dlpy.model.Gpu¶
-
class
dlpy.model.
Gpu
(devices=None, use_tensor_rt=False, precision='fp32', use_exclusive=False)¶ Gpu parameters object.
- Parameters
- deviceslist-of-ints, optional
Specifies a list of GPU devices to be used.
- use_tensor_rtbool, optional
Enables using TensorRT for fast inference. Default: False.
- precisionstring, optional
Specifies the experimental option to incorporate lower computational precision in forward-backward computations to potentially engage tensor cores. Valid Values: FP32, FP16 Default: FP32
- use_exclusivebool, optional
Specifies exclusive use of GPU devices. Default: False
- Returns
-
__init__
(devices=None, use_tensor_rt=False, precision='fp32', use_exclusive=False)¶ Initialize self. See help(type(self)) for accurate signature.
Methods
__init__
([devices, use_tensor_rt, …])Initialize self.
clear
()get
(k[,d])items
()keys
()pop
(k[,d])If key is not found, d is returned if given, otherwise KeyError is raised.
popitem
()as a 2-tuple; but raise KeyError if D is empty.
setdefault
(k[,d])update
([E, ]**F)If E present and has a .keys() method, does: for k in E: D[k] = E[k] If E present and lacks .keys() method, does: for (k, v) in E: D[k] = v In either case, this is followed by: for k, v in F.items(): D[k] = v
values
()