Azure ML Training Workflows

Submit Isaac Lab reinforcement learning and LeRobot behavioral cloning training jobs to Azure Machine Learning using Kubernetes compute targets.

📋 Prerequisites

Component	Requirement
AzureML extension	Deployed via 02-deploy-azureml-extension.sh
Kubernetes compute	GPU-capable compute target attached to AzureML workspace
Azure subscription	Subscription ID, resource group, and workspace name configured

📦 Available Templates

Template	Purpose	Submission Script
train.yaml	Isaac Lab SKRL training	scripts/submit-azureml-training.sh
validate.yaml	Isaac Lab validation	scripts/submit-azureml-validation.sh
lerobot-train.yaml	LeRobot behavioral cloning	scripts/submit-azureml-lerobot-training.sh

⚙️ Isaac Lab Training Parameters

Parameter	Description
mode	Train or retrain (default: train)
checkpoint_mode	Checkpoint strategy: from-scratch, from-trained
task	Isaac Lab task name (e.g., Isaac-Cartpole-v0)
num_envs	Number of parallel environments
headless	Run without rendering (default: true)
max_iterations	Maximum training iterations

🤖 LeRobot Training Parameters

Parameter	Default	Description
dataset_repo_id	(required)	HuggingFace dataset repository
policy_type	act	Policy architecture: act, diffusion
job_name	lerobot-act-training	Unique job identifier
image	pytorch/pytorch:2.4.1-cuda12.4-cudnn9-runtime	Container image
wandb_enable	true	Enable WANDB logging
save_freq	5000	Checkpoint save frequency

🔧 Environment Variables

Variable	Description
AZURE_SUBSCRIPTION_ID	Azure subscription ID
AZURE_RESOURCE_GROUP	Resource group name
AZUREML_WORKSPACE_NAME	Azure ML workspace name
AZUREML_COMPUTE	Kubernetes compute target name

Scripts auto-detect these values from Terraform outputs. Override using CLI arguments or environment variables.

🚀 Quick Start

Isaac Lab SKRL training:

# Default configuration from Terraform outputs
./scripts/submit-azureml-training.sh

# Custom task and environment count
./scripts/submit-azureml-training.sh \
  --task Isaac-Cartpole-v0 \
  --num-envs 512 \
  --max-iterations 1000

Isaac Lab validation:

./scripts/submit-azureml-validation.sh \
  --task Isaac-Cartpole-v0 \
  --checkpoint-mode from-trained

LeRobot training:

./scripts/submit-azureml-lerobot-training.sh \
  --dataset-repo-id lerobot/aloha_sim_insertion_human \
  --policy-type act

💾 Checkpoint Management

Mode	Behavior
from-scratch	Start training from random initialization
from-trained	Resume from an existing checkpoint

Specify the checkpoint mode with --checkpoint-mode:

./scripts/submit-azureml-training.sh \
  --checkpoint-mode from-trained \
  --task Isaac-Cartpole-v0

📚 Related Documentation

• LeRobot Training
• OSMO Training
• MLflow Integration
• Training Guide

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