What are Custom layers in TF learn

This recipe explains what are Custom layers in TF learn

Recipe Objective

This recipe explains what are custom layer in TFLayer.

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Custom Layer

Its syntax is: tflearn.layers.core.custom_layer (incoming, custom_fn, **kwargs)
where its arguments are incoming which is a Tensor or list of Tensor. Incoming tensor, custom_fn which is a custom function, to apply some ops on incoming tensor and, **kwargs which is some custom parameters that custom function might need.
The custom function is passed as a parameter or along with the parameters also any operations to the incoming Tensor or list of Tensor can be applied through a custom layer.

def customlayer(ic, fn, **kwargs):

    name = "Custom_Layer"
    if 'name' in kwargs:
       name = kwargs['name']
    with tf.name_scope(name):
       inf = fn(ic, **kwargs)

    return inf

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