def _compute_path_value(self, user_param_value, storage_dir):
local_path = get_local_path_or_none(user_param_value)
if local_path:
if not os.path.exists(local_path):
raise ExecutionException("Got value %s for parameter %s, but no such file or "
"directory was found." % (user_param_value, self.name))
return os.path.abspath(local_path)
basename = os.path.basename(user_param_value)
dest_path = os.path.join(storage_dir, basename)
if dest_path != user_param_value:
data.download_uri(uri=user_param_value, output_path=dest_path)
return os.path.abspath(dest_path)
def _compute_path_value(self, user_param_value, storage_dir, key_position):
local_path = get_local_path_or_none(user_param_value)
if local_path:
if not os.path.exists(local_path):
raise ExecutionException(
"Got value %s for parameter %s, but no such file or "
"directory was found." % (user_param_value, self.name))
return os.path.abspath(local_path)
target_sub_dir = "param_{}".format(key_position)
download_dir = os.path.join(storage_dir, target_sub_dir)
os.mkdir(download_dir)
return artifact_utils._download_artifact_from_uri(
artifact_uri=user_param_value, output_path=download_dir)
def _get_docker_command(image, active_run):
docker_path = "docker"
cmd = [docker_path, "run", "--rm"]
env_vars = _get_run_env_vars(run_id=active_run.info.run_id,
experiment_id=active_run.info.experiment_id)
tracking_uri = tracking.get_tracking_uri()
local_path, container_tracking_uri = _get_local_uri_or_none(tracking_uri)
artifact_uri_local_path = get_local_path_or_none(
active_run.info.artifact_uri)
if local_path is not None:
cmd += ["-v", "%s:%s" % (local_path, _MLFLOW_DOCKER_TRACKING_DIR_PATH)]
env_vars[tracking._TRACKING_URI_ENV_VAR] = container_tracking_uri
if artifact_uri_local_path is not None:
container_path = artifact_uri_local_path
if not os.path.isabs(container_path):
container_path = os.path.join("/mlflow/projects/code/",
artifact_uri_local_path)
container_path = os.path.normpath(container_path)
artifact_uri_local_abspath = os.path.abspath(artifact_uri_local_path)
cmd += ["-v", "%s:%s" % (artifact_uri_local_abspath, container_path)]
if tracking.utils._is_databricks_uri(tracking_uri):
db_profile = mlflow.tracking.utils.get_db_profile_from_uri(
tracking_uri)
config = databricks_utils.get_databricks_host_creds(db_profile)
# We set these via environment variables so that only the current profile is exposed, rather
# than all profiles in ~/.databrickscfg; maybe better would be to mount the necessary
# part of ~/.databrickscfg into the container
env_vars[tracking._TRACKING_URI_ENV_VAR] = 'databricks'
env_vars['DATABRICKS_HOST'] = config.host
if config.username:
env_vars['DATABRICKS_USERNAME'] = config.username
if config.password:
env_vars['DATABRICKS_PASSWORD'] = config.password
if config.token:
env_vars['DATABRICKS_TOKEN'] = config.token
if config.ignore_tls_verification:
env_vars['DATABRICKS_INSECURE'] = config.ignore_tls_verification
for key, value in env_vars.items():
cmd += ["-e", "{key}={value}".format(key=key, value=value)]
cmd += [image.tags[0]]
return cmd
