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Keras integration with TQDM progress bars.
Keras <https://github.com/fchollet/keras>
__ is an awesome machine learning library for Theano or TensorFlow.TQDM <https://github.com/tqdm/tqdm>
__ is a progress bar library with good support for nested loops and Jupyter/IPython notebooks.TQDM supports nested progress bars. If you have Keras fit and predict loops within an outer TQDM loop, the nested loops will display properly.
TQDM supports Jupyter/IPython notebooks.
TQDM looks great!
TQDMNotebookCallback
with leave_inner=False
(default)
.. figure:: https://github.com/bstriner/keras-tqdm/raw/master/docs/images/leave_inner_False.png :alt: Keras TQDM leave_inner=False
TQDMNotebookCallback
with leave_inner=True
.. figure:: https://github.com/bstriner/keras-tqdm/raw/master/docs/images/leave_inner_True.png :alt: Keras TQDM leave_inner=True
TQDMCallback
for command-line scripts
.. figure:: https://github.com/bstriner/keras-tqdm/raw/master/docs/images/console.png :alt: Keras TQDM CLI
Stable release ::
pip install keras-tqdm
Development release ::
pip install git+https://github.com/bstriner/keras-tqdm.git --upgrade --no-deps
Development mode (changes to source take effect without reinstalling) ::
git clone https://github.com/bstriner/keras-tqdm.git
cd keras-tqdm
python setup.py develop
It's very easy to use Keras TQDM. The only required change is to remove default messages (verbose=0
) and add a callback to model.fit
. The rest happens automatically! For Jupyter Notebook required code modification is as simple as:
::
from keras_tqdm import TQDMNotebookCallback
# keras, model definition...
model.fit(X_train, Y_train, verbose=0, callbacks=[TQDMNotebookCallback()])
For plain text mode (e.g. for Python run from command line)
::
from keras_tqdm import TQDMCallback
# keras, model definition...
model.fit(X_train, Y_train, verbose=0, callbacks=[TQDMCallback()])
Use keras_tqdm
to utilize TQDM progress bars for Keras fit loops.
keras_tqdm
loops can be nested inside TQDM loops to display nested progress bars (although you can use them
inside ordinary for loops as well).
Set verbose=0
to suppress the default progress bar.
::
from keras_tqdm import TQDMCallback
from tqdm import tqdm
for model in tqdm(models, desc="Training several models"):
model.fit(x, y, verbose=0, callbacks=[TQDMCallback()])
For IPython and Jupyter notebook TQDMNotebookCallback
instead of TQDMCallback
. Use tqdm_notebook
in your own code instead of tqdm
.
Formatting is controlled by python format strings. The default metric_format
is "{name}: {value:0.3f}"
.
For example, use TQDMCallback(metric_format="{name}: {value:0.6f}")
for 6 decimal points or {name}: {value:e}
for scientific notation.
Please feel free to submit PRs and issues. Comments, questions, and
requests are welcome. If you need more control, subclass
TQDMCallback
and override the tqdm
function.
FAQs
Keras models with TQDM progress bars in Jupyter notebooks
We found that keras-tqdm demonstrated a healthy version release cadence and project activity because the last version was released less than a year ago. It has 1 open source maintainer collaborating on the project.
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