5cb43a9498315a16412cba20a59e6e76f9721b7b,capsulelayers.py,CapsuleLayer,call,#CapsuleLayer#Any#,94

Before Change

                             initializer=K.zeros([self.input_num_capsule, self.num_capsule, 1, self.dim_vector]))

        // update self.bias by routing algorithm
        for _ in range(self.num_routing):
            c = K.softmax(self.bias)
            c_expand = K.expand_dims(K.expand_dims(K.expand_dims(c, 2), 2), 0)
            outputs = K.sum(c_expand * inputs_hat, [1, 3], keepdims=True)
            outputs = squash(outputs)

            K.update(self.bias, self.bias + K.sum(inputs_hat * outputs, [0, -2, -1]))
        return K.reshape(outputs, [-1, self.num_capsule, self.dim_vector])

    def compute_output_shape(self, input_shape):
        return tuple([None, self.num_capsule, self.dim_vector])

After Change

            b = b + K.sum(inputs_hat * outputs, [0, -2, -1])
            return [i-1, b, outputs]

        cond = lambda i, b, inputs_hat: i > 0
        loop_vars = [K.constant(self.num_routing), self.bias, K.sum(inputs_hat, 1, keepdims=True)]
        _, self.bias, outputs = tf.while_loop(cond, body, loop_vars)

        
        // Routing algorithm V2. Seems not right. This may duplicate tensors by self.num_routing times.
        for _ in range(self.num_routing):

Instances