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d597507 May 6, 2018
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Train a TensorFlow model locally

In this quickstart, we will run a TensorFlow model with the MNIST dataset locally in AI Tools. The MNIST database has a training set of 60,000 examples, and a test set of 10,000 examples of handwritten digits.

Prerequisites

Before you begin, ensure you have the following installed:

Google TensorFlow

Run the following command in a terminal.

pip install tensorflow

or if you have an Nvidia GPU

pip install tensorflow-gpu

NumPy and SciPy

run the following command in a terminal:

pip install numpy scipy

Download sample code

Download this GitHub repository containing samples for getting started with deep learning across TensorFlow, CNTK, Theano and more.

Open a project and train model

  • Launch Visual Studio Code and select File > Open Folder (Ctrl+K Ctrl+Of)

  • Select the examples\tensorflow\MNIST subfolder from your local samples repository.

    Project Folder

  • Open convolutional.py and press F5 to start.

    The output will be printed in the terminal window.

    Sample output from console

[!TIP] Make sure you've selected correct python environment which has necessary packages (tensorFlow, NumPy, SciPy, etc.) installed.
Use command Python: Select Interpreer to select proper Python interpreter. Refers to Setting Up Python Interpreter for detailed information.

See Also