本文整理了Java中org.deeplearning4j.nn.multilayer.MultiLayerNetwork.setParams()方法的一些代码示例，展示了MultiLayerNetwork.setParams()的具体用法。这些代码示例主要来源于Github/Stackoverflow/Maven等平台，是从一些精选项目中提取出来的代码，具有较强的参考意义，能在一定程度帮忙到你。MultiLayerNetwork.setParams()方法的具体详情如下：
包路径：org.deeplearning4j.nn.multilayer.MultiLayerNetwork
类名称：MultiLayerNetwork
方法名：setParams

MultiLayerNetwork.setParams介绍

[英]Set the parameters for this model. This expects a linear ndarray which then be unpacked internally relative to the expected ordering of the model
[中]设置此模型的参数。这需要一个线性数组，然后根据模型的预期顺序在内部解包

代码示例

代码示例来源：origin: org.deeplearning4j/deeplearning4j-nn

/**
 * Sets parameters for the model.
 * This is used to manipulate the weights and biases across
 * all neuralNets (including the output layer)
 *
 * @param params a parameter vector equal 1,numParameters
 */
public void setParameters(INDArray params) {
  setParams(params);
}

代码示例来源：origin: org.deeplearning4j/deeplearning4j-scaleout-akka

@Override
  public void update(Object... o) {
    INDArray arr = (INDArray) o[0];
    multiLayerNetwork.setParams(arr);

  }
}

代码示例来源：origin: CampagneLaboratory/variationanalysis

} else {
  net.setUpdater(savedNet.getUpdater());
  net.setParams(savedNet.params());