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Running backtest for TensorFlowNeuralNetworkAlgorithm.py on computer

Hello,

Thank you for this amazing LEAN. I have just set up the environment and downloaded source code to my computer. I'm just wondering how to run backtest of TensorFlowNeuralNetworkAlgorithm.py on computer. I tried this on website and this worked well. However, everytime I ran backtest on my computer. It only returns thing like this:

.....
20200418 23:21:27.843 Trace:: PythonInitializer.Initialize(): start...
PythonEngine.Initialize(): Runtime.Initialize()...
Runtime.Initialize(): Py_Initialize...
Runtime.Initialize(): PyEval_InitThreads...
Runtime.Initialize(): Initialize types...
Runtime.Initialize(): Initialize types end.
Runtime.Initialize(): AssemblyManager.Initialize()...
Runtime.Initialize(): AssemblyManager.UpdatePath()...
PythonEngine.Initialize(): register atexit callback...
PythonEngine.Initialize(): GetCLRModule()...
PythonEngine.Initialize(): clr GetManifestResourceStream...
20200418 23:21:31.279 Trace:: PythonInitializer.Initialize(): ended
20200418 23:21:31.285 Trace:: AlgorithmPythonWrapper(): Python version 3.6.8 |Anaconda, Inc.| (default, Dec 29 2018, 19:07:09)
[GCC 4.2.1 Compatible Clang 4.0.1 (tags/RELEASE_401/final)]: Importing python module TensorFlowNeuralNetworkAlgorithm
Killed: 9

I don't understand the meaning of "Killled: 9". Does it mean training method not work on computer environment?

Please kindly advise if possible. Thank you very much!

Trung

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Hi Jack,

Receiving a killed 9 error could mean that your computer does not have enough memory to handle this algorithm. What are your system specifications? To help debug the error, can you also try running other algorithms, like the Keras examples?

Let us know if you have any other questions or concerns!

Best
Rahul

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The material on this website is provided for informational purposes only and does not constitute an offer to sell, a solicitation to buy, or a recommendation or endorsement for any security or strategy, nor does it constitute an offer to provide investment advisory services by QuantConnect. In addition, the material offers no opinion with respect to the suitability of any security or specific investment. QuantConnect makes no guarantees as to the accuracy or completeness of the views expressed in the website. The views are subject to change, and may have become unreliable for various reasons, including changes in market conditions or economic circumstances. All investments involve risk, including loss of principal. You should consult with an investment professional before making any investment decisions.


Update Backtest





0

The material on this website is provided for informational purposes only and does not constitute an offer to sell, a solicitation to buy, or a recommendation or endorsement for any security or strategy, nor does it constitute an offer to provide investment advisory services by QuantConnect. In addition, the material offers no opinion with respect to the suitability of any security or specific investment. QuantConnect makes no guarantees as to the accuracy or completeness of the views expressed in the website. The views are subject to change, and may have become unreliable for various reasons, including changes in market conditions or economic circumstances. All investments involve risk, including loss of principal. You should consult with an investment professional before making any investment decisions.


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