Unverified Commit 2ac53fdc authored by Scott Cyphers's avatar Scott Cyphers Committed by GitHub

Merge branch 'master' into etusien/gelu

parents 1c4bc205 7f65c7db
......@@ -21,7 +21,7 @@ include(ExternalProject)
# ONNX.proto definition version
#------------------------------------------------------------------------------
set(ONNX_VERSION 1.3.0)
set(ONNX_VERSION 1.5.0)
#------------------------------------------------------------------------------
# Download and install libonnx ...
......@@ -30,6 +30,9 @@ set(ONNX_VERSION 1.3.0)
set(ONNX_GIT_REPO_URL https://github.com/onnx/onnx.git)
set(ONNX_GIT_BRANCH rel-${ONNX_VERSION})
add_definitions(-DONNX_BUILD_SHARED_LIBS=ON)
add_definitions(-DONNX_ML=ON)
ExternalProject_Add(
ext_onnx
PREFIX onnx
......@@ -58,8 +61,8 @@ ExternalProject_Add(
ExternalProject_Get_Property(ext_onnx SOURCE_DIR BINARY_DIR)
set(ONNX_INCLUDE_DIR ${SOURCE_DIR}/onnx)
set(ONNX_PROTO_INCLUDE_DIR ${BINARY_DIR}/onnx)
set(ONNX_INCLUDE_DIR ${SOURCE_DIR})
set(ONNX_PROTO_INCLUDE_DIR ${BINARY_DIR})
if (WIN32)
set(ONNX_LIBRARY ${BINARY_DIR}/${CMAKE_BUILD_TYPE}/onnx.lib)
set(ONNX_PROTO_LIBRARY ${BINARY_DIR}/${CMAKE_BUILD_TYPE}/onnx_proto.lib)
......
......@@ -16,7 +16,7 @@
#pragma once
#include <onnx-ml.pb.h>
#include <onnx/onnx_pb.h>
#include "ngraph/except.hpp"
#include "tensor.hpp"
......
......@@ -16,7 +16,7 @@
#pragma once
#include <onnx-ml.pb.h>
#include <onnx/onnx_pb.h>
#include <string>
#include <vector>
......
......@@ -14,7 +14,7 @@
// limitations under the License.
//*****************************************************************************
#include <onnx-ml.pb.h>
#include <onnx/onnx_pb.h>
#include "model.hpp"
#include "ngraph/log.hpp"
......
......@@ -16,7 +16,7 @@
#pragma once
#include <onnx-ml.pb.h>
#include <onnx/onnx_pb.h>
#include <ostream>
#include <string>
#include <unordered_map>
......
......@@ -14,7 +14,7 @@
// limitations under the License.
//*****************************************************************************
#include <onnx-ml.pb.h>
#include <onnx/onnx_pb.h>
#include "attribute.hpp"
#include "graph.hpp"
......
......@@ -16,7 +16,7 @@
#pragma once
#include <onnx-ml.pb.h>
#include <onnx/onnx_pb.h>
#include <utility>
#include <vector>
......
......@@ -16,7 +16,7 @@
#pragma once
#include <onnx-ml.pb.h>
#include <onnx/onnx_pb.h>
#include "ngraph/op/constant.hpp"
#include "ngraph/op/parameter.hpp"
......
......@@ -13,7 +13,7 @@
// See the License for the specific language governing permissions and
// limitations under the License.
//*****************************************************************************
#include <onnx-ml.pb.h> // onnx types
#include <onnx/onnx_pb.h> // onnx types
#include "common.hpp"
......
......@@ -15,7 +15,7 @@
//*****************************************************************************
#include <cstdlib> // std::size_t, std::uintptr_t
#include <onnxifi.h>
#include <onnx/onnxifi.h>
#include <stdexcept> // std::invalid_agrument, std::out_of_rage
#include "backend.hpp"
......
......@@ -19,7 +19,7 @@
#include <cstddef> // std::size_t, std::uintptr_t
#include <map> // std::map
#include <mutex> // std::mutex
#include <onnxifi.h>
#include <onnx/onnxifi.h>
#include "backend.hpp"
#include "ngraph/runtime/backend.hpp"
......
......@@ -16,7 +16,7 @@
#pragma once
#include <onnxifi.h>
#include <onnx/onnxifi.h>
namespace ngraph
{
......
......@@ -16,7 +16,7 @@
#include <cstddef>
#include <cstdint>
#include <onnxifi.h>
#include <onnx/onnxifi.h>
#include <stdexcept>
#include "backend_manager.hpp"
......
......@@ -17,7 +17,7 @@
#pragma once
#include <memory>
#include <onnxifi.h>
#include <onnx/onnxifi.h>
#include "ngraph/runtime/backend.hpp"
#include "ngraph/runtime/tensor.hpp"
......
......@@ -24,8 +24,10 @@
using namespace std;
using namespace ngraph;
const string op::BatchMatMul::type_name{"BatchMatMul"};
op::BatchMatMul::BatchMatMul(const shared_ptr<Node>& arg0, const shared_ptr<Node>& arg1)
: Op("BatchMatMul", check_single_output_args({arg0, arg1}))
: Op(check_single_output_args({arg0, arg1}))
{
constructor_validate_and_infer_types();
}
......
......@@ -32,6 +32,9 @@ namespace ngraph
class BatchMatMul : public Op
{
public:
NGRAPH_API
static const std::string type_name;
const std::string& description() const override { return type_name; }
/// \brief Constructs a batch of matmul product operation.
///
/// \param arg0 The node producing the first argument.
......
......@@ -23,6 +23,8 @@
using namespace std;
using namespace ngraph;
const string op::CompiledKernel::type_name{"CompiledKernel"};
shared_ptr<Node> ngraph::op::CompiledKernel::copy_with_new_args(const NodeVector& new_args) const
{
auto args = inputs();
......@@ -64,7 +66,7 @@ shared_ptr<Node> ngraph::op::CompiledKernel::copy_with_new_args(const NodeVector
ngraph::op::CompiledKernel::CompiledKernel(const NodeVector& node_list,
const NodeVector& outputs,
const NodeVector& args)
: Op("CompiledKernel", check_single_output_args({args}))
: Op(check_single_output_args({args}))
, m_node_list(node_list)
, m_output_nodes(outputs)
{
......
......@@ -32,6 +32,9 @@ namespace ngraph
class CompiledKernel : public ngraph::op::Op
{
public:
NGRAPH_API
static const std::string type_name;
const std::string& description() const override { return type_name; }
CompiledKernel(const NodeVector& node_list,
const NodeVector& outputs,
const NodeVector& args);
......
......@@ -20,10 +20,12 @@
using namespace std;
using namespace ngraph;
const string op::DynBroadcast::type_name{"DynBroadcast"};
op::DynBroadcast::DynBroadcast(const shared_ptr<Node>& arg,
const shared_ptr<Node>& shape,
const shared_ptr<Node>& broadcast_axes)
: Op("DynBroadcast", check_single_output_args({arg, shape, broadcast_axes}))
: Op(check_single_output_args({arg, shape, broadcast_axes}))
{
constructor_validate_and_infer_types();
}
......
......@@ -28,6 +28,9 @@ namespace ngraph
class DynBroadcast : public Op
{
public:
NGRAPH_API
static const std::string type_name;
const std::string& description() const override { return type_name; }
/// \brief Constructs a dynamic broadcast operation.
///
/// \param arg Node that produces the input tensor to be broadcast.
......
......@@ -19,12 +19,14 @@
using namespace std;
using namespace ngraph;
const string op::DynPad::type_name{"DynPad"};
op::DynPad::DynPad(const std::shared_ptr<Node>& arg,
const std::shared_ptr<Node>& padding_below,
const std::shared_ptr<Node>& padding_above,
const std::shared_ptr<Node>& padding_value,
op::PadMode pad_mode)
: Op("DynPad", check_single_output_args({arg, padding_below, padding_above, padding_value}))
: Op(check_single_output_args({arg, padding_below, padding_above, padding_value}))
{
constructor_validate_and_infer_types();
}
......
......@@ -27,6 +27,9 @@ namespace ngraph
class DynPad : public Op
{
public:
NGRAPH_API
static const std::string type_name;
const std::string& description() const override { return type_name; }
/// \brief Perform dynamic padding of a tensor
///
/// \param arg The node producing input tensor to be padded.
......
......@@ -24,6 +24,8 @@
using namespace std;
using namespace ngraph;
const string op::DynReplaceSlice::type_name{"DynReplaceSlice"};
op::DynReplaceSlice::DynReplaceSlice(const shared_ptr<Node>& arg,
const shared_ptr<Node>& replacement,
const shared_ptr<Node>& lower_bounds,
......@@ -34,8 +36,7 @@ op::DynReplaceSlice::DynReplaceSlice(const shared_ptr<Node>& arg,
const AxisSet& new_axis,
const AxisSet& shrink_axis,
const AxisSet& ellipsis_mask)
: Op("DynReplaceSlice",
check_single_output_args({arg, replacement, lower_bounds, upper_bounds, strides}))
: Op(check_single_output_args({arg, replacement, lower_bounds, upper_bounds, strides}))
, m_lower_bounds_mask(lower_bounds_mask)
, m_upper_bounds_mask(upper_bounds_mask)
, m_new_axis(new_axis)
......
......@@ -27,6 +27,9 @@ namespace ngraph
class DynReplaceSlice : public Op
{
public:
NGRAPH_API
static const std::string type_name;
const std::string& description() const override { return type_name; }
/// \brief Constructs a dynamic tensor replace-slice operation.
///
/// \param arg The tensor in which to replace the slice.
......
......@@ -24,10 +24,12 @@
using namespace std;
using namespace ngraph;
const string op::DynReshape::type_name{"DynReshape"};
op::DynReshape::DynReshape(const shared_ptr<Node>& arg,
const shared_ptr<Node>& pattern,
bool zero_flag)
: Op("DynReshape", check_single_output_args({arg, pattern}))
: Op(check_single_output_args({arg, pattern}))
, m_zero_flag(zero_flag)
{
constructor_validate_and_infer_types();
......
......@@ -31,6 +31,9 @@ namespace ngraph
class DynReshape : public Op
{
public:
NGRAPH_API
static const std::string type_name;
const std::string& description() const override { return type_name; }
/// \brief Constructs a dynamic reshape operation. This operation does not perform transpose.
///
/// \param arg The tensor to be reshaped.
......
......@@ -24,6 +24,8 @@
using namespace std;
using namespace ngraph;
const string op::DynSlice::type_name{"DynSlice"};
op::DynSlice::DynSlice(const shared_ptr<Node>& arg,
const shared_ptr<Node>& lower_bounds,
const shared_ptr<Node>& upper_bounds,
......@@ -33,7 +35,7 @@ op::DynSlice::DynSlice(const shared_ptr<Node>& arg,
const AxisSet& new_axis,
const AxisSet& shrink_axis,
const AxisSet& ellipsis_mask)
: Op("DynSlice", check_single_output_args({arg, lower_bounds, upper_bounds, strides}))
: Op(check_single_output_args({arg, lower_bounds, upper_bounds, strides}))
, m_lower_bounds_mask(lower_bounds_mask)
, m_upper_bounds_mask(upper_bounds_mask)
, m_new_axis(new_axis)
......
......@@ -27,6 +27,9 @@ namespace ngraph
class DynSlice : public Op
{
public:
NGRAPH_API
static const std::string type_name;
const std::string& description() const override { return type_name; }
/// \brief Constructs a dynamic tensor slice operation.
///
/// \param arg The tensor to be sliced.
......
......@@ -19,10 +19,12 @@
using namespace std;
using namespace ngraph;
const string op::CTCGreedyDecoder::type_name{"CTCGreedyDecoder"};
op::CTCGreedyDecoder::CTCGreedyDecoder(const shared_ptr<Node>& input,
const std::shared_ptr<Node>& seq_len,
const bool ctc_merge_repeated)
: Op("CTCGreedyDecoder", check_single_output_args({input, seq_len}))
: Op(check_single_output_args({input, seq_len}))
, m_ctc_merge_repeated(ctc_merge_repeated)
{
constructor_validate_and_infer_types();
......
......@@ -25,6 +25,9 @@ namespace ngraph
class CTCGreedyDecoder : public Op
{
public:
NGRAPH_API
static const std::string type_name;
const std::string& description() const override { return type_name; }
/// \brief Constructs a CTCGreedyDecoder operation
///
/// \param input Logits on which greedy decoding is performed
......
......@@ -21,14 +21,15 @@
using namespace std;
using namespace ngraph;
const string op::DetectionOutput::type_name{"DetectionOutput"};
op::DetectionOutput::DetectionOutput(const std::shared_ptr<Node>& box_logits,
const std::shared_ptr<Node>& class_preds,
const std::shared_ptr<Node>& proposals,
const std::shared_ptr<Node>& aux_class_preds,
const std::shared_ptr<Node>& aux_box_preds,
const DetectionOutputAttrs& attrs)
: Op("DetectionOutput",
check_single_output_args(
: Op(check_single_output_args(
{box_logits, class_preds, proposals, aux_class_preds, aux_box_preds}))
, m_attrs(attrs)
{
......
......@@ -47,6 +47,9 @@ namespace ngraph
class DetectionOutput : public Op
{
public:
NGRAPH_API
static const std::string type_name;
const std::string& description() const override { return type_name; }
/// \brief Constructs a DetectionOutput operation
///
/// \param box_logits Box logits
......
......@@ -21,10 +21,12 @@
using namespace std;
using namespace ngraph;
const string op::Interpolate::type_name{"Interpolate"};
op::Interpolate::Interpolate(const std::shared_ptr<Node>& image,
const std::shared_ptr<Node>& output_shape,
const InterpolateAttrs& attrs)
: Op("Interpolate", check_single_output_args({image, output_shape}))
: Op(check_single_output_args({image, output_shape}))
, m_attrs(attrs)
{
constructor_validate_and_infer_types();
......
......@@ -36,6 +36,9 @@ namespace ngraph
class Interpolate : public Op
{
public:
NGRAPH_API
static const std::string type_name;
const std::string& description() const override { return type_name; }
/// \brief Constructs a Interpolate operation
///
/// \param image Input image
......
......@@ -21,10 +21,12 @@
using namespace std;
using namespace ngraph;
const string op::PriorBox::type_name{"PriorBox"};
op::PriorBox::PriorBox(const shared_ptr<Node>& layer_shape,
const shared_ptr<Node>& image_shape,
const PriorBoxAttrs& attrs)
: Op("PriorBox", check_single_output_args({layer_shape, image_shape}))
: Op(check_single_output_args({layer_shape, image_shape}))
, m_attrs(attrs)
{
constructor_validate_and_infer_types();
......
......@@ -49,6 +49,9 @@ namespace ngraph
class PriorBox : public Op
{
public:
NGRAPH_API
static const std::string type_name;
const std::string& description() const override { return type_name; }
/// \brief Constructs a PriorBox operation
///
/// \param layer_shape Shape of layer for which prior boxes are computed
......
......@@ -21,10 +21,12 @@
using namespace std;
using namespace ngraph;
const string op::PriorBoxClustered::type_name{"PriorBoxClustered"};
op::PriorBoxClustered::PriorBoxClustered(const shared_ptr<Node>& layer_shape,
const shared_ptr<Node>& image_shape,
const PriorBoxClusteredAttrs& attrs)
: Op("PriorBoxClustered", check_single_output_args({layer_shape, image_shape}))
: Op(check_single_output_args({layer_shape, image_shape}))
, m_attrs(attrs)
{
constructor_validate_and_infer_types();
......
......@@ -47,6 +47,9 @@ namespace ngraph
class PriorBoxClustered : public Op
{
public:
NGRAPH_API
static const std::string type_name;
const std::string& description() const override { return type_name; }
/// \brief Constructs a PriorBoxClustered operation
///
/// \param layer_shape Shape of layer for which prior boxes are computed
......
......@@ -21,11 +21,13 @@
using namespace std;
using namespace ngraph;
const string op::Proposal::type_name{"Proposal"};
op::Proposal::Proposal(const std::shared_ptr<Node>& class_probs,
const std::shared_ptr<Node>& class_logits,
const std::shared_ptr<Node>& image_shape,
const ProposalAttrs& attrs)
: Op("Proposal", check_single_output_args({class_probs, class_logits, image_shape}))
: Op(check_single_output_args({class_probs, class_logits, image_shape}))
, m_attrs(attrs)
{
constructor_validate_and_infer_types();
......
......@@ -57,6 +57,9 @@ namespace ngraph
class Proposal : public Op
{
public:
NGRAPH_API
static const std::string type_name;
const std::string& description() const override { return type_name; }
/// \brief Constructs a Proposal operation
///
/// \param class_probs Class probability scores
......
......@@ -19,6 +19,8 @@
using namespace std;
using namespace ngraph;
const string op::PSROIPooling::type_name{"PSROIPooling"};
op::PSROIPooling::PSROIPooling(const shared_ptr<Node>& input,
const std::shared_ptr<Node>& coords,
const size_t output_dim,
......@@ -26,7 +28,7 @@ op::PSROIPooling::PSROIPooling(const shared_ptr<Node>& input,
const float spatial_scale,
const Shape& num_bins,
const std::string& kind)
: Op("PSROIPooling", check_single_output_args({input, coords}))
: Op(check_single_output_args({input, coords}))
, m_output_dim(output_dim)
, m_group_size(group_size)
, m_spatial_scale(spatial_scale)
......
......@@ -25,6 +25,9 @@ namespace ngraph
class PSROIPooling : public Op
{
public:
NGRAPH_API
static const std::string type_name;
const std::string& description() const override { return type_name; }
/// \brief Constructs a PSROIPooling operation
///
/// \param input Input feature map {N, C, ...}
......
......@@ -19,6 +19,8 @@
using namespace std;
using namespace ngraph;
const string op::RegionYolo::type_name{"RegionYolo"};
op::RegionYolo::RegionYolo(const shared_ptr<Node>& input,
const size_t num_coords,
const size_t num_classes,
......@@ -27,7 +29,7 @@ op::RegionYolo::RegionYolo(const shared_ptr<Node>& input,
const vector<int64_t>& mask,
const int axis,
const int end_axis)
: Op("RegionYolo", check_single_output_args({input}))
: Op(check_single_output_args({input}))
, m_num_coords(num_coords)
, m_num_classes(num_classes)
, m_num_regions(num_regions)
......
......@@ -25,6 +25,9 @@ namespace ngraph
class RegionYolo : public Op
{
public:
NGRAPH_API
static const std::string type_name;
const std::string& description() const override { return type_name; }
/// \brief Constructs a RegionYolo operation
///
/// \param input Input
......
......@@ -21,8 +21,10 @@
using namespace std;
using namespace ngraph;
const string op::ReorgYolo::type_name{"ReorgYolo"};
op::ReorgYolo::ReorgYolo(const shared_ptr<Node>& input, const Strides& strides)
: Op("ReorgYolo", check_single_output_args({input}))
: Op(check_single_output_args({input}))
, m_strides(strides)
{
constructor_validate_and_infer_types();
......
......@@ -25,6 +25,9 @@ namespace ngraph
class ReorgYolo : public Op
{
public:
NGRAPH_API
static const std::string type_name;
const std::string& description() const override { return type_name; }
/// \brief Constructs a ReorgYolo operation
///
/// \param input Input
......
......@@ -19,12 +19,14 @@
using namespace std;
using namespace ngraph;
const string op::ROIPooling::type_name{"ROIPooling"};
op::ROIPooling::ROIPooling(const shared_ptr<Node>& input,
const std::shared_ptr<Node>& coords,
const Shape& output_size,
const float spatial_scale,
const std::string& kind)
: Op("ROIPooling", check_single_output_args({input, coords}))
: Op(check_single_output_args({input, coords}))
, m_output_size(output_size)
, m_spatial_scale(spatial_scale)
, m_kind(kind)
......
......@@ -25,6 +25,9 @@ namespace ngraph
class ROIPooling : public Op
{
public:
NGRAPH_API
static const std::string type_name;
const std::string& description() const override { return type_name; }
/// \brief Constructs a ROIPooling operation
///
/// \param input Input feature map {N, C, ...}
......
......@@ -23,8 +23,10 @@
using namespace std;
using namespace ngraph;
const string op::QuantizedConcat::type_name{"QuantizedConcat"};
op::QuantizedConcat::QuantizedConcat(const NodeVector& args, size_t concatenation_axis)
: Op("QuantizedConcat", check_single_output_args(args))
: Op(check_single_output_args(args))
, m_concatenation_axis(concatenation_axis)
{
constructor_validate_and_infer_types();
......
......@@ -28,6 +28,9 @@ namespace ngraph
class QuantizedConcat : public Op
{
public:
NGRAPH_API
static const std::string type_name;
const std::string& description() const override { return type_name; }
/// \brief Constructs a concatenation operation.
///
/// \param args The nodes producing the input tensors.
......
......@@ -20,8 +20,10 @@
using namespace std;
using namespace ngraph;
const string op::ShapeOf::type_name{"ShapeOf"};
op::ShapeOf::ShapeOf(const shared_ptr<Node>& arg)
: Op("ShapeOf", check_single_output_args({arg}))
: Op(check_single_output_args({arg}))
{
constructor_validate_and_infer_types();
}
......
......@@ -26,6 +26,9 @@ namespace ngraph
class ShapeOf : public Op
{
public:
NGRAPH_API
static const std::string type_name;
const std::string& description() const override { return type_name; }
/// \brief Constructs a shape-of operation.
ShapeOf(const std::shared_ptr<Node>& arg);
......
......@@ -21,8 +21,10 @@
using namespace std;
using namespace ngraph;
const string op::Tile::type_name{"Tile"};
op::Tile::Tile(const std::shared_ptr<Node>& arg, const std::shared_ptr<Node>& repeats)
: Op("Tile", check_single_output_args({arg, repeats}))
: Op(check_single_output_args({arg, repeats}))
{
constructor_validate_and_infer_types();
}
......
......@@ -27,6 +27,9 @@ namespace ngraph
class Tile : public Op
{
public:
NGRAPH_API
static const std::string type_name;
const std::string& description() const override { return type_name; }
/// \brief Perform dynamic padding of a tensor
///
/// \param arg The node producing input tensor to be padded.
......
......@@ -22,8 +22,10 @@
using namespace std;
using namespace ngraph;
const string op::Transpose::type_name{"Transpose"};
op::Transpose::Transpose(const shared_ptr<Node>& arg, const shared_ptr<Node>& input_order)
: Op("Transpose", check_single_output_args({arg, input_order}))
: Op(check_single_output_args({arg, input_order}))
{
constructor_validate_and_infer_types();
}
......
......@@ -28,6 +28,9 @@ namespace ngraph
class Transpose : public Op
{
public:
NGRAPH_API
static const std::string type_name;
const std::string& description() const override { return type_name; }
/// \brief Constructs a transpose operation.
///
/// \param arg Node producing the tensor to be transposed.
......
......@@ -17,7 +17,6 @@
#pragma once
#include "ngraph/op/op.hpp"
#include "ngraph/runtime/cpu/cpu_backend_visibility.h"
namespace ngraph
{
......@@ -35,7 +34,6 @@ namespace ngraph
class BatchMatMulTranspose : public Op
{
public:
CPU_BACKEND_API
static const std::string type_name;
const std::string& description() const override { return type_name; }
/// \brief Constructs a batch of matmul product operation.
......
......@@ -30,7 +30,6 @@ namespace ngraph
class BatchNormTrainingRelu : public Op
{
public:
CPU_BACKEND_API
static const std::string type_name;
const std::string& description() const override { return type_name; }
CPU_BACKEND_API BatchNormTrainingRelu(double eps,
......@@ -60,7 +59,6 @@ namespace ngraph
class BatchNormInferenceRelu : public Op
{
public:
CPU_BACKEND_API
static const std::string type_name;
const std::string& description() const override { return type_name; }
BatchNormInferenceRelu(double eps,
......
......@@ -19,7 +19,6 @@
#include "ngraph/node.hpp"
#include "ngraph/op/op.hpp"
#include "ngraph/op/util/unary_elementwise_arithmetic.hpp"
#include "ngraph/runtime/cpu/cpu_backend_visibility.h"
namespace ngraph
{
......@@ -30,7 +29,6 @@ namespace ngraph
class BoundedRelu : public ngraph::op::util::UnaryElementwiseArithmetic
{
public:
CPU_BACKEND_API
static const std::string type_name;
const std::string& description() const override { return type_name; }
/// \brief Constructs a BoundedRelu operation.
......
......@@ -18,7 +18,6 @@
#include "ngraph/op/convolution.hpp"
#include "ngraph/op/op.hpp"
#include "ngraph/runtime/cpu/cpu_backend_visibility.h"
namespace ngraph
{
......@@ -27,7 +26,6 @@ namespace ngraph
class ConvolutionAdd : public Op
{
public:
CPU_BACKEND_API
static const std::string type_name;
const std::string& description() const override { return type_name; }
ConvolutionAdd(const std::shared_ptr<op::Convolution>& conv,
......
......@@ -28,7 +28,6 @@ namespace ngraph
class ConvolutionRelu : public Op
{
public:
CPU_BACKEND_API
static const std::string type_name;
const std::string& description() const override { return type_name; }
CPU_BACKEND_API ConvolutionRelu(const std::shared_ptr<op::Convolution>& conv);
......
......@@ -35,7 +35,6 @@ namespace ngraph
class ConvertLayout : public ngraph::op::Op
{
public:
CPU_BACKEND_API
static const std::string type_name;
const std::string& description() const override { return type_name; }
CPU_BACKEND_API ConvertLayout(
......
......@@ -18,7 +18,6 @@
#include "ngraph/op/convolution.hpp"
#include "ngraph/op/op.hpp"
#include "ngraph/runtime/cpu/cpu_backend_visibility.h"
namespace ngraph
{
......@@ -28,7 +27,6 @@ namespace ngraph
class DeconvolutionBias : public Op
{
public:
CPU_BACKEND_API
static const std::string type_name;
const std::string& description() const override { return type_name; }
/// \brief Constructs a batched-convolution data batch-backprop operation.
......
......@@ -17,7 +17,6 @@
#pragma once
#include "ngraph/op/op.hpp"
#include "ngraph/runtime/cpu/cpu_backend_visibility.h"
#include "ngraph/util.hpp"
namespace ngraph
......@@ -27,7 +26,6 @@ namespace ngraph
class Dropout : public Op
{
public:
CPU_BACKEND_API
static const std::string type_name;
const std::string& description() const override { return type_name; }
Dropout(const Output<Node>& input,
......
......@@ -17,7 +17,6 @@
#pragma once
#include "ngraph/op/fused/group_conv.hpp"
#include "ngraph/op/op.hpp"
#include "ngraph/runtime/cpu/cpu_backend_visibility.h"
namespace ngraph
{
......@@ -28,7 +27,6 @@ namespace ngraph
class GroupConvolutionBias : public Op
{
public:
CPU_BACKEND_API
static const std::string type_name;
const std::string& description() const override { return type_name; }
GroupConvolutionBias(const std::shared_ptr<op::GroupConvolution>& conv,
......
......@@ -20,7 +20,6 @@
#include <vector>
#include "ngraph/op/op.hpp"
#include "ngraph/runtime/cpu/cpu_backend_visibility.h"
namespace ngraph
{
......@@ -33,7 +32,6 @@ namespace ngraph
class HalideOp : public ngraph::op::Op
{
public:
CPU_BACKEND_API
static const std::string type_name;
const std::string& description() const override { return type_name; }
HalideOp(const OutputVector& args,
......
......@@ -19,7 +19,6 @@
#include "ngraph/node.hpp"
#include "ngraph/op/op.hpp"
#include "ngraph/op/util/unary_elementwise_arithmetic.hpp"
#include "ngraph/runtime/cpu/cpu_backend_visibility.h"
namespace ngraph
{
......@@ -31,7 +30,6 @@ namespace ngraph
class CPULeakyRelu : public ngraph::op::util::UnaryElementwiseArithmetic
{
public:
CPU_BACKEND_API
static const std::string type_name;
const std::string& description() const override { return type_name; }
/// \brief Constructs a CPULeakyRelu operation.
......
......@@ -17,7 +17,6 @@
#pragma once
#include "ngraph/op/op.hpp"
#include "ngraph/runtime/cpu/cpu_backend_visibility.h"
#include "ngraph/runtime/cpu/op/rnn_utils.hpp"
#include "ngraph/util.hpp"
......@@ -28,7 +27,6 @@ namespace ngraph
class Lstm : public Op
{
public:
CPU_BACKEND_API
static const std::string type_name;
const std::string& description() const override { return type_name; }
// INPUTS:
......
......@@ -27,7 +27,6 @@ namespace ngraph
class MatmulBias : public Op
{
public:
CPU_BACKEND_API
static const std::string type_name;
const std::string& description() const override { return type_name; }
CPU_BACKEND_API MatmulBias(const Output<Node>& W,
......
......@@ -32,7 +32,6 @@ namespace ngraph
class MaxPoolWithIndices : public Op
{
public:
CPU_BACKEND_API
static const std::string type_name;
const std::string& description() const override { return type_name; }
CPU_BACKEND_API MaxPoolWithIndices(const Output<Node>& arg,
......@@ -68,7 +67,6 @@ namespace ngraph
class MaxPoolWithIndicesBackprop : public Op
{
public:
CPU_BACKEND_API
static const std::string type_name;
const std::string& description() const override { return type_name; }
CPU_BACKEND_API MaxPoolWithIndicesBackprop(const Output<Node>& arg_forward,
......
......@@ -19,7 +19,6 @@
#include <utility>
#include "ngraph/op/op.hpp"
#include "ngraph/runtime/cpu/cpu_backend_visibility.h"
namespace ngraph
{
......@@ -28,7 +27,6 @@ namespace ngraph
class QuantizedMatmul : public Op
{
public:
CPU_BACKEND_API
static const std::string type_name;
const std::string& description() const override { return type_name; }
QuantizedMatmul(const Output<Node>& data,
......
......@@ -48,7 +48,6 @@ namespace ngraph
class Rnn : public Op
{
public:
CPU_BACKEND_API
static const std::string type_name;
const std::string& description() const override { return type_name; }
CPU_BACKEND_API Rnn(const Output<Node>& src_layer,
......
......@@ -30,7 +30,6 @@ namespace ngraph
class SigmoidMultiply : public Op
{
public:
CPU_BACKEND_API
static const std::string type_name;
const std::string& description() const override { return type_name; }
/// Defines valid function types
......@@ -69,7 +68,6 @@ namespace ngraph
class SigmoidMultiplyBackprop : public Op
{
public:
CPU_BACKEND_API
static const std::string type_name;
const std::string& description() const override { return type_name; }
typedef SigmoidMultiply::FunctionType FunctionType;
......
......@@ -18,7 +18,6 @@
#include "ngraph/coordinate.hpp"
#include "ngraph/op/op.hpp"
#include "ngraph/runtime/cpu/cpu_backend_visibility.h"
#include "ngraph/strides.hpp"
namespace ngraph
......@@ -51,7 +50,6 @@ namespace ngraph
class UpdateSlice : public Op
{
public:
CPU_BACKEND_API
static const std::string type_name;
const std::string& description() const override { return type_name; }
/// \brief Constructs a tensor slice update operation.
......
......@@ -39,7 +39,6 @@ namespace ngraph
class ngraph::runtime::plaidml::op::Convolution final : public ngraph::op::Op
{
public:
NGRAPH_API
static const std::string type_name;
const std::string& description() const override { return type_name; }
Convolution(std::shared_ptr<ngraph::op::Convolution> src,
......@@ -66,7 +65,6 @@ private:
class ngraph::runtime::plaidml::op::ConvolutionBackpropData final : public ngraph::op::Op
{
public:
NGRAPH_API
static const std::string type_name;
const std::string& description() const override { return type_name; }
ConvolutionBackpropData(std::shared_ptr<ngraph::op::ConvolutionBackpropData> src,
......@@ -93,7 +91,6 @@ private:
class ngraph::runtime::plaidml::op::ConvolutionBackpropFilters final : public ngraph::op::Op
{
public:
NGRAPH_API
static const std::string type_name;
const std::string& description() const override { return type_name; }
ConvolutionBackpropFilters(std::shared_ptr<ngraph::op::ConvolutionBackpropFilters> src,
......
......@@ -40,7 +40,6 @@ namespace ngraph
class ngraph::runtime::plaidml::op::ImplicitBroadcast final : public ngraph::op::Op
{
public:
NGRAPH_API
static const std::string type_name;
const std::string& description() const override { return type_name; }
ImplicitBroadcast(const Output<Node>& input, const Shape& shape);
......
......@@ -39,7 +39,6 @@ namespace ngraph
class ngraph::runtime::plaidml::op::Replicate final : public ngraph::op::Op
{
public:
NGRAPH_API
static const std::string type_name;
const std::string& description() const override { return type_name; }
Replicate(const Output<Node>& arg, std::size_t replication_axis, std::size_t replication_count);
......
......@@ -38,7 +38,6 @@ namespace ngraph
class ngraph::runtime::plaidml::op::Winograd final : public ngraph::op::Op
{
public:
NGRAPH_API
static const std::string type_name;
const std::string& description() const override { return type_name; }
Winograd(std::shared_ptr<Convolution> conv, const OutputVector& args);
......
......@@ -17,7 +17,7 @@
#include <cstring>
#include <gtest/gtest.h>
#include <onnxifi.h>
#include <onnx/onnxifi.h>
#include "ngraph/runtime/backend_manager.hpp"
......
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