Update ACL pin to ec4dee8c68a3d0f6d63db184bfb2f4589429778e
* Axis for LogSoftMax and SoftMax can be either positive or negative
Signed-off-by: Teresa Charlin <teresa.charlinreyes@arm.com>
Change-Id: I36b0507ad7600c0a98c3b8be3c0350045ee05b84
Signed-off-by: Nikhil Raj <nikhil.raj@arm.com>
diff --git a/src/backends/neon/workloads/NeonLogSoftmaxWorkload.cpp b/src/backends/neon/workloads/NeonLogSoftmaxWorkload.cpp
index 39ff279..ba5c900 100644
--- a/src/backends/neon/workloads/NeonLogSoftmaxWorkload.cpp
+++ b/src/backends/neon/workloads/NeonLogSoftmaxWorkload.cpp
@@ -23,12 +23,11 @@
const arm_compute::TensorInfo aclInputInfo = armcomputetensorutils::BuildArmComputeTensorInfo(input);
const arm_compute::TensorInfo aclOutputInfo = armcomputetensorutils::BuildArmComputeTensorInfo(output);
- int aclAxis_int = ComputeAclAxis(descriptor.m_Axis, input);
- unsigned int aclAxis = ComputePositiveAxis(aclAxis_int, input);
+ int aclAxis = ComputeAclAxis(descriptor.m_Axis, input);
return arm_compute::NELogSoftmaxLayer::validate(&aclInputInfo,
&aclOutputInfo,
descriptor.m_Beta,
- static_cast<int>(aclAxis));
+ aclAxis);
}
NeonLogSoftmaxWorkload::NeonLogSoftmaxWorkload(const LogSoftmaxQueueDescriptor& descriptor,
@@ -42,9 +41,8 @@
arm_compute::ITensor& output = PolymorphicDowncast<IAclTensorHandle*>(m_Data.m_Outputs[0])->GetTensor();
auto layer = std::make_unique<arm_compute::NELogSoftmaxLayer>(memoryManager);
- int aclAxis_int = ComputeAclAxis(m_Data.m_Parameters.m_Axis, info.m_InputTensorInfos[0]);
- unsigned int aclAxis = ComputePositiveAxis(aclAxis_int, info.m_InputTensorInfos[0]);
- layer->configure(&input, &output, m_Data.m_Parameters.m_Beta, static_cast<int>(aclAxis));
+ int aclAxis = ComputeAclAxis(m_Data.m_Parameters.m_Axis, info.m_InputTensorInfos[0]);
+ layer->configure(&input, &output, m_Data.m_Parameters.m_Beta, aclAxis);
m_LogSoftmaxLayer.reset(layer.release());
}