Command line tool for managing single-purpose cloud VMs
Command line tool for managing single-purpose cloud VMs. Currently works with GCP.
Single command to provision cloud-based disk images with Ubuntu, NVIDIA drivers, Anaconda, PyTorch, FastAI and more..
Single command to attach a disk image, launch a cloud VM instance with any configuration of CPUs, RAM and GPU, and start Jupyter notebook.
cloudman package using
pip install cloudman
cloudman requires the
gcloud command line tool to be installed. Make sure to complete these steps before moving forward.
gcloudCLI using this link: https://cloud.google.com/sdk/docs/downloads-interactive
Make sure the
gcloudcommand is added to your PATH.
gcloudtool your GCP account by running:
(Optional) Create a GCP project by running:
gcloud projects create PROJECT_ID
Replace PROJECT_ID with a unique name e.g. kitten-puppies-999 You can also use an existing project.
Activate a project by running:
gcloud config set project PROJECT_ID
Open the cloud console by running:
Enable billing to start creating cloud VMs.
cloudman allows you to crate standalone boot disks which can be flexibly attached to any type of machine & GPU configuration.
Create a boot disk
cloudman create will create a boot disk of the given size, then install Ubuntu, NVIDIA CUDA libraries, Anaconda, Pytorch and FastAI deep learning libraries. By default, a 50 GB disk is created.
Here are some examples:
# Using default disk size of 50GB cloudman create freesound-2019
# Custom disk size cloudman create freesound-2019 --disk=100GB
cloudman creates a temporary VM instance to install all the required packages, and then deletes the VM, but retains the disk. It uses this shell script for setup.
Start an instance
You can launch an instance with the boot disk attached using the
cloudman start command. You can choose any combination of GPUs and machine types. You can also launch a CPU-only instance, which is the default. Also, you can choose whether you want a preemptible instance (enabled by default, to save cost), or a dedicated instance.
Here are some examples:
# CPU-only, preemptible cloudman start jigsaw-ulmfit # Same as the above command, but explicit cloudman start jigsaw-ulmfit --gpu=nogpu --machine=auto --spot # K80 GPU, dedicated cloudman start jigsaw-ulmfit --gpu=k80 --nospot
Valid GPU types are:
'nogpu', 't4', 'v100', 'p100', 'p4', 'k80'
Valid machine types can be found here: https://cloud.google.com/compute/docs/machine-types
If machine type is set to 'auto', the tool automatically picks a reasonable machine type to match the GPU's RAM & cores. You can see the mapping here.
Once started, you can use the link to access the Jupyter server. Sometimes it may take a minute or two for the Jupyter server to start.
SSH into running instance
To SSH into a running instance use:
cloudman ssh jigsaw-ulmfit
Stop an instance
cloudman stop command to stop a running instance. Example:
cloudman stop jigsaw-ulmfit
List disks and running instances
To see the available boot disks and running instances, run
Delete a boot disk
To delete a boot disk, run
cloudman delete jigsaw-ulmfit
This will stop any running instances and delte the boot disk complete. All your data will be lost, so be careful while using this.
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