Extend direct convolution (F32/F16/QASYMM8)

The new function can handle different block sizes (M0, N0)

New utility macros have been developed to simplify the work and the
future OpenCL kernel development. In particular the work has been done
to also consider cases with:
- the texture pipe support
- dynamic tensor shape support

Change-Id: Ife4c64baf07517938bb8ad18e6a5f4579345c40f
Signed-off-by: Gian Marco Iodice <gianmarco.iodice@arm.com>
Reviewed-on: https://review.mlplatform.org/c/ml/ComputeLibrary/+/5297
Tested-by: Arm Jenkins <bsgcomp@arm.com>
Reviewed-by: Giorgio Arena <giorgio.arena@arm.com>
Comments-Addressed: Arm Jenkins <bsgcomp@arm.com>

1 files changed, 17 insertions, 10 deletions

diff --git a/src/core/gpu/cl/kernels/ClDirectConvolutionKernel.cpp b/src/core/gpu/cl/kernels/ClDirectConvolutionKernel.cpp
index f071dbc468..72801fa6c8 100644
--- a/src/core/gpu/cl/kernels/ClDirectConvolutionKernel.cpp
+++ b/src/core/gpu/cl/kernels/ClDirectConvolutionKernel.cpp
@@ -276,10 +276,12 @@ std::pair<Status, Window> validate_and_configure_window(ITensorInfo *src, ITenso
     if(data_layout == DataLayout::NHWC)
     {
         const unsigned int vec_size = std::min(static_cast<unsigned int>(dst->tensor_shape()[0]), 4u);
+        const unsigned int num_rows = dst->tensor_shape()[0] > 16 ? 2u : 1U;
 
         // Create window and update padding
-        Window win = calculate_max_window(*dst, Steps(vec_size, 1U));
+        Window win = calculate_max_window(*dst, Steps(vec_size, num_rows));
         dst->set_valid_region(ValidRegion(Coordinates(), dst->tensor_shape()));
+
         Status err = Status{};
         return std::make_pair(err, win);
     }
@@ -368,9 +370,9 @@ void ClDirectConvolutionKernel::configure(const CLCompileContext &compile_contex
 
         const unsigned int n0               = win_config.second.x().step();
         const unsigned int m0               = win_config.second.y().step();
-        const unsigned int k0               = adjust_vec_size(16u, src->dimension(channel_idx));
+
+        const unsigned int k0               = adjust_vec_size(8u, src->dimension(channel_idx));
         const unsigned int partial_store_n0 = dst->dimension(channel_idx) % n0;
-        const unsigned int partial_store_m0 = (dst->dimension(width_idx) * dst->dimension(height_idx)) % m0;
         const unsigned int pad_left         = conv_info.pad_left();
         const unsigned int pad_top          = conv_info.pad_top();
 
@@ -379,14 +381,19 @@ void ClDirectConvolutionKernel::configure(const CLCompileContext &compile_contex
             build_options.add_option(std::string("-DHAS_BIAS"));
             build_options.add_option(std::string("-DBIA_DATA_TYPE=" + get_cl_type_from_data_type(biases->data_type())));
         }
+
+        build_options.add_option("-cl-fast-relaxed-math");
+        build_options.add_option("-DSRC_TENSOR_TYPE=BUFFER");
         build_options.add_option("-DSRC_WIDTH=" + support::cpp11::to_string(src->dimension(width_idx)));
         build_options.add_option("-DSRC_HEIGHT=" + support::cpp11::to_string(src->dimension(height_idx)));
         build_options.add_option("-DSRC_CHANNELS=" + support::cpp11::to_string(src->dimension(channel_idx)));
         build_options.add_option("-DSRC_DATA_TYPE=" + get_cl_type_from_data_type(src->data_type()));
+        build_options.add_option("-DDST_TENSOR_TYPE=BUFFER");
         build_options.add_option("-DDST_WIDTH=" + support::cpp11::to_string(dst->dimension(width_idx)));
         build_options.add_option("-DDST_HEIGHT=" + support::cpp11::to_string(dst->dimension(height_idx)));
         build_options.add_option("-DDST_CHANNELS=" + support::cpp11::to_string(dst->dimension(channel_idx)));
         build_options.add_option("-DDST_DATA_TYPE=" + get_cl_type_from_data_type(dst->data_type()));
+        build_options.add_option("-DWEI_TENSOR_TYPE=BUFFER");
         build_options.add_option("-DWEI_WIDTH=" + support::cpp11::to_string(weights->dimension(width_idx)));
         build_options.add_option("-DWEI_HEIGHT=" + support::cpp11::to_string(weights->dimension(height_idx)));
         build_options.add_option("-DWEI_DATA_TYPE=" + get_cl_type_from_data_type(weights->data_type()));
@@ -397,8 +404,7 @@ void ClDirectConvolutionKernel::configure(const CLCompileContext &compile_contex
         build_options.add_option("-DN0=" + support::cpp11::to_string(n0));
         build_options.add_option("-DM0=" + support::cpp11::to_string(m0));
         build_options.add_option("-DK0=" + support::cpp11::to_string(k0));
-        build_options.add_option("-DPARTIAL_STORE_N0=" + support::cpp11::to_string(partial_store_n0));
-        build_options.add_option("-DPARTIAL_STORE_M0=" + support::cpp11::to_string(partial_store_m0));
+        build_options.add_option("-DPARTIAL_N0=" + support::cpp11::to_string(partial_store_n0));
 
         if(is_data_type_quantized(data_type))
         {
@@ -426,6 +432,7 @@ void ClDirectConvolutionKernel::configure(const CLCompileContext &compile_contex
         else
         {
             build_options.add_option("-DACC_DATA_TYPE=" + get_cl_type_from_data_type(data_type));
+            build_options.add_option("-DZERO_VALUE=" + support::cpp11::to_string(0));
             build_options.add_option("-DSRC_OFFSET=" + support::cpp11::to_string(0));
             build_options.add_option("-DWEI_OFFSET=" + support::cpp11::to_string(0));
             build_options.add_option("-DDST_OFFSET=" + support::cpp11::to_string(0));
@@ -529,18 +536,18 @@ void ClDirectConvolutionKernel::run_op(ITensorPack &tensors, const Window &windo
 
     if(_data_layout == DataLayout::NHWC)
     {
-        slice.set(Window::DimY, Window::Dimension(0, dst->info()->dimension(1) * dst->info()->dimension(2), 1));
+        const size_t dim_y_collapsed = ceil_to_multiple(dst->info()->dimension(1) * dst->info()->dimension(2), slice.y().step());
+        slice.set(Window::DimY, Window::Dimension(0, dim_y_collapsed, slice.y().step()));
         slice.set(Window::DimZ, Window::Dimension(0, dst->info()->dimension(3), 1));
 
         unsigned int idx = 0;
-        add_3D_tensor_argument(idx, src, slice);
-        add_3D_tensor_argument(idx, dst, slice);
-        add_3D_tensor_argument(idx, weights, slice);
+        add_4D_tensor_argument(idx, src, slice);
+        add_4D_tensor_argument(idx, dst, slice);
+        add_4D_tensor_argument(idx, weights, slice);
         if(biases != nullptr)
         {
             add_1D_tensor_argument(idx, biases, slice);
         }
-        _kernel.setArg(idx++, static_cast<unsigned int>(weights->info()->strides_in_bytes()[3]));
         enqueue(queue, *this, slice, lws_hint());
     }
     else