COMPMID-2609: Enable quantization with multiplier greater than 1 on OpenCL
Change-Id: I050f1f84e214e61f7cbb0197a672b68a4940edae
Signed-off-by: Michele Di Giorgio <michele.digiorgio@arm.com>
Reviewed-on: https://review.mlplatform.org/c/2158
Comments-Addressed: Arm Jenkins <bsgcomp@arm.com>
Reviewed-by: Manuel Bottini <manuel.bottini@arm.com>
Tested-by: Arm Jenkins <bsgcomp@arm.com>
Reviewed-by: Giorgio Arena <giorgio.arena@arm.com>
diff --git a/src/core/CL/kernels/CLDirectConvolutionLayerKernel.cpp b/src/core/CL/kernels/CLDirectConvolutionLayerKernel.cpp
index 7b74a5a..e61e5c3 100644
--- a/src/core/CL/kernels/CLDirectConvolutionLayerKernel.cpp
+++ b/src/core/CL/kernels/CLDirectConvolutionLayerKernel.cpp
@@ -38,8 +38,8 @@
#include "arm_compute/core/utils/quantization/AsymmHelpers.h"
#include "support/ToolchainSupport.h"
-using namespace arm_compute;
-
+namespace arm_compute
+{
namespace
{
Status validate_arguments(const ITensorInfo *input, const ITensorInfo *weights, const ITensorInfo *biases, const ITensorInfo *output, const PadStrideInfo &conv_info)
@@ -69,7 +69,8 @@
{
const auto supported_data_layout = is_data_type_quantized(data_type) ? DataLayout::NCHW : DataLayout::NHWC;
const auto error_message = std::string("Only " + string_from_data_layout(supported_data_layout) + " layout is supported for 9x9 convolution with " + string_from_data_type(
- data_type) + " type");
+ data_type)
+ + " type");
ARM_COMPUTE_RETURN_ERROR_ON_MSG((supported_data_layout != data_layout), error_message.c_str());
}
@@ -98,6 +99,17 @@
ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DATA_TYPES(input, output);
}
+ if(is_data_type_quantized(data_type))
+ {
+ const UniformQuantizationInfo iqinfo = input->quantization_info().uniform();
+ const UniformQuantizationInfo wqinfo = weights->quantization_info().uniform();
+ const UniformQuantizationInfo oqinfo = output->quantization_info().uniform();
+
+ float multiplier = iqinfo.scale * wqinfo.scale / oqinfo.scale;
+ int output_multiplier = 0;
+ int output_shift = 0;
+ ARM_COMPUTE_RETURN_ON_ERROR(quantization::calculate_quantized_multiplier(multiplier, &output_multiplier, &output_shift));
+ }
return Status{};
}
@@ -483,8 +495,6 @@
}
else
{
- const bool is_quantized_asymm = is_data_type_quantized_asymmetric(data_type);
- build_options.add_option_if(is_quantized_asymm, std::string("-DKERNEL_SIZE=" + support::cpp11::to_string(kernel_size)));
build_options.add_option(std::string("-DDATA_TYPE=" + get_cl_type_from_data_type(data_type)));
build_options.add_option(std::string("-DDATA_SIZE=" + get_data_size_from_data_type(data_type)));
build_options.add_option(std::string("-DWEIGHTS_DEPTH=" + support::cpp11::to_string(_weights->info()->dimension(channel_idx))));
@@ -508,9 +518,35 @@
}
}
build_options.add_option(std::string("-DDATA_TYPE_PROMOTED=" + get_cl_type_from_data_type(data_type)));
- // Create kernel
- _kernel = static_cast<cl::Kernel>(CLKernelLibrary::get().create_kernel(is_quantized_asymm ? "direct_convolution_quantized" : kernel_name.str(),
- build_options.options()));
+
+ if(is_data_type_quantized(data_type))
+ {
+ const UniformQuantizationInfo iqinfo = _input->info()->quantization_info().uniform();
+ const UniformQuantizationInfo wqinfo = _weights->info()->quantization_info().uniform();
+ const UniformQuantizationInfo oqinfo = _output->info()->quantization_info().uniform();
+
+ float multiplier = iqinfo.scale * wqinfo.scale / oqinfo.scale;
+ int output_multiplier = 0;
+ int output_shift = 0;
+ quantization::calculate_quantized_multiplier(multiplier, &output_multiplier, &output_shift);
+ build_options.add_option("-DOUTPUT_MULTIPLIER=" + support::cpp11::to_string(output_multiplier));
+ build_options.add_option("-DOUTPUT_SHIFT=" + support::cpp11::to_string(output_shift));
+ build_options.add_option("-DKERNEL_SIZE=" + support::cpp11::to_string(kernel_size));
+
+ // Create kernel
+ _kernel = static_cast<cl::Kernel>(CLKernelLibrary::get().create_kernel("direct_convolution_quantized", build_options.options()));
+
+ // Set static kernel arguments
+ unsigned int idx = 3 * num_arguments_per_3D_tensor() + ((_biases != nullptr) ? num_arguments_per_1D_tensor() : 0) + 1;
+ _kernel.setArg(idx++, -iqinfo.offset);
+ _kernel.setArg(idx++, -wqinfo.offset);
+ _kernel.setArg(idx++, oqinfo.offset);
+ }
+ else
+ {
+ // Create kernel
+ _kernel = static_cast<cl::Kernel>(CLKernelLibrary::get().create_kernel(kernel_name.str(), build_options.options()));
+ }
}
// Configure kernel window
@@ -518,27 +554,6 @@
ARM_COMPUTE_ERROR_THROW_ON(win_config.first);
ICLKernel::configure_internal(win_config.second);
- // Set static kernel arguments
- if(is_data_type_quantized_asymmetric(data_type))
- {
- const UniformQuantizationInfo iqinfo = _input->info()->quantization_info().uniform();
- const UniformQuantizationInfo wqinfo = _weights->info()->quantization_info().uniform();
- const UniformQuantizationInfo oqinfo = _output->info()->quantization_info().uniform();
-
- int output_multiplier = 0;
- int output_shift = 0;
-
- float multiplier = iqinfo.scale * wqinfo.scale / oqinfo.scale;
- ARM_COMPUTE_THROW_ON_ERROR(quantization::calculate_quantized_multiplier_less_than_one(multiplier, &output_multiplier, &output_shift));
-
- unsigned int idx = 3 * num_arguments_per_3D_tensor() + ((_biases != nullptr) ? num_arguments_per_1D_tensor() : 0) + 1;
- _kernel.setArg(idx++, -iqinfo.offset);
- _kernel.setArg(idx++, -wqinfo.offset);
- _kernel.setArg(idx++, oqinfo.offset);
- _kernel.setArg(idx++, output_multiplier);
- _kernel.setArg(idx++, output_shift);
- }
-
// Set config_id for enabling LWS tuning
_config_id = "direct_convolution_";
_config_id += lower_string(string_from_data_type(data_type));
@@ -614,3 +629,4 @@
}
while(window.slide_window_slice_3D(slice) && win_in.slide_window_slice_3D(slice_in));
}
+} // namespace arm_compute