BitwiseAND and BitwiseOR on HOST and HIP

.Doxyfile

@@ -967,8 +967,9 @@ INPUT                  = README.md \
                         include/rppt_tensor_geometric_augmentations.h \
                         include/rppt_tensor_morphological_operations.h \
                         include/rppt_tensor_statistical_operations.h \
-                        include/rppt_tensor_arithmetic_operations.h
-                        include/rppt_tensor_audio_augmentations.h
+                        include/rppt_tensor_arithmetic_operations.h \
+                        include/rppt_tensor_audio_augmentations.h \
+                        include/rppt_tensor_logical_operations.h
 
 
 # This tag can be used to specify the character encoding of the source files

docs/doxygen/Doxyfile

@@ -966,7 +966,8 @@ INPUT                  = ../../README.md \
                         ../../include/rppt_tensor_filter_augmentations.h \
                         ../../include/rppt_tensor_geometric_augmentations.h \
                         ../../include/rppt_tensor_morphological_operations.h \
-                        ../../include/rppt_tensor_statistical_operations.h
+                        ../../include/rppt_tensor_statistical_operations.h \
+                        ../../include/rppt_tensor_logical_operations.h
 
 
 # This tag can be used to specify the character encoding of the source files

include/rppt.h

@@ -46,6 +46,7 @@ extern "C" {
 #include "rppt_tensor_arithmetic_operations.h"
 #include "rppt_tensor_statistical_operations.h"
 #include "rppt_tensor_audio_augmentations.h"
+#include "rppt_tensor_logical_operations.h"
 
 #ifdef __cplusplus
 }

include/rppt_tensor_arithmetic_operations.h

@@ -228,21 +228,21 @@ RppStatus rppt_multiply_scalar_gpu(RppPtr_t srcPtr, RpptGenericDescPtr srcGeneri
 RppStatus rppt_magnitude_host(RppPtr_t srcPtr1, RppPtr_t srcPtr2, RpptDescPtr srcDescPtr, RppPtr_t dstPtr, RpptDescPtr dstDescPtr, RpptROIPtr roiTensorPtrSrc, RpptRoiType roiType, rppHandle_t rppHandle);
 
 #ifdef GPU_SUPPORT
-/*! \brief Magnitude computation on HOST backend for a NCHW/NHWC layout tensor
+/*! \brief Magnitude computation on HIP backend for a NCHW/NHWC layout tensor
  * \details This function computes magnitude of corresponding pixels for a batch of RGB(3 channel) / greyscale(1 channel) images with an NHWC/NCHW tensor layout.<br>
  *          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. <br>
  * \image html img150x150.jpg Sample Input1
  * \image html img150x150_2.jpg Sample Input2
  * \image html magnitude_operation_img150x150.jpg Sample Output
- * \param [in] srcPtr1 source1 tensor in HOST memory
- * \param [in] srcPtr2 source2 tensor in HOST memory
+ * \param [in] srcPtr1 source1 tensor in HIP memory
+ * \param [in] srcPtr2 source2 tensor in HIP memory
  * \param [in] srcDescPtr source tensor descriptor (Restrictions - numDims = 4, offsetInBytes >= 0, dataType = U8/F16/F32/I8, layout = NCHW/NHWC, c = 1/3)
- * \param [out] dstPtr destination tensor in HOST memory
+ * \param [out] dstPtr destination tensor in HIP memory
  * \param [in] dstDescPtr destination tensor descriptor (Restrictions - numDims = 4, offsetInBytes >= 0, dataType = U8/F16/F32/I8, layout = NCHW/NHWC, c = same as that of srcDescPtr)
- * \param [in] roiTensorSrc 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))
+ * \param [in] roiTensorSrc 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))
  * \param [in] roiType ROI type used (RpptRoiType::XYWH or RpptRoiType::LTRB)
- * \param [in] rppHandle RPP HOST handle created with <tt>\ref rppCreateWithStreamAndBatchSize()</tt>
+ * \param [in] rppHandle RPP HIP handle created with <tt>\ref rppCreateWithStreamAndBatchSize()</tt>
  * \return A <tt> \ref RppStatus</tt> enumeration.
  * \retval RPP_SUCCESS Successful completion.
  * \retval RPP_ERROR* Unsuccessful completion.
@@ -256,4 +256,4 @@ RppStatus rppt_magnitude_gpu(RppPtr_t srcPtr1, RppPtr_t srcPtr2, RpptDescPtr src
 #ifdef __cplusplus
 }
 #endif
-#endif // RPPT_TENSOR_ARITHMETIC_OPERATIONS_H
+#endif // RPPT_TENSOR_ARITHMETIC_OPERATIONS_H

include/rppt_tensor_logical_operations.h

@@ -0,0 +1,139 @@
+/*
+MIT License
+
+Copyright (c) 2019 - 2024 Advanced Micro Devices, Inc.
+
+Permission is hereby granted, free of charge, to any person obtaining a copy
+of this software and associated documentation files (the "Software"), to deal
+in the Software without restriction, including without limitation the rights
+to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
+copies of the Software, and to permit persons to whom the Software is
+furnished to do so, subject to the following conditions:
+
+The above copyright notice and this permission notice shall be included in all
+copies or substantial portions of the Software.
+
+THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
+IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
+FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
+AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
+LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
+OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
+SOFTWARE.
+*/
+
+#ifndef RPPT_TENSOR_LOGICAL_OPERATIONS_H
+#define RPPT_TENSOR_LOGICAL_OPERATIONS_H
+
+#include "rpp.h"
+#include "rppdefs.h"
+#ifdef __cplusplus
+extern "C" {
+#endif
+
+/*!
+ * \file
+ * \brief RPPT Tensor Operations - Logical Operations.
+ * \defgroup group_tensor_logical_operations RPPT Tensor Operations - Logical Operations.
+ * \brief RPPT Tensor Operations - Logical Operations.
+ */
+
+/*! \addtogroup group_rppt_tensor_logical_operations
+ * @{
+ */
+
+/*! \brief Bitwise AND computation on HOST backend for a NCHW/NHWC layout tensor
+ * \details This function computes bitwise AND of corresponding pixels for a batch of RGB(3 channel) / greyscale(1 channel) images with an NHWC/NCHW tensor layout.<br>
+ *          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.
+ * \image html img150x150.jpg Sample Input1
+ * \image html img150x150_2.jpg Sample Input2
+ * \image html bitwise_and_operation_img150x150.jpg Sample Output
+ * \param [in] srcPtr1 source1 tensor in HOST memory
+ * \param [in] srcPtr2 source2 tensor in HOST memory
+ * \param [in] srcDescPtr source tensor descriptor (Restrictions - numDims = 4, offsetInBytes >= 0, dataType = U8/F16/F32/I8, layout = NCHW/NHWC, c = 1/3)
+ * \param [out] dstPtr destination tensor in HOST memory
+ * \param [in] dstDescPtr destination tensor descriptor (Restrictions - numDims = 4, offsetInBytes >= 0, dataType = U8/F16/F32/I8, layout = NCHW/NHWC, c = same as that of srcDescPtr)
+ * \param [in] roiTensorSrc 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))
+ * \param [in] roiType ROI type used (RpptRoiType::XYWH or RpptRoiType::LTRB)
+ * \param [in] rppHandle RPP HOST handle created with <tt>\ref rppCreateWithBatchSize()</tt>
+ * \return A <tt> \ref RppStatus</tt> enumeration.
+ * \retval RPP_SUCCESS Successful completion.
+ * \retval RPP_ERROR* Unsuccessful completion.
+ */
+RppStatus rppt_bitwise_and_host(RppPtr_t srcPtr1, RppPtr_t srcPtr2, RpptDescPtr srcDescPtr, RppPtr_t dstPtr, RpptDescPtr dstDescPtr, RpptROIPtr roiTensorPtrSrc, RpptRoiType roiType, rppHandle_t rppHandle);
+
+#ifdef GPU_SUPPORT
+/*! \brief Bitwise AND computation on HIP backend for a NCHW/NHWC layout tensor
+ * \details This function computes bitwise AND of corresponding pixels for a batch of RGB(3 channel) / greyscale(1 channel) images with an NHWC/NCHW tensor layout.<br>
+ *          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.
+ * \image html img150x150.jpg Sample Input1
+ * \image html img150x150_2.jpg Sample Input2
+ * \image html bitwise_and_operation_img150x150.jpg Sample Output
+ * \param [in] srcPtr1 source1 tensor in HIP memory
+ * \param [in] srcPtr2 source2 tensor in HIP memory
+ * \param [in] srcDescPtr source tensor descriptor (Restrictions - numDims = 4, offsetInBytes >= 0, dataType = U8/F16/F32/I8, layout = NCHW/NHWC, c = 1/3)
+ * \param [out] dstPtr destination tensor in HIP memory
+ * \param [in] dstDescPtr destination tensor descriptor (Restrictions - numDims = 4, offsetInBytes >= 0, dataType = U8/F16/F32/I8, layout = NCHW/NHWC, c = same as that of srcDescPtr)
+ * \param [in] roiTensorSrc 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))
+ * \param [in] roiType ROI type used (RpptRoiType::XYWH or RpptRoiType::LTRB)
+ * \param [in] rppHandle RPP HIP handle created with <tt>\ref rppCreateWithStreamAndBatchSize()</tt>
+ * \return A <tt> \ref RppStatus</tt> enumeration.
+ * \retval RPP_SUCCESS Successful completion.
+ * \retval RPP_ERROR* Unsuccessful completion.
+ */
+RppStatus rppt_bitwise_and_gpu(RppPtr_t srcPtr1, RppPtr_t srcPtr2, RpptDescPtr srcDescPtr, RppPtr_t dstPtr, RpptDescPtr dstDescPtr, RpptROIPtr roiTensorPtrSrc, RpptRoiType roiType, rppHandle_t rppHandle);
+#endif // GPU_SUPPORT
+
+/*! \brief Bitwise OR computation on HOST backend for a NCHW/NHWC layout tensor
+ * \details This function computes bitwise OR of corresponding pixels for a batch of RGB(3 channel) / greyscale(1 channel) images with an NHWC/NCHW tensor layout.<br>
+ *          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.
+ * \image html img150x150.jpg Sample Input1
+ * \image html img150x150_2.jpg Sample Input2
+ * \image html bitwise_or_operation_img150x150.jpg Sample Output
+ * \param [in] srcPtr1 source1 tensor in HOST memory
+ * \param [in] srcPtr2 source2 tensor in HOST memory
+ * \param [in] srcDescPtr source tensor descriptor (Restrictions - numDims = 4, offsetInBytes >= 0, dataType = U8/F16/F32/I8, layout = NCHW/NHWC, c = 1/3)
+ * \param [out] dstPtr destination tensor in HOST memory
+ * \param [in] dstDescPtr destination tensor descriptor (Restrictions - numDims = 4, offsetInBytes >= 0, dataType = U8/F16/F32/I8, layout = NCHW/NHWC, c = same as that of srcDescPtr)
+ * \param [in] roiTensorSrc 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))
+ * \param [in] roiType ROI type used (RpptRoiType::XYWH or RpptRoiType::LTRB)
+ * \param [in] rppHandle RPP HOST handle created with <tt>\ref rppCreateWithBatchSize()</tt>
+ * \return A <tt> \ref RppStatus</tt> enumeration.
+ * \retval RPP_SUCCESS Successful completion.
+ * \retval RPP_ERROR* Unsuccessful completion.
+ */
+RppStatus rppt_bitwise_or_host(RppPtr_t srcPtr1, RppPtr_t srcPtr2, RpptDescPtr srcDescPtr, RppPtr_t dstPtr, RpptDescPtr dstDescPtr, RpptROIPtr roiTensorPtrSrc, RpptRoiType roiType, rppHandle_t rppHandle);
+
+#ifdef GPU_SUPPORT
+/*! \brief Bitwise OR computation on HIP backend for a NCHW/NHWC layout tensor
+ * \details This function computes bitwise OR of corresponding pixels for a batch of RGB(3 channel) / greyscale(1 channel) images with an NHWC/NCHW tensor layout.<br>
+ *          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.
+ * \image html img150x150.jpg Sample Input1
+ * \image html img150x150_2.jpg Sample Input2
+ * \image html bitwise_or_operation_img150x150.jpg Sample Output
+ * \param [in] srcPtr1 source1 tensor in HIP memory
+ * \param [in] srcPtr2 source2 tensor in HIP memory
+ * \param [in] srcDescPtr source tensor descriptor (Restrictions - numDims = 4, offsetInBytes >= 0, dataType = U8/F16/F32/I8, layout = NCHW/NHWC, c = 1/3)
+ * \param [out] dstPtr destination tensor in HIP memory
+ * \param [in] dstDescPtr destination tensor descriptor (Restrictions - numDims = 4, offsetInBytes >= 0, dataType = U8/F16/F32/I8, layout = NCHW/NHWC, c = same as that of srcDescPtr)
+ * \param [in] roiTensorSrc 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))
+ * \param [in] roiType ROI type used (RpptRoiType::XYWH or RpptRoiType::LTRB)
+ * \param [in] rppHandle RPP HIP handle created with <tt>\ref rppCreateWithStreamAndBatchSize()</tt>
+ * \return A <tt> \ref RppStatus</tt> enumeration.
+ * \retval RPP_SUCCESS Successful completion.
+ * \retval RPP_ERROR* Unsuccessful completion.
+ */
+RppStatus rppt_bitwise_or_gpu(RppPtr_t srcPtr1, RppPtr_t srcPtr2, RpptDescPtr srcDescPtr, RppPtr_t dstPtr, RpptDescPtr dstDescPtr, RpptROIPtr roiTensorPtrSrc, RpptRoiType roiType, rppHandle_t rppHandle);
+#endif // GPU_SUPPORT
+
+/*! @}
+ */
+
+#ifdef __cplusplus
+}
+#endif
+#endif // RPPT_TENSOR_LOGICAL_OPERATIONS_H