Updated DeconvolutionIE to support dynamic shapes (#671)
* Updated DeconvolutionIE to support dynamic shapes * Updated DeconvolutionIE to support output_shape input * Updated ConvertConvolutions pass
This commit is contained in:
Gleb Kazantaev
GitHub
parent
cbe45b7d0a
commit
638c7b891c
@ -26,31 +26,30 @@ public:
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DeconvolutionIE(const Output<Node>& data,
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const Output<Node>& filters,
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const Strides& strides,
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const Strides& dilations,
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const CoordinateDiff& pads_begin,
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const CoordinateDiff& pads_end,
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const Strides& dilations,
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const Shape& output_shape,
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const size_t& group = 1,
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const PadType& auto_pad = PadType::EXPLICIT);
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const PadType& auto_pad = PadType::EXPLICIT,
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const CoordinateDiff& output_padding = {},
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const std::shared_ptr<Node> & output_shape = nullptr);
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DeconvolutionIE(const Output<Node>& data,
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const Output<Node>& filters,
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const Output<Node>& bias,
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const Strides& strides,
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const Strides& dilations,
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const CoordinateDiff& pads_begin,
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const CoordinateDiff& pads_end,
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const Strides& dilations,
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const Shape& output_shape,
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const size_t& group = 1,
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const PadType& auto_pad = PadType::EXPLICIT);
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const PadType& auto_pad = PadType::EXPLICIT,
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const CoordinateDiff& output_padding = {},
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const std::shared_ptr<Node> & output_shape = nullptr);
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void validate_and_infer_types() override;
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std::shared_ptr<Node> copy_with_new_args(const NodeVector& new_args) const override;
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std::shared_ptr<Node> clone_with_new_inputs(const OutputVector & new_args) const override;
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/// \return The data batch shape.
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const PartialShape get_output_shape() { return m_output_shape; }
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void set_output_shape(const Shape& output_shape) { m_output_shape = output_shape; }
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/// \return The strides from the forward prop.
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const Strides& get_strides() const { return m_strides; }
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void set_strides(const Strides& strides) { m_strides = strides; }
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@ -75,9 +74,10 @@ protected:
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Strides m_dilations;
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CoordinateDiff m_pads_begin;
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CoordinateDiff m_pads_end;
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CoordinateDiff m_output_padding;
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PadType m_auto_pad;
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Shape m_output_shape;
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size_t m_group;
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std::shared_ptr<Node> m_output_shape;
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};
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} // namespace op
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@ -5,11 +5,13 @@
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#include <algorithm>
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#include <memory>
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#include <vector>
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#include <ngraph/ops.hpp>
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#include "ngraph_ops/deconvolution_ie.hpp"
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#include "ngraph/util.hpp"
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#include "ngraph/validation_util.hpp"
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#include "ngraph/opsets/opset1.hpp"
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using namespace std;
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using namespace ngraph;
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@ -19,20 +21,22 @@ constexpr NodeTypeInfo op::DeconvolutionIE::type_info;
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op::DeconvolutionIE::DeconvolutionIE(const Output<Node>& data,
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const Output<Node>& filters,
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const Strides& strides,
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const Strides& dilations,
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const CoordinateDiff& pads_begin,
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const CoordinateDiff& pads_end,
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const Strides& dilations,
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const Shape& output_shape,
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const size_t& group,
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const PadType& auto_pad)
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const PadType& auto_pad,
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const CoordinateDiff& output_padding,
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const std::shared_ptr<Node> & output_shape)
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: Op({data, filters})
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, m_strides(strides)
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, m_dilations(dilations)
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, m_pads_begin(pads_begin)
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, m_pads_end(pads_end)
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, m_auto_pad(auto_pad)
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, m_output_shape(output_shape)
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, m_group(group) {
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, m_group(group)
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, m_output_padding(output_padding)
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, m_output_shape(output_shape) {
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constructor_validate_and_infer_types();
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}
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@ -40,48 +44,75 @@ op::DeconvolutionIE::DeconvolutionIE(const Output<Node>& data,
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const Output<Node>& filters,
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const Output<Node>& bias,
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const Strides& strides,
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const Strides& dilations,
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const CoordinateDiff& pads_begin,
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const CoordinateDiff& pads_end,
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const Strides& dilations,
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const Shape& output_shape,
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const size_t& group,
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const PadType& auto_pad)
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const PadType& auto_pad,
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const CoordinateDiff& output_padding,
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const std::shared_ptr<Node> & output_shape)
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: Op({data, filters, bias})
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, m_strides(strides)
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, m_dilations(dilations)
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, m_pads_begin(pads_begin)
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, m_pads_end(pads_end)
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, m_auto_pad(auto_pad)
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, m_output_shape(output_shape)
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, m_group(group) {
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, m_group(group)
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, m_output_padding(output_padding)
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, m_output_shape(output_shape) {
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constructor_validate_and_infer_types();
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}
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void op::DeconvolutionIE::validate_and_infer_types() {
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set_output_type(0, get_input_element_type(0), m_output_shape);
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// To calculate output shape we use opset1::GroupConvolutionBackPropData
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// but before we need to reshape weights from I(G*O)YX to GIOYX
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auto weights = input_value(1);
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const auto weights_pshape = weights.get_partial_shape();
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const auto weights_shape_rank = weights_pshape.rank();
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if (weights_pshape.is_static()) {
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auto weights_shape = weights_pshape.to_shape();
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std::vector<int64_t> reshape_dims(3);
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reshape_dims[0] = m_group; // G
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reshape_dims[1] = weights_shape[0]; // I
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reshape_dims[2] = weights_shape[1] / m_group; // O
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reshape_dims.insert(reshape_dims.end(), weights_shape.begin() + 2, weights_shape.end());
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weights = std::make_shared<opset1::Reshape>(weights, opset1::Constant::create(element::i64, Shape{reshape_dims.size()}, reshape_dims), true);
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}
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Output<Node> conv;
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if (m_output_shape) {
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conv = std::make_shared<opset1::GroupConvolutionBackpropData>(input_value(0), weights, m_output_shape,
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m_strides, m_pads_begin, m_pads_end, m_dilations, m_auto_pad, m_output_padding);
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} else {
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conv = std::make_shared<opset1::GroupConvolutionBackpropData>(input_value(0), weights,
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m_strides, m_pads_begin, m_pads_end, m_dilations, m_auto_pad, m_output_padding);
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}
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set_output_type(0, conv.get_element_type(), conv.get_partial_shape());
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}
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shared_ptr<Node> op::DeconvolutionIE::copy_with_new_args(const NodeVector& new_args) const {
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shared_ptr<Node> op::DeconvolutionIE::clone_with_new_inputs(const ngraph::OutputVector &new_args) const {
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if (new_args.size() == 2) {
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return make_shared<DeconvolutionIE>(new_args.at(0),
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new_args.at(1),
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m_strides,
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m_pads_begin,
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m_pads_end,
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m_dilations,
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m_output_shape,
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m_group,
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m_auto_pad);
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} else {
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new_args.at(1),
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m_strides,
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m_dilations,
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m_pads_begin,
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m_pads_end,
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m_group,
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m_auto_pad,
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m_output_padding,
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m_output_shape);
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} else if (new_args.size() == 3) {
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return make_shared<DeconvolutionIE>(new_args.at(0),
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new_args.at(1),
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new_args.at(2),
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m_strides,
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m_pads_begin,
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m_pads_end,
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m_dilations,
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m_output_shape,
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m_group,
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m_auto_pad);
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new_args.at(1),
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new_args.at(2),
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m_strides,
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m_dilations,
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m_pads_begin,
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m_pads_end,
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m_group,
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m_auto_pad,
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m_output_padding,
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m_output_shape);
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}
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throw ngraph::ngraph_error("Unexpected number of arguments");
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}
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@ -14,14 +14,8 @@
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#include <ngraph_ops/deconvolution_ie.hpp>
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void ngraph::pass::ConvertConvolutions::convert_convolution() {
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auto data = std::make_shared<pattern::op::Label>(element::f32, Shape{1, 3, 12, 12});
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auto weights = std::make_shared<pattern::op::Label>(element::f32, Shape{1, 3, 1, 1});
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auto conv = std::make_shared<ngraph::opset1::Convolution>(data,
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weights,
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Strides{1, 1},
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CoordinateDiff{0, 0},
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CoordinateDiff{0, 0},
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Strides{1, 1});
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auto conv = std::make_shared<pattern::op::Label>(element::f32, Shape{},
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pattern::has_class<opset1::Convolution>());
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ngraph::graph_rewrite_callback callback = [](pattern::Matcher& m) {
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auto conv = std::dynamic_pointer_cast<ngraph::opset1::Convolution> (m.get_match_root());
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@ -48,14 +42,8 @@ void ngraph::pass::ConvertConvolutions::convert_convolution() {
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}
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void ngraph::pass::ConvertConvolutions::convert_group_convolution() {
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auto data = std::make_shared<pattern::op::Label>(element::f32, Shape{1, 3, 12, 12});
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auto weights = std::make_shared<pattern::op::Label>(element::f32, Shape{3, 1, 1, 1, 1});
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auto gconv = std::make_shared<ngraph::opset1::GroupConvolution>(data,
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weights,
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Strides{1, 1},
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CoordinateDiff{0, 0},
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CoordinateDiff{0, 0},
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Strides{1, 1});
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auto gconv = std::make_shared<pattern::op::Label>(element::f32, Shape{},
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pattern::has_class<opset1::GroupConvolution>());
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ngraph::graph_rewrite_callback callback = [](pattern::Matcher& m) {
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auto gconv = std::dynamic_pointer_cast<ngraph::opset1::GroupConvolution> (m.get_match_root());
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@ -97,23 +85,8 @@ void ngraph::pass::ConvertConvolutions::convert_group_convolution() {
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}
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void ngraph::pass::ConvertConvolutions::convert_convolution_backprop_data() {
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auto data = std::make_shared<pattern::op::Label>(element::f32, Shape{1, 3, 12, 12});
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auto weights = std::make_shared<pattern::op::Label>(element::f32, Shape{1, 3, 1, 1});
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auto conv = std::make_shared<ngraph::opset1::ConvolutionBackpropData>(data,
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weights,
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Strides{1, 1},
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CoordinateDiff{0, 0},
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CoordinateDiff{0, 0},
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Strides{1, 1});
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auto output_shape = std::make_shared<pattern::op::Label>(element::i64, Shape{2});
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auto conv2 = std::make_shared<ngraph::opset1::ConvolutionBackpropData>(data,
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weights,
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output_shape,
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Strides{1, 1},
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CoordinateDiff{0, 0},
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CoordinateDiff{0, 0},
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Strides{1, 1});
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auto conv = std::make_shared<pattern::op::Label>(element::f32, Shape{},
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pattern::has_class<opset1::ConvolutionBackpropData>());
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ngraph::graph_rewrite_callback callback = [](pattern::Matcher& m) {
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auto deconv = std::dynamic_pointer_cast<ngraph::opset1::ConvolutionBackpropData> (m.get_match_root());
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@ -124,12 +97,14 @@ void ngraph::pass::ConvertConvolutions::convert_convolution_backprop_data() {
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auto deconv_ie = std::make_shared<ngraph::op::DeconvolutionIE>(deconv->input_value(0),
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deconv->input_value(1),
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deconv->get_strides(),
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deconv->get_dilations(),
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deconv->get_pads_begin(),
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deconv->get_pads_end(),
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deconv->get_dilations(),
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deconv->output(0).get_shape(),
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1 /* groups */,
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deconv->get_auto_pad());
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deconv->get_auto_pad(),
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deconv->get_output_padding(),
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(deconv->inputs().size() == 3 ? deconv->input_value(2).get_node_shared_ptr()
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: nullptr));
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deconv_ie->set_friendly_name(deconv->get_friendly_name());
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ngraph::copy_runtime_info(deconv, deconv_ie);
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ngraph::replace_node(deconv, deconv_ie);
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@ -138,29 +113,11 @@ void ngraph::pass::ConvertConvolutions::convert_convolution_backprop_data() {
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auto m = std::make_shared<ngraph::pattern::Matcher>(conv, "ConvertConvolutionBackpropData");
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this->add_matcher(m, callback, PassProperty::CHANGE_DYNAMIC_STATE);
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auto m2 = std::make_shared<ngraph::pattern::Matcher>(conv2, "ConvertConvolutionBackpropData2");
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this->add_matcher(m2, callback, PassProperty::CHANGE_DYNAMIC_STATE);
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}
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void ngraph::pass::ConvertConvolutions::convert_group_convolution_backprop_data() {
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auto data = std::make_shared<pattern::op::Label>(element::f32, Shape{1, 3, 12, 12});
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auto weights = std::make_shared<pattern::op::Label>(element::f32, Shape{3, 1, 1, 1, 1});
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auto gconv = std::make_shared<ngraph::opset1::GroupConvolutionBackpropData>(data,
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weights,
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Strides{1, 1},
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CoordinateDiff{0, 0},
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CoordinateDiff{0, 0},
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Strides{1, 1});
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auto output_shape = std::make_shared<pattern::op::Label>(element::i64, Shape{2});
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auto gconv2 = std::make_shared<ngraph::opset1::GroupConvolutionBackpropData>(data,
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weights,
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output_shape,
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Strides{1, 1},
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CoordinateDiff{0, 0},
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CoordinateDiff{0, 0},
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Strides{1, 1});
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auto gconv = std::make_shared<pattern::op::Label>(element::f32, Shape{},
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pattern::has_class<opset1::GroupConvolutionBackpropData>());
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ngraph::graph_rewrite_callback callback = [](pattern::Matcher& m) {
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auto gconv = std::dynamic_pointer_cast<ngraph::opset1::GroupConvolutionBackpropData> (m.get_match_root());
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@ -182,12 +139,14 @@ void ngraph::pass::ConvertConvolutions::convert_group_convolution_backprop_data(
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auto conv_ie = std::make_shared<ngraph::op::DeconvolutionIE>(gconv->input_value(0),
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reshape,
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gconv->get_strides(),
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gconv->get_dilations(),
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gconv->get_pads_begin(),
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gconv->get_pads_end(),
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gconv->get_dilations(),
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gconv->output(0).get_shape(),
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group,
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gconv->get_auto_pad());
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gconv->get_auto_pad(),
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gconv->get_output_padding(),
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(gconv->inputs().size() == 3 ? gconv->input_value(2).get_node_shared_ptr()
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: nullptr));
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conv_ie->set_friendly_name(gconv->get_friendly_name());
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ngraph::copy_runtime_info(gconv, conv_ie);
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ngraph::replace_node(gconv, conv_ie);
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@ -196,7 +155,4 @@ void ngraph::pass::ConvertConvolutions::convert_group_convolution_backprop_data(
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auto m = std::make_shared<ngraph::pattern::Matcher>(gconv, "ConvertGroupConvolutionBackpropData");
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this->add_matcher(m, callback, PassProperty::CHANGE_DYNAMIC_STATE);
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auto m2 = std::make_shared<ngraph::pattern::Matcher>(gconv2, "ConvertGroupConvolutionBackpropData2");
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this->add_matcher(m2, callback, PassProperty::CHANGE_DYNAMIC_STATE);
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}
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@ -29,7 +29,7 @@ using namespace testing;
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using InputShape = ngraph::PartialShape;
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using WeightsShape = ngraph::Shape;
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class ConvertConvolutionsTest: public CommonTestUtils::TestsCommon,
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class ConvertConvolutionTest: public CommonTestUtils::TestsCommon,
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public testing::WithParamInterface<std::tuple<InputShape, WeightsShape> > {
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public:
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std::shared_ptr<ngraph::Function> f, f_ref;
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@ -66,7 +66,7 @@ private:
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}
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};
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TEST_P(ConvertConvolutionsTest, CompareFunctions) {
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TEST_P(ConvertConvolutionTest, CompareFunctions) {
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const auto & orig_shape = f->get_output_partial_shape(0);
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ngraph::pass::InitNodeInfo().run_on_function(f);
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ngraph::pass::ConvertConvolutions().run_on_function(f);
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@ -76,7 +76,7 @@ TEST_P(ConvertConvolutionsTest, CompareFunctions) {
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ASSERT_TRUE(orig_shape.same_scheme(f->get_output_partial_shape(0))) << "Shape " << orig_shape << " is not equal to " << f->get_output_partial_shape(0);
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}
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INSTANTIATE_TEST_CASE_P(ConvertConvolution, ConvertConvolutionsTest,
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INSTANTIATE_TEST_CASE_P(ConvertConvolution, ConvertConvolutionTest,
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testing::Values(std::make_tuple(InputShape{DYN, DYN, DYN, DYN, DYN}, WeightsShape{8, 3, 1, 2, 3}),
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std::make_tuple(InputShape{DYN, 3, 64, 64, 64}, WeightsShape{8, 3, 1, 2, 3}),
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std::make_tuple(InputShape{2, DYN, 64, 64, 64}, WeightsShape{9, 3, 2, 3, 1}),
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@ -0,0 +1,96 @@
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// Copyright (C) 2020 Intel Corporation
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// SPDX-License-Identifier: Apache-2.0
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//
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#include <gtest/gtest.h>
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#include "common_test_utils/test_common.hpp"
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#include <string>
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#include <sstream>
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#include <fstream>
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#include <memory>
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#include <queue>
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#include <map>
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#include <ngraph/function.hpp>
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#include <ngraph/opsets/opset1.hpp>
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#include <ngraph/pass/constant_folding.hpp>
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#include <transformations/utils/utils.hpp>
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#include <transformations/init_node_info.hpp>
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#include <ngraph/pass/algebraic_simplification.hpp>
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#include <ngraph/pass/visualize_tree.hpp>
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#include <transformations/convert_opset1_to_legacy/convert_convolutions.hpp>
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#include <ngraph_ops/convolution_ie.hpp>
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#include <ngraph_ops/deconvolution_ie.hpp>
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#include "ngraph_test_utils.hpp"
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using namespace testing;
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using InputShape = ngraph::PartialShape;
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using WeightsShape = ngraph::Shape;
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||||
|
||||
class ConvertDeconvolutionTest: public CommonTestUtils::TestsCommon,
|
||||
public testing::WithParamInterface<std::tuple<InputShape, WeightsShape> > {
|
||||
public:
|
||||
std::shared_ptr<ngraph::Function> f, f_ref;
|
||||
|
||||
void SetUp() override {
|
||||
const auto& input_shape = std::get<0>(GetParam());
|
||||
const auto& weights_shape = std::get<1>(GetParam());
|
||||
|
||||
f = get_initial_function(input_shape, weights_shape);
|
||||
f_ref = get_reference_function(input_shape, weights_shape);
|
||||
}
|
||||
|
||||
private:
|
||||
std::shared_ptr<ngraph::Function> get_initial_function(const ngraph::PartialShape & input_shape,
|
||||
const ngraph::Shape & weights_shape) {
|
||||
auto spatial_dims = input_shape.rank().get_length() - 2;
|
||||
auto input = std::make_shared<ngraph::opset1::Parameter>(ngraph::element::f32, input_shape);
|
||||
auto weights = ngraph::opset1::Constant::create(ngraph::element::f32, weights_shape, {1});
|
||||
auto conv = std::make_shared<ngraph::opset1::ConvolutionBackpropData>(input, weights, ngraph::Strides(spatial_dims, 1),
|
||||
ngraph::CoordinateDiff(spatial_dims, 0), ngraph::CoordinateDiff(spatial_dims, 0), ngraph::Strides(spatial_dims, 1));
|
||||
|
||||
return std::make_shared<ngraph::Function>(ngraph::NodeVector{conv}, ngraph::ParameterVector{input});
|
||||
}
|
||||
|
||||
std::shared_ptr<ngraph::Function> get_reference_function(const ngraph::PartialShape & input_shape,
|
||||
const ngraph::Shape & weights_shape) {
|
||||
auto spatial_dims = input_shape.rank().get_length() - 2;
|
||||
auto input = std::make_shared<ngraph::opset1::Parameter>(ngraph::element::f32, input_shape);
|
||||
auto weights = ngraph::opset1::Constant::create(ngraph::element::f32, weights_shape, {1});
|
||||
auto conv = std::make_shared<ngraph::op::DeconvolutionIE>(input, weights, ngraph::Strides(spatial_dims, 1), ngraph::Strides(spatial_dims, 1),
|
||||
ngraph::CoordinateDiff(spatial_dims, 0), ngraph::CoordinateDiff(spatial_dims, 0));
|
||||
|
||||
return std::make_shared<ngraph::Function>(ngraph::NodeVector{conv}, ngraph::ParameterVector{input});
|
||||
}
|
||||
};
|
||||
|
||||
TEST_P(ConvertDeconvolutionTest, CompareFunctions) {
|
||||
const auto & orig_shape = f->get_output_partial_shape(0);
|
||||
ngraph::pass::InitNodeInfo().run_on_function(f);
|
||||
ngraph::pass::ConvertConvolutions().run_on_function(f);
|
||||
ASSERT_NO_THROW(check_rt_info(f));
|
||||
auto res = compare_functions(f, f_ref);
|
||||
ASSERT_TRUE(res.first) << res.second;
|
||||
ASSERT_TRUE(orig_shape.same_scheme(f->get_output_partial_shape(0))) << "Shape " << orig_shape << " is not equal to " << f->get_output_partial_shape(0);
|
||||
}
|
||||
|
||||
INSTANTIATE_TEST_CASE_P(ConvertDeconvolution, ConvertDeconvolutionTest,
|
||||
testing::Values(std::make_tuple(InputShape{DYN, DYN, DYN, DYN, DYN}, WeightsShape{3, 8, 1, 2, 3}),
|
||||
std::make_tuple(InputShape{DYN, 3, 64, 64, 64}, WeightsShape{3, 8, 1, 2, 3}),
|
||||
std::make_tuple(InputShape{2, DYN, 64, 64, 64}, WeightsShape{3, 9, 2, 3, 1}),
|
||||
std::make_tuple(InputShape{3, 3, DYN, 64, 64}, WeightsShape{3, 6, 3, 4, 2}),
|
||||
std::make_tuple(InputShape{3, 3, 64, DYN, 64}, WeightsShape{3, 5, 3, 4, 3}),
|
||||
std::make_tuple(InputShape{3, 3, 64, 64, DYN}, WeightsShape{3, 3, 3, 4, 3}),
|
||||
std::make_tuple(InputShape{1, 3, 64, 64}, WeightsShape{3, 6, 1, 1}),
|
||||
std::make_tuple(InputShape{DYN, DYN, DYN, DYN}, WeightsShape{3, 7, 1, 1}),
|
||||
std::make_tuple(InputShape{DYN, 3, 64, 64}, WeightsShape{3, 8, 1, 2}),
|
||||
std::make_tuple(InputShape{2, DYN, 64, 64}, WeightsShape{3, 9, 2, 3}),
|
||||
std::make_tuple(InputShape{3, 3, DYN, 64}, WeightsShape{3, 6, 3, 4}),
|
||||
std::make_tuple(InputShape{3, 3, 64, DYN}, WeightsShape{3, 5, 3, 4}),
|
||||
std::make_tuple(InputShape{DYN, DYN, DYN}, WeightsShape{3, 5, 1}),
|
||||
std::make_tuple(InputShape{DYN, 3, 10}, WeightsShape{3, 3, 1}),
|
||||
std::make_tuple(InputShape{2, DYN, 9}, WeightsShape{3, 2, 2}),
|
||||
std::make_tuple(InputShape{3, 3, DYN}, WeightsShape{3, 1, 3})));
|
||||
Loading…
Reference in New Issue
Block a user