<p dir="auto">I want to test the performance of AlexNet, ZF Net, GoogLeNet, VGGNet on my own dataset. But I cannot find the code for these models in Keras, then are there any codes for AlexNet, ZF Net, GoogLeNet, VGGNet in Keras? How can I find them? Thank you so much!</p>
<p dir="auto">Please go to TF Forum for help and support:</p>
<p dir="auto"><a href="https://discuss.tensorflow.org/tag/keras" rel="nofollow">https://discuss.tensorflow.org/tag/keras</a></p>
<p dir="auto">If you open a GitHub issue, here is our policy:</p>
<p dir="auto">It must be a bug, a feature request, or a significant problem with the documentation (for small docs fixes please send a PR instead).<br>
The form below must be filled out.</p>
<p dir="auto"><strong>Here's why we have that policy:</strong>.</p>
<p dir="auto">Keras developers respond to issues. We want to focus on work that benefits the whole community, e.g., fixing bugs and adding features. Support only helps individuals. GitHub also notifies thousands of people when issues are filed. We want them to see you communicating an interesting problem, rather than being redirected to Stack Overflow.</p>
<p dir="auto"><strong>System information</strong>.</p>
<ul dir="auto">
<li>Have I written custom code (as opposed to using a stock example script provided in Keras): Yes</li>
<li>OS Platform and Distribution (e.g., Linux Ubuntu 16.04): Google Colab</li>
<li>TensorFlow installed from (source or binary):</li>
<li>TensorFlow version (use command below): 2.7.0</li>
<li>Python version: 3.7.12</li>
<li>Bazel version (if compiling from source): N/A</li>
<li>GPU model and memory: N/A</li>
<li>Exact command to reproduce: N/A</li>
</ul>
<p dir="auto">You can collect some of this information using our environment capture script:</p>
<p dir="auto"><a href="https://github.com/tensorflow/tensorflow/tree/master/tools/tf_env_collect.sh">https://github.com/tensorflow/tensorflow/tree/master/tools/tf_env_collect.sh</a></p>
<p dir="auto">You can obtain the TensorFlow version with:<br>
python -c "import tensorflow as tf; print(tf.version.GIT_VERSION, tf.version.VERSION)"</p>
<p dir="auto"><strong>Describe the problem</strong>.</p>
<p dir="auto">Describe the problem clearly here. Be sure to convey here why it's a bug in Keras or why the requested feature is needed.</p>
<p dir="auto"><strong>Describe the current behavior</strong>.</p>
<p dir="auto">Two instantiations of tf.keras.initializers.RandomNormal(..) objects with the same seed does not produce the same sequence.</p>
<p dir="auto"><strong>Describe the expected behavior</strong>.</p>
<p dir="auto">From the documentation <a href="https://www.tensorflow.org/api_docs/python/tf/keras/initializers/RandomNormal" rel="nofollow">here</a>:</p>
<div class="snippet-clipboard-content notranslate position-relative overflow-auto" data-snippet-clipboard-copy-content=" tf.keras.initializers.RandomNormal(
     mean=0.0, stddev=0.05, seed=None
 )"><pre class="notranslate"><code class="notranslate"> tf.keras.initializers.RandomNormal(
     mean=0.0, stddev=0.05, seed=None
 )
</code></pre></div>
<p dir="auto">Regarding the seed parameter, the documentation states:</p>
<blockquote>
<p dir="auto">... Note that seeded initializer will not produce same random values across multiple calls, but multiple initializers will produce same sequence when constructed with same seed value.</p>
</blockquote>
<p dir="auto">I would expect that if I pass the same seed as a parameter into the two instantiations of initializers.RandomNormal, temp and temp2, both should give the same weights on the first call, which is what I'm observing in Tensorflow 2.3.0, 2.5.0, and 2.6.0 (<a href="https://colab.research.google.com/drive/10KrXpJtxiaAmnI2vKa61hDNheqjiJyu9?usp=sharing" rel="nofollow">example</a>), but not 2.7.0.</p>
<p dir="auto"><strong><a href="https://github.com/keras-team/keras/blob/master/CONTRIBUTING.md">Contributing</a></strong>.</p>
<ul dir="auto">
<li>Do you want to contribute a PR? (yes/no): No</li>
<li>If yes, please read <a href="https://github.com/keras-team/keras/blob/master/CONTRIBUTING.md">this page</a> for instructions</li>
<li>Briefly describe your candidate solution(if contributing):</li>
</ul>
<p dir="auto"><strong>Standalone code to reproduce the issue</strong>.</p>
<p dir="auto">Provide a reproducible test case that is the bare minimum necessary to generate<br>
the problem. If possible, please share a link to Colab/Jupyter/any notebook.</p>
<p dir="auto">Using tensorflow version 2.7.0:<br>
<a href="https://colab.research.google.com/drive/1paNe8kBRzwkrZHBi7QF0yhEX8pXO0f1w?usp=sharing" rel="nofollow">https://colab.research.google.com/drive/1paNe8kBRzwkrZHBi7QF0yhEX8pXO0f1w?usp=sharing</a></p>
<p dir="auto">However, using tensorflow 2.6.0, this issue does not occur (note one has to restart the notebook after the pip install in the first cell before running the second cell):<br>
<a href="https://colab.research.google.com/drive/10KrXpJtxiaAmnI2vKa61hDNheqjiJyu9?usp=sharing" rel="nofollow">https://colab.research.google.com/drive/10KrXpJtxiaAmnI2vKa61hDNheqjiJyu9?usp=sharing</a></p>
<p dir="auto"><strong>Source code / 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. Try to provide a reproducible test case that is the bare minimum necessary to generate the problem.</p>