Neptune.ai

Integration with neptune.ai.

/usr/local/lib/python3.8/dist-packages/torch/cuda/__init__.py:52: UserWarning: CUDA initialization: Found no NVIDIA driver on your system. Please check that you have an NVIDIA GPU and installed a driver from http://www.nvidia.com/Download/index.aspx (Triggered internally at  /pytorch/c10/cuda/CUDAFunctions.cpp:100.)
  return torch._C._cuda_getDeviceCount() > 0

Registration

1. Create account: neptune.ai/register.
2. Export API token to the environment variable (more help here). In your terminal run:

export NEPTUNE_API_TOKEN='YOUR_LONG_API_TOKEN'

or append the command above to your ~/.bashrc or ~/.bash_profile files (recommended). More help is here.

Installation

1. You need to install neptune-client. In your terminal run:

pip install neptune-client

or (alternative installation using conda). In your terminal run:

conda install neptune-client -c conda-forge

1. Install psutil to see hardware monitoring charts:

pip install psutil

How to use?

Key is to call neptune.init() before you create Learner() and call neptune_create_experiment(), before you fit the model.

Use NeptuneCallback in your Learner, like this:

from fastai.callback.neptune import NeptuneCallback
neptune.init('USERNAME/PROJECT_NAME')  # specify project
learn = Learner(dls, model,
                cbs=NeptuneCallback()
                )
neptune.create_experiment()  # start experiment
learn.fit_one_cycle(1)

class NeptuneCallback[source]

NeptuneCallback(log_model_weights=True, keep_experiment_running=False) :: Callback

Log losses, metrics, model weights, model architecture summary to neptune

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