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I have the same problem. I am sure I have tensorflow 1.2
I am new to ML and I miss on every tutorial, even this one, example how to use it. How can I manually input new car's params and get estimated output?
same issue
the error has already been fixed in source
tensorflow/tensorflow@5c1949e
@seanmb I had a similar issue when I was using a numeric column and accidentally had the shape parameter set. In your case it looks like body_style is set to an int64 (which is the 64 in the error) but you are specifying something like tf.feature_column.numeric_column('body-style',5). Drop the 5 and it should resolve this error.
Hi, thanks for article. can you please help me understand how to use that model? simple code sample? many thanks.
if I don't have jupiter notebook (in my case I work in Azure and have no graphics), can I put all the lines of code in one text file and run through it? How?
if I don't have jupiter notebook (in my case I work in Azure and have no graphics), can I put all the lines of code in one text file and run through it? How?
Try using Google CoLab, its free online Jupyter Notebook
I have put the code in one file called code.py which I pass as input to python(3). The job terminates without any output, but with the following messages. Anything I can do to fix?
WARNING:tensorflow:Using temporary folder as model directory: /home/u23885/tmp/tmpzouq5h7f
WARNING:tensorflow:RunConfig.uid (from tensorflow.contrib.learn.python.learn.estimators.run_config) is experimental and may change or be removed at any time, and without warning.
WARNING:tensorflow:RunConfig.uid (from tensorflow.contrib.learn.python.learn.estimators.run_config) is experimental and may change or be removed at any time, and without warning.
WARNING:tensorflow:From /home/u23885/.local/lib/python3.6/site-packages/tensorflow/contrib/learn/python/learn/monitors.py:267: BaseMonitor.init (from tensorflow.contrib.learn.python.learn.monitors) is deprecated and will be removed after 2016-12-05.
Instructions for updating:
Monitors are deprecated. Please use tf.train.SessionRunHook.
In the talk, Martin mentioned that the code was written for Tensorflow 1.2, and wouldn't work with earlier versions. So my guess is that you may be using an earlier version...