Efficient use of quantization parameters in machine-learning models for video coding

An apparatus for encoding an image block using a quantization parameter, comprising:

• a processor that:
• calculates a non-linear value of the quantization parameter using the quantization parameter as an input to a non-linear function, wherein the non-linear function is similar to a function of the quantization parameter that is used to calculate a Lagrange multiplier that is used in a rate-distortion calculation;
• presents, to a machine-learning model, the image block and the non-linear value, wherein the machine-learning model is trained to output mode decision parameters for encoding the image block;
• obtains the mode decision parameters from the machine-learning model;
• and
• encodes, in a compressed bitstream, the image block using the mode decision parameters indicative of a quad-tree partitioning of the image block.

A method for decoding an image block, comprising:

• receiving, in a compressed bitstream, an indication of a quad-tree partitioning of the image block into sub-blocks, wherein an encoder determined the quad-tree partitioning of the image block using a machine-learning model that is trained by:
• using training data as inputs to train the machine-learning model, each training datum includes
• a training block,
• mode decision parameters used for encoding the training block, and
• a non-linear value that is derived by using a quantization parameter as input to a non-linear function,
• wherein the quantization parameter is used for encoding the training block,
• and
• wherein the non-linear function relates to a function used to calculate, using the quantization parameter, a multiplier that is used in a rate-distortion calculation;
• and
• decoding the image block using the indication of the quad-tree partitioning of the image block.