Print out more information about the graph
Besides, the layer name, type and backend, it is useful
to print the count of input/output tensors. Also, we could
print the tensor dimensions.
Signed-off-by: Ayan Halder <ayan.halder@arm.com>
Change-Id: I91ac09ae1d594e13f01e1db60dc531b16ae87dde
diff --git a/src/armnn/Graph.cpp b/src/armnn/Graph.cpp
index 30546e1..7b6f56f 100644
--- a/src/armnn/Graph.cpp
+++ b/src/armnn/Graph.cpp
@@ -70,8 +70,45 @@
for (auto&& it : TopologicalSort())
{
+ auto numInputSlots = it->GetNumInputSlots();
+ auto numOutputSlots = it->GetNumOutputSlots();
+
ARMNN_LOG(info) << it->GetName() << ":" << GetLayerTypeAsCString(it->GetType())
- << ":" << it->GetBackendId().Get();
+ << ":" << it->GetBackendId().Get()
+ << " has " << numInputSlots << " input slots"
+ << " and " << numOutputSlots << " output slots.";
+
+ for (auto i : it->GetInputSlots())
+ {
+ std::ostringstream message;
+ auto inputTensorShape = i.GetConnectedOutputSlot()->GetTensorInfo().GetShape();
+ unsigned int numDims = inputTensorShape.GetNumDimensions();
+
+ message << "The input slot has shape [ ";
+ for (unsigned int dim=0; dim < numDims; dim++)
+ {
+ message << inputTensorShape[dim] << ",";
+ }
+ message << " ]";
+ ARMNN_LOG(info) << message.str();
+ }
+
+ for (unsigned int i = 0; i < it->GetNumOutputSlots(); i++)
+ {
+ const armnn::Layer *layer = it;
+ std::ostringstream message;
+ auto outputTensorShape = layer->GetOutputSlots()[i].GetTensorInfo().GetShape();
+ unsigned int numDims = outputTensorShape.GetNumDimensions();
+
+ message << "The output slot has shape [ ";
+ for (unsigned int dim=0; dim < numDims; dim++)
+ {
+ message << outputTensorShape[dim] << ",";
+ }
+ message << " ]";
+ ARMNN_LOG(info) << message.str();
+ }
+ ARMNN_LOG(info) << "\n";
}
ARMNN_LOG(info) << "\n\n";
