IVGCVSW-4516 Add ConvertFp32ToBf16Layer and Ref workload support
Signed-off-by: Narumol Prangnawarat <narumol.prangnawarat@arm.com>
Change-Id: I9099a4f840fb747336f77d20a0868b64e801a310
diff --git a/src/backends/backendsCommon/test/layerTests/ConvertFp32ToBf16TestImpl.cpp b/src/backends/backendsCommon/test/layerTests/ConvertFp32ToBf16TestImpl.cpp
new file mode 100644
index 0000000..66eb4ee
--- /dev/null
+++ b/src/backends/backendsCommon/test/layerTests/ConvertFp32ToBf16TestImpl.cpp
@@ -0,0 +1,77 @@
+//
+// Copyright © 2020 Arm Ltd. All rights reserved.
+// SPDX-License-Identifier: MIT
+//
+
+#include "ConvertFp32ToBf16TestImpl.hpp"
+
+#include <backendsCommon/test/TensorCopyUtils.hpp>
+#include <backendsCommon/test/WorkloadTestUtils.hpp>
+
+#include <test/TensorHelpers.hpp>
+
+LayerTestResult<armnn::BFloat16, 4> ConvertFp32ToBf16Test(
+ armnn::IWorkloadFactory& workloadFactory,
+ const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager)
+{
+ IgnoreUnused(memoryManager);
+
+ const armnn::TensorInfo inputTensorInfo({1, 2, 4, 3}, armnn::DataType::Float32);
+ const armnn::TensorInfo outputTensorInfo({1, 2, 4, 3}, armnn::DataType::BFloat16);
+
+ auto input = MakeTensor<float, 4>(inputTensorInfo,
+ { -37.5f, -15.2f, -8.76f,
+ -2.0f, -1.5f, -1.3f,
+ -0.5f, -0.4f, 0.0f,
+ 1.0f, 0.4f, 0.5f,
+ 1.3f, 1.5f, 2.0f,
+ 8.76f, 15.2f, 37.5f,
+ 3.8f, // 0x40733333 Round down
+ 3.1055E+29f, // 0x707ADC3C Round up
+ 9.149516E-10f, // 0x307B7FFF Round down
+ -3.8f, // 0xC0733333 Round down
+ -3.1055E+29f, // 0xF07ADC3C Round up
+ -9.149516E-10f // 0xB07B7FFF Round down
+ });
+
+ std::vector<armnn::BFloat16> outputValues = armnnUtils::QuantizedVector<armnn::BFloat16>(
+ {
+ -37.5f, -15.2f, -8.76f,
+ -2.0f, -1.5f, -1.3f,
+ -0.5f, -0.4f, 0.0f,
+ 1.0f, 0.4f, 0.5f,
+ 1.3f, 1.5f, 2.0f,
+ 8.76f, 15.2f, 37.5f,
+ 3.796875f, // 0x4073
+ 3.1072295E29f, // 0x707B
+ 9.131327E-10f, // 0x307B
+ -3.796875f, // 0xC073
+ -3.1072295E29f, // 0xF07B
+ -9.131327E-10f // 0xB07B
+ },
+ 1.0f, 0);
+
+ LayerTestResult<armnn::BFloat16, 4> ret(outputTensorInfo);
+ ret.outputExpected = MakeTensor<armnn::BFloat16, 4>(outputTensorInfo, outputValues);
+
+ std::unique_ptr<armnn::ITensorHandle> inputHandle = workloadFactory.CreateTensorHandle(inputTensorInfo);
+ std::unique_ptr<armnn::ITensorHandle> outputHandle = workloadFactory.CreateTensorHandle(outputTensorInfo);
+
+ armnn::ConvertFp32ToBf16QueueDescriptor data;
+ armnn::WorkloadInfo info;
+ AddInputToWorkload(data, info, inputTensorInfo, inputHandle.get());
+ AddOutputToWorkload(data, info, outputTensorInfo, outputHandle.get());
+
+ std::unique_ptr<armnn::IWorkload> workload = workloadFactory.CreateConvertFp32ToBf16(data, info);
+
+ inputHandle->Allocate();
+ outputHandle->Allocate();
+
+ CopyDataToITensorHandle(inputHandle.get(), &input[0][0][0][0]);
+
+ workload->Execute();
+
+ CopyDataFromITensorHandle(&ret.output[0][0][0][0], outputHandle.get());
+
+ return ret;
+}