#!/bin/bash # Compares VLM inference between vLLM and HuggingFace checkpoints # Usage: ./scripts/compare_vllm.sh [--max-tokens N] [--num-prompts N] [--prob-threshold F] [--seed N] set -e # Default values DEFAULT_MAX_TOKENS=1000 DEFAULT_NUM_PROMPTS=100 DEFAULT_PROB_THRESHOLD=0.20 DEFAULT_SEED=42 # Parse arguments if [ $# -lt 1 ]; then echo "Usage: $0 [--max-tokens N] [--num-prompts N] [--prob-threshold F] [--seed N]" echo "Example: $0 Qwen/Qwen2.5-VL-7B-Instruct" echo "Example: $0 s3://ai2-oe-data/jakep/olmocr/model --max-tokens 50 --num-prompts 200" exit 1 fi MODEL_PATH="$1" MAX_TOKENS="$DEFAULT_MAX_TOKENS" NUM_PROMPTS="$DEFAULT_NUM_PROMPTS" PROB_THRESHOLD="$DEFAULT_PROB_THRESHOLD" SEED="$DEFAULT_SEED" # Parse optional arguments shift 1 while [[ $# -gt 0 ]]; do case $1 in --max-tokens) MAX_TOKENS="$2" shift 2 ;; --num-prompts) NUM_PROMPTS="$2" shift 2 ;; --prob-threshold) PROB_THRESHOLD="$2" shift 2 ;; --seed) SEED="$2" shift 2 ;; *) echo "Unknown option: $1" exit 1 ;; esac done # Check for uncommitted changes if ! git diff-index --quiet HEAD --; then echo "Error: There are uncommitted changes in the repository." echo "Please commit or stash your changes before running the comparison." echo "" echo "Uncommitted changes:" git status --short exit 1 fi # Use conda environment Python if available, otherwise use system Python if [ -n "$CONDA_PREFIX" ]; then PYTHON="$CONDA_PREFIX/bin/python" echo "Using conda Python from: $CONDA_PREFIX" else PYTHON="python" echo "Warning: No conda environment detected, using system Python" fi # Get version from version.py VERSION=$($PYTHON -c 'import olmocr.version; print(olmocr.version.VERSION)') echo "OlmOCR version: $VERSION" # Get first 10 characters of git hash GIT_HASH=$(git rev-parse HEAD | cut -c1-10) echo "Git hash: $GIT_HASH" # Get current git branch name GIT_BRANCH=$(git rev-parse --abbrev-ref HEAD) echo "Git branch: $GIT_BRANCH" # Create full image tag IMAGE_TAG="olmocr-compare-vllm-${VERSION}-${GIT_HASH}" echo "Building Docker image with tag: $IMAGE_TAG" # Build the Docker image echo "Building Docker image..." docker build --platform linux/amd64 -f ./Dockerfile -t $IMAGE_TAG . # Get Beaker username BEAKER_USER=$(beaker account whoami --format json | jq -r '.[0].name') echo "Beaker user: $BEAKER_USER" # Push image to beaker echo "Trying to push image to Beaker..." if ! beaker image create --workspace ai2/oe-data-pdf --name $IMAGE_TAG $IMAGE_TAG 2>/dev/null; then echo "Warning: Beaker image with tag $IMAGE_TAG already exists. Using existing image." fi # Create Python script to run beaker experiment cat << 'EOF' > /tmp/run_compare_vllm_experiment.py import sys from beaker import Beaker, ExperimentSpec, TaskSpec, TaskContext, ResultSpec, TaskResources, ImageSource, Priority, Constraints, EnvVar, DataMount # Get parameters from command line image_tag = sys.argv[1] beaker_user = sys.argv[2] git_branch = sys.argv[3] git_hash = sys.argv[4] model_path = sys.argv[5] max_tokens = sys.argv[6] num_prompts = sys.argv[7] prob_threshold = sys.argv[8] seed = sys.argv[9] # Initialize Beaker client b = Beaker.from_env(default_workspace="ai2/olmocr") # Check if AWS credentials secret exists aws_creds_secret = f"{beaker_user}-AWS_CREDENTIALS_FILE" try: # Try to get the secret to see if it exists b.secret.get(aws_creds_secret, workspace="ai2/olmocr") has_aws_creds = True print(f"Found AWS credentials secret: {aws_creds_secret}") except: has_aws_creds = False print(f"AWS credentials secret not found: {aws_creds_secret}") # Build commands for comparison job commands = [] if has_aws_creds: commands.extend([ "mkdir -p ~/.aws", 'echo "$AWS_CREDENTIALS_FILE" > ~/.aws/credentials' ]) commands.extend([ # Install accelerate "pip install accelerate", # Run comparison f'python -m olmocr.train.compare_vllm_checkpoint --model {model_path} --max-tokens {max_tokens} --num-prompts {num_prompts} --prob-threshold {prob_threshold} --seed {seed}' ]) # Build task spec with optional env vars task_spec_args = { "name": "olmocr-compare-vllm", "image": ImageSource(beaker=f"{beaker_user}/{image_tag}"), "command": [ "bash", "-c", " && ".join(commands) ], "context": TaskContext( priority=Priority.normal, preemptible=True, ), "resources": TaskResources(gpu_count=1), "constraints": Constraints(cluster=["ai2/ceres-cirrascale", "ai2/jupiter-cirrascale-2"]), "result": ResultSpec(path="/noop-results"), "datasets": [ DataMount.new(mount_path="/weka/oe-data-default", weka="oe-data-default"), DataMount.new(mount_path="/weka/oe-training-default", weka="oe-training-default"), ] } # Add env vars if AWS credentials exist if has_aws_creds: task_spec_args["env_vars"] = [ EnvVar(name="AWS_CREDENTIALS_FILE", secret=aws_creds_secret) ] # Create experiment spec experiment_spec = ExperimentSpec( description=f"OlmOCR vLLM vs HF Comparison - Branch: {git_branch}, Commit: {git_hash}, Model: {model_path}", budget="ai2/oe-data", tasks=[TaskSpec(**task_spec_args)], ) # Create the experiment experiment = b.experiment.create(spec=experiment_spec, workspace="ai2/olmocr") print(f"Created comparison experiment: {experiment.id}") print(f"View at: https://beaker.org/ex/{experiment.id}") EOF # Run the Python script to create the experiment echo "Creating Beaker experiment..." echo "Comparing model: $MODEL_PATH" echo "Max tokens: $MAX_TOKENS" echo "Number of prompts: $NUM_PROMPTS" echo "Probability threshold: $PROB_THRESHOLD" echo "Random seed: $SEED" $PYTHON /tmp/run_compare_vllm_experiment.py $IMAGE_TAG $BEAKER_USER $GIT_BRANCH $GIT_HASH "$MODEL_PATH" "$MAX_TOKENS" "$NUM_PROMPTS" "$PROB_THRESHOLD" "$SEED" # Clean up temporary file rm /tmp/run_compare_vllm_experiment.py echo "Comparison experiment submitted successfully!"