```def se_layer(inputs_tensor=None,ratio=None,num=None):
channels = K.int_shape(inputs_tensor)[-1]
x = tf.layers.AveragePooling1D()(inputs_tensor)
x = tf.layers.Reshape((1, 1, channels))(x)
x = tf.layers.Conv1D(channels//ratio, (1, 1), strides=1, name="se_conv1_"+str(num), padding="valid")(x)
x = tf.layers.Activation('relu', name='se_conv1_relu_'+str(num))(x)
x = tf.layers.Conv1D(channels, (1, 1), strides=1, name="se_conv2_"+str(num), padding="valid")(x)
x = tf.layers.Activation('sigmoid', name='se_conv2_relu_'+str(num))(x)
output = tf.layers.multiply([inputs_tensor, x])
return output