Starting tensorboard inline within a Jupyter notebook consistently times out

Consider Stack Overflow for getting support using TensorBoard—they have a larger community with better searchability:

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

Do not use this template for for setup, installation, or configuration issues. Instead, use the “installation problem” issue template:

https://github.com/tensorflow/tensorboard/issues/new?template=installation_problem.md

To report a problem with TensorBoard itself, please fill out the remainder of this template.

Environment information (required)

Please run diagnose_tensorboard.py (link below) in the same environment from which you normally run TensorFlow/TensorBoard, and paste the output here:

Diagnostics

Diagnostics output

--- check: autoidentify
INFO: diagnose_tensorboard.py version 724b56cee52e7d8eb89bbeec1f0d5ce3e38c9682

--- check: general
INFO: sys.version_info: sys.version_info(major=3, minor=8, micro=6, releaselevel='final', serial=0)
INFO: os.name: nt
INFO: os.uname(): N/A
INFO: sys.getwindowsversion(): sys.getwindowsversion(major=10, minor=0, build=19042, platform=2, service_pack='')

--- check: package_management
INFO: has conda-meta: False
INFO: $VIRTUAL_ENV: None

--- check: installed_packages
INFO: installed: tensorboard==2.3.0
INFO: installed: tensorflow==2.3.1
INFO: installed: tensorflow-estimator==2.3.0

--- check: tensorboard_python_version
INFO: tensorboard.version.VERSION: '2.3.0'

--- check: tensorflow_python_version
2020-11-09 11:08:55.313364: W tensorflow/stream_executor/platform/default/dso_loader.cc:59] Could not load dynamic library 'cudart64_101.dll'; dlerror: cudart64_101.dll not found
2020-11-09 11:08:55.314312: I tensorflow/stream_executor/cuda/cudart_stub.cc:29] Ignore above cudart dlerror if you do not have a GPU set up on your machine.
INFO: tensorflow.__version__: '2.3.1'
INFO: tensorflow.__git_version__: 'v2.3.0-54-gfcc4b966f1'

--- check: tensorboard_binary_path
INFO: which tensorboard: b'C:\\Users\\huer\\AppData\\Local\\Programs\\Python\\Python38\\Scripts\\tensorboard.exe\r\n'

--- check: addrinfos
socket.has_ipv6 = True
socket.AF_UNSPEC = <AddressFamily.AF_UNSPEC: 0>
socket.SOCK_STREAM = <SocketKind.SOCK_STREAM: 1>
socket.AI_ADDRCONFIG = <AddressInfo.AI_ADDRCONFIG: 1024>
socket.AI_PASSIVE = <AddressInfo.AI_PASSIVE: 1>
Loopback flags: <AddressInfo.AI_ADDRCONFIG: 1024>
Loopback infos: [(<AddressFamily.AF_INET6: 23>, <SocketKind.SOCK_STREAM: 1>, 0, '', ('::1', 0, 0, 0)), (<AddressFamily.AF_INET: 2>, <SocketKind.SOCK_STREAM: 1>, 0, '', ('127.0.0.1', 0))]
Wildcard flags: <AddressInfo.AI_PASSIVE: 1>
Wildcard infos: [(<AddressFamily.AF_INET6: 23>, <SocketKind.SOCK_STREAM: 1>, 0, '', ('::', 0, 0, 0)), (<AddressFamily.AF_INET: 2>, <SocketKind.SOCK_STREAM: 1>, 0, '', ('0.0.0.0', 0))]

--- check: readable_fqdn
INFO: socket.getfqdn(): 'Surface-Laptop'

--- check: stat_tensorboardinfo
INFO: directory: C:\Users\huer\AppData\Local\Temp\.tensorboard-info
INFO: os.stat(...): os.stat_result(st_mode=16895, st_ino=3940649676184517, st_dev=443364023, st_nlink=1, st_uid=0, st_gid=0, st_size=8192, st_atime=1604948751, st_mtime=1604948698, st_ctime=1603511741)
INFO: mode: 0o40777

--- check: source_trees_without_genfiles
INFO: tensorboard_roots (1): ['C:\\Users\\huer\\AppData\\Local\\Programs\\Python\\Python38\\lib\\site-packages']; bad_roots (0): []

--- check: full_pip_freeze
INFO: pip freeze --all:
absl-py==0.11.0
appdirs==1.4.4
argon2-cffi==20.1.0
astunparse==1.6.3
async-generator==1.10
attrs==20.2.0
backcall==0.2.0
black==20.8b1
bleach==3.2.1
cachetools==4.1.1
certifi==2020.6.20
cffi==1.14.3
chardet==3.0.4
click==7.1.2
colorama==0.4.4
debugpy==1.1.0
decorator==4.4.2
defusedxml==0.6.0
entrypoints==0.3
Flask==1.1.2
gast==0.3.3
google-auth==1.23.0
google-auth-oauthlib==0.4.2
google-pasta==0.2.0
grpcio==1.33.2
h5py==2.10.0
idna==2.10
ipykernel==5.3.4
ipython==7.19.0
ipython-genutils==0.2.0
ipywidgets==7.5.1
itsdangerous==1.1.0
jedi==0.17.2
Jinja2==2.11.2
jsonschema==3.2.0
jupyter==1.0.0
jupyter-client==6.1.7
jupyter-console==6.2.0
jupyter-core==4.6.3
jupyterlab-pygments==0.1.2
Keras-Preprocessing==1.1.2
Markdown==3.3.3
MarkupSafe==1.1.1
mistune==0.8.4
mypy-extensions==0.4.3
nbclient==0.5.1
nbconvert==6.0.7
nbformat==5.0.8
nest-asyncio==1.4.2
notebook==6.1.4
numpy==1.18.5
oauthlib==3.1.0
opt-einsum==3.3.0
packaging==20.4
pandas==1.1.3
pandocfilters==1.4.3
parso==0.7.1
pathspec==0.8.0
pickleshare==0.7.5
pip==20.2.1
prometheus-client==0.8.0
prompt-toolkit==3.0.8
protobuf==3.13.0
pyasn1==0.4.8
pyasn1-modules==0.2.8
pycparser==2.20
Pygments==2.7.2
pyparsing==2.4.7
pyrsistent==0.17.3
python-dateutil==2.8.1
pytz==2020.4
pywin32==228
pywinpty==0.5.7
pyzmq==19.0.2
qtconsole==4.7.7
QtPy==1.9.0
regex==2020.9.27
requests==2.24.0
requests-oauthlib==1.3.0
rsa==4.6
selenium==3.141.0
Send2Trash==1.5.0
setuptools==49.2.1
six==1.15.0
tensorboard==2.3.0
tensorboard-plugin-wit==1.7.0
tensorflow==2.3.1
tensorflow-estimator==2.3.0
termcolor==1.1.0
terminado==0.9.1
testpath==0.4.4
toml==0.10.1
tornado==6.1
traitlets==5.0.5
typed-ast==1.4.1
typing-extensions==3.7.4.3
urllib3==1.25.11
wcwidth==0.2.5
webencodings==0.5.1
Werkzeug==1.0.1
wheel==0.35.1
widgetsnbextension==3.5.1
wrapt==1.12.1

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Issue description

Please describe the bug as clearly as possible. How can we reproduce the problem without additional resources (including external data files and proprietary Python modules)?

Repro steps:

1. Install Python 3.8.6 64-bit on Windows 10
2. Run python -m pip install jupyter tensorflow
3. Run jupyter notebook
4. Create a Jupyter notebook in the browser
5. Run %load_ext tensorboard in one cell, then %tensorboard --logdir logs/fit in a second cell
6. I’d expect to see the tensorboard website appear inline with the message about no active dashboards. Instead, I get a message about timing out waiting for TensorBoard to start:

7. If I rerun the cell with %tensorboard --logdir logs/fit, tensorboard does show up inline.

The diagnostic info above is based on my local machine. I initially thought my local box might simply have a busted tensorboard install, but the problem persisted even after uninstalling and reinstalling tensorflow and tensorboard. I was able to repro this on a clean Windows VM with the above repro steps.

Debugging the iopub messages sent by the Jupyter kernel, the Jupyter kernel does send a message with the ‘Launching TensorBoard…’ message in response to the execution request for %tensorboard --logdir logs/fit the first time, but it doesn’t ever send the iframe back. For some reason requesting the tensorboard launch again results in an immediate response about ‘Reusing TensorBoard on port <…>’, followed by a message with the iframe for display in the cell output.

Happy to provide additional information that will help with diagnosing the issue!

[wchargin]

Hi @joyceerhl—we think we have a fix for this in #4407. It should go out in today’s tb-nightly, or you can build your own Pip package from head with bazel build //tensorboard/pip_package, or you can manually patch the diff into your virtualenv (it’s a small change to one Python file). If this doesn’t fix it on your end, please let us know and we can reopen this. Thanks!

[wchargin]

Excellent! Thanks for letting us know.