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fix of issue 600 #625

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merged 1 commit into from
Dec 15, 2019
Merged

fix of issue 600 #625

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19 changes: 11 additions & 8 deletions pytorch_lightning/core/lightning.py
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Original file line number Diff line number Diff line change
Expand Up @@ -930,7 +930,7 @@ def val_dataloader(self):
return None

@classmethod
def load_from_metrics(cls, weights_path, tags_csv):
def load_from_metrics(cls, weights_path, tags_csv, map_location=None):
"""Primary way of loading model from csv weights path.

:param str weights_path: Path to a PyTorch checkpoint
Expand Down Expand Up @@ -975,9 +975,10 @@ def load_from_metrics(cls, weights_path, tags_csv):
hparams = load_hparams_from_tags_csv(tags_csv)
hparams.__setattr__('on_gpu', False)

# load on CPU only to avoid OOM issues
# then its up to user to put back on GPUs
checkpoint = torch.load(weights_path, map_location=lambda storage, loc: storage)
if map_location is not None:
checkpoint = torch.load(weights_path, map_location=map_location)
else:
checkpoint = torch.load(weights_path, map_location=lambda storage, loc: storage)

# load the state_dict on the model automatically
model = cls(hparams)
Expand All @@ -989,17 +990,19 @@ def load_from_metrics(cls, weights_path, tags_csv):
return model

@classmethod
def load_from_checkpoint(cls, checkpoint_path):
def load_from_checkpoint(cls, checkpoint_path, map_location=None):
"""
Primary way of loading model from a checkpoint
:param checkpoint_path:
:param map_location: dic for mapping storage {'cuda:1':'cuda:0'}
:return:
"""

# load on CPU only to avoid OOM issues
# then its up to user to put back on GPUs
checkpoint = torch.load(checkpoint_path, map_location=lambda storage, loc: storage)
if map_location is not None:
checkpoint = torch.load(checkpoint_path, map_location=map_location)
else:
checkpoint = torch.load(checkpoint_path, map_location=lambda storage, loc: storage)

try:
ckpt_hparams = checkpoint['hparams']
except KeyError:
Expand Down