Fix segfault in ParseTransposeConv2d when output_shape is not constant
We currently check that output_shape is an input for transpose conv2d.
If that is an input, we assume that it is constant and attempt to copy
the data into the descriptor. When this data is not constant and instead
comes from the output of another layer we segfault. When not constant
we will use infer output shapes.
* Adds a check into ParseTransposeConv2d that inputs[0] is constant
Signed-off-by: Ryan OShea <ryan.oshea3@arm.com>
Change-Id: I01176ae22974767a2306a3db749a029ed220d88b
diff --git a/src/armnnTfLiteParser/TfLiteParser.cpp b/src/armnnTfLiteParser/TfLiteParser.cpp
index 9e8af66..279f804 100644
--- a/src/armnnTfLiteParser/TfLiteParser.cpp
+++ b/src/armnnTfLiteParser/TfLiteParser.cpp
@@ -1606,7 +1606,11 @@
auto outputs = GetOutputs(m_Model, subgraphIndex, operatorIndex);
CHECK_VALID_SIZE(outputs.size(), 1);
- if (inputs[0])
+ // This block determines the output shape of the transpose convolution. If the output shape tensor ptr is not null
+ // And the tensor is a constant, we can access the data at load time and set the output shape of the
+ // layer. If this is not constant, We do not have access to the shape data, so we have to use
+ // infer output shape and skip this code block.
+ if (inputs[0] && IsConstTensor(inputs[0]))
{
armnn::TensorInfo tensorInfo = InputTensorInfo(subgraphIndex, operatorIndex, 0);
std::vector<int> output_shape(tensorInfo.GetNumElements());