<p dir="auto"><em>Please make sure that this is a bug. 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:bug_template</em></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 TensorFlow): No</li>
<li>OS Platform and Distribution (e.g., Linux Ubuntu 16.04): 18.04 LTS</li>
<li>Mobile device (e.g. iPhone 8, Pixel 2, Samsung Galaxy) if the issue happens on mobile device:</li>
<li>TensorFlow installed from (source or binary): Docker container tensorflow/tensorflow:2.0.0b1-gpu-py3</li>
<li>TensorFlow version (use command below): 2.0.0-beta1</li>
<li>Python version: 3.6</li>
<li>Bazel version (if compiling from source):</li>
<li>GCC/Compiler version (if compiling from source):</li>
<li>CUDA/cuDNN version:</li>
<li>GPU model and memory: RTX 2080 Ti</li>
</ul>
<p dir="auto">You can collect some of this information using our environment capture<br>
<a href="https://github.com/tensorflow/tensorflow/tree/master/tools/tf_env_collect.sh">script</a><br>
You can also obtain the TensorFlow version with: 1. TF 1.0: <code class="notranslate">python -c "import tensorflow as tf; print(tf.GIT_VERSION, tf.VERSION)"</code> 2. TF 2.0: <code class="notranslate">python -c "import tensorflow as tf; print(tf.version.GIT_VERSION, tf.version.VERSION)"</code></p>
<p dir="auto"><strong>Describe the current behavior</strong><br>
Running the the official example <a href="https://www.tensorflow.org/beta/tutorials/quickstart/advanced" rel="nofollow">https://www.tensorflow.org/beta/tutorials/quickstart/advanced</a> in the official container tensorflow/tensorflow:2.0.0b1-gpu-py3 got the following error:</p>
<div class="snippet-clipboard-content notranslate position-relative overflow-auto" data-snippet-clipboard-copy-content="&gt; python advanced.py 
2019-06-27 17:09:34.195179: I tensorflow/stream_executor/platform/default/dso_loader.cc:42] Successfully opened dynamic library libcuda.so.1
2019-06-27 17:09:34.231111: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:1006] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero
2019-06-27 17:09:34.231786: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1640] Found device 0 with properties: 
name: GeForce RTX 2080 Ti major: 7 minor: 5 memoryClockRate(GHz): 1.635
pciBusID: 0000:01:00.0
2019-06-27 17:09:34.232026: I tensorflow/stream_executor/platform/default/dso_loader.cc:42] Successfully opened dynamic library libcudart.so.10.0
2019-06-27 17:09:34.232777: I tensorflow/stream_executor/platform/default/dso_loader.cc:42] Successfully opened dynamic library libcublas.so.10.0
2019-06-27 17:09:34.233391: I tensorflow/stream_executor/platform/default/dso_loader.cc:42] Successfully opened dynamic library libcufft.so.10.0
2019-06-27 17:09:34.233576: I tensorflow/stream_executor/platform/default/dso_loader.cc:42] Successfully opened dynamic library libcurand.so.10.0
2019-06-27 17:09:34.234366: I tensorflow/stream_executor/platform/default/dso_loader.cc:42] Successfully opened dynamic library libcusolver.so.10.0
2019-06-27 17:09:34.235052: I tensorflow/stream_executor/platform/default/dso_loader.cc:42] Successfully opened dynamic library libcusparse.so.10.0
2019-06-27 17:09:34.236947: I tensorflow/stream_executor/platform/default/dso_loader.cc:42] Successfully opened dynamic library libcudnn.so.7
2019-06-27 17:09:34.237053: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:1006] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero
2019-06-27 17:09:34.237643: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:1006] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero
2019-06-27 17:09:34.238201: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1763] Adding visible gpu devices: 0
2019-06-27 17:09:34.238443: I tensorflow/core/platform/cpu_feature_guard.cc:142] Your CPU supports instructions that this TensorFlow binary was not compiled to use: AVX2 FMA
2019-06-27 17:09:34.323017: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:1006] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero
2019-06-27 17:09:34.324202: I tensorflow/compiler/xla/service/service.cc:168] XLA service 0x39cfd60 executing computations on platform CUDA. Devices:
2019-06-27 17:09:34.324217: I tensorflow/compiler/xla/service/service.cc:175]   StreamExecutor device (0): GeForce RTX 2080 Ti, Compute Capability 7.5
2019-06-27 17:09:34.342363: I tensorflow/core/platform/profile_utils/cpu_utils.cc:94] CPU Frequency: 3600000000 Hz
2019-06-27 17:09:34.343364: I tensorflow/compiler/xla/service/service.cc:168] XLA service 0x3d629c0 executing computations on platform Host. Devices:
2019-06-27 17:09:34.343375: I tensorflow/compiler/xla/service/service.cc:175]   StreamExecutor device (0): &lt;undefined&gt;, &lt;undefined&gt;
2019-06-27 17:09:34.343534: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:1006] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero
2019-06-27 17:09:34.344103: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1640] Found device 0 with properties: 
name: GeForce RTX 2080 Ti major: 7 minor: 5 memoryClockRate(GHz): 1.635
pciBusID: 0000:01:00.0
2019-06-27 17:09:34.344121: I tensorflow/stream_executor/platform/default/dso_loader.cc:42] Successfully opened dynamic library libcudart.so.10.0
2019-06-27 17:09:34.344128: I tensorflow/stream_executor/platform/default/dso_loader.cc:42] Successfully opened dynamic library libcublas.so.10.0
2019-06-27 17:09:34.344135: I tensorflow/stream_executor/platform/default/dso_loader.cc:42] Successfully opened dynamic library libcufft.so.10.0
2019-06-27 17:09:34.344141: I tensorflow/stream_executor/platform/default/dso_loader.cc:42] Successfully opened dynamic library libcurand.so.10.0
2019-06-27 17:09:34.344147: I tensorflow/stream_executor/platform/default/dso_loader.cc:42] Successfully opened dynamic library libcusolver.so.10.0
2019-06-27 17:09:34.344153: I tensorflow/stream_executor/platform/default/dso_loader.cc:42] Successfully opened dynamic library libcusparse.so.10.0
2019-06-27 17:09:34.344160: I tensorflow/stream_executor/platform/default/dso_loader.cc:42] Successfully opened dynamic library libcudnn.so.7
2019-06-27 17:09:34.344188: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:1006] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero
2019-06-27 17:09:34.344698: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:1006] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero
2019-06-27 17:09:34.345203: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1763] Adding visible gpu devices: 0
2019-06-27 17:09:34.345217: I tensorflow/stream_executor/platform/default/dso_loader.cc:42] Successfully opened dynamic library libcudart.so.10.0
2019-06-27 17:09:34.345897: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1181] Device interconnect StreamExecutor with strength 1 edge matrix:
2019-06-27 17:09:34.345905: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1187]      0 
2019-06-27 17:09:34.345910: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1200] 0:   N 
2019-06-27 17:09:34.346029: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:1006] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero
2019-06-27 17:09:34.346619: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:1006] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero
2019-06-27 17:09:34.347293: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1326] Created TensorFlow device (/job:localhost/replica:0/task:0/device:GPU:0 with 7784 MB memory) -&gt; physical GPU (device: 0, name: GeForce RTX 2080 Ti, pci bus id: 0000:01:00.0, compute capability: 7.5)
2019-06-27 17:09:35.539500: I tensorflow/stream_executor/platform/default/dso_loader.cc:42] Successfully opened dynamic library libcublas.so.10.0
2019-06-27 17:09:35.696347: I tensorflow/stream_executor/platform/default/dso_loader.cc:42] Successfully opened dynamic library libcudnn.so.7
2019-06-27 17:09:36.203198: E tensorflow/stream_executor/cuda/cuda_dnn.cc:329] Could not create cudnn handle: CUDNN_STATUS_INTERNAL_ERROR
2019-06-27 17:09:36.209845: E tensorflow/stream_executor/cuda/cuda_dnn.cc:329] Could not create cudnn handle: CUDNN_STATUS_INTERNAL_ERROR
2019-06-27 17:09:36.209897: W tensorflow/core/common_runtime/base_collective_executor.cc:216] BaseCollectiveExecutor::StartAbort Unknown: Failed to get convolution algorithm. This is probably because cuDNN failed to initialize, so try looking to see if a warning log message was printed above.
	 [[{{node my_model/conv2d/Conv2D}}]]
	 [[my_model/dense_1/BiasAdd/_6]]
2019-06-27 17:09:36.209959: W tensorflow/core/common_runtime/base_collective_executor.cc:216] BaseCollectiveExecutor::StartAbort Unknown: Failed to get convolution algorithm. This is probably because cuDNN failed to initialize, so try looking to see if a warning log message was printed above.
	 [[{{node my_model/conv2d/Conv2D}}]]
Traceback (most recent call last):
  File &quot;advanced.py&quot;, line 84, in &lt;module&gt;
    train_step(images, labels)
  File &quot;/usr/local/lib/python3.6/dist-packages/tensorflow/python/eager/def_function.py&quot;, line 428, in __call__
    return self._stateless_fn(*args, **kwds)
  File &quot;/usr/local/lib/python3.6/dist-packages/tensorflow/python/eager/function.py&quot;, line 1335, in __call__
    return graph_function._filtered_call(args, kwargs)  # pylint: disable=protected-access
  File &quot;/usr/local/lib/python3.6/dist-packages/tensorflow/python/eager/function.py&quot;, line 589, in _filtered_call
    (t for t in nest.flatten((args, kwargs), expand_composites=True)
  File &quot;/usr/local/lib/python3.6/dist-packages/tensorflow/python/eager/function.py&quot;, line 671, in _call_flat
    outputs = self._inference_function.call(ctx, args)
  File &quot;/usr/local/lib/python3.6/dist-packages/tensorflow/python/eager/function.py&quot;, line 445, in call
    ctx=ctx)
  File &quot;/usr/local/lib/python3.6/dist-packages/tensorflow/python/eager/execute.py&quot;, line 67, in quick_execute
    six.raise_from(core._status_to_exception(e.code, message), None)
  File &quot;&lt;string&gt;&quot;, line 3, in raise_from
tensorflow.python.framework.errors_impl.UnknownError: 2 root error(s) found.
  (0) Unknown:  Failed to get convolution algorithm. This is probably because cuDNN failed to initialize, so try looking to see if a warning log message was printed above.
	 [[node my_model/conv2d/Conv2D (defined at advanced.py:36) ]]
  (1) Unknown:  Failed to get convolution algorithm. This is probably because cuDNN failed to initialize, so try looking to see if a warning log message was printed above.
	 [[node my_model/conv2d/Conv2D (defined at advanced.py:36) ]]
	 [[my_model/dense_1/BiasAdd/_6]]
0 successful operations.
0 derived errors ignored. [Op:__inference_train_step_848]

Errors may have originated from an input operation.
Input Source operations connected to node my_model/conv2d/Conv2D:
 images (defined at advanced.py:84)

Input Source operations connected to node my_model/conv2d/Conv2D:
 images (defined at advanced.py:84)

Function call stack:
train_step -&gt; train_step
"><pre class="notranslate"><code class="notranslate">&gt; python advanced.py 
2019-06-27 17:09:34.195179: I tensorflow/stream_executor/platform/default/dso_loader.cc:42] Successfully opened dynamic library libcuda.so.1
2019-06-27 17:09:34.231111: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:1006] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero
2019-06-27 17:09:34.231786: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1640] Found device 0 with properties: 
name: GeForce RTX 2080 Ti major: 7 minor: 5 memoryClockRate(GHz): 1.635
pciBusID: 0000:01:00.0
2019-06-27 17:09:34.232026: I tensorflow/stream_executor/platform/default/dso_loader.cc:42] Successfully opened dynamic library libcudart.so.10.0
2019-06-27 17:09:34.232777: I tensorflow/stream_executor/platform/default/dso_loader.cc:42] Successfully opened dynamic library libcublas.so.10.0
2019-06-27 17:09:34.233391: I tensorflow/stream_executor/platform/default/dso_loader.cc:42] Successfully opened dynamic library libcufft.so.10.0
2019-06-27 17:09:34.233576: I tensorflow/stream_executor/platform/default/dso_loader.cc:42] Successfully opened dynamic library libcurand.so.10.0
2019-06-27 17:09:34.234366: I tensorflow/stream_executor/platform/default/dso_loader.cc:42] Successfully opened dynamic library libcusolver.so.10.0
2019-06-27 17:09:34.235052: I tensorflow/stream_executor/platform/default/dso_loader.cc:42] Successfully opened dynamic library libcusparse.so.10.0
2019-06-27 17:09:34.236947: I tensorflow/stream_executor/platform/default/dso_loader.cc:42] Successfully opened dynamic library libcudnn.so.7
2019-06-27 17:09:34.237053: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:1006] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero
2019-06-27 17:09:34.237643: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:1006] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero
2019-06-27 17:09:34.238201: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1763] Adding visible gpu devices: 0
2019-06-27 17:09:34.238443: I tensorflow/core/platform/cpu_feature_guard.cc:142] Your CPU supports instructions that this TensorFlow binary was not compiled to use: AVX2 FMA
2019-06-27 17:09:34.323017: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:1006] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero
2019-06-27 17:09:34.324202: I tensorflow/compiler/xla/service/service.cc:168] XLA service 0x39cfd60 executing computations on platform CUDA. Devices:
2019-06-27 17:09:34.324217: I tensorflow/compiler/xla/service/service.cc:175]   StreamExecutor device (0): GeForce RTX 2080 Ti, Compute Capability 7.5
2019-06-27 17:09:34.342363: I tensorflow/core/platform/profile_utils/cpu_utils.cc:94] CPU Frequency: 3600000000 Hz
2019-06-27 17:09:34.343364: I tensorflow/compiler/xla/service/service.cc:168] XLA service 0x3d629c0 executing computations on platform Host. Devices:
2019-06-27 17:09:34.343375: I tensorflow/compiler/xla/service/service.cc:175]   StreamExecutor device (0): &lt;undefined&gt;, &lt;undefined&gt;
2019-06-27 17:09:34.343534: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:1006] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero
2019-06-27 17:09:34.344103: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1640] Found device 0 with properties: 
name: GeForce RTX 2080 Ti major: 7 minor: 5 memoryClockRate(GHz): 1.635
pciBusID: 0000:01:00.0
2019-06-27 17:09:34.344121: I tensorflow/stream_executor/platform/default/dso_loader.cc:42] Successfully opened dynamic library libcudart.so.10.0
2019-06-27 17:09:34.344128: I tensorflow/stream_executor/platform/default/dso_loader.cc:42] Successfully opened dynamic library libcublas.so.10.0
2019-06-27 17:09:34.344135: I tensorflow/stream_executor/platform/default/dso_loader.cc:42] Successfully opened dynamic library libcufft.so.10.0
2019-06-27 17:09:34.344141: I tensorflow/stream_executor/platform/default/dso_loader.cc:42] Successfully opened dynamic library libcurand.so.10.0
2019-06-27 17:09:34.344147: I tensorflow/stream_executor/platform/default/dso_loader.cc:42] Successfully opened dynamic library libcusolver.so.10.0
2019-06-27 17:09:34.344153: I tensorflow/stream_executor/platform/default/dso_loader.cc:42] Successfully opened dynamic library libcusparse.so.10.0
2019-06-27 17:09:34.344160: I tensorflow/stream_executor/platform/default/dso_loader.cc:42] Successfully opened dynamic library libcudnn.so.7
2019-06-27 17:09:34.344188: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:1006] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero
2019-06-27 17:09:34.344698: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:1006] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero
2019-06-27 17:09:34.345203: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1763] Adding visible gpu devices: 0
2019-06-27 17:09:34.345217: I tensorflow/stream_executor/platform/default/dso_loader.cc:42] Successfully opened dynamic library libcudart.so.10.0
2019-06-27 17:09:34.345897: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1181] Device interconnect StreamExecutor with strength 1 edge matrix:
2019-06-27 17:09:34.345905: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1187]      0 
2019-06-27 17:09:34.345910: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1200] 0:   N 
2019-06-27 17:09:34.346029: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:1006] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero
2019-06-27 17:09:34.346619: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:1006] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero
2019-06-27 17:09:34.347293: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1326] Created TensorFlow device (/job:localhost/replica:0/task:0/device:GPU:0 with 7784 MB memory) -&gt; physical GPU (device: 0, name: GeForce RTX 2080 Ti, pci bus id: 0000:01:00.0, compute capability: 7.5)
2019-06-27 17:09:35.539500: I tensorflow/stream_executor/platform/default/dso_loader.cc:42] Successfully opened dynamic library libcublas.so.10.0
2019-06-27 17:09:35.696347: I tensorflow/stream_executor/platform/default/dso_loader.cc:42] Successfully opened dynamic library libcudnn.so.7
2019-06-27 17:09:36.203198: E tensorflow/stream_executor/cuda/cuda_dnn.cc:329] Could not create cudnn handle: CUDNN_STATUS_INTERNAL_ERROR
2019-06-27 17:09:36.209845: E tensorflow/stream_executor/cuda/cuda_dnn.cc:329] Could not create cudnn handle: CUDNN_STATUS_INTERNAL_ERROR
2019-06-27 17:09:36.209897: W tensorflow/core/common_runtime/base_collective_executor.cc:216] BaseCollectiveExecutor::StartAbort Unknown: Failed to get convolution algorithm. This is probably because cuDNN failed to initialize, so try looking to see if a warning log message was printed above.
	 [[{{node my_model/conv2d/Conv2D}}]]
	 [[my_model/dense_1/BiasAdd/_6]]
2019-06-27 17:09:36.209959: W tensorflow/core/common_runtime/base_collective_executor.cc:216] BaseCollectiveExecutor::StartAbort Unknown: Failed to get convolution algorithm. This is probably because cuDNN failed to initialize, so try looking to see if a warning log message was printed above.
	 [[{{node my_model/conv2d/Conv2D}}]]
Traceback (most recent call last):
  File "advanced.py", line 84, in &lt;module&gt;
    train_step(images, labels)
  File "/usr/local/lib/python3.6/dist-packages/tensorflow/python/eager/def_function.py", line 428, in __call__
    return self._stateless_fn(*args, **kwds)
  File "/usr/local/lib/python3.6/dist-packages/tensorflow/python/eager/function.py", line 1335, in __call__
    return graph_function._filtered_call(args, kwargs)  # pylint: disable=protected-access
  File "/usr/local/lib/python3.6/dist-packages/tensorflow/python/eager/function.py", line 589, in _filtered_call
    (t for t in nest.flatten((args, kwargs), expand_composites=True)
  File "/usr/local/lib/python3.6/dist-packages/tensorflow/python/eager/function.py", line 671, in _call_flat
    outputs = self._inference_function.call(ctx, args)
  File "/usr/local/lib/python3.6/dist-packages/tensorflow/python/eager/function.py", line 445, in call
    ctx=ctx)
  File "/usr/local/lib/python3.6/dist-packages/tensorflow/python/eager/execute.py", line 67, in quick_execute
    six.raise_from(core._status_to_exception(e.code, message), None)
  File "&lt;string&gt;", line 3, in raise_from
tensorflow.python.framework.errors_impl.UnknownError: 2 root error(s) found.
  (0) Unknown:  Failed to get convolution algorithm. This is probably because cuDNN failed to initialize, so try looking to see if a warning log message was printed above.
	 [[node my_model/conv2d/Conv2D (defined at advanced.py:36) ]]
  (1) Unknown:  Failed to get convolution algorithm. This is probably because cuDNN failed to initialize, so try looking to see if a warning log message was printed above.
	 [[node my_model/conv2d/Conv2D (defined at advanced.py:36) ]]
	 [[my_model/dense_1/BiasAdd/_6]]
0 successful operations.
0 derived errors ignored. [Op:__inference_train_step_848]

Errors may have originated from an input operation.
Input Source operations connected to node my_model/conv2d/Conv2D:
 images (defined at advanced.py:84)

Input Source operations connected to node my_model/conv2d/Conv2D:
 images (defined at advanced.py:84)

Function call stack:
train_step -&gt; train_step

</code></pre></div>
<p dir="auto"><strong>Describe the expected behavior</strong></p>
<p dir="auto"><strong>Code to reproduce the issue</strong><br>
Provide a reproducible test case that is the bare minimum necessary to generate the problem.</p>
<p dir="auto"><strong>Other info / logs</strong><br>
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>
<p dir="auto">Please go to Stack Overflow for help and support:</p>
<p dir="auto"><a href="https://stackoverflow.com/questions/tagged/tensorflow" rel="nofollow">https://stackoverflow.com/questions/tagged/tensorflow</a></p>
<p dir="auto">If you open a GitHub issue, here is our policy:</p>
<ol dir="auto">
<li>It must be a bug or a feature request.</li>
<li>The form below must be filled out.</li>
<li>It shouldn't be a TensorBoard issue. Those go <a href="https://github.com/tensorflow/tensorboard/issues">here</a>.</li>
</ol>
<p dir="auto"><strong>Here's why we have that policy</strong>: TensorFlow 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>
<hr>
<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>:</li>
<li><strong>OS Platform and Distribution (e.g., Linux Ubuntu 16.04)</strong>: Archlinux</li>
<li><strong>TensorFlow installed from (source or binary)</strong>:source</li>
<li><strong>TensorFlow version (use command below)</strong>:1.3.0</li>
<li><strong>Python version</strong>: 3.6.2</li>
<li><strong>Bazel version (if compiling from source)</strong>: 0.5.4</li>
<li><strong>CUDA/cuDNN version</strong>:8.0.61</li>
<li><strong>GPU model and memory</strong>: GTX 1070 7.92GiB</li>
<li><strong>Exact command to reproduce</strong>:</li>
</ul>
<div class="snippet-clipboard-content notranslate position-relative overflow-auto" data-snippet-clipboard-copy-content="from tensorflow.examples.tutorials.mnist import input_data"><pre class="notranslate"><code class="notranslate">from tensorflow.examples.tutorials.mnist import input_data
</code></pre></div>
<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</p>
<p dir="auto">python -c "import tensorflow as tf; print(tf.GIT_VERSION, tf.VERSION)"</p>
<h3 dir="auto">Describe the problem</h3>
<p dir="auto">Describe the problem clearly here. Be sure to convey here why it's a bug in TensorFlow or a feature request.</p>
<p dir="auto">when I import input_data module from tensorflow.examples.tutorials.mnist, python throws the following errors.And I cannot find the files related to tensorboard under tensorflow/contrib directory.<br>
I dont know if the issue is a tensorboard issue.</p>
<div class="highlight highlight-source-shell notranslate position-relative overflow-auto" dir="auto" data-snippet-clipboard-copy-content="Traceback (most recent call last):
  File &quot;tf_mnist.py&quot;, line 1, in &lt;module&gt;
    from tensorflow.examples.tutorials.mnist import input_data
  File &quot;/usr/lib/python3.6/site-packages/tensorflow/examples/tutorials/mnist/__init__.py&quot;, line 21, in &lt;modul
e&gt;
    from tensorflow.examples.tutorials.mnist import input_data
  File &quot;/usr/lib/python3.6/site-packages/tensorflow/examples/tutorials/mnist/input_data.py&quot;, line 29, in &lt;mod
ule&gt;
    from tensorflow.contrib.learn.python.learn.datasets.mnist import read_data_sets
  File &quot;/usr/lib/python3.6/site-packages/tensorflow/contrib/__init__.py&quot;, line 38, in &lt;module&gt;
    from tensorflow.contrib import keras
  File &quot;/usr/lib/python3.6/site-packages/tensorflow/contrib/keras/__init__.py&quot;, line 26, in &lt;module&gt;
    from tensorflow.contrib.keras.api.keras import *
  File &quot;/usr/lib/python3.6/site-packages/tensorflow/contrib/keras/api/keras/__init__.py&quot;, line 25, in &lt;module
&gt;
    from tensorflow.contrib.keras.api.keras import activations
  File &quot;/usr/lib/python3.6/site-packages/tensorflow/contrib/keras/api/keras/activations/__init__.py&quot;, line 22
, in &lt;module&gt;
    from tensorflow.contrib.keras.python.keras.activations import elu
  File &quot;/usr/lib/python3.6/site-packages/tensorflow/contrib/keras/python/keras/__init__.py&quot;, line 21, in &lt;mod
ule&gt;
    from tensorflow.contrib.keras.python.keras import activations
  File &quot;/usr/lib/python3.6/site-packages/tensorflow/contrib/keras/python/keras/activations.py&quot;, line 24, in &lt;
module&gt;
    from tensorflow.contrib.keras.python.keras.engine import Layer
  File &quot;/usr/lib/python3.6/site-packages/tensorflow/contrib/keras/python/keras/engine/__init__.py&quot;, line 26,
in &lt;module&gt;
    from tensorflow.contrib.keras.python.keras.engine.training import Model
  File &quot;/usr/lib/python3.6/site-packages/tensorflow/contrib/keras/python/keras/engine/training.py&quot;, line 28,
in &lt;module&gt;
    from tensorflow.contrib.keras.python.keras import callbacks as cbks
  File &quot;/usr/lib/python3.6/site-packages/tensorflow/contrib/keras/python/keras/callbacks.py&quot;, line 34, in &lt;mo
dule&gt;
    from tensorflow.contrib.tensorboard.plugins import projector
ModuleNotFoundError: No module named 'tensorflow.contrib.tensorboard'"><pre class="notranslate">Traceback (most recent call last):
  File <span class="pl-s"><span class="pl-pds">"</span>tf_mnist.py<span class="pl-pds">"</span></span>, line 1, <span class="pl-k">in</span> <span class="pl-k">&lt;</span>module<span class="pl-k">&gt;</span>
    from tensorflow.examples.tutorials.mnist import input_data
  File <span class="pl-s"><span class="pl-pds">"</span>/usr/lib/python3.6/site-packages/tensorflow/examples/tutorials/mnist/__init__.py<span class="pl-pds">"</span></span>, line 21, <span class="pl-k">in</span> <span class="pl-k">&lt;</span>modul
e<span class="pl-k">&gt;</span>
    from tensorflow.examples.tutorials.mnist import input_data
  File <span class="pl-s"><span class="pl-pds">"</span>/usr/lib/python3.6/site-packages/tensorflow/examples/tutorials/mnist/input_data.py<span class="pl-pds">"</span></span>, line 29, <span class="pl-k">in</span> <span class="pl-k">&lt;</span>mod
ule<span class="pl-k">&gt;</span>
    from tensorflow.contrib.learn.python.learn.datasets.mnist import read_data_sets
  File <span class="pl-s"><span class="pl-pds">"</span>/usr/lib/python3.6/site-packages/tensorflow/contrib/__init__.py<span class="pl-pds">"</span></span>, line 38, <span class="pl-k">in</span> <span class="pl-k">&lt;</span>module<span class="pl-k">&gt;</span>
    from tensorflow.contrib import keras
  File <span class="pl-s"><span class="pl-pds">"</span>/usr/lib/python3.6/site-packages/tensorflow/contrib/keras/__init__.py<span class="pl-pds">"</span></span>, line 26, <span class="pl-k">in</span> <span class="pl-k">&lt;</span>module<span class="pl-k">&gt;</span>
    from tensorflow.contrib.keras.api.keras import <span class="pl-k">*</span>
  File <span class="pl-s"><span class="pl-pds">"</span>/usr/lib/python3.6/site-packages/tensorflow/contrib/keras/api/keras/__init__.py<span class="pl-pds">"</span></span>, line 25, <span class="pl-k">in</span> <span class="pl-k">&lt;</span>module
<span class="pl-k">&gt;</span>
    from tensorflow.contrib.keras.api.keras import activations
  File <span class="pl-s"><span class="pl-pds">"</span>/usr/lib/python3.6/site-packages/tensorflow/contrib/keras/api/keras/activations/__init__.py<span class="pl-pds">"</span></span>, line 22
, <span class="pl-k">in</span> <span class="pl-k">&lt;</span>module<span class="pl-k">&gt;</span>
    from tensorflow.contrib.keras.python.keras.activations import elu
  File <span class="pl-s"><span class="pl-pds">"</span>/usr/lib/python3.6/site-packages/tensorflow/contrib/keras/python/keras/__init__.py<span class="pl-pds">"</span></span>, line 21, <span class="pl-k">in</span> <span class="pl-k">&lt;</span>mod
ule<span class="pl-k">&gt;</span>
    from tensorflow.contrib.keras.python.keras import activations
  File <span class="pl-s"><span class="pl-pds">"</span>/usr/lib/python3.6/site-packages/tensorflow/contrib/keras/python/keras/activations.py<span class="pl-pds">"</span></span>, line 24, <span class="pl-k">in</span> <span class="pl-k">&lt;</span>
module<span class="pl-k">&gt;</span>
    from tensorflow.contrib.keras.python.keras.engine import Layer
  File <span class="pl-s"><span class="pl-pds">"</span>/usr/lib/python3.6/site-packages/tensorflow/contrib/keras/python/keras/engine/__init__.py<span class="pl-pds">"</span></span>, line 26,
<span class="pl-k">in</span> <span class="pl-k">&lt;</span>module<span class="pl-k">&gt;</span>
    from tensorflow.contrib.keras.python.keras.engine.training import Model
  File <span class="pl-s"><span class="pl-pds">"</span>/usr/lib/python3.6/site-packages/tensorflow/contrib/keras/python/keras/engine/training.py<span class="pl-pds">"</span></span>, line 28,
<span class="pl-k">in</span> <span class="pl-k">&lt;</span>module<span class="pl-k">&gt;</span>
    from tensorflow.contrib.keras.python.keras import callbacks as cbks
  File <span class="pl-s"><span class="pl-pds">"</span>/usr/lib/python3.6/site-packages/tensorflow/contrib/keras/python/keras/callbacks.py<span class="pl-pds">"</span></span>, line 34, <span class="pl-k">in</span> <span class="pl-k">&lt;</span>mo
dule<span class="pl-k">&gt;</span>
    from tensorflow.contrib.tensorboard.plugins import projector
ModuleNotFoundError: No module named <span class="pl-s"><span class="pl-pds">'</span>tensorflow.contrib.tensorboard<span class="pl-pds">'</span></span></pre></div>
<p dir="auto">And I have installed the tensorboard package.But the problem remains.<br>
Could anyone help me?</p>
<h3 dir="auto">Source code / logs</h3>
<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>