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authorCathal Corbett <cathal.corbett@arm.com>2022-02-22 14:43:32 +0000
committerTeresa Charlin <teresa.charlinreyes@arm.com>2022-02-23 10:03:52 +0000
commitf87b90e4dbb906436cf205a2a19e199bfe9224ed (patch)
tree30e51b634be94e12720c5b3841c44b64341b3615 /src/backends/cl/workloads
parent79cef69b1ec58f9ce010461eaaad04c896a4fe15 (diff)
downloadarmnn-f87b90e4dbb906436cf205a2a19e199bfe9224ed.tar.gz
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
Diffstat (limited to 'src/backends/cl/workloads')
-rw-r--r--src/backends/cl/workloads/ClLstmFloatWorkload.cpp71
1 files changed, 62 insertions, 9 deletions
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)
{