conv.py 文件源码

def global_max_pool(incoming, name="GlobalMaxPool"):
    """ Global Max Pooling.

    Input:
        4-D Tensor [batch, height, width, in_channels].

    Output:
        2-D Tensor [batch, pooled dim]

    Arguments:
        incoming: `Tensor`. Incoming 4-D Tensor.
        name: A name for this layer (optional). Default: 'GlobalMaxPool'.

    """
    input_shape = utils.get_incoming_shape(incoming)
    assert len(input_shape) == 4, "Incoming Tensor shape must be 4-D"

    with tf.name_scope(name):
        inference = tf.reduce_max(incoming, [1, 2])

    # Track output tensor.
    tf.add_to_collection(tf.GraphKeys.LAYER_TENSOR + '/' + name, inference)

    return inference