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        "description": "# cloudman\n\nCommand line tool for managing single-purpose cloud VMs. Currently works with GCP.\n\n![cloudman-start-demo](https://i.imgur.com/g2DEBgN.gif)\n\nFeatures:\n\n1. Single command to provision cloud-based disk images with Ubuntu, NVIDIA drivers, Anaconda, PyTorch, FastAI and more..\n\n2. Single command to attach a disk image, launch a cloud VM instance with any configuration of CPUs, RAM and GPU, and start Jupyter notebook.\n\n## Installation\n\nInstall the `cloudman` package using `pip`.\n\n```\npip install cloudman\n```\n\n`cloudman` requires the `gcloud` command line tool to be installed. Make sure to complete these steps before moving forward.\n\n1. Install `gcloud` CLI using this link: https://cloud.google.com/sdk/docs/downloads-interactive\n\n2. Make sure the `gcloud` command is added to your PATH.\n\n3. Connect the `gcloud` tool your GCP account by running:\n\n   `gcloud init`\n\n4. (Optional) Create a GCP project by running:\n\n   `gcloud projects create PROJECT_ID`\n\nReplace PROJECT_ID with a unique name e.g. kitten-puppies-999\nYou can also use an existing project.\n\n5. Activate a project by running:\n\n   `gcloud config set project PROJECT_ID`\n\n6. Open the cloud console by running:\n\n   `cloudman console`\n\n7. Enable billing to start creating cloud VMs.\n\n## Usage\n\n`cloudman` allows you to crate standalone boot disks which can be flexibly attached to any type of machine & GPU configuration.\n\n### Create a boot disk\n\nRunning the `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.\n\nHere are some examples:\n\n```\n# Using default disk size of 50GB\ncloudman create freesound-2019\n```\n\n```\n# Custom disk size\ncloudman create freesound-2019 --disk=100GB\n```\n\nNote that `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](https://raw.githubusercontent.com/aakashns/cloudman/master/cloudman/setup-scripts/gcp-ubutnu-nvidia410-fastai.sh) for setup.\n\n### Start an instance\n\nYou 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.\n\nHere are some examples:\n\n```\n# CPU-only, preemptible\ncloudman start jigsaw-ulmfit\n\n# Same as the above command, but explicit\ncloudman start jigsaw-ulmfit --gpu=nogpu --machine=auto --spot\n\n# K80 GPU, dedicated\ncloudman start jigsaw-ulmfit --gpu=k80 --nospot\n\n```\n\nValid GPU types are: `'nogpu', 't4', 'v100', 'p100', 'p4', 'k80'`\nValid machine types can be found here: https://cloud.google.com/compute/docs/machine-types\nIf 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](https://github.com/aakashns/cloudman/blob/master/cloudman/gcp/constants.py).\n\nOnce 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.\n\n### SSH into running instance\n\nTo SSH into a running instance use:\n\n```\ncloudman ssh jigsaw-ulmfit\n```\n\n### Stop an instance\n\nUse the `cloudman stop` command to stop a running instance. Example:\n\n```\ncloudman stop jigsaw-ulmfit\n```\n\n### List disks and running instances\n\nTo see the available boot disks and running instances, run\n\n```\ncloudman list\n```\n\n### Delete a boot disk\n\nTo delete a boot disk, run\n\n```\ncloudman delete jigsaw-ulmfit\n```\n\nThis will stop any running instances and delte the boot disk complete. All your data will be lost, so be careful while using this.\n\n\n",
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