation(
            inputs, **{
                "alpha_low": self.alpha_low_constrained,
                "alpha_high": self.alpha_high_constrained,
                "name": "ptrelu6_activation"
            }
        )
        return outputs

After Change

        self.alpha_high_constrained = tf.nn.sigmoid(self.alpha_high, name="constraining_alpha_high_in_0_1")

    def forward(self, inputs):
        pos = tf.nn.relu(inputs)
        pos_6 = -tf.nn.relu(inputs - 6) + self.alpha_high_constrained * tf.nn.relu(inputs - 6)
        neg = -self.alpha_low_constrained * tf.nn.relu(-inputs)

        return pos + pos_6 + neg

Instances