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optimizer must be decorated when training with AMPO2

pull/2732/head
gaotingquan 2023-03-28 09:18:45 +00:00 committed by cuicheng01
parent dc2c8528ad
commit a7ba6eabd2
1 changed files with 11 additions and 27 deletions
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38
ppcls/engine/engine.py
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@ -274,33 +274,17 @@ class Engine(object):
self.config["AMP"]["use_fp16_test"] = True
self.amp_eval = True
# TODO(gaotingquan): to compatible with different versions of Paddle
paddle_version = paddle.__version__[:3]
# paddle version < 2.3.0 and not develop
if paddle_version not in ["2.3", "0.0"]:
if self.mode == "train":
self.model, self.optimizer = paddle.amp.decorate(
models=self.model,
optimizers=self.optimizer,
level=self.amp_level,
save_dtype='float32')
elif self.amp_eval:
if self.amp_level == "O2":
msg = "The PaddlePaddle that installed not support FP16 evaluation in AMP O2. Please use PaddlePaddle version >= 2.3.0. Use FP32 evaluation instead and please notice the Eval Dataset output_fp16 should be 'False'."
logger.warning(msg)
self.amp_eval = False
else:
self.model, self.optimizer = paddle.amp.decorate(
models=self.model,
level=self.amp_level,
save_dtype='float32')
# paddle version >= 2.3.0 or develop
else:
if self.mode == "train" or self.amp_eval:
self.model = paddle.amp.decorate(
models=self.model,
level=self.amp_level,
save_dtype='float32')
if self.mode == "train":
self.model, self.optimizer = paddle.amp.decorate(
models=self.model,
optimizers=self.optimizer,
level=self.amp_level,
save_dtype='float32')
elif self.amp_eval:
self.model = paddle.amp.decorate(
models=self.model,
level=self.amp_level,
save_dtype='float32')
if self.mode == "train" and len(self.train_loss_func.parameters(
)) > 0: