api.py 文件源码

def _upload_benchmark(training_dir, algorithm_id, benchmark_id, benchmark_run_tags, api_key, ignore_open_monitors, skip_videos):
    # We're uploading a benchmark run.
    directories = []
    env_ids = []
    for name, _, files in os.walk(training_dir):
        manifests = monitoring.detect_training_manifests(name, files=files)
        if manifests:
            env_info = monitoring.load_env_info_from_manifests(manifests, training_dir)
            env_ids.append(env_info['env_id'])
            directories.append(name)

    # Validate against benchmark spec
    try:
        spec = benchmark_spec(benchmark_id)
    except error.UnregisteredBenchmark:
        raise error.Error("Invalid benchmark id: {}. Are you using a benchmark registered in gym/benchmarks/__init__.py?".format(benchmark_id))

    spec_env_ids = [task.env_id for task in spec.tasks for _ in range(task.trials)]

    if not env_ids:
        raise error.Error("Could not find any evaluations in {}".format(training_dir))

    # This could be more stringent about mixing evaluations
    if sorted(env_ids) != sorted(spec_env_ids):
        logger.info("WARNING: Evaluations do not match spec for benchmark %s. In %s, we found evaluations for %s, expected %s", benchmark_id, training_dir, sorted(env_ids), sorted(spec_env_ids))

    tags = json.dumps(benchmark_run_tags)
    _create_with_retries = util.retry_exponential_backoff(
        resource.BenchmarkRun.create,
        (error.APIConnectionError,),
        max_retries=5,
        interval=3,
    )
    benchmark_run = _create_with_retries(benchmark_id=benchmark_id, algorithm_id=algorithm_id, tags=tags)
    benchmark_run_id = benchmark_run.id

    # Actually do the uploads.
    for training_dir in directories:
        # N.B. we don't propagate algorithm_id to Evaluation if we're running as part of a benchmark
        _upload_with_retries = util.retry_exponential_backoff(
            _upload,
            (error.APIConnectionError,),
            max_retries=5,
            interval=3,
        )
        _upload_with_retries(training_dir, None, None, benchmark_run_id, api_key, ignore_open_monitors, skip_videos)

    logger.info("""
****************************************************
You successfully uploaded your benchmark on %s to
OpenAI Gym! You can find it at:

    %s

****************************************************
    """.rstrip(), benchmark_id, benchmark_run.web_url())

    return benchmark_run_id