[GitHub] arshitgupta opened a new issue #9042: Avoiding weight sharing among certain layers in BucketingModule?

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arshitgupta opened a new issue #9042: Avoiding weight sharing among certain layers in BucketingModule?
URL: https://github.com/apache/incubator-mxnet/issues/9042
 
 
   I am using BucketingModule for training multiple small models/bots together. Here, the bucket key is bot_id. However, each bot has separate set of target labels/classes (and hence, different size of softmax layer for each bot). 
   Is there any way to train such a model in mxnet, where I want to share the weights for all the layers but one (softmax) among all the bots? 
   How would I initialize such a model using sym_gen method?
    If in the sym_gen method, in the Softmax layer I specify the num_hidden=size_dict[bot] i.e., 
   pred = mx.sym.FullyConnected(data=pred, num_hidden=len(size_dict[bot]), name='pred')
   pred = mx.sym.SoftmaxOutput(data=pred, label=label, name='softmax')
   I get the error:
   "Inferred shape does not match shared_exec.arg_array's shape" which makes sense as each bot has different size.

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