Last updated
Last updated
Performs the sum of quantized Tensors
It consumes two quantized input tensors, their scales and zero points, scale and zero point of output, and computes the quantized output. The quantization formula is y = saturate((x / y_scale) + y_zero_point). It performs the addition of the two vectors once dequantized, then return the quantization of the result of the addition. The broadcasting is supported Scale and zero point must have same shape and the same type. They must be either scalar (per tensor) or N-D tensor (per row for 'a' and per column for 'b'). Scalar refers to per tensor quantization whereas N-D refers to per row or per column quantization.
self
(@Tensor<i8>
) - The first tensor to be additionned (a).
a_scale
(@Tensor<T>
) - Scale for input a
.
a_zero_point
(@Tensor<T>
) - Zero point for input a
.
b
(@Tensor<i8>
) - The second tensor to be additionned
b_scale
(@Tensor<T>
) - Scale for input b
.
b_zero_point
(@Tensor<T>
) - Zero point for input b
.
y_scale
(@Tensor<T>
) - Scale for outut.
y_zero_point
(@Tensor<T>
) - Zero point for output.
A new Tensor<i8>
, containing the quantized result of the addition of the dequantized inputs.
u32 tensor, not supported. fp8x23wide tensor, not supported. fp16x16wide tensor, not supported.