Select

Applicability

Product	Supported
Atlas 350 Accelerator Card	√
Atlas A3 training product / Atlas A3 inference product	√
Atlas A2 training product / Atlas A2 inference product	√
Atlas 200I/500 A2 inference product	√
Atlas inference product AI Core	√
Atlas inference product Vector Core	x
Atlas training product	√

Function Usage

Selects elements from two source operands src0 and src1 based on bit values of selMask (the selection mask) to generate the destination operand dst. When a bit value of selMask is 1, the elements are selected from src0. When a bit value of selMask is 0, the elements are selected from src1.

For high-dimensional tensor sharding computation APIs, the selection results can be filtered again based on the mask parameter. Valid-bit elements update dst and invalid-bit elements preserve its original values. For example, src0 is [1,2,3,4,5,6,7,8], src1 is [9,10,11,12,13,14,15,16], selMask is [0,0,0,0,1,1,1,1], mask is [1,1,1,1,0,0,0,0], and the original dst is [-1,-2,-3,-4,-5,-6,-7,-8]. After bitwise selection based on selMask, dst_temp is [9,10,11,12,5,6,7,8]. The final dst filtered by mask is [9,10,11,12,-5,-6,-7,-8].

This function supports the following modes:

Mode 0: Elements are selected from two tensors based on selMask. The number of valid bits in selMask is restricted by the data type of the source operands. In each iteration, selection is performed based on the valid bits of selMask. The same valid bits of selMask are applied in each iteration.
Mode 1: Elements are selected from either a tensor or a scalar based on selMask. The number of valid bits in selMask is not restricted. In multiple iterations, different parts of selMask are used consecutively in each iteration.
Mode 2: Elements are selected from two tensors based on selMask. The number of valid bits in selMask is not restricted. In multiple iterations, different parts of selMask are used consecutively in each iteration.

Atlas training product : Only mode 0 is supported.

Atlas inference product AI Core: Modes 0, 1, and 2 are supported.

Atlas A2 training product / Atlas A2 inference product : Modes 0, 1, and 2 are supported.

Atlas A3 training product / Atlas A3 inference product : Modes 0, 1, and 2 are supported.

Atlas 200I/500 A2 inference product : Modes 0, 1, and 2 are supported.

Atlas 350 Accelerator Card: Modes 0, 1, and 2 are supported.

Prototype

Computation of the first n pieces of data of a tensor

Selection mode 1

          
               template <typename T, typename U>
__aicore__ inline void Select(const LocalTensor<T>& dst, const LocalTensor<U>& selMask, const LocalTensor<T>& src0, T src1, SELMODE selMode, uint32_t count)

Selection modes 0 and 2

          
               template <typename T, typename U>
__aicore__ inline void Select(const LocalTensor<T>& dst, const LocalTensor<U>& selMask, const LocalTensor<T>& src0, const LocalTensor<T>& src1, SELMODE selMode, uint32_t count)

High-dimensional tensor sharding computation

Selection mode 1

Bitwise mask mode

            
                 template <typename T, typename U, bool isSetMask = true>
__aicore__ inline void Select(const LocalTensor<T>& dst, const LocalTensor<U>& selMask, const LocalTensor<T>& src0, T src1, SELMODE selMode, uint64_t mask[], uint8_t repeatTime, const BinaryRepeatParams& repeatParams)

Contiguous mask mode

            
                 template <typename T, typename U, bool isSetMask = true>
__aicore__ inline void Select(const LocalTensor<T>& dst, const LocalTensor<U>& selMask, const LocalTensor<T>& src0, T src1, SELMODE selMode, uint64_t mask, uint8_t repeatTime, const BinaryRepeatParams& repeatParams)

The mask parameter is not specified. (In this case, this API must be used together with SetVectorMask and SetCmpMask (ISASI).)

            
                 template <typename T, typename U>
__aicore__ inline void Select(const LocalTensor<T>& dst, const LocalTensor<U>& selMask, const LocalTensor<T>& src0, uint8_t repeatTime, const BinaryRepeatParams& repeatParams)

Selection modes 0 and 2

Bitwise mask mode

            
                 template <typename T, typename U, bool isSetMask = true>
__aicore__ inline void Select(const LocalTensor<T>& dst, const LocalTensor<U>& selMask, const LocalTensor<T>& src0, const LocalTensor<T>& src1, SELMODE selMode, uint64_t mask[],  uint8_t repeatTime, const BinaryRepeatParams& repeatParams)

Contiguous mask mode

            
                 template <typename T, typename U, bool isSetMask = true>
__aicore__ inline void Select(const LocalTensor<T>& dst, const LocalTensor<U>& selMask, const LocalTensor<T>& src0, const LocalTensor<T>& src1, SELMODE selMode, uint64_t mask, uint8_t repeatTime, const BinaryRepeatParams& repeatParams)

The mask parameter is not specified. (In this case, this API must be used together with SetVectorMask and SetCmpMask (ISASI).)

            
                 template <typename T, SELMODE selMode>
__aicore__ inline void Select(const LocalTensor<T>& dst, const LocalTensor<T>& src0, const LocalTensor<T>& src1, uint8_t repeatTime, const BinaryRepeatParams& repeatParams)

Parameters

**Table 1** Template parameters
Parameter	Meaning
T	Data type of the source and destination operands.
U	Data type of selMask.
isSetMask	Reserved. Retain the default value. To set mask outside the API, call an API that does not require the mask parameter.
selMode	For details, see the description of the selMode parameter in Table2 Parameters.

Table 2 Parameters

Parameter

Input/Output

Meaning

dst

Output

Destination operand.

The type is LocalTensor, and TPosition can be VECIN, VECCALC, or VECOUT.

The start address of LocalTensor must be 32-byte aligned.

For the Atlas training product , the supported data types are half and float.

For the Atlas inference product AI Core, the supported data types are half and float.

For the Atlas A2 training product / Atlas A2 inference product , the supported data types are half and float.

For the Atlas A3 training product / Atlas A3 inference product , the supported data types are half and float.

For the Atlas 200I/500 A2 inference product , the supported data types are half and float.

For the Atlas 350 Accelerator Card, the supported data types are int8_t, uint8_t, int16_t, uint16_t, half, bfloat16_t, float, int32_t, uint32_t, complex32, int64_t, uint64_t, and complex64.

selMask

Input

Mask used for element selection.

The type is LocalTensor, and TPosition can be VECIN, VECCALC, or VECOUT.

The start address of LocalTensor must be 32-byte aligned.

The supported data types are uint8_t, uint16_t, uint32_t, and uint64_t.

Each bit represents the selection of one element. When a bit in selMask is 1, the element is selected from src0. When the bit is 0, the element is selected from src1.

When selMode is set to mode 0, in each iteration, selection is performed based on the valid bits of selMask. The selMask applied in every iteration remains identical, using the same valid value of selMask. If selMode is set to mode 1 or mode 2, different parts of selMask are used consecutively in each iteration.

Mode 0: Elements are selected from two tensors based on selMask. Each iteration selects elements based on the fixed truncated bit-length of selMask, regardless of the number of iterations. The number of valid bits in selMask is limited to 256/sizeof(T).
Mode 1: Elements are selected from either a tensor or a scalar based on selMask. selMask is stored continuously. In each iteration, the number of selMask bits used is 256/sizeof(T).
Mode 2: Elements are selected from two tensors based on selMask. selMask is stored continuously. In each iteration, the number of selMask bits used is 256/sizeof(T).

src0

Input

Source operand.

The type is LocalTensor, and TPosition can be VECIN, VECCALC, or VECOUT.

The start address of LocalTensor must be 32-byte aligned.

For the Atlas training product , the supported data types are half and float.

For the Atlas inference product AI Core, the supported data types are half and float.

For the Atlas A2 training product / Atlas A2 inference product , the supported data types are half and float.

For the Atlas 200I/500 A2 inference product , the supported data types are half and float.

For the Atlas 350 Accelerator Card, the supported data types are int8_t, uint8_t, int16_t, uint16_t, half, bfloat16_t, float, int32_t, uint32_t, complex32, int64_t, uint64_t, and complex64.

src1

Input

Source operand.

When selMode is set to mode 0 or mode 2:
The type is LocalTensor, and TPosition can be VECIN, VECCALC, or VECOUT.

The start address of LocalTensor must be 32-byte aligned.

When selMode is set to mode 1, the type is T (scalar).

For the Atlas training product , the supported data types are half and float.

For the Atlas inference product AI Core, the supported data types are half and float.

For the Atlas A2 training product / Atlas A2 inference product , the supported data types are half and float.

For the Atlas A3 training product / Atlas A3 inference product , the supported data types are half and float.

For the Atlas 200I/500 A2 inference product , the supported data types are half and float.

For the Atlas 350 Accelerator Card, the supported data types are int8_t, uint8_t, int16_t, uint16_t, half, bfloat16_t, float, int32_t, uint32_t, complex32, int64_t, uint64_t, and complex64.

selMode

Input

Instruction mode (selection mode). The values are as follows:

           
                enum class SELMODE : uint8_t {
    VSEL_CMPMASK_SPR = 0, 
    VSEL_TENSOR_SCALAR_MODE,
    VSEL_TENSOR_TENSOR_MODE,
};

Mode 0: The value is VSEL_CMPMASK_SPR. Elements are selected from two tensors based on selMask. The number of valid bits in selMask is restricted by the data type of the source operands. In each iteration, selection is performed based on the valid bits of selMask. The same valid bits of selMask are applied in each iteration.
Mode 1: The value is VSEL_TENSOR_SCALAR_MODE. Elements are selected from either a tensor or a scalar based on selMask. The number of valid bits in selMask is not restricted. In multiple iterations, different parts of selMask are used consecutively in each iteration.
Mode 2: The value is VSEL_TENSOR_TENSOR_MODE. Elements are selected from two tensors based on selMask. The number of valid bits in selMask is not restricted. In multiple iterations, different parts of selMask are used consecutively in each iteration.

mask/mask[]

Input

mask controls the elements that participate in computation in each iteration.

Bitwise mode: controls the elements that participate in computation by bit. If a bit is set to 1, the corresponding element participates in the computation. If a bit is set to 0, the corresponding element is masked from the computation.
The mask value is an array. The array length and the value range of the array elements are related to the operand data type. When the operand is 16-bit, the array length is 2, with mask[0] and mask[1] each in the range [0, 2⁶⁴ – 1], and they cannot both be 0 at the same time. When the operand is 32-bit, the array length is 1, with mask[0] in the range (0, 2⁶⁴ – 1]. When the operand is 64-bit, the array length is 1, with mask[0] in the range (0, 2³² – 1].

For example, if mask = [0, 8] and 8 = 0b1000, only the fourth element participates in computation.

Contiguous mode: indicates the number of contiguous elements that participate in computation. The value range is related to the operand data type. The maximum number of elements that can be processed in each iteration varies according to the data type. When the operand is 16-bit, mask ∈ [1, 128]. When the operand is 32-bit, mask ∈ [1, 64]. When the operand is 64-bit, mask ∈ [1, 32].

repeatTime

Input

Number of iteration repeats. The Vector Unit reads 256 bytes of contiguous data for computation each time. To read the complete data for processing, the unit needs to read the input data in multiple repeats. repeatTime indicates the number of iterations.

For details about this parameter, see High-dimensional Sharding APIs.

repeatParams

Input

Parameters that control the operand address strides. They are of the BinaryRepeatParams type, and contain such parameters as those that specify the address stride of the operand for the same data block between adjacent iterations and address stride of the operand between different data blocks in a single iteration.

For details about the address stride of the operand between adjacent iterations, see repeatStride. For details about the address stride of the operand between different data blocks in a single iteration, see dataBlockStride.

count

Input

Number of elements involved in the computation.

Returns

None

Restrictions

For details about the operand address alignment requirements, see General Address Alignment Restrictions.
For details about the constraints on operand address overlapping, see General Address Overlapping Restrictions.

For the Atlas A2 training product / Atlas A2 inference product , in mode 1 and mode 2, reserve an 8 KB Unified Buffer as the immediate data storage of the API.
For the Atlas A3 training product / Atlas A3 inference product , in mode 1 and mode 2, reserve an 8 KB Unified Buffer as the immediate data storage of the API.
For the Atlas inference product AI Core, in mode 1 and mode 2, reserve an 8 KB Unified Buffer as the immediate data storage of the API.
For the Atlas 350 Accelerator Card, int8_t, uint8_t, uint64_t, int64_t, complex32, and complex64 support only the APIs that compute the first n pieces of data in a tensor.

Examples

These examples show only part of the code used in the computation.

Example of Select - high-dimensional tensor sharding computation (mode 2)

        
             uint64_t mask = 256/sizeof(float);
int repeat = 4;
AscendC::BinaryRepeatParams repeatParams = { 1, 1, 1, 8, 8, 8 };
// repeat = 4, 64 elements one repeat, 256 elements total
// dstBlkStride, src0BlkStride, src1BlkStride = 1, no gap between blocks in one repeat
// dstRepStride, src0RepStride, src1RepStride = 8, no gap between repeats
AscendC::Select(dstLocal, maskLocal, src0Local, src1Local, AscendC::SELMODE::VSEL_TENSOR_TENSOR_MODE, mask, repeat, repeatParams);

Example of Select - first n pieces of tensor data computation (mode 1)

        
             AscendC::Select(dstLocal, maskLocal, src0Local, static_cast<float>(0), AscendC::SELMODE::VSEL_TENSOR_SCALAR_MODE, dataSize);

Select - first n pieces of tensor data computation sample (Mode 0: In each repeat, only the first 64 bits of maskLocal are valid.)

        
             AscendC::Select(dstLocal, maskLocal, src0Local, src1Local, AscendC::SELMODE::VSEL_CMPMASK_SPR, dataSize);

Select - high-dimensional tensor sharding computation sample - contiguous mask mode (Mode 0: In each repeat, only the first 64 bits of maskLocal are valid.)

        
             uint64_t mask = 256/sizeof(float);
int repeat = 4;
AscendC::BinaryRepeatParams repeatParams = { 1, 1, 1, 8, 8, 8 };
// repeat = 4, 64 elements one repeat, 256 elements total
// dstBlkStride, src0BlkStride, src1BlkStride = 1, no gap between blocks in one repeat
// dstRepStride, src0RepStride, src1RepStride = 8, no gap between repeats
AscendC::Select(dstLocal, maskLocal, src0Local, src1Local, AscendC::SELMODE::VSEL_CMPMASK_SPR, mask, repeat, repeatParams);

Select - high-dimensional tensor sharding computation sample - bitwise mask mode (In each repeat, only the first 64 bits of maskLocal are valid.)

        
             uint64_t mask[2] = { UINT64_MAX, 0};
int repeat = 4;
AscendC::BinaryRepeatParams repeatParams = { 1, 1, 1, 8, 8, 8 };
// repeat = 4, 64 elements one repeat, 256 elements total
// srcBlkStride, = 1, no gap between blocks in one repeat
// dstRepStride, srcRepStride = 8, no gap between repeats
AscendC::Select(dstLocal, maskLocal, src0Local, src1Local, AscendC::SELMODE::VSEL_CMPMASK_SPR, mask, repeat, repeatParams);

Result example:

Example of mode 2:

Input (src0Local):
[-80.4933, 52.2499, -50.6124, -72.3737, -33.7107, -83.4001, 34.3954, 61.3188, 96.5484, 27.1321, -56.8153, 9.80549, 9.11199, -53.1848, -77.2548, -0.0681466, -69.5783, 6.53722, -22.5986, 37.6655, -25.4146, 89.232, 55.4716, 21.6069, 23.0464, 28.5975, -46.3033, 50.0312, -42.6339, 41.8752, -87.0426, 37.9717, 10.4336, 10.7653, -30.6943, -65.4774, 8.38653, -89.6462, 65.1115, 42.2134, -91.1666, -84.6927, -97.9312, 98.861, 19.8888, -64.0522, -27.1243, 72.7673, -9.9489, 94.274, -72.868, 43.1349, 84.1897, 87.0729, 87.2606, 34.5548, 87.7985, 4.84555, -10.2156, -93.7445, 71.8209, -63.4942, 45.6619, 93.4737, 79.6631, 66.8743, 18.1016, -27.7082, -67.0339, -11.9576, 52.0373, -11.5452, -73.8953, -63.5915, 99.4875, -46.2296, 75.453, -67.2079, 89.8868, -19.9666, 30.5359, 42.1465, -19.8105, 82.3653, -89.2164, -0.959167, -50.0723, -30.3058, 48.1772, -27.7686, 26.1484, 94.8462, -15.5663, -87.346, -84.2826, -58.8268, -42.4957, -23.7061, 67.0375, -83.5848, 64.167, 63.3315, -33.3809, 35.1264, 96.6872, 91.8399, 33.9888, 78.5923, -30.4885, 26.3331, -62.3014, -30.3431, 96.9554, 50.3262, 66.612, -71.5939, -97.0042, 71.4549, 42.3891, 71.308, 72.3209, 59.1608, -4.57918, -81.3639, -37.2619, 28.2445, 16.7995, -46.5868, -88.6893, 82.0504, -39.3391, -33.7141, -88.6628, -94.1271, -74.7738, -80.0798, -67.5639, -69.8237, -37.5219, 11.9601, -30.3912, -30.1169, 22.7411, -85.9541, 19.5141, -37.6203, -49.5693, 5.09318, 11.4884, 18.9713, 21.1073, -84.9266, 11.9436, -22.4703, -58.5243, -24.0218, -63.2767, -2.72752, -87.8947, -91.5162, 33.4207, -85.9841, 18.743, 48.9581, 69.3992, 2.42074, -75.0209, -53.2579, -45.4509, 66.6121, 51.6616, -48.073, 74.2754, -51.1623, -89.9345, 4.15238, -4.47531, 79.6587, -31.1646, 69.4103, -83.5936, -78.7341, 56.8626, 72.8834, -27.0248, -80.3328, 71.7272, -77.979, -76.6814, -14.9994, -94.5054, -75.2802, -96.4931, -17.6781, -5.50804, -83.4637, -56.8385, 51.5406, -60.527, -11.0762, -33.3166, -54.9609, -36.9426, -70.3942, 28.3439, 5.28754, -61.4775, 96.0657, -69.1967, 70.5489, 32.817, -53.5746, 49.2601, -88.5728, -1.94822, -3.16238, 19.083, -81.5139, 87.8383, 90.714, 4.75546, 31.9277, -4.1301, -0.160932, -31.2602, 56.4225, -72.1826, 91.5082, 68.2155, -81.7476, -14.0418, -79.4093, -30.7375, 38.8967, -16.5589, -69.4351, 48.6597, -8.44998, -74.4274, -20.3394, -59.2265, 19.407, 88.1542, -15.4888, 60.9066, 59.5144, -42.6935, 20.3518, 11.7192, -31.3635, 26.0055, -26.9334, 79.3798, 46.4724, 22.984, 67.5759]
Input (src1Local):
[35.8789, 44.0334, 54.9997, 44.8567, -30.8579, -53.714, -59.8013, 71.1663, 46.3484, 8.56818, -59.4716, 6.07412, -39.0137, 64.5595, 17.0849, 45.2641, -63.2115, -98.7838, -52.3835, -65.9849, 50.4909, 69.9812, -22.3447, -32.3809, -97.8394, -45.4997, 63.5391, -69.3535, 43.3368, 98.8541, -77.2888, 1.02385, 20.4965, -26.7797, 98.2463, -78.9606, -62.4907, -13.5348, -49.5058, -4.06369, 77.2982, -32.8221, 84.6766, -62.3829, 58.8673, -75.8509, -95.3497, -79.7642, 67.1185, 34.4278, 34.5305, -76.1646, 53.1497, -12.3158, -42.9392, 59.2962, -4.12072, 47.1292, -17.0687, -78.0087, -59.4565, -98.9565, -54.0959, 56.5437, -74.3328, 77.2781, 52.7964, -0.932984, 70.8957, -68.1249, 85.895, 25.4119, 71.9202, -73.1287, 63.6916, 21.4303, 66.0614, 66.1438, -22.2332, 84.0665, -7.86752, -2.38648, 1.37756, -98.691, -35.847, -15.2647, -85.2363, -54.3978, -46.6612, 99.3826, -75.7728, -31.2539, 97.9558, 92.4507, 80.2871, -60.8802, -82.0434, -80.625, 19.6418, 51.0559, 35.3667, -56.306, -41.2088, 0.955906, -85.7743, 8.18112, 36.4615, -0.572343, -16.0821, 36.0277, -4.61647, 26.5385, 88.6082, 9.17454, 44.8951, -42.173, 51.5339, 5.93139, 93.7096, -68.8219, 68.2573, -67.325, -88.4579, -56.8873, -75.8117, -40.5576, -98.378, 32.3699, 64.6693, -73.1523, -57.8738, 63.1893, -40.4731, -1.00914, -80.6115, 44.2928, 76.6212, -29.3298, -58.1212, 83.3083, -20.6412, 26.8912, -82.1719, 26.8713, -56.5484, 35.4743, -8.59957, -12.4709, 27.8249, 76.6877, -27.5806, 63.2649, 66.1106, 15.8328, 9.19251, -79.6418, -9.31359, 63.7053, -8.37093, 55.6421, -99.0591, -64.1341, 91.4046, 26.7268, -92.1002, -34.7002, -6.41819, -18.15, 12.207, 48.6667, -39.4883, -21.0939, -50.3433, 58.2913, 7.64983, -82.6098, -89.6739, -25.9494, 82.4803, 20.8037, 21.483, -29.0788, 31.7695, 50.462, -83.7715, 63.4177, 52.7679, -90.2271, 16.1258, -61.4531, -61.7242, 25.0575, -97.8702, 26.9708, -23.039, -52.7595, -97.0177, -13.1399, -47.6936, -29.7551, 88.9603, -82.1242, -56.6307, 91.7884, 0.0381027, -49.0936, -43.5545, 47.3574, 97.1801, 43.4392, 22.7347, 12.6125, 63.7829, 22.3428, 53.4543, -91.4307, 45.6971, -92.1851, -81.4774, 35.8835, -33.043, -79.7464, 69.0971, -82.6252, -63.0042, -61.0205, -8.00347, -60.0369, 56.2894, -38.1932, 17.976, 5.82004, 4.41524, -52.2192, 93.1915, 21.1114, -29.3558, -18.5685, 20.7356, -4.71108, -0.947533, 73.0143, 62.5668, 96.1632, 41.4265, -89.503, -83.7747, -97.6047, -60.7304, 28.9736, -42.6681, 55.2584, 59.1584, -14.6596, -41.1826, 48.8083]
Input (maskLocal):
[60, 32, 10, 7, 42, 52, 38, 26, 19, 15, 18, 83, 41, 43, 91, 30, 45, 77, 80, 58, 34, 76, 44, 4, 64, 45, 48, 31, 30, 56, 43, 88]
Output (dstLocal):
[35.8789,44.0334,-50.6124,-72.3737,-33.7107,-83.4001,-59.8013,71.1663,46.3484,8.56818,-59.4716,6.07412,-39.0137,-53.1848,17.0849,45.2641,-63.2115,6.53722,-52.3835,37.6655,50.4909,69.9812,-22.3447,-32.3809,23.0464,28.5975,-46.3033,-69.3535,43.3368,98.8541,-77.2888,1.02385,20.4965,10.7653,98.2463,-65.4774,-62.4907,-89.6462,-49.5058,-4.06369,77.2982,-32.8221,-97.9312,-62.3829,19.8888,-64.0522,-95.3497,-79.7642,67.1185,94.274,-72.868,-76.1646,53.1497,87.0729,-42.9392,59.2962,-4.12072,4.84555,-17.0687,-93.7445,71.8209,-98.9565,-54.0959,56.5437,79.6631,66.8743,52.7964,-0.932984,-67.0339,-68.1249,85.895,25.4119,-73.8953,-63.5915,99.4875,-46.2296,66.0614,66.1438,-22.2332,84.0665,-7.86752,42.1465,1.37756,-98.691,-89.2164,-15.2647,-85.2363,-54.3978,48.1772,-27.7686,-75.7728,-31.2539,-15.5663,92.4507,-84.2826,-60.8802,-42.4957,-80.625,19.6418,-83.5848,35.3667,63.3315,-41.2088,0.955906,96.6872,91.8399,36.4615,78.5923,-16.0821,26.3331,-4.61647,26.5385,96.9554,50.3262,44.8951,-71.5939,-97.0042,5.93139,42.3891,-68.8219,68.2573,59.1608,-4.57918,-81.3639,-37.2619,-40.5576,-98.378,32.3699,-88.6893,-73.1523,-39.3391,-33.7141,-40.4731,-94.1271,-80.6115,44.2928,-67.5639,-29.3298,-37.5219,11.9601,-20.6412,26.8912,22.7411,26.8713,-56.5484,35.4743,-8.59957,-12.4709,11.4884,76.6877,21.1073,63.2649,66.1106,-22.4703,9.19251,-24.0218,-63.2767,-2.72752,-8.37093,55.6421,-99.0591,-85.9841,91.4046,26.7268,-92.1002,2.42074,-6.41819,-18.15,12.207,48.6667,51.6616,-48.073,-50.3433,58.2913,-89.9345,-82.6098,-89.6739,-25.9494,-31.1646,69.4103,21.483,-78.7341,31.7695,50.462,-83.7715,63.4177,71.7272,-90.2271,16.1258,-61.4531,-61.7242,25.0575,-97.8702,26.9708,-23.039,-52.7595,-97.0177,-13.1399,-60.527,-29.7551,-33.3166,-82.1242,-36.9426,-70.3942,0.0381027,5.28754,-43.5545,47.3574,97.1801,43.4392,22.7347,12.6125,49.2601,-88.5728,53.4543,-91.4307,19.083,-81.5139,87.8383,90.714,4.75546,-79.7464,69.0971,-82.6252,-63.0042,56.4225,-72.1826,91.5082,68.2155,-38.1932,17.976,5.82004,4.41524,-52.2192,93.1915,-69.4351,48.6597,-8.44998,20.7356,-4.71108,-59.2265,19.407,62.5668,-15.4888,41.4265,59.5144,-83.7747,-97.6047,-60.7304,28.9736,-42.6681,-26.9334,79.3798,-14.6596,22.984,48.8083]

Example of mode 1:

Input (src0Local):
[-80.4933, 52.2499, -50.6124, -72.3737, -33.7107, -83.4001, 34.3954, 61.3188, 96.5484, 27.1321, -56.8153, 9.80549, 9.11199, -53.1848, -77.2548, -0.0681466, -69.5783, 6.53722, -22.5986, 37.6655, -25.4146, 89.232, 55.4716, 21.6069, 23.0464, 28.5975, -46.3033, 50.0312, -42.6339, 41.8752, -87.0426, 37.9717, 10.4336, 10.7653, -30.6943, -65.4774, 8.38653, -89.6462, 65.1115, 42.2134, -91.1666, -84.6927, -97.9312, 98.861, 19.8888, -64.0522, -27.1243, 72.7673, -9.9489, 94.274, -72.868, 43.1349, 84.1897, 87.0729, 87.2606, 34.5548, 87.7985, 4.84555, -10.2156, -93.7445, 71.8209, -63.4942, 45.6619, 93.4737, 79.6631, 66.8743, 18.1016, -27.7082, -67.0339, -11.9576, 52.0373, -11.5452, -73.8953, -63.5915, 99.4875, -46.2296, 75.453, -67.2079, 89.8868, -19.9666, 30.5359, 42.1465, -19.8105, 82.3653, -89.2164, -0.959167, -50.0723, -30.3058, 48.1772, -27.7686, 26.1484, 94.8462, -15.5663, -87.346, -84.2826, -58.8268, -42.4957, -23.7061, 67.0375, -83.5848, 64.167, 63.3315, -33.3809, 35.1264, 96.6872, 91.8399, 33.9888, 78.5923, -30.4885, 26.3331, -62.3014, -30.3431, 96.9554, 50.3262, 66.612, -71.5939, -97.0042, 71.4549, 42.3891, 71.308, 72.3209, 59.1608, -4.57918, -81.3639, -37.2619, 28.2445, 16.7995, -46.5868, -88.6893, 82.0504, -39.3391, -33.7141, -88.6628, -94.1271, -74.7738, -80.0798, -67.5639, -69.8237, -37.5219, 11.9601, -30.3912, -30.1169, 22.7411, -85.9541, 19.5141, -37.6203, -49.5693, 5.09318, 11.4884, 18.9713, 21.1073, -84.9266, 11.9436, -22.4703, -58.5243, -24.0218, -63.2767, -2.72752, -87.8947, -91.5162, 33.4207, -85.9841, 18.743, 48.9581, 69.3992, 2.42074, -75.0209, -53.2579, -45.4509, 66.6121, 51.6616, -48.073, 74.2754, -51.1623, -89.9345, 4.15238, -4.47531, 79.6587, -31.1646, 69.4103, -83.5936, -78.7341, 56.8626, 72.8834, -27.0248, -80.3328, 71.7272, -77.979, -76.6814, -14.9994, -94.5054, -75.2802, -96.4931, -17.6781, -5.50804, -83.4637, -56.8385, 51.5406, -60.527, -11.0762, -33.3166, -54.9609, -36.9426, -70.3942, 28.3439, 5.28754, -61.4775, 96.0657, -69.1967, 70.5489, 32.817, -53.5746, 49.2601, -88.5728, -1.94822, -3.16238, 19.083, -81.5139, 87.8383, 90.714, 4.75546, 31.9277, -4.1301, -0.160932, -31.2602, 56.4225, -72.1826, 91.5082, 68.2155, -81.7476, -14.0418, -79.4093, -30.7375, 38.8967, -16.5589, -69.4351, 48.6597, -8.44998, -74.4274, -20.3394, -59.2265, 19.407, 88.1542, -15.4888, 60.9066, 59.5144, -42.6935, 20.3518, 11.7192, -31.3635, 26.0055, -26.9334, 79.3798, 46.4724, 22.984, 67.5759]
Input (maskLocal):
[60, 32, 10, 7, 42, 52, 38, 26, 19, 15, 18, 83, 41, 43, 91, 30, 45, 77, 80, 58, 34, 76, 44, 4, 64, 45, 48, 31, 30, 56, 43, 88 ]
Output (dstLocal):
[0,0,-50.6124,-72.3737,-33.7107,-83.4001,0,0,0,0,0,0,0,-53.1848,0,0,0,6.53722,0,37.6655,0,0,0,0,23.0464,28.5975,-46.3033,0,0,0,0,0,0,10.7653,0,-65.4774,0,-89.6462,0,0,0,0,-97.9312,0,19.8888,-64.0522,0,0,0,94.274,-72.868,0,0,87.0729,0,0,0,4.84555,0,-93.7445,71.8209,0,0,0,79.6631,66.8743,0,0,-67.0339,0,0,0,-73.8953,-63.5915,99.4875,-46.2296,0,0,0,0,0,42.1465,0,0,-89.2164,0,0,0,48.1772,-27.7686,0,0,-15.5663,0,-84.2826,0,-42.4957,0,0,-83.5848,0,63.3315,0,0,96.6872,91.8399,0,78.5923,0,26.3331,0,0,96.9554,50.3262,0,-71.5939,-97.0042,0,42.3891,0,0,59.1608,-4.57918,-81.3639,-37.2619,0,0,0,-88.6893,0,-39.3391,-33.7141,0,-94.1271,0,0,-67.5639,0,-37.5219,11.9601,0,0,22.7411,0,0,0,0,0,11.4884,0,21.1073,0,0,-22.4703,0,-24.0218,-63.2767,-2.72752,0,0,0,-85.9841,0,0,0,2.42074,0,0,0,0,51.6616,-48.073,0,0,-89.9345,0,0,0,-31.1646,69.4103,0,-78.7341,0,0,0,0,71.7272,0,0,0,0,0,0,0,0,0,0,0,-60.527,0,-33.3166,0,-36.9426,-70.3942,0,5.28754,0,0,0,0,0,0,49.2601,-88.5728,0,0,19.083,-81.5139,87.8383,90.714,4.75546,0,0,0,0,56.4225,-72.1826,91.5082,68.2155,0,0,0,0,0,0,-69.4351,48.6597,-8.44998,0,0,-59.2265,19.407,0,-15.4888,0,59.5144,0,0,0,0,0,-26.9334,79.3798,0,22.984,0]

Example of mode 0:

Input (src0Local):
[-80.4933, 52.2499, -50.6124, -72.3737, -33.7107, -83.4001, 34.3954, 61.3188, 96.5484, 27.1321, -56.8153, 9.80549, 9.11199, -53.1848, -77.2548, -0.0681466, -69.5783, 6.53722, -22.5986, 37.6655, -25.4146, 89.232, 55.4716, 21.6069, 23.0464, 28.5975, -46.3033, 50.0312, -42.6339, 41.8752, -87.0426, 37.9717, 10.4336, 10.7653, -30.6943, -65.4774, 8.38653, -89.6462, 65.1115, 42.2134, -91.1666, -84.6927, -97.9312, 98.861, 19.8888, -64.0522, -27.1243, 72.7673, -9.9489, 94.274, -72.868, 43.1349, 84.1897, 87.0729, 87.2606, 34.5548, 87.7985, 4.84555, -10.2156, -93.7445, 71.8209, -63.4942, 45.6619, 93.4737, 79.6631, 66.8743, 18.1016, -27.7082, -67.0339, -11.9576, 52.0373, -11.5452, -73.8953, -63.5915, 99.4875, -46.2296, 75.453, -67.2079, 89.8868, -19.9666, 30.5359, 42.1465, -19.8105, 82.3653, -89.2164, -0.959167, -50.0723, -30.3058, 48.1772, -27.7686, 26.1484, 94.8462, -15.5663, -87.346, -84.2826, -58.8268, -42.4957, -23.7061, 67.0375, -83.5848, 64.167, 63.3315, -33.3809, 35.1264, 96.6872, 91.8399, 33.9888, 78.5923, -30.4885, 26.3331, -62.3014, -30.3431, 96.9554, 50.3262, 66.612, -71.5939, -97.0042, 71.4549, 42.3891, 71.308, 72.3209, 59.1608, -4.57918, -81.3639, -37.2619, 28.2445, 16.7995, -46.5868, -88.6893, 82.0504, -39.3391, -33.7141, -88.6628, -94.1271, -74.7738, -80.0798, -67.5639, -69.8237, -37.5219, 11.9601, -30.3912, -30.1169, 22.7411, -85.9541, 19.5141, -37.6203, -49.5693, 5.09318, 11.4884, 18.9713, 21.1073, -84.9266, 11.9436, -22.4703, -58.5243, -24.0218, -63.2767, -2.72752, -87.8947, -91.5162, 33.4207, -85.9841, 18.743, 48.9581, 69.3992, 2.42074, -75.0209, -53.2579, -45.4509, 66.6121, 51.6616, -48.073, 74.2754, -51.1623, -89.9345, 4.15238, -4.47531, 79.6587, -31.1646, 69.4103, -83.5936, -78.7341, 56.8626, 72.8834, -27.0248, -80.3328, 71.7272, -77.979, -76.6814, -14.9994, -94.5054, -75.2802, -96.4931, -17.6781, -5.50804, -83.4637, -56.8385, 51.5406, -60.527, -11.0762, -33.3166, -54.9609, -36.9426, -70.3942, 28.3439, 5.28754, -61.4775, 96.0657, -69.1967, 70.5489, 32.817, -53.5746, 49.2601, -88.5728, -1.94822, -3.16238, 19.083, -81.5139, 87.8383, 90.714, 4.75546, 31.9277, -4.1301, -0.160932, -31.2602, 56.4225, -72.1826, 91.5082, 68.2155, -81.7476, -14.0418, -79.4093, -30.7375, 38.8967, -16.5589, -69.4351, 48.6597, -8.44998, -74.4274, -20.3394, -59.2265, 19.407, 88.1542, -15.4888, 60.9066, 59.5144, -42.6935, 20.3518, 11.7192, -31.3635, 26.0055, -26.9334, 79.3798, 46.4724, 22.984, 67.5759]
Input (src1Local):
[35.8789, 44.0334, 54.9997, 44.8567, -30.8579, -53.714, -59.8013, 71.1663, 46.3484, 8.56818, -59.4716, 6.07412, -39.0137, 64.5595, 17.0849, 45.2641, -63.2115, -98.7838, -52.3835, -65.9849, 50.4909, 69.9812, -22.3447, -32.3809, -97.8394, -45.4997, 63.5391, -69.3535, 43.3368, 98.8541, -77.2888, 1.02385, 20.4965, -26.7797, 98.2463, -78.9606, -62.4907, -13.5348, -49.5058, -4.06369, 77.2982, -32.8221, 84.6766, -62.3829, 58.8673, -75.8509, -95.3497, -79.7642, 67.1185, 34.4278, 34.5305, -76.1646, 53.1497, -12.3158, -42.9392, 59.2962, -4.12072, 47.1292, -17.0687, -78.0087, -59.4565, -98.9565, -54.0959, 56.5437, -74.3328, 77.2781, 52.7964, -0.932984, 70.8957, -68.1249, 85.895, 25.4119, 71.9202, -73.1287, 63.6916, 21.4303, 66.0614, 66.1438, -22.2332, 84.0665, -7.86752, -2.38648, 1.37756, -98.691, -35.847, -15.2647, -85.2363, -54.3978, -46.6612, 99.3826, -75.7728, -31.2539, 97.9558, 92.4507, 80.2871, -60.8802, -82.0434, -80.625, 19.6418, 51.0559, 35.3667, -56.306, -41.2088, 0.955906, -85.7743, 8.18112, 36.4615, -0.572343, -16.0821, 36.0277, -4.61647, 26.5385, 88.6082, 9.17454, 44.8951, -42.173, 51.5339, 5.93139, 93.7096, -68.8219, 68.2573, -67.325, -88.4579, -56.8873, -75.8117, -40.5576, -98.378, 32.3699, 64.6693, -73.1523, -57.8738, 63.1893, -40.4731, -1.00914, -80.6115, 44.2928, 76.6212, -29.3298, -58.1212, 83.3083, -20.6412, 26.8912, -82.1719, 26.8713, -56.5484, 35.4743, -8.59957, -12.4709, 27.8249, 76.6877, -27.5806, 63.2649, 66.1106, 15.8328, 9.19251, -79.6418, -9.31359, 63.7053, -8.37093, 55.6421, -99.0591, -64.1341, 91.4046, 26.7268, -92.1002, -34.7002, -6.41819, -18.15, 12.207, 48.6667, -39.4883, -21.0939, -50.3433, 58.2913, 7.64983, -82.6098, -89.6739, -25.9494, 82.4803, 20.8037, 21.483, -29.0788, 31.7695, 50.462, -83.7715, 63.4177, 52.7679, -90.2271, 16.1258, -61.4531, -61.7242, 25.0575, -97.8702, 26.9708, -23.039, -52.7595, -97.0177, -13.1399, -47.6936, -29.7551, 88.9603, -82.1242, -56.6307, 91.7884, 0.0381027, -49.0936, -43.5545, 47.3574, 97.1801, 43.4392, 22.7347, 12.6125, 63.7829, 22.3428, 53.4543, -91.4307, 45.6971, -92.1851, -81.4774, 35.8835, -33.043, -79.7464, 69.0971, -82.6252, -63.0042, -61.0205, -8.00347, -60.0369, 56.2894, -38.1932, 17.976, 5.82004, 4.41524, -52.2192, 93.1915, 21.1114, -29.3558, -18.5685, 20.7356, -4.71108, -0.947533, 73.0143, 62.5668, 96.1632, 41.4265, -89.503, -83.7747, -97.6047, -60.7304, 28.9736, -42.6681, 55.2584, 59.1584, -14.6596, -41.1826, 48.8083]
Input (maskLocal):
[60, 32, 10, 7, 42, 52, 38, 26, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 19, 15, 18, 83, 41, 43, 91, 30, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 45, 77, 80, 58, 34, 76, 44, 4, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 64, 45, 48, 31, 30, 56, 43, 88, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0]
Output (dstLocal):
[35.8789, 44.0334, -50.6124, -72.3737, -33.7107, -83.4001, -59.8013, 71.1663, 46.3484, 8.56818, -59.4716, 6.07412, -39.0137, -53.1848, 17.0849, 45.2641, -63.2115, 6.53722, -52.3835, 37.6655, 50.4909, 69.9812, -22.3447, -32.3809, 23.0464, 28.5975, -46.3033, -69.3535, 43.3368, 98.8541, -77.2888, 1.02385, 20.4965, 10.7653, 98.2463, -65.4774, -62.4907, -89.6462, -49.5058, -4.06369, 77.2982, -32.8221, -97.9312, -62.3829, 19.8888, -64.0522, -95.3497, -79.7642, 67.1185, 94.274, -72.868, -76.1646, 53.1497, 87.0729, -42.9392, 59.2962, -4.12072, 4.84555, -17.0687, -93.7445, 71.8209, -98.9565, -54.0959, 56.5437, -74.3328, 77.2781, 18.1016, -27.7082, -67.0339, -11.9576, 85.895, 25.4119, 71.9202, -73.1287, 63.6916, 21.4303, 66.0614, -67.2079, -22.2332, 84.0665, -7.86752, 42.1465, 1.37756, 82.3653, -35.847, -15.2647, -85.2363, -54.3978, 48.1772, -27.7686, 26.1484, -31.2539, 97.9558, 92.4507, 80.2871, -60.8802, -82.0434, -23.7061, 19.6418, -83.5848, 35.3667, 63.3315, -41.2088, 0.955906, -85.7743, 8.18112, 33.9888, -0.572343, -30.4885, 26.3331, -4.61647, 26.5385, 88.6082, 50.3262, 66.612, -42.173, 51.5339, 71.4549, 93.7096, -68.8219, 68.2573, 59.1608, -88.4579, -81.3639, -37.2619, -40.5576, -98.378, 32.3699, 64.6693, -73.1523, -39.3391, -33.7141, -88.6628, -94.1271, -80.6115, 44.2928, 76.6212, -29.3298, -58.1212, 83.3083, -20.6412, -30.1169, -82.1719, 26.8713, -56.5484, -37.6203, -8.59957, 5.09318, 27.8249, 76.6877, -27.5806, 63.2649, 11.9436, -22.4703, -58.5243, -79.6418, -9.31359, 63.7053, -8.37093, 55.6421, -99.0591, -85.9841, 91.4046, 48.9581, -92.1002, 2.42074, -6.41819, -18.15, 12.207, 48.6667, 51.6616, -21.0939, 74.2754, -51.1623, 7.64983, -82.6098, -89.6739, 79.6587, -31.1646, 20.8037, 21.483, -78.7341, 31.7695, 50.462, -83.7715, -80.3328, 52.7679, -77.979, -76.6814, -61.4531, -61.7242, 25.0575, -97.8702, 26.9708, -5.50804, -83.4637, -56.8385, 51.5406, -47.6936, -29.7551, 88.9603, -82.1242, -56.6307, 91.7884, 0.0381027, 5.28754, -43.5545, 47.3574, 97.1801, 70.5489, 22.7347, -53.5746, 63.7829, 22.3428, 53.4543, -91.4307, 19.083, -81.5139, 87.8383, 35.8835, -33.043, -79.7464, 69.0971, -82.6252, -63.0042, 56.4225, -8.00347, 91.5082, 56.2894, -81.7476, 17.976, 5.82004, 4.41524, -52.2192, -16.5589, 21.1114, 48.6597, -8.44998, 20.7356, -4.71108, -0.947533, 19.407, 88.1542, 96.1632, 41.4265, 59.5144, -83.7747, -97.6047, -60.7304, -31.3635, -42.6681, -26.9334, 79.3798, -14.6596, -41.1826, 48.8083]

Parent topic: Comparison and Selection