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reloading

(★ 1,127)

Change Python code while it's running without losing state

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  - train.py
- - requirements.txt
  - train.py
- __init__.py
- reloading.py
- test_reloading.py
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# Installation Guide

1. Get the code

git clone https://github.com/julvo/reloading

Downloads the entire project code from GitHub to your computer.

cd reloading

Moves into the project folder you just downloaded.

2. Official Install Script

Easy Recommended

Prerequisites

Python 3 Python is required to use pip.

pip install reloading

Installs the package published on PyPI directly — no need to clone the source.

✅ After installing, open a new terminal and run the program's version command (e.g. --version) to confirm it worked.

Pulled directly from this repo's README.

3. Python

Easy

Prerequisites

Git Needed to download the project code from GitHub.
Python 3 On Windows, be sure to check 'Add Python to PATH' during installation.

pip install reloading

Installs the package published on PyPI directly — no need to clone the source.

✅ If it runs without errors and prints output in the terminal, it worked.

Pulled directly from this repo's README.

4. Make

Medium

Prerequisites

Git Needed to download the project code from GitHub.
Make Usually pre-installed on Linux/macOS. On Windows, install separately (e.g. via MSYS2 or WSL).

make

Compiles the code based on the generated build configuration to produce an executable.

✅ If it finishes without errors, it worked. Try running the generated executable directly.

// repository documentation

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# reloading
[![pypi badge](https://img.shields.io/pypi/v/reloading?color=%230c0)](https://pypi.org/project/reloading/)

A Python utility to reload a loop body from source on each iteration without
losing state

Useful for editing source code during training of deep learning models. This lets
you e.g. add logging, print statistics or save the model without restarting the
training and, therefore, without losing the training progress.

![Demo](https://github.com/julvo/reloading/blob/master/examples/demo/demo.gif)

## Install
```
pip install reloading
```

## Usage

To reload the body of a `for` loop from source before each iteration, simply 
wrap the iterator with `reloading`, e.g.
```python
from reloading import reloading

for i in reloading(range(10)):
    # this code will be reloaded before each iteration
    print(i)

```

To reload a function from source before each execution, decorate the function
definition with `@reloading`, e.g.
```python
from reloading import reloading

@reloading
def some_function():
    # this code will be reloaded before each invocation
    pass
```

## Additional Options

Pass the keyword argument `every` to reload only on every n-th invocation or iteration. E.g.
```python
for i in reloading(range(1000), every=10):
    # this code will only be reloaded before every 10th iteration
    # this can help to speed-up tight loops
    pass

@reloading(every=10)
def some_function():
    # this code with only be reloaded before every 10th invocation
    pass
```

Pass `forever=True` instead of an iterable to create an endless reloading loop, e.g. 
```python
for i in reloading(forever=True):
    # this code will loop forever and reload from source before each iteration
    pass
```

## Examples

Here are the short snippets of how to use reloading with your favourite library.
For complete examples, check out the [examples folder](https://github.com/julvo/reloading/blob/master/examples).

### PyTorch
```python
for epoch in reloading(range(NB_EPOCHS)):
    # the code inside this outer loop will be reloaded before each epoch

for images, targets in dataloader:
        optimiser.zero_grad()
        predictions = model(images)
        loss = F.cross_entropy(predictions, targets)
        loss.backward()
        optimiser.step()
```
[Here](https://github.com/julvo/reloading/blob/master/examples/pytorch/train.py) is a full PyTorch example.

### fastai
```python
@reloading
def update_learner(learner):
    # this function will be reloaded from source before each epoch so that you
    # can make changes to the learner while the training is running
    pass

class LearnerUpdater(LearnerCallback):
    def on_epoch_begin(self, **kwargs):
        update_learner(self.learn)

path = untar_data(URLs.MNIST_SAMPLE)
data = ImageDataBunch.from_folder(path)
learn = cnn_learner(data, models.resnet18, metrics=accuracy, 
                    callback_fns=[LearnerUpdater])
learn.fit(10)
```
[Here](https://github.com/julvo/reloading/blob/master/examples/fastai/train.py) is a full fastai example.

### Keras
```python
@reloading
def update_model(model):
    # this function will be reloaded from source before each epoch so that you
    # can make changes to the model while the training is running using
    # K.set_value()
    pass

class ModelUpdater(Callback):
    def on_epoch_begin(self, epoch, logs=None):
        update_model(self.model)

model = Sequential()
model.add(Dense(64, activation='relu', input_dim=20))
model.add(Dense(10, activation='softmax'))

sgd = SGD(lr=0.01, decay=1e-6, momentum=0.9, nesterov=True)
model.compile(loss='categorical_crossentropy',
              optimizer=sgd,
              metrics=['accuracy'])

model.fit(x_train, y_train,
          epochs=200,
          batch_size=128,
          callbacks=[ModelUpdater()])
```
[Here](https://github.com/julvo/reloading/blob/master/examples/keras/train.py) is a full Keras example.

### TensorFlow
```python
for epoch in reloading(range(NB_EPOCHS)):
    # the code inside this outer loop will be reloaded from source
    # before each epoch so that you can change it during training
  
    train_loss.reset_states()
    train_accuracy.reset_states()
    test_loss.reset_states()
    test_accuracy.reset_states()
  
    for images, labels in tqdm(train_ds):
      train_step(images, labels)
  
    for test_images, test_labels in tqdm(test_ds):
      test_step(test_images, test_labels)
```
[Here](https://github.com/julvo/reloading/blob/master/examples/tensorflow/train.py) is a full TensorFlow example.

## Testing

Make sure you have `python` and `python3` available in your path, then run:
```
$ python3 reloading/test_reloading.py
```