rightmost dimensions to treat as dependent.
class torch.distributions.transforms.LowerCholeskyTransform(cache_size=0)
Transform from unconstrained matrices to lower-triangular matrices
   with nonnegative diagonal entries.
This is useful for parameterizing positive definite matrices in
   terms of their Cholesky factorization.
class torch.distributions.transforms.PositiveDefiniteTransform(cache_size=0)
Transform from unconstrained matrices to positive-definite
   matrices.
class torch.distributions.transforms.PowerTransform(exponent, cache_size=0)
Transform via the mapping y = x^{\text{exponent}}.
class torch.distributions.transforms.ReshapeTransform(in_shape, out_shape, cache_size=0)
Unit Jacobian transform to reshape the rightmost part of a tensor.
Note that "in_shape" and "out_shape" must have the same number of
   elements, just as for "torch.Tensor.reshape()".
Parameters:
      * in_shape (torch.Size) -- The input event shape.