def METHOD_NAME(inputs, filters, alpha, kernel=(3, 3), strides=(1, 1)):
    channel_axis = 1 if backend.image_data_format() == "channels_first" else -1
    filters = int(filters * alpha)
    x = layers.Conv2D(filters, kernel, padding="same", use_bias=False, strides=strides, name="conv1")(inputs)
    x = layers.BatchNormalization(axis=channel_axis, name="conv1_bn")(x)
    return layers.ReLU(6.0, name="conv1_relu")(x)