Get started to launch google-cloud-ml with my own dataset
<p>I succeeded at executing all the steps <a href="https://cloud.google.com/ml/docs/quickstarts/training#train_on_the_cloud_distributed" rel="nofollow">of the online tutorial for google cloud ml</a>.</p>

<p>But since the dataset used in this tutorial is already a TFRecord, I didn't understand well in what way transform say my numpy dataset to a TFRecord one.</p>

<p>Then, I tried to create my TFRecord using <a href="http://pastebin.com/YwXBx21V" rel="nofollow">this a little bit modified code compared to the official convert_to_records.py</a>. What I understand is that we can only convert primitive variables to TFRecord and that is why the trick to convert a list of float to bytes is used.
Then I have to somewhere convert back my string to a list of floats. Thus, I tried to perform this task with either the line 97 or the line 98 <a href="http://pastebin.com/yZ5AXZCg" rel="nofollow">in my modified script model.py</a>.</p>

<p>Unfortunately, none of these attempts is working. I always get the following error message :</p>

<pre><code>ValueError: rank of shape must be at least 2 not: 1
</code></pre>

<p>This is because the shape of my variable <em>features</em> is (batch_size,) and not (batch_size, IMAGE_PIXELS). But I don't understand why.</p>

<p>Am I trying to launch google-cloud-ml the wrong way or are there some more parameters to tweak ?</p>