Metadata-Version: 2.1
Name: early-stopping
Version: 0.1.1
Summary: Early stopping for neural networks
Home-page: https://github.com/Ovikx/early-stopping
Author: Ovikx
License: UNKNOWN
Platform: UNKNOWN
Classifier: Programming Language :: Python :: 3
Classifier: License :: OSI Approved :: MIT License
Classifier: Operating System :: OS Independent
Requires-Python: >=3.6
Description-Content-Type: text/markdown
License-File: LICENSE

# Early Stopping
---
I'm too lazy to read the Tensorflow documentation, so I made this simple early stopper. After each training step, feed the object the testing loss result for that epoch and it will return a boolean that says whether or not to break the training loop. 

**Example usage:**

```py
from early_stopping import EarlyStopping

early_stopper = EarlyStopping(
    depth=5,
    ignore=20,
    method='consistency'
)

# Your training loop
for epoch in range(EPOCHS):
    # Train step here
    # Test step here

    # Check if we should break the loop
    if early_stopper.check(testing_loss):
        print('BREAKING THE TRAINING LOOP')
        break

```

