Function exportCNNModel

e2e/integration_tests/create_save_predict.js:91–120

(exportPath)

// Convolutional neural network (CNN).
async function exportCNNModel(exportPath) {
  const model = tfl.sequential();

  // Cover separable and non-separable convoluational layers.
  const inputShape = [40, 40, 3];
  model.add(tfl.layers.conv2d({
    filters: 32,
    kernelSize: [3, 3],
    strides: [2, 2],
    inputShape,
    padding: 'valid',
  }));
  model.add(tfl.layers.batchNormalization({}));
  model.add(tfl.layers.activation({activation: 'relu'}));
  model.add(tfl.layers.dropout({rate: 0.5}));
  model.add(tfl.layers.maxPooling2d({poolSize: 2}));
  model.add(tfl.layers.separableConv2d({
    filters: 32,
    kernelSize: [4, 4],
    strides: [3, 3],
  }));
  model.add(tfl.layers.batchNormalization({}));
  model.add(tfl.layers.activation({activation: 'relu'}));
  model.add(tfl.layers.dropout({rate: 0.5}));
  model.add(tfl.layers.avgPooling2d({poolSize: [2, 2]}));
  model.add(tfl.layers.flatten({}));
  model.add(tfl.layers.dense({units: 100, activation: 'softmax'}));

  await saveModelAndRandomInputs(model, exportPath);
}

async function exportDepthwiseCNNModel(exportPath) {
  const model = tfl.sequential();