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38 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
95d9cfb5c3 static analysis issues 2019-06-20 13:55:20 +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
Liubov Batanina
dfa753c6b4 Support OCV backend 2019-05-14 16:44:57 +03:00
Liubov Batanina
dadb1473c1 Add BatchNorm3d layer 2019-05-14 12:44:48 +03:00
Dmitry Kurtaev
ca5976e3d4 Fix IE backend considering future changes. 2019-02-18 19:26:04 +03:00
Dmitry Kurtaev
f0ddf302b2 Move Inference Engine to new API 2019-01-17 14:28:48 +03:00
Alexander Alekhin
96c71dd3d2 dnn: reduce set of ignored warnings 2018-11-15 13:15:59 +03:00
catree
10b482ff1e Fix code and missing intrin header. Remove useless header. 2018-11-14 19:00:59 +01:00
Alexander Alekhin
9d02d42afe dnn(ocl4dnn): don't use getUMat() 
especially in CPU only processing
 2018-10-05 15:24:51 +03:00
Dmitry Kurtaev
24ab751547 Merge pull request #12565 from dkurt:dnn_non_intel_gpu 
* Remove isIntel check from deep learning layers

* Remove fp16->fp32 fallbacks where it's not necessary

* Fix Kernel::run to prevent localsize > globalsize
 2018-09-26 16:27:00 +03:00
Hamdi Sahloul
a39e0daacf Utilize CV_UNUSED macro 2018-09-07 20:33:52 +09:00
Dmitry Kurtaev
d486204a0d Merge pull request #12264 from dkurt:dnn_remove_forward_method 
* Remove a forward method in dnn::Layer

* Add a test

* Fix tests

* Mark multiple dnn::Layer::finalize methods as deprecated

* Replace back dnn's inputBlobs to vector of pointers

* Remove Layer::forward_fallback from CV_OCL_RUN scopes
 2018-09-06 13:26:47 +03:00
Alexander Alekhin
d2e08a524e core: repair CV_Assert() messages 
Multi-argument CV_Assert() is accessible via CV_Assert_N() (with malformed messages).
 2018-08-15 17:43:10 +03:00
Dmitry Kurtaev
be08730cd6 MVN layer using Intel's Inference Engine backend 2018-08-02 17:49:03 +03:00
Dmitry Kurtaev
7d727ac2fb Fuse top layers to batch normalization 2018-06-09 18:06:53 +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
Maksim Shabunin
895e10c317 dnn: fixed IE support on Windows 2018-05-23 12:46:14 +03:00
Li Peng
ba5e8befa9 fp16 ocl support for more layers 
Signed-off-by: Li Peng <peng.li@intel.com>
 2018-05-16 22:45:04 +08:00
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
Alexander Alekhin
1060c0f439 dnn: apply CV_OVERRIDE/CV_FINAL 2018-03-28 18:43:27 +03:00
Alexander Alekhin
9e0dee1259 Merge pull request #11112 from alalek:cmake_src_include_fix 2018-03-27 13:06:48 +00:00
Dmitry Kurtaev
e8fe6ee4e3 Fix prior box generation in case of squared proposals. 
Fix batch norm in training phase.
 2018-03-23 09:44:59 +03:00
Alexander Alekhin
6c051a55e5 cmake: don't add include <module>/src directory to avoid conflicts 
during opencv_world builds
 2018-03-19 11:14:15 +03:00
Dmitry Kurtaev
ab20d2a3fc Update assertions in batch norm layer 2018-03-12 10:53:06 +03:00
Alexander Alekhin
1b83bc48a1 dnn: make OpenCL DNN code optional 2018-03-01 12:12:40 +03:00
Dmitry Kurtaev
ed94136548 OpenCV face detection network using Inference Engine backend 2018-02-06 17:53:24 +03:00
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
Vadim Pisarevsky
713ec7be45 Merge pull request #10746 from dkurt:dnn_batch_norm_from_nvidia_caffe 2018-02-01 13:22:09 +00:00
Li Peng
83b16ab7b7 fix extra spaces in build option 
Signed-off-by: Li Peng <peng.li@intel.com>
 2018-02-01 17:46:11 +08:00
Dmitry Kurtaev
844f1d0281 Fix Batch Normalization layer imported from NVIDIA Caffe. 2018-01-31 16:25:45 +03:00
Li Peng
2493083935 mvn, batch_norm and relu layer fusion 
Signed-off-by: Li Peng <peng.li@intel.com>
 2018-01-25 18:57:05 +08:00
Li Peng
4189214d04 batch_norm layer ocl update 
use a batch_norm ocl kernel to do the work

Signed-off-by: Li Peng <peng.li@intel.com>
 2018-01-16 19:01:58 +08:00
Li Peng
e3b42bf93b batch_norm and blank layer ocl implementation 
Signed-off-by: Li Peng <peng.li@intel.com>
 2018-01-09 21:58:46 +08:00
Dmitry Kurtaev
bbbec300a6 nn.BatchNormalization and nn.Dropout layers from Torch 2017-12-04 12:57:21 +03:00
Li Peng
8f99083726 Add new layer forward interface 
Add layer forward interface with InputArrayOfArrays and
OutputArrayOfArrays parameters, it allows UMat buffer to be
processed and transferred in the layers.

Signed-off-by: Li Peng <peng.li@intel.com>
 2017-11-09 15:59:39 +08:00
Alexander Alekhin
ed10383359 dnn: added trace macros 2017-06-28 14:57:26 +03:00
Alexander Alekhin
93729784bb dnn: move module from opencv_contrib 
e6f63c7a38/modules/dnn
 2017-06-26 13:41:51 +03:00