fix: skip setting seed when descriptor/fitting_net doesn't exist

deepmodeling · Jul 13, 2024 · c9734d7 · c9734d7
1 parent 30bc1e5
commit c9734d7
Showing 1 changed file with 7 additions and 4 deletions.
diff --git a/dpgen/generator/run.py b/dpgen/generator/run.py
@@ -583,7 +583,9 @@ def make_train_dp(iter_index, jdata, mdata):
  mdata["deepmd_version"]
  ) < Version("3"):
  # 1.x
- if jinput["model"]["descriptor"]["type"] == "hybrid":
+ if "descriptor" not in jinput["model"]:
+ pass
+ elif jinput["model"]["descriptor"]["type"] == "hybrid":
  for desc in jinput["model"]["descriptor"]["list"]:
  desc["seed"] = random.randrange(sys.maxsize) % (2**32)
  elif jinput["model"]["descriptor"]["type"] == "loc_frame":
@@ -592,9 +594,10 @@ def make_train_dp(iter_index, jdata, mdata):
  jinput["model"]["descriptor"]["seed"] = random.randrange(
  sys.maxsize
  ) % (2**32)
- jinput["model"]["fitting_net"]["seed"] = random.randrange(sys.maxsize) % (
- 2**32
- )
+ if "fitting_net" in jinput["model"]:
+ jinput["model"]["fitting_net"]["seed"] = random.randrange(
+ sys.maxsize
+ ) % (2**32)
  if "type_embedding" in jinput["model"]:
  jinput["model"]["type_embedding"]["seed"] = random.randrange(
  sys.maxsize