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 enviornment. 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 the Notebook Configuration section 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 notebook (e.g., training a deep learning model) but
unnecessary for other notebook 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
CPU-only notebooks will be scheduled on a randomly chosen agent.