def get_remote_model(remote_model_checkpoint_path):
if is_anyscale_connect():
# Download training results to local client.
local_dir = "~/ray_results"
# TODO(matt): remove the following line when Anyscale Connect
# supports tilde expansion.
local_dir = os.path.expanduser(local_dir)
remote_dir = "/home/ray/ray_results/"
ray.client().download_results(local_dir=local_dir,
remote_dir=remote_dir)
# Compute local path.
rel_model_checkpoint_path = os.path.relpath(
remote_model_checkpoint_path, remote_dir)
local_model_checkpoint_path = os.path.join(local_dir,
rel_model_checkpoint_path)
# Load model reference.
return get_model(local_model_checkpoint_path)
else:
get_best_model_remote = ray.remote(get_model)
return ray.get(
get_best_model_remote.remote(remote_model_checkpoint_path))
cpus_per_actor=2),
num_boost_round=100,
evals=evallist)
if __name__ == "__main__":
parser = argparse.ArgumentParser()
parser.add_argument("--smoke-test",
action="store_true",
help="Finish quickly for testing.")
args = parser.parse_args()
start = time.time()
client_builder = ray.client()
if is_anyscale_connect():
job_name = os.environ.get("RAY_JOB_NAME", "modin_xgboost_test")
client_builder.job_name(job_name)
client_builder.connect()
main()
taken = time.time() - start
result = {
"time_taken": taken,
}
test_output_json = os.environ.get("TEST_OUTPUT_JSON",
"/tmp/modin_xgboost_test.json")
with open(test_output_json, "wt") as f:
json.dump(result, f)
inference_df,
ray_params=RayParams(cpus_per_actor=2, num_actors=16))
if __name__ == "__main__":
parser = argparse.ArgumentParser()
parser.add_argument("--smoke-test",
action="store_true",
help="Finish quickly for testing.")
args = parser.parse_args()
start = time.time()
addr = os.environ.get("RAY_ADDRESS")
job_name = os.environ.get("RAY_JOB_NAME", "dask_xgboost_test")
if is_anyscale_connect(addr):
ray.init(address=addr, job_name=job_name)
else:
ray.init(address="auto")
main()
taken = time.time() - start
result = {
"time_taken": taken,
}
test_output_json = os.environ.get("TEST_OUTPUT_JSON",
"/tmp/dask_xgboost_test.json")
with open(test_output_json, "wt") as f:
json.dump(result, f)