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Simple fix for memory leak on GPU0 #1094

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Simple fix for memory leak on GPU0 #1094

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5c554a1
SA: for #958: set torch cuda device when finding root
shubhamagarwal92 Mar 8, 2020
2f17b2f
SA: for #958: removing root gpu hack in trainer/evaluation_loop
shubhamagarwal92 Mar 8, 2020
6d89505
SA: setting torch cuda device
shubhamagarwal92 Mar 8, 2020
54e9a5e
comment line too long
shubhamagarwal92 Mar 8, 2020
83c291d
check if root gpu exists or available
shubhamagarwal92 Mar 9, 2020
6cba621
Incorporating suggestions on #1094
shubhamagarwal92 Mar 31, 2020
2c7b802
since root gpu returns none instead of -1 for cpu
shubhamagarwal92 Mar 31, 2020
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10 changes: 8 additions & 2 deletions pytorch_lightning/trainer/evaluation_loop.py
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Expand Up @@ -420,10 +420,16 @@ def evaluation_forward(self, model, batch, batch_idx, dataloader_idx, test_mode:

# single GPU data transfer
if self.single_gpu:
# for single GPU put inputs on gpu manually
root_gpu = 0

if isinstance(self.data_parallel_device_ids, list):
root_gpu = self.data_parallel_device_ids[0]
root_device = (torch.device("cuda", root_gpu)
if root_gpu else torch.device("cpu"))
torch.cuda.set_device(root_device)
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also need to add tpu device...

else:
raise RuntimeError(
'Expected `data_parallel_device_ids` as a list, cannot determine root gpu.'
)
batch = self.transfer_batch_to_gpu(batch, root_gpu)
args[0] = batch

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3 changes: 3 additions & 0 deletions pytorch_lightning/trainer/trainer.py
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Expand Up @@ -365,6 +365,9 @@ def __init__(
self.gpus = gpus
self.data_parallel_device_ids = parse_gpu_ids(self.gpus)
self.root_gpu = determine_root_gpu_device(self.data_parallel_device_ids)
root_device = (torch.device("cuda", self.root_gpu)
if self.root_gpu else torch.device("cpu"))
torch.cuda.set_device(root_device)

# tpu state flags
self.use_tpu = False
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