This document is dedicated to explain how to run the python script for this tutorial. The documentation is available here. Alternatively, you can check this Linear Regression using TensorFlow
blog post for further details.
WARNING:
If TensorFlow is installed in any environment(virtual environment, ...), it must be activated at first. So at first make sure the tensorFlow is available in the current environment using the following script:
Please root to the code/
directory and run the python script as the general form of below:
python [python_code_file.py]
As an example the code can be executed as follows:
python linear_regression.py --num_epochs=50
The --num_epochs
flag is to provide the number of epochs that will be used for training. The --num_epochs
flag is not required because its default value is 50
and is provided in the source code as follows:
tf.app.flags.DEFINE_integer(
'num_epochs', 50, 'The number of epochs for training the model. Default=50')
Since the code is ready-to-go, as long as the TensorFlow can be called in the IDE editor(Pycharm, Spyder,..), the code can be executed successfully.