Multi Label HDF5 Multi Task

[agjay...@gmail.com]

I have a dataset with each image having around 101 labels. I know, I have to use HDF5 data layer to feed my data into the network. But the problem is that I have a multi task setup.  My network has shared parameters for the first 5 layers and then branches off. Out of 101 labels, I want to send 100 labels to one task and 1 label to the second task. 

Now, How do I do this ? Can I somehow do the following : 

layer { name: "data" type: "HDF5Data" top: "data" top: "label1" ############# A scalar label

top : "label2" ######## A vector of size 100 include { phase: TRAIN } hdf5_data_param { source: "path/to/the/text/file/test.txt" batch_size: 10 } }

There are two top blobs in the above setup. One for the 100 dimensional vector(label2) and the other for the remaining label (label1). IS THIS KIND OF A SETUP POSSIBLE ?

I also read somewhere that one can split the multi dimensional vector specifying the split specifications in the prototxt file itself. In that case I would have to use a single top blob for label (101 dimensional) and then somehow split the

101-d vector in two vectors of 100-d and 1-d (scalar). How can this be done ? The layer in that case would like :

layer { name: "data" type: "HDF5Data" top: "data"

top : "label" ######## A vector of size 101 include { phase: TRAIN } hdf5_data_param { source: "path/to/the/text/file/test.txt" batch_size: 10 } }

############# Some layer to split the label blob into two vectors of 100-d and 1-d respectively

Any Idea of how this split may work ?

[James Guo]

Maybe this old post could help a bit, please have a look, thx https://groups.google.com/forum/#!topic/caffe-users/_NdX1tpHt5Y

[Ahmed Ibrahim]

you can do 101 label then slice them

layer {
  name: "slicer_label"
  type: "Slice"
  bottom: "label"
  ## label with a shape N x 101 x 1 x 1
  top: "label1"
  top: "label2"
  slice_param {
    axis: 1
    slice_point: 1 # or 100 if you would like to slice near the end side
  }
}

Or you can setup label1 and label two from the beginning then concatenate them when necessary like

 layer {

  name: "concat"
  bottom: "label1 "
  bottom: "label12"
  top: "out"
  type: "Concat"
  concat_param {
    axis: 1
  }
}

refer to http://caffe.berkeleyvision.org/tutorial/layers.html for more details