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Workflow Templates (OSMO)

Canonical OSMO workflow templates for RL and LeRobot training and evaluation. Template names in this page are based on current YAML files and exclude stale legacy naming.

Template Inventory

TemplatePurposeSource YAML pathTypical submit path
train.yamlIsaacLab RL training with inline payload archivetraining/rl/workflows/osmo/train.yamltraining/rl/scripts/submit-osmo-training.sh
train-dataset.yamlIsaacLab RL training with dataset folder injectiontraining/il/workflows/osmo/train-dataset.yamltraining/il/scripts/submit-osmo-dataset-training.sh
lerobot-train.yamlLeRobot ACT or Diffusion training workflowtraining/il/workflows/osmo/lerobot-train.yamltraining/il/scripts/submit-osmo-lerobot-training.sh
eval.yamlIsaacLab checkpoint evaluation workflowevaluation/sil/workflows/osmo/eval.yamlevaluation/sil/scripts/submit-osmo-eval.sh
lerobot-eval.yamlLeRobot policy evaluation workflowevaluation/sil/workflows/osmo/lerobot-eval.yamlevaluation/sil/scripts/submit-osmo-lerobot-eval.sh

train.yaml

FieldDetails
PurposeOSMO RL training using a base64-encoded runtime payload.
Source YAML pathtraining/rl/workflows/osmo/train.yaml
Primary parameters and overridesdefault-values.task (Isaac-Velocity-Rough-Anymal-C-v0), default-values.num_envs ("2048"), default-values.max_iterations (empty), default-values.checkpoint_mode (from-scratch), default-values.training_backend (skrl), default-values.gpu ("1"), default-values.cpu ("30").
Typical submit pathtraining/rl/scripts/submit-osmo-training.sh
Usage notesUse for RL training when shipping the runtime payload inline. Script flags typically override task, resources, and checkpoint behavior.

train-dataset.yaml

FieldDetails
PurposeOSMO RL training that mounts training code from an uploaded dataset path.
Source YAML pathtraining/il/workflows/osmo/train-dataset.yaml
Primary parameters and overridesdefault-values.dataset_bucket (training), default-values.dataset_name (training-code), default-values.task (Isaac-Velocity-Rough-Anymal-C-v0), default-values.num_envs ("2048"), default-values.checkpoint_mode (from-scratch), default-values.training_backend (skrl).
Typical submit pathtraining/il/scripts/submit-osmo-dataset-training.sh
Usage notesUse when payload size or reuse favors dataset-based delivery. The script stages and uploads training sources before submission.

lerobot-train.yaml

FieldDetails
PurposeOSMO LeRobot training with optional Azure Blob dataset source and checkpoint registration.
Source YAML pathtraining/il/workflows/osmo/lerobot-train.yaml
Primary parameters and overridesdefault-values.policy_type (act), default-values.dataset_repo_id (empty), default-values.training_steps ("100000"), default-values.batch_size ("32"), default-values.learning_rate ("1e-4"), default-values.save_freq ("5000"), default-values.storage_container (datasets), default-values.register_checkpoint (empty).
Typical submit pathtraining/il/scripts/submit-osmo-lerobot-training.sh
Usage notesSupports HuggingFace and blob-backed datasets. Keep policy type and data source aligned with script flags to avoid mixed-source configuration.

eval.yaml

FieldDetails
PurposeOSMO IsaacLab checkpoint evaluation for policy export and validation.
Source YAML pathevaluation/sil/workflows/osmo/eval.yaml
Primary parameters and overridesdefault-values.task (Isaac-Ant-v0), default-values.num_envs ("4"), default-values.max_steps ("500"), default-values.video_length ("200"), default-values.checkpoint_uri (empty), default-values.inference_format (both).
Typical submit pathevaluation/sil/scripts/submit-osmo-eval.sh
Usage notesRequires checkpoint URI at submission. Use inference_format to control ONNX/JIT export behavior for downstream use.

lerobot-eval.yaml

FieldDetails
PurposeOSMO LeRobot evaluation for HuggingFace or AzureML model sources, with optional registration.
Source YAML pathevaluation/sil/workflows/osmo/lerobot-eval.yaml
Primary parameters and overridesdefault-values.policy_repo_id (empty), default-values.policy_type (act), default-values.dataset_repo_id (empty), default-values.eval_episodes ("10"), default-values.eval_batch_size ("10"), default-values.record_video ("false"), default-values.mlflow_enable ("false"), default-values.register_model (empty), default-values.blob_storage_container (datasets).
Typical submit pathevaluation/sil/scripts/submit-osmo-lerobot-eval.sh
Usage notesThis is the canonical LeRobot OSMO evaluation template.

Usage Notes

TopicGuidance
Source of truthUse YAML files under training/ and evaluation/ as the canonical inventory.
Submission flowSubmit through the companion scripts listed above to resolve defaults from CLI, env vars, and Terraform outputs.
Runtime packagingRL workflows use inline payload or dataset injection; choose based on payload size and reuse needs.
Related referenceSee Reference index for adjacent script and artifact guides.