diff --git a/src/mednet/scripts/cli.py b/src/mednet/scripts/cli.py
index fb3f605739811c9a5a5455cf6d8c8a89919c59f3..a6950a566aca7f57dea8cb1ae19de8ef55380af0 100644
--- a/src/mednet/scripts/cli.py
+++ b/src/mednet/scripts/cli.py
@@ -69,3 +69,5 @@ saliency.add_command(
saliency.add_command(
importlib.import_module("..saliency.view", package=__name__).view,
)
+
+cli.add_command(importlib.import_module("..upload", package=__name__).upload)
diff --git a/src/mednet/scripts/upload.py b/src/mednet/scripts/upload.py
new file mode 100644
index 0000000000000000000000000000000000000000..a35184bf71425d784c31012485932aa7f71fc481
--- /dev/null
+++ b/src/mednet/scripts/upload.py
@@ -0,0 +1,155 @@
+# SPDX-FileCopyrightText: Copyright © 2023 Idiap Research Institute <contact@idiap.ch>
+#
+# SPDX-License-Identifier: GPL-3.0-or-later
+
+import os
+import json
+import pathlib
+import shutil
+import tempfile
+import configparser
+
+import gitlab
+import mlflow
+
+import click
+from clapper.click import ResourceOption, verbosity_option
+from clapper.logging import setup
+
+from .click import ConfigCommand
+
+logger = setup(__name__.split(".")[0], format="%(levelname)s: %(message)s")
+
+def get_config():
+ """Returns an instance of the Gitlab object for remote operations."""
+
+ cfg = pathlib.Path(os.path.expanduser("~/.python-gitlab.cfg"))
+ if cfg.exists():
+ gl = gitlab.Gitlab.from_config("idiap", [str(cfg)])
+ config = configparser.ConfigParser()
+ config.read(cfg)
+ else: # ask the user for a token or use one from the current runner
+ server = "https://gitlab.idiap.ch"
+ token = input(f"{server} (user or project) token: ")
+ gl = gitlab.Gitlab(server, private_token=token, api_version="4")
+ config = {"idiap": {"private_token": token}}
+
+ return gl, config
+
+def create_temp_copy(source, target):
+ temp_dir = tempfile.gettempdir()
+ target = os.path.join(temp_dir, target)
+ shutil.copy2(source, target)
+ return target
+
+@click.command(
+ entry_point_group="mednet.config",
+ cls=ConfigCommand,
+ epilog="""Examples:
+
+1. Upload an existing experiment result from a path it resides on (with a default experiment name as {model-name}_{database-name} and a default run name as {date-time}):
+
+ .. code:: sh
+
+ mednet upload --output-folder=path/to/results
+
+2. Upload an existing experiment result with an experiment name:
+
+ .. code:: sh
+
+ mednet upload--output-folder=path/to/results --experiment-name=exp-pasa_mc
+
+3. Upload an existing experiment result with a run name:
+
+ .. code:: sh
+
+ mednet upload--output-folder=path/to/results --run-name=run-1
+""",
+)
+@click.option(
+ "--output-folder",
+ "-o",
+ help="Directory in which to upload results from",
+ required=True,
+ type=click.Path(
+ file_okay=False,
+ dir_okay=True,
+ path_type=pathlib.Path,
+ ),
+ default="results",
+ cls=ResourceOption,
+ )
+@click.option(
+ "--experiment-name",
+ "-e",
+ help='A string indicating the experiment name (e.g. "exp-pasa_mc" or "exp-densenet_mc-ch")',
+ cls=ResourceOption,
+ )
+@click.option(
+ "--run-name",
+ "-r",
+ help='A string indicating the run name (e.g. "run-1")',
+ cls=ResourceOption,
+ )
+@verbosity_option(logger=logger, cls=ResourceOption, expose_value=False)
+def upload(
+ output_folder: pathlib.Path,
+ experiment_name: str,
+ run_name: str,
+ **_, # ignored
+) -> None: # numpydoc ignore=PR01
+ """Upload results from an experiment output folder."""
+
+ logger.info(f"Getting Gitlab credentials for accessing to MLFlow server...")
+ gitlab, config = get_config()
+ project = gitlab.projects.get('biosignal/software/mednet')
+ tracking_uri = gitlab.api_url + f"/projects/{project.id}/ml/mlflow"
+ os.environ["MLFLOW_TRACKING_TOKEN"] = config["idiap"]["private_token"]
+ os.environ["MLFLOW_TRACKING_URI"] = (
+ gitlab.api_url + f"/projects/{project.id}/ml/mlflow"
+ )
+
+ # prepare train files
+ train_output_folder = output_folder / "model"
+ train_meta_file = train_output_folder / "meta.json"
+ train_log_file = train_output_folder / "trainlog.pdf"
+ train_model_file = [str(f) for f in train_output_folder.glob("*lowest*")][0]
+ train_model_temp_file = train_model_file.split(os.sep)[-1].replace("=", "_")
+ train_model_temp_file = create_temp_copy(train_model_file, train_model_temp_file)
+ with train_meta_file.open("r") as f:
+ meta_data = json.load(f)
+
+ # prepare evaluation files
+ evaluation_file = output_folder / "evaluation.json"
+ evaluation_meta_file = output_folder / "evaluation.meta.json"
+ evaluation_log_file = output_folder / "evaluation.pdf"
+ with evaluation_file.open("r") as f:
+ evaluation_data = json.load(f)
+ test_data = evaluation_data["test"]
+
+ # prepare experiment and run names
+ experiment_name = experiment_name if experiment_name else f'{meta_data["model-name"]}_{meta_data["database-name"]}'
+ run_name = run_name if run_name else meta_data["datetime"]
+
+ logger.info(f"Setting experiment and run names on the MLFlow server...")
+ mlflow.set_experiment(experiment_name=experiment_name)
+ with mlflow.start_run(run_name=run_name) as run:
+ # upload metrics
+ logger.info(f"Uploading metrics to MLFlow server...")
+ mlflow.log_metric("threshold", test_data["threshold"])
+ mlflow.log_metric("precision", test_data["precision"])
+ mlflow.log_metric("recall", test_data["recall"])
+ mlflow.log_metric("f1_score", test_data["f1_score"])
+ mlflow.log_metric("average_precision_score", test_data["average_precision_score"])
+ mlflow.log_metric("specificity", test_data["specificity"])
+ mlflow.log_metric("auc_score", test_data["auc_score"])
+ mlflow.log_metric("accuracy", test_data["accuracy"])
+ mlflow.log_param("version", meta_data["package-version"])
+ # upload artifacts
+ logger.info(f"Uploading artifacts to MLFlow server...")
+ mlflow.log_artifact(train_meta_file)
+ mlflow.log_artifact(train_log_file)
+ mlflow.log_artifact(train_model_temp_file)
+ mlflow.log_artifact(evaluation_file)
+ mlflow.log_artifact(evaluation_meta_file)
+ mlflow.log_artifact(evaluation_log_file)
\ No newline at end of file
diff --git a/tests/test_cli.py b/tests/test_cli.py
index aa04ec07067766e5d7174db4cdd892783c7b5de6..c8d597469b7a8ed733f036e9cd5d2d054b2b779f 100644
--- a/tests/test_cli.py
+++ b/tests/test_cli.py
@@ -175,6 +175,12 @@ def test_saliency_evaluate_help():
_check_help(evaluate)
+def test_upload_help():
+ from mednet.scripts.upload import upload
+
+ _check_help(upload)
+
+
@pytest.mark.skip_if_rc_var_not_set("datadir.montgomery")
def test_train_pasa_montgomery(temporary_basedir):
from mednet.scripts.train import train