Merge branch 'master' into feature/cpu_random_uniform_alignment

docs/openvino_custom_sphinx_sitemap/openvino_custom_sphinx_sitemap/__init__.py

@@ -122,7 +122,7 @@ def process_coveo_meta(meta, url, link):
         namespace_element = ET.SubElement(url, namespace)
 
         for tag_name, tag_value in values.items():
-            if tag_name == 'ovcategory':
+            if tag_name == 'ovdoctype':
                 processed_link = process_link(link)
                 ET.SubElement(namespace_element, tag_name).text = processed_link
             else:

docs/sphinx_setup/_static/js/custom.js

@@ -417,13 +417,15 @@ document.addEventListener('DOMContentLoaded', function () {
             await searchInterfaceSa.initialize({
                 accessToken: "xx1f2aebd3-4307-4632-aeea-17c13378b237",
                 organizationId: "intelcorporationnonproduction2ybdyblf7",
+                organizationEndpoints: await searchInterface.getOrganizationEndpoints('intelcorporationnonproduction2ybdyblf7')
             });
             searchInterfaceSa.executeFirstSearch();
         }
         if (searchInterface) {
             await searchInterface.initialize({
                 accessToken: "xx1f2aebd3-4307-4632-aeea-17c13378b237",
                 organizationId: "intelcorporationnonproduction2ybdyblf7",
+                organizationEndpoints: await searchInterface.getOrganizationEndpoints('intelcorporationnonproduction2ybdyblf7')
             });
             searchInterface.executeFirstSearch();
         }

docs/sphinx_setup/conf.py

@@ -84,7 +84,7 @@
 ov_sitemap_meta = [
     ('coveo:metadata', {
         'ovversion': version_name,
-        'ovcategory': 'null'
+        'ovdoctype': 'null'
     })
 ]
 

src/plugins/intel_gpu/src/kernel_selector/cl_kernels/fully_connected_gpu_bf_tiled.cl

@@ -952,6 +952,7 @@ inline void FUNC(fc_bf_tiled_kernel_dyn_quan)(
 
             // Calculate zero-point and scale only for DECOMPRESSION_SCALE_POST_OP enabled
             // Calculate weight : w = (w - dzp) * ds
+            // if DECOMPRESSION_ZP_TERM is not enabled, then dzp is ACCUMULATOR_VAL_ZERO.
             #if DECOMPRESSION_ZP_TERM
                 #if DECOMPRESSION_ZP_SCALAR
                     DQ_SLM_FILTER_UNPACKED_VEC dzp = (DQ_SLM_FILTER_UNPACKED_VEC)(DECOMPRESSION_ZP_VALUE);
@@ -976,8 +977,6 @@ inline void FUNC(fc_bf_tiled_kernel_dyn_quan)(
                         }
                     }
                 #endif
-            #else
-                DQ_SLM_FILTER_UNPACKED_VEC dzp = (DQ_SLM_FILTER_UNPACKED_VEC)(ACCUMULATOR_VAL_ZERO);
             #endif
 
             #if FILTER_LOAD_BLOCK_SIZE == 2
@@ -1026,7 +1025,7 @@ inline void FUNC(fc_bf_tiled_kernel_dyn_quan)(
 
             weights_offset += TILE_K_OFM_PACKED * TILE_OFM_PER_OSV_SIZE * SIMD;
 
-            #if DECOMPRESSION_SCALE_POST_OP && (TILE_IFM_ELEMENTS_SIZE > DECOMPRESSION_SCALE_GROUP_SIZE)
+            #if DQ_DECOMPRESSION_SCALE_POST_OP && (TILE_IFM_ELEMENTS_SIZE > DECOMPRESSION_SCALE_GROUP_SIZE)
                 unroll_for (uint bi = 0; bi < TILE_B; ++bi) {
                     unroll_for(uint fi = 0; fi < TILE_OFM; ++fi) {
                         const uint offset_ofm = out_f + fi*SIMD + sglid;
@@ -1046,7 +1045,7 @@ inline void FUNC(fc_bf_tiled_kernel_dyn_quan)(
             #endif
         }  // Whole tile_k elements of each iteration : ki
 
-        #if DECOMPRESSION_SCALE_POST_OP && (TILE_IFM_ELEMENTS_SIZE <= DECOMPRESSION_SCALE_GROUP_SIZE)
+        #if DQ_DECOMPRESSION_SCALE_POST_OP && (TILE_IFM_ELEMENTS_SIZE <= DECOMPRESSION_SCALE_GROUP_SIZE)
             // Dynamic-quantizing group size set to same or smaller than scale group size
             if ((ni % NUM_LOOP_IN_DYN_QUAN_GROUP) == (NUM_LOOP_IN_DYN_QUAN_GROUP - 1)) {
                 const uint ni_offset = ((ni*TILE_IFM*SIMD) / DECOMPRESSION_SCALE_GROUP_SIZE)*DECOMPRESSION_SCALE_FEATURE_PITCH;
@@ -1175,7 +1174,7 @@ KERNEL(fc)(
 #endif
 ) {
 #if USE_SLM
-    #if DYNAMIC_QUANTIZE && (TILE_OFM == 2)
+    #if DYNAMIC_QUANTIZE
         __local int dq_wei_local_mem[SIMD * TILE_OFM * SIMD];
     #else
         __local ACCUMULATOR_TYPE wei_local_mem[TILE_IFM * SIMD * TILE_OFM * SIMD];
@@ -1317,7 +1316,7 @@ KERNEL(fc)(
         #endif
         );
     } else {
-        #if USE_SLM && DYNAMIC_QUANTIZE && (TILE_OFM == 2)
+        #if USE_SLM && DYNAMIC_QUANTIZE
             FUNC_CALL(fc_bf_tiled_kernel_dyn_quan)(
                 OPTIONAL_SHAPE_INFO_TENSOR
                 input,
@@ -1364,7 +1363,7 @@ KERNEL(fc)(
         #endif
     }
 #else
-    #if USE_SLM && DYNAMIC_QUANTIZE && (TILE_OFM == 2)
+    #if USE_SLM && DYNAMIC_QUANTIZE
         FUNC_CALL(fc_bf_tiled_kernel_dyn_quan)(
             OPTIONAL_SHAPE_INFO_TENSOR
             input,

src/plugins/intel_gpu/src/kernel_selector/kernels/fully_connected/fully_connected_kernel_bf_tiled.cpp

@@ -375,6 +375,9 @@ FullyConnected_bf_tiled::GetAutoTuneParams(const fully_connected_params& params,
 
     if (params.weights.GetDType() == WeightsType::UINT4 || params.weights.GetDType() == WeightsType::INT4) {
         if (!params.is_shape_agnostic && batch == 1) {
+            if (should_dynamic_quantize(params))
+                return selector.Default(tune_params(1, 2, 4, 2, 1, 1, 1, EXE_MODE_DEFAULT));
+
             // Tuning for Meteor Lake
             if (is_weight_vertical(params, output_f)) {
                 if (params.weights.GetLayout() == WeightsLayout::os_is_yx_osv32_isv2) {
@@ -616,7 +619,7 @@ JitConstants FullyConnected_bf_tiled::GetJitConstants(const fully_connected_para
     // Validated perf gain, Dynamic quantize force enable SCALE_POST_OP for char type multiplication
     if (should_dynamic_quantize(params)) {
         jit.AddConstant(MakeJitConstant("DYNAMIC_QUANTIZE", 1));
-        jit.AddConstant(MakeJitConstant("DECOMPRESSION_SCALE_POST_OP", 1));
+        jit.AddConstant(MakeJitConstant("DQ_DECOMPRESSION_SCALE_POST_OP", 1));
         jit.AddConstant(MakeJitConstant("DQ_TYPE", "char"));
         jit.AddConstant(MakeJitConstant("QUANTIZE_GROUP_SIZE", quantize_grp_size));
     } else {

src/plugins/intel_gpu/src/plugin/transformations/convert_fc_to_compressed.cpp

@@ -24,7 +24,7 @@
 namespace ov {
 namespace intel_gpu {
 
-ConvertFullyConnectedToFullyConnectedCompressed::ConvertFullyConnectedToFullyConnectedCompressed(bool convert_u4zp_to_u8) {
+ConvertFullyConnectedToFullyConnectedCompressed::ConvertFullyConnectedToFullyConnectedCompressed() {
     using namespace ov::pass::pattern;
 
     auto compressed_constant = [](const ov::Output<ov::Node>& output) {
@@ -81,6 +81,12 @@ ConvertFullyConnectedToFullyConnectedCompressed::ConvertFullyConnectedToFullyCon
         bool has_transpose = pattern_map.count(transpose_m);
         auto scale_shape = pattern_map.at(mul_const_m).get_shape();
         bool grouped = std::count_if(scale_shape.begin(), scale_shape.end(), [](size_t d) { return d > 1; }) > 1;
+        bool sub_with_convert = (pattern_map.count(sub_with_convert_m) > 0) ? true : false;
+
+        auto weight_ptr = std::dynamic_pointer_cast<ov::op::v0::Constant>(pattern_map.at(weights_m).get_node_shared_ptr());
+        bool weight_u8 = false;
+        if (weight_ptr->get_element_type() == ov::element::u8 || weight_ptr->get_element_type() == ov::element::i8)
+            weight_u8 = true;
 
         auto reshape_const_to_2d = [has_transpose, grouped](std::shared_ptr<ov::Node> node) {
             auto constant = std::dynamic_pointer_cast<ov::op::v0::Constant>(node);
@@ -97,11 +103,17 @@ ConvertFullyConnectedToFullyConnectedCompressed::ConvertFullyConnectedToFullyCon
             return std::make_shared<ov::op::v0::Constant>(*constant, new_shape);
         };
 
-        auto convert_u4const_to_u8 = [convert_u4zp_to_u8](std::shared_ptr<ov::Node> node) {
+        auto convert_const_to_u8 = [&](std::shared_ptr<ov::Node> node) {
             auto constant = std::dynamic_pointer_cast<ov::op::v0::Constant>(node);
-            if (constant->get_element_type() != ov::element::u4 || !convert_u4zp_to_u8)
+            // Convert ZP to u8
+            if (constant->get_element_type() == ov::element::u8)
                 return std::dynamic_pointer_cast<ov::Node>(constant);
-            return std::dynamic_pointer_cast<ov::Node>(std::make_shared<ov::op::v0::Convert>(node, ov::element::u8));
+            if (constant->get_element_type() == ov::element::u4)
+                return std::dynamic_pointer_cast<ov::Node>(std::make_shared<ov::op::v0::Convert>(node, ov::element::u8));
+            if (weight_u8 && sub_with_convert)
+                return std::dynamic_pointer_cast<ov::Node>(std::make_shared<ov::op::v0::Convert>(node, ov::element::u8));
+
+            return std::dynamic_pointer_cast<ov::Node>(constant);
         };
 
 
@@ -111,8 +123,7 @@ ConvertFullyConnectedToFullyConnectedCompressed::ConvertFullyConnectedToFullyCon
 
         const bool with_zero_point = pattern_map.count(sub_no_convert_m) > 0 || pattern_map.count(sub_with_convert_m) > 0;
         if (with_zero_point) {
-            // WA: Convert ZP to u8 for OneDNN case to avoid u4 reorder
-            optional_zero_point = convert_u4const_to_u8(reshape_const_to_2d(pattern_map.at(sub_const_m).get_node_shared_ptr()));
+            optional_zero_point = convert_const_to_u8(reshape_const_to_2d(pattern_map.at(sub_const_m).get_node_shared_ptr()));
         }
 
         std::shared_ptr<ov::Node> fc_input_b = reshape_const_to_2d(pattern_map.at(weights_m).get_node_shared_ptr());

src/plugins/intel_gpu/src/plugin/transformations/convert_fc_to_compressed.hpp

@@ -12,7 +12,7 @@ namespace intel_gpu {
 class ConvertFullyConnectedToFullyConnectedCompressed: public ov::pass::MatcherPass {
 public:
     OPENVINO_RTTI("ConvertFullyConnectedToFullyConnectedCompressed", "0");
-    ConvertFullyConnectedToFullyConnectedCompressed(bool convert_u4zp_to_u8 = false);
+    ConvertFullyConnectedToFullyConnectedCompressed();
 };
 
 }   // namespace intel_gpu

src/plugins/intel_gpu/src/plugin/transformations_pipeline.cpp

@@ -810,7 +810,7 @@ void TransformationsPipeline::apply(std::shared_ptr<ov::Model> func) {
         manager.register_pass<ov::intel_gpu::ClampFP16Output>();
         manager.register_pass<ov::intel_gpu::ConvertMatMulToFullyConnected>();
         manager.register_pass<ov::intel_gpu::MoveFCReshapeToWeights>();
-        manager.register_pass<ov::intel_gpu::ConvertFullyConnectedToFullyConnectedCompressed>(device_info.supports_immad);
+        manager.register_pass<ov::intel_gpu::ConvertFullyConnectedToFullyConnectedCompressed>();
 
         bool disable_horizontal_fc_fusion = false;
         GPU_DEBUG_GET_INSTANCE(debug_config);
@@ -819,10 +819,11 @@ void TransformationsPipeline::apply(std::shared_ptr<ov::Model> func) {
 
         if (!disable_horizontal_fc_fusion)
             manager.register_pass<ov::intel_gpu::FullyConnectedHorizontalFusion>();
+
+        // ZP should not be folded for FC. But still, ZP should be folded for Gather.
+        // Therefore, run MarkDequantizationSubgraph again to fold ZP constant.
+        manager.register_pass<ov::pass::MarkDequantizationSubgraph>(supported_woq_types, true);
         if (device_info.supports_immad) {
-            // For OneDNN, ZP should not be folded for FC. But still, ZP should be folded for Gather.
-            // Therefore, run MarkDequantizationSubgraph again to fold ZP constant.
-            manager.register_pass<ov::pass::MarkDequantizationSubgraph>(supported_woq_types, true);
             if (disable_horizontal_fc_fusion)
                 manager.register_pass<ov::pass::ConstantFolding>();
         }