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DL4J: Add validation for invalid evaluation #6735

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AlexDBlack opened this issue Nov 19, 2018 · 2 comments

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@AlexDBlack
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commented Nov 19, 2018

Example: User tries to perform classification evaluation on a regression model.
We should provide a useful exception, not some obscure exception, and not silently perform the evaluation (unless an exception occurs).

For example, we can look at the output layer configuration to determine if it's classification or regression.

@AlexDBlack AlexDBlack added the DL4J label Nov 19, 2018

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commented Nov 22, 2018

Another place where we can do a similar check: predict etc methods that assume a probability distribution (i.e., incorrectly using predict etc for regression).

AlexDBlack added a commit that referenced this issue Nov 27, 2018
AlexDBlack added a commit that referenced this issue Nov 27, 2018
Misc DL4J/ND4J fixes (#6774)
* #6770 Fix issue with incorrect EWS for TAD resulting in column vectors

* #6748 Add NaN checks in evaluation

* #6735 Add validation for invalid evaluation

* #6734 Fix ComputationGraph layer name inference from param name (get/setParam etc methods)

* #6736 additional CompGraph output overload

* Add commit() in ParallelInference

* Small fix

* put commit() in proper location

* Layer config cloning should clone INDArray fields to avoid excessive relocation issues on CUDA

* ParallelInference: Add commit before passing input array(s) between threads

* Trigger CI
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commented Dec 28, 2018

This thread has been automatically locked since there has not been any recent activity after it was closed. Please open a new issue for related bugs.

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