[GPU] Add int8 input type for pooling ref kernel to cover fs_b_yx_fsv…

…32 and int8 case
openvinotoolkit · Nov 1, 2024 · 5b7e1dd · 5b7e1dd
1 parent b9a94c3
commit 5b7e1dd
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diff --git a/src/plugins/intel_gpu/src/kernel_selector/kernels/pooling/pooling_kernel_gpu_ref.cpp b/src/plugins/intel_gpu/src/kernel_selector/kernels/pooling/pooling_kernel_gpu_ref.cpp
@@ -9,6 +9,8 @@ ParamsKey PoolingKernelGPURef::GetSupportedKey() const {
     ParamsKey k;
     k.EnableInputDataType(Datatype::F16);
     k.EnableInputDataType(Datatype::F32);
+    k.EnableInputDataType(Datatype::UINT8);
+    k.EnableInputDataType(Datatype::INT8);
     k.EnableOutputDataType(Datatype::F16);
     k.EnableOutputDataType(Datatype::F32);
     k.EnableOutputDataType(Datatype::UINT8);

diff --git a/src/plugins/intel_gpu/tests/unit/test_cases/pooling_gpu_test.cpp b/src/plugins/intel_gpu/tests/unit/test_cases/pooling_gpu_test.cpp
@@ -1517,6 +1517,48 @@ TEST(pooling_forward_gpu, b_fs_yx_fsv4)
     } // for (int j = 0; F_array[j]; i++)
 }
 
+TEST(pooling_forward_gpu, fs_b_yx_fsv32_int8)
+{
+    auto& engine = get_test_engine();
+
+    auto input_prim = engine.allocate_memory({ data_types::f32, format::yxfb, { 1, 32, 1, 2 } });
+
+    topology topology;
+    topology.add(input_layout("input", input_prim->get_layout()));
+    topology.add(reorder("reorder_input", input_info("input"), layout(data_types::i8, format::fs_b_yx_fsv32, { 1, 32, 1, 2 })));
+    topology.add(pooling("avg_pooling", input_info("reorder_input"), pooling_mode::average, { 7, 7 }, { 2, 2 }));
+    topology.add(reorder("reorder_after_pooling", input_info("avg_pooling"), layout(data_types::f32, format::fs_b_yx_fsv32, { 1, 32, 1, 1 })));
+
+    network network(engine, topology, get_test_default_config(engine));
+    set_values(input_prim, { 41.f, 42.f, 43.f, 44.f, 45.f, 46.f, 47.f, 48.f,
+                             11.f, 12.f, 13.f, 14.f, 15.f, 16.f, 17.f, 18.f,
+                             21.f, 22.f, 23.f, 24.f, 25.f, 26.f, 27.f, 28.f,
+                             31.f, 32.f, 33.f, 34.f, 35.f, 36.f, 37.f, 38.f,
+
+                             31.f, 32.f, 33.f, 34.f, 35.f, 36.f, 37.f, 38.f,
+                             21.f, 22.f, 23.f, 24.f, 25.f, 26.f, 27.f, 28.f,
+                             51.f, 52.f, 53.f, 54.f, 55.f, 56.f, 57.f, 58.f,
+                             11.f, 12.f, 13.f, 14.f, 15.f, 16.f, 17.f, 18.f });
+    network.set_input_data("input", input_prim);
+
+    auto outputs = network.execute();
+    ASSERT_EQ(outputs.size(), size_t(1));
+    ASSERT_EQ(outputs.begin()->first, "reorder_after_pooling");
+
+    auto output_prim = outputs.begin()->second.get_memory();
+
+    cldnn::mem_lock<float> output_ptr(output_prim, get_test_stream());
+
+    std::vector<float> ref_data = { 36.f, 37.f, 38.f, 39.f, 40.f, 41.f, 42.f, 43.f,
+                                    16.f, 17.f, 18.f, 19.f, 20.f, 21.f, 22.f, 23.f,
+                                    36.f, 37.f, 38.f, 39.f, 40.f, 41.f, 42.f, 43.f,
+                                    21.f, 22.f, 23.f, 24.f, 25.f, 26.f, 27.f, 28.f };
+
+    for (size_t i = 0; i < ref_data.size(); i++) {
+        ASSERT_EQ(ref_data[i], float(output_ptr[i]));
+    }
+}
+
 TEST(pooling_forward_gpu, fs_b_yx_fsv32_avg_3x3_input_2x2_pool_1x1_stride_2x2_output)
 {
     auto& engine = get_test_engine();