config.yaml

description: Simple PyTorch job on MNIST on AMLK8s

target:
  service: amlk8s
  # run "amlt target list amlk8s" to list the names of available AMLK8s targets
  name: itplabrr1cl1 # 32G
#  name: itpscusv100cl #16G
  vc: resrchvc

environment:
#  image: pytorch/pytorch:1.4-cuda10.1-cudnn7-devel
  image: indexserveregistry.azurecr.io/deepscale:1.0.post0
#  image: shumingdocker.azurecr.io
  registry: docker.io # any public registry can be specified here
  setup:
    - pip install tensorboard --user

code:
  # local directory of the code. this will be uploaded to the server.
  # $CONFIG_DIR is expanded to the directory of this config file
  local_dir: $CONFIG_DIR/src

data:
#  # You need to run "python src/download_data.py" beforehand
#  # to generate the dataset to be uploaded
#  # don't forget to run with --upload-data
  local_dir: $CONFIG_DIR/data/
#
#  # The data will be uploaded to your default storage.
#  #   Check ``multi_storage.yaml'' for more flexibility.
  remote_dir: data/applyGPU/


# data:
#   data upload is not required for this example

# list of jobs to run, we run 2 jobs in this example
jobs:
- name: job1
  sku: G8
  command:
   - sleep infinity
#  - python train.py --gpu_devices 4 5 6 7