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| description: Train VQ on Bird Dataset | |
| auth: | |
| # which virtual cluster you belong to (msrlabs, etc.). Everyone has access to "pnrsy". | |
| vc: msrlabspvc12 # msrlabs | |
| # physical cluster to use (cam, gcr, rr1) or Azure clusters (eu1, eu2, etc.) | |
| # cluster: rr2, eu2, eu1 et1 | |
| cluster: eu2 | |
| # docker environment (vm) in which your job will run. we provide "generic" dockers | |
| # with the main deep learning toolkit installed (PyTorch, TF, Chainer, etc.) | |
| docker: | |
| # image: philly/jobs/custom/generic-docker:py27 | |
| # registry: phillyregistry.azurecr.io | |
| image: vlnres/vqvae:v1 # chunyl/vqvae:v2 | |
| registry: index.docker.io | |
| storage: | |
| _default: | |
| #use_phillyfs: True | |
| storage_account_name: sslm | |
| container_name: vqvae | |
| mount_path: /mnt/_default | |
| code: | |
| # local directory of the code. this will be uploaded to the server. | |
| # $CONFIG_DIR is expanded to the directory of this config file | |
| code_upload: False | |
| remote_dir: vq-vae-2-pytorch/ | |
| local_dir: $CONFIG_DIR/src | |
| #data: | |
| # data upload is not required for this example | |
| #data_upload: False | |
| search: | |
| job_template: | |
| name: vq_{experiment_name:s}_{image_size_option:.1f} | |
| sku: G4 # G4 # G1 | |
| command: | |
| - python train_vqvae.py --philly --dataset_name bird --size {image_size_option} --batch 512 | |
| max_trials: 20 | |
| type: grid | |
| params: | |
| - name: image_size_option | |
| spec: discrete | |
| values: [64,128] # [top,bottom] | |