public class MnistDataSetIterator extends BaseDatasetIterator
batch, fetcher, numExamples, preProcessor
Constructor and Description |
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MnistDataSetIterator(int batchSize,
boolean train,
int seed)
Constructor to get the full MNIST data set (either test or train sets) without binarization (i.e., just normalization
into range of 0 to 1), with shuffling based on a random seed.
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MnistDataSetIterator(int batch,
int numExamples) |
MnistDataSetIterator(int batch,
int numExamples,
boolean binarize)
Get the specified number of examples for the MNIST training data set.
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MnistDataSetIterator(int batch,
int numExamples,
boolean binarize,
boolean train,
boolean shuffle,
long rngSeed)
Get the specified number of MNIST examples (test or train set), with optional shuffling and binarization.
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asyncSupported, batch, cursor, getLabels, hasNext, inputColumns, next, next, numExamples, remove, reset, resetSupported, setPreProcessor, totalExamples, totalOutcomes
clone, equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait
public MnistDataSetIterator(int batch, int numExamples) throws java.io.IOException
java.io.IOException
public MnistDataSetIterator(int batch, int numExamples, boolean binarize) throws java.io.IOException
batch
- the batch size of the examplesnumExamples
- the overall number of examplesbinarize
- whether to binarize mnist or notjava.io.IOException
public MnistDataSetIterator(int batchSize, boolean train, int seed) throws java.io.IOException
batchSize
- train
- java.io.IOException
public MnistDataSetIterator(int batch, int numExamples, boolean binarize, boolean train, boolean shuffle, long rngSeed) throws java.io.IOException
batch
- Size of each patchnumExamples
- total number of examples to loadbinarize
- whether to binarize the data or not (if false: normalize in range 0 to 1)train
- Train vs. test setshuffle
- whether to shuffle the examplesrngSeed
- random number generator seed to use when shuffling examplesjava.io.IOException