<p dir="auto"><strong>Windows 10<br>
TF Version: b'v1.11.0-rc2-4-gc19e29306c' 1.11.0<br>
Anaconda Python 3.6.5<br>
GPU: GeForce GTX 1070 Max-Q Design<br>
Tensorflow 2.0 (gpu) preview installed via pip.</strong></p>
<p dir="auto">I'm building a <a href="https://github.com/danaugrs/huskarl">reinforcement learning framework</a> on top of TensorFlow 2.0 using the <code class="notranslate">tf.keras</code> API and I've come across the following issue.</p>
<p dir="auto">The 2.0 API docs for <a href="https://www.tensorflow.org/versions/r2.0/api_docs/python/tf/keras/losses" rel="nofollow"><code class="notranslate">tf.keras.losses</code></a> shows many objects that are not actually available in the preview package. For example the loss classes such as Huber. Hinge, etc... are not accessible.</p>
<ol dir="auto">
<li>Why are those classes not included in the preview package?</li>
<li>Why are there both classes and functions for many of the same loss types? That seems like unnecessary duplication.<br>
2a. Why is there a <code class="notranslate">Huber</code> class but no <code class="notranslate">huber</code> function?</li>
<li>I'd love to contribute PRs and help fix these issues. Would that be desired?</li>
</ol>
<p dir="auto">Edit: This has also been noticed here: <a class="issue-link js-issue-link" data-error-text="Failed to load title" data-id="413335049" data-permission-text="Title is private" data-url="https://github.com/tensorflow/tensorflow/issues/26007" data-hovercard-type="issue" data-hovercard-url="/tensorflow/tensorflow/issues/26007/hovercard" href="https://github.com/tensorflow/tensorflow/issues/26007">#26007</a></p>
<p dir="auto"><strong>System information</strong></p>
<ul dir="auto">
<li>OS Platform and Distribution (e.g., Linux Ubuntu 16.04): Windows 10</li>
<li>TensorFlow installed from (source or binary): binary</li>
<li>TensorFlow version (or github SHA if from source): 1.12</li>
</ul>
<p dir="auto"><strong>Provide the text output from tflite_convert</strong></p>
<div class="snippet-clipboard-content notranslate position-relative overflow-auto" data-snippet-clipboard-copy-content="Some of the operators in the model are not supported by the standard TensorFlow Lite runtime and are not recognized by TensorFlow. If you have a custom implementation for them you can disable this error with --allow_custom_ops, or by setting allow_custom_ops=True when calling tf.lite.TFLiteConverter(). Here is a list of builtin operators you are using: CONCATENATION, CONV_2D, MAXIMUM, MAX_POOL_2D, MUL, PAD. Here is a list of operators for which you will need custom implementations: ExtractImagePatches.
"><pre class="notranslate"><code class="notranslate">Some of the operators in the model are not supported by the standard TensorFlow Lite runtime and are not recognized by TensorFlow. If you have a custom implementation for them you can disable this error with --allow_custom_ops, or by setting allow_custom_ops=True when calling tf.lite.TFLiteConverter(). Here is a list of builtin operators you are using: CONCATENATION, CONV_2D, MAXIMUM, MAX_POOL_2D, MUL, PAD. Here is a list of operators for which you will need custom implementations: ExtractImagePatches.

</code></pre></div>
<p dir="auto">Also, please include a link to a GraphDef or the model if possible.</p>
<p dir="auto"><strong>Any other info / logs</strong></p>
<p dir="auto">Include any logs or source code that would be helpful to diagnose the problem. If including tracebacks, please include the full traceback. Large logs and files should be attached.</p>