func (c *clg) calculate(ctx spec.Context, informationSequence string) error {
// Check the calculated output against the provided expectation, if any. In
// case there is no expectation provided, we simply go with what we
// calculated. This then means we are probably not in a training situation.
expectation, ok := ctx.GetExpectation()
if !ok {
err := c.sendTextResponse(ctx, informationSequence)
if err != nil {
return maskAny(err)
}
return nil
}
// There is an expectation provided. Thus we are going to check the calculated
// output against it. In case the provided expectation does match the
// calculated result, we simply return it.
calculatedOutput := expectation.GetOutput()
if informationSequence == calculatedOutput {
err := c.sendTextResponse(ctx, informationSequence)
if err != nil {
return maskAny(err)
}
}
// The calculated output did not match the given expectation. That means we
// need to calculate some new output to match the given expectation. To do so
// we create a new network payload and assign the input CLG of the current CLG
// tree to it by queueing the new network payload in the underlying storage.
err := c.forwardNetworkPayload(ctx, informationSequence)
if err != nil {
return maskAny(err)
}
// The calculated output did not match the given expectation. We return an
// error to let the neural network know about it.
return maskAnyf(expectationNotMetError, "'%s' != '%s'", informationSequence, calculatedOutput)
}
