///////////////////////////////////////////////////////////////////////////////////////////////////
#include <gtest/gtest.h>
-#include "api/CPP/memory.hpp"
-#include <api/CPP/input_layout.hpp>
-#include "api/CPP/convolution.hpp"
-#include "api/CPP/eltwise.hpp"
-#include "api/CPP/reorder.hpp"
-#include <api/CPP/topology.hpp>
-#include <api/CPP/network.hpp>
-#include <api/CPP/engine.hpp>
+#include "api/memory.hpp"
+#include <api/input_layout.hpp>
+#include "api/convolution.hpp"
+#include "api/eltwise.hpp"
+#include "api/reorder.hpp"
+#include <api/topology.hpp>
+#include <api/network.hpp>
+#include <api/engine.hpp>
#include "test_utils/test_utils.h"
-#include <api/CPP/data.hpp>
+#include <api/data.hpp>
-#include <api_extension/CPP/fused_conv_eltwise.hpp>
+#include <api_extension/fused_conv_eltwise.hpp>
#include <cassert>
#include <cmath>
EXPECT_EQ(out_layout.size.spatial[1], 5);
}
-
TEST(fused_conv_eltwise, dont_fuse_if_conv_elt_are_outputs)
{
const auto& engine = get_test_engine();
auto input_shape = tensor(1, n_features, 4, 1);
auto weights_shape = tensor(n_features, n_features, 3, 1);
- auto biases_shape = tensor(1, 1, n_features, 1);
+ auto biases_shape = tensor(1, n_features, 1, 1);
auto sum_input_shape = tensor(1, n_features, 2, 1);
auto input = memory::allocate(