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2024-04-17MLCE-1248 Removing limitations on zero scale value in quantization.Colm Donelan
Currently Arm NN will fail to load models containing quantization scale value of zero. Signed-off-by: Colm Donelan <colm.donelan@arm.com> Change-Id: Ifefcee1279b8667da63d1aa7d42e5d44875f9fbe
2024-03-13IVGCVSW-7853 Assert audit and removalDeclan-ARM
* src/armnn * src/armnn/layers Signed-off-by: Declan-ARM <decmce01@arm.com> Change-Id: Ic78cbbb59e90fbb15f893205a358c45264243721
2024-03-08IVGCVSW-8299 Optimisation to replace Max + Min with Bounded ReluTeresa Charlin
Signed-off-by: Teresa Charlin <teresa.charlinreyes@arm.com> Change-Id: I0774a9580710350bd0a959cf68dfe057f52e4330
2024-02-28IVGCVSW-8229 & IVGCVSW-8237 ScatterNd: Front end and reference implementationTianle Cheng
(scatter_nd, scatter_nd_add, and scatter_nd_update, scatter_nd_sub, scatter_nd_min, scatter_nd_max, scatter_nd_mul) * Front end support for ScatterNd added. * Reference implementation for ScatterNd added. * Unit tests added. Signed-off-by: Tianle Cheng <tianle.cheng@arm.com> Change-Id: I30da9056d9b03ca9b5fb8d09987341128badbcf4
2023-12-21Add Quantize Support to TOSA Ref BackendTeresa Charlin
* Adding a one to many tosa mapping for Quantize * Added tests * Resolves IVGCVSW-7175 Signed-off-by: John Mcloughlin <john.mcloughlin@arm.com> Signed-off-by: Teresa Charlin <teresa.charlinreyes@arm.com> Change-Id: Ia0852fefb618b4a29c2601b9de8b6b2731229801
2023-12-07IVGCVSW-8157 - Rebase existing GpuFsa patches to 23.11David Monahan
Squashed commit of the following: IVGCVSW-7159 Add GpuFsa backend skeleton IVGCVSW-7380 Update the GpuFsa Skeleton to build and load ACL IVGCVSW-7381 Add IsLayerSupported implementation to GpuFsa backend IVGCVSW-7382 Implementation of Conv2d within GpuFsa Signed-off-by: James Conroy <james.conroy@arm.com> Signed-off-by: Matthew Sloyan <matthew.sloyan@arm.com> Signed-off-by: David Monahan <david.monahan@arm.com> Change-Id: Id23d9ee598535de7b38a99ca223cdf0ad2102cef
2023-10-16IVGCVSW-7752 DTS: Fix QuantizePerChannel testsJohn Mcloughlin
* Added validation for scale on all Quantized types * Added Encoder for Per Axis UINT16 Symmetrical Quantized type * Added error for Per Axis Asymmetrical Quantized type not supported Signed-off-by: John Mcloughlin <john.mcloughlin@arm.com> Change-Id: I433519ccacd71219a92bde2b81955d6abf9219c5
2023-08-31IVGCVSW-7525 Add broadcast_to operatorIdriss Chaouch
Signed-off-by: Idriss Chaouch <idriss.chaouch@arm.com> Signed-off-by: Narumol Prangnawarat <narumol.prangnawarat@arm.com> Change-Id: I94ec5f9120b2d736fdf98d00ec5137a4efd739b8
2023-08-28IVGCVSW-7505 Create FusedLayer and NeonFusedWorkload for AddMulAdd Neon kernelTeresa Charlin
Signed-off-by: Teresa Charlin <teresa.charlinreyes@arm.com> Change-Id: Ic778d35b001474b44fb1e433a6fe276e4ec9f565
2023-08-03IVGCVSW-7635 Remove deprecated code due to be removed in 23.08 (SubgraphView)Francis Murtagh
Signed-off-by: Francis Murtagh <francis.murtagh@arm.com> Signed-off-by: Kevin May <kevin.may@arm.com> Change-Id: I6686ad0a16ef763dbdc771c7ef792ae2890e0ab2
2023-08-02IVGCVSW-7880 Add check for FP16 backend supportRyan OShea
* Check if preferred backends have FP16 support before enable fp16-turbo-mode * Unit tests * Replaced global gpuAccCapabilities with getter method construction * Replaced deprecated function call in SL shim Signed-off-by: Narumol Prangnawarat <narumol.prangnawarat@arm.com> Signed-off-by: Ryan OShea <ryan.oshea3@arm.com> Change-Id: If29b62b330ca8987de8acf6408db11daf25ca0b5
2023-07-25IVGCVSW-7883 Front end and reference implementation for TILETeresa Charlin
Signed-off-by: Teresa Charlin <teresa.charlinreyes@arm.com> Signed-off-by: Cian McGriskin <cian.mcgriskin@arm.com> Change-Id: I0afb2403fee11c5c1e58ea65e2525e99594d8f2d
2023-07-21IVGCVSW-7830 Clean upMike Kelly
* Follow up review to clean up whitespace and copyright errors mentioned in https://review.mlplatform.org/c/ml/armnn/+/9885 * Added BinaryElementwiseOperation to .dot files * Refactored ConnectedToSplitterWithMoreThan4Dims function to more generally useful ConnectedToLayerType function Signed-off-by: Mike Kelly <mike.kelly@arm.com> Change-Id: I0e3d0895888f3a3f0a9758ce30bc031aba50812b
2023-07-17IVGCVSW-7879 Change REVERSE_V2 from LayerWithParameters with 1 input, to ↵Tracy Narine
Layer with 2 inputs * Changing ReverseV2 to use two inputs * This is required by the backends * The ReverseV2Descriptor was removed * Tests updated * Added a Run<> templatefor inputs with different data types Signed-off-by: Tracy Narine <tracy.narine@arm.com> Change-Id: I22f947de829b4b3da6bda3a74f4ffdef4052cc25
2023-07-14IVGCVSW-7830 Add backend optimizations to remove Reshapes where possibleMike Kelly
* Added optimization to remove reshapes for Neon and Ref Backends by using overridden TensorInfos * Added ability to delete Subgraphs during Optimization * Fixed naming error in NeonEndToEndTests and CLEndToEndTests * Added LayerNameAndTypeCheck for testing. * Fixed error where layers were not marked as altered when removed in CLBackend Signed-off-by: Mike Kelly <mike.kelly@arm.com> Change-Id: I1ac25cd4ec9821470d961831ae2c8d24882276cc
2023-07-04IVGCVSW-7831: Front end and Reference Implementation for REVERSE_V2Tianle Cheng
* Descriptors added for ReverseV2 * Layer definition added * Input validation added * Reference workload implementation for ReverseV2 added * Reference layer unit tests made for ReverseV2 * CompareTensors method updated to support comparison between empty tensors * CMake and other build files updated Signed-off-by: Tianle Cheng <tianle.cheng@arm.com> Change-Id: I805738454421309fda77c44218a8df171d68dc18
2023-05-08Improve reusability of code that is defined out by cmake build pathsRyan OShea
* Added new ARMNN_STUB_PROFILING and ARMNN_DISABLE_DYNAMIC_BACKEND defines to replace BUILD_BARE_METAL and BUILD_EXECUTE_NETWORK_STATIC * Add new CMake variables to disable sample apps and dynamic backends * Improve BUILD_SHARED_LIBS CMake variable * Add new archive output location to various libraries so that the static libraries appear in the same location as the shared libraries * Fixes for bare metal build * Add ARMNN_DISABLE_FILE_SYSTEM defines to missing locations Signed-off-by: Ryan OShea <ryan.oshea3@arm.com> Change-Id: I1db9a8f483e7134bd261294b35240cf21b150d45
2023-04-12IVGCVSW-7197 Implement Pimpl Idiom for OptimizerOptionsJohn Mcloughlin
Signed-off-by: John Mcloughlin <john.mcloughlin@arm.com> Change-Id: Id4bdc31e3e6f18ccaef232c29a2d2825c915b21c
2023-04-03IVGCVSW-3808 Deprecation notices for old ElementwiseBinary layersMike Kelly
* Added Deprecation notices for old ElementwiseBinary layers. Signed-off-by: Mike Kelly <mike.kelly@arm.com> Change-Id: I5bd0f186aaed675885d667f47e1e210ee9ec84f8
2023-03-31Revert "IVGCVSW-3808 Deprecation notices for old ElementwiseBinary layers"Mike Kelly
This reverts commit 52e90bf59ecbe90d33368d8fc1fd120f07658aaf. Change-Id: I5a0d244593d8e760ee7ba0c9d38c02377e1bdc24 Signed-off-by: Mike Kelly <mike.kelly@arm.com>
2023-03-30IVGCVSW-3808 Deprecation notices for old ElementwiseBinary layersMike Kelly
* Added Deprecation notices for old ElementwiseBinary layers. Signed-off-by: Mike Kelly <mike.kelly@arm.com> Change-Id: Iebbbaff38cc9c347b25eb2f9054c914a4f931c68
2023-03-14IVGCVSW-3808 Add ElementwiseBinaryLayerMike Kelly
!android-nn-driver:9329 * Added ElementwiseBinaryLayer that can represent all ElementwiseBinary operations including Add, Div, Sub, Maximum, Mul and Minimum. * Updated Delegate to use ElementwiseBinaryLayer instead of the Add, Div, Sub, Maximum, Mul and Minimum layers. * Updated Deserializer to use ElementwiseBinaryLayer instead of the Add, Div, Sub, Maximum, Mul and Minimum layers. * Updated OnnxParser to use ElementwiseBinaryLayer instead of the Add layer. * Updated TfLiteParser to use ElementwiseBinaryLayer instead of the Add, Div, Sub, Maximum, Mul and Minimum layers. * Updated CL and Neon tests to use ElementwiseBinaryLayer. * Updated CL and Neon Backend Specific Optimizations to accept ElementBinaryLayers as well as Add, Div, Mul, Sub, Maximum and Minimum layers. Signed-off-by: Teresa Charlin <teresa.charlinreyes@arm.com> Signed-off-by: Mike Kelly <mike.kelly@arm.com> Change-Id: I7cbb96b60eb01f0e2b57b0541016d48a08b86c75
2023-01-18Github #700: Fix order of optimizations so dequantization works with foldingFrancis Murtagh
* Folding of pad into conv2d expected a Constant layer not Dequantisation * Fusing Dequantisation with Constant to a Constant ensures that. * Group Constant layer optimizations together where possible. * Add unit test. Signed-off-by: Francis Murtagh <francis.murtagh@arm.com> Change-Id: Id0393313bf097595f2f13738b7513e427116ea4a
2023-01-18IVGCVSW-7405 Improving error handling around creating directories.Colm Donelan
The -F execute network option creates a directory to print intermediate tensors but minor problems caused serious failures. This attempts to clean up the error handling. Signed-off-by: Colm Donelan <colm.donelan@arm.com> Change-Id: Ia44c008919b1bee299b43a672235b1fcc25bf1bd
2023-01-04IVGCVSW-7211 Fix float16 operators being wrongly unsupported with ↵Cathal Corbett
android-nn-driver. * Not a concern with the delegate/parser as tflite builtin operators have little float16 support * Will also fix float16 workloads running on the support_library. Signed-off-by: Cathal Corbett <cathal.corbett@arm.com> Change-Id: Iec2033dbc8ece2140b188de1f193c344a68b9c36
2022-12-23Remove Network.cpp debug message merged in "Optimize the calling of ↵Cathal Corbett
IsLayerSupported()." Signed-off-by: Cathal Corbett <cathal.corbett@arm.com> Change-Id: I7fa4110a1b545c1fcd79e387d53ae7d6cd381f31
2022-12-12IVGCVSW-7209 Remove deprecated code due to be removed in 23.02Mike Kelly
* 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
2022-12-12Optimize the calling of IsLayerSupported().Cathal Corbett
* Done as part of 22.11/23.02 innovation days. * IsLayerSupported() is called in model prepare (delegate, android-nn-driver and shim/support_library) and again in ArmNN once model otimization is performed. * From calling IsLayerSupported() the first time, we should know that the layers are supported and what backend they are supported on. * Solution is to set the BackendId of the IConnectableLayer when IsLayerSupported() is called the first time, * In the Optimize() function we then check if the backend is set. If so, we do not call IsLayerSupported() again. * In the case a layer that is supported gets optimized, then the BackendId of that layer get set to "Unknown" for the new optimized layer and IsLayerSupported() will get called on the newly optimized layer. * Includes bug fix IVGCVSW-7213 for Android Mean FP16 CpuAcc tests. Also related to bug IVGCVSW-7211. Signed-off-by: Cathal Corbett <cathal.corbett@arm.com> Change-Id: I7a7820d0cdb079ffb5a3a2e0c44e252f652df53b
2022-11-16IVGCVSW-7214 Disable BF16-Turbo-Mode and remove conversion layersRyan OShea
- Remove Bf16ToFp32 Conversion Layer - Remove Fp32ToBf16 Conversion Layer - Remove B16 Conversion tests * Throw exception if m_ReduceFp32ToBf16 optimzer option is set to true * Provide comments to enable fast math in order to use bf16 * Update docs to inform users to enable fast math for bf16 Execute Network Changes * Require bf16_turbo_mode to also have fast_math_enabled set to true - Remove setting m_ReduceFp32ToBf16 optimizer option Signed-off-by: Ryan OShea <ryan.oshea3@arm.com> Change-Id: Ibaa6da9d29c96a1ce32ff5196b0847fde9f04a1c
2022-10-28IVGCVSW-7296 REDUCE_PROD tests fail when using Tf 2.10Teresa Charlin
* In TF what ArmNN calls quantized data types can be non-quantized as well. * This patch creates 2 models: * ArmNN: model where int8 and uint8 will always be quantized, but scale can be 1 and offset 0 * TFLite: model where int8 and uint8 can be quantized and non-quantized Signed-off-by: Teresa Charlin <teresa.charlinreyes@arm.com> Change-Id: Id960f2f30988f2bbec88cb4e0c52c189ac957bae
2022-10-19MLCE-545 INT8 TFLite model execution abnormalKeith Davis
* Bug fix where files were being overwritten at each debug layer Signed-off-by: Keith Davis <keith.davis@arm.com> Change-Id: I609fdc82afcee925824efb02183c7dbc942fced0
2022-10-19MLCE-545 INT8 TFLite model execution abnormalKeith Davis
* Add functionality to print output tensors to file in tempdir * UnitTests Signed-off-by: Keith Davis <keith.davis@arm.com> Change-Id: Idfb4c186544187db1fecdfca11c662540f645439
2022-10-14IVGCVSW-7267 Make the AllowExpandedDims option workJim Flynn
Signed-off-by: Jim Flynn <jim.flynn@arm.com> Change-Id: I3573078206272c3a72a2b3acf8781ab458ea6c90
2022-10-04MLCE-545 INT8 TFLite model execution abnormalKeith Davis
* Fix for Debug mode in ExNet does not work with ConstTensorsAsInputs * Remove unnecessary assertion with ambiguous message in LoadedNetwork Signed-off-by: Keith Davis <keith.davis@arm.com> Change-Id: I9cd5d1f811dbbc89072d1190c510bf1b22e3069c
2022-09-06IVGCVSW-7006 Remove deprecated code due to be removed in 22.08Teresa Charlin
* AddConv and AddDWConv with weights and bias * ResizeBilinearDescriptor * b,blacklist option in accuracy tool !android-nn-driver:8172 Signed-off-by: Teresa Charlin <teresa.charlinreyes@arm.com> Change-Id: Ibbc04fd18be7f938b11590bf67cd7af103cb4d99
2022-08-29IVGCVSW-6954 'Arm NN SL Improvements'Sadik Armagan
* Move the Conv2D and DepthwiseConv2D validation to Optimization level when the weights and tensors are as constant inputs * Take into account offset and scales values when doing INT8 to FP32 dequantization Signed-off-by: Sadik Armagan <sadik.armagan@arm.com> Change-Id: I1f81f15640395ac041923b10dbe9151159715117
2022-07-28Revert "Revert "IVGCVSW-6650 Refactor ExecuteNetwork""Teresa Charlin
This reverts commit 1a7f033768acb27da11503bd29abb468d2e77f9e. List of fixes to be able to add this code again: * "emplacing_back" the vector inputTensors into the vector m_InputTensorsVec outside the for loop * GetIOInfo() uses IOptimizedNetwork instead of INetwork, where the infered shapes are not saved * Add missing data type Signed32 to SetupInputsAndOutputs() * PrintOutputTensors() prints the actual output without dequantizing * Add profilingDetailsMethod as input in networkProperties in ArmNNExecutor constructor * Fix typos Change-Id: I91de166f87228282db3efa27431fe91458834442 Signed-off-by: Teresa Charlin <teresa.charlinreyes@arm.com> Change-Id: Ic6634d48892d11e5f146cdf285e1e333e93e9937 Signed-off-by: Francis Murtagh <francis.murtagh@arm.com>
2022-07-27IVGCVSW-7109: Add Batch MatMul front end support - ReferenceSamuel Yap
* Descriptors added for BatchMatMul * Layer definition added * Input validation added (will likely change when opt. param support comes in) * Ref workload implementation for BatchMatMul added (will also change with opt. param support) * Ref layer tests made for BatchMatMul * CMake and other build files updated Signed-off-by: Samuel Yap <samuel.yap@arm.com> Change-Id: Ic885301da543ee0fbe7922b85e7f9658c4efc617
2022-07-27IVGCVSW-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>
2022-06-27IVGCVSW-6981 Remove deprecated code 22.05 [Post Release]Nikhil Raj
Signed-off-by: Nikhil Raj <nikhil.raj@arm.com> Change-Id: I9ccaefbe28ea572e9e2b4a2168574804667f7460
2022-06-22Revert "Revert "IVGCVSW-6873 Import inputs but don't export outputs fails.""Francis Murtagh
This reverts commit a0f8b15d4ddb5075f380003ff31b271d389d3b66. Reason for revert: <Test ClDmaBufInternalTests review > Change-Id: Ibc4a77fa008643849da7330391942e4c87b941e2
2022-06-21Revert "IVGCVSW-6873 Import inputs but don't export outputs fails."James Conroy
This reverts commit 03bf98a8bc51ad20eef4b9ca5fbf6ce15e063721. Reason for revert: Caused failures in tests located in internal repo. Change-Id: If35cb0ede349b270e4e7827324382e09455d8cfa
2022-06-20IVGCVSW-6873 Import inputs but don't export outputs fails.Colm Donelan
Only one bool is used to indicate whether inputs should be imported. However, its possible for the user to want to import inputs but not export outputs. In addition it's possible for a user to enabled import during optimize but then pass a memory source that does not require import. * Add m_ExportEnabled to INetwork.hpp. * Modify Network::dNetwork to consider both m_ImportEnabled and m_ExportEnabled. * Add ValidateSourcesMatchOptimizedNetwork to LoadedNetwork to validate import options between optimize and network load. * Update the TfLite delegate consider exportEnabled flag in the optimizer. !armnn-internal-tests:425350 Signed-off-by: Colm Donelan <colm.donelan@arm.com> Change-Id: I776eab81595898e43f91ab40306962eae61329f4
2022-05-23IVGCVSW-6123 ConstTensorsAsInputs: Conv2dKeith Davis
* Use new INetwork::AddConvolution2dLayer instead of deprecated version * Remove duplicated test in SerlializerTests * Fix some cosmetics Signed-off-by: Keith Davis <keith.davis@arm.com> Change-Id: I3407815bfdc1cdc01ca0a667b8e4d80d8621783f
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>
2022-05-18IVGCVSW-6929 Support for models with implicit expandedMike Kelly
dimensions * Added allow-expanded-dims to TFLite parser and ArmNN delegate * If true ArmNN will disregard dimensions with a size of 1 when validating tensor shapes. Tensor sizes must still match. * This allows us to support models where tensors have expanded dimensions (i.e. extra dimensions with a size of 1). * Fixed bug in Network where it assumed that only the first option could be ShapeInferenceMethod. * Fixed bug where m_ShapeInferenceMethod was lost when copying or moving Graphs. * Changed Delegate to pass "infer-output-shape", "allow-expanded-dims" and other BackendOptions through to the Network during construction. Signed-off-by: Mike Kelly <mike.kelly@arm.com> Change-Id: Ibe7c5ae6597796fc9164cb07bd372bd7f8f8cacf
2022-05-17IVGCVSW-6126 ConstTensorsAsInput: Conv2d - BackendsCathal Corbett
!android-nn-driver:7477 Signed-off-by: Cathal Corbett <cathal.corbett@arm.com> Change-Id: Ibf633ccccc385bd980934ff829407d21981323ef
2022-05-16IVGCVSW-6124 ConstTensorsAsInput: Conv2d - FrontEndKeith Davis
* Update Front-end and Tools. * Updated Serializer, Deserializer and unit tests to reflect this. * Updated TfLiteDelegate, TfLiteParser and OnnxParser. * Updated Ref. * Fixed resulting Neon / CL tests * Unified optimizers for conv2d ops * Optimizer Fix - Fp32ToBf16 * Partial implementation for ACL backends to fix VTS failures !android-nn-driver:7477 Signed-off-by: Keith Davis <keith.davis@arm.com> Change-Id: I5fb18877f7ee32643e15a9818945356274bb401b
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
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