Dl4j-fit(DataSetIterator iterator)研究（四） dropout
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前向传播过程的核心内容即为preOut这一部分所体现的网络模型运行机制。
public INDArray preOutput(boolean training) {
applyDropOutIfNecessary(training);
INDArray b = getParam(DefaultParamInitializer.BIAS_KEY);
INDArray W = getParam(DefaultParamInitializer.WEIGHT_KEY);
//Input validation:
if (input.rank() != 2 || input.columns() != W.rows()) {
if (input.rank() != 2) {
throw new DL4JInvalidInputException("Input that is not a matrix; expected matrix (rank 2), got rank "
+ input.rank() + " array with shape " + Arrays.toString(input.shape()));全部评论 (0)
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