Dynamic quantization of neural networks
AssigneeIntel Corporation
InventorMichael E. Deisher
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Abstract
An apparatus for applying dynamic quantization of a neural network is described herein. The apparatus includes a scaling unit and a quantizing unit. The scaling unit is to calculate an initial desired scale factors of a plurality of inputs, weights and a bias and apply the input scale factor to a summation node. Also, the scaling unit is to determine a scale factor for a multiplication node based on the desired scale factors of the inputs and select a scale factor for an activation function and an output node. The quantizing unit is to dynamically requantize the neural network by traversing a graph of the neural network.
Claims20
At least one non-transitory computer readable medium comprising instructions to cause at least one processor circuit to at least:
- determine a scale factor based on a maximum value over a window of past first values;
- train a neural network based on second values scaled by the scale factor;
- and
- quantize respective ones of the scaled second values.
An apparatus comprising:
- interface circuitry;
- computer-readable instructions;
- and
- programmable circuitry to at least one of instantiate or execute the computer-readable instructions to at least:
- determine a scale factor based on a maximum value over a window of past first values;
- train a neural network based on a plurality of second values scaled by the scale factor;
- and
- quantize respective ones of the scaled second values.
A method comprising:
- determining a scale factor based on a maximum value over a window of past first values;
- training a neural network based on a plurality of second values scaled by the scale factor;
- and
- quantizing respective ones of the plurality of scaled second values.
Dependencies are inferred from the claim text.