Hello,
I’m trying to sample from the Student T distribution.
I use the following code:
m = StudentT(torch.tensor([4846]))
m.sample()
That is derived from the docs:
https://pytorch.org/docs/stable/distributions.html
Here is the error in and the traceback:
--------------------------------------------------------------------------
RuntimeError Traceback (most recent call last)
<ipython-input-73-3011aef638a1> in <module>()
6 annual_investment = torch.tensor([0])
7 m = StudentT(torch.tensor([4846]))
----> 8 m.sample()
9 # for x in range(iterations):
10
2 frames
/usr/local/lib/python3.6/dist-packages/torch/distributions/distribution.py in sample(self, sample_shape)
117 """
118 with torch.no_grad():
--> 119 return self.rsample(sample_shape)
120
121 def rsample(self, sample_shape=torch.Size()):
/usr/local/lib/python3.6/dist-packages/torch/distributions/studentT.py in rsample(self, sample_shape)
68 # Y = X / sqrt(Z / df) ~ StudentT(df)
69 shape = self._extended_shape(sample_shape)
---> 70 X = _standard_normal(shape, dtype=self.df.dtype, device=self.df.device)
71 Z = self._chi2.rsample(sample_shape)
72 Y = X * torch.rsqrt(Z / self.df)
/usr/local/lib/python3.6/dist-packages/torch/distributions/utils.py in _standard_normal(shape, dtype, device)
39 return torch.normal(torch.zeros(shape, dtype=dtype, device=device),
40 torch.ones(shape, dtype=dtype, device=device))
---> 41 return torch.empty(shape, dtype=dtype, device=device).normal_()
42
43
RuntimeError: _th_normal_ not supported on CPUType for Long
