loadingpy
In this repository, we provide a custom made progress bar for python iterables. This library can be used as is or modified for any purposes (see licence).
for deep learning
There is now a new progress bar available for deep learning purposes (I guess it could be leveraged for other stuff as well...). Say, you want to train a model using a dataset $D$ over $e$ epochs. Using TrainBaryou can get a double progress bar (first for the epochs and second for the steps in the current epoch) on a single line. you can check the test or this simple example:
from loadingpy import TrainBar
for data in TrainBar(
trainloader,
num_epochs=e,
base_str="training",
):
inputs, labels = data
Example
You can install with pip pip install loadingpy and use as follows
from loadingpy import PyBar
loss = 0.0
accuracy = 0.0
for inputs, labels in PyBar(dataset, monitoring=[loss, accuracy], naming=["loss", "accuracy"], base_str="training"):
# do whatever you please
loss += 0.0 # update monitoring variables in place
accuracy += 0.0 # update monitoring variables in place
For a more detailed exampel (in torch) check this tutorial. You can use a global argument in order to disable the verbatim from the loading bars as follows:
from loadingpy import BarConfig
BarConfig["disable loading bar"] = True
Arguments
Here is a list of the arguments and their description
| argument | description | type |
|---|---|---|
| iterable | python object that can be iterated over | can be a list, tuple, range, np.ndarray, torch.Tensor, dataset,... |
| monitoring | a python object (or list of python objects) that will be printed after each iteration using the following format f'{monitoring}'. IF they are updated during the loop, make sure to update inplace, in order to see the changes | an be a tensor, float or list of these |
| naming | if you want to add a descritpion prefix to the monitoring variables | str or list of str |
| total_steps | number of iterations to perform (if you set it to a lower value than the length of the iterable, then the process will stop after the given total_steps) | int |
| base_str | prefix description of the loop we are iterating over | str |
| color | which color to use for the loading bar | str |
1 maintainer
Metadata
1 maintainer
Release files for loadingpy 0.1.4
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