[CPU][ARM] Weights compression f32->f16 is moved to CPU Plug-in side

samples/cpp/benchmark_app/main.cpp

@@ -233,7 +233,7 @@ void fuse_mean_scale(ov::preprocess::PrePostProcessor& preproc, const benchmark_
  * @brief The entry point of the benchmark application
  */
 int main(int argc, char* argv[]) {
-    std::shared_ptr<StatisticsReport> statistics;
+        std::shared_ptr<StatisticsReport> statistics;
     try {
         ov::CompiledModel compiledModel;
 

src/common/transformations/include/transformations/fp16_compression/mark_decompression_convert_constant_folding.hpp

@@ -14,6 +14,7 @@ namespace pass {
 class TRANSFORMATIONS_API EnableDecompressionConvertConstantFolding;
 class TRANSFORMATIONS_API DisableDecompressionConvertConstantFolding;
 class TRANSFORMATIONS_API KeepConstAndDecompression;
+class TRANSFORMATIONS_API KeepConstFP32Unfolded;
 class TRANSFORMATIONS_API KeepConstantsPrecisionAndAddConverts;
 
 }  // namespace pass
@@ -49,6 +50,12 @@ class ov::pass::KeepConstAndDecompression : public MatcherPass {
     KeepConstAndDecompression();
 };
 
+class ov::pass::KeepConstFP32Unfolded : public MatcherPass {
+public:
+    OPENVINO_RTTI("KeepConstFP32Unfolded", "0");
+    KeepConstFP32Unfolded();
+};
+
 /**
  * @ingroup ie_transformation_common_api
  * @brief Prevents Consts precision conversion and adds Convert with disabled ConstantFolding

src/common/transformations/include/transformations/rt_info/decompression.hpp

@@ -23,6 +23,12 @@ TRANSFORMATIONS_API void unmark_as_decompression(const std::shared_ptr<Node>& no
 
 TRANSFORMATIONS_API bool is_decompression(const std::shared_ptr<Node>& node);
 
+TRANSFORMATIONS_API void mark_as_compression(const std::shared_ptr<Node>& node);
+
+TRANSFORMATIONS_API void unmark_as_compression(const std::shared_ptr<Node>& node);
+
+TRANSFORMATIONS_API bool is_compression(const std::shared_ptr<Node>& node);
+
 /**
  * @ingroup ie_runtime_attr_api
  * @brief Decompression class represents runtime info attribute that marks operation
@@ -43,4 +49,19 @@ class TRANSFORMATIONS_API Decompression : public RuntimeAttribute {
     }
 };
 
+class TRANSFORMATIONS_API Compression : public RuntimeAttribute {
+public:
+    OPENVINO_RTTI("Compression", "0");
+
+    Compression() = default;
+
+    bool visit_attributes(AttributeVisitor& visitor) override {
+        return true;
+    }
+
+    bool is_copyable() const override {
+        return false;
+    }
+};
+
 }  // namespace ov

src/common/transformations/src/transformations/fp16_compression/align_mixed_fp32_fp16_types.cpp

@@ -11,6 +11,7 @@
 #include "openvino/op/util/precision_sensitive_attribute.hpp"
 #include "openvino/pass/constant_folding.hpp"
 #include "transformations/rt_info/disable_fp16_compression.hpp"
+#include "transformations/rt_info/decompression.hpp"
 
 using namespace ov;
 
@@ -48,6 +49,7 @@ bool ov::pass::AlignMixedFP32FP16Types::run_on_model(const std::shared_ptr<ov::M
                 copy_runtime_info(incoming_node, convert);
                 input.replace_source_output(convert);
                 disable_fp16_compression(convert);
+                mark_as_compression(convert);
                 pass::disable_constant_folding(convert);
                 is_changed = true;
             }
@@ -76,6 +78,7 @@ bool ov::pass::AlignMixedFP32FP16Types::run_on_model(const std::shared_ptr<ov::M
                     auto init_name = node->get_friendly_name() + "_compressed_to_f16";
                     convert->set_friendly_name(generate_uniq_name(init_name));
                     out_inputs.replace_source_output(convert);
+                    mark_as_compression(convert);
                     pass::disable_constant_folding(convert);
                     is_changed = true;
                 }

src/common/transformations/src/transformations/fp16_compression/mark_decompression_convert_constant_folding.cpp

@@ -77,6 +77,32 @@ pass::KeepConstAndDecompression::KeepConstAndDecompression() {
     register_matcher(m, callback);
 }
 
+pass::KeepConstFP32Unfolded::KeepConstFP32Unfolded() {
+    MATCHER_SCOPE(KeepConstFP16Unfolded);
+
+    auto node_pattern = pattern::wrap_type<ov::op::v0::MatMul>();
+
+    matcher_pass_callback callback = [=](pattern::Matcher& m) {
+        auto node = m.get_match_root();
+
+        if (transformation_callback(node)) {
+            return false;
+        }
+
+        auto constNode = node->get_input_node_shared_ptr(1);
+        if (!is_type<ov::op::v0::Constant>(constNode) || constNode->get_output_element_type(0) != element::f32)
+            return false;
+
+        disable_constant_folding(constNode);
+        enable_keep_const_precision(constNode);
+        disable_fp16_compression(constNode);
+
+        return false;
+    };
+    auto m = std::make_shared<pattern::Matcher>(node_pattern, matcher_name);
+    register_matcher(m, callback);
+}
+
 pass::KeepConstantsPrecisionAndAddConverts::KeepConstantsPrecisionAndAddConverts() {
     MATCHER_SCOPE(KeepConstantsPrecisionAndAddConverts);
     auto const_pattern = pattern::wrap_type<ov::op::v0::Constant>();

src/common/transformations/src/transformations/fp16_compression/mark_subgraphs_to_keep_in_mixed_precision.cpp

@@ -432,16 +432,16 @@ bool MarkSugraphsToKeepInMixedPrecision::run_on_model(const shared_ptr<ov::Model
     Manager manager(get_pass_config());
     // Mark root of Division with eps pattern to keep in FP32
     REGISTER_PASS(manager, MarkDivWithEps)
-    REGISTER_PASS(manager, MarkExpInReduceOpPath)
-    REGISTER_PASS(manager, PropagateDownDisableSensitivityForQuantized)
-
+        REGISTER_PASS(manager, MarkExpInReduceOpPath)
+        REGISTER_PASS(manager, PropagateDownDisableSensitivityForQuantized)
+    
     // both Up and Down propagations are needed.
     // Why both of them are needed is explained in comments in passes declarations.
     REGISTER_PASS(manager, PropagateDownMarkToKeepInMixedPrecision)
-
+    
     auto propagate_up = manager.register_pass<BackwardGraphRewrite>();
     ADD_MATCHER(propagate_up, PropagateUpMarkToKeepInMixedPrecision)
-
+    
     // Mark nodes in ShapeOf subgraphs to keep in FP32
     REGISTER_PASS(manager, MarkPrecisionSensitiveShapeOfSubgraphs)
     manager.run_passes(m);

src/common/transformations/src/transformations/rt_info/decompression.cpp

@@ -18,3 +18,18 @@ bool ov::is_decompression(const std::shared_ptr<Node>& node) {
     const auto& rt_info = node->get_rt_info();
     return rt_info.count(Decompression::get_type_info_static());
 }
+
+void ov::mark_as_compression(const std::shared_ptr<Node>& node) {
+    auto& rt_info = node->get_rt_info();
+    rt_info[Compression::get_type_info_static()] = Compression();
+}
+
+void ov::unmark_as_compression(const std::shared_ptr<Node>& node) {
+    auto& rt_info = node->get_rt_info();
+    rt_info.erase(Compression::get_type_info_static());
+}
+
+bool ov::is_compression(const std::shared_ptr<Node>& node) {
+    const auto& rt_info = node->get_rt_info();
+    return rt_info.count(Compression::get_type_info_static());
+}

src/plugins/intel_cpu/src/graph_optimizer.cpp

@@ -921,8 +921,8 @@ void GraphOptimizer::FuseFCAndConvertOnWeights(Graph& graph) {
                         && parent->getChildEdges().size() == 1
                         && parent->getChildEdgeAt(0)->getOutputNum() == 1
                         && parent->getChildEdgeAt(0)->getChild()->getType() == Type::FullyConnected
-                        && one_of(parent->getOriginalInputPrecisionAtPort(0), Precision::FP16)
-                        && one_of(parent->getOriginalOutputPrecisionAtPort(0), Precision::FP32, Precision::BF16)
+                        && one_of(parent->getOriginalInputPrecisionAtPort(0), Precision::FP32, Precision::BF16, Precision::FP16)
+                        && one_of(parent->getOriginalOutputPrecisionAtPort(0), Precision::FP32, Precision::BF16, Precision::FP16)
                         && parent->isConstant();
         return res;
     };

src/plugins/intel_cpu/src/transformations/cpu_opset/common/pass/convert_matmul_to_fc.cpp

@@ -37,7 +37,7 @@ ov::intel_cpu::ConvertMatMulToFC::ConvertMatMulToFC() {
         auto fc_input_b = pattern_map.at(weights_m);
         bool is_convert = false;
         if (auto convert_node = std::dynamic_pointer_cast<ov::op::v0::Convert>(fc_input_b.get_node_shared_ptr())) {
-            if (is_decompression(convert_node)) {
+            if (is_decompression(convert_node) || fp16_compression_is_disabled(convert_node) || is_compression(convert_node)) {
                 is_convert = true;
                 fc_input_b = convert_node->get_input_node_shared_ptr(0);
             } else {

src/plugins/intel_cpu/src/transformations/transformation_pipeline.cpp

@@ -291,6 +291,7 @@ void Transformations::PreLpt(const std::vector<ov::element::Type>& defaultPrecis
     // It cannot be static data, because it may be difference for different inferencePrecision
     const auto precisions = get_convert_precisions();
     if (inferencePrecision == ov::element::f16) {
+        CPU_REGISTER_PASS_ARM(manager, ov::pass::KeepConstFP32Unfolded);
         precisions_map fp_convert_precision_map = {{ov::element::f32, ov::element::f16}};
         type_to_fuse_map empty_fuse_map = {};
         const bool keep_precision_sensitive_in_fp32 = true;