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author | Narumol Prangnawarat <narumol.prangnawarat@arm.com> | 2019-03-14 11:55:03 +0000 |
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committer | Áron Virginás-Tar <aron.virginas-tar@arm.com> | 2019-03-15 15:24:44 +0000 |
commit | 65d30965eef7e8534fc16ea4ded413c42a81c362 (patch) | |
tree | 3ed591e57ee4bd68f98fce0d2b47aa0e621f2973 /src/backends/neon | |
parent | 222c753ba83bec5dc915f01d999ff76826ec45d0 (diff) | |
download | armnn-65d30965eef7e8534fc16ea4ded413c42a81c362.tar.gz |
IVGCVSW-2354 Caffe SqueezeNet through armnn Cl and Neon
* Compute Softmax Acl axis for Cl and Neon
* Add unittests for Softmax in 3D and 4D
* Correct input and output layer names in CaffeSqueezeNet inference test
Change-Id: I2d369d9a2db19c40f2af3341039dd33f0c5637b1
Signed-off-by: Narumol Prangnawarat <narumol.prangnawarat@arm.com>
Diffstat (limited to 'src/backends/neon')
-rw-r--r-- | src/backends/neon/test/NeonLayerTests.cpp | 13 | ||||
-rw-r--r-- | src/backends/neon/workloads/NeonSoftmaxFloatWorkload.cpp | 4 | ||||
-rw-r--r-- | src/backends/neon/workloads/NeonSoftmaxUint8Workload.cpp | 6 |
3 files changed, 17 insertions, 6 deletions
diff --git a/src/backends/neon/test/NeonLayerTests.cpp b/src/backends/neon/test/NeonLayerTests.cpp index 01773dba03..b34e2ddc60 100644 --- a/src/backends/neon/test/NeonLayerTests.cpp +++ b/src/backends/neon/test/NeonLayerTests.cpp @@ -275,14 +275,21 @@ ARMNN_AUTO_TEST_CASE(UNSUPPORTED_IgnorePaddingL2Pooling2dSize3Uint8, IgnorePaddi // Activation ARMNN_AUTO_TEST_CASE(ConstantLinearActivation, ConstantLinearActivationTest) +// ReLu +ARMNN_AUTO_TEST_CASE(ReLu1Uint8, BoundedReLuUint8UpperAndLowerBoundTest) +ARMNN_AUTO_TEST_CASE(ReLu6Uint8, BoundedReLuUint8UpperBoundOnlyTest) + +// Softmax ARMNN_AUTO_TEST_CASE(SimpleSoftmaxBeta1, SimpleSoftmaxTest, 1.0f) ARMNN_AUTO_TEST_CASE(SimpleSoftmaxBeta2, SimpleSoftmaxTest, 2.0f) - ARMNN_AUTO_TEST_CASE(SimpleSoftmaxBeta1Uint8, SimpleSoftmaxUint8Test, 1.0f) ARMNN_AUTO_TEST_CASE(SimpleSoftmaxBeta2Uint8, SimpleSoftmaxUint8Test, 2.0f) -ARMNN_AUTO_TEST_CASE(ReLu1Uint8, BoundedReLuUint8UpperAndLowerBoundTest) -ARMNN_AUTO_TEST_CASE(ReLu6Uint8, BoundedReLuUint8UpperBoundOnlyTest) +ARMNN_AUTO_TEST_CASE(Simple3dSoftmaxBeta1, Simple3dSoftmaxTest, 1.0f) +ARMNN_AUTO_TEST_CASE(Simple3dSoftmaxBeta1Uint8, Simple3dSoftmaxUint8Test, 1.0f) + +ARMNN_AUTO_TEST_CASE(Simple4dSoftmaxBeta1, Simple4dSoftmaxTest, 1.0f) +ARMNN_AUTO_TEST_CASE(Simple4dSoftmaxBeta1Uint8, Simple4dSoftmaxUint8Test, 1.0f) // Splitter ARMNN_AUTO_TEST_CASE(SimpleSplitter, SplitterTest) diff --git a/src/backends/neon/workloads/NeonSoftmaxFloatWorkload.cpp b/src/backends/neon/workloads/NeonSoftmaxFloatWorkload.cpp index d9c78bbd43..afc6135e0f 100644 --- a/src/backends/neon/workloads/NeonSoftmaxFloatWorkload.cpp +++ b/src/backends/neon/workloads/NeonSoftmaxFloatWorkload.cpp @@ -7,6 +7,7 @@ #include "NeonWorkloadUtils.hpp" +#include <aclCommon/ArmComputeUtils.hpp> #include <arm_compute/runtime/NEON/functions/NESoftmaxLayer.h> namespace armnn @@ -22,8 +23,9 @@ NeonSoftmaxFloatWorkload::NeonSoftmaxFloatWorkload(const SoftmaxQueueDescriptor& arm_compute::ITensor& input = boost::polymorphic_downcast<INeonTensorHandle*>(m_Data.m_Inputs[0])->GetTensor(); arm_compute::ITensor& output = boost::polymorphic_downcast<INeonTensorHandle*>(m_Data.m_Outputs[0])->GetTensor(); + unsigned int aclAxis = ComputeSoftmaxAclAxis(info.m_InputTensorInfos[0]); auto layer = std::make_unique<arm_compute::NESoftmaxLayer>(memoryManager); - layer->configure(&input, &output, m_Data.m_Parameters.m_Beta); + layer->configure(&input, &output, m_Data.m_Parameters.m_Beta, aclAxis); m_SoftmaxLayer.reset(layer.release()); } diff --git a/src/backends/neon/workloads/NeonSoftmaxUint8Workload.cpp b/src/backends/neon/workloads/NeonSoftmaxUint8Workload.cpp index f780589075..7f295d6548 100644 --- a/src/backends/neon/workloads/NeonSoftmaxUint8Workload.cpp +++ b/src/backends/neon/workloads/NeonSoftmaxUint8Workload.cpp @@ -4,9 +4,10 @@ // #include "NeonSoftmaxUint8Workload.hpp" - #include "NeonWorkloadUtils.hpp" +#include <aclCommon/ArmComputeUtils.hpp> + #include <arm_compute/runtime/NEON/functions/NESoftmaxLayer.h> namespace armnn @@ -29,9 +30,10 @@ NeonSoftmaxUint8Workload::NeonSoftmaxUint8Workload(const SoftmaxQueueDescriptor& throw InvalidArgumentException( "Invalid quantization for output. Only scale = 1.0f / 256.0f and offset = 0 supported"); } + unsigned int aclAxis = ComputeSoftmaxAclAxis(info.m_InputTensorInfos[0]); auto layer = std::make_unique<arm_compute::NESoftmaxLayer>(memoryManager); - layer->configure(&input, &output, descriptor.m_Parameters.m_Beta); + layer->configure(&input, &output, descriptor.m_Parameters.m_Beta, aclAxis); m_SoftmaxLayer.reset(layer.release()); } |