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[CPU] Fixed fusing Convolution with Sum (#4617)

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This commit is contained in:
Alexandra Sidorova 2021-03-26 10:26:57 +03:00 committed by GitHub
parent 3eac187e2e
commit 54f60ee761
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GPG Key ID: 4AEE18F83AFDEB23
2 changed files with 84 additions and 1 deletions
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1
inference-engine/src/mkldnn_plugin/nodes/mkldnn_conv_node.cpp
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@ -301,6 +301,7 @@ void MKLDNNConvolutionNode::getSupportedDescriptors() {
// bofore the fused convolution. This behaviour might be more correct regarding expected markup
// of the graph but performance of first and second approaches might be different. Need to verify
outputDataType = eltwisePrecision == Precision::BF16 ? memory::data_type::bf16 : memory::data_type::f32;
eltwisePrecision = MKLDNNExtensionUtils::DataTypeToIEPrecision(outputDataType);
}
}
// correction for cases of FP32 input - we do not have FP32 convolution supported BF16 output

84
inference-engine/tests/functional/plugin/cpu/single_layer_tests/convolution.cpp
View File

@ -68,8 +68,10 @@ protected:
if (inPrc == Precision::UNSPECIFIED) {
selectedType += std::string("_") + Precision(Precision::FP32).name();
} else {
} else if (inPrc == Precision::BF16) {
selectedType += std::string("_") + inPrc.name();
} else {
selectedType += std::string("_") + Precision(netPrecision).name();
}
ngraph::op::PadType padType;
@ -202,6 +204,22 @@ INSTANTIATE_TEST_CASE_P(smoke_Conv_2D_Planar_BF16, ConvolutionLayerCPUTest,
::testing::Values(cpuBF16PluginConfig)),
ConvolutionLayerCPUTest::getTestCaseName);
INSTANTIATE_TEST_CASE_P(smoke_Conv_2D_Planar_I8, ConvolutionLayerCPUTest,
::testing::Combine(
::testing::Combine(
convParams_ExplicitPadding_Planar_2D,
::testing::Values(Precision::FP32),
::testing::Values(Precision::I8),
::testing::Values(Precision::UNSPECIFIED),
::testing::Values(Layout::ANY),
::testing::Values(Layout::ANY),
::testing::Values(std::vector<size_t >({ 2, 12, 7, 7 })),
::testing::Values(CommonTestUtils::DEVICE_CPU)),
::testing::ValuesIn(filterCPUInfoForDevice(CPUParams_Planar_2D)),
::testing::Values(fusingSum),
::testing::Values(cpuEmptyPluginConfig)),
ConvolutionLayerCPUTest::getTestCaseName);
/* ============= GroupConvolution (Planar 3D) ============= */
const auto convParams_ExplicitPadding_Planar_3D = ::testing::Combine(
::testing::ValuesIn(kernels3d),
@ -249,6 +267,22 @@ INSTANTIATE_TEST_CASE_P(smoke_Conv_3D_Planar_BF16, ConvolutionLayerCPUTest,
::testing::Values(cpuBF16PluginConfig)),
ConvolutionLayerCPUTest::getTestCaseName);
INSTANTIATE_TEST_CASE_P(smoke_Conv_3D_Planar_I8, ConvolutionLayerCPUTest,
::testing::Combine(
::testing::Combine(
convParams_ExplicitPadding_Planar_3D,
::testing::Values(Precision::FP32),
::testing::Values(Precision::I8),
::testing::Values(Precision::UNSPECIFIED),
::testing::Values(Layout::ANY),
::testing::Values(Layout::ANY),
::testing::Values(std::vector<size_t >({ 2, 12, 7, 7, 7 })),
::testing::Values(CommonTestUtils::DEVICE_CPU)),
::testing::ValuesIn(filterCPUInfoForDevice(CPUParams_Planar_3D)),
::testing::Values(fusingSum),
::testing::Values(cpuEmptyPluginConfig)),
ConvolutionLayerCPUTest::getTestCaseName);
/* ============= GroupConvolution (Blocked 2D) ============= */
const auto convParams_ExplicitPadding_Blocked_2D = ::testing::Combine(
::testing::ValuesIn(kernels2d),
@ -298,6 +332,22 @@ INSTANTIATE_TEST_CASE_P(smoke_Conv_2D_Blocked_BF16, ConvolutionLayerCPUTest,
::testing::Values(cpuBF16PluginConfig)),
ConvolutionLayerCPUTest::getTestCaseName);
INSTANTIATE_TEST_CASE_P(smoke_Conv_2D_Blocked_I8, ConvolutionLayerCPUTest,
::testing::Combine(
::testing::Combine(
convParams_ExplicitPadding_Blocked_2D,
::testing::Values(Precision::FP32),
::testing::Values(Precision::I8),
::testing::Values(Precision::UNSPECIFIED),
::testing::Values(Layout::ANY),
::testing::Values(Layout::ANY),
::testing::Values(std::vector<size_t >({ 2, 64, 7, 7 })),
::testing::Values(CommonTestUtils::DEVICE_CPU)),
::testing::ValuesIn(filterCPUInfoForDevice(CPUParams_Blocked_2D)),
::testing::Values(fusingSum),
::testing::Values(cpuEmptyPluginConfig)),
ConvolutionLayerCPUTest::getTestCaseName);
/* ============= GroupConvolution (Blocked 3D) ============= */
const auto convParams_ExplicitPadding_Blocked_3D = ::testing::Combine(
::testing::ValuesIn(kernels3d),
@ -347,6 +397,22 @@ INSTANTIATE_TEST_CASE_P(smoke_Conv_3D_Blocked_BF16, ConvolutionLayerCPUTest,
::testing::Values(cpuBF16PluginConfig)),
ConvolutionLayerCPUTest::getTestCaseName);
INSTANTIATE_TEST_CASE_P(smoke_Conv_3D_Blocked_I8, ConvolutionLayerCPUTest,
::testing::Combine(
::testing::Combine(
convParams_ExplicitPadding_Blocked_3D,
::testing::Values(Precision::FP32),
::testing::Values(Precision::I8),
::testing::Values(Precision::UNSPECIFIED),
::testing::Values(Layout::ANY),
::testing::Values(Layout::ANY),
::testing::Values(std::vector<size_t >({ 2, 64, 7, 7, 7 })),
::testing::Values(CommonTestUtils::DEVICE_CPU)),
::testing::ValuesIn(filterCPUInfoForDevice(CPUParams_Blocked_3D)),
::testing::Values(fusingSum),
::testing::Values(cpuEmptyPluginConfig)),
ConvolutionLayerCPUTest::getTestCaseName);
/* ============= Kernel_1x1 (2D) ============= */
const auto convParams_ExplicitPadding_1x1_2D = ::testing::Combine(
@ -397,6 +463,22 @@ INSTANTIATE_TEST_CASE_P(smoke_Conv_2D_1x1_BF16, ConvolutionLayerCPUTest,
::testing::Values(cpuBF16PluginConfig)),
ConvolutionLayerCPUTest::getTestCaseName);
INSTANTIATE_TEST_CASE_P(smoke_Conv_2D_1x1_I8, ConvolutionLayerCPUTest,
::testing::Combine(
::testing::Combine(
convParams_ExplicitPadding_1x1_2D,
::testing::Values(Precision::FP32),
::testing::Values(Precision::I8),
::testing::Values(Precision::UNSPECIFIED),
::testing::Values(Layout::ANY),
::testing::Values(Layout::ANY),
::testing::Values(std::vector<size_t >({ 2, 64, 7, 7 })),
::testing::Values(CommonTestUtils::DEVICE_CPU)),
::testing::ValuesIn(filterCPUInfoForDevice(CPUParams_1x1_2D)),
::testing::Values(fusingSum),
::testing::Values(cpuEmptyPluginConfig)),
ConvolutionLayerCPUTest::getTestCaseName);
/* ========= */
} // namespace