From 0bd4c6230974e7e446cd26104180d520b643d5bb Mon Sep 17 00:00:00 2001
From: Matthew Sloyan <matthew.sloyan@arm.com>
Date: Thu, 27 Apr 2023 11:48:26 +0100
Subject: IVGCVSW-7574 IVGCVSW-7590 IVGCVSW-7600 Implement Activation,
 FullyConnected and Prelu operators for Opaque Delegate

 * Added missing headers to opaque/CMakeLists.txt (Control and Comparison)
 * Cleaned up Control.hpp headers.

Signed-off-by: Matthew Sloyan <matthew.sloyan@arm.com>
Change-Id: I442edb9c467b515b130fbaf02879f0802006255f
---
 delegate/opaque/src/Activation.hpp | 147 +++++++++++++++++++++++++++++++++++++
 1 file changed, 147 insertions(+)

(limited to 'delegate/opaque/src/Activation.hpp')

diff --git a/delegate/opaque/src/Activation.hpp b/delegate/opaque/src/Activation.hpp
index e16969768e..a45bba95a9 100644
--- a/delegate/opaque/src/Activation.hpp
+++ b/delegate/opaque/src/Activation.hpp
@@ -2,3 +2,150 @@
 // Copyright © 2023 Arm Ltd and Contributors. All rights reserved.
 // SPDX-License-Identifier: MIT
 //
+
+#pragma once
+
+#include <OpaqueDelegateUtils.hpp>
+
+namespace armnnOpaqueDelegate
+{
+
+TfLiteStatus ValidateActivationOperator(DelegateData& delegateData,
+                                        TfLiteOpaqueContext* tfLiteContext,
+                                        const armnn::TensorInfo& inputInfo,
+                                        const armnn::TensorInfo& outputInfo,
+                                        armnn::ActivationDescriptor& activationDesc)
+{
+    bool isSupported = false;
+    auto validateFunc = [&](const armnn::TensorInfo& outputInfo, bool& isSupported)
+    {
+        FORWARD_LAYER_OPAQUE_SUPPORT_FUNC("ACTIVATION",
+                                          tfLiteContext,
+                                          IsActivationSupported,
+                                          delegateData.m_Backends,
+                                          isSupported,
+                                          armnn::BackendId(),
+                                          inputInfo,
+                                          outputInfo,
+                                          activationDesc);
+    };
+
+    validateFunc(outputInfo, isSupported);
+    return isSupported ? kTfLiteOk : kTfLiteError;
+}
+
+TfLiteStatus VisitActivationOperator(DelegateData& delegateData,
+                                     TfLiteOpaqueContext* tfLiteContext,
+                                     TfLiteOpaqueNode* tfLiteNode,
+                                     int nodeIndex,
+                                     int32_t operatorCode)
+{
+    TF_LITE_ENSURE_STATUS(ValidateNumInputs(tfLiteContext, tfLiteNode, 1, nodeIndex));
+    TF_LITE_ENSURE_STATUS(ValidateNumOutputs(tfLiteContext, tfLiteNode, 1, nodeIndex));
+
+    // Gather input indices and use to get input tensor.
+    int numInputs = 0;
+    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;
+    }
+
+    const TfLiteOpaqueTensor* tfLiteInputTensor = TfLiteOpaqueContextGetOpaqueTensor(tfLiteContext, inputTensors[0]);
+    if (!IsValid(tfLiteContext, tfLiteInputTensor, operatorCode, nodeIndex))
+    {
+        return kTfLiteError;
+    }
+
+    // Gather output indices and use to get 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;
+    }
+
+    const TfLiteOpaqueTensor* tfLiteOutputTensor = TfLiteOpaqueContextGetOpaqueTensor(tfLiteContext, outputTensors[0]);
+    if (!IsValid(tfLiteContext, tfLiteOutputTensor, operatorCode, nodeIndex))
+    {
+        return kTfLiteError;
+    }
+
+    const armnn::TensorInfo& inputTensorInfo  = GetTensorInfoForTfLiteOpaqueTensor(tfLiteInputTensor);
+    const armnn::TensorInfo& outputTensorInfo = GetTensorInfoForTfLiteOpaqueTensor(tfLiteOutputTensor, true);
+
+    armnn::ActivationDescriptor activationDesc;
+    switch(operatorCode)
+    {
+        case kTfLiteBuiltinRelu:
+        {
+            activationDesc.m_Function = armnn::ActivationFunction::ReLu;
+            break;
+        }
+        case kTfLiteBuiltinRelu6:
+        {
+            activationDesc.m_Function = armnn::ActivationFunction::BoundedReLu;
+            activationDesc.m_A = 6.0f;
+            break;
+        }
+        case kTfLiteBuiltinLogistic:
+        {
+            activationDesc.m_Function = armnn::ActivationFunction::Sigmoid;
+            break;
+        }
+        case kTfLiteBuiltinTanh:
+        {
+            activationDesc.m_Function = armnn::ActivationFunction::TanH;
+            activationDesc.m_A = 1.0f;
+            activationDesc.m_B = 1.0f;
+            break;
+        }
+        case kTfLiteBuiltinElu:
+        {
+            activationDesc.m_Function = armnn::ActivationFunction::Elu;
+            activationDesc.m_A = 1.0f;
+            break;
+        }
+        case kTfLiteBuiltinHardSwish:
+        {
+            activationDesc.m_Function = armnn::ActivationFunction::HardSwish;
+            break;
+        }
+        default:
+        {
+            return kTfLiteError;
+        }
+    }
+    if (!delegateData.m_Network)
+    {
+        return ValidateActivationOperator(delegateData,
+                                          tfLiteContext,
+                                          inputTensorInfo,
+                                          outputTensorInfo,
+                                          activationDesc);
+    }
+    armnn::IConnectableLayer* activationLayer = delegateData.m_Network->AddActivationLayer(activationDesc);
+    ARMNN_ASSERT(activationLayer != nullptr);
+
+    armnn::IOutputSlot& outputSlot = activationLayer->GetOutputSlot(0);
+    outputSlot.SetTensorInfo(outputTensorInfo);
+
+    // try to connect the Constant Inputs if there are any
+    if(ProcessInputs(activationLayer,delegateData, tfLiteContext, tfLiteNode) != kTfLiteOk )
+    {
+        return kTfLiteError;
+    }
+
+    // Connect
+    return Connect(activationLayer, tfLiteContext, tfLiteNode, delegateData);
+}
+
+} // namespace armnnDelegate
-- 
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