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Correct format for NetChain?

Lenny Johnson
Posted 8 years ago
POSTED BY: Lenny Johnson
6 Replies
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POSTED BY: Kotaro Okazaki
Lenny Johnson
Lenny Johnson
Posted 8 years ago
POSTED BY: Lenny Johnson

This net does not have an explicit loss function, so a loss function will be chosen automatically based on the final layer or layers in the net.

The Details and Options of CrossEntropyLossLayer Help say,

When appropriate, CrossEntropyLossLayer is automatically used by NetTrain if an explicit loss specification is not provided. One of "Binary", "Probabilities", or "Index" will be chosen based on the final activation used for the output port and the form of any attached NetDecoder.

and

For CrossEntropyLossLayer["Index"], the input should be a vector of probabilities {p1,...,pc} that sums to 1, or a tensor of such vectors. The target should be an integer between 1 and c, or a tensor of such integers."

So, I think this net needs SoftmaxLayer for NetTrain.
POSTED BY: Kotaro Okazaki
Lenny Johnson
Lenny Johnson
Posted 8 years ago

That seems like a plausible explanation. The answer is in the details.

Thank you.
POSTED BY: Lenny Johnson

Your NetChain outputs a vector of length 30, and you are trying to feed this into a NetDecoder that expecting only 10 inputs. Hence the error. So something like this will work:

NetChain[{LinearLayer[10]}, 
 "Input" -> NetEncoder[{"Image", {28, 28}, "Grayscale"}], 
 "Output" -> NetDecoder[{"Class", Range[0, 9]}]]
POSTED BY: Sebastian Bodenstein
Lenny Johnson
Lenny Johnson
Posted 8 years ago

Thanks. I had misinterpreted the Output decoder as actually creating an output layer. Using the above network seems to generating an error when attempting to train the network. 

testNet =NetChain[{LinearLayer[10]}, 
 "Input" -> NetEncoder[{"Image", {28, 28}, "Grayscale"}], 
 "Output" -> NetDecoder[{"Class", Range[0, 9]}]]

enter image description here

myResource = ResourceObject["MNIST"];
trainingData = ResourceData[myResource, "TrainingData"];
testData = ResourceData[myResource."TestData"];
testNet = NetInitialize[testNet]

enter image description here

trainedNet = 
 NetTrain[testNet, trainingData, BatchSize -> 1000, 
  MaxTrainingRounds -> 1]

This generates the error...

NetTrain::invindim: Data provided to port "Output" should be a list of length-10 vectors.

A simple validation to check if the net is receiving data and output an expected type appears correct.

testNet[Keys[trainingData[[1]]]]
1

Obviously the network is not trained so the output digit may be incorrect but it is a scalar in our range 0-9.

Do you have any ideas why the it believes the output data is not of the correct length?
POSTED BY: Lenny Johnson
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