def build(self, input_shape):
Conv1D.build(self, input_shape)
if self.needs_drop:
dc_kernel = K.dropout(self.kernel, self.prob, self.noise_shape)
self.kernel = self.replace_tensor(dc_kernel, self.kernel)
if self.drop_bias:
dc_bias = K.dropout(self.bias, self.prob, self.noise_shape)
self.bias = self.replace_tensor(dc_bias, self.bias)
def call(self, inputs, training=None):
if 0. < self.rate < 1.:
noise_shape = self._get_noise_shape(inputs)
return K.dropout(inputs, self.rate, noise_shape, seed=self.seed)
return inputs