<jupyter_start><jupyter_text>Keras Progress Bars The following examples show two different `keras_tqdm` progress bars.* TQDM notebook widget* TQDM console outputTo use `keras_tqdm` progress bars in your own code, just add `TQDMCallback` or `TQDMNotebookCallback` to the `callbacks` passed to `model.fit`. Set `verbose=0` to suppress the built-in progress bars.  MNIST Example In this experiment, we train a Keras model on the MNIST dataset.<jupyter_code>from mnist_model import mnist_model
from keras_tqdm import TQDMCallback, TQDMNotebookCallback<jupyter_output>Using Theano backend.
WARNING (theano.gof.compilelock): Overriding existing lock by dead process '20256' (I am process '24968')
Using gpu device 0: GeForce GTX 770M (CNMeM is enabled with initial size: 80.0% of memory, cuDNN 5005)<jupyter_text>TQDM Progress Bar (ipywidget)<jupyter_code>mnist_model(0, [TQDMNotebookCallback()])<jupyter_output><empty_output><jupyter_text>TQDM Progress Bar (text)<jupyter_code>mnist_model(0, [TQDMCallback()])<jupyter_output>Training:   0%|                                         | 0/10 [00:00<?, ?it/s]
Epoch: 0:   0%|                                       | 0/1875 [00:00<?, ?it/s]
Epoch: 0 - loss: 1.792, acc: 0.420  1%|     | 16/1875 [00:00<00:11, 155.34it/s]
Epoch: 0 - loss: 1.337, acc: 0.568  2%|     | 32/1875 [00:00<00:11, 154.89it/s]
Epoch: 0 - loss: 1.139, acc: 0.631  3%|▏    | 47/1875 [00:00<00:11, 152.92it/s]
Epoch: 0 - loss: 1.009, acc: 0.672  3%|▏    | 65/1875 [00:00<00:11, 158.88it/s]
Epoch: 0 - loss: 0.928, acc: 0.697  4%|▏    | 84/1875 [00:00<00:10, 166.65it/s]
Epoch: 0 - loss: 0.876, acc: 0.718  5%|▏   | 103/1875 [00:00<00:10, 171.62it/s]
Epoch: 0 - loss: 0.826, acc: 0.731  7%|▎   | 122/1875 [00:00<00:09, 175.77it/s]
Epoch: 0 - loss: 0.780, acc: 0.750  8%|▎   | 141/1875 [00:00<00:09, 179.81it/s]
Epoch: 0 - loss: 0.743, acc: 0.762  9%|▎   | 160/1875 [00:00<00:09, 181.70it/s]
Epoch: 0 - loss: 0.709, acc: 0.771 10%|▍   | 180/1875 [00:01<00:09, 184.25it/s]
Epoch: 0 - loss: 0.678, acc: 0.780 11%|▍[...]
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