|
|
|
#!/usr/bin/env python
|
|
|
|
# -*- encoding: utf-8 -*-
|
|
|
|
|
|
|
|
import torch
|
|
|
|
|
|
|
|
|
|
|
|
def set_to_cuda(models):
|
|
|
|
"""Send model to gpu.
|
|
|
|
|
|
|
|
:param models: nn.module or a list of module
|
|
|
|
"""
|
|
|
|
if isinstance(models, list) and len(models) > 1:
|
|
|
|
ret = []
|
|
|
|
for model in models:
|
|
|
|
ret.append(model.to(get_current_device()))
|
|
|
|
return ret
|
|
|
|
elif isinstance(models, list):
|
|
|
|
return models[0].to(get_current_device())
|
|
|
|
else:
|
|
|
|
return models.to(get_current_device())
|
|
|
|
|
|
|
|
|
|
|
|
def get_current_device() -> torch.device:
|
|
|
|
"""
|
|
|
|
Returns currently selected device (gpu/cpu).
|
|
|
|
If cuda available, return gpu, otherwise return cpu.
|
|
|
|
"""
|
|
|
|
if torch.cuda.is_available():
|
|
|
|
return torch.device(f'cuda:{torch.cuda.current_device()}')
|
|
|
|
else:
|
|
|
|
return torch.device('cpu')
|
|
|
|
|
|
|
|
|
|
|
|
def synchronize():
|
|
|
|
"""Similar to cuda.synchronize().
|
|
|
|
Waits for all kernels in all streams on a CUDA device to complete.
|
|
|
|
"""
|
|
|
|
if torch.cuda.is_available():
|
|
|
|
torch.cuda.synchronize()
|
|
|
|
|
|
|
|
|
|
|
|
def empty_cache():
|
|
|
|
"""Similar to cuda.empty_cache()
|
|
|
|
Releases all unoccupied cached memory currently held by the caching allocator.
|
|
|
|
"""
|
|
|
|
if torch.cuda.is_available():
|
|
|
|
torch.cuda.empty_cache()
|