Hi,
I have Convolutional layers, InnerProduct and Eltwise layers in my model. The caffe ouput and tidl outputs of the convolutional layer and innerproduct layers are matching. But in the elwise layer, some of the elements of the tidl matrix vary too much with the elements of caffe output.
For example, let's say Eltwise layer adds two blobs of size 1x5. Here is how the caffe and tidl output looks like:
Caffe output: [22.24 -2.33 -15.85 -14.89 -11.05]
TIDL output: [21.29 59.05 -15.00 -14.03 -10.16]
As you could see the [1] element vary too much.
To convert the data to floating point, I am dividing the output data by the OutQ in the logs as mentioned in this thread(e2e.ti.com/.../2370081
Regards,
Navinprashath.R.R
