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path: root/src/armnn/optimizations/All.hpp
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2022-07-22IVGCVSW-6978: RedirectMembersToConstantInputs does not work with ↵Francis Murtagh
Fp32NetworkToBf16Converter * Fuse FP32ToBF16Layers with Constant Layer so Conv2d/FullyConnected can have their weights redirected. * If BF16 Unsupported in Conv2d || FullyConnected revert fused Constant Layer to FP32 Change-Id: If523c708a822659d64597d9ae39cca1c2f84b76f Signed-off-by: Francis Murtagh <francis.murtagh@arm.com>
2022-05-18IVGCVSW-6147 ConstTensorsAsInput: Optimizer - FusePermuteIntoConstLayerCathal Corbett
* No trailing permute layer after a constant layer * Unit test for optimization Signed-off-by: Cathal Corbett <cathal.corbett@arm.com> Change-Id: I0d098f5af41d2c55df7cef1ccfb848093320ddc1
2022-05-18IVGCVSW-6455 Support Const + Dequantize layer and optimize it.Teresa Charlin
* Support Float16 as input to Dequantize layer * Add Optimization to substitute Const+Dequantize layers with Const layer Signed-off-by: Teresa Charlin <teresa.charlinreyes@arm.com> Change-Id: I58bb7e3871ca480c7b6fca93c4efb2de84e09e64 Signed-off-by: David <david.monahan@arm.com>
2022-05-12IVGCVSW-6940 ConstTensorsAsInput: DepthwiseConvolution2d - Complete ACLCathal Corbett
* Added backend specific optimization & test for CpuAcc and GpuAcc: PermuteDepthwiseConv2dWeights Signed-off-by: Cathal Corbett <cathal.corbett@arm.com> Change-Id: I600476b2e9c557a39818a574c1091c9d650b21b1
2021-06-30IVGCVSW-6161 ConstTensorsAsInput: Optimizer - Redirect ConstTensor layer membersMatthew Sloyan
* Optimization that searches for layers with ConstantLayers as inputs. * The layer member variables are then redirected to these ConstantLayers. Signed-off-by: Matthew Sloyan <matthew.sloyan@arm.com> Change-Id: I24a2bf0e8575b808343e0bbe3897b344e94796ad
2021-04-21Fold PAD into Pooling2d if possibleDiego Lopez Recas
Some models would add a PAD layer before a pooling when they can't express their padding configuration as SAME or VALID. ArmNN can potentially merge the two merge the two because pooling layers are described with explicit padding. The merge is possible if the extra padding is neutral in the combined pooling operation. A merged operation can only fuse paddings in the dimensions that accept explicit padding in a pooling operation, i.e. the spatial dimensions. Signed-off-by: Diego Lopez Recas <diego.lopez.recas@gmail.com> Signed-off-by: Colm Donelan <Colm.Donelan@arm.com> Change-Id: Icd54718dcd9e797c923456b7fa6e0213e288e668
2021-03-23Revert "Fold PAD into Pooling2d"Jim Flynn
This reverts commit 51ce7d487c761358de105f82ff90553570aedac0. Reason for revert: https://jira.arm.com/browse/IVGCVSW-5798 LargeGraph_TENSOR_FLOAT32 CTS tests failures Change-Id: Ib031a47f605340b2202ecf074ce96a8b54c51075
2021-03-22Fold PAD into Pooling2dDiego Lopez Recas
Some models would add a PAD layer before a pooling when they can't express their padding configuration as SAME or VALID. Arm NN can merge the two because pooling layers are described with explicit padding. Signed-off-by: Diego Lopez Recas <diego.lopez.recas@gmail.com> Change-Id: Id048186db6a005e0257bfbc1406c3b0dab2cdd58
2020-10-29IVGCVSW-5314 Create OptimizeForExclusiveConnectionTeresa Charlin
* FuseBatchNorm class has been added to facilitate testing * Only Convolution2D FP32 being fused Signed-off-by: Teresa Charlin <teresa.charlinreyes@arm.com> Change-Id: I049c4770946ddca21b08516d4c9f4d0d22bf9b45
2020-09-15IVGCVSW-5305 AddBroadcastReshapeLayer as optimizerNarumol Prangnawarat
* Remove AddBroadcastReshapeLayer from TfLiteParser * Add AddBroadcastReshapeLayer as optimizer * AddBroadcastReshapeLayer optimizer unit tests * Load-scope dynamic tensor broadcasting unit tests Signed-off-by: Narumol Prangnawarat <narumol.prangnawarat@arm.com> Change-Id: I3549e85b71b41cbd4d96c0f1ece7887acbca76d1
2020-06-03remove BOM from filesLaurent Carlier
Change-Id: Ia4b4bb3be0ed6e933c77d58f8e9879b1370e9537 Signed-off-by: Laurent Carlier <laurent.carlier@arm.com>
2020-03-20IVGCVSW-4520 Implement BFloat16 OptimizerNarumol Prangnawarat
* Add ReduceFp32ToBf16 to OptimizerOptions * Add ConvertFp32NetworkToBf16 * Add utility functions to insert conversion layers * Add constant conversion BF16 <-> FP32 * Unit tests Signed-off-by: Narumol Prangnawarat <narumol.prangnawarat@arm.com> Change-Id: Iaff77e20c721400b052cb37eb9ef6fe16d7abaff
2020-03-03IVGCVSW-4375 Add support for Transpose to optimizationsMike Kelly
* Changed some existing Permutation specific optimizations to also support Transpose * Added MoveTransposeUp optimization * Added TransposeAsReshape optimization * Added tests for Transpose optimizations * Added missing layer tests for Transpose Signed-off-by: Mike Kelly <mike.kelly@arm.com> Change-Id: I20d099b284861402ae94aaa5dbf34907327a485f
2019-09-27NNXSW-1826 Add an optimization step which combines Permute and BatchToSpace ↵Rob Hughes
into DepthToSpace This is only possible in some limited cases, but removes an extra layer from the graph and so should improve performance in all cases. Change-Id: I7b3e6ba5dacb4fdb816ad270edaecda1436ab4cf Signed-off-by: Rob Hughes <robert.hughes@arm.com>
2019-04-19IVGCVSW-2925: Combine Pad with Convolution2d in the OptimizerNina Drozd
* Added new optimization for folding pad layer into convolution2d layer following it * Added new test in OptimizerTests.cpp * Added new optimization into All optimizations * Added call to new optimization in Optimize in Network.cpp * Updated CMakeLists.txt Signed-off-by: Nina Drozd <nina.drozd@arm.com> Change-Id: I682e07c71bbd42c49c02dda30a848a9ab2b16e7e
2018-12-11IVGCVSW-1434 Add debug mode to Optimizerkeidav01
* Modified optimizer to support debug mode via DebugLayer Change-Id: Ic8f313778e55540c182cf99876c44a0823be04c6
2018-09-17IVGCVSW-1807 : change license text in file headersDavid Beck
All changes are the same: // // Copyright © 2017 ARM Ltd. All rights reserved. -// See LICENSE file in the project root for full license information. +// SPDX-License-Identifier: MIT // Change-Id: I37eae011411133663ca9d2b059714d92f8bf8e24
2018-08-31Release 18.08telsoa01
2018-03-09Release 18.02telsoa01
Change-Id: Id3c11dc5ee94ef664374a988fcc6901e9a232fa6
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