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removed some CPU fallback wrappers because directml seems to work now without them

remotes/1710274000886183304/main
mrq 2023-04-29 00:46:36 +07:00
parent 2f7d9ab932
commit b6a213bbbd
1 changed files with 5 additions and 5 deletions
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10
tortoise/utils/device.py
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@ -81,10 +81,7 @@ def get_device_vram( name=get_device_name() ):
return available / (1024 ** 3)
def get_device_batch_size(name=None):
if not name:
name = get_device_name()
def get_device_batch_size(name=get_device_name()):
vram = get_device_vram(name)
if vram > 14:
@ -110,6 +107,8 @@ def get_device_count(name=get_device_name()):
return 1
# if you're getting errors make sure you've updated your torch-directml, and if you're still getting errors then you can uncomment the below block
"""
if has_dml():
_cumsum = torch.cumsum
_repeat_interleave = torch.repeat_interleave
@ -127,4 +126,5 @@ if has_dml():
torch.Tensor.new = lambda self, *args, **kwargs: ( _Tensor_new(self.to("cpu"), *args, **kwargs).to(self.device) )
torch.Tensor.cumsum = lambda self, *args, **kwargs: ( _Tensor_cumsum(self.to("cpu"), *args, **kwargs).to(self.device) )
torch.Tensor.repeat_interleave = lambda self, *args, **kwargs: ( _Tensor_repeat_interleave(self.to("cpu"), *args, **kwargs).to(self.device) )
torch.Tensor.multinomial = lambda self, *args, **kwargs: ( _Tensor_multinomial(self.to("cpu"), *args, **kwargs).to(self.device) )
torch.Tensor.multinomial = lambda self, *args, **kwargs: ( _Tensor_multinomial(self.to("cpu"), *args, **kwargs).to(self.device) )
"""