RPPT Tensor Operations - Statistical Operations.#
RPPT Tensor Operations - Statistical Operations. More...
Functions | |
RppStatus | rppt_tensor_sum_host (RppPtr_t srcPtr, RpptDescPtr srcDescPtr, RppPtr_t tensorSumArr, Rpp32u tensorSumArrLength, RpptROIPtr roiTensorPtrSrc, RpptRoiType roiType, rppHandle_t rppHandle) |
Tensor sum operation on HOST backend for a NCHW/NHWC layout tensor. More... | |
RppStatus | rppt_tensor_sum_gpu (RppPtr_t srcPtr, RpptDescPtr srcDescPtr, RppPtr_t tensorSumArr, Rpp32u tensorSumArrLength, RpptROIPtr roiTensorPtrSrc, RpptRoiType roiType, rppHandle_t rppHandle) |
Tensor sum operation on HIP backend for a NCHW/NHWC layout tensor. More... | |
RppStatus | rppt_tensor_min_host (RppPtr_t srcPtr, RpptDescPtr srcDescPtr, RppPtr_t minArr, Rpp32u minArrLength, RpptROIPtr roiTensorPtrSrc, RpptRoiType roiType, rppHandle_t rppHandle) |
Tensor min operation on HOST backend for a NCHW/NHWC layout tensor. More... | |
RppStatus | rppt_tensor_min_gpu (RppPtr_t srcPtr, RpptDescPtr srcDescPtr, RppPtr_t imageMinArr, Rpp32u imageMinArrLength, RpptROIPtr roiTensorPtrSrc, RpptRoiType roiType, rppHandle_t rppHandle) |
Tensor min operation on HIP backend for a NCHW/NHWC layout tensor. More... | |
RppStatus | rppt_tensor_max_host (RppPtr_t srcPtr, RpptDescPtr srcDescPtr, RppPtr_t maxArr, Rpp32u maxArrLength, RpptROIPtr roiTensorPtrSrc, RpptRoiType roiType, rppHandle_t rppHandle) |
Tensor max operation on HOST backend for a NCHW/NHWC layout tensor. More... | |
RppStatus | rppt_tensor_max_gpu (RppPtr_t srcPtr, RpptDescPtr srcDescPtr, RppPtr_t imageMaxArr, Rpp32u imageMaxArrLength, RpptROIPtr roiTensorPtrSrc, RpptRoiType roiType, rppHandle_t rppHandle) |
Tensor max operation on HIP backend for a NCHW/NHWC layout tensor. More... | |
RppStatus | rppt_normalize_host (RppPtr_t srcPtr, RpptGenericDescPtr srcGenericDescPtr, RppPtr_t dstPtr, RpptGenericDescPtr dstGenericDescPtr, Rpp32u axisMask, Rpp32f *meanTensor, Rpp32f *stdDevTensor, Rpp8u computeMeanStddev, Rpp32f scale, Rpp32f shift, Rpp32u *roiTensor, rppHandle_t rppHandle) |
Normalize Generic augmentation on HOST backend. More... | |
RppStatus | rppt_normalize_gpu (RppPtr_t srcPtr, RpptGenericDescPtr srcGenericDescPtr, RppPtr_t dstPtr, RpptGenericDescPtr dstGenericDescPtr, Rpp32u axisMask, Rpp32f *meanTensor, Rpp32f *stdDevTensor, Rpp8u computeMeanStddev, Rpp32f scale, Rpp32f shift, Rpp32u *roiTensor, rppHandle_t rppHandle) |
Normalize Generic augmentation on HIP backend. More... | |
RppStatus | rppt_tensor_mean_host (RppPtr_t srcPtr, RpptDescPtr srcDescPtr, RppPtr_t tensorMeanArr, Rpp32u tensorMeanArrLength, RpptROIPtr roiTensorPtrSrc, RpptRoiType roiType, rppHandle_t rppHandle) |
Tensor mean operation on HOST backend for a NCHW/NHWC layout tensor. More... | |
RppStatus | rppt_tensor_mean_gpu (RppPtr_t srcPtr, RpptDescPtr srcDescPtr, RppPtr_t tensorMeanArr, Rpp32u tensorMeanArrLength, RpptROIPtr roiTensorPtrSrc, RpptRoiType roiType, rppHandle_t rppHandle) |
Tensor mean operation on HIP backend for a NCHW/NHWC layout tensor. More... | |
RppStatus | rppt_tensor_stddev_host (RppPtr_t srcPtr, RpptDescPtr srcDescPtr, RppPtr_t tensorStddevArr, Rpp32u tensorStddevArrLength, Rpp32f *meanTensor, RpptROIPtr roiTensorPtrSrc, RpptRoiType roiType, rppHandle_t rppHandle) |
Tensor stddev operation on HOST backend for a NCHW/NHWC layout tensor. More... | |
RppStatus | rppt_tensor_stddev_gpu (RppPtr_t srcPtr, RpptDescPtr srcDescPtr, RppPtr_t tensorStddevArr, Rpp32u tensorStddevArrLength, Rpp32f *meanTensor, RpptROIPtr roiTensorPtrSrc, RpptRoiType roiType, rppHandle_t rppHandle) |
Tensor stddev operation on HIP backend for a NCHW/NHWC layout tensor. More... | |
Detailed Description
RPPT Tensor Operations - Statistical Operations.
Function Documentation
◆ rppt_normalize_gpu()
RppStatus rppt_normalize_gpu | ( | RppPtr_t | srcPtr, |
RpptGenericDescPtr | srcGenericDescPtr, | ||
RppPtr_t | dstPtr, | ||
RpptGenericDescPtr | dstGenericDescPtr, | ||
Rpp32u | axisMask, | ||
Rpp32f * | meanTensor, | ||
Rpp32f * | stdDevTensor, | ||
Rpp8u | computeMeanStddev, | ||
Rpp32f | scale, | ||
Rpp32f | shift, | ||
Rpp32u * | roiTensor, | ||
rppHandle_t | rppHandle | ||
) |
Normalize Generic augmentation on HIP backend.
Normalizes the input generic ND buffer by removing the mean and dividing by the standard deviation for a given ND Tensor.
- Parameters
-
[in] srcPtr source tensor memory in HIP memory [in] srcGenericDescPtr source tensor descriptor [out] dstPtr destination tensor memory in HIP memory [in] dstGenericDescPtr destination tensor descriptor [in] axisMask axis along which normalization needs to be done [in] meanTensor values to be subtracted from input [in] stdDevTensor standard deviation values to scale the input [in] computeMeanStddev flag to represent internal computation of mean, stddev (Wherein 0th bit used to represent computeMean and 1st bit for computeStddev, 0- Externally provided) [in] scale value to be multiplied with data after subtracting from mean [in] shift value to be added finally [in] roiTensor values to represent dimensions of input tensor [in] rppHandle RPP HIP handle created with rppCreateWithStreamAndBatchSize()
- Returns
- A
RppStatus
enumeration.
- Return values
-
RPP_SUCCESS Successful completion. RPP_ERROR* Unsuccessful completion.
◆ rppt_normalize_host()
RppStatus rppt_normalize_host | ( | RppPtr_t | srcPtr, |
RpptGenericDescPtr | srcGenericDescPtr, | ||
RppPtr_t | dstPtr, | ||
RpptGenericDescPtr | dstGenericDescPtr, | ||
Rpp32u | axisMask, | ||
Rpp32f * | meanTensor, | ||
Rpp32f * | stdDevTensor, | ||
Rpp8u | computeMeanStddev, | ||
Rpp32f | scale, | ||
Rpp32f | shift, | ||
Rpp32u * | roiTensor, | ||
rppHandle_t | rppHandle | ||
) |
Normalize Generic augmentation on HOST backend.
Normalizes the input generic ND buffer by removing the mean and dividing by the standard deviation for a given ND Tensor. Supports u8->f32, i8->f32, f16->f16 and f32->f32 datatypes. Also has toggle variant(NHWC->NCHW) support for 3D.
- Parameters
-
[in] srcPtr source tensor memory in HOST memory [in] srcGenericDescPtr source tensor descriptor [out] dstPtr destination tensor memory in HOST memory [in] dstGenericDescPtr destination tensor descriptor [in] axisMask axis along which normalization needs to be done [in] meanTensor values to be subtracted from input [in] stdDevTensor standard deviation values to scale the input [in] computeMeanStddev flag to represent internal computation of mean, stddev (Wherein 0th bit used to represent computeMean and 1st bit for computeStddev, 0- Externally provided) [in] scale value to be multiplied with data after subtracting from mean [in] shift value to be added finally [in] roiTensor values to represent dimensions of input tensor [in] rppHandle RPP HOST handle created with rppCreateWithBatchSize()
- Returns
- A
RppStatus
enumeration.
- Return values
-
RPP_SUCCESS Successful completion. RPP_ERROR* Unsuccessful completion.
◆ rppt_tensor_max_gpu()
RppStatus rppt_tensor_max_gpu | ( | RppPtr_t | srcPtr, |
RpptDescPtr | srcDescPtr, | ||
RppPtr_t | imageMaxArr, | ||
Rpp32u | imageMaxArrLength, | ||
RpptROIPtr | roiTensorPtrSrc, | ||
RpptRoiType | roiType, | ||
rppHandle_t | rppHandle | ||
) |
Tensor max operation on HIP backend for a NCHW/NHWC layout tensor.
The tensor max is a reduction operation that finds the channel-wise (R max / G max / B max) and overall max for each image in a batch of RGB(3 channel) / greyscale(1 channel) images with an NHWC/NCHW tensor layout.
- srcPtr depth ranges - Rpp8u (0 to 255), Rpp16f (0 to 1), Rpp32f (0 to 1), Rpp8s (-128 to 127).
- dstPtr depth ranges - Will be same depth as srcPtr.
- Parameters
-
[in] srcPtr source tensor in HIP memory [in] srcDescPtr source tensor descriptor (Restrictions - numDims = 4, offsetInBytes >= 0, dataType = U8/F16/F32/I8, layout = NCHW/NHWC, c = 1/3) [out] maxArr destination array in HIP memory [in] maxArrLength length of provided destination array (Restrictions - if srcDescPtr->c == 1 then tensorSumArrLength >= srcDescPtr->n, and if srcDescPtr->c == 3 then tensorSumArrLength >= srcDescPtr->n * 4) [in] roiTensorPtrSrc ROI data in HIP memory, for each image in source tensor (2D tensor of size batchSize * 4, in either format - XYWH(xy.x, xy.y, roiWidth, roiHeight) or LTRB(lt.x, lt.y, rb.x, rb.y)) | (Restrictions - roiTensorSrc[i].xywhROI.roiWidth <= 3840 and roiTensorSrc[i].xywhROI.roiHeight <= 2160) [in] roiType ROI type used (RpptRoiType::XYWH or RpptRoiType::LTRB) [in] rppHandle RPP HIP handle created with rppCreateWithBatchSize()
- Returns
- A
RppStatus
enumeration.
- Return values
-
RPP_SUCCESS Successful completion. RPP_ERROR* Unsuccessful completion.
◆ rppt_tensor_max_host()
RppStatus rppt_tensor_max_host | ( | RppPtr_t | srcPtr, |
RpptDescPtr | srcDescPtr, | ||
RppPtr_t | maxArr, | ||
Rpp32u | maxArrLength, | ||
RpptROIPtr | roiTensorPtrSrc, | ||
RpptRoiType | roiType, | ||
rppHandle_t | rppHandle | ||
) |
Tensor max operation on HOST backend for a NCHW/NHWC layout tensor.
The tensor max is a reduction operation that finds the channel-wise (R max / G max / B max) and overall max for each image in a batch of RGB(3 channel) / greyscale(1 channel) images with an NHWC/NCHW tensor layout.
- srcPtr depth ranges - Rpp8u (0 to 255), Rpp16f (0 to 1), Rpp32f (0 to 1), Rpp8s (-128 to 127).
- dstPtr depth ranges - Will be same depth as srcPtr.
- Parameters
-
[in] srcPtr source tensor in HOST memory [in] srcDescPtr source tensor descriptor (Restrictions - numDims = 4, offsetInBytes >= 0, dataType = U8/F16/F32/I8, layout = NCHW/NHWC, c = 1/3) [out] maxArr destination array in HOST memory [in] maxArrLength length of provided destination array (Restrictions - if srcDescPtr->c == 1 then tensorSumArrLength >= srcDescPtr->n, and if srcDescPtr->c == 3 then tensorSumArrLength >= srcDescPtr->n * 4) [in] roiTensorPtrSrc ROI data in HOST memory, for each image in source tensor (2D tensor of size batchSize * 4, in either format - XYWH(xy.x, xy.y, roiWidth, roiHeight) or LTRB(lt.x, lt.y, rb.x, rb.y)) | (Restrictions - roiTensorSrc[i].xywhROI.roiWidth <= 3840 and roiTensorSrc[i].xywhROI.roiHeight <= 2160) [in] roiType ROI type used (RpptRoiType::XYWH or RpptRoiType::LTRB) [in] rppHandle RPP HOST handle created with rppCreateWithBatchSize()
- Returns
- A
RppStatus
enumeration.
- Return values
-
RPP_SUCCESS Successful completion. RPP_ERROR* Unsuccessful completion.
◆ rppt_tensor_mean_gpu()
RppStatus rppt_tensor_mean_gpu | ( | RppPtr_t | srcPtr, |
RpptDescPtr | srcDescPtr, | ||
RppPtr_t | tensorMeanArr, | ||
Rpp32u | tensorMeanArrLength, | ||
RpptROIPtr | roiTensorPtrSrc, | ||
RpptRoiType | roiType, | ||
rppHandle_t | rppHandle | ||
) |
Tensor mean operation on HIP backend for a NCHW/NHWC layout tensor.
The tensor mean is a reduction operation that finds the channel-wise (R mean / G mean / B mean) and total mean for each image in a batch of RGB(3 channel) / greyscale(1 channel) images with an NHWC/NCHW tensor layout.
- srcPtr depth ranges - Rpp8u (0 to 255), Rpp16f (0 to 1), Rpp32f (0 to 1), Rpp8s (-128 to 127).
- dstPtr depth ranges - Will be same depth as srcPtr.
- Parameters
-
[in] srcPtr source tensor in HIP memory [in] srcDescPtr source tensor descriptor (Restrictions - numDims = 4, offsetInBytes >= 0, dataType = U8/F16/F32/I8, layout = NCHW/NHWC, c = 1/3) [out] tensorMeanArr destination array in HIP memory [in] tensorMeanArrLength length of provided destination array (Restrictions - if srcDescPtr->c == 1 then tensorMeanArrLength = srcDescPtr->n, and if srcDescPtr->c == 3 then tensorMeanArrLength = srcDescPtr->n * 4) [in] roiTensorPtrSrc ROI data in HIP memory, for each image in source tensor (2D tensor of size batchSize * 4, in either format - XYWH(xy.x, xy.y, roiWidth, roiHeight) or LTRB(lt.x, lt.y, rb.x, rb.y)) | (Restrictions - roiTensorSrc[i].xywhROI.roiWidth <= 3840 and roiTensorSrc[i].xywhROI.roiHeight <= 2160) [in] roiType ROI type used (RpptRoiType::XYWH or RpptRoiType::LTRB) [in] rppHandle RPP HIP handle created with rppCreateWithStreamAndBatchSize()
- Returns
- A
RppStatus
enumeration.
- Return values
-
RPP_SUCCESS Successful completion. RPP_ERROR* Unsuccessful completion.
◆ rppt_tensor_mean_host()
RppStatus rppt_tensor_mean_host | ( | RppPtr_t | srcPtr, |
RpptDescPtr | srcDescPtr, | ||
RppPtr_t | tensorMeanArr, | ||
Rpp32u | tensorMeanArrLength, | ||
RpptROIPtr | roiTensorPtrSrc, | ||
RpptRoiType | roiType, | ||
rppHandle_t | rppHandle | ||
) |
Tensor mean operation on HOST backend for a NCHW/NHWC layout tensor.
The tensor mean is a reduction operation that finds the channel-wise (R mean / G mean / B mean) and total mean for each image in a batch of RGB(3 channel) / greyscale(1 channel) images with an NHWC/NCHW tensor layout.
- srcPtr depth ranges - Rpp8u (0 to 255), Rpp16f (0 to 1), Rpp32f (0 to 1), Rpp8s (-128 to 127).
- dstPtr depth ranges - Will be same depth as srcPtr.
- Parameters
-
[in] srcPtr source tensor in HOST memory [in] srcDescPtr source tensor descriptor (Restrictions - numDims = 4, offsetInBytes >= 0, dataType = U8/F16/F32/I8, layout = NCHW/NHWC, c = 1/3) [out] tensorMeanArr destination array in HOST memory [in] tensorMeanArrLength length of provided destination array (Restrictions - if srcDescPtr->c == 1 then tensorMeanArrLength = srcDescPtr->n, and if srcDescPtr->c == 3 then tensorMeanArrLength = srcDescPtr->n * 4) [in] roiTensorPtrSrc ROI data in HOST memory, for each image in source tensor (2D tensor of size batchSize * 4, in either format - XYWH(xy.x, xy.y, roiWidth, roiHeight) or LTRB(lt.x, lt.y, rb.x, rb.y)) | (Restrictions - roiTensorSrc[i].xywhROI.roiWidth <= 3840 and roiTensorSrc[i].xywhROI.roiHeight <= 2160) [in] roiType ROI type used (RpptRoiType::XYWH or RpptRoiType::LTRB) [in] rppHandle RPP HOST handle created with rppCreateWithBatchSize()
- Returns
- A
RppStatus
enumeration.
- Return values
-
RPP_SUCCESS Successful completion. RPP_ERROR* Unsuccessful completion.
◆ rppt_tensor_min_gpu()
RppStatus rppt_tensor_min_gpu | ( | RppPtr_t | srcPtr, |
RpptDescPtr | srcDescPtr, | ||
RppPtr_t | imageMinArr, | ||
Rpp32u | imageMinArrLength, | ||
RpptROIPtr | roiTensorPtrSrc, | ||
RpptRoiType | roiType, | ||
rppHandle_t | rppHandle | ||
) |
Tensor min operation on HIP backend for a NCHW/NHWC layout tensor.
The tensor min is a reduction operation that finds the channel-wise (R min / G min / B min) and overall min for each image in a batch of RGB(3 channel) / greyscale(1 channel) images with an NHWC/NCHW tensor layout.
- srcPtr depth ranges - Rpp8u (0 to 255), Rpp16f (0 to 1), Rpp32f (0 to 1), Rpp8s (-128 to 127).
- dstPtr depth ranges - Will be same depth as srcPtr.
- Parameters
-
[in] srcPtr source tensor in HIP memory [in] srcDescPtr source tensor descriptor (Restrictions - numDims = 4, offsetInBytes >= 0, dataType = U8/F16/F32/I8, layout = NCHW/NHWC, c = 1/3) [out] minArr destination array in HIP memory [in] minArrLength length of provided destination array (Restrictions - if srcDescPtr->c == 1 then tensorSumArrLength >= srcDescPtr->n, and if srcDescPtr->c == 3 then tensorSumArrLength >= srcDescPtr->n * 4) [in] roiTensorPtrSrc ROI data in HIP memory, for each image in source tensor (2D tensor of size batchSize * 4, in either format - XYWH(xy.x, xy.y, roiWidth, roiHeight) or LTRB(lt.x, lt.y, rb.x, rb.y)) | (Restrictions - roiTensorSrc[i].xywhROI.roiWidth <= 3840 and roiTensorSrc[i].xywhROI.roiHeight <= 2160) [in] roiType ROI type used (RpptRoiType::XYWH or RpptRoiType::LTRB) [in] rppHandle RPP HIP handle created with rppCreateWithStreamAndBatchSize()
- Returns
- A
RppStatus
enumeration.
- Return values
-
RPP_SUCCESS Successful completion. RPP_ERROR* Unsuccessful completion.
◆ rppt_tensor_min_host()
RppStatus rppt_tensor_min_host | ( | RppPtr_t | srcPtr, |
RpptDescPtr | srcDescPtr, | ||
RppPtr_t | minArr, | ||
Rpp32u | minArrLength, | ||
RpptROIPtr | roiTensorPtrSrc, | ||
RpptRoiType | roiType, | ||
rppHandle_t | rppHandle | ||
) |
Tensor min operation on HOST backend for a NCHW/NHWC layout tensor.
The tensor min is a reduction operation that finds the channel-wise (R min / G min / B min) and overall min for each image in a batch of RGB(3 channel) / greyscale(1 channel) images with an NHWC/NCHW tensor layout.
- srcPtr depth ranges - Rpp8u (0 to 255), Rpp16f (0 to 1), Rpp32f (0 to 1), Rpp8s (-128 to 127).
- dstPtr depth ranges - Will be same depth as srcPtr.
- Parameters
-
[in] srcPtr source tensor in HOST memory [in] srcDescPtr source tensor descriptor (Restrictions - numDims = 4, offsetInBytes >= 0, dataType = U8/F16/F32/I8, layout = NCHW/NHWC, c = 1/3) [out] minArr destination array in HOST memory [in] minArrLength length of provided destination array (Restrictions - if srcDescPtr->c == 1 then tensorSumArrLength >= srcDescPtr->n, and if srcDescPtr->c == 3 then tensorSumArrLength >= srcDescPtr->n * 4) [in] roiTensorPtrSrc ROI data in HOST memory, for each image in source tensor (2D tensor of size batchSize * 4, in either format - XYWH(xy.x, xy.y, roiWidth, roiHeight) or LTRB(lt.x, lt.y, rb.x, rb.y)) | (Restrictions - roiTensorSrc[i].xywhROI.roiWidth <= 3840 and roiTensorSrc[i].xywhROI.roiHeight <= 2160) [in] roiType ROI type used (RpptRoiType::XYWH or RpptRoiType::LTRB) [in] rppHandle RPP HOST handle created with rppCreateWithBatchSize()
- Returns
- A
RppStatus
enumeration.
- Return values
-
RPP_SUCCESS Successful completion. RPP_ERROR* Unsuccessful completion.
◆ rppt_tensor_stddev_gpu()
RppStatus rppt_tensor_stddev_gpu | ( | RppPtr_t | srcPtr, |
RpptDescPtr | srcDescPtr, | ||
RppPtr_t | tensorStddevArr, | ||
Rpp32u | tensorStddevArrLength, | ||
Rpp32f * | meanTensor, | ||
RpptROIPtr | roiTensorPtrSrc, | ||
RpptRoiType | roiType, | ||
rppHandle_t | rppHandle | ||
) |
Tensor stddev operation on HIP backend for a NCHW/NHWC layout tensor.
The tensor stddev is a reduction operation that finds the channel-wise (R stddev / G stddev / B stddev) and total standard deviation for each image with respect to meanTensor passed.
- srcPtr depth ranges - Rpp8u (0 to 255), Rpp16f (0 to 1), Rpp32f (0 to 1), Rpp8s (-128 to 127).
- dstPtr depth ranges - Will be same depth as srcPtr.
- Parameters
-
[in] srcPtr source tensor in HIP memory [in] srcDescPtr source tensor descriptor (Restrictions - numDims = 4, offsetInBytes >= 0, dataType = U8/F16/F32/I8, layout = NCHW/NHWC, c = 1/3) [out] tensorStddevArr destination array in HIP memory [in] tensorStddevArrLength length of provided destination array (Restrictions - if srcDescPtr->c == 1 then tensorStddevArrLength = srcDescPtr->n, and if srcDescPtr->c == 3 then tensorStddevArrLength = srcDescPtr->n * 4) [in] meanTensor mean values for stddev calculation (1D tensor of size batchSize * 4 in format (MeanR, MeanG, MeanB, MeanImage) for each image in batch) [in] roiTensorPtrSrc ROI data in HIP memory, for each image in source tensor (2D tensor of size batchSize * 4, in either format - XYWH(xy.x, xy.y, roiWidth, roiHeight) or LTRB(lt.x, lt.y, rb.x, rb.y)) | (Restrictions - roiTensorSrc[i].xywhROI.roiWidth <= 3840 and roiTensorSrc[i].xywhROI.roiHeight <= 2160) [in] roiType ROI type used (RpptRoiType::XYWH or RpptRoiType::LTRB) [in] rppHandle RPP HIP handle created with rppCreateWithStreamAndBatchSize()
- Returns
- A
RppStatus
enumeration.
- Return values
-
RPP_SUCCESS Successful completion. RPP_ERROR* Unsuccessful completion.
◆ rppt_tensor_stddev_host()
RppStatus rppt_tensor_stddev_host | ( | RppPtr_t | srcPtr, |
RpptDescPtr | srcDescPtr, | ||
RppPtr_t | tensorStddevArr, | ||
Rpp32u | tensorStddevArrLength, | ||
Rpp32f * | meanTensor, | ||
RpptROIPtr | roiTensorPtrSrc, | ||
RpptRoiType | roiType, | ||
rppHandle_t | rppHandle | ||
) |
Tensor stddev operation on HOST backend for a NCHW/NHWC layout tensor.
The tensor stddev is a reduction operation that finds the channel-wise (R stddev / G stddev / B stddev) and total standard deviation for each image with respect to meanTensor passed.
- srcPtr depth ranges - Rpp8u (0 to 255), Rpp16f (0 to 1), Rpp32f (0 to 1), Rpp8s (-128 to 127).
- dstPtr depth ranges - Will be same depth as srcPtr.
- Parameters
-
[in] srcPtr source tensor in HOST memory [in] srcDescPtr source tensor descriptor (Restrictions - numDims = 4, offsetInBytes >= 0, dataType = U8/F16/F32/I8, layout = NCHW/NHWC, c = 1/3) [out] tensorStddevArr destination array in HOST memory [in] tensorStddevArrLength length of provided destination array (Restrictions - if srcDescPtr->c == 1 then tensorStddevArrLength = srcDescPtr->n, and if srcDescPtr->c == 3 then tensorStddevArrLength = srcDescPtr->n * 4) [in] meanTensor mean values for stddev calculation (1D tensor of size batchSize * 4 in format (MeanR, MeanG, MeanB, MeanImage) for each image in batch) [in] roiTensorPtrSrc ROI data in HOST memory, for each image in source tensor (2D tensor of size batchSize * 4, in either format - XYWH(xy.x, xy.y, roiWidth, roiHeight) or LTRB(lt.x, lt.y, rb.x, rb.y)) | (Restrictions - roiTensorSrc[i].xywhROI.roiWidth <= 3840 and roiTensorSrc[i].xywhROI.roiHeight <= 2160) [in] roiType ROI type used (RpptRoiType::XYWH or RpptRoiType::LTRB) [in] rppHandle RPP HOST handle created with rppCreateWithBatchSize()
- Returns
- A
RppStatus
enumeration.
- Return values
-
RPP_SUCCESS Successful completion. RPP_ERROR* Unsuccessful completion.
◆ rppt_tensor_sum_gpu()
RppStatus rppt_tensor_sum_gpu | ( | RppPtr_t | srcPtr, |
RpptDescPtr | srcDescPtr, | ||
RppPtr_t | tensorSumArr, | ||
Rpp32u | tensorSumArrLength, | ||
RpptROIPtr | roiTensorPtrSrc, | ||
RpptRoiType | roiType, | ||
rppHandle_t | rppHandle | ||
) |
Tensor sum operation on HIP backend for a NCHW/NHWC layout tensor.
The tensor sum is a reduction operation that finds the channel-wise (R sum / G sum / B sum) and total sum for each image in a batch of RGB(3 channel) / greyscale(1 channel) images with an NHWC/NCHW tensor layout.
- srcPtr depth ranges - Rpp8u (0 to 255), Rpp16f (0 to 1), Rpp32f (0 to 1), Rpp8s (-128 to 127).
- dstPtr depth ranges - Will be same depth as srcPtr.
- Parameters
-
[in] srcPtr source tensor in HIP memory [in] srcDescPtr source tensor descriptor (Restrictions - numDims = 4, offsetInBytes >= 0, dataType = U8/F16/F32/I8, layout = NCHW/NHWC, c = 1/3) [out] tensorSumArr destination array in HIP memory [in] tensorSumArrLength length of provided destination array (Restrictions - if srcDescPtr->c == 1 then tensorSumArrLength >= srcDescPtr->n, and if srcDescPtr->c == 3 then tensorSumArrLength >= srcDescPtr->n * 4) [in] roiTensorPtrSrc ROI data in HIP memory, for each image in source tensor (2D tensor of size batchSize * 4, in either format - XYWH(xy.x, xy.y, roiWidth, roiHeight) or LTRB(lt.x, lt.y, rb.x, rb.y)) | (Restrictions - roiTensorSrc[i].xywhROI.roiWidth <= 3840 and roiTensorSrc[i].xywhROI.roiHeight <= 2160) [in] roiType ROI type used (RpptRoiType::XYWH or RpptRoiType::LTRB) [in] rppHandle RPP HIP handle created with rppCreateWithStreamAndBatchSize()
- Returns
- A
RppStatus
enumeration.
- Return values
-
RPP_SUCCESS Successful completion. RPP_ERROR* Unsuccessful completion.
◆ rppt_tensor_sum_host()
RppStatus rppt_tensor_sum_host | ( | RppPtr_t | srcPtr, |
RpptDescPtr | srcDescPtr, | ||
RppPtr_t | tensorSumArr, | ||
Rpp32u | tensorSumArrLength, | ||
RpptROIPtr | roiTensorPtrSrc, | ||
RpptRoiType | roiType, | ||
rppHandle_t | rppHandle | ||
) |
Tensor sum operation on HOST backend for a NCHW/NHWC layout tensor.
The tensor sum is a reduction operation that finds the channel-wise (R sum / G sum / B sum) and total sum for each image in a batch of RGB(3 channel) / greyscale(1 channel) images with an NHWC/NCHW tensor layout.
- srcPtr depth ranges - Rpp8u (0 to 255), Rpp16f (0 to 1), Rpp32f (0 to 1), Rpp8s (-128 to 127).
- dstPtr depth ranges - Will be same depth as srcPtr.
- Parameters
-
[in] srcPtr source tensor in HOST memory [in] srcDescPtr source tensor descriptor (Restrictions - numDims = 4, offsetInBytes >= 0, dataType = U8/F16/F32/I8, layout = NCHW/NHWC, c = 1/3) [out] tensorSumArr destination array in HOST memory [in] tensorSumArrLength length of provided destination array (Restrictions - if srcDescPtr->c == 1 then tensorSumArrLength >= srcDescPtr->n, and if srcDescPtr->c == 3 then tensorSumArrLength >= srcDescPtr->n * 4) [in] roiTensorPtrSrc ROI data in HOST memory, for each image in source tensor (2D tensor of size batchSize * 4, in either format - XYWH(xy.x, xy.y, roiWidth, roiHeight) or LTRB(lt.x, lt.y, rb.x, rb.y)) | (Restrictions - roiTensorSrc[i].xywhROI.roiWidth <= 3840 and roiTensorSrc[i].xywhROI.roiHeight <= 2160) [in] roiType ROI type used (RpptRoiType::XYWH or RpptRoiType::LTRB) [in] rppHandle RPP HOST handle created with rppCreateWithBatchSize()
- Returns
- A
RppStatus
enumeration.
- Return values
-
RPP_SUCCESS Successful completion. RPP_ERROR* Unsuccessful completion.