COMPMID-2306: CLDepthwiseConvolution: support for QUANT8_PER_CHANNEL_SYMM
Change-Id: I18c886400daa2dcba0b91011bc4e503d807a4732
Signed-off-by: Michele Di Giorgio <michele.digiorgio@arm.com>
Reviewed-on: https://review.mlplatform.org/c/2143
Comments-Addressed: Arm Jenkins <bsgcomp@arm.com>
Reviewed-by: Giorgio Arena <giorgio.arena@arm.com>
Tested-by: Arm Jenkins <bsgcomp@arm.com>
diff --git a/src/core/CL/kernels/CLDepthwiseConvolutionLayerNativeKernel.cpp b/src/core/CL/kernels/CLDepthwiseConvolutionLayerNativeKernel.cpp
index 2115fc6..3fc236e 100644
--- a/src/core/CL/kernels/CLDepthwiseConvolutionLayerNativeKernel.cpp
+++ b/src/core/CL/kernels/CLDepthwiseConvolutionLayerNativeKernel.cpp
@@ -42,13 +42,13 @@
namespace
{
Status validate_arguments(const ITensorInfo *input, const ITensorInfo *weights, const ITensorInfo *biases, const ITensorInfo *output, const DWCWeightsKernelInfo &dwc_weights_info,
- const DWCKernelInfo &dwc_info, const PadStrideInfo &conv_info, unsigned int depth_multiplier, const Size2D &dilation)
+ const DWCKernelInfo &dwc_info, const PadStrideInfo &conv_info, unsigned int depth_multiplier, const Size2D &dilation,
+ const ITensorInfo *output_multipliers, const ITensorInfo *output_shifts)
{
ARM_COMPUTE_UNUSED(dwc_info);
ARM_COMPUTE_RETURN_ERROR_ON_F16_UNSUPPORTED(input);
ARM_COMPUTE_RETURN_ERROR_ON_DATA_LAYOUT_NOT_IN(input, DataLayout::NHWC);
ARM_COMPUTE_RETURN_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(input, 1, DataType::QASYMM8, DataType::F16, DataType::F32);
- ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DATA_TYPES(input, weights);
ARM_COMPUTE_RETURN_ERROR_ON(depth_multiplier > 1 && dwc_weights_info.n0 != 1);
ARM_COMPUTE_RETURN_ERROR_ON(conv_info.stride().first < 1);
ARM_COMPUTE_RETURN_ERROR_ON(conv_info.stride().second < 1);
@@ -57,24 +57,53 @@
ARM_COMPUTE_UNUSED(idx_c);
ARM_COMPUTE_RETURN_ERROR_ON(weights->dimension(idx_c) != (input->dimension(idx_c) * depth_multiplier));
+ const TensorShape output_shape = arm_compute::misc::shape_calculator::compute_depthwise_convolution_shape(*input, *weights, conv_info, depth_multiplier, dilation);
+
+ const bool is_quantized = is_data_type_quantized(input->data_type());
+
if(biases != nullptr)
{
- ARM_COMPUTE_RETURN_ERROR_ON(biases->dimension(0) != weights->dimension(0));
+ ARM_COMPUTE_RETURN_ERROR_ON(biases->dimension(0) != output_shape[idx_c]);
ARM_COMPUTE_RETURN_ERROR_ON(biases->num_dimensions() > 1);
- if(is_data_type_quantized(input->data_type()))
+ if(is_quantized)
{
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_MISMATCHING_DATA_TYPES(input, biases);
}
}
+ if(is_quantized)
+ {
+ ARM_COMPUTE_RETURN_ERROR_ON_NULLPTR(output_multipliers, output_shifts);
+ ARM_COMPUTE_RETURN_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(output_multipliers, 1, DataType::S32);
+ ARM_COMPUTE_RETURN_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(output_shifts, 1, DataType::S32);
+ ARM_COMPUTE_RETURN_ERROR_ON(output_multipliers->num_dimensions() > 1);
+ ARM_COMPUTE_RETURN_ERROR_ON(output_shifts->num_dimensions() > 1);
+
+ if(is_data_type_quantized_per_channel(weights->data_type()))
+ {
+ ARM_COMPUTE_RETURN_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(weights, 1, DataType::QSYMM8_PER_CHANNEL);
+ ARM_COMPUTE_RETURN_ERROR_ON(output_shape[idx_c] != output_multipliers->dimension(0));
+ ARM_COMPUTE_RETURN_ERROR_ON(output_shape[idx_c] != output_shifts->dimension(0));
+ }
+ else
+ {
+ ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DATA_TYPES(input, weights);
+ ARM_COMPUTE_RETURN_ERROR_ON(1 != output_multipliers->dimension(0));
+ ARM_COMPUTE_RETURN_ERROR_ON(1 != output_shifts->dimension(0));
+ }
+ }
+ else
+ {
+ ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DATA_TYPES(input, weights);
+ }
+
if(output->total_size() != 0)
{
- const TensorShape output_shape = arm_compute::misc::shape_calculator::compute_depthwise_convolution_shape(*input, *weights, conv_info, depth_multiplier, dilation);
ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DIMENSIONS(output->tensor_shape(), output_shape);
}
@@ -82,7 +111,8 @@
}
std::pair<Status, Window> validate_and_configure_window(ITensorInfo *input, ITensorInfo *weights, ITensorInfo *bias, ITensorInfo *output, const DWCWeightsKernelInfo &dwc_weights_info,
- const DWCKernelInfo &dwc_info, const PadStrideInfo &conv_info, unsigned int depth_multiplier, const Size2D &dilation)
+ const DWCKernelInfo &dwc_info, const PadStrideInfo &conv_info, unsigned int depth_multiplier, const Size2D &dilation,
+ ITensorInfo *output_multipliers, ITensorInfo *output_shifts)
{
ARM_COMPUTE_UNUSED(dwc_info);
@@ -113,6 +143,21 @@
window_changed = update_window_and_padding(win, input_access, weights_access, output_access);
}
+ if(is_data_type_quantized(input->data_type()))
+ {
+ if((output_multipliers != nullptr) && (output_shifts != nullptr))
+ {
+ AccessWindowHorizontal output_multipliers_access(output_multipliers, 0, n0);
+ AccessWindowHorizontal output_shifts_access(output_shifts, 0, n0);
+ window_changed = window_changed || update_window_and_padding(win, output_multipliers_access, output_shifts_access);
+ }
+ else
+ {
+ Status err = ARM_COMPUTE_CREATE_ERROR(ErrorCode::RUNTIME_ERROR, "output_multipliers and output_shifts must be non-nullptr for quantized input");
+ return std::make_pair(err, win);
+ }
+ }
+
output_access.set_valid_region(win, ValidRegion(Coordinates(), output->tensor_shape()));
Status err = (window_changed) ? ARM_COMPUTE_CREATE_ERROR(ErrorCode::RUNTIME_ERROR, "Insufficient Padding!") : Status{};
@@ -121,32 +166,44 @@
} // namespace
CLDepthwiseConvolutionLayerNativeKernel::CLDepthwiseConvolutionLayerNativeKernel()
- : _input(nullptr), _weights(nullptr), _biases(nullptr), _output(nullptr), _depth_multiplier(1)
+ : _input(nullptr),
+ _weights(nullptr),
+ _biases(nullptr),
+ _output(nullptr),
+ _depth_multiplier(1),
+ _output_multipliers(nullptr),
+ _output_shifts(nullptr),
+ _is_quantized(false)
{
}
void CLDepthwiseConvolutionLayerNativeKernel::configure(const ICLTensor *input, const ICLTensor *weights, const ICLTensor *biases, ICLTensor *output, const DWCWeightsKernelInfo &dwc_weights_info,
- const DWCKernelInfo &dwc_info, const PadStrideInfo &conv_info, unsigned int depth_multiplier, const Size2D &dilation)
+ const DWCKernelInfo &dwc_info, const PadStrideInfo &conv_info, unsigned int depth_multiplier, const Size2D &dilation,
+ const ICLTensor *output_multipliers, const ICLTensor *output_shifts)
{
ARM_COMPUTE_ERROR_ON_NULLPTR(input, weights, output);
- ARM_COMPUTE_ERROR_THROW_ON(validate_arguments(input->info(), weights->info(), (biases != nullptr) ? biases->info() : nullptr, output->info(), dwc_weights_info, dwc_info, conv_info, depth_multiplier,
- dilation));
+ ARM_COMPUTE_ERROR_THROW_ON(validate_arguments(input->info(), weights->info(), (biases != nullptr) ? biases->info() : nullptr, output->info(),
+ dwc_weights_info, dwc_info, conv_info, depth_multiplier, dilation,
+ (output_multipliers != nullptr) ? output_multipliers->info() : nullptr, (output_shifts != nullptr) ? output_shifts->info() : nullptr));
- auto win_config = validate_and_configure_window(input->info(), weights->info(), biases != nullptr ? biases->info() : nullptr, output->info(), dwc_weights_info, dwc_info, conv_info, depth_multiplier,
- dilation);
+ auto win_config = validate_and_configure_window(input->info(), weights->info(), biases != nullptr ? biases->info() : nullptr, output->info(),
+ dwc_weights_info, dwc_info, conv_info, depth_multiplier, dilation,
+ (output_multipliers != nullptr) ? output_multipliers->info() : nullptr, (output_shifts != nullptr) ? output_shifts->info() : nullptr);
ARM_COMPUTE_ERROR_THROW_ON(win_config.first);
- _input = input;
- _output = output;
- _weights = weights;
- _biases = biases;
- _depth_multiplier = depth_multiplier;
+ _input = input;
+ _output = output;
+ _weights = weights;
+ _biases = biases;
+ _depth_multiplier = depth_multiplier;
+ _output_multipliers = output_multipliers;
+ _output_shifts = output_shifts;
+ _is_quantized = is_data_type_quantized(input->info()->data_type());
const size_t idx_w = get_data_layout_dimension_index(input->info()->data_layout(), DataLayoutDimension::WIDTH);
const size_t idx_h = get_data_layout_dimension_index(input->info()->data_layout(), DataLayoutDimension::HEIGHT);
const size_t weights_width = weights->info()->dimension(idx_w);
const size_t weights_height = weights->info()->dimension(idx_h);
- const bool is_quantized = is_data_type_quantized(input->info()->data_type());
CLBuildOptions build_opts;
build_opts.add_option_if(_biases != nullptr, "-DHAS_BIAS");
@@ -166,24 +223,18 @@
build_opts.add_option("-DDILATION_X=" + support::cpp11::to_string(dilation.x()));
build_opts.add_option("-DDILATION_Y=" + support::cpp11::to_string(dilation.y()));
- std::string kernel_name = (is_quantized) ? "dwc_MxN_native_quantized8_nhwc" : "dwc_MxN_native_fp_nhwc";
+ std::string kernel_name = (_is_quantized) ? "dwc_MxN_native_quantized8_nhwc" : "dwc_MxN_native_fp_nhwc";
- if(is_quantized)
+ if(_is_quantized)
{
const UniformQuantizationInfo iq_info = _input->info()->quantization_info().uniform();
const UniformQuantizationInfo wq_info = _weights->info()->quantization_info().uniform();
const UniformQuantizationInfo oq_info = _output->info()->quantization_info().uniform();
- float multiplier = iq_info.scale * wq_info.scale / oq_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("-DINPUT_OFFSET=" + support::cpp11::to_string(-iq_info.offset));
build_opts.add_option("-DWEIGHTS_OFFSET=" + support::cpp11::to_string(-wq_info.offset));
build_opts.add_option("-DOUTPUT_OFFSET=" + support::cpp11::to_string(oq_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_if(is_data_type_quantized_per_channel(weights->info()->data_type()), "-DPER_CHANNEL_QUANTIZATION");
if(dwc_info.activation_info.enabled())
{
@@ -199,6 +250,9 @@
build_opts.add_option("-DS1_VAL=" + float_to_string_with_full_precision(s1));
build_opts.add_option("-DO1_VAL=" + support::cpp11::to_string(o1));
}
+
+ build_opts.add_option("-DDATA_TYPE=" + get_cl_type_from_data_type(input->info()->data_type()));
+ build_opts.add_option("-DWEIGHTS_TYPE=" + get_cl_type_from_data_type(weights->info()->data_type()));
}
else
{
@@ -228,12 +282,15 @@
}
Status CLDepthwiseConvolutionLayerNativeKernel::validate(const ITensorInfo *input, const ITensorInfo *weights, const ITensorInfo *biases, const ITensorInfo *output,
- const DWCWeightsKernelInfo &dwc_weights_info, const DWCKernelInfo &dwc_info, const PadStrideInfo &conv_info, unsigned int depth_multiplier, const Size2D &dilation)
+ const DWCWeightsKernelInfo &dwc_weights_info, const DWCKernelInfo &dwc_info, const PadStrideInfo &conv_info,
+ unsigned int depth_multiplier, const Size2D &dilation, const ITensorInfo *output_multipliers, const ITensorInfo *output_shifts)
{
- ARM_COMPUTE_RETURN_ON_ERROR(validate_arguments(input, weights, biases, output, dwc_weights_info, dwc_info, conv_info, depth_multiplier, dilation));
+ ARM_COMPUTE_RETURN_ON_ERROR(validate_arguments(input, weights, biases, output, dwc_weights_info, dwc_info, conv_info, depth_multiplier, dilation, output_multipliers, output_shifts));
ARM_COMPUTE_RETURN_ON_ERROR(validate_and_configure_window(input->clone().get(), weights->clone().get(),
biases != nullptr ? biases->clone().get() : nullptr,
- output->clone().get(), dwc_weights_info, dwc_info, conv_info, depth_multiplier, dilation)
+ output->clone().get(), dwc_weights_info, dwc_info, conv_info, depth_multiplier, dilation,
+ output_multipliers != nullptr ? output_multipliers->clone().get() : nullptr,
+ output_shifts != nullptr ? output_shifts->clone().get() : nullptr)
.first);
return Status{};
@@ -255,15 +312,23 @@
slice_out.set(Window::DimX, Window::Dimension(0, _input->info()->tensor_shape()[0], 1));
}
+ unsigned int idx = 2 * num_arguments_per_4D_tensor() + num_arguments_per_3D_tensor();
+
+ // Set output multipliers in case of quantized data type
+ if(_is_quantized)
+ {
+ add_1D_tensor_argument(idx, _output_multipliers, slice_in);
+ add_1D_tensor_argument(idx, _output_shifts, slice_in);
+ }
+
if(_biases != nullptr)
{
- unsigned int idx = 2 * num_arguments_per_4D_tensor() + num_arguments_per_3D_tensor();
add_1D_tensor_argument(idx, _biases, slice_in);
}
do
{
- unsigned int idx = 0;
+ idx = 0;
add_4D_tensor_argument(idx, _input, slice_in);
add_4D_tensor_argument(idx, _output, slice_out);
add_3D_tensor_argument(idx, _weights, slice_out);