SigOpt CLI Commands
Command | Description |
|---|---|
Same command to configure the API token and enable other features (logs and source code collection). | |
Create template files in the current directory to help you get started. | |
Show the version of the SigOpt CLI. |
Command | Description |
|---|---|
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. |
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
Command | Description |
|---|---|
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. | |
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. | |
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. |
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
Last modified 1yr ago