1 files changed, 110 insertions, 0 deletions
diff --git a/delegate/classic/src/Transpose.hpp b/delegate/classic/src/Transpose.hpp
new file mode 100644
index 0000000000..41178d0b59
--- /dev/null
+++ b/delegate/classic/src/Transpose.hpp
@@ -0,0 +1,110 @@
+//
+// Copyright © 2022-2023 Arm Ltd and Contributors. All rights reserved.
+// SPDX-License-Identifier: MIT
+//
+
+#pragma once
+
+#include <armnn/utility/IgnoreUnused.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 <tensorflow/lite/kernels/internal/tensor_ctypes.h>
+
+namespace armnnDelegate
+{
+
+TfLiteStatus VisitTransposeOperator(DelegateData& delegateData,
+                                    TfLiteContext* tfLiteContext,
+                                    TfLiteNode* tfLiteNode,
+                                    int nodeIndex,
+                                    int32_t tfliteTransposeOperatorCode)
+{
+    TF_LITE_ENSURE_STATUS(ValidateNumInputs(tfLiteContext, tfLiteNode, 2, nodeIndex));
+    TF_LITE_ENSURE_STATUS(ValidateNumOutputs(tfLiteContext, tfLiteNode, 1, nodeIndex));
+
+    const TfLiteTensor *tfLiteTensors = tfLiteContext->tensors;
+    const TfLiteTensor& tfLiteInputTensor0 = tfLiteTensors[tfLiteNode->inputs->data[0]];
+    if (IsDynamicTensor(tfLiteInputTensor0))
+    {
+        TF_LITE_MAYBE_KERNEL_LOG(tfLiteContext,
+                                 "TfLiteArmnnDelegate: Dynamic input tensors are not supported in "
+                                 "operator #%d node #%d: ",
+                                 tfliteTransposeOperatorCode, nodeIndex);
+
+        return kTfLiteError;
+    }
+
+    const TfLiteTensor& tfLiteInputTensor1 = tfLiteTensors[tfLiteNode->inputs->data[1]];
+    if (IsDynamicTensor(tfLiteInputTensor1))
+    {
+        TF_LITE_MAYBE_KERNEL_LOG(tfLiteContext,
+                                 "TfLiteArmnnDelegate: Dynamic input tensors are not supported in "
+                                 "operator #%d node #%d: ",
+                                 tfliteTransposeOperatorCode, nodeIndex);
+        return kTfLiteError;
+    }
+
+    const TfLiteTensor& tfLiteOutputTensor = tfLiteTensors[tfLiteNode->outputs->data[0]];
+    if (IsDynamicTensor(tfLiteOutputTensor))
+    {
+        TF_LITE_MAYBE_KERNEL_LOG(tfLiteContext,
+                                 "TfLiteArmnnDelegate: Dynamic output tensors are not supported in "
+                                 "operator #%d node #%d: ",
+                                 tfliteTransposeOperatorCode, nodeIndex);
+        return kTfLiteError;
+    }
+
+    const armnn::TensorInfo& inputTensorInfo0 = GetTensorInfoForTfLiteTensor(tfLiteInputTensor0);
+    const armnn::TensorInfo& outputTensorInfo = GetTensorInfoForTfLiteTensor(tfLiteOutputTensor, true);
+
+    auto* permTensorDataPtr = tflite::GetTensorData<int32_t>(&tfLiteInputTensor1);
+    unsigned int numEl = tfLiteInputTensor1.dims->data[0];
+
+    ARMNN_ASSERT( numEl <= static_cast<int>(armnn::MaxNumOfTensorDimensions));
+    ARMNN_ASSERT( tfLiteInputTensor1.dims->size == 1); // ensure only single dimension to the permutation tensor
+
+    armnn::TransposeDescriptor descriptor(armnn::PermutationVector(
+        reinterpret_cast<const armnn::PermutationVector::ValueType *> (permTensorDataPtr),
+        static_cast<armnn::PermutationVector::SizeType>(numEl)));
+
+    bool isSupported = false;
+    armnn::BackendId setBackend;
+    auto validateFunc = [&](const armnn::TensorInfo& outputTensorInfo, bool& isSupported)
+    {
+        FORWARD_LAYER_SUPPORT_FUNC("TRANSPOSE",
+                                   tfLiteContext,
+                                   IsTransposeSupported,
+                                   delegateData.m_Backends,
+                                   isSupported,
+                                   setBackend,
+                                   inputTensorInfo0,
+                                   outputTensorInfo,
+                                   descriptor);
+    };
+
+    if (!delegateData.m_Network)
+    {
+        validateFunc(outputTensorInfo, isSupported);
+        return isSupported ? kTfLiteOk : kTfLiteError;
+    }
+
+    armnn::IConnectableLayer* transposeLayer = delegateData.m_Network->AddTransposeLayer(descriptor);
+    transposeLayer->SetBackendId(setBackend);
+    ARMNN_ASSERT(transposeLayer != nullptr);
+    ARMNN_ASSERT(transposeLayer->GetNumInputSlots() == 1);     // permutation vector given to descriptor object
+
+    armnn::IOutputSlot& outputSlot = transposeLayer->GetOutputSlot(0);
+    outputSlot.SetTensorInfo(outputTensorInfo);
+
+    // try to connect the Constant Inputs if there are any
+    if(ProcessInputs(transposeLayer,delegateData, tfLiteContext, tfLiteNode) != kTfLiteOk )
+    {
+        return kTfLiteError;
+    }
+
+    return Connect(transposeLayer, tfLiteNode, delegateData);
+}
+} // namespace armnnDelegate