Neptune.ai tensorflow-keras integration library
Project description
Neptune + TensorFlow/Keras Integration
Experiment tracking, model registry, data versioning, and live model monitoring for TensorFlow/Keras trained models.
What will you get with this integration?
- Log, display, organize, and compare ML experiments in a single place
- Version, store, manage, and query trained models, and model building metadata
- Record and monitor model training, evaluation, or production runs live
- Collaborate with a team
What will be logged to Neptune?
- hyperparameters for every run,
- learning curves for losses and metrics during training,
- hardware consumption and stdout/stderr output during training,
- TensorFlow tensors as images to see model predictions live,
- training code and git commit information,
- model weights
- other metadata
Example charts in the Neptune UI with logged accuracy and loss
Resources
Example
# On the command line:
pip install tensorflow neptune-client neptune-tensorflow-keras
# In Python:
import neptune.new as neptune
from neptune.new.integrations.tensorflow_keras import NeptuneCallback
# Start a run
run = neptune.init(project="common/tf-keras-integration",
api_token="ANONYMOUS")
# Create a NeptuneCallback instance
neptune_cbk = NeptuneCallback(run=run, base_namespace="metrics")
# Pass the callback to model.fit()
model.fit(x_train, y_train,
epochs=5,
batch_size=64,
callbacks=[neptune_cbk])
# Stop the run
run.stop()
Support
If you got stuck or simply want to talk to us, here are your options:
- Check our FAQ page
- You can submit bug reports, feature requests, or contributions directly to the repository.
- Chat! When in the Neptune application click on the blue message icon in the bottom-right corner and send a message. A real person will talk to you ASAP (typically very ASAP),
- You can just shoot us an email at support@neptune.ai
Project details
Release history Release notifications | RSS feed
Download files
Download the file for your platform. If you're not sure which to choose, learn more about installing packages.
Source Distribution
Built Distribution
Close
Hashes for neptune_tensorflow_keras-2.0.1.tar.gz
Algorithm | Hash digest | |
---|---|---|
SHA256 | 10a21db0eb6c5bb268a58fefdcd5db3020c6125c929754a5562e6397de2132f8 |
|
MD5 | bb3b4d662e710ab43dd8e9eb5480e865 |
|
BLAKE2b-256 | 3a66123b408c2614054fcd56abf7c22cdf6459a2686941c96f142d9224869f29 |
Close
Hashes for neptune_tensorflow_keras-2.0.1-py3-none-any.whl
Algorithm | Hash digest | |
---|---|---|
SHA256 | 293256e70259c9f01a27f39dcb59d99797a24ef56cdb6e8f7731d32efad48cba |
|
MD5 | 8b51d8f182d5844b1cabf5f577875e22 |
|
BLAKE2b-256 | 7d9bc6fc9b0bf09af8e14218b815a735d217893b29430afbec21f7d664cef2fc |