if len(sys.argv) < 2:
raise ValueError(
"An experiment run guid must be passed as the first argument")
# Print run details as may be useful for debugging
experiment_run_guid = sys.argv[1]
experiment_run_details = studio_utils.get_wml_client(
).experiments.get_run_details(experiment_run_guid)
print("\nExperiment run details",
json.dumps(experiment_run_details, sort_keys=True, indent=4))
training_runs = experiment_run_details["entity"]["training_statuses"]
for run in training_runs:
run_guid = run["training_guid"]
# Download logs for this training run
remote_path = "%s/learner-1" % run_guid
remote_log_name = "training-log.txt"
remote_log_file = "%s/%s" % (remote_path, remote_log_name)
local_path = os.path.join("experiment_runs", experiment_run_guid)
os.makedirs(local_path, exist_ok=True)
local_log_file = os.path.join(local_path, "%s-log.txt" % run_guid)
print("Downloading log file to: %s" % local_log_file)
studio_utils.get_cos_utils().download_file(
project_utils.get_results_bucket(),
remote_log_file,
local_log_file,
is_redownload=True)
# Initialize various utilities that will make our lives easier
studio_utils = WatsonStudioUtils(region="us-south")
studio_utils.configure_utilities_from_file()
project_utils = ProjectUtils(studio_utils)
# Did user pass a training run?
if len(sys.argv) < 2:
raise ValueError(
"A training run guid must be passed as the first argument")
training_run_guid = sys.argv[1]
results_bucket = project_utils.get_results_bucket()
all_objects = studio_utils.get_cos_utils().get_all_objects_in_bucket(
results_bucket, prefix=training_run_guid)
for object in all_objects:
remote_file = object["Key"]
local_file = remote_file
local_file = os.path.join("training_runs", local_file)
if local_file.rfind(os.sep) != len(local_file) - 1: # not a directory
studio_utils.get_cos_utils().download_file(results_bucket,
remote_file,
local_file,
is_redownload=True)