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-rw-r--r--delegate/opaque/src/Unpack.hpp227
1 files changed, 227 insertions, 0 deletions
diff --git a/delegate/opaque/src/Unpack.hpp b/delegate/opaque/src/Unpack.hpp
index e16969768e..9b87bf7995 100644
--- a/delegate/opaque/src/Unpack.hpp
+++ b/delegate/opaque/src/Unpack.hpp
@@ -2,3 +2,230 @@
// Copyright © 2023 Arm Ltd and Contributors. All rights reserved.
// SPDX-License-Identifier: MIT
//
+
+#pragma once
+
+#include <OpaqueDelegateUtils.hpp>
+
+namespace armnnOpaqueDelegate
+{
+
+TfLiteStatus VisitUnpackOperator(DelegateData& delegateData,
+ TfLiteOpaqueContext* tfLiteContext,
+ TfLiteOpaqueNode* tfLiteNode,
+ int nodeIndex,
+ int32_t operatorCode)
+{
+ // Check inputs
+ TF_LITE_ENSURE_STATUS(ValidateNumInputs(tfLiteContext, tfLiteNode, 1, nodeIndex));
+
+ const int* inputTensors;
+ int numInputs;
+ if (TfLiteOpaqueNodeInputs(tfLiteNode, &inputTensors, &numInputs) != kTfLiteOk)
+ {
+ TF_LITE_OPAQUE_MAYBE_KERNEL_LOG(
+ tfLiteContext,
+ "TfLiteArmnnOpaqueDelegate: Unable to gather input tensor indices from node #%d: ",
+ nodeIndex);
+ return kTfLiteError;
+ }
+ const TfLiteOpaqueTensor* tfLiteInputTensor = TfLiteOpaqueContextGetOpaqueTensor(tfLiteContext,
+ inputTensors[0]);
+ if (!IsValid(tfLiteContext, tfLiteInputTensor, operatorCode, nodeIndex))
+ {
+ return kTfLiteError;
+ }
+
+ auto* tfLiteNodeParameters = reinterpret_cast<TfLiteUnpackParams*>(TfLiteOpaqueNodeGetBuiltinData(tfLiteNode));
+ const armnn::TensorInfo& inputTensorInfo = GetTensorInfoForTfLiteOpaqueTensor(tfLiteInputTensor);
+
+ // Get Unpack Axis
+ const unsigned int unpackAxis = NonNegative(tfLiteNodeParameters->axis, nodeIndex);
+
+ if (unpackAxis >= inputTensorInfo.GetNumDimensions())
+ {
+ TF_LITE_OPAQUE_MAYBE_KERNEL_LOG(
+ tfLiteContext,
+ "TfLiteArmnnOpaqueDelegate: 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(tfLiteNodeParameters->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_OPAQUE_MAYBE_KERNEL_LOG(
+ tfLiteContext,
+ "TfLiteArmnnOpaqueDelegate: 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_OPAQUE_MAYBE_KERNEL_LOG(
+ tfLiteContext,
+ "TfLiteArmnnOpaqueDelegate: 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);
+ }
+
+ // Gather output indices and use to get output tensors.
+ const int* outputTensors;
+ int numOutputs;
+ if (TfLiteOpaqueNodeOutputs(tfLiteNode, &outputTensors, &numOutputs) != kTfLiteOk)
+ {
+ TF_LITE_OPAQUE_MAYBE_KERNEL_LOG(
+ tfLiteContext,
+ "TfLiteArmnnOpaqueDelegate: Unable to gather output tensor indices from node #%d: ",
+ nodeIndex);
+ return kTfLiteError;
+ }
+
+ // Validate all outputs and get TensorInfo
+ std::vector<armnn::TensorInfo> outputs;
+ for (unsigned int i = 0; i < unpackNum; ++i)
+ {
+ const TfLiteOpaqueTensor* tfLiteOutputTensor = TfLiteOpaqueContextGetOpaqueTensor(tfLiteContext,
+ outputTensors[i]);
+ if (!IsValid(tfLiteContext, tfLiteOutputTensor, operatorCode, nodeIndex))
+ {
+ return kTfLiteError;
+ }
+
+ outputs.push_back(GetTensorInfoForTfLiteOpaqueTensor(tfLiteOutputTensor, true));
+ }
+
+ const std::vector<std::reference_wrapper<armnn::TensorInfo>> outputTensorInfos(outputs.begin(), outputs.end());
+
+ // Determine the shape of the Splitter layer outputs for validation
+ armnn::TensorShape splitOutShape = armnn::TensorShape(static_cast<unsigned int>(unpackDimSizes.size()),
+ unpackDimSizes.data());
+
+ std::vector<armnn::TensorInfo> splitterOutputs;
+ for (unsigned int outputIndex = 0; outputIndex < outputTensorInfos.size(); ++outputIndex)
+ {
+ splitterOutputs.push_back(armnn::TensorInfo(splitOutShape,
+ outputTensorInfos[outputIndex].get().GetDataType(),
+ outputTensorInfos[outputIndex].get().GetQuantizationScale(),
+ outputTensorInfos[outputIndex].get().GetQuantizationOffset()));
+ }
+ std::vector<std::reference_wrapper<armnn::TensorInfo>> splitterOutputTensorInfos(splitterOutputs.begin(),
+ splitterOutputs.end());
+
+ armnn::BackendId setBackendSplit;
+ if (!delegateData.m_Network)
+ {
+ // Check if splitter is supported
+ bool isSupported = false;
+ FORWARD_LAYER_OPAQUE_SUPPORT_FUNC("UNPACK",
+ tfLiteContext,
+ IsSplitterSupported,
+ delegateData.m_Backends,
+ isSupported,
+ setBackendSplit,
+ inputTensorInfo,
+ splitterOutputTensorInfos,
+ splitDesc);
+ return isSupported ? kTfLiteOk : kTfLiteError;
+ }
+
+ // Create Reshape descriptor from the first outputTensorInfo to validate a single Reshape layer
+ // Use this descriptor later when creating every ReshapeLayer as all Reshape Layers should be the same
+ armnn::ReshapeDescriptor reshapeDescriptor;
+ reshapeDescriptor.m_TargetShape = outputTensorInfos[0].get().GetShape();
+
+ armnn::BackendId setBackendReshape;
+ if (!delegateData.m_Network)
+ {
+ bool isSupported = false;
+ FORWARD_LAYER_OPAQUE_SUPPORT_FUNC("RESHAPE",
+ tfLiteContext,
+ IsReshapeSupported,
+ delegateData.m_Backends,
+ isSupported,
+ setBackendReshape,
+ splitterOutputTensorInfos[0],
+ outputTensorInfos[0],
+ reshapeDescriptor);
+ return isSupported ? kTfLiteOk : kTfLiteError;
+ };
+
+ std::string splitterLayerName("Unpack Splitter");
+
+ armnn::IConnectableLayer* splitterLayer = delegateData.m_Network->AddSplitterLayer(splitDesc,
+ splitterLayerName.c_str());
+ splitterLayer->SetBackendId(setBackendSplit);
+ ARMNN_ASSERT(splitterLayer != nullptr);
+
+ for (unsigned int k = 0; k < splitterLayer->GetNumOutputSlots(); ++k)
+ {
+ splitterLayer->GetOutputSlot(k).SetTensorInfo(outputs[k]);
+ }
+
+ // Connect the input slots
+ auto inputIndex = static_cast<unsigned int>(inputTensors[0]);
+ delegateData.m_OutputSlotForNode[inputIndex]->Connect(splitterLayer->GetInputSlot(0));
+
+ // Create reshape to remove the unpacked dimension for unpack operator of each output from Splitter.
+ for (unsigned int outputIndex = 0; outputIndex < splitterLayer->GetNumOutputSlots(); ++outputIndex)
+ {
+ std::string reshapeLayerName("Unpack Reshape");
+ armnn::IConnectableLayer* reshapeLayer = delegateData.m_Network->AddReshapeLayer(reshapeDescriptor,
+ reshapeLayerName.c_str());
+ reshapeLayer->SetBackendId(setBackendReshape);
+ ARMNN_ASSERT(reshapeLayer != nullptr);
+
+ splitterLayer->GetOutputSlot(outputIndex).SetTensorInfo(splitterOutputTensorInfos[outputIndex]);
+ splitterLayer->GetOutputSlot(outputIndex).Connect(reshapeLayer->GetInputSlot(0));
+
+ armnn::TensorInfo outputTensorInfo = outputTensorInfos[outputIndex];
+ reshapeLayer->GetOutputSlot(0).SetTensorInfo(outputTensorInfo);
+
+ armnn::IOutputSlot& slot = reshapeLayer->GetOutputSlot(0);
+
+ delegateData.m_OutputSlotForNode[
+ static_cast<unsigned long>(static_cast<unsigned int>(outputTensors[outputIndex]))] = &slot;
+
+ }
+
+ return kTfLiteOk;
+}
+
+} // namespace armnnOpaqueDelegate \ No newline at end of file
generated by cgit v1.2.1 (git 2.23.0) at 2024-06-01 01:41:30 +0000