* Remove fp16 of Convert layer test from skip_tests.config.cpp as it works now
* update repo
* add initial op impl check tests
* add op imple check tests
* add op impl check tests
* add rnn cell based ops
* modify lstmsequence
* update rnn cell base op test
* add priorbox, priorboxclustered, proposal
* add ROIAlign to ReverseSequence
* add Roll to ScatterElementsUpdate
* add select to swish tests
* add tensoriterator to variadicsplit test
* temporary block of LSTMCell v1 due to crash in mkldnn
* use ov namespace instead of ngraph as possible
* update indexing of vector array
* update multiple parameter vector
* add loop test
* fix cpplint errors
* fix build error
* Fix in Preprocessing python bindings - add correct default arguments for:
- PreProcessSteps::convert_element_type
- PostProcessSteps::convert_element_type
- InputTensorInfo::set_color_format
Otherwise, python users must always specify optional params
E.g. instead of writing `tensor().set_color_format(ColorFormat.RGB)` python users will have to write `tensor().set_color_format(ColorFormat.RGB, [])`
* Corrected 'help' output
* Exposing 'openvino.runtime.Type.undefined' and use it in 'convert_element_type' documentation
* Fixed Apple install
* Update path to libs in setupvars.sh
* Fix IE_CPACK_RUNTIME_PATH for Apple
* Fix wheels packaging
Co-authored-by: Alexey Suhov <alexey.suhov@intel.com>
* [DOCS] hddl update
include info on hddl and myriad working at the same time
* Update docs/OV_Runtime_UG/supported_plugins/MYRIAD.md
Co-authored-by: Andrey Zaytsev <andrey.zaytsev@intel.com>
* Update HDDL.md
* Update MYRIAD.md
Co-authored-by: Ilya Lavrenov <ilya.lavrenov@intel.com>
Co-authored-by: Andrey Zaytsev <andrey.zaytsev@intel.com>
* Added inputs argument to all compare() function overloads
* Rewritten compare() function for NMS
* Implemented sorting by name of expected outputs
* Implemented sorting by name of actual outputs
* Added accounting for simultaneous dynamism and the need to convert outputs in Template plugin
* Added a separate case to the GetBlob function for correct dimensions
* Rewritten Expected outputs sorting to work correctly on cpuFuncTests
* Fixing code style problems
* Implemented sorting by name of actual outputs for functional tests
* Debug prints removed
* Replacing a raw pointer with a vector
* Fixing code style problems
* Shifting the sorting place Expected outputs
* Added sorting of Expected exits in one more place
* Quality transition to SLT2.0
* Removing unnecessary code after SLT2.0
* Fix soft_nms_sigma argument
* Removing unnecessary parts after SLT2.0
* Remove unnecessary outputs sorting
* Removing parts from the code for debugging
* Fix for NMS
* Trying to make CI green
* Checking test passage without adding convert precision
* Checking CI
* There is an algorithm that adds Convert only if there is f16, fp16 in inputs
* Add Convert Op in cases where inputs are not already installed f32
* Check that the CI will go away if you put everything back
* Revert changes, validate f32 change on ci
* Adding Convert f16-f32 only if there is a function parameter of type f16
* The presence of f16/bf16 as a parameter type is now mandatory to add Convert
* Added prints for params, inputs, outputs
* Logic checking the absence of Convert
* Cosmetic fixes
* Setting the correct value for selected_scores_type NMS-5
* Fix bf
* Increased readability
* Missing parts added
* Removed the static for the vector
* [MO] Clean-up MO cmd-line options
Remove the following Model Optimizer deprecated options that are no longer used for several releases: disable_fusing, disable_gfusing, generate_deprecated_IR_V7,
legacy_ir_generation, keep_shape_ops, move_to_preprocess
Deprecate through CLI the following options for which functionality triggered from POT or automatically: disable_weights_compression, disable_nhwc_to_nchw,
disable_resnet_optimization, finegrain_fusing.
Correct and extend description of each MO option to be printed during model conversion.
Signed-off-by: Roman Kazantsev <roman.kazantsev@intel.com>
* Correct documentation about input shapes
Signed-off-by: Roman Kazantsev <roman.kazantsev@intel.com>
* Perform final corrections in documentation
Signed-off-by: Roman Kazantsev <roman.kazantsev@intel.com>
* Remove legacy_ir_generation overall
Signed-off-by: Roman Kazantsev <roman.kazantsev@intel.com>
* Clean-up tests from deprecated options
Signed-off-by: Roman Kazantsev <roman.kazantsev@intel.com>
* Recover disable_fusing option as deprecated
Signed-off-by: Roman Kazantsev <roman.kazantsev@intel.com>
* Fix keys for static_shape and extensions
Signed-off-by: Roman Kazantsev <roman.kazantsev@intel.com>
* Remove extension key that does not work
Signed-off-by: Roman Kazantsev <roman.kazantsev@intel.com>
* Apply feedback: remove disable_gfusing, correct docs
Signed-off-by: Roman Kazantsev <roman.kazantsev@intel.com>
* Recover disable_fusing option for unit-tests
Signed-off-by: Roman Kazantsev <roman.kazantsev@intel.com>
* Apply feedback for documentation
Signed-off-by: Roman Kazantsev <roman.kazantsev@intel.com>
* Apply feedback about parameters use_legacy_frontend and use_new_frontend
Signed-off-by: Roman Kazantsev <roman.kazantsev@intel.com>
* DO minor fixes for indentation of MO logs
Signed-off-by: Roman Kazantsev <roman.kazantsev@intel.com>
* Revert log.error for fallback message
Signed-off-by: Roman Kazantsev <roman.kazantsev@intel.com>
* Revert disable_weights_compression parameter for tests
Signed-off-by: Roman Kazantsev <roman.kazantsev@intel.com>
* Fixed some comments about transformations
* Changed transformation guide
* Fixed typo
* Moved transformation doc to extensibility
* Moved images to Extensibility_UG
* Added separate document for each pass
* Added see also section
* Fixed comments
* Checking compatibility between 'pyopenvino' and 'libopenvino' on 'import phase'
This fix is to prevent undefined behavior when user loads OpenVINO from python, but pyopenvino loads different version of 'libopenvino'
This may happen if user has several releases installed and played around PATH/PYTHONPATH environment variables.
In such case, user may have undefined behavior - application may crash in the middle of the usage or use incorrect release.
Fix checks build versions for pyopenvino and ov::get_openvino_version. If mismatch occurs, exception is thrown.
This logic is disabled if user has built OpenVINO locally, experienced developers probably know what they're doing, so if version has 'custom_' prefix - this logic is disabled
* Removed custom logic for CI_BUILD_NUMBER, it is reused from already included version.cmake
* Use addVersionDefines macro
* Update samples and samplers with the new DataLoader format
* Update with utils
* Pylint updates
* Update metric with the exception
* Pylint
* Update with the exception
* Pylint
* Revert index sampler changes
* Update ImageLoader & SimplifiedEngine
* Update with the different solution
* Remove utils
* Pylint
* Remove list wrapping
* Remove list from meta_data
* Improve `-o` and `-oname` flags
* Apply clang-format tool
* fix saving output files
* Apply clang-format
* Fix error when `-oname` not specified
* apply clang format
* Fix error `-oname`
* Use output name with port to find model output
* fix comment line breaking
* fix comparison with reference for multiple outputs
* Fix output name printing error
* try to fix clang format
* fix problem with bs > 1
* minimal change to rerun test pipeline
* clang format
* Revert "Fix error `-oname`"
This reverts commit c33d5f16e8.
* Used new config for streams and threads
* Fixed review coments in ba
* format fix
* fixed hello_query_device
* Added STL string io
* fixed tests
* Fixed test
* Fixed build
* fixed format
* Fixed build
* try fix win
* other any io specialization
* Fixed after merge
* renamed streams
* build fixed
* fixed build
* fixed format
* fix for old mac build
* Fixed type of exception
* test fix
* Added ov configuration test
* Added common OV properties tests
* fix mklnn
* fixed foramat
* merge conflicts
* Remoed compile_model tests
* removed duplicated test
* [GPU] Enable deconv with oneDNN
remove post-op data_type into oneDNN.
Signed-off-by: hyunback <hyunback.kim@intel.com>
* Update to use data_type in conv sum post-op.
Signed-off-by: hyunback <hyunback.kim@intel.com>
* checking the network batchability (internal helper func on top of batch tracking) before doing hetero
* more general logic with respect to batch-ability of the network
* a dynamism check that I've owed from the PR-10560
* using the DO-detached mechanism for early hetero exit, also fixed this flag in the Batching plugin (although minor, as the DO is removed by HETERO)
* adding the dimension tracking logic depending on whether implicitly/expicitly the auto-batching is enabled
* changed the DetectionOutput affinity markup to go over results, also accomodate Convert, so only 2 subgraphs are made by the HETERO
* installing-openvino-yocto: fix documentation links
Point to the new Yocto docs website.
Signed-off-by: Anuj Mittal <anuj.mittal@intel.com>
* Update installing-openvino-yocto.md
* installing-openvino-yocto: add step to checkout specific branch
Request users to checkout specific branch of meta-intel where this
version of OpenVINO is available.
Signed-off-by: Anuj Mittal <anuj.mittal@intel.com>
Co-authored-by: Yuan Xu <yuan1.xu@intel.com>
Co-authored-by: Anuj Mittal <anuj.mittal@intel.com>
Co-authored-by: Yuan Xu <yuan1.xu@intel.com>
* Revised unique ID setting scheme. Previously it was using program id to distinguish the loop body networks' id.
However, it results in cl cache miss for same network loaded multiple time, because program ids are differnt.
Now revised it to use parent primitive id instead of program_id for unique id of nodes in body networks.
* Revised adding unique_id to entry points to have a temporal number as unique id
* Revert the canceld change
* Added test to check whether two networks loaded from same function creates same cl cache
Transformation insert Transpose for MatMul's weights and
sets its transpose_b attribute to true.
If executed by MO, it helps to reduce LoadNetwork time on CPU plugin,
since ConvertMatMulToFC doesn't have to insert Transpose by itself.
Ticket: 78635
* support config key device priority
for example:
if AUTO:CPU,GPU
the priority of CPU will be higher than GPU
Signed-off-by: Hu, Yuan2 <yuan2.hu@intel.com>
* add test and fix compile and test error
Signed-off-by: Hu, Yuan2 <yuan2.hu@intel.com>
* add an info for device priority and add lost [AUTOPLUGIN] on log
Signed-off-by: Hu, Yuan2 <yuan2.hu@intel.com>
* parseMetaDevice return all DEVICE of GPU, when use AUTO:GPU
Signed-off-by: Hu, Yuan2 <yuan2.hu@intel.com>
* fix compile issue
Signed-off-by: Hu, Yuan2 <yuan2.hu@intel.com>
* modify test and add test case, fix code issue
Signed-off-by: Hu, Yuan2 <yuan2.hu@intel.com>
* fix a bug and mutli with HETERO test failed
Signed-off-by: Hu, Yuan2 <yuan2.hu@intel.com>
* fix mock test faild issue
Signed-off-by: Hu, Yuan2 <yuan2.hu@intel.com>
* fix misprint
Signed-off-by: Hu, Yuan2 <yuan2.hu@intel.com>
* Disable AUTO:MYRIAD case
MYRIAD/CoreThreadingTests.smoke_QueryNetwork/targetDevice=MULTI_config=MULTI_DEVICE_PRIORITIES:MYRIAD_
faild on windows
the error is
myriadFuncTests-0 INFO: [E:] [BSL] found 0 ioexpander device
Signed-off-by: Hu, Yuan2 <yuan2.hu@intel.com>
* use ov::device::priorities key in this PR
Signed-off-by: Hu, Yuan2 <yuan2.hu@intel.com>
* fix a logic bug in key_network_priority after enable device priority
add test case cover it
Signed-off-by: Hu, Yuan2 <yuan2.hu@intel.com>
* [MO] Upgrade TensorFlow version dependency due to SNYK hits
Signed-off-by: Roman Kazantsev <roman.kazantsev@intel.com>
* Still use 2.5.0 TensorFlow for Python 3.6 and older
Signed-off-by: Roman Kazantsev <roman.kazantsev@intel.com>
* Upgrade protobuf to 3.19.4
* Upgdate precompiled protoc version
* Update protobuf to v3.18.2
Updating further peding this fix to be released
https://github.com/protocolbuffers/protobuf/pull/9437
* Disable warnings for protobuf
* Fixing SetUp for SLT tests of ShapeOF
* Attempting to pass outputPrecision into the test
* Correcting deficiencies, taking into account in the name of the test of the output precision
* remove formatTimeMilli from time_utils.cpp
* add traceCallStacks test case
* add traceCallStacks test case in format_test.cpp
* add param:"test" to function TraceCallStacks()
* rollback file in master branch
* add traceCallStacks test case in format_test.cpp
* remove formatTimeMilli from time_utils.cpp and add traceCallStacks test case in format_test.cpp
[GPU] Enable shuffle and fsv32 in implicit concat
* Support shuffle fsv32
* Check feature depths in first input depedency.
* Add to select onednn convolution in case block format in get_preferred_impl_type func.
Signed-off-by: hyunback <hyunback.kim@intel.com>
* Initial commit. Need to remove debug code
* Remove extra flags. Fix comparation in the matchers
* Fix small issue with the default args
* Update eltwise.hpp
* Update ov_subgraph.cpp
* Optimized any compilation time
* Fixed Any compilation time
* any::addressof
* reverted
* Fixed read write
* format fix
* Fixed build
* format fix
* Moved any tests back
* removed inline
* fix format
* used static inline
* format fix
* removed inline static
* fixed merge confkicts
After enabling deconv b32 onednn, colorization-siggraph f16 b32 has regresison,
Fix it. Add to check sum post ops in case deconv onednn.
Signed-off-by: hyunback <hyunback.kim@intel.com>
* Added info on DockerHub CI Framework
* Feature/azaytsev/change layout (#3295)
* Changes according to feedback comments
* Replaced @ref's with html links
* Fixed links, added a title page for installing from repos and images, fixed formatting issues
* Added links
* minor fix
* Added DL Streamer to the list of components installed by default
* Link fixes
* Link fixes
* ovms doc fix (#2988)
* added OpenVINO Model Server
* ovms doc fixes
Co-authored-by: Trawinski, Dariusz <dariusz.trawinski@intel.com>
* Updated openvino_docs.xml
* Updated the link to software license agreements
* Revert "Updated the link to software license agreements"
This reverts commit 706dac500e.
* Removed the Intel logo
Co-authored-by: Trawinski, Dariusz <dariusz.trawinski@intel.com>
- Replace find with compare func to avoid dumping all layers that contain layer name
Signed-off-by: Andrew Kwangwoong Park <andrew.kwangwoong.park@intel.com>
When post-op has pattern like below, binary_mul was ignored previously.
1. binary_add
2. eltwise_linear
3. binary_mul
4. binary_add
It happens when prev_post_op_idx == 2, cur_post_op_idx == 4.
prev_post_op_idx was supposed to proceed to idx 3, but it did not.
* Use tensor names instead of friendly names, handle one output tensor to several Result ops case
* fix python tests
* fix python test
* fix incorrect merge
* remove redundant files
* fix variable names generation, fix python test
* Apply review comments
* fix python test
Even though it is not possible to hit into this situation using existing plugins - there is theoretical possibility that some plugin may return 'nullptr' as it is allowed.
So this check shall remain in generic part which should not rely on plugin-specific behavior
* handle 'and' marker in requirements
* Revert "handle 'and' marker in requirements"
This reverts commit 952bb949ca.
* moved importlib-metadata from requirements.txt into setup.py
* Remove fp16 of Convert layer test from skip_tests.config.cpp as it works now
* update repo
* add initial op reference code of TensorIterator with LSTM body function
* add GRU/RNN case in setup
* add all other test cases
* add visitor api test
* remove unnecessary header files
* fix clang-format issue
* fix copyright year and remove ngraph_helper namespace
* rename ti.cpp to tensor_iterator.cpp in core unit test
* apply suggestions
* [CPU] Add transformation that aligns elementwise input ranks
* fix tests - check also aBcd16b format
* add support for fq
* add test for sqr diff
* move to moc transformations
* fix tests
* align only for numpy autobroadcast type
* fix fetching autob from fq
* [CPU] Eltwise tests corrected & callback for CPU removed
* remove transformation callback call
* revert changes to getMKLDNNOutputMemoryFormats
* remove comment
* use single wrap_type
Co-authored-by: Vladislav Golubev <vladislav.golubev@intel.com>
* [DOCS] add minor changes to install guides
[DOCS] add minor changes to install guides
[DOCS] add minor changes to install guides
[DOCS] add minor changes to install guides
[DOCS] add minor changes to install guides
[DOCS] add minor changes to install guides
* [DOCS] add minor changes to install guides
* Fix ONNX's PriorBoxClustered accuracy
If step_heights == 0 and step_heights == 0, but 'step' is 16, then we should treat this as both = 16
* Removed workaround for ONNX frontend
* save work
* save work
* save work
* basic changes with api 2.0
* Support input file mapping and bin files
* Some impovements
* remove mapping support
* Add -ref_layers parameter
* Fix error handler
* Update Readme and remove old parameters
* Fix readme
* remove info about precision
* rename layer to op
* rename blob to tensor
* remove info about shape
* remove unused imports
* Added info on DockerHub CI Framework
* Feature/azaytsev/change layout (#3295)
* Changes according to feedback comments
* Replaced @ref's with html links
* Fixed links, added a title page for installing from repos and images, fixed formatting issues
* Added links
* minor fix
* Added DL Streamer to the list of components installed by default
* Link fixes
* Link fixes
* ovms doc fix (#2988)
* added OpenVINO Model Server
* ovms doc fixes
Co-authored-by: Trawinski, Dariusz <dariusz.trawinski@intel.com>
* Updated openvino_docs.xml
* Updated the link to software license agreements
* Revert "Updated the link to software license agreements"
This reverts commit 706dac500e.
* Revised dlstreamer documentation
* Minor edits
* Fixed link
* Fix
* Edits after review
* Shorten DL Streamer name in the TOC
* Update documentation.md
Co-authored-by: Trawinski, Dariusz <dariusz.trawinski@intel.com>
* [GPU] Support batch32 deconv onednn
onednn rls-v2.6-pc2 support deconv batch32,
so remove the batch size limitation.
Signed-off-by: hyunback <hyunback.kim@intel.com>
* Update to merge duplicated checking onednn condidton in deconv.
Signed-off-by: hyunback <hyunback.kim@intel.com>
* Update to use is_node_for_onednn func in get_preferred_impl_type
Signed-off-by: hyunback <hyunback.kim@intel.com>
* Delete _extension suffix in file names; add extension.hpp header to include all extensions
* add extension.hpp file to include all extensions
* codestyle
* fixed perf-counters
* explicit auto-batching params that should guarantee the auto-batching is triggered ( to avoid fallback to no-batching when the selected batch1 size is just 1)
* makeConvPoolReluNoReshapes and using that whenever applicable to gaurantee the auto-batching is required (not important for things like plugin/executable-network config tests, but important for the inference-requests)
* getDefaultNGraphFunctionForTheDevice moved to the ov_behavior_test_utils.hpp
* fixed version comparison: for comparsion extracted hashes are used
* shortened 7 -> 11 to match the current version fromat from nightly
* corrected regex, added comparing by minimal hash len
* remove formatTimeMilli from time_utils.cpp
* add traceCallStacks test case
* add traceCallStacks test case in format_test.cpp
* add param:"test" to function TraceCallStacks()
* catch the exception of checkFormat
* add space for try catch
* rollback time_utils.cpp time_utils.hpp and log_utils_format_test.cpp
* modify testcase for log.hpp
* modify testcase from format_s to format_s_d_ld_u_lu2
fix canConvolutionBeTransformed arguments
fix isAsymmetricOnWeights in GPU plugin
added defaultPrecisions in TestTransformationParams
set new default attribute precisions
try to set const default precisions in network_helper.cpp
apply precision_set
[LPT] Default precisions
rebase
remove extra const
used defaultPrecision in tests
fixed SimpleLowPrecisionTransformer default argument
fixed AttributeParameters default argument
added defaultPrecisions in functions
fix assign_and_read_value_transformation tests
fixed wrong defaultPrecisions definition
fixed ConcatWithNeighborsWithConvolutionTransformation tests
remove getDefaultPrecisions
rebase
remove getDefaultPrecisions from gpu plugin
remove getDefaultPrecisions from lpt_mkldnn_plugin.cpp
use predefined member
update mkldnn_plugin.cpp & lpt_mkldnn_plugin.cpp
resolved conversations
make all lambda captures by ref
* Used new config for streams and threads
* Fixed review coments in ba
* format fix
* fixed hello_query_device
* Added STL string io
* fixed tests
* Fixed test
* Fixed build
* fixed format
* Fixed build
* try fix win
* other any io specialization
* Fixed after merge
* renamed streams
* build fixed
* fixed build
* fixed format
* fix for old mac build
* Fixed type of exception
* test fix
* Added info on DockerHub CI Framework
* Feature/azaytsev/change layout (#3295)
* Changes according to feedback comments
* Replaced @ref's with html links
* Fixed links, added a title page for installing from repos and images, fixed formatting issues
* Added links
* minor fix
* Added DL Streamer to the list of components installed by default
* Link fixes
* Link fixes
* ovms doc fix (#2988)
* added OpenVINO Model Server
* ovms doc fixes
Co-authored-by: Trawinski, Dariusz <dariusz.trawinski@intel.com>
* Updated openvino_docs.xml
* Updated the link to software license agreements
* Revert "Updated the link to software license agreements"
This reverts commit 706dac500e.
* Added POT, replaced IE with OV Runtime
Co-authored-by: Trawinski, Dariusz <dariusz.trawinski@intel.com>
- Change the constant value to the maximum work group size
- Add CLK_GLOBAL_MEM_FENCE barrier to synchronize storing result in intermediate buffer
- Add condition to prevent access local array out of range
Signed-off-by: Andrew Kwangwoong Park <andrew.kwangwoong.park@intel.com>
+ Reverted WA for fsv32 format first conv
+ Applied blocked input format bsv8fsv4 & bsv8fsv2 for onednn first conv
+ Implemented onednn usage for first conv of feature size 1
+ Added new weight format ABcd16a4b
+ Bugfix in fetch_weight
+ Updated thirdparty onednn_gpu
+ Known issue : AcdB16a4b is not supported
Signed-off-by: Min, Byungil <byungil.min@intel.com>
Current SmartReshape finds matched to Param->Reshape->Proposal patterns
For FP16 models, there is additional 'Convert' is inserted after 'Parameter'.
It causes transformation is not applied and 'ov::set_batch' or CNNNetwork::set_batch will throw
Proposal1Scales and Proposal4Scales transformations were updated to handle these conditions
* forced split argument dtype to int
* added unit-test
* fixed typo in split_test.py
* set explicitly np.int64 instead of np.int
* use split_length's dtype
* Update LSTMSequence backend_attrs
* Add missed attribute clip
* Update backend_attrs for all *sequence operations
* Add extender for GRUSequence
* Add GRUSequence to custom ops list
* use has_and_set instead if direct acces to attributes
* Automation for preserving rt info in output ports; Update FunctionComparator to compare rt info correctly
* Update LPT tests to use real rt_info attributes, so they can be compared
* Fix tests
* Reshape op pruning support
* Minor reshape fix
* GroupConv reshape extended support
* Comment ir test
* Fix: reshape can only work with constants
* Apply comments
* Fix output shape computing for reshape op
* Fix comment
* fix bug in Serialize (#74447)
add simple serialization test to check pads changes
clang fix
add check and change pads in conv
refactor ov::clone_model
fix
check in test
* fix FrameworkNode and add test
* fix assert in identiry.cpp
* fix clone_nodes
* remove for node and constructor for node_input.cpp
add spaces
add space
* Add sqrt extender
* Update check to not use default infer in infer was set before
* Update comment
* Fix comment
* Remove Sqrt extender
* Remove unnecessary changes
* Add MO implementation of SQRT operation
* Added info on DockerHub CI Framework
* Feature/azaytsev/change layout (#3295)
* Changes according to feedback comments
* Replaced @ref's with html links
* Fixed links, added a title page for installing from repos and images, fixed formatting issues
* Added links
* minor fix
* Added DL Streamer to the list of components installed by default
* Link fixes
* Link fixes
* ovms doc fix (#2988)
* added OpenVINO Model Server
* ovms doc fixes
Co-authored-by: Trawinski, Dariusz <dariusz.trawinski@intel.com>
* Updated openvino_docs.xml
* Updated the link to software license agreements
* Revert "Updated the link to software license agreements"
This reverts commit 706dac500e.
* Added a link to the omz repo
Co-authored-by: Trawinski, Dariusz <dariusz.trawinski@intel.com>
* [GNA] Add support for non-functional subgraphs
Details:
* Insert copy before the last layer to allow nonfunc subgraphs
Tickets:
57363
* Traverse graph in upstream order
* Add param-reshape-result tests
* Fix insert condition
* review comments
* Added compatibility check of layout with partial shape
E.g. layout "NC" in not compatible with PartialShape{1,3,224,224}
Check is added:
- For parameter set_layout
- For parameter set_partial_shape
- For result set_layout
- Checked also compatibility for all results after 'validate_and_infer_types'
* Fix incorrect tests
* Fix of more incorrect tests
* Removed couple of obsoleted error-handling tests - these are catched now on earlier stages
Co-authored-by: Ilya Lavrenov <ilya.lavrenov@intel.com>
* Any value can fromm inner string
* Fixed review coment
* strict str to value conversion
* fix format
* [VPU] update config header (#9857)
* [VPU] update config header
* Review fixes
* Performance hint config update
* Removal deprecated vpu config stuff
* Review changes
* Rename myriad properties from camelCase to snake_case
* Review changes
* Review fixes
* Removal intel_myriad::common namespace
* OV throughput stream option
* Test fix
* Reverted disable_convert & disable_reorder
* Bugfixes
* Change default value for PerformanceHintNumRequestsOption
* fixed excessive outputs copying (in case when the fallback happened) and updated the test for that (#10110)
* fixed excessive outputs copying (in case when the fallback happened) and updated the test for that
* enum eExecutionFlavor to cover initial state
* Transformations: eltwise and FQ fusings fixes (#10078)
* FQ fusings fixes
* FQ Fusings: added negative test-cases for non-broadcasted constant
* Disable single-image-super-resolution-1032 from MemCheck precommit (#10133)
* add performance hint to time infer
* disable model from memcheck
* Fixed input cut for case when port is not specified. (#10134)
* Fix for android type info comparison
Co-authored-by: Aleksandr Korolev <aleksandr.korolev@intel.com>
Co-authored-by: Maxim Shevtsov <maxim.y.shevtsov@intel.com>
Co-authored-by: Vladislav Golubev <vladislav.golubev@intel.com>
Co-authored-by: Victor Kuznetsov <victor.kuznetsov@intel.com>
Co-authored-by: Anastasia Popova <anastasia.popova@intel.com>
* Adjust preferred format of resample operation
* Applied review comment
* Not to fix resample layout when there is permute user unless the permute order is rotating
* Check the selected frontend to correspond use_new/legacy_frontend options
Signed-off-by: Roman Kazantsev <roman.kazantsev@intel.com>
* Fix a default case when no frontend is found
Signed-off-by: Roman Kazantsev <roman.kazantsev@intel.com>
* Added op names to tensor names for MaskRCNN replacement transformation. Fixed output layout for MaskRCNN.
* Applied commentes left from PR with tensor names fix.
* Added tests for remove_tensor_names().
* Added checks in emitter.
* Removed debug output.
* Small fix.
* Small fix.
* Depricated Any implicit cast
* Fixed test
* fixed gna build
* Fixed warnings in benchmark_app
* Fixed test build
* ncc exception for PrintTo
* Error mesage in test
* Error mesage in test
* fixed build
* Fixed tensor names setting in InputCut, fixed tensor names losing in AutomlEfficientDet.
* Changed op name adding to tensor names in InputCut for output port case only.
* Remove fp16 of Convert layer test from skip_tests.config.cpp as it works now
* update repo
* fix demension dynamic support bug in mish op reference test
* Remove fp16 of Convert layer test from skip_tests.config.cpp as it works now
* update repo
* add initial op reference test of rnn_sequence
* add op reference test of GRUSequence
* replace input and refOut data to hard coded value
* update copyright year and namespace of Tensor
* rename S_t to sequence_lengths
* Added new correct gna frequency result for Alder Lake
* Update samples/cpp/speech_sample/utils.hpp
Co-authored-by: Krzysztof Bruniecki <krzysztof.bruniecki@intel.com>
Co-authored-by: Krzysztof Bruniecki <krzysztof.bruniecki@intel.com>
* Refactored statistics output with JSON support
* Detailed/average reports are added
* stylefix
* Update samples/cpp/benchmark_app/statistics_report.hpp
Co-authored-by: Ivan Vikhrev <ivan.vikhrev@intel.com>
* Linux Fixes
* stylefixes
* data_shape field format is changed
* stylefix
Co-authored-by: Ivan Vikhrev <ivan.vikhrev@intel.com>
* [Python API] Rename configuration API + update tests/tools
* keep old api for compatibility
* add deprecation warnings
* apply comments to query sample
* remove convert to pyobject
* use Any instead of string
* update tests
* update set_property
* fix sample
* update test + try-except for pot
* add docstrings
* fix codestyle for pot
* change order of transformations to work correctly with Convolutions in Kaldi LSTM networks
* removed unneeded changes and add unit tests
* remove comment
* remove changes from memory_offset_adjustment, move all fixes inside add_reshape_transpose_around_conv_pool to avoid new bugs
* removed test for deleted changes
* replace -1 by None
* Calculate value bounds in ReshapeSequenceFusion
* Reashape fusion upper bounds check
* Revert last return to false
* Add transformation unit tests
* Use output node as check param
* Use evaluate helper and remove deprecation macro
* Header update
* Checks refactor and comments
* Update unit tests
* Get element type from node_out
* Moved memory tests to OV API 2.0
* Added configs for OV api 2, updated configs for api 1
* Commented several models in configs (no such models on omz)
* Updated fillTensors
* Fix to get network inputs
* Updated fillTensors and configs
i32 or i64 is used for index_element_type. So it is more convenient to get rid of the condition and stay only with the i32 option.
Tickets:
75748
75747
75029
* Correct Loaders for TensorFlow StridedSlice and Pack operations
Signed-off-by: Roman Kazantsev <roman.kazantsev@intel.com>
* Supress INFO and WARNING messages from TensorFlow
Signed-off-by: Roman Kazantsev <roman.kazantsev@intel.com>
* Install libGNAconfig.cmake
* Refactor gnaConfig to correctly find from OV package
* remove ENABLE_INTEL_GNA option from CI
* Apply comments and fix CI
* re-trigger CI (demos issue)
* Enable GNA/samples smoke tests
* rename GNA to GNA_EXT_DIR
* re-trigger CI (mxnet cpu test issue)
* Pick azhogov changes to check CI
* try win wa
* fix win build
* re-trigger onnx
* tests
* disable win samples tests
Co-authored-by: Alexander Zhogov <alexander.zhogov@intel.com>
* Moved stress tests to OV API 2.0
* Fix for using ouput index instead of get_index
* Removed ov::runtime namespace in stress tests
* Updated stress tests according to latest changes in OV 2.0
* Fix memleaks tests
* Updated run_memcheck.py to process gtest_filter
* Updated fillTensors, added InferAPI1 and InferAPI2 classes
* Updated test_inference_with_streams
* Updated isImage, comments
* Updated fillTensors to fill image_info inputs with positive pseudo-random numbers
* Removed redundant variable in fillTensors
* Update AUTO OV 2.0 c++ configuration API.
Signed-off-by: ywang2 <yang4.wang@intel.com>
* Support the OV 2.0 key to set model priority and add the test case to verify the prioirty map logic within AUTO plugin.
Signed-off-by: ywang2 <yang4.wang@intel.com>
* Replace the old model priority key and add the corresponding test case.
Signed-off-by: ywang2 <yang4.wang@intel.com>
* Fix LSTMSequence/GPUSequence validation behavior consistent with RNNSequence
Fixed issue with no exception if num_directions=2, but 'm_direction' is not set to BIDIRECTIONAL. Previously there was no error with this (and luckily it failed later in some CPU transformations during compile_network)
Corrected several tests which use copy-pasted num_directions=2 without m_direction set
Also for dynamic 'num_directions' - output shape still has 1 or 2 directions, because m_direction is known. Tests for GRU/LSTM are updated for this
Also several tests worked incorrectly for LSTMv0 - expectation was specific error to be thrown, but no expection was also allowed
* Fixed clang-format
* Store the expected output data in the TestCase class
* Skip the failing ONNX If tests
* Disable failing ONNX Softmax tests
* Disable the remaining failures
* ROI tensor support for Template plugin + tests for Template and CPU plugins
GPU doesn'tsupport ROI tensors, so tests were not added for GPU
* Added asserts for unsupported mixed axis order (like 0,3,1,2), and unsupported types like int4/int2 for ROI tensors
* Avoid duplicated outputs with the same name
* Revert onnx graph changes
* Allow output duplicates in ie_plugin_internal check
* Add test with onnx model
* Check get_tensor_ptr instead of any_name
* More outputs test
* Refactor to use std::transform
* test manifest update
* Remove redundant header
* INTERPRETER segfaults fix for duplicated output names
* Simplify duplication assert
* Update test names
* Test update
Currently, calling QueryNetwork from Myriad plugin with dynamic network could result in exception, this PR should fix this by removing nodes that could cause it from consideration.
Co-authored-by: Polina <polina.brzezinskaya@intel.com>
Support matmuls with two non-const inputs.
Detect concat inputs to matmul as changing batch size and
handle appropriately.
Enable tests in GNA_SW_EXACT mode for convolution stride > kernel size.
* Remove fp16 of Convert layer test from skip_tests.config.cpp as it works now
* update repo
* initial code commit
* add runtime reference
* apply ov::Model
* initial lstmcell-1 definition
* initial change
* apply Peepholes
* apply input_forget option
* apply initial test case of lstmsequence-1
* fix clang-format error
* fix clang-format error 2
* add lstms_sequence test cases by runtime reference and onnx test cases
* fix clang-format error
* fix clang-format error
* fix onnx test failure of LSTM IE_CPU
* fix clang-format issue
* fix clang-format issue 2
* add type_prop and visitor api test of lstm_sequence_v1
* fix clang-format error
* replace input/refOut data to hard coded and remove unnecessary enum definition
* update namespace of Tensor()
* remove supported test cases in disabling list
This PR fixes error
inference-engine/src/vpu/graph_transformer/src/stages/interpolate.cpp:65 Current Interpolate does not support resize by channels that started to appear after sample refactoring.
Issues: -75837
* [GNA] Fix large eltwise split in case split dimension is less than alignment
* Update src/plugins/intel_gna/optimizer/gna_pass_manager.cpp
Co-authored-by: Krzysztof Bruniecki <krzysztof.bruniecki@intel.com>
Co-authored-by: Krzysztof Bruniecki <krzysztof.bruniecki@intel.com>
* Further fixes of plugins.xml generation
1) Unregistration is done by name (e.g. CPU), not by file name (ov_cpu_plugin)
2) Unregistered line is searched by name="MULTI" instead of just 'MULTI' to not conflict with MULTI_WORK_MODE_AS_AUTO entry
3) Removed list of all possible plugins from ov_runtime as logic shall not rely on this (not possible to add 3rd party plugins)
* Revert ov_runtime - some CI jobs require plugins.xml even though plugins are not built
Registration - if some entry already exists in XML - don't copy it.
E.g.
- Registration of 'TEMPLATE' is performed
- Registration loops through existing plugins.xml
- If name="TEMPLATE" is found - don't take it to newContent
- If name like "myCustomPlugin" is found - take it
- As result - "myCustomPlugin" will exist after update, but old "TEMPLATE" will be removed
* Add missing change
* Detect casting node inside preprocessing block and leave it
Signed-off-by: Roman Kazantsev <roman.kazantsev@intel.com>
* Fix unit-test for ObjectDetectionAPI
Signed-off-by: Roman Kazantsev <roman.kazantsev@intel.com>
* Implement interpolate-1 and interpolate-4 in template plugin test
* Fix clang error
* Fix clang error
* Fix clang error
* Fix linux build
* Fix cpplint error
* Fix clang error
* Fix linux build
* Change way to pass attribute into struct for linux build
* Correct supported type
* Fix clang error
* Add visitor api test for interpolate-1 and interpoate-4
* Fix typo and cpplint
* Update copyright
* Avoid using a class that will be deprecated
* Rollback to CoordinateTransform
* Remove interpolate.in.cpp
Without fix, build of 'cpuUnitTests' will fail as 'inference_engine_s' will contain:
IE_STATIC_DEPENDENT_FILES = file_utils.cpp
$<TARGET_OBJECTS:${TARGET_NAME}_obj> - containing 'unity_cxx' which includes 'file_utils.cpp'
This causes multiple definition error of all methods inside file_utils.cpp
- Added registration (and unregistration) of ov_auto_batch_plugin. Otherwise 'BATCH' plugin will always produce new XML line without removing old one
- Added unregistration of legacy plugin names (<= 2021.4 release). Otherwise old lines like "libHeteroPlugin.so" will not be removed from plugins.xml file
* grouped convolution resolver fix
* add reverse_infer for Transpose, Elementwise, Identity and some fixes to successfully OOB convert MXNet models
* add reverse_infer for BatchNorms, dynamic groups fix, multi_box_prior.py fix
* add reverse infer for trivial cases
* input rank setting for image detection ops
* reverse_infer for Gather, AttributedGather add todo comment for Parameter
* reverse infer for LSTM, swapaxis; fixes and unit-tests for Elementwise, Gather, Transpose; also generalized Parameter reverse_infer; fixed DetectionOutput and partial reverse_infer
* clarified comment for LSTM reverse_infer
* detalized Elementwise reverse_infer, added several more unit-tests, Split reverse_infer fix, IteratorGetNext_ext.py fix
* generalized group convolution resolver
* specified in_ports explicitly
* clarified Split, Concat, Parameter, other minor typos
* relaxed compatibility check for elementwise; simplified scalar extracting for convolution.py and gather.py, fixed replacer order for ConvolutionNormalizer.py
* added routine set_input_shapes for image detection ops
* fixed typos to pass locally E2E, slightly changed LSTM reverse_infer
* VariadicSplit reverse_infer bugfix
* IteratorGetNextCut.py added check if port is connected
* explicitly specified in_port, added asserts, improved Split reverse infer
* sorted imports
* reverse_infer for ONNX and MXNet LSTM, GRU, RNN operations
* replaced Error raising with red warning
* added missing return for defined input shapes, fixed getting num groups for tf conv
* added mandatory attributes; fixed failing unit-tests, fixed typo with scalar group in ConvolutionNormalizer
* removed priorbox reverse_infer; Parameter reverse_infer corrected to use the only one existing out_port
* fixed clarify_partial_shape_test
* Preserve outputs order TF.
* Preserve of input/output indices for MxNet.
* Small fix.
* Added check.
* Small fix.
* Corrected Keras model importing.
* Fixed Keras model loading.
* Small correction.
* Corrected model loading.
* Small fix.
* Comment corrected.
* Removed unnecessary import.
* add performance hint to time infer
* add reshape methods for time infer tool
* add func declarations to common_utils.h
* add check if node is static (reshape pipeline)
* changes in desc of reshape funcs
* fix logic operator
* add reshape utils.h | move parsing logic in main func
* add tests_shared_lib to CMakeLists.txt
* change fill blobs with setStaticShapesBlobs
* change delimiter
* Preserving of input/output indices for ONNX.
* Fixed checks.
* Fixed for case of multiple outputs of node before Result.
* Added test for multiple tensor names before Result.
* Multiple tensor names before Result fix.
* Added order alignment for user input/output.
* Extended for case of input names in Parameter tensor list.
* Fixed unit tests.
* Corrected help.
* Small correction.
* Code refactoring.
* Temporarily reverted refactor.
* Fixed wrong changes.
* Fixed wrong changes.
* Returned reverted refactoring.
* Removed inputs_list from serializing.
* [Python API] Remove offline transformations from old python api
* [Python API] Move wheel folder to the python dir
* codestyle files
* [Python API] Move old python bindings
* move api
* one more codestyle
* fix install stage
* remove unexisting file from gitignore
* flake8 style
* try to fix jenkins
* undo comments
* return variable
* remove cpack
* fix after merge
* try to fix version
* fix test
* remove debug info
* version of python
* try to fix pyversion
* update tests
Co-authored-by: Alexander Zhogov <alexander.zhogov@intel.com>
* Loop/If/TensorIterator - fix dynamic input cases
Reference evaluate for body uses Model::evaluate instead of custom evaluation
Loop/TensorIterator additional fix - set result shape according to body execution result
Only op_eval test verifies issues, template tests were added just in case (these passed even without fix)
* Fix clang-format
* rename ti.cpp
* move gpu functional tests for range to correct location
* disable range layer test on gpu
it needs dynamic shapes support
Co-authored-by: Serhii Pavlovskyi <spavlovskyi@lohika.com>
* Squash commit: implement Conversion extensions
* Refactor PaddlePaddle FrontEnd
* Codestyle
* FrontEnd,InputModel,Place base classes -> abstract, renamed model file
* Fix unit tests
* fix unit tests
* ngraph:: to ov::
* Rename frontends dir to frontend
* fix merge conflicts
* Fix ConversionExtension
* get rid of NamedInputs/Outputs in TF FE
* Rename paddlepaddle to paddle; pdpd to paddle
* add missing file
* codestyle
* Remove local change
* paddlepaddle -> paddle for azure configs and .md files
* fix package name, fix config files
* Fix win build
* Revert Broadcast/AutoBroadcast changes
* codestyle
* fix FronEnd class
* fix ngraph_cpp_api.config
* fix incorrect merge, codestyle
* fix conversion extension
* conversion extension
* codestyle
* merge master
* fix build
* refactoring; revert broadcast/autobroadcast changes
* codestyle
* fix MacOS config
* resolve merge conflicts
* refactor includes
* register ConversionExtension in FrontEnds
* move get_op_type to base NodeContex class
* set op_translator map in ctor of Paddle FE; fix unit tests
* update unit tests; codestyle
* codestyle
* preliminary version of conversion extension in pybind
* conversion extension
* get_attribute_as_any method for NodeContext
* move get_attribute methods to NodeContext base class, rename get_ng_input to get_input
* add missed file
* Implement ov::Any getter in ONNX NodeContext
* fix py bindings
* Add update ConversionExtension unit tests, add SO unit tests, fix TF FE
* fix segfault on destructor
* fix NodeContext interface, fix unit tests
* set different names for ConversionExtensions in unit tests
* fix PaddleFuzzy tests
* fix Paddle Fuzzy tests
* revert changes in generate_slice.py
* fix codestyle
* fix pybindings
* revert local changes in generate_slice.py
* delete duplicate exceptions.hpp
* Refactoring: fix names according to convention
* pybinding for NodeContext, FrontEnd, ConversionExtension; fix unit tests; implement new unit tests
* Refactoring
* fix the case when a new converter rewrites existed one; delete unnecessary NodeContext from pybindings; use CreatorFunctons from the base class in ConversionExtension; update unit tests
* Revert local change
* PythonAPI: fix get_attribute method; fix get_input method; implement support of dtype and default attributes
* Fix py unit tests: add support for vector<ov::element::Type> as attribute
* resolve review comments
* fix unit tests
* move extension_holder to openvino/frontend/extension folder
* fix build on mac os
* temporary disable cast from vector<bool> to investigate issue on mac os
* Resolve review comments
* Resolve review comments
* Use dev API for .so extension
* Link frontends to pyopenvino as separate targets
* Temporary enable tf fe installation
* ignore PEP8 E402 for init files, set correct directory for py modules
* revert local changes
* Fix deadlock in pybind GIL; fix Win build; fix PEP8
* fix PEP8
* Add a return type annotation
* fix builds; fix ON/OFF switcher for ENABLE_OV_xxx_FRONTEND cmake options
* Fix the issue with ifdefs on WinOS; fix the issue related to pybindings and static c++ object
* fix python unit tests
* fix static build on WinOS
* Retrigger CI builds
* Fix static build on Windows
* fix static build on Windows again
* Retrigger CI
* delete unused includes; add a comment about issue on MacOS
* fix missprint
* resolve review comments
* fix missprint
* resolve review remarks
* Resolve review comments
* win win wheels build
* resolve review comments
* Python bindings - test for telemetry extension
This also ensures that actual 'Telemetry' object containing callbacks is still alive even there is no explicit Python objects holding it
* Fix pylint
* fix clang-format
* Remove fp16 of Convert layer test from skip_tests.config.cpp as it works now
* update repo
* add op reference test of region_tolo
* add type_prop test and remove backend test of region_yolo
* apply type conversion for loading file test and add bf16 test case in skip_test_config
* change location of compile definition under target and use path_join from file_util
* add dependency of test_model_zoo
* apply ov::Model
* remove unnecessary
* changed compile definition of TEST_FILES
* skip test cases of external test file
* remove test cases of importing data file
* Use std::string for static map instead of py::str
Probable reason is that this static map is destroyed after 'pybind' module is destoryed itself, thus py::str can't be cleaned up properly
* Added test via 'subprocess' execution of separate file
* if only one Device, not select
Signed-off-by: Hu, Yuan2 <yuan2.hu@intel.com>
* modify test case to match logic
Signed-off-by: Hu, Yuan2 <yuan2.hu@intel.com>
* [PYTHON] Add python APIs for loadNetwork and compile_networt without device name
CVS: https://jira.devtools.intel.com/browse/CVS-75249
Change-Id: Ia28e35f4ee66fc8fc5997b5bafe1b159670f9a21
Signed-off-by: River,Li <river.li@intel.com>
* Fix clang issue
Change-Id: I9988b16863af0e3883e99369f124cd05761d3210
* Fixed positional arguments issue
Change-Id: I6c3aa98bb693a619fa54fd6e96cf5eb89cdb9369
* Fixed 2 blank lines issue
Change-Id: I7f2afd7ebb80867a69d0c3ac9a6d4a38d95edb12
* Set AUTO as default device if no device name is set
Change-Id: Ic8646b12af0a2ab2fec6a07f5a12d460dcf781d7
* Resolve comments from code reviewer
Change-Id: Ia47faeb48937096e41e22ac59fbd88ec82cc6733
* moving the HETERO logic to the Auto-Batch (WIP), reverting to the ALLOW_AUTO_BATCHING and using that in the GPU remote tests
* shortned the vars names in the ie_core and prevented recursive auto-batching calls by checking for exclusive requests and disabling further auto-batching in the plugin, when HETERO is involved
* checking for the batch-dim presence (this is still WA until the https://github.com/openvinotoolkit/openvino/pull/9559 is merged) - pls see CVS-75317
+clang for the ie_core.cpp
* moving the HETERO logic back to the ie_core.cpp, storing the _so internally for no-batch code-path
* [IE SAMPLES] activated NCC tool for c++ samples
* exclude ov_ncc_naming_style for tests
* fixed NCC hit
* Added support for source files in samples
* changed style of methods for benchmark
* changed style for speech sample
* changed code style
* changed code style for shared_tensor
* benchmark changes
* changed remote_tensors_filling
* fixed notes
* rebase of branch
Useful in cases when pad_value is a subgraph marked as decompression
which cannot be constant folded, but still, Pad can be eliminated
if pad_value evaluates to zero.
* fix: set shape in fbc if undefined dimension in model
* Update tools/pot/openvino/tools/pot/algorithms/quantization/fast_bias_correction/algorithm.py
Co-authored-by: Liubov Talamanova <piccione-mail@yandex.ru>
* Apply suggestions from code review
Co-authored-by: Liubov Talamanova <piccione-mail@yandex.ru>
* update shape in bc id dynamic shape
Co-authored-by: Liubov Talamanova <piccione-mail@yandex.ru>
* changed permutes
* fixed permutes
* fixed kernel
* fix transpose after convolution
* fix for convnet
* insert transposes for all convolutions and poolings
* refactor transformations;
added unit tests;
removed old transformations for addinf permutes/reshapes
* fixed constant types
* fixes after merge
* fixed bug for rm_cnn4a: added correct time_dim for the first convolution
* added fix for timeheightconvolution: in this case we have correct time set in convolution kernel already
* minor review fixes: renamed transformation and file
* rename in test
* rename in test
* sort imports + couplt changes in comments
* review fixes: refactoring
* replaced recursive implementation by nx.topological_sort;
fixed comments
* minor fixes: comment + preserving node names
* Graph comparator - take sinks into accounts
Previously graph has been traversed only from Results, so any differences in 'Sinks' were not detected
* Fix functional tests
* Update after internal discussion
* Fix low_latency_test (addition to low_latency_v2_test)
* Fix typo
* add limit format on snprintf
Signed-off-by: Hu, Yuan2 <yuan2.hu@intel.com>
* add limit on format
Signed-off-by: Hu, Yuan2 <yuan2.hu@intel.com>
* add test case
Signed-off-by: Hu, Yuan2 <yuan2.hu@intel.com>
* fix a bug for LOG_TRACE
Signed-off-by: Hu, Yuan2 <yuan2.hu@intel.com>
* remove debug info
* Change dynamic_to_static to dinamic_to_undefined function to use -1 values instead of upperbounds in serialized IRs
* Resolve conflict after src files transition
* Remove resolve_dynamic_shapes function
* Fix typo
* Fix codestyle
* add warning about order if both mean and scale set
* Update tools/mo/openvino/tools/mo/main.py
Co-authored-by: Anastasia Popova <anastasia.popova@intel.com>
* removed warning, added phrase in documentation
* fixed merge
* added phrase about order of ,mean and scale in MO help
* duplicate MO help phrase in doc
* Update docs/MO_DG/prepare_model/convert_model/Converting_Model.md
Co-authored-by: Anastasiya Ageeva <anastasiya.ageeva@intel.com>
* Update docs/MO_DG/prepare_model/convert_model/Converting_Model.md
Co-authored-by: Anastasiya Ageeva <anastasiya.ageeva@intel.com>
* Update docs/MO_DG/prepare_model/convert_model/Converting_Model.md
Co-authored-by: Anastasiya Ageeva <anastasiya.ageeva@intel.com>
* Update tools/mo/openvino/tools/mo/utils/cli_parser.py
Co-authored-by: Anastasiya Ageeva <anastasiya.ageeva@intel.com>
* Update tools/mo/openvino/tools/mo/utils/cli_parser.py
Co-authored-by: Anastasiya Ageeva <anastasiya.ageeva@intel.com>
* remove tabs
* fix in order of reverse, mean, scale
Co-authored-by: Anastasia Popova <anastasia.popova@intel.com>
Co-authored-by: Anastasiya Ageeva <anastasiya.ageeva@intel.com>
* [Python API] Rename offline_transformations in the new api
* remove comments
* one more place to rename
* fix mo building
* fix after merge
* fix for pot import
* Add include guard to file_utils.cpp
* Rebase src
* Rename acc tests, fix rebase
* Revert debug changes
* Fix linter
* Move ac tests to new template
* Test updated
* Fix result operation are sharing output tensor with previous op
* Pruning test visualzation option
* Add ac support for all test cases with pruned kernels
* Remove redundant files
* Enable extended pruning logging by env variable
* Adjust pruning tests
* Remove pruning extended debug env var
* Enable init masks only in debug mode
* Set result mask to input tensor instead of output tensor by separate key
* Bug fix / Test coverage
* Fix comments
* passing by reference to fix performance inefficiencies.
Signed-off-by: Wang, Yang <yang4.wang@intel.com>
* Passing by const reference.
Signed-off-by: Wang, Yang <yang4.wang@intel.com>
* Q/DQ + mulichannel support
backup
fix interval
mfk_functiun.cpp
WIP moveDequantizationBefore
add moveDequantizationBefore function
add cpu and gpu tests
attribute cmp false
attribute cmp false
rm temp line
mkl-dnn update
concat with multichanels for mOve_fake_quantize_function, bad runtime info for q/dq
rm extra qualification
fix run time info for q/dq
add support of multichanel fakequantize, bad test for it
work tests for multi chanel FQ
rm workaround
cpplint fix
cpplint fix
don't worl Variadic split
ieFuncTest work
cpuFuncTest work
Fix benchmark_app build (#7577)
[GPU] Added onednn dependency. (#6564)
cpp lint
cpplint
fix get_shape
fix fq constants
cpp lint
some fix in mfk.cpp
resolve conversations, add spil_nodes function
add new tests for multi-chanels, rename NetworkHelper::split_consts_before_concat()
fix get fq constants
* add new multi-chanels test and use constant_fold to split constant
* remove extra spaces
fix namespase terminated
fix namespase terminated
* resolved minor comments
* added check for convert_q
* Eliminate no-op elementwise operations
This change adds EliminateEltwise pass to NopElimination.
EliminateEltwise removes:
- Subtract with zero
- Multiply with one
- Divide by one
* add Add support to EliminateEltwise
* fix unit test
* use get_all_data_elements_bitwise_identical instead of get_single_value
* fix are_all_data_elements_bitwise_identical for constant created from HostTensor
* fix lpt tests
* check for mul in is_dequantization_subgraph function
* optimize fetching constant value
* apply review comments
* [Common FrontEnd] Implement ChangePlaceholderType transformation with OldApiMap
Signed-off-by: Roman Kazantsev <roman.kazantsev@intel.com>
* Add ChangePlaceholderType pass into frontend normalize
Signed-off-by: Roman Kazantsev <roman.kazantsev@intel.com>
* Add a comment about the transformation
Signed-off-by: Roman Kazantsev <roman.kazantsev@intel.com>
* Fix build issue
Signed-off-by: Roman Kazantsev <roman.kazantsev@intel.com>
* Apply code review comments: remove ngraph namespace rountine, etc.
Signed-off-by: Roman Kazantsev <roman.kazantsev@intel.com>
* Remove use of extra Node object in set_old_api_map call
Signed-off-by: Roman Kazantsev <roman.kazantsev@intel.com>
* Create separate pass for legacy nGraph transformations for MO with new frontend
Signed-off-by: Roman Kazantsev <roman.kazantsev@intel.com>
* Fix build for ieFuncTests
Signed-off-by: Roman Kazantsev <roman.kazantsev@intel.com>
* Fix build issue with namespace conflicts
Signed-off-by: Roman Kazantsev <roman.kazantsev@intel.com>
* Revert "Fix build issue with namespace conflicts"
This reverts commit 50a189f4e5.
* Move legacy transformations to ngraph namespace
Signed-off-by: Roman Kazantsev <roman.kazantsev@intel.com>
* Fix build issue with unresolved MOCLegacyTransformation
Signed-off-by: Roman Kazantsev <roman.kazantsev@intel.com>
* Adjust code to new OldApiMap API
Signed-off-by: Roman Kazantsev <roman.kazantsev@intel.com>
* Resolve merge conflicts
Signed-off-by: Roman Kazantsev <roman.kazantsev@intel.com>
* Fix build issue
Signed-off-by: Roman Kazantsev <roman.kazantsev@intel.com>
* Do not set legacy type for parameter in case user defined type
Signed-off-by: Roman Kazantsev <roman.kazantsev@intel.com>
* Removed old dynamism API from infer request
* Fixed segfault
* Fixed some tests
* Added method to set inputs, outputs
* Fix python tests
* Try to fix window build
* Calculate model layout based on 'tensor' layout and convert steps
Previously, 'model layout' is set to '...' by default,
thus no shape conversion happened when tensor layout is set to 'NHWC', then there was explicit convert_layout "NCHW"
Now "model layout" is calculated based on tensor layout and conversion steps:
Examples:
1) Tensor: NHWC, Convert: NCHW. Result: NCHW
2) Tensor: NHWC, Convert: 0312. Result: NCHW
* Initial move of tensor data calculation
* Moved 'impls' to new file
* Postprocessing + unit tests
* clang-format fix
* Added more details to preprocessing nodes
- Mean/Scale - will print mean/scale values
- Convert type - will print type
- Convert layout - will print destination layout
- Convert color - will print destination color
It is needed to troubleshoot the problems. If error occurs, message will not display last op's target shape/layout/type
* Add python bindings
* update tests
* Added memory type to dump if set
* Code style fix
* unity build fix
* Dump tensor if only memory type is set
* Added debug print
* Fix Param->Result case
Previously, layout was set by preprocessing set to old parameter as well
This is incorrect because in case of exception layout info will not be reverted
In this case old Result pointed to old Parameter and was able to preserve runtime info
After fixing of this, case Param->Result was broken if revalidation is not triggerred
Fix is to detect 'Result' as a consumer of some parameter and force revalidation in this case
* Revert occasionally committed line
* And one more line
* rename inference_engine to OpenVINO
* correct exception for batch
* check all inputs to find batch dimension before throwing exception
* correct warning about batch
* avoid set_shape in static case
* refactoring latency output
* message about benchmarking mode
* use new precision naming
* use pass manager instead offline_transformations
* Move 'NV12toRGB/BGR' reference evaluates to template plugin
CPU doesn't need this fallback, so implementation can be moved to reduce core binary size
* Moved evaluate_nv12 to 'runtime::reference'
* Fix arm build
* ShutdownProtobufLibrary when unload paddle frontend dynmaic library to fix probuf memory leak
* ShutdownProtobufLibrary if the frontend libraries use protobuf
* make shutdown_protobuf a library
* Set THROUGHPUT as the default configration for all the plugin and display the config of the plugin.
Signed-off-by: Wang, Yang <yang4.wang@intel.com>
* updated format.
Signed-off-by: Wang, Yang <yang4.wang@intel.com>
* Update benchmark python API.
Signed-off-by: Wang, Yang <yang4.wang@intel.com>
* Replace str 'THROUGHPUT' with CONFIG_VALUE(THROUGHPUT).
Signed-off-by: Wang, Yang <yang4.wang@intel.com>
* Using CONFIG_VALUE(THROUGHPUT) replace 'THROUGHPUT' string.
Signed-off-by: Wang, Yang <yang4.wang@intel.com>
* update code style.
Signed-off-by: Wang, Yang <yang4.wang@intel.com>
* Move the setting output code into the try block.
Signed-off-by: Wang, Yang <yang4.wang@intel.com>
* Calculate model layout based on 'tensor' layout and convert steps
Previously, 'model layout' is set to '...' by default,
thus no shape conversion happened when tensor layout is set to 'NHWC', then there was explicit convert_layout "NCHW"
Now "model layout" is calculated based on tensor layout and conversion steps:
Examples:
1) Tensor: NHWC, Convert: NCHW. Result: NCHW
2) Tensor: NHWC, Convert: 0312. Result: NCHW
* Fix for set_shape + resize case
* Implement the batch to space shape infer
* Implement the space_to_batch shape inference.
* Implement shape infer of space_to_depth and depth_to_space OPs
* Fix Azure building issue.
* Add namespace for the shape_infer function.
* Avoid using friend declaration for shape infer.
* update coding style issue
* Update based on review comments
* Apply review comments
* Add test cases.
* Update the shape infer flow.
* Fix the bug in the previous test case.
* Update coding style.
* Fix the code bug caused by the DepthToSpace check fix.
* update coding style.
* Implment the Dimension/StaticDimension division operator by a value
* Refine the the code.
* Fix the issue when T is implicitly construct StaticShape with PartialShape when comparing
* Update the CI issue.
* Move the shape_infer helper into src folder.
* Apply the review comments.
* Coding style fix.
* Remove the ngraph folder
* Applied review comments
* Fix CI windows building issue
* Move test into new folder.
* Not support divisor is negative.
* Apply review comments.
* Fix CI issues
* Apply review comments.
* Update
Co-authored-by: Evgenya Stepyreva <evgenya.stepyreva@intel.com>
* Q/DQ + mulichannel support
backup
fix interval
mfk_functiun.cpp
WIP moveDequantizationBefore
add moveDequantizationBefore function
add cpu and gpu tests
attribute cmp false
attribute cmp false
rm temp line
mkl-dnn update
concat with multichanels for mOve_fake_quantize_function, bad runtime info for q/dq
rm extra qualification
fix run time info for q/dq
add support of multichanel fakequantize, bad test for it
work tests for multi chanel FQ
rm workaround
cpplint fix
cpplint fix
don't worl Variadic split
ieFuncTest work
cpuFuncTest work
Fix benchmark_app build (#7577)
[GPU] Added onednn dependency. (#6564)
cpp lint
cpplint
fix get_shape
fix fq constants
cpp lint
some fix in mfk.cpp
resolve conversations, add spil_nodes function
add new tests for multi-chanels, rename NetworkHelper::split_consts_before_concat()
fix get fq constants
* add new multi-chanels test and use constant_fold to split constant
* remove extra spaces
fix namespase terminated
fix namespase terminated
* Updated requirements for MO and POT with telemetry.
* Added mock telemetry common class for unit tests.
* Used mock telemetry in preprocessing unit tests.
* Small correction.
* Fix in the transformation PreserveRuntimeInfo: now Transpose is inserted before input port 0 of Result only, not after data node of layer before Result layer.
* Deleted commented code.
* Added more tests for the MO transformation PreserveRuntimeInfo.
* Use fp16-int8 mixed precision, instead of fp32-int8 mixed precision for onednn
* Allow quantization fusion into bsv32_fsv16 conv
* For conv, do not select bsv16_fsv16. Select bsv32_fsv16 for mixed-layout
* depthwise conv is supported even though it is not fp16
* Allow resample kernel to work as cross-layout
* test case for cross-layout of resample_opt kernel
* Select onednn-friendly format from cldnn conv
* Optimization for fp16 mixed precision
* Choose mixed layout in case of mixed precision from reorder_inputs
* Support for mixed precision from depth_to_space
* Do not convert first conv format
* Use onednn for FC output of fp16
* Choose bsv8_fsv4 from quantization even when conv kernel size is not 7
* Select cldnn for first conv when input feature depth is 1
* For first conv, use onednn only when kernel size is 7x7
* Use short variable name and added is_i8_u8 helper function
Co-authored-by: Kim,SungEun <sungeun.kim@intel.com>
* [LPT] Documentation
* 1) ToC was removed 2) SVG => PNG temporary conversion
* [LPT] Refactoring + developer guide
* [LPT] attribute doxygen documentation was added
* [LPT] Developer Guide to Reference API links were added
* [LPT] comments fixes
* [LPT] Reference API to Developer Guide links were added
* [LPT] titles were changed
* [LPT] comments fixes#2
* [LPT] root document was moved to Plugin DG
* [LPT] Documentation: image link quick fix
* [LPT] Docummentation: PrecisionsAttribute description quick fix
* fix comments from Karol
* fixes
* movement
* directive was added
* movement #2
* LPT reference in Executable Network rollback
* snippets were updated ini accordance with new API
* Handle names collisions for old IR with new API
* Fixed load model
* Try to fix tests
* Try to fix tests
* Try to fix build
* Try to fix tests
* Fixed tests
* Revert "Fixed tests"
This reverts commit 35da307210.
* Refactoring
* Fixed functional test
* Try to fix CPU tests
Co-authored-by: Ilya Lavrenov <ilya.lavrenov@intel.com>
* [Python API] Remove offline transformations from old python api
* try to fix import error
* try to fix pylint
* try to fix pylint2
* Use new api in graph_utils
* Fix pylint
* Try to fix pylint
* Use serialize from pass manager
* try to skip tests
* try to use new ir
Co-authored-by: AlexeyLebedev1 <alexey.lebedev@intel.com>
* [GPU] Enable unet2d enable on DG2
Add to support is_os_yx_isa2_osa8_isv8_osv2 format, which is used in
weight reorder.
Signed-off-by: hyunback <hyunback.kim@intel.com>
* [GPU] Enable implicit concat batch1 in oneDNN.
* Use gpu_usm memory offset, enable implicit concat batch1 in oneDNN.
And optimized_out node doesn't always have to be mutable input,
so add to check whether mutable input is existed in optimized node.
* Update to check use_usm condition in implicit concat.
* Add the condition for implicit concat.
* implicit concat's dependency should not be fused_op with eltwise.
* Buffer reuse is required for onednn sum post operation, output padding
did the buffer reuse failure.
Signed-off-by: hyunback <hyunback.kim@intel.com>
+ cldnn supports hard sigmoid activation function but onednn doesn't.
+ split it into eltwise linear and eltwise clip in
add_onednn_optimization_attributes pass.
* Add MatMulMultiplyFusion
MatMulMultiplyFusion replaces following subgraph:
MatMul->Multiply (with const)
to following:
Multiply->MatMul
where Multiply is applied to MatMul's second input.
We suppose that you are an enthusiastic coder, want to contribute some code. For that purpose OpenVINO project now has a repository on the GitHub, to simplify everybody's life! All the bug fixes, new functionality, new tutorials etc. should be submitted via the GitHub's mechanism of pull requests.
If you are not familiar with the mechanism - do not worry, it's very simple. Keep reading.
## Before you start contributing you should
- Make sure you agree to contribute your code under [OpenVINO (Apache 2.0)](https://github.com/openvinotoolkit/openvino/blob/master/LICENSE) license.
- If you are submitting a new module, you should go into [openvino_contrib](https://github.com/openvinotoolkit/openvino_contrib) repository by default.
- If you are going to fix a bug, check that it's still exists. This can be done by building the latest [releases/2020/3](https://github.com/openvinotoolkit/openvino/tree/releases/2020/3) branch (LTS release) or the latest master branch, and make sure that the error is still reproducible there. We do not fix bugs that only affect older non-LTS releases like 2020.2 for example (more details about [branching strategy](https://github.com/openvinotoolkit/openvino/wiki/Branches))
- Make sure that nobody beat you into fixing or reporting the issue by doing a search on the [Github OpenVINO issues](https://github.com/openvinotoolkit/openvino/issues) page, and making sure that there isn't someone working on it. In the latter case you might provide support or suggestion in the issue or in the linked pull request.
- If you have a question about the software, then this is **NOT** the right place. You should open up a question at the [OpenVINO forum](https://community.intel.com/t5/Intel-Distribution-of-OpenVINO/bd-p/distribution-openvino-toolkit). In order to post a decent question from the start, feel free to read the official forum guidelines.
Before you open up anything on the OpenVINO GitHub page, be sure that you are at the right place with your problem.
## "Fork & Pull Request model" for code contribution
### [](https://github.com/openvinotoolkit/openvino/wiki/Contribute#the-instruction-in-brief)The instruction in brief
- Register at GitHub. Create your fork of OpenVINO repository [https://github.com/openvinotoolkit/openvino](https://github.com/openvinotoolkit/openvino) (see [https://help.github.com/articles/fork-a-repo](https://help.github.com/articles/fork-a-repo) for details).
- Install Git.
- Set your user name and email address in a Git configuration according to GitHub account (see [https://git-scm.com/book/en/v2/Getting-Started-First-Time-Git-Setup](https://git-scm.com/book/en/v2/Getting-Started-First-Time-Git-Setup) for details).
- Choose a task for yourself. It could be a bugfix or some new code.
- Choose a base branch for your work. More details about branches and policies are here: [Branches](https://github.com/openvinotoolkit/openvino/wiki/Branches)
- Clone your fork to your computer.
- Create a new branch (with a meaningful name) from the base branch you chose.
- Modify / add the code following our [Coding Style Guide](https://github.com/openvinotoolkit/openvino/wiki/CodingStyleGuideLines) and [Documentation guidelines](https://github.com/openvinotoolkit/openvino/wiki/CodingStyleGuideLinesDocumentation).
- If you want to add a new sample, please look at this [Guide for contributing to C++/C/Python IE samples](https://github.com/openvinotoolkit/openvino/wiki/SampleContribute)
- Run testsuite locally:
- execute each test binary from the artifacts directory, e.g. `<source dir>/bin/intel64/Release/ieFuncTests`
- If you contribute to the documentation and want to add a new guide:
- Create a new markdown file in an appropriate folder.
-**REQUIRED:** The document title must contain a document label in a form: `{#openvino_docs_<name>}`. For example: `Deep Learning Network Intermediate Representation and Operation Sets in OpenVINO™ {#openvino_docs_MO_DG_IR_and_opsets}`.
- Add your file to the documentation structure. Open the documentation structure file [`docs/doxygen/ie_docs.xml`](https://github.com/openvinotoolkit/openvino/blob/master/docs/doxygen/ie_docs.xml) and add your file path to the appropriate section.
- When you are done, make sure that your branch is to date with latest state of the branch you want to contribute to (e.g. `git fetch upstream && git merge upstream/master`), push your branch to your GitHub fork; then create a pull request from your branch to the base branch (see [https://help.github.com/articles/using-pull-requests](https://help.github.com/articles/using-pull-requests) for details).
## Making a good pull request
Following these guidelines will increase the likelihood of your pull request being accepted:
- Before pushing your PR to the repository, make sure that it builds perfectly fine on your local system.
- Add enough information, like a meaningful title, the reason why you made the commit and a link to the issue page if you opened one for this PR.
- Scope your PR to one issue. Before submitting, make sure the diff contains no unrelated changes. If you want to cover more than one issue, submit your changes for each as separate pull requests.
- If you have added new functionality, you should update/create the relevant documentation, as well as add tests for it to the testsuite.
- Try not to include "oops" commits - ones that just fix an error in the previous commit. If you have those, then before submitting [squash](https://github.com/openvinotoolkit/openvino/wiki/Contribute#https://git-scm.com/book/en/v2/Git-Tools-Rewriting-History#Squashing-Commits) those fixes directly into the commits where they belong.
- Make sure to choose the right base branch and to follow the [Coding Style Guide](https://github.com/openvinotoolkit/openvino/wiki/CodingStyleGuideLines) for your code or [Documentation guidelines](https://github.com/openvinotoolkit/openvino/wiki/CodingStyleGuideLinesDocumentation) you are changing documentation files.
- Make sure to add test for new functionality or test that reproduces fixed bug with related test data. Please do not add extra images or videos, if some of existing media files are suitable.
## Testing and merging pull requests
- Your pull request will be automatically tested by OpenVINO's precommit (testing status are automatically reported as "green" or "red" circles in precommit steps on PR's page). If any builders have failed, you should fix the issue. To rerun the automatic builds just push changes to your branch on GitHub. No need to close pull request and open a new one!
- Once all the builders are "green", one of OpenVINO developers will review your code. Reviewer could ask you to modify your pull request. Please provide timely response for reviewers (within weeks, not months), otherwise you submission could be postponed or even rejected.
## PR review good practices
- Originator is responsible for driving the review of changes and should ping reviewers periodically.
- Originator should close comments from the Reviewer when it is resolved. The Reviewer may re-open the comment if he does not agree with the resolution.
- Originator should request re-review from the Reviewer when all comments are resolved by pushing the button in the “Reviewers” section.
- If it is still WIP and you want to check CI test results early then use _Draft_ PR.
- Do **NOT** rewrite history (push -f) once you converted draft PR into regular one, add new commits instead. Looking at diffs makes review easier.
- Write meaningful description of commits resulting from review. _"Addressing review comments"_ is **NOT** a good description! Having a quick look at good descriptions can tell you much what is going on in PR without a need to go through all of resolved comments.
## Merging PR
As soon as the reviewer is fine with the pull request and Precommit likes your code and shows "green" status, the "Approved" review status is put, which signals OpenVINO maintainers that they can merge your pull request.
This toolkit allows developers to deploy pre-trained deep learning models
through a high-level C++ Inference Engine API integrated with application logic.
through a high-level OpenVINO™ Runtime C++ and Python APIs integrated with application logic.
This open source version includes several components: namely [Model Optimizer], [nGraph] and
[Inference Engine], as well as CPU, GPU, MYRIAD, multi device and heterogeneous plugins to accelerate deep learning inferencing on Intel® CPUs and Intel® Processor Graphics.
This open source version includes several components: namely [Model Optimizer], [OpenVINO™ Runtime], [Post-Training Optimization Tool], as well as CPU, GPU, MYRIAD, multi device and heterogeneous plugins to accelerate deep learning inferencing on Intel® CPUs and Intel® Processor Graphics.
It supports pre-trained models from the [Open Model Zoo], along with 100+ open
source and public models in popular formats such as Caffe\*, TensorFlow\*,
MXNet\* and ONNX\*.
source and public models in popular formats such as TensorFlow, ONNX, PaddlePaddle, MXNet, Caffe, Kaldi.
## Repository components:
* [Inference Engine]
* [nGraph]
## Repository components
* [OpenVINO™ Runtime]
* [Model Optimizer]
* [Post-Training Optimization Tool]
## License
Deep Learning Deployment Toolkit is licensed under [Apache License Version 2.0](LICENSE).
By contributing to the project, you agree to the license and copyright terms therein
# Mute -fsanitize=function Indirect call of a function through a function pointer of the wrong type.
# Sample cases:
# call to function GetAPIVersion through pointer to incorrect function type 'void *(*)()'
# Mute -fsanitize=alignment Use of a misaligned pointer or creation of a misaligned reference. Also sanitizes assume_aligned-like attributes.
# Sample cases:
# VPU_FixedMaxHeapTest.DefaultConstructor test case load of misaligned address 0x62000000187f for type 'const DataType', which requires 4 byte alignment
# Mute -fsanitize=bool Load of a bool value which is neither true nor false.
# Samples cases:
# ie_c_api_version.apiVersion test case load of value 32, which is not a valid value for type 'bool'
# Mute -fsanitize=enum Load of a value of an enumerated type which is not in the range of representable values for that enumerated type.
# Samples cases:
# load of value 4294967295, which is not a valid value for type 'const (anonymous namespace)::onnx::Field'
Some files were not shown because too many files have changed in this diff
Show More
Reference in New Issue
Block a user
Blocking a user prevents them from interacting with repositories, such as opening or commenting on pull requests or issues. Learn more about blocking a user.