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author | Sadik Armagan <sadik.armagan@arm.com> | 2019-07-12 13:55:57 +0100 |
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committer | Sadik Armagan <sadik.armagan@arm.com> | 2019-07-12 13:55:57 +0100 |
commit | 5e9521ce5eac717b25844f9da4849b1fc2082f76 (patch) | |
tree | 05f5d7bc6656033784996c7ee08501789c9a5616 | |
parent | 6bda94a88536e8abb487a6ab29da4b8cfc8034e1 (diff) | |
download | android-nn-driver-5e9521ce5eac717b25844f9da4849b1fc2082f76.tar.gz |
IVGCVSW-3458 Fix VTS sub dynamic_output_shape test failures
Signed-off-by: Sadik Armagan <sadik.armagan@arm.com>
Change-Id: Ia6e2a082ed4a0255d8c9c10375590553e6ede9f0
-rw-r--r-- | 1.1/HalPolicy.cpp | 12 | ||||
-rw-r--r-- | OutputShapeUtils.cpp | 64 | ||||
-rw-r--r-- | OutputShapeUtils.hpp | 2 |
3 files changed, 52 insertions, 26 deletions
diff --git a/1.1/HalPolicy.cpp b/1.1/HalPolicy.cpp index 9f2c9be1..fbd2e08e 100644 --- a/1.1/HalPolicy.cpp +++ b/1.1/HalPolicy.cpp @@ -178,10 +178,11 @@ bool HalPolicy::ConvertSub(const Operation& operation, const Model& model, Conve return false; } - const armnn::TensorInfo& outputInfo = GetTensorInfoForOperand(*outputOperand); + armnn::TensorInfo outputInfo = GetTensorInfoForOperand(*outputOperand); if (IsDynamicOutput(outputInfo)) { - return Fail("%s: Dynamic output not supported", __func__); + ALOGD("Output shape not set, will infer from inputs"); + outputInfo.SetShape(InferSubOutputShape(input0.GetTensorInfo().GetShape(), input1.GetTensorInfo().GetShape())); } if (!IsLayerSupportedForAnyBackend(__func__, @@ -203,7 +204,12 @@ bool HalPolicy::ConvertSub(const Operation& operation, const Model& model, Conve if (endLayer) { BroadcastTensor(input0, input1, startLayer, *data.m_Network); - return SetupAndTrackLayerOutputSlot<hal_1_1::HalPolicy>(operation, 0, *endLayer, model, data); + return SetupAndTrackLayerOutputSlot<hal_1_1::HalPolicy>(operation, + 0, + *endLayer, + model, + data, + armnn::Optional<armnn::TensorInfo>(outputInfo)); } return Fail("%s: ProcessActivation failed", __func__); diff --git a/OutputShapeUtils.cpp b/OutputShapeUtils.cpp index a1a49d70..739038ac 100644 --- a/OutputShapeUtils.cpp +++ b/OutputShapeUtils.cpp @@ -8,6 +8,42 @@ #include <algorithm> #include <vector> +namespace +{ + +using namespace armnn; + +TensorShape CalculateMaxShape(const TensorShape& inShape0, const TensorShape& inShape1) +{ + // NOTE: The inferred output size will be the maximum size along each dimension + // of inShape0 and inShape1, starting with the trailing dimensions, and working its way forward. + // + // Example: inShape0={4, 1, 2}, inShape1={5, 4, 3, 1} => outputShape={5, 4, 3, 2} + + const unsigned int numInput0Dims = inShape0.GetNumDimensions(); + const unsigned int numInput1Dims = inShape1.GetNumDimensions(); + + const unsigned int maxNumDims = std::max(numInput0Dims, numInput1Dims); + + TensorShape outputShape = TensorShape(maxNumDims); + for (unsigned int reverseIdx = 1u; reverseIdx <= maxNumDims; ++reverseIdx) + { + const int input0Idx = numInput0Dims - reverseIdx; + const int input1Idx = numInput1Dims - reverseIdx; + + const unsigned int input0DimSize = input0Idx >= 0 ? inShape0[input0Idx] : 0u; + const unsigned int input1DimSize = input1Idx >= 0 ? inShape1[input1Idx] : 0u; + + const unsigned int outputIdx = maxNumDims - reverseIdx; + outputShape[outputIdx] = std::max(input0DimSize, input1DimSize); + } + + return outputShape; +} + +} // namespace annonymous + + namespace armnn_driver { @@ -38,30 +74,12 @@ TensorShape InferPadOutputShape(const TensorShape& inputShape, 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 CalculateMaxShape(inputShape, alphaShape); +} - return outputShape; +TensorShape InferSubOutputShape(const TensorShape& input0Shape, const TensorShape& input1Shape) +{ + return CalculateMaxShape(input0Shape, input1Shape); } } // namespace armnn_driver
\ No newline at end of file diff --git a/OutputShapeUtils.hpp b/OutputShapeUtils.hpp index d1818db1..be255c28 100644 --- a/OutputShapeUtils.hpp +++ b/OutputShapeUtils.hpp @@ -17,6 +17,8 @@ armnn::TensorShape InferPadOutputShape(const armnn::TensorShape& inputShape, armnn::TensorShape InferPreluOutputShape(const armnn::TensorShape& inputShape, const armnn::TensorShape& alphaShape); +armnn::TensorShape InferSubOutputShape(const armnn::TensorShape& input0Shape, const armnn::TensorShape& input1Shape); + } // namespace armnn_driver |