Vector API 快速访问链接

下表列出了向量API的函数。"EW"列指示操作是否逐元素执行。

"签名"列旨在快速传达操作的概念输入和输出的类型。这些签名仅旨在传达有多少（概念上的）输入和输出以及它们的维度。

这些函数本身通常需要比这些签名所示的更多的参数。例如，大多数函数接受向量长度作为输入，并且许多函数接受用于控制元素位深度增长的移位值。请查阅对应函数的完整文档以获取更详细的信息。

以下符号在签名中使用：

符号	描述
$\mathbb{S}$	标量输入或输出值。
$\mathbb{V}$	向量值输入或输出。
$\mathbb{M}$	矩阵值输入或输出。
$\varnothing$	占位符，表示无输入或输出。

例如，操作签名 $(\mathbb{V \times V \times S}) \to \mathbb{V}$ 表示该操作接受两个向量输入和一个标量输入，并且输出为一个向量。

• 32位向量操作
• 16位向量操作
• 8位向量操作
• 32位复数向量操作
• 16位复数向量操作
• 定点数向量操作
• 浮点数向量操作
• 其他向量操作
• 向量类型转换

32位向量操作

函数	EW	签名
vect_s32_copy()		$\mathbb{V} \to \mathbb{V}$
vect_s32_abs()	x	$\mathbb{V} \to \mathbb{V}$
vect_s32_abs_sum()		$\mathbb{V} \to \mathbb{S}$
vect_s32_add()	x	$(\mathbb{V} \times \mathbb{V}) \to \mathbb{V}$
vect_s32_add_scalar()	x	$(\mathbb{V} \times \mathbb{S}) \to \mathbb{V}$
vect_s32_argmax()		$\mathbb{V} \to \mathbb{S}$
vect_s32_argmin()		$\mathbb{V} \to \mathbb{S}$
vect_s32_clip()	x	$(\mathbb{V} \times \mathbb{S} \times \mathbb{S}) \to \mathbb{V}$
vect_s32_dot()		$(\mathbb{V} \times \mathbb{V}) \to \mathbb{S}$
vect_s32_energy()		$\mathbb{V} \to \mathbb{S}$
vect_s32_headroom()		$\mathbb{V} \to \mathbb{S}$
vect_s32_inverse()	x	$\mathbb{V} \to \mathbb{V}$
vect_s32_max()		$\mathbb{V} \to \mathbb{S}$
vect_s32_max_elementwise()	x	$(\mathbb{V} \times \mathbb{V}) \to \mathbb{V}$
vect_s32_min()		$\mathbb{V} \to \mathbb{S}$
vect_s32_min_elementwise()	x	$(\mathbb{V} \times \mathbb{V}) \to \mathbb{V}$
vect_s32_mul()	x	$(\mathbb{V} \times \mathbb{V}) \to \mathbb{V}$
vect_s32_macc()	x	$(\mathbb{V} \times \mathbb{V} \times \mathbb{V}) \to \mathbb{V}$
vect_s32_nmacc()	x	$(\mathbb{V} \times \mathbb{V} \times \mathbb{V}) \to \mathbb{V}$
vect_s32_rect()	x	$\mathbb{V} \to \mathbb{V}$
vect_s32_scale()	x	$(\mathbb{V} \times \mathbb{S}) \to \mathbb{V}$
vect_s32_set()	x	$\mathbb{S} \to \mathbb{V}$
vect_s32_shl()	x	$(\mathbb{V} \times \mathbb{S}) \to \mathbb{V}$
vect_s32_shr()	x	$(\mathbb{V} \times \mathbb{S}) \to \mathbb{V}$
vect_s32_sqrt()	x	$\mathbb{V} \to \mathbb{V}$
vect_s32_sub()	x	$(\mathbb{V} \times \mathbb{V}) \to \mathbb{V}$
vect_s32_sum()		$\mathbb{V} \to \mathbb{S}$
vect_s32_zip()		$(\mathbb{V} \times \mathbb{V}) \to \mathbb{V}$
vect_s32_unzip()		$\mathbb{V} \to (\mathbb{V} \times \mathbb{V})$
vect_s32_convolve_valid()		$(\mathbb{V} \times \mathbb{V}) \to \mathbb{V}$
vect_s32_convolve_same()		$(\mathbb{V} \times \mathbb{V}) \to \mathbb{V}$
vect_s32_log_base()	x	$(\mathbb{V} \times \mathbb{S}) \to \mathbb{V}$
vect_s32_log()	x	$\mathbb{V} \to \mathbb{V}$
vect_s32_log2()	x	$\mathbb{V} \to \mathbb{V}$
vect_s32_log10()	x	$\mathbb{V} \to \mathbb{V}$
chunk_s32_dot()		$(\mathbb{V} \times \mathbb{V}) \to \mathbb{S}$
chunk_s32_log()	x	$\mathbb{V} \to \mathbb{V}$

16位向量操作

函数	EW	签名
vect_s16_abs()	x	$\mathbb{V} \to \mathbb{V}$
vect_s16_abs_sum()		$\mathbb{V} \to \mathbb{S}$
vect_s16_add()	x	$(\mathbb{V} \times \mathbb{V}) \to \mathbb{V}$
vect_s16_add_scalar()	x	$(\mathbb{V} \times \mathbb{S}) \to \mathbb{V}$
vect_s16_argmax()		$\mathbb{V} \to \mathbb{S}$
vect_s16_argmin()		$\mathbb{V} \to \mathbb{S}$
vect_s16_clip()	x	$(\mathbb{V} \times \mathbb{S} \times \mathbb{S}) \to \mathbb{V}$
vect_s16_dot()		$(\mathbb{V} \times \mathbb{V}) \to \mathbb{S}$
vect_s16_energy()		$\mathbb{V} \to \mathbb{S}$
vect_s16_headroom()		$\mathbb{V} \to \mathbb{S}$
vect_s16_inverse()	x	$\mathbb{V} \to \mathbb{V}$
vect_s16_max()		$\mathbb{V} \to \mathbb{S}$
vect_s16_max_elementwise()	x	$(\mathbb{V} \times \mathbb{V}) \to \mathbb{V}$
vect_s16_min()		$\mathbb{V} \to \mathbb{S}$
vect_s16_min_elementwise()	x	$(\mathbb{V} \times \mathbb{V}) \to \mathbb{V}$
vect_s16_mul()	x	$(\mathbb{V} \times \mathbb{V}) \to \mathbb{V}$
vect_s16_macc()	x	$(\mathbb{V} \times \mathbb{V} \times \mathbb{V}) \to \mathbb{V}$
vect_s16_nmacc()	x	$(\mathbb{V} \times \mathbb{V} \times \mathbb{V}) \to \mathbb{V}$
vect_s16_rect()	x	$\mathbb{V} \to \mathbb{V}$
vect_s16_scale()	x	$(\mathbb{V} \times \mathbb{S}) \to \mathbb{V}$
vect_s16_set()	x	$\mathbb{S} \to \mathbb{V}$
vect_s16_shl()	x	$(\mathbb{V} \times \mathbb{S}) \to \mathbb{V}$
vect_s16_shr()	x	$(\mathbb{V} \times \mathbb{S}) \to \mathbb{V}$
vect_s16_sqrt()	x	$\mathbb{V} \to \mathbb{V}$
vect_s16_sub()	x	$(\mathbb{V} \times \mathbb{V}) \to \mathbb{V}$
vect_s16_sum()		$\mathbb{V} \to \mathbb{S}$
vect_s16_extract_high_byte()	x	$\mathbb{V} \to \mathbb{V}$
vect_s16_extract_low_byte()	x	$\mathbb{V} \to \mathbb{V}$

8位向量操作

函数	EW	签名	Brief
vect_s8_is_negative()	x	$\mathbb{V} \to \mathbb{V}$	Identify negative elements

32位复数向量操作

函数	EW	签名
vect_complex_s32_add()	x	$(\mathbb{V \times V}) \to \mathbb{V}$
vect_complex_s32_add_scalar()	x	$(\mathbb{V \times S}) \to \mathbb{V}$
vect_complex_s32_conj_macc()	x	$(\mathbb{V \times V \times V}) \to \mathbb{V}$
vect_complex_s32_conj_mul()	x	$(\mathbb{V \times V}) \to \mathbb{V}$
vect_complex_s32_conj_nmacc()	x	$(\mathbb{V \times V \times V}) \to \mathbb{V}$
vect_complex_s32_conjugate()	x	$\mathbb{V} \to \mathbb{V}$
vect_complex_s32_headroom()		$\mathbb{V} \to \mathbb{S}$
vect_complex_s32_macc()	x	$(\mathbb{V \times V \times V}) \to \mathbb{V}$
vect_complex_s32_mag()	x	$\mathbb{V} \to \mathbb{V}$
vect_complex_s32_mul()	x	$(\mathbb{V \times V}) \to \mathbb{V}$
vect_complex_s32_nmacc()	x	$(\mathbb{V \times V \times V}) \to \mathbb{V}$
vect_complex_s32_real_mul()	x	$(\mathbb{V \times V}) \to \mathbb{V}$
vect_complex_s32_real_scale()	x	$(\mathbb{V \times S}) \to \mathbb{V}$
vect_complex_s32_scale()	x	$(\mathbb{V \times S}) \to \mathbb{V}$
vect_complex_s32_set()	x	$\mathbb{S} \to \mathbb{V}$
vect_complex_s32_shl()	x	$(\mathbb{V \times S}) \to \mathbb{V}$
vect_complex_s32_shr()	x	$(\mathbb{V \times S}) \to \mathbb{V}$
vect_complex_s32_squared_mag()	x	$\mathbb{V} \to \mathbb{V}$
vect_complex_s32_sub()	x	$(\mathbb{V \times V}) \to \mathbb{V}$
vect_complex_s32_sum()		$\mathbb{V} \to \mathbb{S}$
vect_complex_s32_tail_reverse()		$\mathbb{V} \to \mathbb{V}$

16位复数向量操作

函数	EW	签名
vect_complex_s16_add()	x	$(\mathbb{V} \times \mathbb{V}) \to \mathbb{V}$
vect_complex_s16_add_scalar()	x	$(\mathbb{V} \times \mathbb{S}) \to \mathbb{V}$
vect_complex_s16_conj_mul()	x	$(\mathbb{V} \times \mathbb{V}) \to \mathbb{V}$
vect_complex_s16_conj_macc()	x	$(\mathbb{V} \times \mathbb{V} \times \mathbb{V}) \to \mathbb{V}$
vect_complex_s16_conj_nmacc()	x	$(\mathbb{V} \times \mathbb{V} \times \mathbb{V}) \to \mathbb{V}$
vect_complex_s16_headroom()		$\mathbb{V} \to \mathbb{S}$
vect_complex_s16_macc()	x	$(\mathbb{V} \times \mathbb{V} \times \mathbb{V}) \to \mathbb{V}$
vect_complex_s16_mag()	x	$\mathbb{V} \to \mathbb{V}$
vect_complex_s16_mul()	x	$(\mathbb{V} \times \mathbb{V}) \to \mathbb{V}$
vect_complex_s16_nmacc()	x	$(\mathbb{V} \times \mathbb{V} \times \mathbb{V}) \to \mathbb{V}$
vect_complex_s16_real_mul()	x	$(\mathbb{V} \times \mathbb{V}) \to \mathbb{V}$
vect_complex_s16_real_scale()	x	$(\mathbb{V} \times \mathbb{S}) \to \mathbb{V}$
vect_complex_s16_scale()	x	$(\mathbb{V} \times \mathbb{S}) \to \mathbb{V}$
vect_complex_s16_set()	x	$\mathbb{S} \to \mathbb{V}$
vect_complex_s16_shl()	x	$(\mathbb{V} \times \mathbb{S}) \to \mathbb{V}$
vect_complex_s16_shr()	x	$(\mathbb{V} \times \mathbb{S}) \to \mathbb{V}$
vect_complex_s16_squared_mag()	x	$\mathbb{V} \to \mathbb{V}$
vect_complex_s16_sub()	x	$(\mathbb{V} \times \mathbb{V}) \to \mathbb{V}$
vect_complex_s16_sum()		$\mathbb{V} \to \mathbb{S}$

定点数向量操作

函数	EW	签名
vect_q30_power_series()	x	$(\mathbb{V} \times \mathbb{V}) \to \mathbb{V}$
vect_q30_exp_small()	x	$\mathbb{V} \to \mathbb{V}$
chunk_q30_power_series()	x	$(\mathbb{V} \times \mathbb{V}) \to \mathbb{V}$
chunk_q30_exp_small()	x	$\mathbb{V} \to \mathbb{V}$

浮点数向量操作

函数	EW	签名
vect_f32_max_exponent()		$\mathbb{V} \to \mathbb{S}$
vect_f32_dot()		$(\mathbb{V} \times \mathbb{V}) \to \mathbb{S}$
vect_f32_add()	x	$(\mathbb{V} \times \mathbb{V}) \to \mathbb{V}$
vect_float_s32_log_base()	x	$(\mathbb{V} \times \mathbb{S}) \to \mathbb{V}$
vect_float_s32_log()	x	$\mathbb{V} \to \mathbb{V}$
vect_float_s32_log2()	x	$\mathbb{V} \to \mathbb{V}$
vect_float_s32_log10()	x	$\mathbb{V} \to \mathbb{V}$
chunk_float_s32_log()	x	$\mathbb{V} \to \mathbb{V}$
vect_complex_f32_add()	x	$(\mathbb{V} \times \mathbb{V}) \to \mathbb{V}$
vect_complex_f32_mul()	x	$(\mathbb{V} \times \mathbb{V}) \to \mathbb{V}$
vect_complex_f32_conj_mul()	x	$(\mathbb{V} \times \mathbb{V}) \to \mathbb{V}$
vect_complex_f32_macc()	x	$(\mathbb{V} \times \mathbb{V} \times \mathbb{V}) \to \mathbb{V}$
vect_complex_f32_conj_macc()	x	$(\mathbb{V} \times \mathbb{V} \times \mathbb{V}) \to \mathbb{V}$

Note that several of the functions below take vectors of the split_acc_s32_t type. This is a 32-bit vector type used for accumulating results of 8- or 16-bit operations in a manner optimized for the XS3 VPU.

其他向量操作

函数	EW	签名
vect_split_acc_s32_shr()	x	$(\mathbb{V} \times \mathbb{S}) \to \mathbb{V}$
vect_s32_merge_accs()	x	$\mathbb{V} \to \mathbb{V}$
vect_s32_split_accs()	x	$\mathbb{V} \to \mathbb{V}$
chunk_s16_accumulate()	x	$\mathbb{V} \to \mathbb{V}$
mat_mul_s8_x_s8_yield_s32()		$(\mathbb{M} \times \mathbb{V}) \to \mathbb{V}$
mat_mul_s8_x_s16_yield_s32()		$(\mathbb{M} \times \mathbb{V}) \to \mathbb{V}$

向量类型转换

函数	输入元素的类型	输出元素的类型
vect_s16_to_vect_s32()	int16_t	int32_t
vect_s32_to_vect_s16()	int32_t	int16_t
vect_s32_to_vect_f32()	int32_t	float
vect_f32_to_vect_s32()	float	int32_t
vect_complex_s16_to_vect_complex_s32()	complex_s16_t	complex_s32_t
vect_complex_s32_to_vect_complex_s16()	complex_s32_t	complex_s16_t