IVGCVSW-4623 Add android-nn-driver Support for FILL
* Added FILL operator support to HAL 1.3 Driver
!armnn:3447
Signed-off-by: Sadik Armagan <sadik.armagan@arm.com>
Change-Id: I271151857d805e8159b9dd675bd6e9e99e6ff69d
diff --git a/ConversionUtils_1_3.hpp b/ConversionUtils_1_3.hpp
index dada670..3acb49a 100644
--- a/ConversionUtils_1_3.hpp
+++ b/ConversionUtils_1_3.hpp
@@ -66,6 +66,92 @@
}
template<typename HalPolicy,
+ typename HalOperation = typename HalPolicy::Operation,
+ typename HalModel = typename HalPolicy::Model>
+bool ConvertFill(const HalOperation& operation, const HalModel& model, ConversionData& data)
+{
+ using HalOperand = typename HalPolicy::Operand;
+ using HalOperandType = typename HalPolicy::OperandType;
+
+ LayerInputHandle input = ConvertToLayerInputHandle<HalPolicy>(operation, 0, model, data);
+ if (!input.IsValid())
+ {
+ return Fail("%s: Operation has invalid inputs", __func__);
+ }
+
+ const HalOperand* output = GetOutputOperand<HalPolicy>(operation, 0, model);
+ if (!output)
+ {
+ return Fail("%s: Could not read output", __func__);
+ }
+
+ const TensorInfo& inputInfo = input.GetTensorInfo();
+ const TensorInfo& outputInfo = GetTensorInfoForOperand(*output);
+ if (IsDynamicTensor(outputInfo))
+ {
+ return Fail("%s: Dynamic output tensors are not supported", __func__);
+ }
+
+ // Determine data type of output tensor
+ HalOperandType outputType = output->type;
+ FillDescriptor descriptor;
+ // Read the scalar fill value
+ if (outputType == HalOperandType::TENSOR_FLOAT16)
+ {
+ Half value;
+
+ if (!GetInputScalar<HalPolicy>(operation, 1, HalOperandType::FLOAT16, value, model, data))
+ {
+ return Fail("%s: Operation has invalid inputs %d", __func__, outputType);
+ }
+
+ descriptor.m_Value = static_cast<float>(value);
+ }
+ else if (outputType == HalOperandType::TENSOR_FLOAT32)
+ {
+ if (!GetInputScalar<HalPolicy>(operation, 1, HalOperandType::FLOAT32, descriptor.m_Value, model, data))
+ {
+ return Fail("%s: Operation has invalid inputs %d", __func__, outputType);
+ }
+ }
+ else if (outputType == HalOperandType::TENSOR_INT32)
+ {
+ int32_t value;
+
+ if (!GetInputScalar<HalPolicy>(operation, 1, HalOperandType::INT32, value, model, data))
+ {
+ return Fail("%s: Operation has invalid inputs %d", __func__, outputType);
+ }
+
+ descriptor.m_Value = static_cast<float>(value);
+ }
+ else
+ {
+ return Fail("%s: Unsupported input tensor type: %d", __func__, outputType);
+ }
+
+ bool isSupported = false;
+ FORWARD_LAYER_SUPPORT_FUNC(__func__,
+ IsFillSupported,
+ data.m_Backends,
+ isSupported,
+ inputInfo,
+ outputInfo,
+ descriptor);
+ if (!isSupported)
+ {
+ return false;
+ }
+
+ IConnectableLayer* const layer = data.m_Network->AddFillLayer(descriptor);
+ assert(layer != nullptr);
+ input.Connect(layer->GetInputSlot(0));
+ layer->GetOutputSlot(0).SetTensorInfo(outputInfo);
+
+ return SetupAndTrackLayerOutputSlot<HalPolicy>(operation, 0, *layer, model, data);
+}
+
+template<typename HalPolicy,
typename HalOperation = typename HalPolicy::Operation,
typename HalModel = typename HalPolicy::Model>
bool ConvertQuantizedLstm(const HalOperation& operation, const HalModel& model, ConversionData& data)