def _try_resolve(v) -> Tuple[bool, Any]:
if isinstance(v, Domain):
# Domain to sample from
return False, v
elif isinstance(v, dict) and len(v) == 1 and "eval" in v:
# Lambda function in eval syntax
return False, Function(
lambda spec: eval(v["eval"], _STANDARD_IMPORTS, {"spec": spec})
)
elif isinstance(v, dict) and len(v) == 1 and "grid_search" in v:
# Grid search values
grid_values = v["grid_search"]
return False, Categorical(grid_values).grid()
return True, v
def _try_resolve(v) -> Tuple[bool, Any]:
if isinstance(v, Domain):
# Domain to sample from
return False, v
elif isinstance(v, dict) and len(v) == 1 and "eval" in v:
# Lambda function in eval syntax
return False, Function(
lambda spec: eval(v["eval"], _STANDARD_IMPORTS, {"spec": spec}))
elif isinstance(v, dict) and len(v) == 1 and "grid_search" in v:
# Grid search values
grid_values = v["grid_search"]
if not isinstance(grid_values, list):
raise TuneError(
"Grid search expected list of values, got: {}".format(
grid_values))
return False, Categorical(grid_values).grid()
return True, v