function residualDown(x, params) {
var out = convLayer_1.convDown(x, params.conv1);
out = convLayer_1.convNoRelu(out, params.conv2);
var pooled = tf.avgPool(x, 2, 2, 'valid');
var zeros = tf.zeros(pooled.shape);
var isPad = pooled.shape[3] !== out.shape[3];
var isAdjustShape = pooled.shape[1] !== out.shape[1] || pooled.shape[2] !== out.shape[2];
if (isAdjustShape) {
var padShapeX = out.shape.slice();
padShapeX[1] = 1;
var zerosW = tf.zeros(padShapeX);
out = tf.concat([out, zerosW], 1);
var padShapeY = out.shape.slice();
padShapeY[2] = 1;
var zerosH = tf.zeros(padShapeY);
out = tf.concat([out, zerosH], 2);
}
pooled = isPad ? tf.concat([pooled, zeros], 3) : pooled;
out = tf.add(pooled, out);
out = tf.relu(out);
return out;
}
function zeros(shape, dtype) {
return tfc.zeros(shape);
}