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| Also, 'RoundLength' turns out to be 'the number of samples that is expected to be seen during a Round (epoch)', so it should be equal to the number of training samples, 'ntrain' in this case: trained = NetTrain[net, {genTrain,... |
| I think you should use a generator function, for example: enc = NetEncoder[{"Function", Flatten[IntegerDigits[#, 2, 8]] &, {192}}] b = ByteArray[Table[RandomInteger[{0, 255}], 10 * 24]] genTrain = Function[ArrayReshape[Normal[b[[1 ;;... |
| Hi, I have a dataset of 192 binary inputs (0/1) and corresponding outputs. I have compressed the inputs to 24 8-bit integers, so that the entire dataset can fit into RAM which greatly speeds up training of the neural network. Obviously, before a... |
| Please see [FunctionLayer error compilerr: Cannot interpret as a network][1] for a way to achieve this using NetEncoder. Regards, GW [1]: https://community.wolfram.com/groups/-/m/t/3096538 |
| Thank you! I modified your function to support the 24 8-bit integers expanding to 192 integers as follows: NetEncoder[{"Function", Flatten[IntegerDigits[#, 2, 8]] &, {192}}] and the following commands indeed produce the same output: ... |
| This is how Mathematica fundamentally works, if you input an exact quantity it will return an exact quantity. Since Erf[2] can not be simply written, it will leave it as is; the simplest way is Erf[2]. If you input a machine-precision number 2.0, it... |
| On my box running under OpenSUSE Leap 15.3, the CUDALink functionality in Mathematica 13.1.0.0 works fine with latest NVIDIA drivers (CUDADriverVersion[] returns "525.60.11") and NVIDIA CUDA Toolkit 11.8. |
| Hi, I want to use a custom LossFunction (in particular, a loss function that calculates the q'th percentile of the absolute differences), but I cannot figure out how to do this from the documentation. Through some educated guessing I found out... |
| Hi, I now see that I have not updated this question with the answer. It turned out that my input vectors were 'too random'. The use case was to train a neural network on a number of international draughts positions. If you choose a collection of... |
| When the net specified in LossFunction produces an array (not a scalar number), a SummationLayer[] is automatically added. So the total of the numbers in the output array is used as a loss. Thanks for spotting, we will add a note in the... |