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[IE CLDNN] Quantized deeplabv3 optimizations (#646)

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Enabled dilation for imad dw fsv16 kernel
Added argmax and mutable_data to fsv16 white list
Enabled byxf input for quantize scale_shift kernel
This commit is contained in:
Vladimir Paramuzov 2020-06-02 09:17:39 +03:00 committed by GitHub
parent 3863656f44
commit dbdaaa93dd
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GPG Key ID: 4AEE18F83AFDEB23
5 changed files with 12 additions and 4 deletions
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1
inference-engine/thirdparty/clDNN/kernel_selector/core/actual_kernels/convolution/convolution_kernel_b_fs_yx_fsv_16_32_imad_dw.cpp vendored
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@ -66,6 +66,7 @@ ParamsKey kernel_selector::ConvolutionKernel_b_fs_yx_fsv_16_32_imad_dw::GetSuppo
k.EnableQuantization(QuantizationType::ASYMMETRIC_DATA_AND_WEIGHTS);
k.EnableDepthwiseSeparableOpt();
k.EnableGroupedConvolution();
k.EnableDilation();
return k;
}

1
inference-engine/thirdparty/clDNN/kernel_selector/core/actual_kernels/quantize/quantize_kernel_scale_shift_opt.cpp vendored
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@ -33,6 +33,7 @@ ParamsKey QuantizeKernelScaleShift::GetSupportedKey() const {
k.EnableOutputDataType(Datatype::INT8);
k.EnableInputLayout(DataLayout::bfyx);
k.EnableInputLayout(DataLayout::yxfb);
k.EnableInputLayout(DataLayout::byxf);
k.EnableInputLayout(DataLayout::bfzyx);
k.EnableInputLayout(DataLayout::b_fs_yx_fsv16);
k.EnableInputLayout(DataLayout::b_fs_zyx_fsv16);

3
inference-engine/thirdparty/clDNN/src/layout_optimizer.cpp vendored
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@ -367,8 +367,7 @@ bool layout_optimizer::convolution_b_fs_yx_fsv16_opt(layout const &input_layout,
weights_layout.size.batch[0] >= 16 &&
((conv->groups == 1 && conv->split() == 1) ||
conv->groups == static_cast<uint32_t>(input_layout.size.feature[0]) ||
conv->split() == static_cast<int32_t>(input_layout.size.feature[0])) &&
conv->dilation == tensor{ 1 })
conv->split() == static_cast<int32_t>(input_layout.size.feature[0])))
return true;
// Check for grouped convolution
else if (input_layout.size.spatial[2] == 1 && input_layout.size.batch[0] < 16 &&

5
inference-engine/thirdparty/clDNN/src/program.cpp vendored
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@ -46,6 +46,7 @@
#include "deconvolution_inst.h"
#include "detection_output_inst.h"
#include "input_layout_inst.h"
#include "arg_max_min_inst.h"
#include "lstm_inst.h"
#include "lstm_elt_inst.h"
#include "lstm_gemm_inst.h"
@ -1130,7 +1131,9 @@ void program_impl::set_layout_optimizer_attributes(layout_optimizer& lo) {
(prim.type() != cldnn::mvn::type_id()
|| (prim.as<mvn>().input().get_output_layout().data_type != data_types::u8 &&
prim.as<mvn>().input().get_output_layout().data_type != data_types::i8)
|| prim.as<mvn>().get_primitive()->across_channels))
|| prim.as<mvn>().get_primitive()->across_channels) &&
prim.type() != cldnn::arg_max_min::type_id() &&
prim.type() != cldnn::mutable_data::type_id())
can_use_fsv16 = false;
// WA to keep bfyx_f16 layout disabled for some topologies where it leads to regressions.

6
inference-engine/thirdparty/clDNN/tests/test_cases/convolution_gpu_test.cpp vendored
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@ -4746,7 +4746,6 @@ protected:
build_options opts;
opts.set_option(build_option::optimize_data(false));
opts.set_option(build_option::graph_dumps_dir("/tmp/cldnn_dumps/"));
topology topology(input_layout("input", input.get_layout()),
data("weights", weights),
@ -8214,6 +8213,11 @@ struct params_generator : std::vector<convolution_random_test_all_params> {
b, 32, 24, { 19, 19 }, { 3, 3 }, { 1, 1 }, { -1, -1 }, { 2, 2 }, true, 1, input_format, asymm_weights, asymm_data, padded_input });
push_back(convolution_random_test_all_params{
b, 32, 24, { 19, 19 }, { 3, 3 }, { 2, 2 }, { -1, -1 }, { 2, 2 }, true, 1, input_format, asymm_weights, asymm_data, padded_input });
// depthwise + dilation
push_back(convolution_random_test_all_params{
b, 64, 64, { 19, 19 }, { 3, 3 }, { 1, 1 }, { -1, -1 }, { 2, 2 }, true, 64, input_format, asymm_weights, asymm_data, padded_input });
push_back(convolution_random_test_all_params{
b, 64, 64, { 19, 19 }, { 3, 3 }, { 2, 2 }, { -1, -1 }, { 2, 2 }, true, 64, input_format, asymm_weights, asymm_data, padded_input });
}
return *this;
}