code: def forward(ctx, loc, scale_tril, shape):
      white = torch.randn(shape, dtype=loc.dtype, device=loc.device)
      z = torch.matmul(white, scale_tril.t())
      ctx.save_for_backward(z, white, scale_tril)
      return loc + z
  
file_path: pyro/pyro/distributions/omt_mvn.py
imports: import torch
  from torch.autograd import Function
  from torch.autograd.function import once_differentiable
  from torch.distributions import constraints
  from pyro.distributions.torch import MultivariateNormal
  from pyro.distributions.util import eye_like, sum_leftmost
label_desc: Use image node_id 1 for calling the _OMTMVNSample obj's underlying member method code with example usage: obj.forward(ctx, loc, scale_tril, shape) and returns: unknown