tensorflow / tensorflow/tensorboard
No step marker observed and hence the step time is unknown
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Description
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 516a2f9433ba4f9c3a4fdb0f89735870eda054a1
--- check: general
INFO: sys.version_info: sys.version_info(major=3, minor=8, micro=10, releaselevel='final', serial=0)
INFO: os.name: posix
INFO: os.uname(): posix.uname_result(sysname='Linux', nodename='71d6fe811d18', release='6.0.5-200.fc36.x86_64', version='#1 SMP PREEMPT_DYNAMIC Wed Oct 26 15:55:21 UTC 2022', machine='x86_64')
INFO: sys.getwindowsversion(): N/A
--- check: package_management
INFO: has conda-meta: False
INFO: $VIRTUAL_ENV: None
--- check: installed_packages
INFO: installed: tensorboard==2.11.0
WARNING: no installation among: ['tensorflow', 'tensorflow-gpu', 'tf-nightly', 'tf-nightly-2.0-preview', 'tf-nightly-gpu', 'tf-nightly-gpu-2.0-preview']
INFO: installed: tensorflow-estimator==2.11.0
INFO: installed: tensorboard-data-server==0.6.1
--- check: tensorboard_python_version
INFO: tensorboard.version.VERSION: '2.11.0'
--- check: tensorflow_python_version
INFO: tensorflow.__version__: '2.11.0'
INFO: tensorflow.__git_version__: 'v2.11.0-rc2-17-gd5b57ca93e5'
--- check: tensorboard_data_server_version
INFO: data server binary: '/usr/local/lib/python3.8/dist-packages/tensorboard_data_server/bin/server'
INFO: data server binary version: b'rustboard 0.6.1'
--- check: tensorboard_binary_path
INFO: which tensorboard: b'/usr/local/bin/tensorboard\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: 32>
socket.AI_PASSIVE = <AddressInfo.AI_PASSIVE: 1>
Loopback flags: <AddressInfo.AI_ADDRCONFIG: 32>
Loopback infos: [(<AddressFamily.AF_INET: 2>, <SocketKind.SOCK_STREAM: 1>, 6, '', ('127.0.0.1', 0))]
Wildcard flags: <AddressInfo.AI_PASSIVE: 1>
Wildcard infos: [(<AddressFamily.AF_INET: 2>, <SocketKind.SOCK_STREAM: 1>, 6, '', ('0.0.0.0', 0)), (<AddressFamily.AF_INET6: 10>, <SocketKind.SOCK_STREAM: 1>, 6, '', ('::', 0, 0, 0))]
--- check: readable_fqdn
INFO: socket.getfqdn(): '71d6fe811d18'
--- check: stat_tensorboardinfo
INFO: directory: /tmp/.tensorboard-info
INFO: os.stat(...): os.stat_result(st_mode=16895, st_ino=805882112, st_dev=51, st_nlink=2, st_uid=0, st_gid=0, st_size=6, st_atime=1677293427, st_mtime=1677293598, st_ctime=1677293598)
INFO: mode: 0o40777
--- check: source_trees_without_genfiles
INFO: tensorboard_roots (1): ['/usr/local/lib/python3.8/dist-packages']; bad_roots (0): []
--- check: full_pip_freeze
INFO: pip freeze --all:
absl-py==1.3.0
anyio==3.6.2
argon2-cffi==21.3.0
argon2-cffi-bindings==21.2.0
asttokens==2.1.0
astunparse==1.6.3
attrs==22.1.0
backcall==0.2.0
beautifulsoup4==4.11.1
bleach==5.0.1
cachetools==5.2.0
certifi==2022.9.24
cffi==1.15.1
charset-normalizer==2.1.1
contourpy==1.0.6
cycler==0.11.0
debugpy==1.6.3
decorator==5.1.1
defusedxml==0.7.1
entrypoints==0.4
executing==1.2.0
fastjsonschema==2.16.2
flatbuffers==22.10.26
fonttools==4.38.0
gast==0.4.0
google-auth==2.14.1
google-auth-oauthlib==0.4.6
google-pasta==0.2.0
grpcio==1.50.0
gviz-api==1.10.0
h5py==3.7.0
idna==3.4
importlib-metadata==5.0.0
importlib-resources==5.10.0
ipykernel==5.1.1
ipython==8.6.0
ipython-genutils==0.2.0
ipywidgets==8.0.2
jedi==0.17.2
Jinja2==3.1.2
jsonschema==4.17.0
jupyter==1.0.0
jupyter-client==7.4.7
jupyter-console==6.4.4
jupyter-core==5.0.0
jupyter-http-over-ws==0.0.8
jupyter-server==1.23.2
jupyterlab-pygments==0.2.2
jupyterlab-widgets==3.0.3
keras==2.11.0
kiwisolver==1.4.4
libclang==14.0.6
Markdown==3.4.1
MarkupSafe==2.1.1
matplotlib==3.6.2
matplotlib-inline==0.1.6
mistune==2.0.4
nbclassic==0.4.8
nbclient==0.7.0
nbconvert==7.2.5
nbformat==4.4.0
nest-asyncio==1.5.6
notebook==6.5.2
notebook-shim==0.2.2
numpy==1.23.4
oauthlib==3.2.2
opt-einsum==3.3.0
packaging==21.3
pandocfilters==1.5.0
parso==0.7.1
pexpect==4.8.0
pickleshare==0.7.5
Pillow==9.3.0
pip==20.2.4
pkgutil-resolve-name==1.3.10
platformdirs==2.5.4
prometheus-client==0.15.0
prompt-toolkit==3.0.32
protobuf==3.19.6
psutil==5.9.4
ptyprocess==0.7.0
pure-eval==0.2.2
pyasn1==0.4.8
pyasn1-modules==0.2.8
pycparser==2.21
Pygments==2.13.0
pyparsing==3.0.9
pyrsistent==0.19.2
python-dateutil==2.8.2
pyzmq==24.0.1
qtconsole==5.4.0
QtPy==2.3.0
requests==2.28.1
requests-oauthlib==1.3.1
rsa==4.9
Send2Trash==1.8.0
setuptools==65.5.1
six==1.16.0
sniffio==1.3.0
soupsieve==2.3.2.post1
stack-data==0.6.1
tensorboard==2.11.0
tensorboard-data-server==0.6.1
tensorboard-plugin-profile==2.11.1
tensorboard-plugin-wit==1.8.1
tensorflow-cpu==2.11.0
tensorflow-estimator==2.11.0
tensorflow-io-gcs-filesystem==0.27.0
termcolor==2.1.0
terminado==0.17.0
tinycss2==1.2.1
tornado==6.2
traitlets==5.5.0
typing-extensions==4.4.0
urllib3==1.26.12
wcwidth==0.2.5
webencodings==0.5.1
websocket-client==1.4.2
Werkzeug==2.2.2
wheel==0.34.2
widgetsnbextension==4.0.3
wrapt==1.14.1
zipp==3.10.0
Next steps
No action items identified. Please copy ALL of the above output,
including the lines containing only backticks, into your GitHub issue
or comment. Be sure to redact any sensitive information.
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- Browser type and version (e.g., Chrome 64.0.3282.140):
- Screenshot, if it’s a visual issue:
Issue description
Running very standard example of tensorboard callback, code below, and getting No step marker observed issue
import tensorflow as tf
import datetime
mnist = tf.keras.datasets.mnist
(x_train, y_train),(x_test, y_test) = mnist.load_data()
x_train, x_test = x_train / 255.0, x_test / 255.0
def create_model():
return tf.keras.models.Sequential([
tf.keras.layers.Flatten(input_shape=(28, 28), name='layers_flatten'),
tf.keras.layers.Dense(512, activation='relu', name='layers_dense'),
tf.keras.layers.Dropout(0.2, name='layers_dropout'),
tf.keras.layers.Dense(10, activation='softmax', name='layers_dense_2')
])
model = create_model()
model.compile(optimizer='adam',
loss='sparse_categorical_crossentropy',
metrics=['accuracy'])
log_dir = "logs/fit/" + datetime.datetime.now().strftime("%Y%m%d-%H%M%S")
tensorboard_callback = tf.keras.callbacks.TensorBoard(log_dir=log_dir, histogram_freq=1, profile_batch=(1,50))
model.fit(x=x_train,
y=y_train,
epochs=5,
validation_data=(x_test, y_test),
callbacks=[tensorboard_callback])
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)?
Step markers are either not getting logged by Keras or are not being read by tensorboard. I would expect that this information is logged so that I can use the module for optimizing tf.data usage. The environment that this is run in is a standard tensorflow docker container with the only additional package installed being tensorboard_plugin_profile
Contributor guide
First steps
- Read the whole issue, then the project's contributing guide.
- Comment on the issue to say you are picking it up — it saves two people doing the same work.
- Fork the repository and make your change on a branch.
- Open a pull request that references the issue number.
Research direction
Start with diagnose_tensorboard.py and the supplied diagnostics to establish the TensorBoard environment and reproduce the missing step marker. The report does not identify a source file, test, reproduction steps, or expected behavior, so the issue needs clarification before a newcomer can define what a completed fix would be.
Written by the indexing model from the issue text.
Assessment
- Tech stack
- python
- Domain
- data-visualization
- Issue type
- Bug
- Difficulty
- 4/5
- Estimated time
- 3-5 days
- Activity status
- Stale
- Clarity
- Needs clarification
- Newbie friendliness
- 18/100