tensor.qlinear_leakyrelu

    fn qlinear_leakyrelu(self: @Tensor<i8>, a_scale: @Tensor<T>, a_zero_point: @Tensor<T>, alpha: T) -> Tensor::<i8>;

Applies the Leaky Relu operator to a quantized Tensor

QLinar LeakyRelu takes as input a quantized Tensor, its scale and zero point and an scalar alpha, and produces one output data (a quantized Tensor) where the function f(x) = alpha * x for x < 0, f(x) = x for x >= 0, is applied to the data tensor elementwise. The quantization formula is y = saturate((x / y_scale) + y_zero_point). 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.

Args

  • self(@Tensor<i8>) - The first tensor to be multiplied (a).

  • a_scale(@Tensor<T>) - Scale for input a.

  • a_zero_point(@Tensor<T>) - Zero point for input a.

  • alpha(T) - The factor multiplied to negative elements.

Returns

A new Tensor<i8>, containing result of the Leaky Relu.

Type Constraints

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

Example

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