[GPU] Fix compressed KV-cache shape infer for QKV order {1,2,0,3} (#2…

…8592)

### Details:
- This change restores the original logic of axis calculation for
scales/zp and fixes the shape inference of KV-Cache operation.
Previously, it needed to be adjusted with concat_axis, but after the
introduction of independent macros for key and value scale/zp offsets
calculation in micro_sdpa kernel, this adjustment is no longer needed
and causes incorrect indexing. Therefore, this change reverts to the
original fixed scale/zp axis equal to 2.

src/plugins/intel_gpu/src/graph/graph_optimizer/prepare_buffer_fusing.cpp

@@ -943,7 +943,7 @@ void prepare_buffer_fusing::run(program& p) {
                 auto update_scale_zp = [&](size_t kv_cache_output_idx, size_t read_value_output_idx) {
                     auto scales_out_layout = node.get_output_layout(false, kv_cache_output_idx);
 
-                    const auto scales_zp_concat_axis = kv_cache_inst::get_scale_zp_sequence_axis(desc->concat_axis, desc->quantization_attributes);
+                    const auto scales_zp_concat_axis = kv_cache_inst::get_scale_zp_sequence_axis();
                     padding::DynamicDimsMask info_dynamic_pad_scales;
                     info_dynamic_pad_scales[scales_zp_concat_axis] = 1;
                     scales_out_layout.data_padding._dynamic_dims_mask = info_dynamic_pad_scales;

src/plugins/intel_gpu/src/graph/include/kv_cache_inst.h

@@ -62,8 +62,8 @@ class typed_primitive_inst<kv_cache> : public typed_primitive_inst_base<kv_cache
         return sequence_axis >= 0 ? sequence_axis : past_layout_rank + sequence_axis;
     }
 
-    static int64_t get_scale_zp_sequence_axis(int64_t sequence_axis, const kv_cache::QuantizationAttributes& quantization_attrs) {
-        const auto scale_zp_concat_axis = quantization_attrs.scales_zp_output_order[sequence_axis];
+    static int64_t get_scale_zp_sequence_axis() {
+        const auto scale_zp_concat_axis = 2;
         return scale_zp_concat_axis;
     }
 

src/plugins/intel_gpu/src/graph/primitive_inst.cpp

@@ -851,7 +851,7 @@ void primitive_inst::realloc_if_needed(bool prev_execution_skipped) {
             auto prealloc_shape = updated_layouts[i].get_shape();
             const auto shape_rank = prealloc_shape.size();
             const auto seq_axis = i == 0 ? kv_cache_inst::get_sequence_axis(desc->concat_axis, shape_rank)
-                                         : kv_cache_inst::get_scale_zp_sequence_axis(desc->concat_axis, desc->quantization_attributes);
+                                         : kv_cache_inst::get_scale_zp_sequence_axis();
 
             prealloc_shape[seq_axis] += tmp_prealloc_count;
             required_buffer_size = std::accumulate(prealloc_shape.begin(), prealloc_shape.end(), size_t(1), std::multiplies<size_t>());
@@ -883,7 +883,7 @@ void primitive_inst::realloc_if_needed(bool prev_execution_skipped) {
             const auto& desc = _node->as<kv_cache>().get_primitive();
             const auto shape_rank = updated_layouts[i].get_shape().size();
             const auto seq_axis = i == 0 ? kv_cache_inst::get_sequence_axis(desc->concat_axis, shape_rank)
-                                         : kv_cache_inst::get_scale_zp_sequence_axis(desc->concat_axis, desc->quantization_attributes);
+                                         : kv_cache_inst::get_scale_zp_sequence_axis();
 
             prealloc_info = sp.predict_preallocation_shape(id(), updated_layouts[i], false, i, tmp_prealloc_count, seq_axis);
         } else {
@@ -907,7 +907,7 @@ void primitive_inst::realloc_if_needed(bool prev_execution_skipped) {
                 auto& present_layout = _impl_params->output_layouts[i];
                 const auto present_layout_rank = present_layout.get_partial_shape().size();
                 const auto sequence_axis = i == 0 ? kv_cache_inst::get_sequence_axis(desc->concat_axis, present_layout_rank)
-                                                  : kv_cache_inst::get_scale_zp_sequence_axis(desc->concat_axis, desc->quantization_attributes);
+                                                  : kv_cache_inst::get_scale_zp_sequence_axis();
 
                 auto max_pad = kv_cache_inst::get_max_pad(present_layout,
                                                           _max_output_layout_count[i],
@@ -978,7 +978,7 @@ void primitive_inst::realloc_if_needed(bool prev_execution_skipped) {
             if (max_pad > 0) {
                 if (auto compressed_cache_variable = dynamic_cast<ov::intel_gpu::VariableStateIndirectKVCacheCompressed*>(&variable)) {
                     auto present_scales_layout = _impl_params->output_layouts[2];
-                    const auto sequence_axis = kv_cache_inst::get_scale_zp_sequence_axis(desc->concat_axis, desc->quantization_attributes);
+                    const auto sequence_axis = kv_cache_inst::get_scale_zp_sequence_axis();
 
                     // In case of compressed KV-cache, calling update_impl for each iteration
                     // because of scales layout [batch, num_heads, seq_len, head_size], which requires proper
@@ -1374,7 +1374,7 @@ void primitive_inst::do_runtime_in_place_kv_cache() {
         if (desc->compressed) {
             auto compressed_cache_variable = dynamic_cast<ov::intel_gpu::VariableStateIndirectKVCacheCompressed*>(&variable);
             auto& present_scales_layout = _impl_params->output_layouts[2];
-            const auto sequence_axis = kv_cache_inst::get_scale_zp_sequence_axis(desc->concat_axis, desc->quantization_attributes);
+            const auto sequence_axis = kv_cache_inst::get_scale_zp_sequence_axis();
             kv_cache_inst::update_pad(present_scales_layout, max_pad - new_seq_len, sequence_axis);
             GPU_DEBUG_TRACE_DETAIL << "[do runtime_in_place_kv_cache] " << id()
                                    << " Updated present_scale_layout's pad : " << present_scales_layout.to_string() << std::endl;
@@ -1398,7 +1398,7 @@ void primitive_inst::do_runtime_in_place_kv_cache() {
 
             if (desc->compressed) {
                 auto& past_scale_layout = _impl_params->input_layouts[3];
-                const auto sequence_axis = kv_cache_inst::get_scale_zp_sequence_axis(desc->concat_axis, desc->quantization_attributes);
+                const auto sequence_axis = kv_cache_inst::get_scale_zp_sequence_axis();
                 kv_cache_inst::update_pad(past_scale_layout, max_pad, sequence_axis);
 
                 if (desc->get_compression_zp_inputs_num() > 0) {

src/plugins/intel_gpu/src/plugin/transformations/op/kv_cache.cpp

@@ -191,8 +191,7 @@ std::vector<ov::PartialShape> shape_infer(const KVCacheCompressed* op,
         auto quantized_data_shapes =
             ov::op::internal::DynamicQuantize::shape_infer(&dq_op, { input_shapes[1] });
 
-        const auto concat_axis = ov::util::normalize(op->get_concat_axis(), input_shapes[0].size());
-        const auto scales_concat_axis = op->get_quantization_attrs().scales_zp_output_order[concat_axis];
+        const auto scales_concat_axis = 2;
         ov::PartialShape compression_scale_shape = input_shapes[3];
         compression_scale_shape[scales_concat_axis] += quantized_data_shapes[1][scales_concat_axis];
         out_shapes[2] = compression_scale_shape;

src/plugins/intel_gpu/tests/common/subgraphs_builders.hpp

@@ -120,8 +120,8 @@ inline std::shared_ptr<ov::Node> make_qkv_transpose(ov::Output<ov::Node> qkv, st
     return std::make_shared<ov::op::v1::Transpose>(qkv, transpose_const);
 }
 
-inline std::shared_ptr<ov::Node> make_kv_rearrange(ov::Output<ov::Node> kv_past, ov::Output<ov::Node> beam_idx) {
-    auto axis = std::make_shared<ov::op::v0::Constant>(ov::element::i32, ov::Shape{}, 0);
+inline std::shared_ptr<ov::Node> make_kv_rearrange(ov::Output<ov::Node> kv_past, ov::Output<ov::Node> beam_idx, int axis_val = 0) {
+    auto axis = std::make_shared<ov::op::v0::Constant>(ov::element::i32, ov::Shape{}, axis_val);
     return std::make_shared<ov::op::v8::Gather>(kv_past, beam_idx, axis, 0);
 }
 
@@ -242,8 +242,8 @@ inline std::shared_ptr<ov::Model> make_llm_kv_cache_sdpa_pattern(ov::Dimension b
         in_beam_idx->set_friendly_name("beam_idx");
         params.push_back(in_beam_idx);
 
-        concat_k_input = make_kv_rearrange(past_k, in_beam_idx);
-        concat_v_input = make_kv_rearrange(past_v, in_beam_idx);
+        concat_k_input = make_kv_rearrange(past_k, in_beam_idx, qkv_order[0]);
+        concat_v_input = make_kv_rearrange(past_v, in_beam_idx, qkv_order[0]);
     }
 
     auto concat_k = std::make_shared<ov::op::v0::Concat>(ov::OutputVector{concat_k_input, in_k_token}, concat_axis);

src/plugins/intel_gpu/tests/functional/subgraph_tests/dynamic/kv_cache_sdpa.cpp

@@ -342,6 +342,7 @@ std::vector<Params> get_test_params() {
     p.push_back({with_rearrange, with_mask, !with_scale, !causal, !compressed, 1, ov::element::Type_t::f16, 10, 4, 1, {0, 1, 2, 3}});
     p.push_back({with_rearrange, with_mask, !with_scale, !causal, !compressed, 1, ov::element::Type_t::f16, 10, 4, 1, {0, 2, 1, 3}});
     p.push_back({!with_rearrange, with_mask, !with_scale, !causal, !compressed, 1, ov::element::Type_t::f16, 10, 4, 1, {0, 2, 1, 3}});
+    p.push_back({!with_rearrange, with_mask, !with_scale, !causal, !compressed, 1, ov::element::Type_t::f16, 10, 4, 1, {1, 2, 0, 3}});
 
     // Beam search
     p.push_back({with_rearrange, !with_mask, !with_scale, !causal, !compressed, 2, ov::element::Type_t::f16, 10, 4, 1, {0, 1, 2, 3}});
@@ -351,6 +352,7 @@ std::vector<Params> get_test_params() {
     p.push_back({with_rearrange, with_mask, !with_scale, !causal, compressed, 1, ov::element::Type_t::f16, 10, 1, 1, {0, 1, 2, 3}});
     p.push_back({with_rearrange, with_mask, !with_scale, !causal, compressed, 1, ov::element::Type_t::f16, 10, 4, 1, {0, 2, 1, 3}});
     p.push_back({with_rearrange, with_mask, !with_scale, !causal, compressed, 1, ov::element::Type_t::f16, 10, 4, 1, {0, 1, 2, 3}});
+    p.push_back({with_rearrange, with_mask, !with_scale, !causal, compressed, 1, ov::element::Type_t::f16, 10, 4, 1, {1, 2, 0, 3}});
 
     /* -- causal mask -- */
 
@@ -367,6 +369,8 @@ std::vector<Params> get_test_params() {
     p.push_back({with_rearrange, with_mask, !with_scale, causal, compressed, 1, ov::element::Type_t::f16, 10, 1, 1, {0, 1, 2, 3}});
     p.push_back({with_rearrange, with_mask, !with_scale, causal, compressed, 1, ov::element::Type_t::f16, 10, 4, 1, {0, 2, 1, 3}});
     p.push_back({with_rearrange, with_mask, !with_scale, causal, compressed, 1, ov::element::Type_t::f16, 10, 4, 1, {0, 1, 2, 3}});
+    p.push_back({with_rearrange, with_mask, !with_scale, causal, compressed, 1, ov::element::Type_t::f16, 10, 4, 1, {1, 2, 0, 3}});
+
     return p;
 }