Add update/index/output (m+1)/2d/(m+n) support for CLScatter

Resolves: COMPMID-6894, COMPMID-6896

Change-Id: I9d29fd3701a7e0f28d83f81a6c42a7234c2587c3
Signed-off-by: Gunes Bayir <gunes.bayir@arm.com>
Reviewed-on: https://review.mlplatform.org/c/ml/ComputeLibrary/+/11477
Tested-by: Arm Jenkins <bsgcomp@arm.com>
Comments-Addressed: Arm Jenkins <bsgcomp@arm.com>
Reviewed-by: Ramy Elgammal <ramy.elgammal@arm.com>
Dynamic-Fusion: Ramy Elgammal <ramy.elgammal@arm.com>
Benchmark: Arm Jenkins <bsgcomp@arm.com>

5 files changed, 189 insertions, 76 deletions

diff --git a/src/core/CL/cl_kernels/common/scatter.cl b/src/core/CL/cl_kernels/common/scatter.cl
index 73b714e042..ac9f828df2 100644
--- a/src/core/CL/cl_kernels/common/scatter.cl
+++ b/src/core/CL/cl_kernels/common/scatter.cl
@@ -22,8 +22,7 @@
  * SOFTWARE.
  */
 #include "helpers.h"
-
-#if defined(INDICES_SHAPE_Y) && defined(DATA_TYPE) &&  defined(OUT_SHAPE_X) && defined(SCATTER_FUNCTION)
+#include "tile_helpers.h"
 
 // The below defines the various reduce operations for our purposes.
 // Where a corresponds to the existing value, and b the new value.
@@ -33,64 +32,114 @@
 #define MIN_OP(a, b) fmin(a, b)
 #define UPDATE_OP(a, b) (b)
 
-/** Performs the ScatterND operation
- * @note Datatype should be given as a preprocessor argument using -DDATA_TYPE=type. e.g. -DDATA_TYPE=short
- * @note the size of the dst tensor in the "x" dimension should be passed using -DOUT_SHAPE_X at compile time.
- * @note the number of values in the indices tensor in the y-dim should be passed with -DINDICES_SHAPE_Y at compile time.
- * @note Negative indices are treated as out of bounds.
+#ifdef SCATTER_MP1D_2D_MPND
+
+/** This kernel performs scatter operation
+ *
+ * @note Datatype should be given as a compile-time argument using -DDATA_TYPE=type. e.g. -DDATA_TYPE=short
+ * @note Number of indices should be given as a compile-time argument using -DNUM_INDICES, e.g. -DNUM_INDICES=3
+ * @note Index length should be given as a compile-time argument using -DINDEX_LENGTH, e.g. -DINDEX_LENGTH=2
+ * @note Outermost output shapes should be given as a compile-time argument using -DOUT_SHAPE_N_MINUS_X, where
+ *       X must be 1,2,3,4,5, e.g. -DOUT_SHAPE_N_MINUS_1=3, ...
+ * @note Number of elements to copy in a row should be given as a compile-time argument using -DN0, e.g. -DN0=4
+ * @note Number of partial elements at the edge to copy in a row should be given as a compile-time argument using
+ *       -DPARTIAL_N0, e.g. -DPARTIAL_N0=2
+ * @note Scatter function should be given as a compile-time argument using -DSCATTER_FUNCTION, e.g. -DSCATTER_FUNCTION=ADD
+ * @note If the kernel should skip reading the output tensor, -DSKIP_OUTPUT_READ option should be provided.
+ * @note Kernel name in uppercase letters should be provided as a compile-time argument, e.g. -DSCATTER_MP1D_2D_MPND
  *
- * @param[in]  updates_ptr                           Pointer to the source tensor. Supported data types: All
- * @param[in]  updates_stride_x                      Stride of the source tensor in X dimension (in bytes)
- * @param[in]  updates_step_x                        updates_stride_x * number of elements along X processed per work item (in bytes)
- * @param[in]  updates_stride_y                      Stride of the source tensor in Y dimension (in bytes)
- * @param[in]  updates_step_y                        updates_stride_y * number of elements along Y processed per work item (in bytes)
- * @param[in]  updates_stride_z                      Stride of the source tensor in Y dimension (in bytes)
- * @param[in]  updates_step_z                        updates_stride_z * number of elements along Z processed per work item (in bytes)
- * @param[in]  updates_stride_w                      Stride of the source tensor in Z dimension (in bytes)
- * @param[in]  updates_step_w                        updates_stride_w * number of elements along W processed per work item (in bytes)
- * @param[in]  updates_offset_first_element_in_bytes Offset of the first element in the source tensor
- * @param[in]  indices_ptr                           Pointer to the indices vector. Supported data types: S32.
- * @param[in]  indices_stride_x                      Stride of the indices vector in X dimension (in bytes)
- * @param[in]  indices_step_x                        updates_stride_x * number of elements along X processed per work item (in bytes)
- * @param[in]  indices_offset_first_element_in_bytes Offset of the first element in the indices vector
- * @param[out] output_ptr                            Pointer to the destination tensor. Supported data types: same as @p updates_ptr
+ * @param[in]  updates_ptr                           Pointer to the updates tensor. Data Types: F32
+ * @param[in]  updates_stride_x                      Stride of the updates tensor in X dimension (in bytes)
+ * @param[in]  updates_step_x                        updates_stride_x * number of elements along X processed per workitem(in bytes)
+ * @param[in]  updates_stride_y                      Stride of the updates tensor in Y dimension (in bytes)
+ * @param[in]  updates_step_y                        updates_stride_y * number of elements along Y processed per workitem(in bytes)
+ * @param[in]  updates_offset_first_element_in_bytes The offset of the first element in the updates tensor
+ * @param[in]  indices_ptr                           Pointer to the indices tensor. Data Types: S32
+ * @param[in]  indices_stride_x                      Stride of the indices tensor in X dimension (in bytes)
+ * @param[in]  indices_step_x                        indices_stride_x * number of elements along X processed per workitem(in bytes)
+ * @param[in]  indices_stride_y                      Stride of the indices tensor in Y dimension (in bytes)
+ * @param[in]  indices_step_y                        indices_stride_y * number of elements along Y processed per workitem(in bytes)
+ * @param[in]  indices_offset_first_element_in_bytes The offset of the first element in the indices tensor
+ * @param[out] output_ptr                            Pointer to the destination tensor. Same as @p upt_ptr
  * @param[in]  output_stride_x                       Stride of the destination tensor in X dimension (in bytes)
- * @param[in]  output_step_x                         output_stride_x * number of elements along X processed per work item (in bytes)
+ * @param[in]  output_step_x                         output_stride_x * number of elements along X processed per workitem(in bytes)
  * @param[in]  output_stride_y                       Stride of the destination tensor in Y dimension (in bytes)
- * @param[in]  output_step_y                         output_stride_y * number of elements along Y processed per work item (in bytes)
- * @param[in]  output_stride_z                       Stride of the destination tensor in Z dimension (in bytes)
- * @param[in]  output_step_z                         output_stride_z * number of elements along Z processed per work item (in bytes)
- * @param[in]  output_stride_w                       Stride of the destination tensor in W dimension (in bytes)
- * @param[in]  output_step_w                         output_stride_w * number of elements along W processed per work item (in bytes)
- * @param[in]  output_offset_first_element_in_bytes  Offset of the first element in the destination tensor
+ * @param[in]  output_step_y                         output_stride_y * number of elements along Y processed per workitem(in bytes)
+ * @param[in]  output_offset_first_element_in_bytes  The offset of the first element in the destination tensor
+ * @param[in]  upt_block_stride                      Update tensor data block stride in bytes
+ * @param[in]  out_block_stride                      Output tensor data block stride in bytes
  */
-// The below kernel code is expected to be excecuted sequentially with a single thread to ensure a deterministic outcome.
-__kernel void scatter1D(
-    TENSOR4D_DECLARATION(updates),
-    TENSOR4D_DECLARATION(indices),
-    TENSOR4D_DECLARATION(output))
+__kernel void scatter_mp1d_2d_mpnd(
+    IMAGE_DECLARATION(updates),
+    IMAGE_DECLARATION(indices),
+    IMAGE_DECLARATION(output),
+    int upt_block_stride,
+    int out_block_stride
+    )
 {
-    // Currently 1D - only iterate through y dimension of indices.
-    unsigned int* indices_start_offset = (unsigned int*)(indices_ptr + indices_offset_first_element_in_bytes);
-    DATA_TYPE* updates_start_offset = (DATA_TYPE*)(updates_ptr + updates_offset_first_element_in_bytes);
-    DATA_TYPE* out_start_offset = (DATA_TYPE*)(output_ptr + output_offset_first_element_in_bytes);
-    for (int px = 0; px < INDICES_SHAPE_Y; px++)
+    const int out_shape[5] = {OUT_SHAPE_N_MINUS_1, OUT_SHAPE_N_MINUS_2, OUT_SHAPE_N_MINUS_3,
+        OUT_SHAPE_N_MINUS_4, OUT_SHAPE_N_MINUS_5};
+
+    const int x = GET_SPATIAL_IDX(0, N0, PARTIAL_N0); // x-coordinate in the tensor
+    const int y = get_global_id(1); // collapsed y-coordinate (ignoring the outermost dimensions)
+
+    const bool x_cond = (PARTIAL_N0 != 0 && get_global_id(0) == 0);
+
+    uchar *ind_ptr_raw = indices_ptr + indices_offset_first_element_in_bytes;
+    const uchar *out_ptr_raw =  output_ptr + output_offset_first_element_in_bytes
+        + x * sizeof(DATA_TYPE) + y * output_stride_y;
+
+    const uchar *upt_ptr_raw = updates_ptr + updates_offset_first_element_in_bytes
+        + x * sizeof(DATA_TYPE) + y * updates_stride_y;
+
+    for(int index_element = 0; index_element < NUM_INDICES; ++index_element)
     {
-        const int index_value = *(indices_start_offset);
-        DATA_TYPE* out_addr = out_start_offset + index_value;
-        if((index_value < OUT_SHAPE_X) && (index_value >= 0))
+        const int *ind_ptr = (const int *) (ind_ptr_raw);
+
+        // Out of bounds check
+        bool out_of_bounds = false;
+        LOOP_UNROLLING(int, i, 0, 1, INDEX_LENGTH,
+        {
+            if(ind_ptr[i] >= out_shape[i] || ind_ptr[i] < 0)
+            {
+                out_of_bounds = true;
+            }
+        });
+
+        ind_ptr_raw += indices_stride_y;
+
+        if(out_of_bounds)
         {
-            *(__global DATA_TYPE *)(out_addr) = SCATTER_FUNCTION(*(out_addr), *updates_start_offset);
+            continue;
         }
-        // Increment pointers.
-        indices_start_offset++;
-        updates_start_offset++;
+
+        // Index calculation
+        int index = 0;
+        LOOP_UNROLLING(int, i, 0, 1, INDEX_LENGTH,
+        {
+            index = index * out_shape[i] + ind_ptr[i];
+        });
+
+        DATA_TYPE *out_ptr = (DATA_TYPE *) (out_ptr_raw + index * out_block_stride);
+
+        const DATA_TYPE *upt_ptr = (const DATA_TYPE *) (upt_ptr_raw + index_element * upt_block_stride);
+
+        VEC_DATA_TYPE(DATA_TYPE, N0) data_in0 = VLOAD(N0)(0, (__global DATA_TYPE *) upt_ptr);
+
+#ifdef SKIP_OUTPUT_READ
+        STORE_VECTOR_SELECT(data_in, DATA_TYPE, (__global DATA_TYPE *) out_ptr, N0, PARTIAL_N0, x_cond);
+#else // ifdef SKIP_OUTPUT_READ
+        VEC_DATA_TYPE(DATA_TYPE, N0) data_out0 = VLOAD(N0)(0, (__global DATA_TYPE *) out_ptr);
+        data_out0 = SCATTER_FUNCTION(data_out0, data_in0);
+
+        STORE_VECTOR_SELECT(data_out, DATA_TYPE, (__global DATA_TYPE *) out_ptr, N0, PARTIAL_N0, x_cond);
+#endif // ifdef SKIP_OUTPUT_READ
     }
 }
 
-#endif //defined(DATA_TYPE) && defined(SCATTER_FUNCTION) && defined(OUT_SHAPE_X) && defined(INDICES_SHAPE_Y)
+#endif // SCATTER_MP1D_2D_MPND
 
-#if defined(DATA_TYPE) && defined(SCATTER_FUNCTION) && defined(OUT_SHAPE_X) && !defined(INDICES_SHAPE_Y)
+#ifdef SCATTER1D_PARALLEL
 
 // NOTE : This code is non-deterministic and can only be excecuted with the "update" ScatterFunction
 // This code is currently unusued as it requires changes to the existing test suite.
@@ -114,4 +163,4 @@ __kernel void scatter1D_parallel(
     }
 }
 
-#endif //defined(DATA_TYPE) && defined(SCATTER_FUNCTION) && defined(OUT_SHAPE_X) && !defined(INDICES_SHAPE_Y)
+#endif // SCATTER1D_PARALLEL
diff --git a/src/gpu/cl/ClKernelLibrary.cpp b/src/gpu/cl/ClKernelLibrary.cpp
index 3e32a27d03..c4117b8a1a 100644
--- a/src/gpu/cl/ClKernelLibrary.cpp
+++ b/src/gpu/cl/ClKernelLibrary.cpp
@@ -441,6 +441,7 @@ const std::map<std::string, std::string> ClKernelLibrary::_kernel_program_map =
     {"reorg_layer_nhwc", "nhwc/reorg_layer.cl"},
     {"scale_nearest_neighbour_nhwc", "nhwc/scale.cl"},
     {"scale_bilinear_nhwc", "nhwc/scale.cl"},
+    {"scatter_mp1d_2d_mpnd", "common/scatter.cl"},
     {"scatter1D", "common/scatter.cl"},
     {"space_to_batch_nhwc", "nhwc/space_to_batch.cl"},
     {"space_to_batch_static_nhwc", "nhwc/space_to_batch.cl"},
diff --git a/src/gpu/cl/kernels/ClScatterKernel.cpp b/src/gpu/cl/kernels/ClScatterKernel.cpp
index c95e156679..9c25b63c72 100644
--- a/src/gpu/cl/kernels/ClScatterKernel.cpp
+++ b/src/gpu/cl/kernels/ClScatterKernel.cpp
@@ -27,17 +27,26 @@
 #include "arm_compute/core/ITensorPack.h"
 #include "arm_compute/core/TensorInfo.h"
 #include "arm_compute/core/Utils.h"
+#include "arm_compute/core/utils/helpers/AdjustVecSize.h"
 
 #include "src/common/utils/Log.h"
 #include "src/core/helpers/WindowHelpers.h"
 #include "support/Cast.h"
 
+#include <cstdint>
+
 namespace arm_compute
 {
 namespace opencl
 {
 namespace kernels
 {
+
+namespace
+{
+constexpr int max_index_length = 5;
+} // namespace
+
 ClScatterKernel::ClScatterKernel()
 {
 }
@@ -47,21 +56,33 @@ Status ClScatterKernel::validate(const ITensorInfo *updates,
                                  const ITensorInfo *dst,
                                  const ScatterInfo &info)
 {
-    ARM_COMPUTE_ERROR_ON_MISMATCHING_DATA_TYPES(updates, dst);
-    ARM_COMPUTE_ERROR_ON_DATA_TYPE_NOT_IN(indices, DataType::S32);
-    ARM_COMPUTE_ERROR_ON_DATA_TYPE_NOT_IN(dst, DataType::F32);
-    ARM_COMPUTE_RETURN_ERROR_ON_MSG(dst->num_dimensions() > 1, "Only 1D output tensors are currently supported.");
-    ARM_COMPUTE_RETURN_ERROR_ON_MSG(indices->num_dimensions() > 2, "Only 2D indices tensors are currently supported.");
-    ARM_COMPUTE_RETURN_ERROR_ON_MSG(updates->num_dimensions() > 1, "Only 1D update tensors are currently supported.");
+    ARM_COMPUTE_UNUSED(info);
+
+    const TensorShape &ind_shape = indices->tensor_shape();
+    const TensorShape &upt_shape = updates->tensor_shape();
+    const TensorShape &dst_shape = dst->tensor_shape();
+
+    const int32_t upt_dims = upt_shape.num_dimensions();
+    const int32_t dst_dims = dst_shape.num_dimensions();
+    const int32_t ind_dims = ind_shape.num_dimensions();
+
+    const int32_t index_len = ind_shape[0];
+
+    ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DATA_TYPES(updates, dst);
+    ARM_COMPUTE_RETURN_ERROR_ON_DATA_TYPE_NOT_IN(indices, DataType::S32);
+    ARM_COMPUTE_RETURN_ERROR_ON_DATA_TYPE_NOT_IN(dst, DataType::F32);
+    ARM_COMPUTE_RETURN_ERROR_ON_MSG(ind_dims > 2, "Only 2D indices tensors are currently supported.");
     ARM_COMPUTE_RETURN_ERROR_ON_MSG(
-        indices->tensor_shape().y() != updates->tensor_shape()[updates->num_dimensions() - 1],
+        ind_shape[1] != upt_shape[upt_dims - 1],
         "Height of indices tensor should match size of highest dimension in updates tensor.");
-    ARM_COMPUTE_RETURN_ERROR_ON_MSG(updates->num_dimensions() > dst->num_dimensions(),
-                                    "Update tensor cannot have more dims than output tensor.");
-    ARM_COMPUTE_UNUSED(info);
+    ARM_COMPUTE_RETURN_ERROR_ON_MSG(upt_dims > dst_dims, "Update tensor cannot have more dims than output tensor.");
+
+    ARM_COMPUTE_RETURN_ERROR_ON_MSG(index_len > max_index_length, "Maximum supported index length is 5!");
+    ARM_COMPUTE_RETURN_ERROR_ON(index_len != dst_dims - upt_dims + 1);
 
     return Status{};
 }
+
 void ClScatterKernel::configure(const ClCompileContext &compile_context,
                                 const ITensorInfo      *updates,
                                 const ITensorInfo      *indices,
@@ -71,22 +92,51 @@ void ClScatterKernel::configure(const ClCompileContext &compile_context,
     ARM_COMPUTE_ERROR_ON_NULLPTR(updates, dst, indices);
     ARM_COMPUTE_LOG_PARAMS(updates, indices, dst, info);
 
-    // Configure kernel window
-    const auto indices_shape = indices->tensor_shape();
-    Window     win           = calculate_max_window(
-                      *indices, Steps(indices_shape.x(), indices_shape.y())); // Ensures single thread for deterministic output.
+    const TensorShape &dst_shape = dst->tensor_shape();
+
+    const bool is_scalar_block = updates->num_dimensions() == 1;
+    const int  n0 = adjust_vec_size(16 / updates->element_size(), is_scalar_block ? 1 : updates->dimension(0));
+
+    const int partial_n0 = updates->dimension(0) % n0;
+
+    // The GWS will be 2D [x, y]
+    //  x-dimension refers to the x coordinate of the dst tensor
+    //  y-dimension refers to the collapsed y-coordinate of the data part of the dst tensor
+    Window    win       = calculate_max_window(dst_shape, Steps(n0));
+    const int index_len = indices->dimension(0);
+
+    // Collapse the dimensions corresponding to indices in the execution window
+    for (int i = 0; i < index_len; ++i)
+    {
+        win.set(dst->num_dimensions() - (i + 1), Window::Dimension(0, 1, 1));
+    }
+
+    win = win.collapse(win, 1);
 
     // Set build options
     CLBuildOptions build_opts;
     build_opts.add_option("-DDATA_TYPE=" + get_cl_type_from_data_type(dst->data_type()));
-    build_opts.add_option("-DINDICES_DIMS=" + support::cpp11::to_string(indices->num_dimensions()));
-    build_opts.add_option("-DINDICES_SHAPE_Y=" + support::cpp11::to_string(indices_shape.y()));
-    build_opts.add_option("-DOUT_SHAPE_X=" + support::cpp11::to_string(dst->tensor_shape().x()));
+
+    const int num_dims = dst->num_dimensions();
+
+    build_opts.add_option("-DNUM_INDICES=" + support::cpp11::to_string(indices->dimension(1)));
+    build_opts.add_option("-DINDEX_LENGTH=" + support::cpp11::to_string(index_len));
+
+    // We provide 5 variables to use in a constant array
+    for (int i = 1; i <= max_index_length; i++)
+    {
+        build_opts.add_option("-DOUT_SHAPE_N_MINUS_" + support::cpp11::to_string(i) + "=" +
+                              support::cpp11::to_string(dst_shape[std::max(num_dims - i, 0)]));
+    }
+
+    build_opts.add_option("-DN0=" + support::cpp11::to_string(n0));
+    build_opts.add_option("-DPARTIAL_N0=" + support::cpp11::to_string(partial_n0));
 
     switch (info.func)
     {
         case ScatterFunction::Update:
             build_opts.add_option("-DSCATTER_FUNCTION=UPDATE_OP");
+            build_opts.add_option("-DSKIP_OUTPUT_READ");
             break;
         case ScatterFunction::Add:
             build_opts.add_option("-DSCATTER_FUNCTION=ADD_OP");
@@ -105,9 +155,12 @@ void ClScatterKernel::configure(const ClCompileContext &compile_context,
     }
 
     // Create kernel
-    std::string kernel_name("scatter1D");
+    std::string kernel_name = "scatter_mp1d_2d_mpnd";
+    build_opts.add_option("-D" + upper_string(kernel_name));
+
     ICLKernel::configure_internal(win);
     _kernel = create_kernel(compile_context, kernel_name, build_opts.options());
+
     // Set config_id for enabling LWS tuning
     _config_id = kernel_name;
     _config_id += "_";
@@ -123,18 +176,29 @@ void ClScatterKernel::configure(const ClCompileContext &compile_context,
 
 void ClScatterKernel::run_op(ITensorPack &tensors, const Window &window, cl::CommandQueue &queue)
 {
-    unsigned int idx = 0;
-
-    Window window_collapsed = window.collapse_if_possible(ICLKernel::window(), Window::DimZ);
-
     const auto updates =
         utils::cast::polymorphic_downcast<const ICLTensor *>(tensors.get_const_tensor(TensorType::ACL_SRC_0));
     const auto indices =
         utils::cast::polymorphic_downcast<const ICLTensor *>(tensors.get_const_tensor(TensorType::ACL_SRC_1));
     auto dst = utils::cast::polymorphic_downcast<ICLTensor *>(tensors.get_tensor(TensorType::ACL_DST));
-    add_4D_tensor_argument(idx, updates, window_collapsed);
-    add_4D_tensor_argument(idx, indices, window_collapsed);
-    add_4D_tensor_argument(idx, dst, window_collapsed);
+
+    const ITensorInfo *dst_info = dst->info();
+    const int          num_dims = dst_info->num_dimensions();
+
+    const int index_len = indices->info()->dimension(0);
+
+    // calculate m-dimensional data block strides in updates and destination tensors
+    const int upt_block_stride = updates->info()->strides_in_bytes()[updates->info()->num_dimensions() - 1];
+    const int out_block_stride = dst_info->strides_in_bytes()[num_dims - index_len];
+
+    unsigned int idx = 0;
+
+    add_2D_tensor_argument(idx, updates, window);
+    add_2D_tensor_argument(idx, indices, window);
+    add_2D_tensor_argument(idx, dst, window);
+
+    _kernel.setArg<cl_int>(idx++, upt_block_stride);
+    _kernel.setArg<cl_int>(idx++, out_block_stride);
 
     enqueue(queue, *this, window, lws_hint());
 }
diff --git a/src/gpu/cl/kernels/ClScatterKernel.h b/src/gpu/cl/kernels/ClScatterKernel.h
index d2a41adde9..e1b469c88e 100644
--- a/src/gpu/cl/kernels/ClScatterKernel.h
+++ b/src/gpu/cl/kernels/ClScatterKernel.h
@@ -37,6 +37,7 @@ namespace opencl
 {
 namespace kernels
 {
+
 class ClScatterKernel : public IClKernel
 {
 public:
diff --git a/src/gpu/cl/operators/ClScatter.cpp b/src/gpu/cl/operators/ClScatter.cpp
index 62711ddfe8..a11ecd7e6a 100644
--- a/src/gpu/cl/operators/ClScatter.cpp
+++ b/src/gpu/cl/operators/ClScatter.cpp
@@ -48,8 +48,6 @@ Status ClScatter::validate(const ITensorInfo *src,
                            const ScatterInfo &info)
 {
     ARM_COMPUTE_RETURN_ERROR_ON_NULLPTR(updates, indices, dst);
-    ARM_COMPUTE_RETURN_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(indices, 1, DataType::S32);
-    ARM_COMPUTE_RETURN_ERROR_ON_DATA_TYPE_NOT_IN(dst, DataType::F32); // Currently, other datatypes are not suppported.
     if (src != nullptr)
     {
         // Check dst/src are same shape and datatype.