IVGCVSW-3456 Add support for dynamic output shape in ConvertPrelu
Signed-off-by: Aron Virginas-Tar <Aron.Virginas-Tar@arm.com>
Change-Id: I8fc7a716455be3f51b51177f6896a73790a41fc3
diff --git a/1.2/HalPolicy.cpp b/1.2/HalPolicy.cpp
index fe0cfbd..b194a57 100644
--- a/1.2/HalPolicy.cpp
+++ b/1.2/HalPolicy.cpp
@@ -5,6 +5,8 @@
#include "HalPolicy.hpp"
+#include "OutputShapeUtils.hpp"
+
#include "../1.0/HalPolicy.hpp"
#include "../1.1/HalPolicy.hpp"
@@ -539,7 +541,13 @@
const armnn::TensorInfo& inputInfo = input.GetTensorInfo();
const armnn::TensorInfo& alphaInfo = alpha.GetTensorInfo();
- const armnn::TensorInfo& outputInfo = GetTensorInfoForOperand(*output);
+
+ armnn::TensorInfo outputInfo = GetTensorInfoForOperand(*output);
+ if (outputInfo.GetNumElements() == 0u)
+ {
+ ALOGD("Output shape not set, will infer from inputs");
+ outputInfo.SetShape(InferPreluOutputShape(inputInfo.GetShape(), alphaInfo.GetShape()));
+ }
if (!IsLayerSupportedForAnyBackend(__func__,
armnn::IsPreluSupported,
@@ -560,7 +568,12 @@
BroadcastTensor(input, alpha, layer, *data.m_Network);
- return SetupAndTrackLayerOutputSlot<hal_1_2::HalPolicy>(operation, 0, *layer, model, data);
+ return SetupAndTrackLayerOutputSlot<hal_1_2::HalPolicy>(operation,
+ 0,
+ *layer,
+ model,
+ data,
+ armnn::Optional<armnn::TensorInfo>(outputInfo));
}
bool HalPolicy::ConvertResize(const Operation& operation,
diff --git a/Android.mk b/Android.mk
index bee57dd..215b0a8 100644
--- a/Android.mk
+++ b/Android.mk
@@ -334,6 +334,7 @@
ConversionUtils.cpp \
DriverOptions.cpp \
ModelToINetworkConverter.cpp \
+ OutputShapeUtils.cpp \
RequestThread.cpp \
Utils.cpp
diff --git a/ConversionUtils.hpp b/ConversionUtils.hpp
index d30b8a4..c9be000 100644
--- a/ConversionUtils.hpp
+++ b/ConversionUtils.hpp
@@ -1028,7 +1028,8 @@
armnn::IConnectableLayer& layer,
uint32_t layerOutputIndex,
const HalModel& model,
- ConversionData& data)
+ ConversionData& data,
+ const armnn::Optional<armnn::TensorInfo>& outputInfo = armnn::EmptyOptional())
{
using HalOperand = typename HalPolicy::Operand;
@@ -1043,7 +1044,15 @@
const uint32_t operandIndex = operation.outputs[operationOutputIndex];
data.m_OutputSlotForOperand[operandIndex] = &outputSlot;
- outputSlot.SetTensorInfo(GetTensorInfoForOperand(*outputOperand));
+ if (outputInfo.has_value())
+ {
+ outputSlot.SetTensorInfo(outputInfo.value());
+ ALOGD("Output info overwritten");
+ }
+ else
+ {
+ outputSlot.SetTensorInfo(GetTensorInfoForOperand(*outputOperand));
+ }
return true;
}
@@ -1092,9 +1101,16 @@
uint32_t outputIndex,
armnn::IConnectableLayer& layer,
const HalModel& model,
- ConversionData& data)
+ ConversionData& data,
+ const armnn::Optional<armnn::TensorInfo>& outputInfo = armnn::EmptyOptional())
{
- return SetupAndTrackLayerOutputSlot<HalPolicy>(operation, outputIndex, layer, outputIndex, model, data);
+ return SetupAndTrackLayerOutputSlot<HalPolicy>(operation,
+ outputIndex,
+ layer,
+ outputIndex,
+ model,
+ data,
+ outputInfo);
}
template<typename HalPolicy,
diff --git a/OutputShapeUtils.cpp b/OutputShapeUtils.cpp
new file mode 100644
index 0000000..de27630
--- /dev/null
+++ b/OutputShapeUtils.cpp
@@ -0,0 +1,43 @@
+//
+// Copyright © 2017 Arm Ltd. All rights reserved.
+// SPDX-License-Identifier: MIT
+//
+
+#include "OutputShapeUtils.hpp"
+
+#include <algorithm>
+
+namespace armnn_driver
+{
+
+using namespace armnn;
+
+TensorShape InferPreluOutputShape(const TensorShape& inputShape, const TensorShape& alphaShape)
+{
+ // NOTE: The inferred PReLU output size will be the maximum size along each dimension
+ // of input and alpha, starting with the trailing dimensions, and working its way forward.
+ //
+ // Example: inputShape={4, 1, 2}, alphaShape={5, 4, 3, 1} => outputShape={5, 4, 3, 2}
+
+ const unsigned int numInputDims = inputShape.GetNumDimensions();
+ const unsigned int numAlphaDims = alphaShape.GetNumDimensions();
+
+ const unsigned int maxNumDims = std::max(numInputDims, numAlphaDims);
+
+ TensorShape outputShape = TensorShape(maxNumDims);
+ for (unsigned int reverseIdx = 1u; reverseIdx <= maxNumDims; ++reverseIdx)
+ {
+ const int inputIdx = numInputDims - reverseIdx;
+ const int alphaIdx = numAlphaDims - reverseIdx;
+
+ const unsigned int inputDimSize = inputIdx >= 0 ? inputShape[inputIdx] : 0u;
+ const unsigned int alphaDimSize = alphaIdx >= 0 ? alphaShape[alphaIdx] : 0u;
+
+ const unsigned int outputIdx = maxNumDims - reverseIdx;
+ outputShape[outputIdx] = std::max(inputDimSize, alphaDimSize);
+ }
+
+ return outputShape;
+}
+
+} // namespace armnn_driver
\ No newline at end of file
diff --git a/OutputShapeUtils.hpp b/OutputShapeUtils.hpp
new file mode 100644
index 0000000..f314252
--- /dev/null
+++ b/OutputShapeUtils.hpp
@@ -0,0 +1,17 @@
+//
+// Copyright © 2017 Arm Ltd. All rights reserved.
+// SPDX-License-Identifier: MIT
+//
+
+#pragma once
+
+#include <armnn/ArmNN.hpp>
+
+namespace armnn_driver
+{
+
+armnn::TensorShape InferPreluOutputShape(const armnn::TensorShape& inputShape, const armnn::TensorShape& alphaShape);
+
+} // namespace armnn_driver
+
+