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Signed-off-by: Teresa Charlin <teresa.charlinreyes@arm.com>
Change-Id: I0e7132f61001f7b2a9fad3d7b21acf2558c01df4
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Signed-off-by: Teresa Charlin <teresa.charlinreyes@arm.com>
Change-Id: I60da1414ab41ea196cdebc27f0f014a502274fa8
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Change-Id: I3cf8d9dbc4f8c95e0e2311505dd7e9f9069f1ab5
Signed-off-by: Ruomei Yan <ruomei.yan@arm.com>
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* Refactored RefConvolution2dWorkload to support all DataTypes through Encoders and Decoders.
* Added Convolute function to ConvImpl that uses Encoders and Decoders to support all DataTypes.
* Deleted RefConvolution2dFloat32Workload and RefConvolution2dUint8Workload.
Signed-off-by: Mike Kelly <mike.kelly@arm.com>
Signed-off-by: Teresa Charlin <teresa.charlinreyes@arm.com>
Change-Id: Ic5ef0f499d08b948fa65fdee54b5f681fd0b1c05
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* Added OptimizeSubgraphViewTests file covering a number of
use cases for the Optimization API
* Fixed a bug in the sub-graph selector algorithm that skipped the
first layer in a sub-graph if it wasn't an input layer
* Changed the graph splitting logic to make use of maps instead of
unordered_maps to keep the split sub-graphs in consistent order
between executions
* Added more common unit test utils
* Minor fixes to comply to the include file conventions
Change-Id: Iad464eaedd004109e5ef41aa487cea3ad86177d3
Signed-off-by: Matteo Martincigh <matteo.martincigh@arm.com>
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Adds unit tests for dilated depthwise conv
Change-Id: Iad0a1b33d07fb0ef8f9f6edf0fd0f83a5800a36d
Signed-off-by: Bruno Goncalves <bruno.slackware@gmail.com>
Signed-off-by: Matthew Bentham <matthew.bentham@arm.com>
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!android-nn-driver:968
Signed-off-by: Aron Virginas-Tar <Aron.Virginas-Tar@arm.com>
Change-Id: I03ccb4842b060a9893567542bfcadc180bbc7311
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Change-Id: I7359617a307b9abb4c30b3d5f2364dc6d0f828f0
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in favor of a type-indepent implementation that takes void-pointers
* The new implementation requires the size of the type to be passed
to the function
* Updated all the usages accordingly
* Removed the old implementation no longer used
!android-nn-driver:469
Change-Id: I37f4e6d62a38fbb8ec8c39bb559a2c54c83365d4
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* Unified ArmNN's weight format to [ M, I, H, W ] for the depthwise convolution
* Added conversion utilities to permute/reshape the weights as appropriate
when using CL and Neon backends
* Updated the reference implementation of the convolution
* Updated the relevant unit tests accordingly
!android-nn-driver:459
Change-Id: I07d0818efa9d1ca1e5dad82983aac1fe78eadb18
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Change-Id: Iae6a3bfad06cb669ef0abea465d03163bb8316f5
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* Since DataLayoutIndexed is now required in the TF parser, this
changes move it to the armnnUtils library so that it'll be
accessible by the armnnTfParser
* Modified CMake files and Android.mk files accordingly
Change-Id: Ie2620359ef288aeff64cb9e9bec068a466eee0e9
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* helper methods for creating TensorShape and TensorInfo objects
Change-Id: I371fc7aea08ca6bbb9c205a143ce36e8353a1c48
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Change-Id: If8d8087d9d365e467d3ca9bf9c40d7219cb75cfd
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Change-Id: Idc0f94590566ac362f7e1d1999361d025cc2f67a
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* Added quick workaround for the memory management errors in the
CL/Neon unit tests
Change-Id: I56250db462cdbdc1acc0a5824807d288fb0c1d11
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Change-Id: I663a0a0fccb43ee960ec070121a59df9db0bb04e
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