com.microsoft - QLinearAdd#
QLinearAdd - 1 (com.microsoft)#
Version
name: QLinearAdd (GitHub)
domain: com.microsoft
since_version: 1
function:
support_level:
shape inference:
This version of the operator has been available since version 1 of domain com.microsoft.
Summary
Performs element-wise binary addition on 8 bit data types (with Numpy-style broadcasting support).
C = (A_scale * (A - A_zero_point) + B_scale * (B - B_zero_point))/C_scale + C_zero_point
Inputs
Between 7 and 8 inputs.
A (heterogeneous) - T: First operand.
A_scale (heterogeneous) - tensor(float): Input A’s scale. It’s a scalar, which means a per-tensor/layer quantization.
A_zero_point (optional, heterogeneous) - T: Input A zero point. Default value is 0 if it’s not specified. It’s a scalar, which means a per-tensor/layer quantization.
B (heterogeneous) - T: Second operand.
B_scale (heterogeneous) - tensor(float): Input B’s scale. It’s a scalar, which means a per-tensor/layer quantization.
B_zero_point (optional, heterogeneous) - T: Input B zero point. Default value is 0 if it’s not specified. It’s a scalar, which means a per-tensor/layer quantization.
C_scale (heterogeneous) - tensor(float): Output scale. It’s a scalar, which means a per-tensor/layer quantization.
C_zero_point (optional, heterogeneous) - T: Output zero point. Default value is 0 if it’s not specified. It’s a scalar, which means a per-tensor/layer quantization.
Outputs
C (heterogeneous) - T: Result, has same element type as two inputs
Examples