COMPMID-1316 Using 8 bit dot product instruction in CLDepthWiseConvolution with QASYMM8
Change-Id: I3fc37bdceaae8b4b1effa51129b71bf352388564
Reviewed-on: https://eu-gerrit-1.euhpc.arm.com/138374
Tested-by: Jenkins <bsgcomp@arm.com>
Reviewed-by: Anthony Barbier <anthony.barbier@arm.com>
Reviewed-by: Gian Marco Iodice <gianmarco.iodice@arm.com>
diff --git a/src/core/CL/kernels/CLDepthwiseConvolutionLayer3x3NHWCKernel.cpp b/src/core/CL/kernels/CLDepthwiseConvolutionLayer3x3NHWCKernel.cpp
index 7754e1b..610bfb5 100644
--- a/src/core/CL/kernels/CLDepthwiseConvolutionLayer3x3NHWCKernel.cpp
+++ b/src/core/CL/kernels/CLDepthwiseConvolutionLayer3x3NHWCKernel.cpp
@@ -82,23 +82,26 @@
std::pair<Status, Window> validate_and_configure_window(ITensorInfo *input, ITensorInfo *weights, ITensorInfo *bias, ITensorInfo *output,
const PadStrideInfo &conv_info)
{
+ // Get convolved dimensions
+ const TensorShape output_shape = compute_depthwise_convolution_shape(*input, *weights, conv_info, 1 /* depth_multiplier */);
+
+ // Output auto inizialitation if not yet initialized
+ auto_init_if_empty(*output,
+ output_shape,
+ 1,
+ input->data_type(),
+ input->quantization_info());
+
const bool is_qasymm = is_data_type_quantized_asymmetric(input->data_type());
const bool is_stride_1 = ((conv_info.stride().first == conv_info.stride().second) && (conv_info.stride().first == 1));
- const unsigned int num_rows_processed_per_iteration = is_qasymm ? 4 : (is_stride_1 ? 2 : 1);
+ const unsigned int num_rows_processed_per_iteration = is_stride_1 ? 2 : 1;
const unsigned int num_elems_accessed_per_iteration = is_qasymm ? 4 : 2;
const unsigned int num_rows_read_per_iteration = num_rows_processed_per_iteration + 2;
const unsigned int num_rows_written_per_iteration = std::ceil(num_rows_processed_per_iteration / static_cast<float>(conv_info.stride().first));
BorderSize border_size;
- if(is_qasymm)
- {
- border_size = BorderSize(std::max(conv_info.pad_left(), conv_info.pad_top()), 0, std::max(conv_info.pad_right(), conv_info.pad_bottom()), 0);
- }
- else
- {
- border_size = BorderSize(conv_info.pad_left(), 0, std::max(std::max(conv_info.pad_right(), conv_info.pad_bottom()), conv_info.pad_top()), 0);
- }
+ border_size = BorderSize(conv_info.pad_left(), 0, std::max(std::max(conv_info.pad_right(), conv_info.pad_bottom()), conv_info.pad_top()), 0);
// Configure kernel window
Window win = calculate_max_window(*output, Steps(num_elems_accessed_per_iteration, num_rows_written_per_iteration));
@@ -163,20 +166,12 @@
_weights = weights;
_biases = biases;
_conv_stride_y = conv_info.stride().second;
- _num_rows_processed_per_iteration = is_qasymm ? 4 : (is_stride_1 ? 2 : 1);
- _num_planes_processed_per_iteration = (is_stride_1 && !is_qasymm) ? 2 : 1;
+ _num_rows_processed_per_iteration = is_stride_1 ? 2 : 1;
+ _num_planes_processed_per_iteration = is_stride_1 ? 2 : 1;
+ _border_size = BorderSize(conv_info.pad_left(), 0, std::max(std::max(conv_info.pad_right(), conv_info.pad_bottom()), conv_info.pad_top()), 0);
const unsigned int num_elems_accessed_per_iteration = is_qasymm ? 4 : 2;
- if(is_qasymm)
- {
- _border_size = BorderSize(std::max(conv_info.pad_left(), conv_info.pad_top()), 0, std::max(conv_info.pad_right(), conv_info.pad_bottom()), 0);
- }
- else
- {
- _border_size = BorderSize(conv_info.pad_left(), 0, std::max(std::max(conv_info.pad_right(), conv_info.pad_bottom()), conv_info.pad_top()), 0);
- }
-
CLBuildOptions build_opts;
build_opts.add_option_if(_biases != nullptr, "-DHAS_BIAS");
build_opts.add_option("-DVEC_SIZE=" + support::cpp11::to_string(num_elems_accessed_per_iteration));
@@ -226,7 +221,8 @@
}
}
}
- else if(is_stride_1)
+
+ if(is_stride_1)
{
build_opts.add_option("-DNUM_ROWS_PROCESSED=" + support::cpp11::to_string(_num_rows_processed_per_iteration));
build_opts.add_option("-DNUM_PLANES_PROCESSED=" + support::cpp11::to_string(_num_planes_processed_per_iteration));
@@ -239,11 +235,9 @@
}
// Create kernel
- std::string kernel_name = std::string("depthwise_convolution_3x3") + (is_qasymm ? std::string("_quantized") : std::string()) + std::string("_nhwc");
- if(is_qasymm || is_stride_1)
- {
- kernel_name += std::string("_stride") + support::cpp11::to_string(conv_stride_x);
- }
+ const bool is_dot8_supported = dot8_supported(CLKernelLibrary::get().get_device());
+ std::string kernel_name = std::string("depthwise_convolution_3x3") + (is_qasymm ? std::string("_quantized") + ((is_dot8_supported
+ && is_stride_1 /* FIXME (COMPMID-1424) */) ? "_dot8" : "") : "") + "_nhwc" + (is_stride_1 ? "_stride1" : "");
_kernel = static_cast<cl::Kernel>(CLKernelLibrary::get().create_kernel(kernel_name, build_opts.options()));
@@ -299,23 +293,19 @@
Window slice_in = win_in.first_slice_window_3D();
Window slice_out = win.first_slice_window_3D();
+ unsigned int idx = 3 * num_arguments_per_3D_tensor();
+
if(_biases != nullptr)
{
- unsigned int idx = 3 * num_arguments_per_3D_tensor();
- Window win_biases;
+ Window win_biases;
win_biases.use_tensor_dimensions(_biases->info()->tensor_shape());
win_biases.set_dimension_step(Window::DimX, window.x().step());
add_1D_tensor_argument(idx, _biases, win_biases);
}
- if(!(is_data_type_quantized_asymmetric(_input->info()->data_type())))
- {
- unsigned int idx = 3 * num_arguments_per_3D_tensor() + ((_biases != nullptr) ? num_arguments_per_1D_tensor() : 0);
- const int max_offset = _input->info()->strides_in_bytes().z() * _input->info()->dimension(2) - (_input->info()->padding().bottom + _input->info()->padding().top) *
- _input->info()->strides_in_bytes().y();
-
- _kernel.setArg(idx, max_offset);
- }
+ const int max_offset = _input->info()->strides_in_bytes().z() * _input->info()->dimension(2) - (_input->info()->padding().bottom + _input->info()->padding().top) *
+ _input->info()->strides_in_bytes().y();
+ _kernel.setArg(idx, max_offset);
do
{