SigOpt CLI Commands

Get Started Commands

Command	Description
sigopt config	Same command to configure the API token and enable other features (logs and source code collection).
sigopt init	Create template files in the current directory to help you get started.
sigopt version	Show the version of the SigOpt CLI.

Runs CLI Commands

Command	Description
sigopt run [-r/--run-file <RUN YML FILE>] [-p/--project <PROJECT_ID>] [EXECUTABLE COMMAND]	Execute a Run from the indicated model execution code. An executable command must be provided, either as command arguments or via the run section of the provided run file (run.yml in the current directory by default). The Project can be specified manually, otherwise the SIGOPT_PROJECT environment variable or current directory name will be used.

Runs YAML File Formatting

Specify the configuration of a Run or Runs that are produced during an AI Experiment. When used with SigOpt Orchestrate, job resource specifications will be determined by the resources specified in the run.yml file.

Field	Required?	Description
image	Yes	Name of Docker container SigOpt Orchestrate creates. You can also point this to an existing Docker container to use for SigOpt Orchestrate.
name	Yes	Name for your SigOpt Run or AI Experiment
run	No	Model file to execute
resources	No	Resources to allocate to each Run. Can specify limits and requests for cpu, memory, ephemeral-storage and can specify GPUs.

# example Run yml file
name: My Run
run: python mymodel.py
resources:
 requests:
 cpu: 0.5
 memory: 512Mi
 limits:
 cpu: 2
 memory: 4Gi
 gpus: 1
image: my-run

AI Experiments CLI Commands

Command	Description
sigopt optimize [-e/--experiment-file <EXPERIMENT YML FILE>] [-p/--project <PROJECT_ID>] [EXECUTABLE COMMAND]	Execute a SigOpt AI Experiment from the indicated execution code. AI Experiment settings must be provided, either with an experiment.yml file in the current directory or by manually specifying the file location. The Project can be specified manually, otherwise the SIGOPT_PROJECT environment variable or current directory name will be used.
sigopt create experiment [-e/--experiment-file <EXPERIMENT YML FILE>] [-p/--project <PROJECT_ID>]	Create a Sigopt AI Experiment using an experiment file. Execution of the AI Experiment should be done manually with the sigopt start-worker command, or by fetching the AI Experiment in your code.
sigopt start-worker EXPERIMENT_ID [-r/--run-file run.yml] [EXECUTABLE COMMAND]	This command starts a new AI Experiment worker. It has similar options to sigopt run, but requires an Experiment ID. If no commands are provided, the worker will use the run.yml file to specify execution.

AI Experiment YML File Formatting

Specify the configuration of a Run or Runs that are produced during an AI Experiment.

Field	Required?	Description
name	Yes	Name of the AI Experiment
type	Yes	Type of AI Experiment to execute (see table below)
parameters	Yes	Parameters and ranges specified for a SigOpt AI Experiment
metrics	Yes	Evaluation and storage metrics for a SigOpt AI Experiment
parallel_bandwidth	No	Number of workers
budget	Yes	Number of Runs for a SigOpt AI Experiment

AI Experiment Type	Type Flag
SigOpt Optimization Experiment	offline
All Constraints Experiment	offline
Grid Search	grid
Random Search	random

# single_metric_experiment.yml
name: Single metric optimization
type: offline
parameters:
 - name: hidden_layer_size
   type: int
   bounds:
     min: 32
     max: 512
 - name: activation_function
   type: categorical
   categorical_values: ['relu', 'tanh']
metrics:
 - name: holdout_accuracy
   strategy: optimize
   objective: maximize
parallel_bandwidth: 1
budget: 30