<p dir="auto"><em>Please make sure that this is a build/installation issue. As per our <a href="https://github.com/tensorflow/tensorflow/blob/master/ISSUES.md">GitHub Policy</a>, we only address code/doc bugs, performance issues, feature requests and build/installation issues on GitHub. tag:build_template</em></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>Mobile device (e.g. iPhone 8, Pixel 2, Samsung Galaxy) if the issue happens on mobile device: N/A</li>
<li>TensorFlow installed from (source or binary): Source</li>
<li>TensorFlow version: 1.12</li>
<li>Python version: 3.6</li>
<li>Installed using virtualenv? pip? conda?: pip</li>
<li>Bazel version (if compiling from source): 0.18.1</li>
<li>GCC/Compiler version (if compiling from source): Visual Stuido 2015</li>
<li>CUDA/cuDNN version: CUDA 10/ cudnn 7</li>
<li>GPU model and memory: Titan V</li>
</ul>
<p dir="auto"><strong>Describe the problem</strong><br>
Unable to build with Tensor RT in windows. Newest version (Tensor RT5) claims windows support but build script (configure.py) assumes linux only.</p>
<p dir="auto">Has anybody successfully built with TensorRT5 on windows? Will TF 1.13 include support?</p>
<p dir="auto">Ref <a class="issue-link js-issue-link" data-error-text="Failed to load title" data-id="211483260" data-permission-text="Title is private" data-url="https://github.com/tensorflow/tensorflow/issues/8023" data-hovercard-type="issue" data-hovercard-url="/tensorflow/tensorflow/issues/8023/hovercard" href="https://github.com/tensorflow/tensorflow/issues/8023">#8023</a></p>
<h3 dir="auto">System information</h3>
<ul dir="auto">
<li><strong>Have I written custom code (as opposed to using a stock example script provided in TensorFlow)</strong>: Yes</li>
<li><strong>OS Platform and Distribution (e.g., Linux Ubuntu 16.04)</strong>: Ubuntu 16.04</li>
<li><strong>TensorFlow installed from (source or binary)</strong>: Docker image</li>
<li><strong>TensorFlow version (use command below)</strong>: 1.1.0</li>
<li><strong>Bazel version (if compiling from source)</strong>: N/A</li>
<li><strong>CUDA/cuDNN version</strong>: Per Docker image</li>
<li><strong>GPU model and memory</strong>: K80</li>
<li><strong>Exact command to reproduce</strong>: N/A</li>
</ul>
<h3 dir="auto">Describe the problem</h3>
<p dir="auto">The logging configuration in <code class="notranslate">tf_logging</code> is odd and inconsistent with how things are generally done in Python.</p>
<p dir="auto">In general, it's typical to attach handlers to the root logger in Python: <a href="https://docs.python.org/2/library/logging.html#logging.Logger.propagate" rel="nofollow">https://docs.python.org/2/library/logging.html#logging.Logger.propagate</a></p>
<p dir="auto">However, because <code class="notranslate">tf_logging</code> sets up its own stream handler, and does not disable the propagate flag, anybody who does follow the standard Python convention of attaching handlers to the root logger gets duplicated log output from TensorFlow.</p>
<p dir="auto">Per <a class="issue-link js-issue-link" data-error-text="Failed to load title" data-id="211483260" data-permission-text="Title is private" data-url="https://github.com/tensorflow/tensorflow/issues/8023" data-hovercard-type="issue" data-hovercard-url="/tensorflow/tensorflow/issues/8023/hovercard" href="https://github.com/tensorflow/tensorflow/issues/8023">#8023</a>, while this isn't a bug per se, it's still wrong and undesirable.</p>
<p dir="auto">The cleanest way forward is probably to just set <code class="notranslate">propagate=False</code> on the TF logger.</p>