machine learning - How to generate customer Pooling layer prototxt in pycaffe? -

my goal achieve pooling layer prototxt code follows:

layer {   name: "my_pooling"   type: "pooling_custom"   bottom: "conv1"   top: "my_pooling"   pooling_custom_param {     pool: max     kernel_size: 2     stride: 2     engine : caffe   } } 

where pooking_custom , pooling_custom_param modify pooling. want use python generate above output. using netspec it:

from caffe import params p n = caffe.netspec() my_pooling = l.pooling(conv1, type="pooling_custom",  pool=p.pooling.max, kernel_size=2, stride=2, engine=1) 

however, cannot generate pooling_custom_param. how can it? current result is

layer {   name: "my_pooling"   type: "pooling_custom"   bottom: "conv1"   top: "my_pooling"   pooling_param {     pool: max     kernel_size: 2     stride: 2     engine : caffe   } } 

if you're doing subtype of pooling, can't: attribute names defined parent template. can change values (right side of each item, after colon).

the functional reason you're incorporating methods parent class in field names hard-coded. instance, there refers pooling_param["kernel_size"]. if have changed name pooling_custom_param, need reconfigure software ... , that's outside language's software implementation.

if really need change attribute name, you're welcome clone entire pooling class, make change, , instantiate layers of new class.