Age | Commit message (Collapse) | Author |
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* Removed weights and bias from Convolution, DepthwiseConv & FullyConnected
layers
* Removed the weight and bias ConstTensorHandles from the QueueDescriptors
* Updated Workloads to take tensors from WorkloadInfo rather than the
QueueDescriptors
* Removed unused RedirectMembersToConstantInputs optimization and tests.
Signed-off-by: Teresa Charlin <teresa.charlinreyes@arm.com>
Signed-off-by: Mike Kelly <mike.kelly@arm.com>
Change-Id: I9ffcdc4a1c0dff725539dd69fc435b700bd98a56
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* IVGCVSW-6940 ConstTensorsAsInput: DepthwiseConvolution2d - Complete Neon and Cl Bug Fix
* Bug fix to enable Cl and Neon Backend Compatibility ConstantTensorsAsInputs
* Updated Cl and Neon FullyConnected workloads to handle constant
weights and bias as inputs rather than reading from member variables.
* Prevent non const weights and biases passing CL and NEON validate
for Depthwise Convolution.
Signed-off-by: Cathal Corbett <cathal.corbett@arm.com>
Change-Id: I0f505ff5998a183152f843d0f6cc74327ba920e7
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Use armnn::Optional for optional bias TensorInfos, similar to how
it's already done in Convolution etc.
Fixes some test failures found using -fsanitize=undefined
Change-Id: I7b887e63e2ffab14aeab14415069be738d938ebb
Signed-off-by: Matthew Bentham <matthew.bentham@arm.com>
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* Neon workloads to extend NeonBaseWorkload instead of BaseWorkload
* Cl workload to extend ClBaseWorkload instead of BaseWorkload
Signed-off-by: Teresa Charlin <teresa.charlinreyes@arm.com>
Change-Id: I8f39a31a89a8865ac4acf18573ab290d548d2864
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Move the following header files from backendsCommon to armnn/backends.
* MemCopyWorkload.hpp
* TensorHandle.hpp
* Workload.hpp
* WorkloadData.hpp
* WorkloadFactory.hpp
Replace them with forwarding headers and a pragma deprecation message.
Resolve the deprecation messages in Arm NN code.
Signed-off-by: Colm Donelan <colm.donelan@arm.com>
Change-Id: I47f116b30f86e478c9057795bc518c391a8ae514
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* Added Fused Activation Optimization to both CL and Neon backends.
* Added Fused Activation support to all the CL and Neon workloads
that support it.
* Changed ProfilingTest network to be a Convolution layer
followed by an Abs layer rather than an Activation layer.
* Added IBackendInternal::OptimizeSubgraphView function that can accept a
ModelOptions.
* Network will now call OptimizeSubgraphView passing in the ModelOptions.
Signed-off-by: Keith Davis <keith.davis@arm.com>
Signed-off-by: Mike Kelly <mike.kelly@arm.com>
Signed-off-by: Teresa Charlin <teresa.charlinreyes@arm.com>
Change-Id: Ib536ac3cbafc7d9b35c139ad9a65b7735262cd9d
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Just include the function definition that is specifically needed for each workload.
Also, tighten up the scope where Compute Library functions are available.
Knocks about 30seconds off a 4m30s single-threaded compile of the Neon workloads.
Change-Id: Idac438f3bc77ff978295fbc9505cb42447def145
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Change-Id: I663a0a0fccb43ee960ec070121a59df9db0bb04e
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armnn:149855
Change-Id: I26e8cf83422a65049386a5ebdb6d0001627aefaa
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