Commit Graph

118 Commits

Author SHA1 Message Date
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
Alexander Alekhin
2ad0487cec Merge remote-tracking branch 'upstream/3.4' into merge-3.4 2019-08-13 18:32:29 +00:00
Dmitry Kurtaev
6193e403e7 Enable some tests for 2019R2 2019-08-07 09:07:53 +03:00
Alexander Alekhin
174b4ce29d Merge remote-tracking branch 'upstream/3.4' into merge-3.4 2019-08-05 18:11:43 +00:00
Dmitry Kurtaev
a0c3bb70a9 Modify SSD from TensorFlow graph generation script to enable MyriadX 2019-07-26 13:57:08 +03:00
Alexander Alekhin
0cf479dd5c Merge remote-tracking branch 'upstream/3.4' into merge-3.4 2019-07-25 19:21:47 +00:00
Alexander Alekhin
416c693b3f dnn(test): OpenVINO 2019R2 2019-07-25 19:01:16 +03:00
Alexander Alekhin
f6c573880e Merge remote-tracking branch 'upstream/3.4' into merge-3.4 2019-07-12 18:45:06 +00:00
Lubov Batanina
8bcd7e122a Merge pull request #14842 from l-bat:ocv_conv3d
* Support Conv3D on OCV backend

* Add header

* Add perf tests

* Support pool3d

* Enable Resnet34_kinetics on OCV backend

* Add test

* Fix conv

* Optimize Conv2D
2019-07-11 20:13:52 +03:00
Alexander Alekhin
b95e93c20a Merge remote-tracking branch 'upstream/3.4' into merge-3.4 2019-06-26 20:19:04 +00:00
Alexander Alekhin
13a782c039 test: fix usage of findDataFile()
misused 'optional' mode
2019-06-20 18:20:14 +03:00
Alexander Alekhin
f3de2b4be7 Merge remote-tracking branch 'upstream/3.4' into merge-3.4 2019-06-05 19:11:52 +03:00
Dmitry Kurtaev
9c0af1f675 Enable more deconvolution layer configurations with IE backend 2019-06-03 08:15:52 +03:00
Alexander Alekhin
43467a2ac7 Merge remote-tracking branch 'upstream/3.4' into merge-3.4 2019-05-28 18:29:48 +00:00
Dmitry Kurtaev
44d21e5a79 Enable Slice layer on Inference Engine backend 2019-05-27 16:28:01 +03:00
Alexander Alekhin
4001346a30 Merge remote-tracking branch 'upstream/3.4' into merge-3.4 2019-04-03 19:33:52 +00:00
Alexander Alekhin
cafa010389 dnn(test): skip tests 2019-04-03 17:49:05 +03:00
Alexander Alekhin
33dde339fe Merge remote-tracking branch 'upstream/3.4' into merge-3.4 2019-04-01 18:11:55 +03:00
Alexander Alekhin
fcb07c64f3 cmake: fix build of dnn tests with shared common code
- don't share .cpp files (PCH support is broken)
2019-03-31 08:52:25 +00:00
Alexander Alekhin
7442100caa Merge remote-tracking branch 'upstream/3.4' into merge-3.4 2019-03-29 19:29:36 +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 Alekhin
c3cf35ab63 Merge remote-tracking branch 'upstream/3.4' into merge-3.4 2019-02-26 17:34:42 +03:00
Dmitry Kurtaev
ed710eaa1c Make Inference Engine R3 as a minimal supported version 2019-02-21 09:32:26 +03:00
Alexander Alekhin
8bde6aea4b Merge remote-tracking branch 'upstream/3.4' into merge-3.4 2019-02-19 19:49:13 +00:00
Liubov Batanina
183c0fcab1 Changed condition for resize and lrn layers 2019-02-14 13:11:14 +03:00
Alexander Alekhin
631b246881 Merge remote-tracking branch 'upstream/3.4' into merge-3.4 2019-01-22 18:00:34 +00:00
Dmitry Kurtaev
f0ddf302b2 Move Inference Engine to new API 2019-01-17 14:28:48 +03:00
Alexander Alekhin
e82e672a93 Merge remote-tracking branch 'upstream/3.4' into merge-3.4 2018-12-06 07:06:58 +00:00
Maksim Shabunin
fe459c82e5 Merge pull request #13332 from mshabunin:dnn-backends
DNN backends registry (#13332)

* Added dnn backends registry

* dnn: process DLIE/FPGA target
2018-12-05 18:11:45 +03:00
Alexander Alekhin
7fa7fa0226 Merge remote-tracking branch 'upstream/3.4' into merge-3.4 2018-11-21 08:33:39 +00:00
Dmitry Kurtaev
0d117312c9 DNN_TARGET_FPGA using Intel's Inference Engine 2018-11-19 11:41:43 +03:00
Alexander Alekhin
22dbcf98c5 Merge remote-tracking branch 'upstream/3.4' into merge-3.4 2018-11-17 14:17:35 +00:00
Alexander Alekhin
96c71dd3d2 dnn: reduce set of ignored warnings 2018-11-15 13:15:59 +03:00
Alexander Alekhin
edacd91a27 Merge remote-tracking branch 'upstream/3.4' into merge-3.4 2018-10-15 20:15:42 +00:00
tompollok
0b77600718 change area() emptiness checks to empty() 2018-10-13 21:35:10 +02:00
Alexander Alekhin
d74b98c3d9 Merge remote-tracking branch 'upstream/3.4' into merge-3.4 2018-09-04 18:39:03 +00:00
Jakub Golinowski
9f1218b00b Merge pull request #11897 from Jakub-Golinowski:hpx_backend
* Add HPX backend for OpenCV implementation
Adds hpx backend for cv::parallel_for_() calls respecting the nstripes chunking parameter. C++ code for the backend is added to modules/core/parallel.cpp. Also, the necessary changes to cmake files are introduced.
Backend can operate in 2 versions (selectable by cmake build option WITH_HPX_STARTSTOP): hpx (runtime always on) and hpx_startstop (start and stop the backend for each cv::parallel_for_() call)

* WIP: Conditionally include hpx_main.hpp to tests in core module
Header hpx_main.hpp is included to both core/perf/perf_main.cpp and core/test/test_main.cpp.
The changes to cmake files for linking hpx library to above mentioned test executalbles are proposed but have issues.

* Add coditional iclusion of hpx_main.hpp to cpp cpu modules

* Remove start/stop version of hpx backend
2018-08-31 16:23:26 +03:00
Alexander Alekhin
c557193b8c dnn(test): use dnnBackendsAndTargets() param generator 2018-08-31 15:11:58 +03:00
Alexander Alekhin
3e6b3a6856 dnn(perf): fix and merge Convolution tests
- OpenCL tests didn't run any OpenCL kernels
- use real configuration from existed models (the first 100 cases)
- batch size = 1
2018-08-31 15:02:19 +03:00
Dmitry Kurtaev
8e034053af Faster-RCNN from TensorFlow on CPU with Intel's Inference Engine backend 2018-08-01 11:29:58 +03:00
Dmitry Kurtaev
2c291bc2fb Enable FastNeuralStyle and OpenFace networks with IE backend 2018-06-09 15:57:12 +03:00
Dmitry Kurtaev
40765c5f8d Enable SSD models from TensorFlow with OpenCL plugin of Intel's Inference Engine 2018-06-08 16:55:21 +03:00
David
7175f257b5 Added ResizeBilinear op for tf (#11050)
* Added ResizeBilinear op for tf

Combined ResizeNearestNeighbor and ResizeBilinear layers into Resize (with an interpolation param).

Minor changes to tf_importer and resize layer to save some code lines

Minor changes in init.cpp

Minor changes in tf_importer.cpp

* Replaced implementation of a custom ResizeBilinear layer to all layers

* Use Mat::ptr. Replace interpolation flags
2018-06-07 16:29:04 +03:00
Dmitry Kurtaev
f3a6ae5f00 Wrap Inference Engine init to try-catch 2018-06-07 12:55:52 +03:00
Vadim Pisarevsky
3cbd2e2764 Merge pull request #11650 from dkurt:dnn_default_backend 2018-06-06 09:30:39 +00:00
Alexander Alekhin
6816495bee dnn(test): reuse test/test_common.hpp, eliminate dead code warning 2018-06-05 12:52:53 +03:00
Dmitry Kurtaev
b781ac7346 Make Intel's Inference Engine backend is default if no preferable backend is specified. 2018-06-04 18:31:46 +03:00
Dmitry Kurtaev
f96f934426 Update Intel's Inference Engine deep learning backend (#11587)
* Update Intel's Inference Engine deep learning backend

* Remove cpu_extension dependency

* Update Darknet accuracy tests
2018-05-31 14:05:21 +03:00
Li Peng
1b517a45ae add fp16 accuracy and perf test
Signed-off-by: Li Peng <peng.li@intel.com>
2018-05-16 22:45:07 +08:00
Dmitry Kurtaev
bd77d100e1 Enable some tests for clDNN plugin from Intel's Inference Engine 2018-04-20 10:47:46 +03:00
Dmitry Kurtaev
97fec07d96 Support YOLOv3 model from Darknet 2018-04-16 18:44:12 +03:00
Dmitry Kurtaev
709cf5d038 OpenCL GPU target for Inference Engine deep learning backend
Enable FP16 GPU target for DL Inference Engine backend.
2018-04-09 17:21:35 +03:00
Dmitry Kurtaev
7972f47ed4 Load networks from intermediate representation of Intel's Deep learning deployment toolkit. 2018-03-26 07:24:21 +03:00
Dmitry Kurtaev
7fe97376c2 MobileNet-SSD from TensorFlow 1.3 and Inception-V2-SSD using Inference Engine backend 2018-02-09 13:45:45 +03:00
Dmitry Kurtaev
ed94136548 OpenCV face detection network using Inference Engine backend 2018-02-06 17:53:24 +03:00
Alexander Alekhin
2a1f46c42d Merge pull request #9770 from alalek:refactor_test_files 2018-02-06 09:33:58 +00:00
Dmitry Kurtaev
10e1de74d2 Intel Inference Engine deep learning backend (#10608)
* Intel Inference Engine deep learning backend.

* OpenFace network using Inference Engine backend
2018-02-06 11:57:35 +03:00
Alexander Alekhin
4a297a2443 ts: refactor OpenCV tests
- removed tr1 usage (dropped in C++17)
- moved includes of vector/map/iostream/limits into ts.hpp
- require opencv_test + anonymous namespace (added compile check)
- fixed norm() usage (must be from cvtest::norm for checks) and other conflict functions
- added missing license headers
2018-02-03 19:39:47 +00:00
Alexander Alekhin
9b131b5f7e dnn(test): avoid calling of cv::setNumThreads() in tests directly
It is not necessary by default.
Also it breaks test system command-line parameters: --perf_threads / --test_threads
2017-12-27 15:16:41 +00:00
Dmitry Kurtaev
6aabd6cc7a Remove cv::dnn::Importer 2017-12-18 18:08:28 +03:00
Dmitry Kurtaev
ef0650179b Fix conv/deconv/fc layers FLOPS computation 2017-12-07 11:42:04 +03:00
Alexander Alekhin
d8a737b4b0 dnn: SSD performance test 2017-12-06 15:55:18 +03:00
pengli
e340ff9c3a Merge pull request #9114 from pengli:dnn_rebase
add libdnn acceleration to dnn module  (#9114)

* import libdnn code

Signed-off-by: Li Peng <peng.li@intel.com>

* add convolution layer ocl acceleration

Signed-off-by: Li Peng <peng.li@intel.com>

* add pooling layer ocl acceleration

Signed-off-by: Li Peng <peng.li@intel.com>

* add softmax layer ocl acceleration

Signed-off-by: Li Peng <peng.li@intel.com>

* add lrn layer ocl acceleration

Signed-off-by: Li Peng <peng.li@intel.com>

* add innerproduct layer ocl acceleration

Signed-off-by: Li Peng <peng.li@intel.com>

* add HAVE_OPENCL macro

Signed-off-by: Li Peng <peng.li@intel.com>

* fix for convolution ocl

Signed-off-by: Li Peng <peng.li@intel.com>

* enable getUMat() for multi-dimension Mat

Signed-off-by: Li Peng <peng.li@intel.com>

* use getUMat for ocl acceleration

Signed-off-by: Li Peng <peng.li@intel.com>

* use CV_OCL_RUN macro

Signed-off-by: Li Peng <peng.li@intel.com>

* set OPENCL target when it is available

and disable fuseLayer for OCL target for the time being

Signed-off-by: Li Peng <peng.li@intel.com>

* fix innerproduct accuracy test

Signed-off-by: Li Peng <peng.li@intel.com>

* remove trailing space

Signed-off-by: Li Peng <peng.li@intel.com>

* Fixed tensorflow demo bug.

Root cause is that tensorflow has different algorithm with libdnn
to calculate convolution output dimension.

libdnn don't calculate output dimension anymore and just use one
passed in by config.

* split gemm ocl file

split it into gemm_buffer.cl and gemm_image.cl

Signed-off-by: Li Peng <peng.li@intel.com>

* Fix compile failure

Signed-off-by: Li Peng <peng.li@intel.com>

* check env flag for auto tuning

Signed-off-by: Li Peng <peng.li@intel.com>

* switch to new ocl kernels for softmax layer

Signed-off-by: Li Peng <peng.li@intel.com>

* update softmax layer

on some platform subgroup extension may not work well,
fallback to non subgroup ocl acceleration.

Signed-off-by: Li Peng <peng.li@intel.com>

* fallback to cpu path for fc layer with multi output

Signed-off-by: Li Peng <peng.li@intel.com>

* update output message

Signed-off-by: Li Peng <peng.li@intel.com>

* update fully connected layer

fallback to gemm API if libdnn return false

Signed-off-by: Li Peng <peng.li@intel.com>

* Add ReLU OCL implementation

* disable layer fusion for now

Signed-off-by: Li Peng <peng.li@intel.com>

* Add OCL implementation for concat layer

Signed-off-by: Wu Zhiwen <zhiwen.wu@intel.com>

* libdnn: update license and copyrights

Also refine libdnn coding style

Signed-off-by: Wu Zhiwen <zhiwen.wu@intel.com>
Signed-off-by: Li Peng <peng.li@intel.com>

* DNN: Don't link OpenCL library explicitly

* DNN: Make default preferableTarget to DNN_TARGET_CPU

User should set it to DNN_TARGET_OPENCL explicitly if want to
use OpenCL acceleration.

Also don't fusion when using DNN_TARGET_OPENCL

* DNN: refine coding style

* Add getOpenCLErrorString

* DNN: Use int32_t/uint32_t instread of alias

* Use namespace ocl4dnn to include libdnn things

* remove extra copyTo in softmax ocl path

Signed-off-by: Li Peng <peng.li@intel.com>

* update ReLU layer ocl path

Signed-off-by: Li Peng <peng.li@intel.com>

* Add prefer target property for layer class

It is used to indicate the target for layer forwarding,
either the default CPU target or OCL target.

Signed-off-by: Li Peng <peng.li@intel.com>

* Add cl_event based timer for cv::ocl

* Rename libdnn to ocl4dnn

Signed-off-by: Li Peng <peng.li@intel.com>
Signed-off-by: wzw <zhiwen.wu@intel.com>

* use UMat for ocl4dnn internal buffer

Remove allocateMemory which use clCreateBuffer directly

Signed-off-by: Li Peng <peng.li@intel.com>
Signed-off-by: wzw <zhiwen.wu@intel.com>

* enable buffer gemm in ocl4dnn innerproduct

Signed-off-by: Li Peng <peng.li@intel.com>

* replace int_tp globally for ocl4dnn kernels.

Signed-off-by: wzw <zhiwen.wu@intel.com>
Signed-off-by: Li Peng <peng.li@intel.com>

* create UMat for layer params

Signed-off-by: Li Peng <peng.li@intel.com>

* update sign ocl kernel

Signed-off-by: Li Peng <peng.li@intel.com>

* update image based gemm of inner product layer

Signed-off-by: Li Peng <peng.li@intel.com>

* remove buffer gemm of inner product layer

call cv::gemm API instead

Signed-off-by: Li Peng <peng.li@intel.com>

* change ocl4dnn forward parameter to UMat

Signed-off-by: Li Peng <peng.li@intel.com>

* Refine auto-tuning mechanism.

- Use OPENCV_OCL4DNN_KERNEL_CONFIG_PATH to set cache directory
  for fine-tuned kernel configuration.
  e.g. export OPENCV_OCL4DNN_KERNEL_CONFIG_PATH=/home/tmp,
  the cache directory will be /home/tmp/spatialkernels/ on Linux.

- Define environment OPENCV_OCL4DNN_ENABLE_AUTO_TUNING to enable
  auto-tuning.

- OPENCV_OPENCL_ENABLE_PROFILING is only used to enable profiling
  for OpenCL command queue. This fix basic kernel get wrong running
  time, i.e. 0ms.

- If creating cache directory failed, disable auto-tuning.

* Detect and create cache dir on windows

Signed-off-by: Li Peng <peng.li@intel.com>

* Refine gemm like convolution kernel.

Signed-off-by: Li Peng <peng.li@intel.com>

* Fix redundant swizzleWeights calling when use cached kernel config.

* Fix "out of resource" bug when auto-tuning too many kernels.

* replace cl_mem with UMat in ocl4dnnConvSpatial class

* OCL4DNN: reduce the tuning kernel candidate.

This patch could reduce 75% of the tuning candidates with less
than 2% performance impact for the final result.

Signed-off-by: Zhigang Gong <zhigang.gong@intel.com>

* replace cl_mem with umat in ocl4dnn convolution

Signed-off-by: Li Peng <peng.li@intel.com>

* remove weight_image_ of ocl4dnn inner product

Actually it is unused in the computation

Signed-off-by: Li Peng <peng.li@intel.com>

* Various fixes for ocl4dnn

1. OCL_PERFORMANCE_CHECK(ocl::Device::getDefault().isIntel())
2. Ptr<OCL4DNNInnerProduct<float> > innerProductOp
3. Code comments cleanup
4. ignore check on OCL cpu device

Signed-off-by: Li Peng <peng.li@intel.com>

* add build option for log softmax

Signed-off-by: Li Peng <peng.li@intel.com>

* remove unused ocl kernels in ocl4dnn

Signed-off-by: Li Peng <peng.li@intel.com>

* replace ocl4dnnSet with opencv setTo

Signed-off-by: Li Peng <peng.li@intel.com>

* replace ALIGN with cv::alignSize

Signed-off-by: Li Peng <peng.li@intel.com>

* check kernel build options

Signed-off-by: Li Peng <peng.li@intel.com>

* Handle program compilation fail properly.

* Use std::numeric_limits<float>::infinity() for large float number

* check ocl4dnn kernel compilation result

Signed-off-by: Li Peng <peng.li@intel.com>

* remove unused ctx_id

Signed-off-by: Li Peng <peng.li@intel.com>

* change clEnqueueNDRangeKernel to kernel.run()

Signed-off-by: Li Peng <peng.li@intel.com>

* change cl_mem to UMat in image based gemm

Signed-off-by: Li Peng <peng.li@intel.com>

* check intel subgroup support for lrn and pooling layer

Signed-off-by: Li Peng <peng.li@intel.com>

* Fix convolution bug if group is greater than 1

Signed-off-by: Li Peng <peng.li@intel.com>

* Set default layer preferableTarget to be DNN_TARGET_CPU

Signed-off-by: Li Peng <peng.li@intel.com>

* Add ocl perf test for convolution

Signed-off-by: Li Peng <peng.li@intel.com>

* Add more ocl accuracy test

Signed-off-by: Li Peng <peng.li@intel.com>

* replace cl_image with ocl::Image2D

Signed-off-by: Li Peng <peng.li@intel.com>

* Fix build failure in elementwise layer

Signed-off-by: Li Peng <peng.li@intel.com>

* use getUMat() to get blob data

Signed-off-by: Li Peng <peng.li@intel.com>

* replace cl_mem handle with ocl::KernelArg

Signed-off-by: Li Peng <peng.li@intel.com>

* dnn(build): don't use C++11, OPENCL_LIBRARIES fix

* dnn(ocl4dnn): remove unused OpenCL kernels

* dnn(ocl4dnn): extract OpenCL code into .cl files

* dnn(ocl4dnn): refine auto-tuning

Defaultly disable auto-tuning, set OPENCV_OCL4DNN_ENABLE_AUTO_TUNING
environment variable to enable it.

Use a set of pre-tuned configs as default config if auto-tuning is disabled.
These configs are tuned for Intel GPU with 48/72 EUs, and for googlenet,
AlexNet, ResNet-50

If default config is not suitable, use the first available kernel config
from the candidates. Candidate priority from high to low is gemm like kernel,
IDLF kernel, basick kernel.

* dnn(ocl4dnn): pooling doesn't use OpenCL subgroups

* dnn(ocl4dnn): fix perf test

OpenCV has default 3sec time limit for each performance test.
Warmup OpenCL backend outside of perf measurement loop.

* use ocl::KernelArg as much as possible

Signed-off-by: Li Peng <peng.li@intel.com>

* dnn(ocl4dnn): fix bias bug for gemm like kernel

* dnn(ocl4dnn): wrap cl_mem into UMat

Signed-off-by: Li Peng <peng.li@intel.com>

* dnn(ocl4dnn): Refine signature of kernel config

- Use more readable string as signture of kernel config
- Don't count device name and vendor in signature string
- Default kernel configurations are tuned for Intel GPU with
  24/48/72 EUs, and for googlenet, AlexNet, ResNet-50 net model.

* dnn(ocl4dnn): swap width/height in configuration

* dnn(ocl4dnn): enable configs for Intel OpenCL runtime only

* core: make configuration helper functions accessible from non-core modules

* dnn(ocl4dnn): update kernel auto-tuning behavior

Avoid unwanted creation of directories

* dnn(ocl4dnn): simplify kernel to workaround OpenCL compiler crash

* dnn(ocl4dnn): remove redundant code

* dnn(ocl4dnn): Add more clear message for simd size dismatch.

* dnn(ocl4dnn): add const to const argument

Signed-off-by: Li Peng <peng.li@intel.com>

* dnn(ocl4dnn): force compiler use a specific SIMD size for IDLF kernel

* dnn(ocl4dnn): drop unused tuneLocalSize()

* dnn(ocl4dnn): specify OpenCL queue for Timer and convolve() method

* dnn(ocl4dnn): sanitize file names used for cache

* dnn(perf): enable Network tests with OpenCL

* dnn(ocl4dnn/conv): drop computeGlobalSize()

* dnn(ocl4dnn/conv): drop unused fields

* dnn(ocl4dnn/conv): simplify ctor

* dnn(ocl4dnn/conv): refactor kernelConfig localSize=NULL

* dnn(ocl4dnn/conv): drop unsupported double / untested half types

* dnn(ocl4dnn/conv): drop unused variable

* dnn(ocl4dnn/conv): alignSize/divUp

* dnn(ocl4dnn/conv): use enum values

* dnn(ocl4dnn): drop unused innerproduct variable

Signed-off-by: Li Peng <peng.li@intel.com>

* dnn(ocl4dnn): add an generic function to check cl option support

* dnn(ocl4dnn): run softmax subgroup version kernel first

Signed-off-by: Li Peng <peng.li@intel.com>
2017-10-02 15:38:00 +03:00
Alexander Alekhin
78788e1efb dnn(perf): update perf tests 2017-09-25 15:32:37 +03:00
Dmitry Kurtaev
5c43a394c5 Added performance test for Caffe framework 2017-08-27 19:40:58 +03:00
dkurt
70ff3804e9 Fix SqueezeNet Halide performance test 2017-07-24 10:45:04 +03:00
Alexander Alekhin
72a765d766 dnn: fix compilation of Halide tests 2017-06-29 16:36:34 +03:00
Alexander Alekhin
93729784bb dnn: move module from opencv_contrib
e6f63c7a38/modules/dnn
2017-06-26 13:41:51 +03:00