From f87b90e4dbb906436cf205a2a19e199bfe9224ed Mon Sep 17 00:00:00 2001
From: Cathal Corbett <cathal.corbett@arm.com>
Date: Tue, 22 Feb 2022 14:43:32 +0000
Subject: Revert "IVGCVSW-6268 Add support of Unidirectional Sequence Lstm
 fp32/fp16 to Neon"

This reverts commit b0baff73b1574a198e57d46fcd704cedc43cea16.

Reason for revert: cannot update ACL pin until 22.02 release.

Change-Id: I049a125ba3b6a9b1cd6514ef9dd14d807773ed00
---
 src/backends/cl/workloads/ClLstmFloatWorkload.cpp | 71 ++++++++++++++++++++---
 1 file changed, 62 insertions(+), 9 deletions(-)

(limited to 'src/backends/cl/workloads')

diff --git a/src/backends/cl/workloads/ClLstmFloatWorkload.cpp b/src/backends/cl/workloads/ClLstmFloatWorkload.cpp
index e190f33bbc..37dfab6a5f 100644
--- a/src/backends/cl/workloads/ClLstmFloatWorkload.cpp
+++ b/src/backends/cl/workloads/ClLstmFloatWorkload.cpp
@@ -7,7 +7,6 @@
 #include <cl/ClTensorHandle.hpp>
 #include <armnn/backends/TensorHandle.hpp>
 #include <cl/ClLayerSupport.hpp>
-#include <aclCommon/ArmComputeUtils.hpp>
 #include <aclCommon/ArmComputeTensorUtils.hpp>
 
 #include <armnn/utility/NumericCast.hpp>
@@ -20,8 +19,8 @@ namespace armnn
 {
 using namespace armcomputetensorutils;
 
-ClLstmFloatWorkload::ClLstmFloatWorkload(const LstmQueueDescriptor& descriptor,
-                                         const WorkloadInfo& info,
+ClLstmFloatWorkload::ClLstmFloatWorkload(const LstmQueueDescriptor &descriptor,
+                                         const WorkloadInfo &info,
                                          const arm_compute::CLCompileContext& clCompileContext)
         : FloatWorkload<LstmQueueDescriptor>(descriptor, info)
 {
@@ -29,7 +28,7 @@ ClLstmFloatWorkload::ClLstmFloatWorkload(const LstmQueueDescriptor& descriptor,
     ARMNN_REPORT_PROFILING_WORKLOAD_DESC("ClLstmFloatWorkload_Construct",
                                          descriptor.m_Parameters,
                                          info,
-                                         GetGuid());
+                                         this->GetGuid());
 
     arm_compute::LSTMParams<arm_compute::ICLTensor> lstm_param;
 
@@ -164,8 +163,35 @@ ClLstmFloatWorkload::ClLstmFloatWorkload(const LstmQueueDescriptor& descriptor,
     float projection_threshold = m_Data.m_Parameters.m_ClippingThresProj;
 
     // for preparing the object for the class ActivationLayerInfo, we need to consider 5 situations
-    arm_compute::ActivationLayerInfo activationLayerInfo =
-        ConvertLstmActivationFuncToAclLayerInfo(m_Data.m_Parameters.m_ActivationFunc);
+    arm_compute::ActivationLayerInfo activationLayerInfo;
+    if (m_Data.m_Parameters.m_ActivationFunc == 0)
+    {
+        // no activation, do nothing
+    }
+    else if (m_Data.m_Parameters.m_ActivationFunc == 1)
+    {
+        activationLayerInfo = arm_compute::ActivationLayerInfo(
+                arm_compute::ActivationLayerInfo::ActivationFunction::RELU);
+    }
+    else if (m_Data.m_Parameters.m_ActivationFunc == 3)
+    {
+        activationLayerInfo = arm_compute::ActivationLayerInfo(
+                arm_compute::ActivationLayerInfo::ActivationFunction::BOUNDED_RELU, 6.0);
+    }
+    else if (m_Data.m_Parameters.m_ActivationFunc == 4)
+    {
+        activationLayerInfo =  arm_compute::ActivationLayerInfo(
+                arm_compute::ActivationLayerInfo::ActivationFunction::TANH, 1.0, 1.0);
+    }
+    else if (m_Data.m_Parameters.m_ActivationFunc == 6)
+    {
+        activationLayerInfo =  arm_compute::ActivationLayerInfo(
+                arm_compute::ActivationLayerInfo::ActivationFunction::LOGISTIC);
+    }
+    else
+    {
+        throw armnn::Exception("Wrong Type of Activation Function!");
+    }
 
     {
         ARMNN_SCOPED_PROFILING_EVENT(Compute::Undefined, "ClLstmFloatWorkload_configure");
@@ -237,7 +263,7 @@ ClLstmFloatWorkload::ClLstmFloatWorkload(const LstmQueueDescriptor& descriptor,
 
 void ClLstmFloatWorkload::Execute() const
 {
-    ARMNN_SCOPED_PROFILING_EVENT_CL_GUID("ClLstmFloatWorkload_Execute", GetGuid());
+    ARMNN_SCOPED_PROFILING_EVENT_CL_GUID("ClLstmFloatWorkload_Execute", this->GetGuid());
     RunClFunction(m_LstmLayer, CHECK_LOCATION());
 }
 
@@ -328,8 +354,35 @@ arm_compute::Status ClLstmFloatWorkloadValidate(const TensorInfo& input, const T
     float projection_threshold = descriptor.m_ClippingThresProj;
 
     // for preparing the object for the class ActivationLayerInfo, we need to consider 5 situations
-    arm_compute::ActivationLayerInfo activationLayerInfo =
-        ConvertLstmActivationFuncToAclLayerInfo(descriptor.m_ActivationFunc);
+    arm_compute::ActivationLayerInfo activationLayerInfo;
+    if (descriptor.m_ActivationFunc == 0)
+    {
+        // no activation, do nothing
+    }
+    else if (descriptor.m_ActivationFunc == 1)
+    {
+        activationLayerInfo = arm_compute::ActivationLayerInfo(
+                arm_compute::ActivationLayerInfo::ActivationFunction::RELU);
+    }
+    else if (descriptor.m_ActivationFunc == 3)
+    {
+        activationLayerInfo = arm_compute::ActivationLayerInfo(
+                arm_compute::ActivationLayerInfo::ActivationFunction::BOUNDED_RELU, 6.0);
+    }
+    else if (descriptor.m_ActivationFunc == 4)
+    {
+        activationLayerInfo =  arm_compute::ActivationLayerInfo(
+                arm_compute::ActivationLayerInfo::ActivationFunction::TANH, 1.0, 1.0);
+    }
+    else if (descriptor.m_ActivationFunc == 6)
+    {
+        activationLayerInfo =  arm_compute::ActivationLayerInfo(
+                arm_compute::ActivationLayerInfo::ActivationFunction::LOGISTIC);
+    }
+    else
+    {
+        throw armnn::Exception("Wrong Type of Activation Function!");
+    }
 
     if (descriptor.m_LayerNormEnabled)
     {
-- 
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