Mkl Dnn Supports (WorkInProgress) #363
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…run on 2-D inputs.
1. backToUsr seg fault <- storage of Tensor will be set to 0. 2. validation accuracy is wrong <- hasConverted is set to true, but not set back to false because val has no backward. 3. Optimizer supports MklDnn.
Some issues: 1. the dnn version of SpatialBatchNormalization seems not working on VGG. It will not converge if we use it. 2. the dnn version of SpatialConvolution seems existing a bug, when the input width / height is less than kernel width. Details are not here.
1. Delete empty primitive when initlizing Concat layer because sum and split are not initlized after validation. 2. Random segment fault. Because it can't convert weight to mkl memory from scala array. We should convert it from mkl layout which is converted at updateOutput instead. 3. Make model threadpool to single thread, which will have much better performance on Inception or AlexNet. 4. Add AlexNet which was temporarily deleted. 5. Add offset to scaleShift in BatchNormalization. Because weight and bias does not start with 0 but an offset.
[fix] can not do serialization when save model (alexnet/inception) [fix] can not change batch size with linear and relu layers.
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