python-3.x - 如何解决将 GPyTorch 与 SpectralMixture Kernel 一起使用时遇到的错误？

Question

我正在使用 GPyTorch 来拟合高斯过程回归模型（主要用于学习过程）。在遵循他们的教程时，我正在尝试使用SpectralMixtureKernel. 但是，我收到以下错误。但首先是代码（与他们的教程基本相同，但为方便起见，在此处复制）：

class ExactGPModel(gpytorch.models.ExactGP):
    def __init__(self,train_x,train_y,likelihood):
        super(ExactGPModel, self).__init__(train_x,train_y,likelihood)
        self.mean_module = gpytorch.means.ConstantMean()

        self.covar_module = gpytorch.kernels.SpectralMixtureKernel(num_mixtures=4)

        self.covar_module.initialize_from_data(train_x, train_y)



    def forward(self,x):
        mean_x = self.mean_module(x)
        covar_x = self.covar_module(x)
        return gpytorch.distributions.MultivariateNormal(mean_x,covar_x)

熊猫数据框转换为torch.tensor以下

train_x = torch.tensor(train_x.values.astype(np.float32))
train_y = torch.tensor(train_y.values.astype(np.float32))

test_x = torch.tensor(test_x.values.astype(np.float32))
test_y = torch.tensor(test_y.values.astype(np.float32))

然后

likelihood = gpytorch.likelihoods.GaussianLikelihood()

model = ExactGPModel(train_x,train_y, likelihood)

运行最后一行后，我收到以下错误：

Traceback (most recent call last):

  File "<ipython-input-195-e3bc37af324c>", line 1, in <module>
    model = ExactGPModel(train_x,train_y, likelihood)

  File "<ipython-input-186-323eff9c5819>", line 7, in __init__
    self.covar_module.initialize_from_data(train_x, train_y)

  File "/anaconda3/envs/py36/lib/python3.6/site-packages/gpytorch/kernels/spectral_mixture_kernel.py", line 163, in initialize_from_data
    self.raw_mixture_scales.data.normal_().mul_(max_dist).abs_().pow_(-1)

RuntimeError: output with shape [4, 1, 1] doesn't match the broadcast shape [4, 1, 33]

任何解决此问题的帮助将不胜感激。

谢谢。

标签： python-3.xdata-sciencegaussian