Cleanup IE and ngraph

1. InferenceEngine::SizeVector 2. InferenceEngine::parallel_for 3. all ngraph namespace except ngraph::op
riverlijunjie · Nov 1, 2023 · f5fd042 · f5fd042
1 parent 51cf5fa
commit f5fd042
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Showing 228 changed files with 1,158 additions and 1,159 deletions.
diff --git a/src/plugins/intel_cpu/src/compiled_model.cpp b/src/plugins/intel_cpu/src/compiled_model.cpp
@@ -56,7 +56,6 @@ CompiledModel::CompiledModel(const std::shared_ptr<ov::Model>& model,
       m_name{model->get_name()},
       m_loaded_from_cache(loaded_from_cache) {
     bool isFloatModel = !ov::op::util::has_op_with_type<ngraph::op::FakeQuantize>(m_model);
-
     m_mutex = std::make_shared<std::mutex>();
     const auto& core = m_plugin->get_core();
     if (!core)

diff --git a/src/plugins/intel_cpu/src/emitters/x64/cpu_generator.cpp b/src/plugins/intel_cpu/src/emitters/x64/cpu_generator.cpp
@@ -31,7 +31,7 @@ using namespace std;
     [this](const ov::snippets::lowered::ExpressionPtr& expr) -> std::shared_ptr<snippets::Emitter> { \
         return std::make_shared<e_type>(h.get(), isa, expr); \
     }, \
-    [](const std::shared_ptr<ngraph::Node>& n) -> std::set<std::vector<element::Type>> { \
+    [](const std::shared_ptr<ov::Node>& n) -> std::set<std::vector<element::Type>> { \
         return e_type::get_supported_precisions(n); \
     } \
 };
@@ -40,7 +40,7 @@ using namespace std;
     [this](const ov::snippets::lowered::ExpressionPtr& expr) -> std::shared_ptr<snippets::Emitter> { \
         return std::make_shared<e_type>(h.get(), isa, expr->get_node()); \
     }, \
-    [](const std::shared_ptr<ngraph::Node>& n) -> std::set<std::vector<element::Type>> { \
+    [](const std::shared_ptr<ov::Node>& n) -> std::set<std::vector<element::Type>> { \
         return e_type::get_supported_precisions(n); \
     } \
 };

diff --git a/src/plugins/intel_cpu/src/emitters/x64/jit_conversion_emitters.cpp b/src/plugins/intel_cpu/src/emitters/x64/jit_conversion_emitters.cpp
@@ -17,7 +17,7 @@ using namespace Xbyak;
 namespace ov {
 namespace intel_cpu {
 
-jit_convert_emitter::jit_convert_emitter(jit_generator *host, cpu_isa_t host_isa, const std::shared_ptr<ngraph::Node>& node, Precision exec_prc)
+jit_convert_emitter::jit_convert_emitter(jit_generator *host, cpu_isa_t host_isa, const std::shared_ptr<ov::Node>& node, Precision exec_prc)
 : jit_emitter(host, host_isa, exec_prc) {
     input_type = node->get_input_element_type(0);
     output_type = node->get_output_element_type(0);
@@ -58,7 +58,7 @@ void jit_convert_emitter::float2bfloat(const std::vector<size_t> &in_vec_idxs, c
 }
 
 jit_convert_truncation_emitter::jit_convert_truncation_emitter(jit_generator *host, cpu_isa_t host_isa,
-                                                               const std::shared_ptr<ngraph::Node>& node, Precision exec_prc)
+                                                               const std::shared_ptr<ov::Node>& node, Precision exec_prc)
         : jit_convert_emitter(host, host_isa, node, exec_prc) {
     prepare_table();
 }
@@ -193,7 +193,7 @@ void jit_convert_truncation_emitter::dword2int8(const std::vector<size_t> &in_ve
 }
 
 jit_convert_saturation_emitter::jit_convert_saturation_emitter(jit_generator *host, cpu_isa_t host_isa,
-                                                               const std::shared_ptr<ngraph::Node>& node, Precision exec_prc)
+                                                               const std::shared_ptr<ov::Node>& node, Precision exec_prc)
     : jit_convert_emitter(host, host_isa, node, exec_prc) {
 }
 

diff --git a/src/plugins/intel_cpu/src/emitters/x64/jit_conversion_emitters.hpp b/src/plugins/intel_cpu/src/emitters/x64/jit_conversion_emitters.hpp
@@ -14,7 +14,7 @@ namespace intel_cpu {
 class jit_convert_emitter : public jit_emitter {
 public:
     jit_convert_emitter(dnnl::impl::cpu::x64::jit_generator *host, dnnl::impl::cpu::x64::cpu_isa_t host_isa,
-                        const std::shared_ptr<ngraph::Node>& n, InferenceEngine::Precision exec_prc = InferenceEngine::Precision::FP32);
+                        const std::shared_ptr<ov::Node>& n, InferenceEngine::Precision exec_prc = InferenceEngine::Precision::FP32);
 
     size_t get_inputs_num() const override;
 
@@ -47,7 +47,7 @@ class jit_convert_emitter : public jit_emitter {
 class jit_convert_truncation_emitter : public jit_convert_emitter {
 public:
     jit_convert_truncation_emitter(dnnl::impl::cpu::x64::jit_generator *host, dnnl::impl::cpu::x64::cpu_isa_t host_isa,
-                                   const std::shared_ptr<ngraph::Node>& n, InferenceEngine::Precision exec_prc = InferenceEngine::Precision::FP32);
+                                   const std::shared_ptr<ov::Node>& n, InferenceEngine::Precision exec_prc = InferenceEngine::Precision::FP32);
 
 private:
     void emit_impl(const std::vector<size_t>& in, const std::vector<size_t>& out) const override;
@@ -68,7 +68,7 @@ class jit_convert_truncation_emitter : public jit_convert_emitter {
 class jit_convert_saturation_emitter : public jit_convert_emitter {
 public:
     jit_convert_saturation_emitter(dnnl::impl::cpu::x64::jit_generator *host, dnnl::impl::cpu::x64::cpu_isa_t host_isa,
-                                   const std::shared_ptr<ngraph::Node>& n, InferenceEngine::Precision exec_prc = InferenceEngine::Precision::FP32);
+                                   const std::shared_ptr<ov::Node>& n, InferenceEngine::Precision exec_prc = InferenceEngine::Precision::FP32);
 
 private:
     void emit_impl(const std::vector<size_t>& in, const std::vector<size_t>& out) const override;

diff --git a/src/plugins/intel_cpu/src/emitters/x64/jit_dnnl_emitters.cpp b/src/plugins/intel_cpu/src/emitters/x64/jit_dnnl_emitters.cpp
@@ -13,11 +13,11 @@ using namespace Xbyak;
 namespace ov {
 namespace intel_cpu {
 
-std::set<std::vector<element::Type>> jit_dnnl_emitter::get_supported_precisions(const std::shared_ptr<ngraph::Node>& node) {
+std::set<std::vector<element::Type>> jit_dnnl_emitter::get_supported_precisions(const std::shared_ptr<ov::Node>& node) {
     return {{element::f32}};
 }
 
-jit_dnnl_emitter::jit_dnnl_emitter(jit_generator *host, cpu_isa_t host_isa, const std::shared_ptr<ngraph::Node>& node, InferenceEngine::Precision exec_prc)
+jit_dnnl_emitter::jit_dnnl_emitter(jit_generator *host, cpu_isa_t host_isa, const std::shared_ptr<ov::Node>& node, InferenceEngine::Precision exec_prc)
     : jit_emitter(host, host_isa, exec_prc) {
 
     kind = dnnl_eltwise_tanh;

diff --git a/src/plugins/intel_cpu/src/emitters/x64/jit_dnnl_emitters.hpp b/src/plugins/intel_cpu/src/emitters/x64/jit_dnnl_emitters.hpp
@@ -20,13 +20,13 @@ class jit_dnnl_emitter : public jit_emitter {
 
     void emit_impl(const std::vector<size_t> &in_idxs, const std::vector<size_t> &out_idxs) const override {};
 
-    static std::set<std::vector<element::Type>> get_supported_precisions(const std::shared_ptr<ngraph::Node>& node = nullptr);
+    static std::set<std::vector<element::Type>> get_supported_precisions(const std::shared_ptr<ov::Node>& node = nullptr);
 
 protected:
     jit_dnnl_emitter(dnnl::impl::cpu::x64::jit_generator *host, dnnl::impl::cpu::x64::cpu_isa_t host_isa,
                        dnnl_alg_kind_t algKind, float inpAlpha, float inpBeta,
                        InferenceEngine::Precision exec_prc = InferenceEngine::Precision::FP32);
-    jit_dnnl_emitter(dnnl::impl::cpu::x64::jit_generator *host, dnnl::impl::cpu::x64::cpu_isa_t host_isa, const std::shared_ptr<ngraph::Node>& n,
+    jit_dnnl_emitter(dnnl::impl::cpu::x64::jit_generator *host, dnnl::impl::cpu::x64::cpu_isa_t host_isa, const std::shared_ptr<ov::Node>& n,
                        InferenceEngine::Precision exec_prc = InferenceEngine::Precision::FP32);
     void set_injector();
 

diff --git a/src/plugins/intel_cpu/src/emitters/x64/jit_dnnl_ext_emitters.hpp b/src/plugins/intel_cpu/src/emitters/x64/jit_dnnl_ext_emitters.hpp
@@ -13,7 +13,7 @@ namespace intel_cpu {
 
 class jit_relu_emitter : public jit_dnnl_emitter {
 public:
-    jit_relu_emitter(dnnl::impl::cpu::x64::jit_generator *host, dnnl::impl::cpu::x64::cpu_isa_t host_isa, const std::shared_ptr<ngraph::Node>& n,
+    jit_relu_emitter(dnnl::impl::cpu::x64::jit_generator *host, dnnl::impl::cpu::x64::cpu_isa_t host_isa, const std::shared_ptr<ov::Node>& n,
                        InferenceEngine::Precision exec_prc = InferenceEngine::Precision::FP32)
         : jit_dnnl_emitter(host, host_isa, n, exec_prc) {
             kind = dnnl_eltwise_relu;
@@ -26,7 +26,7 @@ class jit_relu_emitter : public jit_dnnl_emitter {
 
 class jit_sigmoid_emitter : public jit_dnnl_emitter {
 public:
-    jit_sigmoid_emitter(dnnl::impl::cpu::x64::jit_generator *host, dnnl::impl::cpu::x64::cpu_isa_t host_isa, const std::shared_ptr<ngraph::Node>& n,
+    jit_sigmoid_emitter(dnnl::impl::cpu::x64::jit_generator *host, dnnl::impl::cpu::x64::cpu_isa_t host_isa, const std::shared_ptr<ov::Node>& n,
                        InferenceEngine::Precision exec_prc = InferenceEngine::Precision::FP32)
         : jit_dnnl_emitter(host, host_isa, n, exec_prc) {
             kind = dnnl_eltwise_logistic;
@@ -39,7 +39,7 @@ class jit_sigmoid_emitter : public jit_dnnl_emitter {
 
 class jit_tanh_emitter : public jit_dnnl_emitter {
 public:
-    jit_tanh_emitter(dnnl::impl::cpu::x64::jit_generator *host, dnnl::impl::cpu::x64::cpu_isa_t host_isa, const std::shared_ptr<ngraph::Node>& n,
+    jit_tanh_emitter(dnnl::impl::cpu::x64::jit_generator *host, dnnl::impl::cpu::x64::cpu_isa_t host_isa, const std::shared_ptr<ov::Node>& n,
                        InferenceEngine::Precision exec_prc = InferenceEngine::Precision::FP32)
         : jit_dnnl_emitter(host, host_isa, n, exec_prc) {
             kind = dnnl_eltwise_tanh;
@@ -52,11 +52,11 @@ class jit_tanh_emitter : public jit_dnnl_emitter {
 
 class jit_elu_emitter : public jit_dnnl_emitter {
 public:
-    jit_elu_emitter(dnnl::impl::cpu::x64::jit_generator *host, dnnl::impl::cpu::x64::cpu_isa_t host_isa, const std::shared_ptr<ngraph::Node>& n,
+    jit_elu_emitter(dnnl::impl::cpu::x64::jit_generator *host, dnnl::impl::cpu::x64::cpu_isa_t host_isa, const std::shared_ptr<ov::Node>& n,
                        InferenceEngine::Precision exec_prc = InferenceEngine::Precision::FP32)
         : jit_dnnl_emitter(host, host_isa, n, exec_prc) {
             kind = dnnl_eltwise_elu;
-            alpha = ngraph::as_type_ptr<ov::op::v0::Elu>(n)->get_alpha();
+            alpha = ov::as_type_ptr<ov::op::v0::Elu>(n)->get_alpha();
             beta = 0.f;
 
             set_injector();
@@ -65,7 +65,7 @@ class jit_elu_emitter : public jit_dnnl_emitter {
 
 class jit_exp_emitter : public jit_dnnl_emitter {
 public:
-    jit_exp_emitter(dnnl::impl::cpu::x64::jit_generator *host, dnnl::impl::cpu::x64::cpu_isa_t host_isa, const std::shared_ptr<ngraph::Node>& n,
+    jit_exp_emitter(dnnl::impl::cpu::x64::jit_generator *host, dnnl::impl::cpu::x64::cpu_isa_t host_isa, const std::shared_ptr<ov::Node>& n,
                        InferenceEngine::Precision exec_prc = InferenceEngine::Precision::FP32)
         : jit_dnnl_emitter(host, host_isa, n, exec_prc) {
             kind = dnnl_eltwise_exp;
@@ -78,7 +78,7 @@ class jit_exp_emitter : public jit_dnnl_emitter {
 
 class jit_abs_emitter : public jit_dnnl_emitter {
 public:
-    jit_abs_emitter(dnnl::impl::cpu::x64::jit_generator *host, dnnl::impl::cpu::x64::cpu_isa_t host_isa, const std::shared_ptr<ngraph::Node>& n,
+    jit_abs_emitter(dnnl::impl::cpu::x64::jit_generator *host, dnnl::impl::cpu::x64::cpu_isa_t host_isa, const std::shared_ptr<ov::Node>& n,
                        InferenceEngine::Precision exec_prc = InferenceEngine::Precision::FP32)
         : jit_dnnl_emitter(host, host_isa, n, exec_prc) {
             kind = dnnl_eltwise_abs;
@@ -91,11 +91,11 @@ class jit_abs_emitter : public jit_dnnl_emitter {
 
 class jit_clamp_emitter : public jit_dnnl_emitter {
 public:
-    jit_clamp_emitter(dnnl::impl::cpu::x64::jit_generator *host, dnnl::impl::cpu::x64::cpu_isa_t host_isa, const std::shared_ptr<ngraph::Node>& n,
+    jit_clamp_emitter(dnnl::impl::cpu::x64::jit_generator *host, dnnl::impl::cpu::x64::cpu_isa_t host_isa, const std::shared_ptr<ov::Node>& n,
                        InferenceEngine::Precision exec_prc = InferenceEngine::Precision::FP32)
         : jit_dnnl_emitter(host, host_isa, n, exec_prc) {
             kind = dnnl_eltwise_clip;
-            auto op = ngraph::as_type_ptr<ov::op::v0::Clamp>(n);
+            auto op = ov::as_type_ptr<ov::op::v0::Clamp>(n);
             alpha = op->get_min();
             beta = op->get_max();
 
@@ -105,11 +105,11 @@ class jit_clamp_emitter : public jit_dnnl_emitter {
 
 class jit_swish_emitter : public jit_dnnl_emitter {
 public:
-    jit_swish_emitter(dnnl::impl::cpu::x64::jit_generator *host, dnnl::impl::cpu::x64::cpu_isa_t host_isa, const std::shared_ptr<ngraph::Node>& n,
+    jit_swish_emitter(dnnl::impl::cpu::x64::jit_generator *host, dnnl::impl::cpu::x64::cpu_isa_t host_isa, const std::shared_ptr<ov::Node>& n,
                         InferenceEngine::Precision exec_prc = InferenceEngine::Precision::FP32)
             : jit_dnnl_emitter(host, host_isa, n, exec_prc) {
         kind = dnnl_eltwise_swish;
-        auto op = ngraph::as_type_ptr<ov::intel_cpu::SwishNode>(n);
+        auto op = ov::as_type_ptr<ov::intel_cpu::SwishNode>(n);
         alpha = op->get_alpha();
         beta = 0.f;
 
@@ -119,7 +119,7 @@ class jit_swish_emitter : public jit_dnnl_emitter {
 
 class jit_hswish_emitter : public jit_dnnl_emitter {
 public:
-    jit_hswish_emitter(dnnl::impl::cpu::x64::jit_generator *host, dnnl::impl::cpu::x64::cpu_isa_t host_isa, const std::shared_ptr<ngraph::Node>& n,
+    jit_hswish_emitter(dnnl::impl::cpu::x64::jit_generator *host, dnnl::impl::cpu::x64::cpu_isa_t host_isa, const std::shared_ptr<ov::Node>& n,
                         InferenceEngine::Precision exec_prc = InferenceEngine::Precision::FP32)
             : jit_dnnl_emitter(host, host_isa, n, exec_prc) {
         // since v3.0 oneDNN has flexible version of hardswish, ov still uses the one with hardcoded alpha and beta
@@ -133,7 +133,7 @@ class jit_hswish_emitter : public jit_dnnl_emitter {
 
 class jit_gelu_v0_emitter : public jit_dnnl_emitter {
 public:
-    jit_gelu_v0_emitter(dnnl::impl::cpu::x64::jit_generator *host, dnnl::impl::cpu::x64::cpu_isa_t host_isa, const std::shared_ptr<ngraph::Node>& n,
+    jit_gelu_v0_emitter(dnnl::impl::cpu::x64::jit_generator *host, dnnl::impl::cpu::x64::cpu_isa_t host_isa, const std::shared_ptr<ov::Node>& n,
                         InferenceEngine::Precision exec_prc = InferenceEngine::Precision::FP32)
             : jit_dnnl_emitter(host, host_isa, n, exec_prc) {
         kind = dnnl_eltwise_gelu_erf;
@@ -144,7 +144,7 @@ class jit_gelu_v0_emitter : public jit_dnnl_emitter {
 
 class jit_gelu_v7_emitter : public jit_dnnl_emitter {
 public:
-    jit_gelu_v7_emitter(dnnl::impl::cpu::x64::jit_generator *host, dnnl::impl::cpu::x64::cpu_isa_t host_isa, const std::shared_ptr<ngraph::Node>& n,
+    jit_gelu_v7_emitter(dnnl::impl::cpu::x64::jit_generator *host, dnnl::impl::cpu::x64::cpu_isa_t host_isa, const std::shared_ptr<ov::Node>& n,
                         InferenceEngine::Precision exec_prc = InferenceEngine::Precision::FP32)
             : jit_dnnl_emitter(host, host_isa, n, exec_prc) {
         auto gelu = getNgraphOpAs<ngraph::op::v7::Gelu>(n);
@@ -167,7 +167,7 @@ class jit_round_emitter : public jit_dnnl_emitter {
     jit_round_emitter(
         dnnl::impl::cpu::x64::jit_generator *host,
         dnnl::impl::cpu::x64::cpu_isa_t host_isa,
-        const std::shared_ptr<ngraph::Node>& n,
+        const std::shared_ptr<ov::Node>& n,
         InferenceEngine::Precision exec_prc = InferenceEngine::Precision::FP32) : jit_dnnl_emitter(host, host_isa, n, exec_prc) {
         const auto round = getNgraphOpAs<ngraph::op::v5::Round>(n);
         const auto mode = round->get_mode();