* wip: layer normalization on cpu
* wip: add cuda implementation, nor working yet
* wip: try to fix cuda implementation
* swap grid_strid_range and grid_strid_range_y: does not work yet
* fix CUDA implementation
* implement cuda gradient
* add documentation, move layer_norm, update bn_visitor
* add tests
* use stddev instead of variance in test (they are both 1, anyway)
* add test for means and invstds on CPU and CUDA
* rename visitor to disable_duplicative_bias
* handle more cases in the visitor_disable_input_bias
* Add tests for visitor_disable_input_bias
* add visitor to remove bias from bn_ inputs (#closes 2155)
* remove unused parameter and make documentation more clear
* remove bias from bn_ layers too and use better name
* let the batch norm keep their bias, use even better name
* be more consistent with impl naming
* remove default constructor
* do not use method to prevent some errors
* add disable bias method to pertinent layers
* update dcgan example
- grammar
- print number of network parameters to be able to check bias is not allocated
- at the end, give feedback to the user about what the discriminator thinks about each generated sample
* fix fc_ logic
* add documentation
* add bias_is_disabled methods and update to_xml
* print use_bias=false when bias is disabled
* fix some warnings when running tests
* rever changes in CMakeLists.txt
* update example make use of newly promoted method
* update tests to make use of newly promoted methods
* wip: dcgan-example
* wip: dcgan-example
* update example to use leaky_relu and remove bias from net
* wip
* it works!
* add more comments
* add visualization code
* add example documentation
* rename example
* fix comment
* better comment format
* fix the noise generator seed
* add message to hit enter for image generation
* fix srand, too
* add std::vector overload to update_parameters
* improve training stability
* better naming of variables
make sure it is clear we update the generator with the discriminator's
gradient using fake samples and true labels
* fix comment: generator -> discriminator
* update leaky_relu docs to match the relu ones
* replace not with !
* add Davis' suggestions to make training more stable
* use tensor instead of resizable_tensor
* do not use dnn_trainer for discriminator
