Utilize padded info transposed by input_order for dynamic padding

Author: kelvinchoi-intel

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

@@ -200,14 +200,14 @@ KERNEL(gemm_tiled_opt)(
 #endif // TRANSPOSE_INPUT0
 #if TRANSPOSE_INPUT1 == TRANSPOSE_X_LAST
     const __global INPUT1_TYPE* b_ptr = input1 + batch_offset_input1;
-    #if HAS_DYNAMIC_N_PADDING || INPUT1_HAS_PADDING
+    #if HAS_DYNAMIC_K_PADDING || INPUT1_HAS_PADDING
         const uint input1_offset = FUNC_CALL(get_input1_index)(OPTIONAL_SHAPE_INFO_TENSOR b, f, w, z, 1, tile_n_offset) - batch_offset_input1;
     #else
         const uint input1_offset = FUNC_CALL(get_input1_index)(OPTIONAL_SHAPE_INFO_TENSOR 0, 0, 0, 0, 1, 0);
     #endif
 #elif TRANSPOSE_INPUT1 == TRANSPOSE_Y_LAST
     const __global INPUT1_TYPE* b_ptr = input1 + batch_offset_input1;
-    #if HAS_DYNAMIC_N_PADDING || INPUT1_HAS_PADDING
+    #if HAS_DYNAMIC_K_PADDING || INPUT1_HAS_PADDING
         const uint input1_offset = FUNC_CALL(get_input1_index)(OPTIONAL_SHAPE_INFO_TENSOR b, f, w, z, 0, (tile_n_offset + 1)) - batch_offset_input1;
         const uint input1_offset1 = FUNC_CALL(get_input1_index)(OPTIONAL_SHAPE_INFO_TENSOR b, f, w, z, (TILE_K), tile_n_offset) - batch_offset_input1;
     #else

src/plugins/intel_gpu/src/kernel_selector/kernel_selector_utils.h

@@ -53,6 +53,12 @@ struct DimensionAccessHelperJit : virtual DimensionAccessHelperBase {
                     pad_before_after_sizes.push_back(toCodeString(d.pad.before));
                     pad_before_after_sizes.push_back(toCodeString(d.pad.after));
                 }
+
+                if (d.pad.is_dynamic || d.is_dynamic) {
+                    dims_padded.push_back(true);
+                } else {
+                    dims_padded.push_back(false);
+                }
             }
         }
     }
@@ -76,6 +82,7 @@ struct DimensionAccessHelperJit : virtual DimensionAccessHelperBase {
 
     std::vector<std::string> dims_sizes;
     std::vector<std::string> pad_before_after_sizes;
+    std::vector<bool> dims_padded;
 };
 
 std::vector<size_t> GetImageSizes(const kernel_selector::WeightsTensor& dimensions, const WeightsLayout layout);

src/plugins/intel_gpu/src/kernel_selector/kernels/gemm/gemm_kernel_tiled_opt.cpp

@@ -205,27 +205,10 @@ JitConstants GemmKernelTiledOpt::GetJitConstants(const gemm_params& params) cons
         else
             jit.AddConstant(MakeJitConstant("TRANSPOSE_OUTPUT", 0 /* set as TRANSPOSE_X_LAST */));
 
-        bool has_dynamic_k_padding = params.transpose_input0 ? params.inputs[0].Y().pad.is_dynamic
-                                                             : params.inputs[0].X().pad.is_dynamic;
-        bool has_dynamic_n_padding = params.transpose_input1 ? params.inputs[1].Y().pad.is_dynamic
-                                                             : params.inputs[1].X().pad.is_dynamic;
+        bool has_dynamic_k_padding = params.transpose_input0 ? dims0_padded.dims_padded[input0_dims[6]]
+                                                             : dims0_padded.dims_padded[input0_dims[7]];
         if (has_dynamic_k_padding)
             jit.AddConstant(MakeJitConstant("HAS_DYNAMIC_K_PADDING", 1));
-        if (has_dynamic_n_padding)
-            jit.AddConstant(MakeJitConstant("HAS_DYNAMIC_N_PADDING", 1));
-
-        auto hasDynamicPad = [](DataTensor dt) -> bool {
-            auto dims = dt.GetDims();
-            for (auto d : dims) {
-                if (d.pad.is_dynamic)
-                    return true;
-            }
-            return false;
-        };
-        if (hasDynamicPad(params.inputs[0]))
-            jit.AddConstant(MakeJitConstant("INPUT0_HAS_PADDING", 1));
-        if (hasDynamicPad(params.inputs[1]))
-            jit.AddConstant(MakeJitConstant("INPUT1_HAS_PADDING", 1));
     } else {
         auto get_transposed_dim_size = [](const kernel_selector::DataTensor &data_tensor,
                                           const std::vector<int64_t>& dims_order, const std::string dim) {