| @@ -31,8 +31,8 @@ class ResnetBlock(Model): | |||
| self.merge = Add() | |||
| if self.__down_sample: | |||
| # perform down sampling using stride of 2, according to [1]. | |||
| self.res_conv = Conv2D( | |||
| self.res_conv = Conv2D( | |||
| self.__channels, strides=2, kernel_size=(1, 1), kernel_initializer=INIT_SCHEME, padding="same") | |||
| self.res_bn = BatchNormalization() | |||
| @@ -49,7 +49,7 @@ class ResnetBlock(Model): | |||
| res = self.res_conv(res) | |||
| res = self.res_bn(res) | |||
| # if not perform down sample, then add a shortcut directly | |||
| x = self.merge([x, res]) | |||
| out = x + tf.sin(x)**2 #tf.nn.relu(x) | |||
| return out | |||