- Specify a different execution environment that does not require a partitionable datastore.
- Create a custom partitionable datastore. If you need to create a custom datastore that supports parallel or multi-GPU training, then your datastore must implement the "matlab.io.datastore.Partitionable" class.
Why am I getting an error saying my Datastore is not shuffable?
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MathWorks Support Team
on 19 May 2020
Answered: MathWorks Support Team
on 8 Dec 2020
Why am I getting an error saying my Datastore is not shuffable?
Warning: Input datastore is not shuffleable but trainingOptions specified shuffling. Training will proceed without shuffling.
Error using nnet.internal.cnn.GeneralDatastoreDispatcher.splitDatastore (line 501)
The input datastore is not Partitionable and does not support parallel operations.
Accepted Answer
MathWorks Support Team
on 19 May 2020
If you specify the "ExecutionEnvironment" in "trainingOptions" for a deep network to be "multiple-gpu" or another form of parallel processing, then it requires the underlying datastore to be partitionable. Most datastores are partitionable, but if you use the "combine" function, this may result in a new datastore that is not partitionable. There are two "solutions" to running into this error:
You can check if a datastore is partitionable using the function "ispartitionable".
For more information on using parallel computing with datastores, please also refer to the following page:
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