diff --git a/inference-engine/thirdparty/clDNN/kernel_selector/core/actual_kernels/eltwise/eltwise_kernel_vload8.cpp b/inference-engine/thirdparty/clDNN/kernel_selector/core/actual_kernels/eltwise/eltwise_kernel_vload8.cpp
index fb7cac013d4ada..80b786897f3a3f 100644
--- a/inference-engine/thirdparty/clDNN/kernel_selector/core/actual_kernels/eltwise/eltwise_kernel_vload8.cpp
+++ b/inference-engine/thirdparty/clDNN/kernel_selector/core/actual_kernels/eltwise/eltwise_kernel_vload8.cpp
@@ -40,8 +40,8 @@ bool EltwiseKernel_vload8::Validate(const Params& params, const optional_params&
             return false;
     }
     if ((ewParams.output.GetLayout() == DataLayout::b_fs_yx_fsv16 && ewParams.output.Feature().v % 16 != 0) ||
-       (ewParams.output.GetLayout() == DataLayout::b_fs_zyx_fsv16 && ewParams.output.Feature().v % 16 != 0) ||
-       (ewParams.output.GetLayout() == DataLayout::b_fs_yx_fsv4 && ewParams.output.Feature().v % 8 != 0) ||
+        (ewParams.output.GetLayout() == DataLayout::b_fs_zyx_fsv16 && ewParams.output.Feature().v % 16 != 0) ||
+        (ewParams.output.GetLayout() == DataLayout::b_fs_yx_fsv4 && ewParams.output.Feature().v % 8 != 0) ||
         ewParams.output.GetLayout() == DataLayout::fs_b_yx_fsv32)
         return false;
 
diff --git a/inference-engine/thirdparty/clDNN/kernel_selector/core/common/kernel_selector_utils.cpp b/inference-engine/thirdparty/clDNN/kernel_selector/core/common/kernel_selector_utils.cpp
index 867dc94ad4041e..a32f5bd0f0f159 100644
--- a/inference-engine/thirdparty/clDNN/kernel_selector/core/common/kernel_selector_utils.cpp
+++ b/inference-engine/thirdparty/clDNN/kernel_selector/core/common/kernel_selector_utils.cpp
@@ -220,44 +220,53 @@ std::vector<size_t> GetOptimalLocalWorkGroupSizes(std::vector<size_t> gws, const
 bool CheckInputsOutputNoPitchSameDims(const base_params& params) {
     bool no_pitch_same_dims = true;
 
-    std::vector<std::pair <DataLayout, int>> block_layouts = {
-        {DataLayout::b_fs_yx_fsv16,          16},
-        {DataLayout::b_fs_zyx_fsv16,         16},
-        {DataLayout::b_fs_yx_fsv32,          32},
-        {DataLayout::b_fs_zyx_fsv32,         32},
-        {DataLayout::bs_fs_yx_bsv16_fsv16,   16},
-        {DataLayout::bs_fs_zyx_bsv16_fsv16,  16},
-        {DataLayout::bs_f_bsv8__af8,         8},
-        {DataLayout::bs_f_bsv16__af8,        16},
-        {DataLayout::b_fs_yx_fsv4,           4},
-        {DataLayout::fs_b_yx_fsv32,          32},
-        {DataLayout::b_fs_yx_32fp,           32}
+    std::map<DataLayout, std::pair<int, int>> block_layouts {
+        {DataLayout::b_fs_yx_fsv16,          {1, 16}},
+        {DataLayout::b_fs_zyx_fsv16,         {1, 16}},
+        {DataLayout::b_fs_yx_fsv32,          {1, 32}},
+        {DataLayout::b_fs_zyx_fsv32,         {1, 32}},
+        {DataLayout::bs_fs_yx_bsv16_fsv16,   {16, 16}},
+        {DataLayout::bs_fs_zyx_bsv16_fsv16,  {16, 16}},
+        {DataLayout::bs_f_bsv8__af8,         {8, 8}},
+        {DataLayout::bs_f_bsv16__af8,        {16, 8}},
+        {DataLayout::b_fs_yx_fsv4,           {1, 4}},
+        {DataLayout::fs_b_yx_fsv32,          {1, 32}},
+        {DataLayout::b_fs_yx_32fp,           {1, 32}}
     };
 
     if (params.inputs.size()) {
         no_pitch_same_dims = !params.inputs[0].PitchesDifferFromLogicalDims();
-        for (const auto& layout : block_layouts) {
-            if (params.fused_ops.size()) {
-                for (auto fused_op : params.fused_ops) {
-                    for (size_t in = 0; in < fused_op.tensors.size(); in++) {
-                        if (fused_op.tensors[in].LogicalSize() == 1)
-                            continue;
-                        if (fused_op.tensors[in].GetLayout() == layout.first && fused_op.tensors[in].Feature().v % layout.second != 0)
-                            return false;
-                        no_pitch_same_dims = no_pitch_same_dims && (params.inputs[0] == fused_op.tensors[in]);
-                    }
-                }
-            }
+        if (params.fused_ops.size()) {
+            for (auto fused_op : params.fused_ops) {
+                for (size_t in = 0; in < fused_op.tensors.size(); in++) {
+                    if (fused_op.tensors[in].LogicalSize() == 1)
+                        continue;
 
-            for (size_t i = 0; i < params.inputs.size(); i++) {
-                no_pitch_same_dims = no_pitch_same_dims && (params.inputs[0] == params.inputs[i]);
+                    auto layout = block_layouts.find(fused_op.tensors[in].GetLayout());
+                    if (layout == block_layouts.end())
+                        continue;
 
-                if (params.inputs[i].GetLayout() == layout.first && params.inputs[i].Feature().v % layout.second != 0)
-                    return false;
+                    auto block_size = layout->second;
+                    if (fused_op.tensors[in].Batch().v % block_size.first != 0 || fused_op.tensors[in].Feature().v % block_size.second != 0)
+                        return false;
+
+                    no_pitch_same_dims = no_pitch_same_dims && (params.inputs[0] == fused_op.tensors[in]);
+                }
             }
+        }
+
+        for (size_t i = 0; i < params.inputs.size(); i++) {
+            no_pitch_same_dims = no_pitch_same_dims && (params.inputs[0] == params.inputs[i]);
+            auto layout = block_layouts.find(params.inputs[i].GetLayout());
+            if (layout == block_layouts.end())
+                continue;
 
-            no_pitch_same_dims = no_pitch_same_dims && (params.inputs[0] == params.output);
+            auto block_size = layout->second;
+            if (params.inputs[i].Batch().v % block_size.first != 0 || params.inputs[i].Feature().v % block_size.second != 0)
+                return false;
         }
+
+        no_pitch_same_dims = no_pitch_same_dims && (params.inputs[0] == params.output);
     }
 
     return no_pitch_same_dims;