COMPMID-443 Use 3D tensor for pixel multiply (Needed for Normalization Layer)
Change-Id: I117688f12334e6afc705c863acdf71b0bb1fc6e8
Reviewed-on: http://mpd-gerrit.cambridge.arm.com/80352
Tested-by: Kaizen <jeremy.johnson+kaizengerrit@arm.com>
Reviewed-by: Georgios Pinitas <georgios.pinitas@arm.com>
diff --git a/src/core/CL/cl_kernels/pixelwise_mul_float.cl b/src/core/CL/cl_kernels/pixelwise_mul_float.cl
index 89367dc..98127e0 100644
--- a/src/core/CL/cl_kernels/pixelwise_mul_float.cl
+++ b/src/core/CL/cl_kernels/pixelwise_mul_float.cl
@@ -43,31 +43,37 @@
* @param[in] in1_step_x in1_stride_x * number of elements along X processed per workitem(in bytes)
* @param[in] in1_stride_y Stride of the source image in Y dimension (in bytes)
* @param[in] in1_step_y in1_stride_y * number of elements along Y processed per workitem(in bytes)
+ * @param[in] in1_stride_z Stride of the source image in Y dimension (in bytes)
+ * @param[in] in1_step_z in1_stride_z * number of elements along Y processed per workitem(in bytes)
* @param[in] in1_offset_first_element_in_bytes The offset of the first element in the source image
* @param[in] in2_ptr Pointer to the source image. Supported data types: U8, S16, F16, F32
* @param[in] in2_stride_x Stride of the source image in X dimension (in bytes)
* @param[in] in2_step_x in2_stride_x * number of elements along X processed per workitem(in bytes)
* @param[in] in2_stride_y Stride of the source image in Y dimension (in bytes)
* @param[in] in2_step_y in2_stride_y * number of elements along Y processed per workitem(in bytes)
+ * @param[in] in2_stride_z Stride of the source image in Y dimension (in bytes)
+ * @param[in] in2_step_z in2_stride_z * number of elements along Y processed per workitem(in bytes)
* @param[in] in2_offset_first_element_in_bytes The offset of the first element in the source image
* @param[out] out_ptr Pointer to the destination image. Supported data types: U8, S16, F16, F32
* @param[in] out_stride_x Stride of the destination image in X dimension (in bytes)
* @param[in] out_step_x out_stride_x * number of elements along X processed per workitem(in bytes)
* @param[in] out_stride_y Stride of the destination image in Y dimension (in bytes)
* @param[in] out_step_y out_stride_y * number of elements along Y processed per workitem(in bytes)
+ * @param[in] out_stride_z Stride of the destination image in Y dimension (in bytes)
+ * @param[in] out_step_z out_stride_z * number of elements along Y processed per workitem(in bytes)
* @param[in] out_offset_first_element_in_bytes The offset of the first element in the destination image
* @param[in] scale Float scaling factor. Supported data types: F32
*/
__kernel void pixelwise_mul_float(
- IMAGE_DECLARATION(in1),
- IMAGE_DECLARATION(in2),
- IMAGE_DECLARATION(out),
+ TENSOR3D_DECLARATION(in1),
+ TENSOR3D_DECLARATION(in2),
+ TENSOR3D_DECLARATION(out),
const float scale)
{
// Get pixels pointer
- Image in1 = CONVERT_TO_IMAGE_STRUCT(in1);
- Image in2 = CONVERT_TO_IMAGE_STRUCT(in2);
- Image out = CONVERT_TO_IMAGE_STRUCT(out);
+ Tensor3D in1 = CONVERT_TO_TENSOR3D_STRUCT(in1);
+ Tensor3D in2 = CONVERT_TO_TENSOR3D_STRUCT(in2);
+ Tensor3D out = CONVERT_TO_TENSOR3D_STRUCT(out);
// Load data
VEC_DATA_TYPE(DATA_TYPE_RES, 16)
diff --git a/src/core/CL/cl_kernels/pixelwise_mul_int.cl b/src/core/CL/cl_kernels/pixelwise_mul_int.cl
index a407a32..b5734a3 100644
--- a/src/core/CL/cl_kernels/pixelwise_mul_int.cl
+++ b/src/core/CL/cl_kernels/pixelwise_mul_int.cl
@@ -59,31 +59,37 @@
* @param[in] in1_step_x in1_stride_x * number of elements along X processed per workitem(in bytes)
* @param[in] in1_stride_y Stride of the source image in Y dimension (in bytes)
* @param[in] in1_step_y in1_stride_y * number of elements along Y processed per workitem(in bytes)
+ * @param[in] in1_stride_z Stride of the source image in Y dimension (in bytes)
+ * @param[in] in1_step_z in1_stride_z * number of elements along Y processed per workitem(in bytes)
* @param[in] in1_offset_first_element_in_bytes The offset of the first element in the source image
* @param[in] in2_ptr Pointer to the source image. Supported data types: same as @p in1_ptr
* @param[in] in2_stride_x Stride of the source image in X dimension (in bytes)
* @param[in] in2_step_x in2_stride_x * number of elements along X processed per workitem(in bytes)
* @param[in] in2_stride_y Stride of the source image in Y dimension (in bytes)
* @param[in] in2_step_y in2_stride_y * number of elements along Y processed per workitem(in bytes)
+ * @param[in] in2_stride_z Stride of the source image in Y dimension (in bytes)
+ * @param[in] in2_step_z in2_stride_z * number of elements along Y processed per workitem(in bytes)
* @param[in] in2_offset_first_element_in_bytes The offset of the first element in the source image
* @param[out] out_ptr Pointer to the destination image. Supported data types: same as @p in1_ptr
* @param[in] out_stride_x Stride of the destination image in X dimension (in bytes)
* @param[in] out_step_x out_stride_x * number of elements along X processed per workitem(in bytes)
* @param[in] out_stride_y Stride of the destination image in Y dimension (in bytes)
* @param[in] out_step_y out_stride_y * number of elements along Y processed per workitem(in bytes)
+ * @param[in] out_stride_z Stride of the destination image in Y dimension (in bytes)
+ * @param[in] out_step_z out_stride_z * number of elements along Y processed per workitem(in bytes)
* @param[in] out_offset_first_element_in_bytes The offset of the first element in the destination image
* @param[in] scale Integer scaling factor. Supported data types: S32 (ignored for QS8 and QS16 as the assumption is scale = 1).
*/
__kernel void pixelwise_mul_int(
- IMAGE_DECLARATION(in1),
- IMAGE_DECLARATION(in2),
- IMAGE_DECLARATION(out),
+ TENSOR3D_DECLARATION(in1),
+ TENSOR3D_DECLARATION(in2),
+ TENSOR3D_DECLARATION(out),
const uint scale)
{
// Get pixels pointer
- Image in1 = CONVERT_TO_IMAGE_STRUCT(in1);
- Image in2 = CONVERT_TO_IMAGE_STRUCT(in2);
- Image out = CONVERT_TO_IMAGE_STRUCT(out);
+ Tensor3D in1 = CONVERT_TO_TENSOR3D_STRUCT(in1);
+ Tensor3D in2 = CONVERT_TO_TENSOR3D_STRUCT(in2);
+ Tensor3D out = CONVERT_TO_TENSOR3D_STRUCT(out);
// Load data
VEC_DATA_TYPE(DATA_TYPE_RES, 16)
diff --git a/src/core/CL/kernels/CLPixelWiseMultiplicationKernel.cpp b/src/core/CL/kernels/CLPixelWiseMultiplicationKernel.cpp
index b95e8fa..33c8b81 100644
--- a/src/core/CL/kernels/CLPixelWiseMultiplicationKernel.cpp
+++ b/src/core/CL/kernels/CLPixelWiseMultiplicationKernel.cpp
@@ -149,7 +149,7 @@
_kernel = static_cast<cl::Kernel>(CLKernelLibrary::get().create_kernel(kernel_name, build_opts));
// Set scale argument
- unsigned int idx = 3 * num_arguments_per_2D_tensor(); //Skip the inputs and output parameters
+ unsigned int idx = 3 * num_arguments_per_3D_tensor(); //Skip the inputs and output parameters
if(scale_int >= 0)
{
@@ -183,15 +183,15 @@
ARM_COMPUTE_ERROR_ON_UNCONFIGURED_KERNEL(this);
ARM_COMPUTE_ERROR_ON_INVALID_SUBWINDOW(ICLKernel::window(), window);
- Window slice = window.first_slice_window_2D();
+ Window slice = window.first_slice_window_3D();
do
{
unsigned int idx = 0;
- add_2D_tensor_argument(idx, _input1, slice);
- add_2D_tensor_argument(idx, _input2, slice);
- add_2D_tensor_argument(idx, _output, slice);
+ add_3D_tensor_argument(idx, _input1, slice);
+ add_3D_tensor_argument(idx, _input2, slice);
+ add_3D_tensor_argument(idx, _output, slice);
enqueue(queue, *this, slice);
}
- while(window.slide_window_slice_2D(slice));
+ while(window.slide_window_slice_3D(slice));
}