def call(self, inputs):
ternary_kernel = ternarize(self.kernel, H=self.H)
output = K.dot(inputs, ternary_kernel)
if self.use_bias:
output = K.bias_add(output, self.bias)
if self.activation is not None:
output = self.activation(output)
return output
def call(self, inputs):
ternary_kernel = ternarize(self.kernel, H=self.H)
outputs = K.conv2d(inputs,
ternary_kernel,
strides=self.strides,
padding=self.padding,
data_format=self.data_format,
dilation_rate=self.dilation_rate)
if self.use_bias:
outputs = K.bias_add(outputs,
self.bias,
data_format=self.data_format)
if self.activation is not None:
return self.activation(outputs)
return outputs
def ternary_tanh(x):
x = K.clip(x, -1, 1)
return ternarize(x)
