function sparseCategoricalCrossentropy(target, output, fromLogits) {
if (fromLogits === void 0) { fromLogits = false; }
var flatTarget = tfc.floor(flatten(target));
var outputShape = shape(output);
var oneHotTarget = reshape(tfc.oneHot(flatTarget, outputShape[outputShape.length - 1]), outputShape);
return categoricalCrossentropy(oneHotTarget, output, fromLogits);
}
function oneHot(indices, numClasses) {
if (ndim(indices) !== 1) {
throw new Error('Only 1D one-hot tensors are supported in the ' +
'deeplearn backend, at present.');
}
return tfc.oneHot(indices, numClasses);
}