fd1c11f06438db0f586e6c552010145f0aa3e82a,tflearn/layers/conv.py,,residual_bottleneck,#,1221

Before Change

    in_channels = incoming.get_shape().as_list()[-1]

    // Variable Scope fix for older TF
    try:
        vscope = tf.variable_scope(scope, default_name=name, values=[incoming],
                                   reuse=reuse)
    except Exception:
        vscope = tf.variable_op_scope([incoming], scope, name, reuse=reuse)

    with vscope as scope:
        name = scope.name //TODO

        for i in range(nb_blocks):

After Change

    resnet = incoming
    in_channels = incoming.get_shape().as_list()[-1]

    with tf.variable_scope(scope, default_name=name, values=[incoming],
                           reuse=reuse) as scope:

        name = scope.name //TODO

Instances