Alexander Alekhin
5c76f99fdd
Merge remote-tracking branch 'upstream/3.4' into merge-3.4
2020-09-05 19:37:38 +00:00
YashasSamaga
1df533c914
fix typo in fusion tests
2020-09-02 14:25:36 +05:30
Alexander Alekhin
ba147d2be2
Merge remote-tracking branch 'upstream/3.4' into merge-3.4
2020-08-26 15:51:25 +00:00
Alexander Alekhin
792722865f
Merge pull request #17919 from zhaoyue-zephyrus:flownet2_with_anysize
2020-08-26 11:43:17 +00:00
Alexander Alekhin
b45273eccb
Merge remote-tracking branch 'upstream/3.4' into merge-3.4
2020-08-14 19:45:45 +00:00
Yashas Samaga B L
2171cae8ff
Merge pull request #17976 from YashasSamaga:dnn-fusion-tests-fix-ocl
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dnn: add exhaustive fusion tests, enable more eltwise fusions
* add eltwise fusion tests, enable more eltwise fusions
* merge weighted eltwise tests with eltwise tests
2020-08-13 10:55:41 +00:00
zhaoyue-zephyrus
e231be86b7
support flownet2 with arbitary input size
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revise default proto to match the filename in documentations
fix a bug
beautify python codes
fix bug
beautify codes
add test samples with larger/smaller size
remove unless code
using bytearray without creating tmp file
remove useless codes
2020-08-12 00:50:58 +08:00
Alexander Alekhin
fa25faa2d2
Merge remote-tracking branch 'upstream/3.4' into merge-3.4
2020-08-06 14:15:52 +00:00
Dmitry Kurtaev
cf8f65d806
Do not use size_t for nGraph layers
2020-08-02 20:50:44 +03:00
Alexander Alekhin
9b7b22ee0e
Merge remote-tracking branch 'upstream/3.4' into merge-3.4
2020-07-16 20:13:27 +00:00
Alexander Alekhin
b2ebd37ee2
Merge pull request #17856 from alalek:dnn_openvino_2020.4.0
2020-07-16 20:08:00 +00:00
Alexander Alekhin
81e027eef7
dnn: fix OpenCL implementation of Slice layer
2020-07-16 04:33:52 +00:00
Alexander Alekhin
1c371d07b5
dnn(test): adjust tests for OpenVINO 2020.4
2020-07-15 23:47:40 +00:00
Alexander Alekhin
21e28adb87
Merge remote-tracking branch 'upstream/3.4' into merge-3.4
2020-05-22 19:50:14 +00:00
Liubov Batanina
d991c22090
Merge pull request #16575 from l-bat:flownet2
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Support FlowNet2 model
* Support DataAugmentation layer
* Fix warnings
* Fix comments
* Support Correlation layer
* TEST
* Support Correlation layer
* Supported Accum and FlowWarp layers
* Supported ChannelNorm layer
* Supported Resample with inputs.size() > 1
* Fixed comments
* Refactoring
* Added tests
* Add resample test
* Added asserts in resize layer
* Updated DataAugmentation layer
* Update convolution layer
* Refactoring
* Fix data augmentation layer
* Fix caffe importer
* Fix resize
* Switch to Mat ptr
* Remove useless resize type
* Used ResizeLayer in Accum
* Split ChannelNormLayer
* Delete duplicate assert
* Add sample
* Fix sample
* Added colormap
2020-05-19 12:29:50 +00:00
Alexander Alekhin
593af7287b
Merge remote-tracking branch 'upstream/3.4' into merge-3.4
2020-05-18 17:50:16 +00:00
Dmitry Kurtaev
df305e83fa
Fix BatchNorm reinitialization after fusion
2020-05-13 22:15:36 +03:00
Alexander Alekhin
09799402f9
Merge remote-tracking branch 'upstream/3.4' into merge-3.4
2020-05-06 19:53:51 +00:00
Dmitry Kurtaev
8b13b85c5e
dnn: Slice with variable input shapes
2020-05-05 13:35:17 +03:00
Alexander Alekhin
225566da7b
Merge remote-tracking branch 'upstream/3.4' into merge-3.4
2020-02-04 19:49:24 +03:00
Dmitry Kurtaev
005f38fb45
Fix dnn::ResizeLayer to manage varying input shapes
2020-02-04 09:06:17 +03:00
Alexander Alekhin
2ced568d34
Merge pull request #16220 from YashasSamaga:cuda4dnn-roi-pooling-test_fix-optim
2020-01-29 20:57:15 +00:00
Yashas Samaga B L
d85e67d3ec
Merge pull request #16063 from YashasSamaga:cuda4dnn-shortcut-unequal
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support eltwise sum with different number of input channels in CUDA backend
* add shortcut primitive
* add offsets in shortcut kernel
* skip tests involving more than two inputs
* remove redundant modulus operation
* support multiple inputs
* remove whole file indentation
* skip acc in0 trunc test if weighted
* use shortcut iff channels are unequal
2020-01-16 21:54:00 +03:00
YashasSamaga
fd369a5004
fix and optimize ROIPooling
2020-01-15 22:53:48 +05:30
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
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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
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* 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
92b9888837
Merge remote-tracking branch 'upstream/3.4' into merge-3.4
2019-12-12 13:02:19 +03:00
Alexander Alekhin
5ee7abbe3c
Merge pull request #16088 from alalek:dnn_eltwise_layer_different_src_channels
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dnn(eltwise): fix handling of different number of channels
* dnn(test): reproducer for Eltwise layer issue from PR16063
* dnn(eltwise): rework support for inputs with different channels
* dnn(eltwise): get rid of finalize(), variableChannels
* dnn(eltwise): update input sorting by number of channels
- do not swap inputs if number of channels are same after truncation
* dnn(test): skip "shortcut" with batch size 2 on MYRIAD targets
2019-12-11 20:16:58 +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
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* Support nGraph
* Fix resize
2019-12-02 16:16:06 +03:00
Alexander Alekhin
055ffc0425
Merge remote-tracking branch 'upstream/3.4' into merge-3.4
2019-10-24 18:21:19 +00:00
Yashas Samaga B L
613c12e590
Merge pull request #14827 from YashasSamaga:cuda4dnn-csl-low
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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
af61a15839
Fix Darknet eltwise
2019-10-19 12:54:15 +03:00
Dmitry Kurtaev
adbd613660
Enable Eltwise layer with different numbers of inputs channels
2019-10-18 18:51:52 +03:00
Alexander Alekhin
7ce9428e96
Merge pull request #15580 from smbz:dnn-lstm-reverse
2019-09-25 15:54:06 +00:00
Andrew Ryrie
b88435fdc2
dnn: Allow LSTM layer to operate in reverse direction
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This is useful for bidirectional LSTMs.
2019-09-25 14:12:43 +01:00
Dmitry Kurtaev
ba703157cf
Merge pull request #15063 from dkurt:dnn_ie_ocv_layers
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* Wrap unsupported by IE layers as custom layers
* Replace pointers to layers blobs to their shapes
* Enable Faster R-CNN with IE backend on CPU
2019-09-03 18:58:57 +03:00
Alexander Alekhin
b584c23061
Merge pull request #15158 from dkurt:fix_tf_ssd_configs
2019-08-02 16:08:55 +00:00
Lubov Batanina
5a6b23e8f3
Support for several min and max sizes in PriorBox layer (Merge pull request #15076 )
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* Support for several min and max sizes in PriorBox layer
* Fix minSize
* Check size
* Modify initInfEngine
* Fix tests
* Fix IE support
* Add priorbox test
* Remove inputs
2019-07-30 17:23:47 +03:00
Dmitry Kurtaev
77d4e3e8d2
Fix 2019R2 tests
2019-07-27 13:30:15 +03:00
Dmitry Kurtaev
75f4c1abf2
Enable some tests for Inference Engine backend
2019-06-28 15:52:31 +03:00
Alexander Alekhin
894f208de3
dnn(test): replace SkipTestException with tags
2019-06-23 13:12:23 +00:00
Dmitry Kurtaev
eba696a41e
Merge pull request #14792 from dkurt:dnn_ie_min_version_r5
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* Remove Inference Engine 2018R3 and 2018R4
* Fix 2018R5
2019-06-14 18:17:02 +03:00
Alexander Alekhin
8483801eab
dnn: use OpenVINO 2019R1 defines
2019-04-03 15:39:47 +03:00
Lubov Batanina
7d3d6bc4e2
Merge pull request #13932 from l-bat:MyriadX_master_dldt
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* 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
Dmitry Kurtaev
ed710eaa1c
Make Inference Engine R3 as a minimal supported version
2019-02-21 09:32:26 +03:00
Alexander Alekhin
f67b197d49
Merge pull request #13738 from dkurt:dnn_ie_lock_shared_plugins
2019-02-06 12:09:58 +00:00
Dmitry Kurtaev
bc4e471847
Add a mutex for shared Inference Engine plugins
2019-02-05 19:26:58 +03:00
Dmitry Kurtaev
c918ac298c
Fix IE tests
2019-01-31 14:14:38 +03:00