fn dequantize_linear(self: @Tensor<Q>, x_scale: @Tensor<T>, x_zero_point: @Tensor<T>) -> Tensor::<T>;

Dequantizes a Tensor using linear dequantization.

The linear dequantization operator. It consumes a quantized tensor, a scale, and a zero point to compute the full precision tensor. The dequantization formula is y = (x - x_zero_point) * x_scale. x_scale and x_zero_point must have same shape, and can be either a scalar for per-tensor / per layer quantization, or a 1-D tensor for per-axis quantization.


  • self(@Tensor<Q>) - The input tensor.

  • x_scale(@Tensor<T>) - Scale for input x.

  • x_zero_point(@Tensor<T>) - Zero point for input x.


A new Tensor<T> with the same shape as the input tensor, containing the dequantized values.

Type Constraints

u32 tensor, not supported. fp8x23wide tensor, not supported. fp16x16wide tensor, not supported.


 use core::array::{ArrayTrait, SpanTrait};
 use orion::operators::tensor::{TensorTrait, Tensor, I8Tensor, I32Tensor};
 fn dequantize_linear_example() -> Tensor<i32> {
     // We instantiate a 1D Tensor here.
     let x = TensorTrait::<i8>::new(
         shape: array![4].span(),
         data: array![0, 3, 125, 127].span(),
     // We instantiate the x_scale here.
     let x_scale = TensorTrait::<i32>::new(
         shape: array![1].span(), data: array![2].span(),
     // We instantiate the x_zero_point here.
     let x_zero_point = TensorTrait::<i32>::new(
         shape: array![1].span(), data: array![0].span(),
     return x.dequantize_linear(@x_scale, @x_zero_point);
>>> [0, 6, 250, 254]

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