def prepare_for_save(cls, call: APICall, fields: dict):
if call.requested_endpoint_version >= cls.max_version:
return
docker_cmd = nested_get(fields, cls.field)
if docker_cmd is not None:
image, _, arguments = docker_cmd.partition(" ")
nested_set(fields, ("container", "image"), value=image)
nested_set(fields, ("container", "arguments"), value=arguments)
nested_delete(fields, cls.field)
def params_prepare_for_save(fields: dict, previous_task: Task = None):
"""
If legacy hyper params or configuration is passed then replace the corresponding section in the new structure
Escape all the section and param names for hyper params and configuration to make it mongo sage
"""
for old_params_field, new_params_field, default_section in (
(("execution", "parameters"), "hyperparams",
hyperparams_default_section),
(("execution", "model_desc"), "configuration", None),
):
legacy_params = nested_get(fields, old_params_field)
if legacy_params is None:
continue
if (not fields.get(new_params_field) and previous_task
and previous_task[new_params_field]):
previous_data = previous_task.to_proper_dict().get(
new_params_field)
removed = _remove_legacy_params(previous_data,
with_sections=default_section
is not None)
if not legacy_params and not removed:
# if we only need to delete legacy fields from the db
# but they are not there then there is no point to proceed
continue
fields_update = {new_params_field: previous_data}
params_unprepare_from_saved(fields_update)
fields.update(fields_update)
for full_name, value in legacy_params.items():
section, name = split_param_name(full_name, default_section)
new_path = list(filter(None, (new_params_field, section, name)))
new_param = dict(name=name,
type=hyperparams_legacy_type,
value=str(value))
if section is not None:
new_param["section"] = section
nested_set(fields, new_path, new_param)
nested_delete(fields, old_params_field)
for param_field in ("hyperparams", "configuration"):
params = fields.get(param_field)
if params:
escaped_params = {
ParameterKeyEscaper.escape(key):
{ParameterKeyEscaper.escape(k): v
for k, v in value.items()}
if isinstance(value, dict) else value
for key, value in params.items()
}
fields[param_field] = escaped_params
def prepare_for_save(cls, call: APICall, fields: dict):
if call.requested_endpoint_version >= cls.max_version:
return
for mode, field in cls.mode_to_fields.items():
value = nested_get(fields, field)
if value is None:
continue
val = [
dict(
name=TaskModelNames[mode],
model=value,
updated=datetime.utcnow(),
)
] if value else []
nested_set(fields, (cls.models_field, mode), value=val)
nested_delete(fields, field)
def _upgrade_task_data(task_data: dict) -> dict:
"""
Migrate from execution/parameters and model_desc to hyperparams and configuration fiields
Upgrade artifacts list to dict
Migrate from execution.model and output.model to the new models field
Move docker_cmd contents into the container field
:param task_data: Upgraded in place
:return: The upgraded task data
"""
for old_param_field, new_param_field, default_section in (
("execution.parameters", "hyperparams",
hyperparams_default_section),
("execution.model_desc", "configuration", None),
):
legacy_path = old_param_field.split(".")
legacy = nested_get(task_data, legacy_path)
if legacy:
for full_name, value in legacy.items():
section, name = split_param_name(full_name,
default_section)
new_path = list(
filter(None, (new_param_field, section, name)))
if not nested_get(task_data, new_path):
new_param = dict(name=name,
type=hyperparams_legacy_type,
value=str(value))
if section is not None:
new_param["section"] = section
nested_set(task_data, path=new_path, value=new_param)
nested_delete(task_data, legacy_path)
artifacts_path = ("execution", "artifacts")
artifacts = nested_get(task_data, artifacts_path)
if isinstance(artifacts, list):
nested_set(
task_data,
path=artifacts_path,
value={get_artifact_id(a): a
for a in artifacts},
)
models = task_data.get("models", {})
now = datetime.utcnow()
for old_field, type_ in (
("execution.model", TaskModelTypes.input),
("output.model", TaskModelTypes.output),
):
old_path = old_field.split(".")
old_model = nested_get(task_data, old_path)
new_models = models.get(type_, [])
name = TaskModelNames[type_]
if old_model and not any(
m for m in new_models
if m.get("model") == old_model or m.get("name") == name):
model_item = {"model": old_model, "name": name, "updated": now}
if type_ == TaskModelTypes.input:
new_models = [model_item, *new_models]
else:
new_models = [*new_models, model_item]
models[type_] = new_models
nested_delete(task_data, old_path)
task_data["models"] = models
docker_cmd_path = ("execution", "docker_cmd")
docker_cmd = nested_get(task_data, docker_cmd_path)
if docker_cmd and not task_data.get("container"):
image, _, arguments = docker_cmd.partition(" ")
task_data["container"] = {"image": image, "arguments": arguments}
nested_delete(task_data, docker_cmd_path)
return task_data