IVGCVSW-3212 Refactor the Reference BatchNormalization workloads to

handle Float32 and QAsymm8 types

 * Removed the type-specific workload implementations
 * Added type-independent RefBatchNormalizationWorkload implementation
 * Reworked BachNormImpl to use decoders/encoders
 * Improved the validation of the BatchNorm queue descriptor
 * Fixed unit tests where necessary

Change-Id: Icf3fa1332292d38ec2fa0b1cb984cab78426034b
Signed-off-by: Matteo Martincigh <matteo.martincigh@arm.com>

1 files changed, 45 insertions, 0 deletions

diff --git a/src/backends/reference/workloads/RefBatchNormalizationWorkload.cpp b/src/backends/reference/workloads/RefBatchNormalizationWorkload.cpp
new file mode 100644
index 0000000000..b43b104459
--- /dev/null
+++ b/src/backends/reference/workloads/RefBatchNormalizationWorkload.cpp
@@ -0,0 +1,45 @@
+//
+// Copyright © 2017 Arm Ltd. All rights reserved.
+// SPDX-License-Identifier: MIT
+//
+
+#include "RefBatchNormalizationWorkload.hpp"
+
+#include "BatchNormImpl.hpp"
+#include "RefWorkloadUtils.hpp"
+
+#include "Profiling.hpp"
+
+namespace armnn
+{
+
+RefBatchNormalizationWorkload::RefBatchNormalizationWorkload(const BatchNormalizationQueueDescriptor& descriptor,
+                                                             const WorkloadInfo& info)
+    : BaseWorkload(descriptor, info)
+    , m_Mean    (std::make_unique<ScopedCpuTensorHandle>(*(descriptor.m_Mean)))
+    , m_Variance(std::make_unique<ScopedCpuTensorHandle>(*(descriptor.m_Variance)))
+    , m_Beta    (std::make_unique<ScopedCpuTensorHandle>(*(descriptor.m_Beta)))
+    , m_Gamma   (std::make_unique<ScopedCpuTensorHandle>(*(descriptor.m_Gamma)))
+{}
+
+void RefBatchNormalizationWorkload::Execute() const
+{
+    ARMNN_SCOPED_PROFILING_EVENT(Compute::CpuRef, "RefBatchNormalizationWorkload_Execute");
+
+    std::unique_ptr<Decoder<float>> meanDecoder = MakeDecoder<float>(GetTensorInfo(m_Mean.get()),
+                                                                     m_Mean.get()->Map(true));
+    std::unique_ptr<Decoder<float>> varianceDecoder = MakeDecoder<float>(GetTensorInfo(m_Variance.get()),
+                                                                         m_Variance.get()->Map(true));
+    std::unique_ptr<Decoder<float>> gammaDecoder = MakeDecoder<float>(GetTensorInfo(m_Gamma.get()),
+                                                                      m_Gamma.get()->Map(true));
+    std::unique_ptr<Decoder<float>> betaDecoder = MakeDecoder<float>(GetTensorInfo(m_Beta.get()),
+                                                                     m_Beta.get()->Map(true));
+    std::unique_ptr<Decoder<float>> inputDecoder = MakeDecoder<float>(GetTensorInfo(m_Data.m_Inputs[0]),
+                                                                      m_Data.m_Inputs[0]->Map());
+    std::unique_ptr<Encoder<float>> outputEncoder = MakeEncoder<float>(GetTensorInfo(m_Data.m_Outputs[0]),
+                                                                       m_Data.m_Outputs[0]->Map());
+
+    BatchNormImpl(m_Data, *meanDecoder, *varianceDecoder, *betaDecoder, *gammaDecoder, *inputDecoder, *outputEncoder);
+}
+
+} //namespace armnn