Added a test in test_NetworkCompare to verify cudnn and exconv, fixed a bug in cudnn_conv in dealing with groups

* Make float equal works well.
  * compare 0.01 and 0.009999999999 will return true.

Change-Id: Ic80845c892c96c37a0df0ddc433fe1aeaa5a9d1c

out = w * input
where w is a parameter of size 1

Change-Id: Ife682d62323ceb1a20cbbf6269421b20a862d888

* Fix #436

Making '*' support the multiplication between a scalar and LayerOutput

Also changing '+' to support adding between a vector and a scalar.

Change-Id: I7daf35590dc2b2f855a29d9ef43ac57979442e0f

fail in hl_activetype; also fix the hasinputsset in submodel

* set mixedlayer output size according to input operator
* change from num_channel to num_channels for conv_operator (the old one is
really misleading because all the others are num_channels)

* also changed the arg name in projections.py

* some tiny fixs

* use VLOG(3)

And rebase

Change-Id: I7ea234b3aa8fc70675af15d91db08242c43fb5ff

This allows user to implement any type of cost by summing over the output of non-cost layers.

Change-Id: Ic55aaabbf0c1299e70b8e48a0effcc91f8f5bd29