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NervanaSystems / ngraph-python

Original Python version of Intel® Nervana™ Graph
http://ngraph.nervanasys.com/docs/legacy/
Apache License 2.0
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TensorFlow frontend for ngraph #21

Open sangameshnr opened 6 years ago

sangameshnr commented 6 years ago

Hi,

The performance of the VGG16 network imported to ngraph via TF frontend appears to be very very slow. To get the perspective, I have 3 implementations of VGG16: 1) Neon-Ng : Neon frontend in ngraph ( VGG16 using layers of neon frontend) 2) TF : TensorFlow code (VGG16 using tf.nn.conv2d, tf.nn.bias_add, tf.nn.relu/max_pool etc) 3) TF-Ng : I import the checkpoint files of the implementation 2 here .

And for batch size of 64 on a skylake machine I get the following performances: Implementation 1: 1561 GFlops/s Implementation 2: 1309 GFlops/s ( Using tensorflow 1.4.0-dev on intel python) Implementation 3: 51.82 GFlops/s.

I am trying to investigate why the TF frontend in ngraph is slow. Any inputs would be very helpful.

sangameshnr commented 6 years ago

Also, when I added tf.nn.bias_add after the tf.nn.conv2d in the TF code. The output tensors were concatenated in ngraph instead of adding them up since the axes were different. I had to write a separate function to implement this addition on the "ops_bridge.py" to make their axes same before adding.

avijit-nervana commented 6 years ago

We are working on a new version of ngraph (nGraph++) which is being implemented in C++ and the performance issue you are observing will be addressed in the forthcoming release.

sangameshnr commented 6 years ago

Thanks @avijit-nervana , I will look forward to the release.

shubhamn94 commented 5 years ago

Could someone please guide on if there's any update on this? Do we have nGraph++ which resolves the issue mentioned by Sangameshnr? I want to use TF frontend and create a new backend for nGraph.

avijit-nervana commented 5 years ago

@shubhamn94 We do have a C++ implementation for nGraph: https://github.com/NervanaSystems/ngraph.git The TensorFlow bridge is here: https://github.com/NervanaSystems/ngraph-tf.git

To get started, please clone the nGraph-TensrFlow bridge and run build_ngtf.py to build the TF version of nGraph (all C++). Please let us know if you have any questions Will be happy to help you put together a new backend for nGraph.

shubhamn94 commented 5 years ago

Sure. Thanks @avijit-nervana . Will let you know.

avijit-nervana commented 5 years ago

@shubhamn94 We recently moved the nGraph bridge repository to TensorFlow organization. Here's the new URL: https://github.com/tensorflow/ngraph-bridge

(The nGraph library remains in the same location: https://github.com/NervanaSystems/ngraph.git)

Please update your bookmarks.

shubhamn94 commented 5 years ago

Thanks for update!