allenai--olmocr/scripts/run_benchmark.sh

#!/bin/bash

# Runs an olmocr-bench run using the full pipeline (no fallback)
#  Without model parameter (default behavior): uses the default image from hugging face
#   ./scripts/run_benchmark.sh
#  With model parameter: for testing custom models
#   ./scripts/run_benchmark.sh --model your-model-name
#  With cluster parameter: specify a specific cluster to use
#   ./scripts/run_benchmark.sh --cluster ai2/titan-cirrascale
#  With beaker image: skip Docker build and use provided Beaker image
#   ./scripts/run_benchmark.sh --beaker-image jakep/olmocr-benchmark-0.3.3-780bc7d934
#  With repeats parameter: run the pipeline multiple times for increased accuracy (default: 1)
#   ./scripts/run_benchmark.sh --repeats 3
#  With noperf flag: skip the performance test job
#   ./scripts/run_benchmark.sh --noperf
#  With benchrepo parameter: use a different benchmark dataset repository (default: allenai/olmOCR-bench)
#   ./scripts/run_benchmark.sh --benchrepo allenai/olmOCR-bench-internal
#  With benchbranch parameter: use a specific branch/revision of the benchmark dataset
#   ./scripts/run_benchmark.sh --benchbranch olmOCR-bench-1125
#  With benchpath parameter: use benchmark dataset from a local path or S3 path (mutually exclusive with benchrepo/benchbranch)
#   ./scripts/run_benchmark.sh --benchpath s3://ai2-oe-data/jakep/olmocr/olmOCR-bench-1125/
#  With max-tokens parameter: set max tokens for model output per page (default: 8000)
#   ./scripts/run_benchmark.sh --max-tokens 16000

set -e

# Parse command line arguments
MODEL=""
CLUSTER=""
BENCH_BRANCH=""
BENCH_REPO=""
BENCH_PATH=""
BEAKER_IMAGE=""
REPEATS="1"
NOPERF=""
MAX_TOKENS=""
while [[ $# -gt 0 ]]; do
    case $1 in
        --model)
            MODEL="$2"
            shift 2
            ;;
        --cluster)
            CLUSTER="$2"
            shift 2
            ;;
        --benchbranch)
            BENCH_BRANCH="$2"
            shift 2
            ;;
        --benchrepo)
            BENCH_REPO="$2"
            shift 2
            ;;
        --benchpath)
            BENCH_PATH="$2"
            shift 2
            ;;
        --beaker-image)
            BEAKER_IMAGE="$2"
            shift 2
            ;;
        --repeats)
            REPEATS="$2"
            shift 2
            ;;
        --noperf)
            NOPERF="1"
            shift
            ;;
        --max-tokens)
            MAX_TOKENS="$2"
            shift 2
            ;;
        *)
            echo "Unknown option: $1"
            echo "Usage: $0 [--model MODEL_NAME] [--cluster CLUSTER_NAME] [--benchbranch BRANCH_NAME] [--benchrepo REPO_URL] [--benchpath PATH] [--beaker-image IMAGE_NAME] [--repeats NUMBER] [--noperf] [--max-tokens NUMBER]"
            exit 1
            ;;
    esac
done

# Check for mutual exclusivity between benchpath and benchrepo/benchbranch
if [ -n "$BENCH_PATH" ] && ([ -n "$BENCH_REPO" ] || [ -n "$BENCH_BRANCH" ]); then
    echo "Error: --benchpath is mutually exclusive with --benchrepo and --benchbranch"
    echo "Use either --benchpath OR --benchrepo/--benchbranch, not both."
    exit 1
fi

# Check for uncommitted changes
if [ -n "$BEAKER_IMAGE" ]; then
 echo "Skipping docker build"
else
    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 benchmark."
        echo ""
        echo "Uncommitted changes:"
        git status --short
        exit 1
    fi
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"

# Check if a Beaker image was provided
if [ -n "$BEAKER_IMAGE" ]; then
    echo "Using provided Beaker image: $BEAKER_IMAGE"
    IMAGE_TAG="$BEAKER_IMAGE"
else
    # Create full image tag
    IMAGE_TAG="olmocr-benchmark-${VERSION}-${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 .

    # 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
fi

# Get Beaker username
BEAKER_USER=$(beaker account whoami --format json | jq -r '.[0].name')
echo "Beaker user: $BEAKER_USER"

# Create Python script to run beaker experiment
cat << 'EOF' > /tmp/run_benchmark_experiment.py
import sys
from beaker import Beaker, BeakerExperimentSpec, BeakerTaskSpec, BeakerTaskContext, BeakerResultSpec, BeakerTaskResources, BeakerImageSource, BeakerJobPriority, BeakerConstraints, BeakerEnvVar

# Get image tag, beaker user, git branch, git hash, optional model, cluster, bench branch, bench repo, and repeats from command line
image_tag = sys.argv[1]
beaker_user = sys.argv[2]
git_branch = sys.argv[3]
git_hash = sys.argv[4]
model = None
cluster = None
bench_branch = None
bench_repo = "allenai/olmOCR-bench"  # Default repository
bench_path = None
repeats = 1
noperf = False
max_tokens = None

# Parse remaining arguments
arg_idx = 5
while arg_idx < len(sys.argv):
    if sys.argv[arg_idx] == "--cluster":
        cluster = sys.argv[arg_idx + 1]
        arg_idx += 2
    elif sys.argv[arg_idx] == "--benchbranch":
        bench_branch = sys.argv[arg_idx + 1]
        arg_idx += 2
    elif sys.argv[arg_idx] == "--benchrepo":
        bench_repo = sys.argv[arg_idx + 1]
        arg_idx += 2
    elif sys.argv[arg_idx] == "--benchpath":
        bench_path = sys.argv[arg_idx + 1]
        arg_idx += 2
    elif sys.argv[arg_idx] == "--repeats":
        repeats = int(sys.argv[arg_idx + 1])
        arg_idx += 2
    elif sys.argv[arg_idx] == "--noperf":
        noperf = True
        arg_idx += 1
    elif sys.argv[arg_idx] == "--max-tokens":
        max_tokens = int(sys.argv[arg_idx + 1])
        arg_idx += 2
    else:
        model = sys.argv[arg_idx]
        arg_idx += 1

# Initialize Beaker client
b = Beaker.from_env(default_workspace="ai2/olmocr")

# Note: pipeline commands will be built in the loop based on repeats

# 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}")

# Check if HF_TOKEN secret exists
hf_token_secret = f"{beaker_user}-HF_TOKEN"
try:
    # Try to get the secret to see if it exists
    b.secret.get(hf_token_secret, workspace="ai2/olmocr")
    has_hf_token = True
    print(f"Found HuggingFace token secret: {hf_token_secret}")
except:
    has_hf_token = False
    print(f"HuggingFace token secret not found: {hf_token_secret}")

# First experiment: Original benchmark job
commands = []
if has_aws_creds:
    commands.extend([
        "mkdir -p ~/.aws",
        'echo "$AWS_CREDENTIALS_FILE" > ~/.aws/credentials'
    ])

if has_hf_token:
    commands.append('export HF_TOKEN="$HF_TOKEN"')

# Install s5cmd (needed for S3 operations)
commands.append("pip install s5cmd")

# Handle benchmark data download based on source type
if bench_path:
    # If bench_path is provided, use it (can be S3 or local path)
    if bench_path.startswith("s3://"):
        # S3 path - use s5cmd to download
        commands.append(f"s5cmd cp {bench_path.rstrip('/')}/* ./olmOCR-bench/")
    else:
        # Local path - copy directly
        commands.append(f"cp -r {bench_path} ./olmOCR-bench")
else:
    # Use HuggingFace download (default behavior)
    hf_download_cmd = f"hf download --repo-type dataset {bench_repo} --max-workers 2"
    if bench_branch:
        hf_download_cmd += f" --revision {bench_branch}"
    hf_download_cmd += " --local-dir ./olmOCR-bench"
    commands.append(hf_download_cmd)

# Run pipeline multiple times based on repeats
for i in range(1, repeats + 1):
    workspace_dir = f"./localworkspace{i}"
    pipeline_cmd = f"python -m olmocr.pipeline {workspace_dir} --markdown --pdfs ./olmOCR-bench/bench_data/pdfs/**/*.pdf"
    if model:
        pipeline_cmd += f" --model {model}"
    if max_tokens:
        pipeline_cmd += f" --max_tokens {max_tokens}"
    commands.append(pipeline_cmd)

# Process all workspaces with workspace_to_bench.py
for i in range(1, repeats + 1):
    workspace_dir = f"localworkspace{i}/"
    workspace_to_bench_cmd = f"python olmocr/bench/scripts/workspace_to_bench.py {workspace_dir} olmOCR-bench/bench_data/olmocr --bench-path ./olmOCR-bench/ --repeat-index {i}"
    commands.append(workspace_to_bench_cmd)

# Copy each workspace to S3
for i in range(1, repeats + 1):
    workspace_dir = f"localworkspace{i}/"
    commands.append(f"s5cmd cp {workspace_dir} s3://ai2-oe-data/jakep/olmocr-bench-runs/$BEAKER_WORKLOAD_ID/workspace{i}/")

commands.append("python -m olmocr.bench.benchmark --dir ./olmOCR-bench/bench_data")

# Build task spec with optional env vars
# If image_tag contains '/', it's already a full beaker image reference
if '/' in image_tag:
    image_ref = image_tag
else:
    image_ref = f"{beaker_user}/{image_tag}"

task_spec_args = {
    "name": "olmocr-benchmark",
    "image": BeakerImageSource(beaker=image_ref),
    "command": [
        "bash", "-c",
        " && ".join(commands)
    ],
    "context": BeakerTaskContext(
        priority=BeakerJobPriority["normal"],
        preemptible=True,
    ),
    "resources": BeakerTaskResources(gpu_count=1),
    "constraints": BeakerConstraints(cluster=[cluster] if cluster else ["ai2/ceres-cirrascale", "ai2/jupiter-cirrascale-2"]),
    "result": BeakerResultSpec(path="/noop-results"),
}

# Add env vars if AWS credentials or HF token exist
env_vars = []
if has_aws_creds:
    env_vars.append(BeakerEnvVar(name="AWS_CREDENTIALS_FILE", secret=aws_creds_secret))
if has_hf_token:
    env_vars.append(BeakerEnvVar(name="HF_TOKEN", secret=hf_token_secret))
if env_vars:
    task_spec_args["env_vars"] = env_vars

# Create first experiment spec
experiment_spec = BeakerExperimentSpec(
    description=f"OlmOCR Benchmark Run - Branch: {git_branch}, Commit: {git_hash}",
    budget="ai2/oe-base",
    tasks=[BeakerTaskSpec(**task_spec_args)],
)

# Create the first experiment
workload = b.experiment.create(spec=experiment_spec, workspace="ai2/olmocr")
print(f"Created benchmark experiment: {workload.experiment.id}")
print(f"View at: https://beaker.org/ex/{workload.experiment.id}")
print("-------")
print("")

# Second experiment: Performance test job (only if --noperf not specified)
if not noperf:
    perf_pipeline_cmd = "python -m olmocr.pipeline ./localworkspace1 --markdown --pdfs s3://ai2-oe-data/jakep/olmocr/olmOCR-mix-0225/benchmark_set/*.pdf"
    if model:
        perf_pipeline_cmd += f" --model {model}"
    if max_tokens:
        perf_pipeline_cmd += f" --max_tokens {max_tokens}"

    perf_commands = []
    if has_aws_creds:
        perf_commands.extend([
            "mkdir -p ~/.aws",
            'echo "$AWS_CREDENTIALS_FILE" > ~/.aws/credentials'
        ])
    if has_hf_token:
        perf_commands.append('export HF_TOKEN="$HF_TOKEN"')
    perf_commands.append(perf_pipeline_cmd)

    # Build performance task spec
    perf_task_spec_args = {
        "name": "olmocr-performance",
        "image": BeakerImageSource(beaker=image_ref),
        "command": [
            "bash", "-c",
            " && ".join(perf_commands)
        ],
        "context": BeakerTaskContext(
            priority=BeakerJobPriority["normal"],
            preemptible=True,
        ),
        # Need to reserve all 8 gpus for performance spec or else benchmark results can be off (1 for titan-cirrascale)
        "resources": BeakerTaskResources(gpu_count=1 if cluster == "ai2/titan-cirrascale" else 8),
        "constraints": BeakerConstraints(cluster=[cluster] if cluster else ["ai2/ceres-cirrascale", "ai2/jupiter-cirrascale-2"]),
        "result": BeakerResultSpec(path="/noop-results"),
    }

    # Add env vars if AWS credentials or HF token exist
    env_vars = []
    if has_aws_creds:
        env_vars.append(BeakerEnvVar(name="AWS_CREDENTIALS_FILE", secret=aws_creds_secret))
    if has_hf_token:
        env_vars.append(BeakerEnvVar(name="HF_TOKEN", secret=hf_token_secret))
    if env_vars:
        perf_task_spec_args["env_vars"] = env_vars

    # Create performance experiment spec
    perf_experiment_spec = BeakerExperimentSpec(
        description=f"OlmOCR Performance Test - Branch: {git_branch}, Commit: {git_hash}",
        budget="ai2/oe-base",
        tasks=[BeakerTaskSpec(**perf_task_spec_args)],
    )

    # Create the performance experiment
    perf_workload = b.experiment.create(spec=perf_experiment_spec, workspace="ai2/olmocr")
    print(f"Created performance experiment: {perf_workload.experiment.id}")
    print(f"View at: https://beaker.org/ex/{perf_workload.experiment.id}")
else:
    print("Skipping performance test (--noperf flag specified)")
EOF

# Run the Python script to create the experiments
echo "Creating Beaker experiments..."

# Build command with appropriate arguments
CMD="$PYTHON /tmp/run_benchmark_experiment.py $IMAGE_TAG $BEAKER_USER $GIT_BRANCH $GIT_HASH"

if [ -n "$MODEL" ]; then
    echo "Using model: $MODEL"
    CMD="$CMD $MODEL"
fi

if [ -n "$CLUSTER" ]; then
    echo "Using cluster: $CLUSTER"
    CMD="$CMD --cluster $CLUSTER"
fi

if [ -n "$BENCH_BRANCH" ]; then
    echo "Using bench branch: $BENCH_BRANCH"
    CMD="$CMD --benchbranch $BENCH_BRANCH"
fi

if [ -n "$BENCH_REPO" ]; then
    echo "Using bench repo: $BENCH_REPO"
    CMD="$CMD --benchrepo $BENCH_REPO"
fi

if [ -n "$BENCH_PATH" ]; then
    echo "Using bench path: $BENCH_PATH"
    CMD="$CMD --benchpath $BENCH_PATH"
fi

if [ "$REPEATS" != "1" ]; then
    echo "Using repeats: $REPEATS"
    CMD="$CMD --repeats $REPEATS"
fi

if [ -n "$NOPERF" ]; then
    echo "Skipping performance tests"
    CMD="$CMD --noperf"
fi

if [ -n "$MAX_TOKENS" ]; then
    echo "Using max tokens: $MAX_TOKENS"
    CMD="$CMD --max-tokens $MAX_TOKENS"
fi

eval $CMD

# Clean up temporary file
rm /tmp/run_benchmark_experiment.py

echo "Benchmark experiments submitted successfully!"