custom_ops.py 文件源码

def __call__(self, input_layer, output_size, scope=None, in_dim=None, stddev=0.02, bias_start=0.0):
        shape = input_layer.shape
        input_ = input_layer.tensor
        try:
            if len(shape) == 4:
                input_ = tf.reshape(input_, tf.pack([tf.shape(input_)[0], np.prod(shape[1:])]))
                input_.set_shape([None, np.prod(shape[1:])])
                shape = input_.get_shape().as_list()

            with tf.variable_scope(scope or "Linear"):
                matrix = self.variable("Matrix", [in_dim or shape[1], output_size], dt=tf.float32,
                                       init=tf.random_normal_initializer(stddev=stddev))
                bias = self.variable("bias", [output_size], init=tf.constant_initializer(bias_start))
                return input_layer.with_tensor(tf.matmul(input_, matrix) + bias, parameters=self.vars)
        except Exception:
            import ipdb; ipdb.set_trace()