1 files changed, 110 insertions, 0 deletions
diff --git a/Convolution2D.cpp b/Convolution2D.cpp
new file mode 100644
index 00000000..a8491955
--- /dev/null
+++ b/Convolution2D.cpp
@@ -0,0 +1,110 @@
+//
+// Copyright © 2017 Arm Ltd. All rights reserved.
+// SPDX-License-Identifier: MIT
+//
+#include "../DriverTestHelpers.hpp"
+#include <boost/test/unit_test.hpp>
+#include <log/log.h>
+
+#include <OperationsUtils.h>
+
+BOOST_AUTO_TEST_SUITE(Convolution2DTests)
+
+using namespace android::hardware;
+using namespace driverTestHelpers;
+using namespace armnn_driver;
+
+namespace
+{
+
+void PaddingTestImpl(android::nn::PaddingScheme paddingScheme)
+{
+    auto driver = std::make_unique<ArmnnDriver>(DriverOptions(armnn::Compute::CpuRef));
+    V1_0::Model model  = {};
+
+    uint32_t outSize = paddingScheme == android::nn::kPaddingSame ? 2 : 1;
+
+    // add operands
+    float weightValue[] = {1, -1, 0, 1};
+    float biasValue[]   = {0};
+
+    AddInputOperand(model, hidl_vec<uint32_t>{1, 2, 3, 1});
+    AddTensorOperand(model, hidl_vec<uint32_t>{1, 2, 2, 1}, weightValue);
+    AddTensorOperand(model, hidl_vec<uint32_t>{1}, biasValue);
+    AddIntOperand(model, (int32_t)paddingScheme); // padding
+    AddIntOperand(model, 2); // stride x
+    AddIntOperand(model, 2); // stride y
+    AddIntOperand(model, 0); // no activation
+    AddOutputOperand(model, hidl_vec<uint32_t>{1, 1, outSize, 1});
+
+    // make the convolution operation
+    model.operations.resize(1);
+    model.operations[0].type = V1_0::OperationType::CONV_2D;
+    model.operations[0].inputs  = hidl_vec<uint32_t>{0, 1, 2, 3, 4, 5, 6};
+    model.operations[0].outputs = hidl_vec<uint32_t>{7};
+
+    // make the prepared model
+    android::sp<IPreparedModel> preparedModel = PrepareModel(model, *driver);
+
+    // construct the request
+    DataLocation inloc    = {};
+    inloc.poolIndex       = 0;
+    inloc.offset          = 0;
+    inloc.length          = 6 * sizeof(float);
+    RequestArgument input = {};
+    input.location        = inloc;
+    input.dimensions      = hidl_vec<uint32_t>{};
+
+    DataLocation outloc    = {};
+    outloc.poolIndex       = 1;
+    outloc.offset          = 0;
+    outloc.length          = outSize * sizeof(float);
+    RequestArgument output = {};
+    output.location        = outloc;
+    output.dimensions      = hidl_vec<uint32_t>{};
+
+    Request request = {};
+    request.inputs  = hidl_vec<RequestArgument>{input};
+    request.outputs = hidl_vec<RequestArgument>{output};
+
+
+    // set the input data (matching source test)
+    float indata[] = {4, 1, 0, 3, -1, 2};
+    AddPoolAndSetData(6, request, indata);
+
+    // add memory for the output
+    android::sp<IMemory> outMemory = AddPoolAndGetData(outSize, request);
+    float* outdata   = static_cast<float*>(static_cast<void*>(outMemory->getPointer()));
+
+    // run the execution
+    Execute(preparedModel, request);
+
+    // check the result
+    if (paddingScheme == android::nn::kPaddingValid)
+    {
+        BOOST_TEST(outdata[0] == 2);
+    }
+    else if (paddingScheme == android::nn::kPaddingSame)
+    {
+        BOOST_TEST(outdata[0] == 2);
+        BOOST_TEST(outdata[1] == 0);
+    }
+    else
+    {
+        BOOST_TEST(false);
+    }
+}
+
+} // namespace <anonymous>
+
+BOOST_AUTO_TEST_CASE(ConvValidPadding)
+{
+    PaddingTestImpl(android::nn::kPaddingValid);
+}
+
+BOOST_AUTO_TEST_CASE(ConvSamePadding)
+{
+    PaddingTestImpl(android::nn::kPaddingSame);
+}
+
+BOOST_AUTO_TEST_SUITE_END()