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authorSadik Armagan <sadik.armagan@arm.com>2019-07-12 13:55:57 +0100
committerSadik Armagan <sadik.armagan@arm.com>2019-07-12 13:55:57 +0100
commit5e9521ce5eac717b25844f9da4849b1fc2082f76 (patch)
tree05f5d7bc6656033784996c7ee08501789c9a5616 /OutputShapeUtils.cpp
parent6bda94a88536e8abb487a6ab29da4b8cfc8034e1 (diff)
downloadandroid-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
Diffstat (limited to 'OutputShapeUtils.cpp')
-rw-r--r--OutputShapeUtils.cpp64
1 files changed, 41 insertions, 23 deletions
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