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83 Commits

Author SHA1 Message Date
Zihao Mu
1e2ceca4df add enableWinograd API for Net. 2022-10-09 09:33:07 +08:00
Zihao Mu
bb64db98d8
Further optimization of Conv2D, fused Conv_Add_Activation, bring latest code from ficus OpConv.fx. (#22401) 2022-08-26 12:57:25 +03:00
Alexander Alekhin
13a995cc1d Merge remote-tracking branch 'upstream/3.4' into merge-3.4 2022-04-02 19:45:44 +00:00
Alexander Alekhin
4d927e73f1 dnn(test): update OpenVINO tests 2022.1.0 2022-04-02 17:42:53 +00:00
Alexander Alekhin
8b4fa2605e Merge remote-tracking branch 'upstream/3.4' into merge-3.4 2021-12-03 12:32:49 +00:00
Alexander Alekhin
bd396e1fd5 dnn(test): re-enable tests which works with OpenVINO 2021.4.x (3.4) 2021-12-02 11:30:45 +00:00
Alexander Alekhin
57ee14d62d Merge remote-tracking branch 'upstream/3.4' into merge-3.4 2021-11-27 16:50:55 +00:00
Alexander Alekhin
985aa0423d dnn(test): update InferenceEngine tests 2021-11-26 18:46:26 +00:00
Alexander Alekhin
8fad85edda Merge remote-tracking branch 'upstream/3.4' into merge-3.4 2021-07-01 10:52:31 +00:00
Alexander Alekhin
6797fd65a5 dnn(test): update tests for OpenVINO 2021.4 2021-06-30 22:30:15 +00:00
Alexander Alekhin
35eaacd1db Merge remote-tracking branch 'upstream/3.4' into merge-3.4 2021-03-27 15:35:16 +00:00
Alexander Alekhin
26ea4760ad Merge pull request #19774 from aarongreig:aaron/dnn/oclTestAccuracyThresholds 2021-03-25 16:58:07 +00:00
Aaron Greig
f59917bea1 Introduce relaxed accuracy thresholds for CL target in some dnn tests. 
Partially addresses #9821
 2021-03-25 10:58:23 +00:00
Alexander Alekhin
b62d015285 Merge remote-tracking branch 'upstream/3.4' into merge-3.4 2021-03-24 18:58:46 +00:00
Alexander Alekhin
e56e4876e7 dnn(test): update tests for OpenVINO 2021.3 2021-03-24 14:50:42 +00:00
YashasSamaga
0f8ab0557e enable fusion tests, update thresholds and fix missed eltwise fusions 2020-11-21 17:35:20 +05:30
Alexander Alekhin
1b443219ed Merge remote-tracking branch 'upstream/3.4' into merge-3.4 2020-10-09 20:09:26 +00:00
Alexander Alekhin
6da05f7086 dnn(test): update tests for OpenVINO 2021.1 2020-10-08 10:22:31 +00:00
Alexander Alekhin
295afd5882 Merge remote-tracking branch 'upstream/3.4' into merge-3.4 2020-09-28 21:33:29 +00:00
Tomoaki Teshima
48368dc9a1 loosen threshold for Mali 2020-09-27 00:37:52 +09:00
Alexander Alekhin
45d073f889 Merge remote-tracking branch 'upstream/3.4' into merge-3.4 2020-02-26 20:09:03 +03:00
Dmitry Kurtaev
d8dea7896b
Merge pull request #16628 from dkurt:dnn_ngraph_custom_layers 
* Custom layers with nGraph

* nGraph: multiple outputs from nodes
 2020-02-26 17:51:18 +03:00
Alexander Alekhin
aa2777ed61 Merge remote-tracking branch 'upstream/3.4' into merge-3.4 2020-02-10 19:40:29 +03:00
Alexander Alekhin
8ecfb59930 dnn(test): skip failed ngraph tests 2020-02-07 22:43:40 +00:00
Alexander Alekhin
4cb9faf6c9 Merge remote-tracking branch 'upstream/3.4' into merge-3.4 2020-01-14 17:04:22 +03:00
Dmitry Kurtaev
8f1e36f7c1 Disable some tests for Myriad target of nGraph 
Add lightweight IE hardware targets checks

nGraph: Concat with paddings

Enable more nGraph tests

Restore FP32->FP16 for GPU plugin of IE

try to fix buildbot

Use lightweight IE targets check only starts from R4
 2020-01-13 15:35:47 +03:00
Yashas Samaga B L
1fac1421e5 Merge pull request #16010 from YashasSamaga:cuda4dnn-fp16-tests 
* enable tests for DNN_TARGET_CUDA_FP16

* disable deconvolution tests

* disable shortcut tests

* fix typos and some minor changes

* dnn(test): skip CUDA FP16 test too (run_pool_max)
 2019-12-20 16:36:32 +03:00
Alexander Alekhin
4b0132ed7a Merge remote-tracking branch 'upstream/3.4' into merge-3.4 2019-12-02 16:26:52 +03:00
Lubov Batanina
7523c777c5 Merge pull request #15537 from l-bat:ngraph 
* Support nGraph

* Fix resize
 2019-12-02 16:16:06 +03:00
Yashas Samaga B L
613c12e590 Merge pull request #14827 from YashasSamaga:cuda4dnn-csl-low 
CUDA backend for the DNN module

* stub cuda4dnn design

* minor fixes for tests and doxygen

* add csl public api directory to module headers

* add low-level CSL components

* add high-level CSL components

* integrate csl::Tensor into backbone code

* switch to CPU iff unsupported; otherwise, fail on error

* add fully connected layer

* add softmax layer

* add activation layers

* support arbitary rank TensorDescriptor

* pass input wrappers to `initCUDA()`

* add 1d/2d/3d-convolution

* add pooling layer

* reorganize and refactor code

* fixes for gcc, clang and doxygen; remove cxx14/17 code

* add blank_layer

* add LRN layer

* add rounding modes for pooling layer

* split tensor.hpp into tensor.hpp and tensor_ops.hpp

* add concat layer

* add scale layer

* add batch normalization layer

* split math.cu into activations.cu and math.hpp

* add eltwise layer

* add flatten layer

* add tensor transform api

* add asymmetric padding support for convolution layer

* add reshape layer

* fix rebase issues

* add permute layer

* add padding support for concat layer

* refactor and reorganize code

* add normalize layer

* optimize bias addition in scale layer

* add prior box layer

* fix and optimize normalize layer

* add asymmetric padding support for pooling layer

* add event API

* improve pooling performance for some padding scenarios

* avoid over-allocation of compute resources to kernels

* improve prior box performance

* enable layer fusion

* add const layer

* add resize layer

* add slice layer

* add padding layer

* add deconvolution layer

* fix channelwise  ReLU initialization

* add vector traits

* add vectorized versions of relu, clipped_relu, power

* add vectorized concat kernels

* improve concat_with_offsets performance

* vectorize scale and bias kernels

* add support for multi-billion element tensors

* vectorize prior box kernels

* fix address alignment check

* improve bias addition performance of conv/deconv/fc layers

* restructure code for supporting multiple targets

* add DNN_TARGET_CUDA_FP64

* add DNN_TARGET_FP16

* improve vectorization

* add region layer

* improve tensor API, add dynamic ranks

1. use ManagedPtr instead of a Tensor in backend wrapper
2. add new methods to tensor classes
  - size_range: computes the combined size of for a given axis range
  - tensor span/view can be constructed from a raw pointer and shape
3. the tensor classes can change their rank at runtime (previously rank was fixed at compile-time)
4. remove device code from tensor classes (as they are unused)
5. enforce strict conditions on tensor class APIs to improve debugging ability

* fix parametric relu activation

* add squeeze/unsqueeze tensor API

* add reorg layer

* optimize permute and enable 2d permute

* enable 1d and 2d slice

* add split layer

* add shuffle channel layer

* allow tensors of different ranks in reshape primitive

* patch SliceOp to allow Crop Layer

* allow extra shape inputs in reshape layer

* use `std::move_backward` instead of `std::move` for insert in resizable_static_array

* improve workspace management

* add spatial LRN

* add nms (cpu) to region layer

* add max pooling with argmax ( and a fix to limits.hpp)

* add max unpooling layer

* rename DNN_TARGET_CUDA_FP32 to DNN_TARGET_CUDA

* update supportBackend to be more rigorous

* remove stray include from preventing non-cuda build

* include op_cuda.hpp outside condition #if

* refactoring, fixes and many optimizations

* drop DNN_TARGET_CUDA_FP64

* fix gcc errors

* increase max. tensor rank limit to six

* add Interp layer

* drop custom layers; use BackendNode

* vectorize activation kernels

* fixes for gcc

* remove wrong assertion

* fix broken assertion in unpooling primitive

* fix build errors in non-CUDA build

* completely remove workspace from public API

* fix permute layer

* enable accuracy and perf. tests for DNN_TARGET_CUDA

* add asynchronous forward

* vectorize eltwise ops

* vectorize fill kernel

* fixes for gcc

* remove CSL headers from public API

* remove csl header source group from cmake

* update min. cudnn version in cmake

* add numerically stable FP32 log1pexp

* refactor code

* add FP16 specialization to cudnn based tensor addition

* vectorize scale1 and bias1 + minor refactoring

* fix doxygen build

* fix invalid alignment assertion

* clear backend wrappers before allocateLayers

* ignore memory lock failures

* do not allocate internal blobs

* integrate NVTX

* add numerically stable half precision log1pexp

* fix indentation, following coding style,  improve docs

* remove accidental modification of IE code

* Revert "add asynchronous forward"

This reverts commit 1154b9da9da07e9b52f8a81bdcea48cf31c56f70.

* [cmake] throw error for unsupported CC versions

* fix rebase issues

* add more docs, refactor code, fix bugs

* minor refactoring and fixes

* resolve warnings/errors from clang

* remove haveCUDA() checks from supportBackend()

* remove NVTX integration

* changes based on review comments

* avoid exception when no CUDA device is present

* add color code for CUDA in Net::dump
 2019-10-21 14:28:00 +03:00
Dmitry Kurtaev
e35fd463e7 Enable ENet with Inference Engine backend on CPU 2019-10-04 18:10:11 +03:00
Dmitry Kurtaev
6193e403e7 Enable some tests for 2019R2 2019-08-07 09:07:53 +03:00
Alexander Alekhin
894f208de3 dnn(test): replace SkipTestException with tags 2019-06-23 13:12:23 +00:00
Alexander Alekhin
13a782c039 test: fix usage of findDataFile() 
misused 'optional' mode
 2019-06-20 18:20:14 +03:00
Dmitry Kurtaev
eba696a41e Merge pull request #14792 from dkurt:dnn_ie_min_version_r5 
* Remove Inference Engine 2018R3 and 2018R4

* Fix 2018R5
 2019-06-14 18:17:02 +03:00
Dmitry Kurtaev
9c0af1f675 Enable more deconvolution layer configurations with IE backend 2019-06-03 08:15:52 +03:00
Alexander Alekhin
e0841f3d6e dnn(test-tags): add time / memory tags 2019-04-08 19:18:25 +00:00
Lubov Batanina
7d3d6bc4e2 Merge pull request #13932 from l-bat:MyriadX_master_dldt 
* Fix precision in tests for MyriadX

* Fix ONNX tests

* Add output range in ONNX tests

* Skip tests on Myriad OpenVINO 2018R5

* Add detect MyriadX

* Add detect MyriadX on OpenVINO R5

* Skip tests on Myriad next version of OpenVINO

* dnn(ie): VPU type from environment variable

* dnn(test): validate VPU type

* dnn(test): update DLIE test skip conditions
 2019-03-29 16:42:58 +03:00
Alexander Nesterov
74574dfae4 Added optimization fuse 2019-03-05 18:12:03 -01:00
Dmitry Kurtaev
ed710eaa1c Make Inference Engine R3 as a minimal supported version 2019-02-21 09:32:26 +03:00
Liubov Batanina
183c0fcab1 Changed condition for resize and lrn layers 2019-02-14 13:11:14 +03:00
Liubov Batanina
6b4becfd03 Enabled tests on IE backend 2019-02-11 12:39:28 +03:00
Dmitry Kurtaev
f0ddf302b2 Move Inference Engine to new API 2019-01-17 14:28:48 +03:00
Alexander Alekhin
14633bc857 Merge pull request #13497 from dkurt:dnn_torch_bn_train 2018-12-21 14:29:10 +00:00
Dmitry Kurtaev
840c892abd Batch normalization in training phase from Torch 2018-12-21 14:36:55 +03:00
Dmitry Kurtaev
59ce1d80a5 Fix dnn tests for Inference Engine R5 2018-12-21 12:33:30 +03:00
Dmitry Kurtaev
53f6198f27 Minor fixes in IE backend tests 2018-12-10 20:08:13 +03:00
Dmitry Kurtaev
b5c54e447c Extra hyperparameters for Intel's Inference Engine layers 2018-11-15 20:06:37 +03:00
Dmitry Kurtaev
e7015f6ae8 Fix ENet test 2018-10-19 17:43:26 +03:00
Dmitry Kurtaev
58ac3e09da Change default value of crop argument of blobFromImage from true to false 2018-09-12 19:02:58 +03:00