Remove QConvInteger test case

src/ngraph/runtime/cpu/mkldnn_emitter.hpp

@@ -44,8 +44,8 @@
 #include "ngraph/op/fused/group_conv.hpp"
 #include "ngraph/op/lrn.hpp"
 #include "ngraph/op/max_pool.hpp"
-#include "ngraph/op/quantized_convolution.hpp"
 #include "ngraph/op/quantize.hpp"
+#include "ngraph/op/quantized_convolution.hpp"
 #include "ngraph/op/softmax.hpp"
 #include "ngraph/runtime/cpu/cpu_executor.hpp"
 #include "ngraph/runtime/cpu/cpu_tensor_view_wrapper.hpp"

test/builder_quantization.cpp

@@ -192,41 +192,6 @@ TEST(builder, scaled_QC)
               read_vector<int8_t>(result));
 }
 
-#if 0
-TEST(builder, scaled_QConvInteger)
-{
-    Shape shape_a{1, 1, 3, 4}; // input shape
-    Shape shape_b{1, 1, 3, 3}; // filter shape
-    Shape shape_r{1, 1, 3, 4}; // output shape
-    vector<uint8_t> a_data = {1, 2, 3, 4, 5, 6, 7, 0, 1, 2, 3, 4};
-    vector<int8_t> b_data = {1, 2, 3, 4, 5, 0, 0, 1, 2};
-    auto A = make_shared<op::Parameter>(element::u8, shape_a);
-    auto B = make_shared<op::Parameter>(element::i8, shape_b);
-    auto CV =
-        ngraph::builder::quantization::QuantizedConvInteger(A,
-                                                            B,
-                                                            Strides{1, 1},        // move_strides
-                                                            Strides{1, 1},        // filter_dilation
-                                                            CoordinateDiff{1, 1}, // below_pads
-                                                            CoordinateDiff{1, 1}, // above_pads
-                                                            Strides{1, 1});       // data_dilation
-    auto f = make_shared<Function>(NodeVector{CV}, ParameterVector{A, B});
-    constant_fold(f);
-
-    auto backend = runtime::Backend::create("CPU");
-    // Create some tensors for input/output
-    auto a = backend->create_tensor(element::u8, shape_a);
-    copy_data(a, a_data);
-    auto b = backend->create_tensor(element::i8, shape_b);
-    copy_data(b, b_data);
-    auto result = backend->create_tensor(element::i32, shape_r);
-    auto handle = backend->compile(f);
-    handle->call_with_validate({result}, {a, b});
-    EXPECT_EQ((vector<int32_t>{22, 34, 30, 32, 38, 72, 90, 43, 33, 52, 43, 39}),
-              read_vector<int32_t>(result));
-}
-#endif
-
 TEST(builder, dynamic_scaled_QC)
 {
     Shape shape_a{1, 1, 3, 4}; // input shape