add a private function to find adam opt pass

trainerSaveLoadParams
Yancey1989 8 years ago
parent da960ada49
commit e9737d600f

@ -401,11 +401,8 @@ class DistributeTranspiler:
# HACK: optimization global ops only used to scale beta1 and beta2
# replace it with dependency engine.
for op in self.optimize_ops:
if op.type == "scale":
for in_name in op.input_arg_names:
if in_name.startswith("beta1_pow_acc") or \
in_name.startswith("beta2_pow_acc"):
global_ops.append(op)
if self._is_adam_connected_op(op):
global_ops.append(op)
def __append_optimize_op__(op, block, grad_to_block_id):
if self._is_opt_op(op):
@ -1152,13 +1149,20 @@ class DistributeTranspiler:
op.input("Param")[0]),
self.origin_program.global_block().var(
op.input("Grad")[0])))
elif op.type == "scale":
# for adam optimize op
for in_name in op.input_arg_names:
if in_name.startswith("beta1_pow_acc") or \
in_name.startswith("beta2_pow_acc"):
opt_ops.append(op)
break
elif self._is_adam_connected_op(op):
opt_ops.append(op)
else:
pass
return opt_ops, params_grads
def _is_adam_connected_op(self, op):
"""
A hack function to determinate whether the input operator
is connected to optimize operator.
"""
if op.type == "scale":
for in_name in op.input_arg_names:
if in_name.startswith("beta1_pow_acc") or \
in_name.startswith("beta2_pow_acc"):
return True
return False

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