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Add support for GroupConvolution in DilatedConvolutionConverter (#15168)

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* Add support for GroupConvolution in DilatedConvolutionConverter

* Fix codestyle

* Update src/common/transformations/tests/common_optimizations/dilated_convolution_converter.cpp

* Update src/common/transformations/tests/common_optimizations/dilated_convolution_converter.cpp

* Add tf frontend test

* Apply codestyle

* Update src/frontends/tensorflow/tests/convert_tricky_models.cpp
This commit is contained in:
Maxim Vafin authored and GitHub committed 2023-01-22 14:01:16 +03:00
1 parent 2ec116f592
commit d4cb719213
5 files changed
+564 -18
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src/common/transformations/include/transformations/common_optimizations/dilated_convolution_converter.hpp
+2 -2
View File
@@ -20,8 +20,8 @@ class TRANSFORMATIONS_API DilatedConvolutionConverter;
/**
* @ingroup ie_transformation_common_api
* @brief DilatedConvolutionConverter transformation replaces following graph:
* SpaceToBatch -> Convolution -> BatchToSpace
* to a single Convolution node with updated pads and dilations
* SpaceToBatch -> Convolution(GroupConvolution) -> BatchToSpace
* to a single Convolution(GroupConvolution) node with updated pads and dilations
* Restrictions:
* - pads in SpaceToBatch must have 0 on first and second position
*/
src/common/transformations/src/transformations/common_optimizations/dilated_convolution_converter.cpp
+49 -16
View File
@@ -5,14 +5,17 @@
#include "transformations/common_optimizations/dilated_convolution_converter.hpp"
#include <memory>
#include <ngraph/pattern/op/wrap_type.hpp>
#include <ngraph/rt_info.hpp>
#include <openvino/opsets/opset6.hpp>
#include <vector>
#include "itt.hpp"
#include "openvino/core/rt_info.hpp"
#include "openvino/opsets/opset6.hpp"
#include "openvino/pass/pattern/op/or.hpp"
#include "openvino/pass/pattern/op/wrap_type.hpp"
#include "transformations/utils/utils.hpp"
// Replace the following graph SpaceToBatch -> Convolution(GroupConvolution) -> BatchToSpace with single
// Convolution(GroupConvolution) node
ov::pass::DilatedConvolutionConverter::DilatedConvolutionConverter() {
MATCHER_SCOPE(DilatedConvolutionConverter);
auto data_pattern = pattern::any_input();
@@ -21,7 +24,9 @@ ov::pass::DilatedConvolutionConverter::DilatedConvolutionConverter() {
auto pads_end_pattern = pattern::wrap_type<opset6::Constant>();
auto space_to_batch_pattern = pattern::wrap_type<opset6::SpaceToBatch>(
{data_pattern, block_shape_pattern, pads_begin_pattern, pads_end_pattern});
auto conv_pattern = pattern::wrap_type<opset6::Convolution>({space_to_batch_pattern, pattern::any_input()});
auto conv_p = pattern::wrap_type<opset6::Convolution>({space_to_batch_pattern, pattern::any_input()});
auto gconv_p = pattern::wrap_type<opset6::GroupConvolution>({space_to_batch_pattern, pattern::any_input()});
auto conv_pattern = std::make_shared<pattern::op::Or>(OutputVector{conv_p, gconv_p});
auto crops_begin_pattern = pattern::wrap_type<opset6::Constant>();
auto crops_end_pattern = pattern::wrap_type<opset6::Constant>();
auto batch_to_space_pattern = pattern::wrap_type<opset6::BatchToSpace>(
@@ -49,13 +54,30 @@ ov::pass::DilatedConvolutionConverter::DilatedConvolutionConverter() {
std::dynamic_pointer_cast<opset6::Constant>(pattern_map.at(crops_end_pattern).get_node_shared_ptr());
if (!crops_end)
return false;
auto conv = std::dynamic_pointer_cast<opset6::Convolution>(pattern_map.at(conv_pattern).get_node_shared_ptr());
if (!conv)
return false;
auto block_shape_val = block_shape->cast_vector<size_t>();
auto dilations = conv->get_dilations();
ov::Strides dilations;
ov::Strides strides;
std::shared_ptr<ov::Node> conv_node;
if (pattern_map.count(conv_p)) {
conv_node = pattern_map.at(conv_p).get_node_shared_ptr();
auto conv = std::dynamic_pointer_cast<opset6::Convolution>(conv_node);
if (!conv)
return false;
dilations = conv->get_dilations();
strides = conv->get_strides();
} else if (pattern_map.count(gconv_p)) {
conv_node = pattern_map.at(gconv_p).get_node_shared_ptr();
auto conv = std::dynamic_pointer_cast<opset6::GroupConvolution>(conv_node);
if (!conv)
return false;
dilations = conv->get_dilations();
strides = conv->get_strides();
} else {
return false;
}
for (size_t i = 0; i < dilations.size(); i++)
dilations[i] = block_shape_val[i + 2];
auto pads_begin_val = pads_begin->cast_vector<std::ptrdiff_t>();
@@ -76,13 +98,24 @@ ov::pass::DilatedConvolutionConverter::DilatedConvolutionConverter() {
return false;
new_pads_end.push_back(pads_end_val[i] - crops_end_val[i]);
}
auto new_conv = register_new_node<opset6::Convolution>(pattern_map.at(data_pattern),
conv->input_value(1),
conv->get_strides(),
new_pads_begin,
new_pads_end,
dilations,
op::PadType::EXPLICIT);
std::shared_ptr<ov::Node> new_conv;
if (pattern_map.count(gconv_p)) {
new_conv = register_new_node<opset6::GroupConvolution>(pattern_map.at(data_pattern),
conv_node->input_value(1),
strides,
new_pads_begin,
new_pads_end,
dilations,
op::PadType::EXPLICIT);
} else {
new_conv = register_new_node<opset6::Convolution>(pattern_map.at(data_pattern),
conv_node->input_value(1),
strides,
new_pads_begin,
new_pads_end,
dilations,
op::PadType::EXPLICIT);
}
auto batch_to_space = pattern_map.at(batch_to_space_pattern).get_node_shared_ptr();
new_conv->set_friendly_name(batch_to_space->get_friendly_name());
@@ -90,7 +123,7 @@ ov::pass::DilatedConvolutionConverter::DilatedConvolutionConverter() {
copy_runtime_info(
{
pattern_map.at(space_to_batch_pattern).get_node_shared_ptr(),
pattern_map.at(conv_pattern).get_node_shared_ptr(),
conv_node,
batch_to_space,
},
new_conv);
src/common/transformations/tests/common_optimizations/dilated_convolution_converter.cpp
+41
View File
@@ -112,3 +112,44 @@ TEST_F(TransformationTestsF, NegativeDilatedConvolutionConverterNonZeroPadsForNC
manager.register_pass<pass::DilatedConvolutionConverter>();
}
}
TEST_F(TransformationTestsF, DilatedGroupConvolutionConverter) {
{
auto data = std::make_shared<opset6::Parameter>(element::f32, Shape{1, 4, 10, 10});
auto filters = std::make_shared<opset6::Parameter>(element::f32, Shape{4, 1, 1, 3, 3});
auto space_to_batch =
std::make_shared<opset6::SpaceToBatch>(data,
op::Constant::create(element::i64, Shape{4}, {1, 1, 2, 2}),
op::Constant::create(element::i64, Shape{4}, {0, 0, 2, 2}),
op::Constant::create(element::i64, Shape{4}, {0, 0, 2, 2}));
auto conv = std::make_shared<opset6::GroupConvolution>(space_to_batch,
filters,
Strides{1, 1},
CoordinateDiff{0, 0},
CoordinateDiff{0, 0},
Strides{1, 1});
auto batch_to_space =
std::make_shared<opset6::BatchToSpace>(conv,
op::Constant::create(element::i64, Shape{4}, {1, 1, 2, 2}),
op::Constant::create(element::i64, Shape{4}, {0, 0, 1, 1}),
op::Constant::create(element::i64, Shape{4}, {0, 0, 1, 1}));
function = std::make_shared<Function>(NodeVector{batch_to_space}, ParameterVector{data, filters});
manager.register_pass<pass::DilatedConvolutionConverter>();
}
{
auto data = std::make_shared<opset6::Parameter>(element::f32, Shape{1, 4, 10, 10});
auto filters = std::make_shared<opset6::Parameter>(element::f32, Shape{4, 1, 1, 3, 3});
auto conv = std::make_shared<opset6::GroupConvolution>(data,
filters,
Strides{1, 1},
CoordinateDiff{1, 1},
CoordinateDiff{1, 1},
Strides{2, 2},
op::PadType::EXPLICIT);
function_ref = std::make_shared<Function>(NodeVector{conv}, ParameterVector{data, filters});
}
comparator.enable(FunctionsComparator::CmpValues::CONST_VALUES);
comparator.enable(FunctionsComparator::CmpValues::ACCURACY);
comparator.enable(FunctionsComparator::CmpValues::ATTRIBUTES);
}
src/frontends/tensorflow/tests/convert_tricky_models.cpp
+25
View File
@@ -221,3 +221,28 @@ TEST_F(TransformationTestsF, InjectedBodyAndIf) {
model_ref = make_shared<Model>(OutputVector{if_op}, ParameterVector{x, y});
}
}
// Ticket 101756
TEST_F(TransformationTestsF, DISABLED_ModelWithDilatedGroupConvolution) {
{
model = convert_model("dilated_gconv_model/dilated_gconv_model.pb");
// need to call MOC to fuse BatchToSpace/SpaceToBatch with GroupConvolution
manager.register_pass<pass::MOCTransformations>(false);
}
{
auto x = make_shared<Parameter>(f32, Shape{1, 129, 257, 384});
auto transpose_before_const = make_shared<Constant>(i64, Shape{4}, std::vector<int64_t>{0, 3, 1, 2});
auto transpose_before = make_shared<Transpose>(x, transpose_before_const);
auto const_filter = make_shared<Constant>(f32, Shape{384, 1, 1, 3, 3}, std::vector<float>(384 * 3 * 3, 0));
Strides dilations{2, 2};
CoordinateDiff pads_begin{2, 2};
CoordinateDiff pads_end{2, 2};
Strides strides{1, 1};
auto gconv =
make_shared<GroupConvolution>(transpose_before, const_filter, strides, pads_begin, pads_end, dilations);
auto transpose_after_const = make_shared<Constant>(i64, Shape{4}, std::vector<int64_t>{0, 2, 3, 1});
auto transpose_after = make_shared<Transpose>(gconv, transpose_after_const);
model_ref = make_shared<Model>(OutputVector{transpose_after}, ParameterVector{x});
}
}
src/frontends/tensorflow/tests/test_models/models_pbtxt/dilated_gconv_model.pbtxt
+447
View File
@@ -0,0 +1,447 @@
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attr {
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dim {
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dim {
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