IVGCVSW-6124 ConstTensorsAsInput: Conv2d - FrontEnd

 * Update Front-end and Tools.
 * Updated Serializer, Deserializer and unit tests to reflect this.
 * Updated TfLiteDelegate, TfLiteParser and OnnxParser.
 * Updated Ref.
 * Fixed resulting Neon / CL tests
 * Unified optimizers for conv2d ops
 * Optimizer Fix - Fp32ToBf16
 * Partial implementation for ACL backends to fix VTS failures

!android-nn-driver:7477

Signed-off-by: Keith Davis <keith.davis@arm.com>
Change-Id: I5fb18877f7ee32643e15a9818945356274bb401b

1 files changed, 25 insertions, 0 deletions

diff --git a/src/armnn/BackendHelper.cpp b/src/armnn/BackendHelper.cpp
index 03f32ac191..9f97c26a75 100644
--- a/src/armnn/BackendHelper.cpp
+++ b/src/armnn/BackendHelper.cpp
@@ -373,6 +373,31 @@ bool LayerSupportHandle::IsConvolution2dSupported(const TensorInfo& input,
     TensorInfo biasesVal =  biases.has_value() ? biases.value() : TensorInfo();
     TensorInfos infos{input, output, weights, biasesVal};
 
+    Optional<const BackendOptions::BackendOption> capability ;
+    if(!m_BackendId.IsUndefined())
+    {
+        capability = GetCapability("ConstantTensorsAsInputs", m_BackendId);
+        if(!capability.has_value() || capability.value().GetValue().AsBool() == false)
+        {
+            if(!weights.IsConstant())
+            {
+                return false;
+            }
+            if (descriptor.m_BiasEnabled && !biases.has_value())
+            {
+                return false;
+            }
+
+
+            // At the first stage we will only print a warning. this is to give
+            // backend developers a chance to adopt and read weights from input slots.
+            ARMNN_LOG(warning) << "The backend makes use of a deprecated interface to read constant tensors. "
+                                  "If you are a backend developer please find more information in our "
+                                  "doxygen documentation on github https://github.com/ARM-software/armnn "
+                                  "under the keyword 'ConstTensorsAsInputs'.";
+        }
+    }
+
     return m_LayerSupport->IsLayerSupported(LayerType::Convolution2d,
                                             infos,
                                             descriptor,