Issue 1:
Please make sure that this is a bug. As per our GitHub Policy, we only address code/doc bugs, performance issues, feature requests and build/installation issues on GitHub. tag:bug_template

System information

Have I written custom code (as opposed to using a stock example script provided in TensorFlow): No

OS Platform and Distribution (e.g., Linux Ubuntu 16.04): 18.04 LTS

Mobile device (e.g. iPhone 8, Pixel 2, Samsung Galaxy) if the issue happens on mobile device:

TensorFlow installed from (source or binary): Docker container tensorflow/tensorflow:2.0.0b1-gpu-py3

TensorFlow version (use command below): 2.0.0-beta1

Python version: 3.6

Bazel version (if compiling from source):

GCC/Compiler version (if compiling from source):

CUDA/cuDNN version:

GPU model and memory: RTX 2080 Ti

You can collect some of this information using our environment capture

script

You can also obtain the TensorFlow version with: 1. TF 1.0: python -c "import tensorflow as tf; print(tf.GIT_VERSION, tf.VERSION)" 2. TF 2.0: python -c "import tensorflow as tf; print(tf.version.GIT_VERSION, tf.version.VERSION)"

Describe the current behavior

Running the the official example https://www.tensorflow.org/beta/tutorials/quickstart/advanced in the official container tensorflow/tensorflow:2.0.0b1-gpu-py3 got the following error:

> 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): <undefined>, <undefined>
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) -> 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 <module>
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 "<string>", 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 -> train_step

Describe the expected behavior

Code to reproduce the issue

Provide a reproducible test case that is the bare minimum necessary to generate the problem.

Other info / logs

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.

Issue 2:
Please go to Stack Overflow for help and support:

https://stackoverflow.com/questions/tagged/tensorflow

If you open a GitHub issue, here is our policy:

It must be a bug or a feature request.

The form below must be filled out.

It shouldn't be a TensorBoard issue. Those go here.

Here's why we have that policy: 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.

System information

Have I written custom code (as opposed to using a stock example script provided in TensorFlow):

OS Platform and Distribution (e.g., Linux Ubuntu 16.04): Archlinux

TensorFlow installed from (source or binary):source

TensorFlow version (use command below):1.3.0

Python version: 3.6.2

Bazel version (if compiling from source): 0.5.4

CUDA/cuDNN version:8.0.61

GPU model and memory: GTX 1070 7.92GiB

Exact command to reproduce:

from tensorflow.examples.tutorials.mnist import input_data

You can collect some of this information using our environment capture script:

https://github.com/tensorflow/tensorflow/tree/master/tools/tf_env_collect.sh

You can obtain the TensorFlow version with

python -c "import tensorflow as tf; print(tf.GIT_VERSION, tf.VERSION)"

Describe the problem

Describe the problem clearly here. Be sure to convey here why it's a bug in TensorFlow or a feature request.

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.

I dont know if the issue is a tensorboard issue.

Traceback (most recent call last):
File "tf_mnist.py", line 1, in <module>
from tensorflow.examples.tutorials.mnist import input_data
File "/usr/lib/python3.6/site-packages/tensorflow/examples/tutorials/mnist/__init__.py", line 21, in <modul
e>
from tensorflow.examples.tutorials.mnist import input_data
File "/usr/lib/python3.6/site-packages/tensorflow/examples/tutorials/mnist/input_data.py", line 29, in <mod
ule>
from tensorflow.contrib.learn.python.learn.datasets.mnist import read_data_sets
File "/usr/lib/python3.6/site-packages/tensorflow/contrib/__init__.py", line 38, in <module>
from tensorflow.contrib import keras
File "/usr/lib/python3.6/site-packages/tensorflow/contrib/keras/__init__.py", line 26, in <module>
from tensorflow.contrib.keras.api.keras import *
File "/usr/lib/python3.6/site-packages/tensorflow/contrib/keras/api/keras/__init__.py", line 25, in <module
>
from tensorflow.contrib.keras.api.keras import activations
File "/usr/lib/python3.6/site-packages/tensorflow/contrib/keras/api/keras/activations/__init__.py", line 22
, in <module>
from tensorflow.contrib.keras.python.keras.activations import elu
File "/usr/lib/python3.6/site-packages/tensorflow/contrib/keras/python/keras/__init__.py", line 21, in <mod
ule>
from tensorflow.contrib.keras.python.keras import activations
File "/usr/lib/python3.6/site-packages/tensorflow/contrib/keras/python/keras/activations.py", line 24, in <
module>
from tensorflow.contrib.keras.python.keras.engine import Layer
File "/usr/lib/python3.6/site-packages/tensorflow/contrib/keras/python/keras/engine/__init__.py", line 26,
in <module>
from tensorflow.contrib.keras.python.keras.engine.training import Model
File "/usr/lib/python3.6/site-packages/tensorflow/contrib/keras/python/keras/engine/training.py", line 28,
in <module>
from tensorflow.contrib.keras.python.keras import callbacks as cbks
File "/usr/lib/python3.6/site-packages/tensorflow/contrib/keras/python/keras/callbacks.py", line 34, in <mo
dule>
from tensorflow.contrib.tensorboard.plugins import projector
ModuleNotFoundError: No module named 'tensorflow.contrib.tensorboard'

And I have installed the tensorboard package.But the problem remains.

Could anyone help me?

Source code / logs

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.