Update nGraph to v0.22.1

cmake/external/ngraph.cmake

@@ -11,7 +11,7 @@ set(ngraph_SRC ${CMAKE_CURRENT_BINARY_DIR}/ngraph/src/project_ngraph)
 set(prebuilt_ONNX_SOURCE_DIR "${PROJECT_SOURCE_DIR}/external/onnx")
 set(prebuilt_ONNX_BINARY_DIR "${CMAKE_CURRENT_BINARY_DIR}/onnx")
 set(ngraph_URL "https://github.com/NervanaSystems/ngraph.git")
-set(ngraph_TAG "v0.18.1")
+set(ngraph_TAG "v0.22.1")
 
 # Libraries for python package.
 if (WIN32)
@@ -42,7 +42,7 @@ else()
 endif()
 
 # discard prior changes due to unblock incremental builds.
-set(NGRAPH_PATCH_DISCARD_COMMAND cd ${ngraph_SRC} && git checkout -- .)
+set(NGRAPH_PATCH_DISCARD_COMMAND cd ${ngraph_SRC} && git reset HEAD --hard && git clean -fx)
 
 if (MSVC)
     set(prebuilt_ONNX_BINARY_DIR "${CMAKE_CURRENT_BINARY_DIR}/onnx/${CMAKE_BUILD_TYPE}")
@@ -54,12 +54,12 @@ if (MSVC)
             PREFIX ngraph
             GIT_REPOSITORY ${ngraph_URL}
             GIT_TAG ${ngraph_TAG}
+            GIT_CONFIG core.autocrlf=input
             PATCH_COMMAND ${NGRAPH_PATCH_DISCARD_COMMAND}
             COMMAND ${CMAKE_COMMAND} -E copy ${PROJECT_SOURCE_DIR}/patches/ngraph/ngraph_onnx.cmake ${ngraph_SRC}/cmake/external_onnx.cmake
             COMMAND git apply --ignore-space-change --ignore-whitespace ${PROJECT_SOURCE_DIR}/patches/ngraph/ngraph_protobuf.patch
-            COMMAND git apply --ignore-space-change --ignore-whitespace ${PROJECT_SOURCE_DIR}/patches/ngraph/ngraph_fix_install_error.patch
-            COMMAND git apply --ignore-space-change --ignore-whitespace ${PROJECT_SOURCE_DIR}/patches/ngraph/ngraph_fix_library_path.patch
             COMMAND git apply --ignore-space-change --ignore-whitespace ${PROJECT_SOURCE_DIR}/patches/ngraph/ngraph_fix_memory.patch
+            COMMAND git apply --ignore-space-change --ignore-whitespace ${PROJECT_SOURCE_DIR}/patches/ngraph/ngraph_fix_mkldnn_missing_symbol.patch
             CMAKE_ARGS
                 -DCMAKE_BUILD_TYPE=${CMAKE_BUILD_TYPE}
                 -DNGRAPH_DEX_ONLY=ON

cmake/patches/ngraph/ngraph_fix_mkldnn_missing_symbol.patch

@@ -0,0 +1,64 @@
+ cmake/external_mkldnn.cmake   |  1 +
+ cmake/mkldnn_fix_missing_symbol.patch | 99 +++++++++++++++++++++++++++++++++++
+ 2 files changed, 100 insertions(+)
+ create mode 100644 cmake/mkldnn_fix_missing_symbol.patch
+
+diff --git a/cmake/external_mkldnn.cmake b/cmake/external_mkldnn.cmake
+index 7874aca76..bbae6d1a4 100644
+--- a/cmake/external_mkldnn.cmake
++++ b/cmake/external_mkldnn.cmake
+@@ -194,7 +194,8 @@ if (WIN32)
+         CONFIGURE_COMMAND
+         PATCH_COMMAND ${MKLDNN_PATCH_REVERT_COMMAND}
+         COMMAND git apply --ignore-space-change --ignore-whitespace ${CMAKE_SOURCE_DIR}/cmake/${MKLDNN_PATCH_FILE}
+         COMMAND git apply --ignore-space-change --ignore-whitespace ${CMAKE_SOURCE_DIR}/cmake/mkldnn_fix_memory.patch
++        COMMAND git apply --ignore-space-change --ignore-whitespace ${CMAKE_SOURCE_DIR}/cmake/mkldnn_fix_missing_symbol.patch
+         CMAKE_GENERATOR ${CMAKE_GENERATOR}
+         CMAKE_GENERATOR_PLATFORM ${CMAKE_GENERATOR_PLATFORM}
+         CMAKE_GENERATOR_TOOLSET ${CMAKE_GENERATOR_TOOLSET}
+diff --git a/cmake/mkldnn_fix_missing_symbol.patch b/cmake/mkldnn_fix_missing_symbol.patch
+new file mode 100644
+index 000000000..ea1a3bd61
+--- /dev/null
++++ b/cmake/mkldnn_fix_missing_symbol.patch
+@@ -0,0 +1,40 @@
++commit d485a54ac2b07b7349dabd833961415315a18fea
++Author: Denis Samoilov <[email protected]>
++Date:   Sun Apr 14 20:11:33 2019 -0700
++
++    cpu: gemv: fix unresolved symbol
++
++    Fixes #456
++
++diff --git a/src/cpu/gemm/gemm_driver.cpp b/src/cpu/gemm/gemm_driver.cpp
++index 0773b212..df7bc44d 100644
++--- a/src/cpu/gemm/gemm_driver.cpp
+++++ b/src/cpu/gemm/gemm_driver.cpp
++@@ -1304,10 +1304,8 @@ static mkldnn_status_t gemm_threading_driver(
++                 (float *) arg->co);
++     }
++ 
++-    if (data_traits<a_type>::data_type == data_type::s8) {
++-        if (gemm_s8u8s32_jump_to_gemv_s8u8s32(arg)) {
++-            return mkldnn_success;
++-        }
+++    if (gemm_s8u8s32_jump_to_gemv_s8u8s32(arg)) {
+++        return mkldnn_success;
++     }
++ 
++     int nthr = (mkldnn_in_parallel()) ? 1 : mkldnn_get_max_threads();
++diff --git a/src/cpu/gemm/s8x8s32/jit_avx512_core_gemv_s8u8s32.cpp b/src/cpu/gemm/s8x8s32/jit_avx512_core_gemv_s8u8s32.cpp
++index 73d50e40..81646a43 100644
++--- a/src/cpu/gemm/s8x8s32/jit_avx512_core_gemv_s8u8s32.cpp
+++++ b/src/cpu/gemm/s8x8s32/jit_avx512_core_gemv_s8u8s32.cpp
++@@ -29,6 +29,10 @@ namespace cpu {
++ template <typename T>
++ int gemm_s8u8s32_jump_to_gemv_s8u8s32(T *arg);
++ 
+++template <>
+++int gemm_s8u8s32_jump_to_gemv_s8u8s32(
+++        gemm_info_t<float, float, float> *arg) { return 0; }
+++
++ template <>
++ int gemm_s8u8s32_jump_to_gemv_s8u8s32(
++         gemm_info_t<int8_t, uint8_t, int32_t> *arg) {

onnxruntime/core/providers/ngraph/ngraph_custom_op.cc

@@ -35,15 +35,23 @@ static bool check_ngraph_dump_ops() {
 #endif
 }
 
-NGRAPHCustomOp::NGRAPHCustomOp(const ComputeContext* context, const ONNX_NAMESPACE::ModelProto& model_proto,
-                               const std::shared_ptr<ngraph::runtime::Backend>& ng_backend)
-    : ng_backend_{ng_backend},
-      model_proto_{model_proto} {
+NGRAPHCustomOp::NGRAPHCustomOp(const ComputeContext* context,
+                               const ONNX_NAMESPACE::ModelProto& model_proto,
+                               const std::shared_ptr<ONNX_NAMESPACE::AttributeProto> initializers,
+                               const std::shared_ptr<ngraph::runtime::Backend>& ng_backend) :
+  ng_backend_{ng_backend}, model_proto_{model_proto}
+{
   allocate_func_ = context->allocate_func;
   release_func_ = context->release_func;
   allocator_ = context->allocator_handle;
   name_ = context->node_name;
 
+  auto graph_proto = model_proto_.mutable_graph();
+
+  for (const auto& initializer : initializers->tensors()) {
+    graph_proto->add_initializer()->CopyFrom(initializer);
+  }
+
   if (check_ngraph_dump_ops()) {
     std::fstream dump(name_ + ".onnx", std::ios::out | std::ios::trunc | std::ios::binary);
     model_proto_.SerializeToOstream(&dump);
@@ -59,7 +67,6 @@ NGRAPHCustomOp::~NGRAPHCustomOp() {
 //This method gets called in critical path of execution: Optimize
 void NGRAPHCustomOp::Initialize(const OrtCustomOpApi* api, OrtKernelContext* context) const {
   Ort::CustomOpApi ort{*api};
-  LOGS_DEFAULT(INFO) << "nGraph compiling customOp: " << name_;
 
   size_t num_inputs = ort.KernelContext_GetInputCount(context);
 
@@ -88,6 +95,9 @@ void NGRAPHCustomOp::Initialize(const OrtCustomOpApi* api, OrtKernelContext* con
     return;
   } else {
     auto graph_proto = model_proto_.mutable_graph();
+
+    LOGS_DEFAULT(INFO) << "[NGRAPHCustomOp] Compiling customOp: " << name_;
+
     // Clear previous shapes if any and set new input shapes
     for (size_t i = 0; i < num_inputs; i++) {
       auto g_in_shape = graph_proto->mutable_input((int)i)->mutable_type()->mutable_tensor_type()->mutable_shape();
@@ -108,12 +118,12 @@ void NGRAPHCustomOp::Initialize(const OrtCustomOpApi* api, OrtKernelContext* con
     try {
       ng_function = ngraph::onnx_import::import_onnx_model(model_stream);
     } catch (const std::exception& exp) {
-      LOGS_DEFAULT(FATAL) << "[" << name_ << "] "
-                          << "Exception while converting onnx to nGraph: " << std::string(exp.what());
+      LOGS_DEFAULT(FATAL) << "[NGRAPHCustomOp] " << " - " << name_ << " - "
+                          << "Exception while importing model to nGraph: " << std::string(exp.what());
       throw;
     } catch (...) {
-      LOGS_DEFAULT(FATAL) << "[" << name_ << "] "
-                          << "Unknown exception while converting onnx to nGraph";
+      LOGS_DEFAULT(FATAL) << "[NGRAPHCustomOp] " << " - " << name_ << " - "
+                          << "Unknown exception while importing model to nGraph";
       throw;
     }
 
@@ -125,9 +135,10 @@ void NGRAPHCustomOp::Initialize(const OrtCustomOpApi* api, OrtKernelContext* con
     try {
       ng_curr_exe_ = ng_backend_->compile(ng_function);
     } catch (const std::exception& exp) {
-      LOGS_DEFAULT(FATAL) << "Exception while compiling nGraph Op: " << name_ << std::string(exp.what());
+      LOGS_DEFAULT(FATAL) << "[NGRAPHCustomOp] " << " - " << name_ << " - "
+                          << "Exception while compiling ngraph::Function: " << std::string(exp.what());
     } catch (...) {
-      LOGS_DEFAULT(FATAL) << "Unknown exception while compiling nGraph Op: " << name_;
+      LOGS_DEFAULT(FATAL) << "[NGRAPHCustomOp] " << " - " << name_ << " - " << "Unknown exception while compiling ngraph::Function";
     }
     it.first->second = ng_curr_exe_;
   }
@@ -157,9 +168,9 @@ Status NGRAPHCustomOp::Compute(const OrtCustomOpApi* api, OrtKernelContext* cont
       ng_inputs.emplace_back(ng_backend_->create_tensor(ng_param->get_output_element_type(0), ng_param->get_output_shape(0), input_data));
     }
   } catch (const std::exception& exp) {
-    return ORT_MAKE_STATUS(ONNXRUNTIME, FAIL, "Exception while copying input data to nGraph: " + std::string(exp.what()));
+    return ORT_MAKE_STATUS(ONNXRUNTIME, FAIL, name_ + ": Exception while copying input data to nGraph: " + std::string(exp.what()));
   } catch (...) {
-    return ORT_MAKE_STATUS(ONNXRUNTIME, FAIL, "Unknown exception while copying input data to nGraph");
+    return ORT_MAKE_STATUS(ONNXRUNTIME, FAIL, name_ + ": Unknown exception while copying input data to nGraph");
   }
 
   // Initialize output tensors
@@ -176,19 +187,19 @@ Status NGRAPHCustomOp::Compute(const OrtCustomOpApi* api, OrtKernelContext* cont
       ng_outputs.emplace_back(ng_backend_->create_tensor(dtype, shape, output_data));
     }
   } catch (const std::exception& exp) {
-    return ORT_MAKE_STATUS(ONNXRUNTIME, FAIL, "Exception while creating nGraph output Tensor: " + std::string(exp.what()));
+    return ORT_MAKE_STATUS(ONNXRUNTIME, FAIL, name_ + ": Exception while creating nGraph output Tensor: " + std::string(exp.what()));
   } catch (...) {
-    return ORT_MAKE_STATUS(ONNXRUNTIME, FAIL, "Unknown exception while creating nGraph output Tensor");
+    return ORT_MAKE_STATUS(ONNXRUNTIME, FAIL, name_ + ": Unknown exception while creating nGraph output Tensor");
   }
 
   // Run the graph through nGraph.
   try {
     if (!ng_curr_exe_->call(ng_outputs, ng_inputs))
-      return ORT_MAKE_STATUS(ONNXRUNTIME, FAIL, "Error while executing nGraph computation");
+      return ORT_MAKE_STATUS(ONNXRUNTIME, FAIL, name_ + ": Error while executing nGraph computation");
   } catch (const std::exception& exp) {
-    return ORT_MAKE_STATUS(ONNXRUNTIME, FAIL, "Exception while executing nGraph computation: " + std::string(exp.what()));
+    return ORT_MAKE_STATUS(ONNXRUNTIME, FAIL, name_ + ": Exception while executing nGraph computation: " + std::string(exp.what()));
   } catch (...) {
-    return ORT_MAKE_STATUS(ONNXRUNTIME, FAIL, "Unknown exception while executing nGraph computation");
+    return ORT_MAKE_STATUS(ONNXRUNTIME, FAIL, name_ + ": Unknown exception while executing nGraph computation");
   }
 
   return Status::OK();

onnxruntime/core/providers/ngraph/ngraph_custom_op.h

@@ -25,7 +25,10 @@ namespace ngraph_ep {
 
 class NGRAPHCustomOp {
  public:
-  NGRAPHCustomOp(const ComputeContext* context, const ONNX_NAMESPACE::ModelProto& model_proto, const std::shared_ptr<ngraph::runtime::Backend>& ng_backend);
+  NGRAPHCustomOp(const ComputeContext* context,
+                 const ONNX_NAMESPACE::ModelProto& model_proto,
+                 const std::shared_ptr<ONNX_NAMESPACE::AttributeProto> initializers,
+                 const std::shared_ptr<ngraph::runtime::Backend>& ng_backend);
 
   Status Compute(const OrtCustomOpApi* api, OrtKernelContext* context) const;