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Updated dependencies:

  • NumPy 1.15.4 =>1.18.2
  • Pillow 5.2.0=>6.2.2
  • TensorFlow 1.13.1 =>1.15.2
  • Keras 2.2.4 =>2.2.5
  • MXNet 1.2.0 =>1.6.0
  • CNTK 2.6 =>2.7
  • SciPy==1.4.1
  • Scikit-image==0.16.2

Bug Fixed and Improvement:

  • Fix op [LRN]
  • Fix tensorflow_parser[Slice], [DepthwiseConv2dNative]
  • Fix caffe_emitter[Relu6]
  • Add op [Unpool]
  • Add keras [Affine]
  • Add tensorflow [AddV2], [FusedBatchNormV3]
  • Stability improvements.

Tips:

We recommand Python 3.6 since Python 2 has retired. If you experience incompatibility with other Python 3.x versions, please submit an issue.

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Updated dependencies:

Numpy 1.14.5 => 1.15.4
Tensorflow 1.9.0 => 1.13.1
Keras 2.1.6=>2.2.4
CoreML 0.8=> 2.1.0
Cntk 2.5.1=>2.6
MXNet 1.1.0 post0 => 1.2.0
Onnx 1.2.1=>1.4.1
Onnx-tf =>1.2.1(python3), 1.1.2(python2)

Bug Fixes and Improvements:

  • Fix Caffe constant emit
  • Add visual studio solution file
  • Add pytorch_emit [Prelu]
  • Add tf_parser & pytorch_emit [Cast]
  • Add keras_parser [Conv1DTranspose], [Conv2DTranspose], [Conv3DTranspose]
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  1. Initial implementation for RNN operators including GRU (Gated Recurrent Unit) cell, LSTM (Long Short-Term Memory) cell (no support for peephole yet) by matching the cell's corresponding pattern and fold them into a fuction or class in target framework.

  2. Various fixes and stability improvements.

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  1. Support for for ssd and fastrcnn in tensorflow frozen parser.

  2. Initial support for resnet-v2 , inception_resnet-v2 and facenet.

  3. Add some ops which include Pack, Shape, Scale, StrideSlice, Prelu, Mul, Abs, Sub, Squeeze.

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