import json
import sys
# Add our source directory to the path as Python doesn't like sub-directories
source_path = os.path.join("..","source")
sys.path.insert(0, source_path)
from watson_studio_utils import WatsonStudioUtils
studio_utils = WatsonStudioUtils(region="us-south")
studio_utils.configure_utilities_from_file()
if len(sys.argv) < 2:
raise ValueError("An experiment run guid must be passed as the first argument")
# Download details about this experiment run
experiment_run_guid = sys.argv[1]
experiment_run_details = studio_utils.get_wml_client().experiments.get_run_details(experiment_run_guid)
print("\nExperiment details", json.dumps(experiment_run_details, indent=2))
import json
import os
import sys
# Add our source directory to the path as Python doesn't like sub-directories
source_path = os.path.join("..", "source")
sys.path.insert(0, source_path)
from watson_studio_utils import WatsonStudioUtils
from project_utils import ProjectUtils
# 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(
"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"]
import sys
import os
# Add source directory to the path as Python doesn't like sub-directories
source_path = os.path.join("..", "source")
sys.path.insert(0, source_path)
from watson_studio_utils import WatsonStudioUtils
from experiment_utils import Experiment
from project_utils import ProjectUtils
# 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)
# Initialize our experiment
experiment = Experiment("Fashion MNIST-dropout tests",
"Test two different dropout values", "tensorflow",
"1.5", "python", "3.5", studio_utils, project_utils)
# Add two training runs to determine which dropout is best: 0.4 or 0.9
run_1a_path = os.path.join("experiment_zips", "dropout_0.4.zip")
run_1b_path = os.path.join("experiment_zips", "dropout_0.6.zip")
# Specify different GPU types as "k80", "k80x2", "k80x4", "p100", ...
experiment.add_training_run("Run #1", "python3 experiment.py", run_1a_path,
"k80")
experiment.add_training_run("Run #2", "python3 experiment.py", run_1b_path,
"k80")
import json
import os
import sys
# Add our source directory to the path as Python doesn't like sub-directories
source_path = os.path.join("..", "source")
sys.path.insert(0, source_path)
from watson_studio_utils import WatsonStudioUtils
from project_utils import ProjectUtils
# 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