Tingqian Li 068f7c8806 Revise Mish op (#6009)
* use RTTI macro

Signed-off-by: Li, Tingqian <tingqian.li@intel.com>

* add backend test

Signed-off-by: Li, Tingqian <tingqian.li@intel.com>

* add visitor API test

Signed-off-by: Li, Tingqian <tingqian.li@intel.com>

* add checks for input size and type in validate_and_infer_types()

Signed-off-by: Li, Tingqian <tingqian.li@intel.com>

* add test for incompatible input data types to type_prop

Signed-off-by: Li, Tingqian <tingqian.li@intel.com>

* disable fp16 tests for IE backend

Signed-off-by: Li, Tingqian <tingqian.li@intel.com>

* fix bugs:
add static linkage to mish_test
use T instead of double for calculation of expected answer

Signed-off-by: Li, Tingqian <tingqian.li@intel.com>
2021-06-28 06:59:25 +03:00
2021-06-28 06:59:25 +03:00
2021-06-08 11:00:02 +03:00
2021-06-22 17:43:17 +03:00
2020-07-20 17:36:08 +03:00
2021-05-31 15:24:56 +03:00
2018-10-16 13:45:03 +03:00
2021-06-22 17:43:17 +03:00
2020-11-17 16:44:44 +03:00

OpenVINO™ Toolkit

Stable release Apache License Version 2.0 GitHub branch checks state Azure DevOps builds (branch)

This toolkit allows developers to deploy pre-trained deep learning models through a high-level C++ Inference Engine API 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. 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*.

Repository components:

License

Deep Learning Deployment Toolkit is licensed under Apache License Version 2.0. By contributing to the project, you agree to the license and copyright terms therein and release your contribution under these terms.

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C++ 80.5%
Python 15.5%
C 2.8%
CMake 0.9%
Cython 0.1%