IVGCVSW-7886 Add TILE to delegate and opaque delegate
* Adding support for Tile in classic and opaque delegates
* CMake files updated
* Tests added
Signed-off-by: Tianle Cheng <tianle.cheng@arm.com>
Change-Id: I9b52cea3480eb71961cbccb1a346805f73b5661a
diff --git a/delegate/opaque/src/Tile.hpp b/delegate/opaque/src/Tile.hpp
new file mode 100644
index 0000000..17cbdee
--- /dev/null
+++ b/delegate/opaque/src/Tile.hpp
@@ -0,0 +1,188 @@
+//
+// Copyright © 2023 Arm Ltd and Contributors. All rights reserved.
+// SPDX-License-Identifier: MIT
+//
+
+#pragma once
+
+#include <OpaqueDelegateUtils.hpp>
+
+namespace armnnOpaqueDelegate
+{
+TfLiteStatus ValidateTileOperator(DelegateData& delegateData,
+ TfLiteOpaqueContext *tfLiteContext,
+ const armnn::TensorInfo& inputInfo,
+ const armnn::TensorInfo& outputInfo,
+ const armnn::TileDescriptor& descriptor)
+{
+ bool isSupported = false;
+ FORWARD_LAYER_OPAQUE_SUPPORT_FUNC("TILE",
+ tfLiteContext,
+ IsTileSupported,
+ delegateData.m_Backends,
+ isSupported,
+ armnn::BackendId(),
+ inputInfo,
+ outputInfo,
+ descriptor);
+ return isSupported ? kTfLiteOk : kTfLiteError;
+}
+
+TfLiteStatus VisitTileOperator(DelegateData& delegateData,
+ TfLiteOpaqueContext* tfLiteContext,
+ TfLiteOpaqueNode* tfLiteNode,
+ int nodeIndex,
+ int32_t tileOperatorCode)
+{
+ TF_LITE_ENSURE_STATUS(ValidateNumInputs(tfLiteContext, tfLiteNode, 2, nodeIndex));
+ TF_LITE_ENSURE_STATUS(ValidateNumOutputs(tfLiteContext, tfLiteNode, 1, nodeIndex));
+
+ // Gather input tensors
+ auto numInputs = TfLiteOpaqueNodeNumberOfInputs(tfLiteNode);
+ const int* inputTensors;
+ 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;
+ }
+
+ // Gather output tensors
+ int numOutputs = 0;
+ const int* outputTensors;
+ 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;
+ }
+
+ // The input contains the data that should be tiled
+ const TfLiteOpaqueTensor* tfLiteInputTensor =
+ TfLiteOpaqueContextGetOpaqueTensor(tfLiteContext, inputTensors[0]);
+ if (IsDynamicTensor(tfLiteInputTensor))
+ {
+ TF_LITE_OPAQUE_MAYBE_KERNEL_LOG(
+ tfLiteContext,
+ "TfLiteArmnnOpaqueDelegate: Dynamic input tensors are not supported in operator #%d node #%d: ",
+ tileOperatorCode, nodeIndex);
+ return kTfLiteError;
+ }
+
+ // The multiples tensor contains the number of copies for each axis
+ const TfLiteOpaqueTensor* tfLiteMultiplesTensor =
+ TfLiteOpaqueContextGetOpaqueTensor(tfLiteContext, inputTensors[1]);;
+ if (IsDynamicTensor(tfLiteMultiplesTensor))
+ {
+ TF_LITE_OPAQUE_MAYBE_KERNEL_LOG(
+ tfLiteContext,
+ "TfLiteArmnnOpaqueDelegate: Dynamic input tensors are not supported in operator #%d node #%d: ",
+ tileOperatorCode, nodeIndex);
+ return kTfLiteError;
+ }
+
+ // The output tensor
+ const TfLiteOpaqueTensor* tfLiteOutputTensor =
+ TfLiteOpaqueContextGetOpaqueTensor(tfLiteContext, outputTensors[0]);
+ if (IsDynamicTensor(tfLiteOutputTensor))
+ {
+ TF_LITE_OPAQUE_MAYBE_KERNEL_LOG(
+ tfLiteContext,
+ "TfLiteArmnnOpaqueDelegate: Dynamic output tensors are not supported in operator #%d node #%d: ",
+ tileOperatorCode, nodeIndex);
+ return kTfLiteError;
+ }
+
+ const armnn::TensorInfo& inputTensorInfo = GetTensorInfoForTfLiteOpaqueTensor(tfLiteInputTensor);
+ const armnn::TensorInfo& multiplesTensorInfo = GetTensorInfoForTfLiteOpaqueTensor(tfLiteMultiplesTensor);
+ const armnn::TensorInfo& outputTensorInfo = GetTensorInfoForTfLiteOpaqueTensor(tfLiteOutputTensor, true);
+
+ // Multiples length must be the same as the number of dimension in input tensor
+ if (multiplesTensorInfo.GetNumElements() != inputTensorInfo.GetNumDimensions())
+ {
+ TF_LITE_OPAQUE_MAYBE_KERNEL_LOG(
+ tfLiteContext,
+ "TfLiteArmnnOpaqueDelegate:",
+ "The Multiples length must be the same as the number of dimension in input tensor",
+ "Operator: #%d node #%d: ",
+ tileOperatorCode, nodeIndex);
+ return kTfLiteError;
+ }
+
+ // Get the Multiples data: In armnn, the values of the multiples input tensor is saved in the operator descriptor
+ // We have to read it from the input tensor and write it the descriptor
+ auto* multiplesTensorDataPtr = static_cast<int32_t*>(TfLiteOpaqueTensorData(tfLiteMultiplesTensor));
+ auto multiplesTensorNum = TfLiteOpaqueTensorDim(tfLiteMultiplesTensor, 0);
+ std::vector<int32_t> multiplesIntData(multiplesTensorDataPtr, multiplesTensorDataPtr + multiplesTensorNum);
+
+ // The multiples must be positive
+ for (auto multiple : multiplesIntData)
+ {
+ if (multiple < 0)
+ {
+ TF_LITE_OPAQUE_MAYBE_KERNEL_LOG(
+ tfLiteContext,
+ "TfLiteArmnnOpaqueDelegate: The Multiples must be positive values",
+ "Operator: #%d node #%d: ",
+ tileOperatorCode, nodeIndex);
+ return kTfLiteError;
+ }
+ }
+
+ // The original input from TFLite is int32, and we have to make it as uint32 for our descriptor
+ std::vector<uint32_t> multiplesUintData;
+ std::transform(multiplesIntData.begin(),
+ multiplesIntData.end(),
+ std::back_inserter(multiplesUintData),
+ [] (const int value)
+ {
+ return static_cast<uint32_t>(value);
+ });
+
+ armnn::TileDescriptor tileDescriptor;
+ tileDescriptor.m_Multiples = multiplesUintData;
+
+ // Check output dimensions
+ if (inputTensorInfo.GetNumDimensions() != outputTensorInfo.GetNumDimensions())
+ {
+ TF_LITE_OPAQUE_MAYBE_KERNEL_LOG(
+ tfLiteContext,
+ "TfLiteArmnnOpaqueDelegate: Input tensor dimension and output tensor dimension differ",
+ "Operator: #%d node #%d: ",
+ tileOperatorCode, nodeIndex);
+ return kTfLiteError;
+ }
+
+ // No network pointer indicates that only support for this operator should be checked
+ if (!delegateData.m_Network)
+ {
+ return ValidateTileOperator(delegateData,
+ tfLiteContext,
+ inputTensorInfo,
+ outputTensorInfo,
+ tileDescriptor);
+ }
+
+ std::string layerName("Tile");
+ armnn::IConnectableLayer* layer = delegateData.m_Network->AddTileLayer(tileDescriptor, layerName.c_str());
+
+ if (layer == nullptr)
+ {
+ return kTfLiteError;
+ }
+
+ layer->GetOutputSlot(0).SetTensorInfo(outputTensorInfo);
+
+ if (ProcessInputs(layer, delegateData, tfLiteContext, tfLiteNode) != kTfLiteOk)
+ {
+ return kTfLiteError;
+ }
+
+ return Connect(layer, tfLiteContext, tfLiteNode, delegateData);
+}
+
+} // namespace armnnOpaqueDelegate
\ No newline at end of file