* Azure: Add Ninja
* Fix 'Install Ninja' on Linux
* Fix bin dir path on Windows
* Add -Wno-unused-variable on Mac
* Add -Wno-error=unused-command-line-argument on Mac
* Set CXXFLAGS for Mac
* Improvements
* Fix BIN_DIR on Linux
* [CPU] Updated DepthToSpace and SpaceToDepth layers to be conformant with the specification
The patch also includes n[d]hwc layout support as well as some optimizations
* [CPU][TESTS] Removed old DepthToSpace test since it doesn't corresponds to layer's specification
* [nGraph] Utilize CommonOptimizations pass with custom transformations callback
Implemented three operations: EmbeddingBagPackedSum,
EmbeddingBagOffsetsSum and EmbeddingSegmentsSum. These operations do
the same work but have a different format of inputs.
- change repo name to openvino
- update driver version
- fix path to samples data
- remove section about Movidius driver installation
- change latest release to 2020.3
- merge fixes in install_dependencies.sh from 2020 branch
adds fusing support to all available pooling kernels
tests all possible input type/output type configurations
fixes minor bug in max pooling in pooling_gpu_test.cpp
fixed minor bug with yxbf format in pooling_gpu_ref and pooling_gpu_int8_ref kernels
fixes bug with b_fs_yx_fsv32 format in pooling_gpu kernel
resolves bug with max pooling accuracy missmatch in case of non zero pad end layer parameter
resolves average pooling accuracy missmatch in case of non zero pad end layer parameter
The problem behind this error was in program_impl::init_graph() where in calculate_prior_boxes we are trying to calculate output layout of an entire network recursively which causes stack overflow. Calculating output layouts beforehand in processing order fixes this issue.
fix the following compile error:
inference-engine/src/mkldnn_plugin/mkldnn_memory_solver.hpp:60:9: error: 'int64_t' does not name a type
| 60 | int64_t size;
| | ^~~~~~~
include stdint.h to fix this.
Signed-off-by: Liwei Song <liwei.song@windriver.com>
* Create generic RecurrentSequenceDirection enum.
* Helper class RecurrentSequenceOp.
* Add ONNX GRU & RNN operators.
* Use OutputVector.
* Update doc.
* Add UTs for GRU and skip them on IE_CPU
* Add UT for bidirectional mode and fix it.
* Normalize activation function name case.
* Add unit-tests for RNN operator.
* UT for GRU with linear_before_reset set to true.
* Fix ONNX GRU for linear_before_reset case.
* Remove unnecessary symbol export macro.
* Fix CentOS error.
* Update UTs.
- Update few tests accuracy tolerance
- Update rnn_fwd_activations with new reference values and model.
* Review comment: add check for static shape
* Add UT for RNN with constant inputs W, R.
* Skip UT with const W,R on IE_CPU
