COMPMID-811 Add NHWC data format support for CL depthwise convolution
Change-Id: I574f7945f0be009c638d860028bce8b52b4120fd
Reviewed-on: https://eu-gerrit-1.euhpc.arm.com/136484
Tested-by: Jenkins <bsgcomp@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 d24ef0f..1de08aa 100644
--- a/src/core/CL/kernels/CLDepthwiseConvolutionLayer3x3NHWCKernel.cpp
+++ b/src/core/CL/kernels/CLDepthwiseConvolutionLayer3x3NHWCKernel.cpp
@@ -44,18 +44,27 @@
Status validate_arguments(const ITensorInfo *input, const ITensorInfo *weights, const ITensorInfo *biases, const ITensorInfo *output, const PadStrideInfo &conv_info, unsigned int depth_multiplier,
const ActivationLayerInfo &act_info)
{
- ARM_COMPUTE_RETURN_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(input, 1, DataType::QASYMM8);
- ARM_COMPUTE_RETURN_ERROR_ON_MSG((act_info.enabled()) && (act_info.activation() != ActivationLayerInfo::ActivationFunction::LU_BOUNDED_RELU)
- && (act_info.activation() != ActivationLayerInfo::ActivationFunction::BOUNDED_RELU)
- && (act_info.activation() != ActivationLayerInfo::ActivationFunction::RELU),
- "For QASYMM8 only relu, lower bounded relu and lower-upper bounded relu are supported");
+ ARM_COMPUTE_RETURN_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(input, 1, DataType::F32, DataType::QASYMM8);
+ ARM_COMPUTE_RETURN_ERROR_ON_MSG((act_info.enabled()) && (input->data_type() == DataType::F32 || ((act_info.activation() != ActivationLayerInfo::ActivationFunction::LU_BOUNDED_RELU)
+ && (act_info.activation() != ActivationLayerInfo::ActivationFunction::BOUNDED_RELU)
+ && (act_info.activation() != ActivationLayerInfo::ActivationFunction::RELU))),
+ "For QASYMM8 only relu, lower bounded relu and lower-upper bounded relu are supported"); //COMPMID-1317 add fused activation for F32
ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DATA_TYPES(input, weights);
ARM_COMPUTE_RETURN_ERROR_ON(depth_multiplier > 1); // COMPMID-1071 Add depth multiplier support for NHWC
ARM_COMPUTE_RETURN_ERROR_ON(weights->dimension(1) != 3 || weights->dimension(2) != 3);
+ const bool is_qasymm = is_data_type_quantized_asymmetric(input->data_type());
+
if(biases != nullptr)
{
- ARM_COMPUTE_RETURN_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(biases, 1, DataType::S32);
+ if(is_qasymm)
+ {
+ ARM_COMPUTE_RETURN_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(biases, 1, DataType::S32);
+ }
+ else
+ {
+ ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DATA_TYPES(weights, biases);
+ }
ARM_COMPUTE_RETURN_ERROR_ON(biases->dimension(0) != weights->dimension(0));
ARM_COMPUTE_RETURN_ERROR_ON(biases->num_dimensions() > 1);
}
@@ -72,12 +81,23 @@
std::pair<Status, Window> validate_and_configure_window(ITensorInfo *input, ITensorInfo *weights, ITensorInfo *bias, ITensorInfo *output,
const PadStrideInfo &conv_info)
{
- const unsigned int num_rows_processed_per_iteration = 4;
- const unsigned int num_elems_accessed_per_iteration = 4;
- const unsigned int num_rows_read_per_iteration = num_rows_processed_per_iteration + 2;
- const unsigned int num_rows_written_per_iteration = num_rows_processed_per_iteration / conv_info.stride().first;
+ 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 BorderSize border_size(std::max(conv_info.pad_left(), conv_info.pad_top()), 0, std::max(conv_info.pad_right(), conv_info.pad_bottom()), 0);
+ const unsigned int num_rows_processed_per_iteration = is_qasymm ? 4 : (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);
+ }
// Configure kernel window
Window win = calculate_max_window(*output, Steps(num_elems_accessed_per_iteration, num_rows_written_per_iteration));
@@ -103,7 +123,7 @@
} // namespace
CLDepthwiseConvolutionLayer3x3NHWCKernel::CLDepthwiseConvolutionLayer3x3NHWCKernel()
- : _num_rows_processed_per_iteration(1)
+ : _num_rows_processed_per_iteration(1), _num_planes_processed_per_iteration(1)
{
}
@@ -135,66 +155,97 @@
ARM_COMPUTE_ERROR_ON(conv_stride_x < 1 || conv_stride_x > 2);
ARM_COMPUTE_ERROR_ON(std::max(conv_info.pad_top(), conv_info.pad_bottom()) > 1);
- _input = input;
- _output = output;
- _weights = weights;
- _biases = biases;
- _conv_stride_y = conv_info.stride().second;
- _num_rows_processed_per_iteration = 4;
+ const bool is_qasymm = is_data_type_quantized_asymmetric(input->info()->data_type());
+ const bool is_stride_1 = ((conv_info.stride().first == conv_info.stride().second) && (conv_info.stride().first == 1));
- const unsigned int num_elems_accessed_per_iteration = 4;
+ _input = input;
+ _output = output;
+ _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;
- _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);
+ const unsigned int num_elems_accessed_per_iteration = is_qasymm ? 4 : 2;
- float multiplier = _input->info()->quantization_info().scale * _weights->info()->quantization_info().scale / _output->info()->quantization_info().scale;
- int output_multiplier = 0;
- int output_shift = 0;
- quantization::calculate_quantized_multiplier_less_than_one(multiplier, &output_multiplier, &output_shift);
+ 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("-DINPUT_OFFSET=" + support::cpp11::to_string(-_input->info()->quantization_info().offset));
- build_opts.add_option("-DWEIGHTS_OFFSET=" + support::cpp11::to_string(-_weights->info()->quantization_info().offset));
- build_opts.add_option("-DOUTPUT_OFFSET=" + support::cpp11::to_string(_output->info()->quantization_info().offset));
- build_opts.add_option("-DK_OFFSET=" + support::cpp11::to_string(9 * input->info()->quantization_info().offset * weights->info()->quantization_info().offset));
- build_opts.add_option("-DOUTPUT_MULTIPLIER=" + support::cpp11::to_string(output_multiplier));
- build_opts.add_option("-DOUTPUT_SHIFT=" + support::cpp11::to_string(output_shift));
build_opts.add_option("-DVEC_SIZE=" + support::cpp11::to_string(num_elems_accessed_per_iteration));
- build_opts.add_option("-DSRC_DIM_1=" + support::cpp11::to_string(_input->info()->dimension(1)));
build_opts.add_option("-DSRC_DIM_2=" + support::cpp11::to_string(_input->info()->dimension(2)));
build_opts.add_option("-DCONV_PAD_TOP=" + support::cpp11::to_string(conv_info.pad_top()));
build_opts.add_option("-DCONV_PAD_LEFT=" + support::cpp11::to_string(conv_info.pad_left()));
- if(act_info.enabled())
+ if(is_qasymm)
{
- const int a_val = input->info()->quantization_info().quantize(act_info.a(), RoundingPolicy::TO_NEAREST_UP);
- const int b_val = input->info()->quantization_info().quantize(act_info.b(), RoundingPolicy::TO_NEAREST_UP);
- const int o1 = input->info()->quantization_info().offset;
+ float multiplier = _input->info()->quantization_info().scale * _weights->info()->quantization_info().scale / _output->info()->quantization_info().scale;
+ int output_multiplier = 0;
+ int output_shift = 0;
+ quantization::calculate_quantized_multiplier_less_than_one(multiplier, &output_multiplier, &output_shift);
- build_opts.add_option("-DFUSED_ACTIVATION=" + lower_string(string_from_activation_func(act_info.activation())));
- build_opts.add_option("-DA_VAL=" + support::cpp11::to_string(a_val));
- build_opts.add_option("-DB_VAL=" + support::cpp11::to_string(b_val));
- build_opts.add_option("-DCONST_0=" + support::cpp11::to_string(o1));
+ build_opts.add_option("-DSRC_DIM_1=" + support::cpp11::to_string(_input->info()->dimension(1)));
+ build_opts.add_option("-DINPUT_OFFSET=" + support::cpp11::to_string(-_input->info()->quantization_info().offset));
+ build_opts.add_option("-DWEIGHTS_OFFSET=" + support::cpp11::to_string(-_weights->info()->quantization_info().offset));
+ build_opts.add_option("-DOUTPUT_OFFSET=" + support::cpp11::to_string(_output->info()->quantization_info().offset));
+ build_opts.add_option("-DK_OFFSET=" + support::cpp11::to_string(9 * input->info()->quantization_info().offset * weights->info()->quantization_info().offset));
+ build_opts.add_option("-DOUTPUT_MULTIPLIER=" + support::cpp11::to_string(output_multiplier));
+ build_opts.add_option("-DOUTPUT_SHIFT=" + support::cpp11::to_string(output_shift));
- if(output != nullptr)
+ if(act_info.enabled())
{
- const float s1 = input->info()->quantization_info().scale;
- const float s2 = output->info()->quantization_info().scale;
- const int o2 = output->info()->quantization_info().offset;
+ const int a_val = input->info()->quantization_info().quantize(act_info.a(), RoundingPolicy::TO_NEAREST_UP);
+ const int b_val = input->info()->quantization_info().quantize(act_info.b(), RoundingPolicy::TO_NEAREST_UP);
+ const int o1 = input->info()->quantization_info().offset;
- if(o1 != o2 || s1 != s2)
+ build_opts.add_option("-DFUSED_ACTIVATION=" + lower_string(string_from_activation_func(act_info.activation())));
+ build_opts.add_option("-DA_VAL=" + support::cpp11::to_string(a_val));
+ build_opts.add_option("-DB_VAL=" + support::cpp11::to_string(b_val));
+ build_opts.add_option("-DCONST_0=" + support::cpp11::to_string(o1));
+
+ if(output != nullptr)
{
- build_opts.add_option("-DS1_VAL=" + float_to_string_with_full_precision(s1));
- build_opts.add_option("-DS2_VAL=" + float_to_string_with_full_precision(s2));
- build_opts.add_option("-DO1_VAL=" + support::cpp11::to_string(o1));
- build_opts.add_option("-DO2_VAL=" + support::cpp11::to_string(o2));
+ const float s1 = input->info()->quantization_info().scale;
+ const float s2 = output->info()->quantization_info().scale;
+ const int o2 = output->info()->quantization_info().offset;
+
+ if(o1 != o2 || s1 != s2)
+ {
+ build_opts.add_option("-DS1_VAL=" + float_to_string_with_full_precision(s1));
+ build_opts.add_option("-DS2_VAL=" + float_to_string_with_full_precision(s2));
+ build_opts.add_option("-DO1_VAL=" + support::cpp11::to_string(o1));
+ build_opts.add_option("-DO2_VAL=" + support::cpp11::to_string(o2));
+ }
}
}
}
+ else 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));
+ build_opts.add_option("-DDST_DIM_2=" + support::cpp11::to_string(_output->info()->dimension(2)));
+ }
+ else
+ {
+ build_opts.add_option("-DCONV_STRIDE_X=" + support::cpp11::to_string(conv_stride_x));
+ build_opts.add_option("-DCONV_STRIDE_Y=" + support::cpp11::to_string(_conv_stride_y));
+ }
// Create kernel
- std::string kernel_name = std::string("depthwise_convolution_3x3_quantized_nhwc_stride") + support::cpp11::to_string(conv_stride_x);
- _kernel = static_cast<cl::Kernel>(CLKernelLibrary::get().create_kernel(kernel_name, build_opts.options()));
+ 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);
+ }
+
+ _kernel = static_cast<cl::Kernel>(CLKernelLibrary::get().create_kernel(kernel_name, build_opts.options()));
// Configure kernel window
auto win_config = validate_and_configure_window(input->info(), weights->info(), biases != nullptr ? biases->info() : nullptr, output->info(), conv_info);
@@ -213,6 +264,8 @@
_config_id += support::cpp11::to_string(output->info()->dimension(0));
_config_id += "_";
_config_id += support::cpp11::to_string(output->info()->dimension(1));
+ _config_id += "_";
+ _config_id += string_from_data_type(input->info()->data_type());
}
Status CLDepthwiseConvolutionLayer3x3NHWCKernel::validate(const ITensorInfo *input, const ITensorInfo *weights, const ITensorInfo *biases, const ITensorInfo *output, const PadStrideInfo &conv_info,
@@ -233,15 +286,18 @@
ARM_COMPUTE_ERROR_ON_UNCONFIGURED_KERNEL(this);
ARM_COMPUTE_ERROR_ON_INVALID_SUBWINDOW(IKernel::window(), window);
+ Window win = window;
+ win.set(Window::DimZ, Window::Dimension(0, std::ceil(_output->info()->dimension(2) / static_cast<float>(_num_planes_processed_per_iteration)), 1));
+
// Create input window and adjust
- Window win_in = window;
+ Window win_in = win;
win_in.set_dimension_step(Window::DimY, _num_rows_processed_per_iteration);
win_in.set_dimension_step(Window::DimZ, _conv_stride_y);
ARM_COMPUTE_ERROR_ON((win_in.y().step() < window.y().step()) || (win_in.z().step() < window.z().step()));
Window slice_in = win_in.first_slice_window_3D();
- Window slice_out = window.first_slice_window_3D();
+ Window slice_out = win.first_slice_window_3D();
if(_biases != nullptr)
{
@@ -252,6 +308,15 @@
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);
+ }
+
do
{
unsigned int idx = 0;