IVGCVSW-5970 TfLiteDelegate: Add UNPACK operator Support
Signed-off-by: Kevin May <kevin.may@arm.com>
Change-Id: I23731718236043b46c143eaf416cb375edd93983
diff --git a/delegate/src/Unpack.hpp b/delegate/src/Unpack.hpp
new file mode 100644
index 0000000..87200ff
--- /dev/null
+++ b/delegate/src/Unpack.hpp
@@ -0,0 +1,184 @@
+//
+// Copyright © 2021 Arm Ltd and Contributors. All rights reserved.
+// SPDX-License-Identifier: MIT
+//
+
+#pragma once
+
+#include <armnn/utility/IgnoreUnused.hpp>
+
+#include "DelegateUtils.hpp"
+
+#include <tensorflow/lite/builtin_ops.h>
+#include <tensorflow/lite/c/builtin_op_data.h>
+#include <tensorflow/lite/c/common.h>
+#include <tensorflow/lite/minimal_logging.h>
+#include <numeric>
+
+namespace armnnDelegate
+{
+
+TfLiteStatus VisitUnpackOperator(DelegateData& delegateData,
+ TfLiteContext* tfLiteContext,
+ TfLiteNode* tfLiteNode,
+ int nodeIndex,
+ int32_t operatorCode)
+{
+ TF_LITE_ENSURE_STATUS(ValidateNumInputs(tfLiteContext, tfLiteNode, 1, nodeIndex));
+
+ const TfLiteTensor* tfLiteTensors = tfLiteContext->tensors;
+ const TfLiteTensor& tfLiteInputTensor = tfLiteTensors[tfLiteNode->inputs->data[0]];
+
+ if (!IsValid(tfLiteContext, tfLiteInputTensor, operatorCode, nodeIndex))
+ {
+ return kTfLiteError;
+ }
+
+ // Get Unpack Axis
+ const auto params = reinterpret_cast<TfLiteUnpackParams*>(tfLiteNode->builtin_data);
+
+ const unsigned int unpackAxis = NonNegative(params->axis, nodeIndex);
+
+ const armnn::TensorInfo& inputTensorInfo = GetTensorInfoForTfLiteTensor(tfLiteInputTensor);
+
+ if (unpackAxis >= inputTensorInfo.GetNumDimensions())
+ {
+ TF_LITE_MAYBE_KERNEL_LOG(
+ tfLiteContext,
+ "TfLiteArmnnDelegate: The unpack axis #%d cannot be greater than or equal to "
+ "the number of input dimensions #%d in operator #%d node #%d",
+ unpackAxis, inputTensorInfo.GetNumDimensions(), operatorCode, nodeIndex);
+ return kTfLiteError;
+ }
+
+ // Get Unpack Num
+ unsigned int unpackNum = NonNegative(params->num, nodeIndex);
+
+ // If num is not defined, automatically infer from the length of the dimension axis.
+ if(unpackNum == 0)
+ {
+ unpackNum = inputTensorInfo.GetShape()[unpackAxis];
+ }
+
+ // If unpack number cannot be inferred and is still zero, return kTfLiteError.
+ if(unpackNum == 0)
+ {
+ TF_LITE_MAYBE_KERNEL_LOG(
+ tfLiteContext,
+ "TfLiteArmnnDelegate: Number to unpack must greater than zero in operator #%d node #%d: ",
+ operatorCode, nodeIndex);
+ return kTfLiteError;
+ }
+
+ // Check outputs
+ TF_LITE_ENSURE_STATUS(ValidateNumOutputs(tfLiteContext, tfLiteNode, unpackNum, nodeIndex));
+
+
+ auto inputDimSize = inputTensorInfo.GetNumDimensions();
+ std::vector<unsigned int> unpackDimSizes(inputDimSize);
+
+ // Add current input shape to unpackDimSizes
+ for (unsigned int i = 0; i < inputDimSize; ++i)
+ {
+ unpackDimSizes[i] = inputTensorInfo.GetShape()[i];
+ }
+
+ if (unpackDimSizes[unpackAxis] != unpackNum)
+ {
+ TF_LITE_MAYBE_KERNEL_LOG(
+ tfLiteContext,
+ "TfLiteArmnnDelegate: Number to unpack must be the same as length "
+ "of the dimension to unpack along in operator #%d node #%d: ",
+ operatorCode, nodeIndex);
+ return kTfLiteError;
+ }
+
+ unpackDimSizes[unpackAxis] /= unpackNum;
+
+ armnn::SplitterDescriptor splitDesc(unpackNum, static_cast<unsigned int>(unpackDimSizes.size()));
+ for (unsigned int j = 0; j < unpackNum; ++j)
+ {
+ // Set the size of the views.
+ for (unsigned int dimIdx = 0; dimIdx < unpackDimSizes.size(); ++dimIdx)
+ {
+ splitDesc.SetViewSize(j, dimIdx, unpackDimSizes[dimIdx]);
+ }
+ splitDesc.SetViewOriginCoord(j, unpackAxis, unpackDimSizes[unpackAxis] * j);
+ }
+
+ std::vector<armnn::TensorInfo> outputs;
+ for (unsigned int i = 0; i < unpackNum; ++i)
+ {
+ const TfLiteTensor& tfLiteOutputTensor = tfLiteTensors[tfLiteNode->outputs->data[i]];
+ if (!IsValid(tfLiteContext, tfLiteOutputTensor, operatorCode, nodeIndex))
+ {
+ return kTfLiteError;
+ }
+ outputs.push_back(GetTensorInfoForTfLiteTensor(tfLiteOutputTensor));
+ }
+ const std::vector<std::reference_wrapper<armnn::TensorInfo>> outputTensorInfos(outputs.begin(), outputs.end());
+
+ if (!delegateData.m_Network)
+ {
+ // Check if supported
+ bool isSupported = false;
+ FORWARD_LAYER_SUPPORT_FUNC(__func__,
+ tfLiteContext,
+ IsSplitterSupported,
+ delegateData.m_Backends,
+ isSupported,
+ inputTensorInfo,
+ outputTensorInfos,
+ splitDesc);
+ return isSupported ? kTfLiteOk : kTfLiteError;
+ }
+
+ std::string splitterLayerName("Unpack Splitter");
+
+ armnn::IConnectableLayer* splitterLayer = delegateData.m_Network->AddSplitterLayer(splitDesc,
+ splitterLayerName.c_str());
+ ARMNN_ASSERT(splitterLayer != nullptr);
+
+ for (unsigned int k = 0; k < splitterLayer->GetNumOutputSlots(); ++k)
+ {
+ splitterLayer->GetOutputSlot(k).SetTensorInfo(outputs[k]);
+ }
+
+ // Connect the input slots
+ delegateData.m_OutputSlotForNode[tfLiteNode->inputs->data[0]]->Connect(splitterLayer->GetInputSlot(0));
+
+ armnn::TensorShape splitOutShape = armnn::TensorShape(static_cast<unsigned int>(unpackDimSizes.size()),
+ unpackDimSizes.data());
+
+ // Create reshape to remove the unpacked dimension for unpack operator of each output from Splitter.
+ for (unsigned int outputIndex = 0; outputIndex < splitterLayer->GetNumOutputSlots(); ++outputIndex)
+ {
+ armnn::TensorInfo outputTensorInfo = outputTensorInfos[outputIndex];
+
+ std::string reshapeLayerName("Unpack Reshape");
+ armnn::ReshapeDescriptor reshapeDescriptor;
+ reshapeDescriptor.m_TargetShape = outputTensorInfo.GetShape();
+ armnn::IConnectableLayer* reshapeLayer = delegateData.m_Network->AddReshapeLayer(reshapeDescriptor,
+ reshapeLayerName.c_str());
+
+ ARMNN_ASSERT(reshapeLayer != nullptr);
+
+ splitterLayer->GetOutputSlot(outputIndex).SetTensorInfo(armnn::TensorInfo(splitOutShape,
+ outputTensorInfo.GetDataType(),
+ outputTensorInfo.GetQuantizationScale(),
+ outputTensorInfo.GetQuantizationOffset()));
+ splitterLayer->GetOutputSlot(outputIndex).Connect(reshapeLayer->GetInputSlot(0));
+
+ reshapeLayer->GetOutputSlot(0).SetTensorInfo(outputTensorInfo);
+
+ armnn::IOutputSlot& slot = reshapeLayer->GetOutputSlot(0);
+
+ delegateData.m_OutputSlotForNode[
+ static_cast<unsigned long>(tfLiteNode->outputs->data[outputIndex])] = &slot;
+
+ }
+
+ return kTfLiteOk;
+}
+
+} // namespace armnnDelegate