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[Docs] Update MO What's new description #2481

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Oct 1, 2020
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[Docs] Update MO What's new description #2481

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51 changes: 38 additions & 13 deletions docs/MO_DG/Deep_Learning_Model_Optimizer_DevGuide.md
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Expand Up @@ -15,23 +15,48 @@ Model Optimizer produces an Intermediate Representation (IR) of the network, whi
## What's New in the Model Optimizer in this Release?

* Common changes:
* Implemented generation of a compressed OpenVINO IR suitable for INT8 inference, which takes up to 4 times less disk space than an expanded one. Use the `--disable_weights_compression` Model Optimizer command-line parameter to get an expanded version.
* Implemented an optimization transformation to replace a sub-graph with the `Erf` operation into the `GeLU` operation.
* Implemented an optimization transformation to replace an upsamping pattern that is represented as a sequence of `Split` and `Concat` operations to a single `Interpolate` operation.
* Fixed a number of Model Optimizer bugs to generate reshape-able IRs of many models with the command line parameter `--keep_shape_ops`.
* Fixed a number of Model Optimizer transformations to set operations name in an IR equal to the original framework model operation name.
* The following operations are no longer generated with `version="opset1"`: `MVN`, `ROIPooling`, `ReorgYolo`. They became a part of new `opset2` operation set and generated with `version="opset2"`. Before this fix, the operations were generated with `version="opset1"` by mistake, they were not a part of `opset1` nGraph namespace; `opset1` specification was fixed accordingly.

* Implemented several optimization transformations to replace sub-graphs of operations with HSwish, Mish, Swish and SoftPlus operations.
* Model Optimizer generates IR keeping shape-calculating sub-graphs **by default**. Previously, this behavior was triggered if the "--keep_shape_ops" command line parameter was provided. The key is ignored in this release and will be deleted in the next release. To trigger the legacy behavior to generate an IR for a fixed input shape (folding ShapeOf operations and shape-calculating sub-graphs to Constant), use the "--static_shape" command line parameter. Changing model input shape using the Inference Engine API in runtime may fail for such an IR.
* Fixed Model Optimizer conversion issues resulted in non-reshapeable IR using the Inference Engine reshape API.
* Enabled transformations to fix non-reshapeable patterns in the original networks:
* Hardcoded Reshape
* In Reshape(2D)->MatMul pattern
* Reshape->Transpose->Reshape when the pattern can be fused to the ShuffleChannels or DepthToSpace operation
* Hardcoded Interpolate
* In Interpolate->Concat pattern
* Added a dedicated requirements file for TensorFlow 2.X as well as the dedicated install prerequisites scripts.
* Replaced the SparseToDense operation with ScatterNDUpdate-4.
* ONNX*:
* Added support for the following operations: `MeanVarianceNormalization` if normalization is performed over spatial dimensions.

* Enabled an ability to specify the model output **tensor** name using the "--output" command line parameter.
* Added support for the following operations:
* Acosh
* Asinh
* Atanh
* DepthToSpace-11, 13
* DequantizeLinear-10 (zero_point must be constant)
* HardSigmoid-1,6
* QuantizeLinear-10 (zero_point must be constant)
* ReduceL1-11, 13
* ReduceL2-11, 13
* Resize-11, 13 (except mode="nearest" with 5D+ input, mode="tf_crop_and_resize", and attributes exclude_outside and extrapolation_value with non-zero values)
* ScatterND-11, 13
* SpaceToDepth-11, 13
* TensorFlow*:
* Added support for the TensorFlow Object Detection models version 1.15.X.
* Added support for the following operations: `BatchToSpaceND`, `SpaceToBatchND`, `Floor`.

* Added support for the following operations:
* Acosh
* Asinh
* Atanh
* CTCLoss
* EuclideanNorm
* ExtractImagePatches
* FloorDiv
* MXNet*:
* Added support for the following operations:
* `Reshape` with input shape values equal to -2, -3, and -4.
* Acosh
* Asinh
* Atanh
* Kaldi*:
* Fixed bug with ParallelComponent support. Now it is fully supported with no restrictions.

> **NOTE:**
> [Intel® System Studio](https://software.intel.com/en-us/system-studio) is an all-in-one, cross-platform tool suite, purpose-built to simplify system bring-up and improve system and IoT device application performance on Intel® platforms. If you are using the Intel® Distribution of OpenVINO™ with Intel® System Studio, go to [Get Started with Intel® System Studio](https://software.intel.com/en-us/articles/get-started-with-openvino-and-intel-system-studio-2019).
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