Other functions need to quantization

These function are used to accelerate quantization algorithms in Synet Framework. More...

Functions
SIMD_API void	SimdSynetDequantizeLinear (const uint8_t *src, size_t size, int32_t bias, const float *norm, float *dst)
	Performs UINT8 linear dequantization. More...
SIMD_API void	SimdSynetQuantizeLinear (const float *src, size_t size, const float *norm, int32_t zero, uint8_t *dst)
	Performs UINT8 linear quantization. More...

Detailed Description

These function are used to accelerate quantization algorithms in Synet Framework.

Function Documentation

SimdSynetDequantizeLinear()

void SimdSynetDequantizeLinear	(	const uint8_t *	src,
		size_t	size,
		int32_t	bias,
		const float *	norm,
		float *	dst
	)

Performs UINT8 linear dequantization.

Algorithm's details for SimdSynetDequantizeLinear:

for(i = 0; i < size; ++i)
    dst[i] = (src[i] + bias) * norm[0];

Parameters

[in]	src	- a pointer to UINT8 input tensor.
[in]	size	- a size of the input and output tensors.
[in]	bias	- a dequantization bias (-zero).
[in]	norm	- a dequantization norm (scale).
[out]	dst	- a pointer to FP32 output tensor.

SimdSynetQuantizeLinear()

void SimdSynetQuantizeLinear	(	const float *	src,
		size_t	size,
		const float *	norm,
		int32_t	zero,
		uint8_t *	dst
	)

Performs UINT8 linear quantization.

Algorithm's details for SimdSynetQuantizeLinear:

for(i = 0; i < size; ++i)
    dst[i] = Min(Max(std::nearbyint(src[i] * scale[0]) + zero), 0), 255);

Parameters

[in]	src	- a pointer to FP32 input tensor.
[in]	size	- a size of the input and output tensors.
[in]	norm	- a quantization norm (1/scale).
[in]	zero	- a quantization zero.
[out]	dst	- a pointer to UINT8 output tensor.