What is the PyTorch equivalent of TensorFlow’s MultivariateNormalDiag distribution? Specifically, I have a B x N x D mean tensor and B x N x D variance tensor where B is batch size, N is number of data points, D is the dimension of each data point. I want to create a multi-variate normal distribution with diagonal covariance from these tensors. How can this be implemented ?

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Does that mean that

```
import tensorflow as tf
import torch
D = torch.distributions
tf.MultivariateNormalDiag(...) == D.Independent(D.Normal(...))
```

Also from computational efficiency perspective?