Notebook Configuration

Determined makes it easy to modify the dependencies that are installed into the notebook’s environment:

$ det notebook start --config environment.tensorflow=1.13.1

More generally, notebooks may be supplied an optional notebook configuration to configure the notebook’s environment. In addition to the --config flag, configuration may also be supplied via a YAML file (--config-file):

$ cat > config.yaml <<EOL
description: test-notebook
resources:
  slots: 2
environment:
  python: "3.6.9"
  tensorflow: "1.13.1"
  keras: "2.2.4"
bind_mounts:
  - host_path: /data/notebook_scratch
    container_path: /scratch
EOL
$ det notebook start --config-file config.yaml

See Command Configuration for full documentation of the supported configuration options.

Example: CPU-Only Notebooks

By default, each notebook is assigned a single GPU. This is useful for some uses of notebooks (e.g., training a deep learning model) but unnecessary for other tasks (e.g., analyzing the training metrics of a previously trained model). To launch a notebook that does not use any GPUs, set resources.slots to 0:

$ det notebook start --config resources.slots=0