After running the train.py, error "Unable to solve the normal equations in LinearFeatureBaseline. The matrix X^T*X (with X the design matrix) is not full-rank, regardless of the regularization (maximum regularization: 1.0)." occurs.

[bianca-li-bupt]

The solution is as below.
In baseline.py line 60:

1. Replace the 'torch.lstsq' with 'torch.linalg.lstsq'. Because the former function was removed.
2. Output coeffs is an instance now, not a tensor. So use coeffs.solution referring to the value.

for _ in range(5):
           try:
               coeffs= torch.linalg.lstsq(XT_y, XT_X + reg_coeff * self._eye, driver='gelsy')
               # coeffs,_ = torch.lstsq(XT_y, XT_X + reg_coeff * self._eye)
               # An extra round of increasing regularization eliminated
               # inf or nan in the least-squares solution most of the time

               if torch.isnan(coeffs.solution).any() or torch.isinf(coeffs.solution).any():
                   raise RuntimeError

               break
           except RuntimeError:
               reg_coeff *= 10
       else:
           raise RuntimeError('Unable to solve the normal equations in '
               '`LinearFeatureBaseline`. The matrix X^T*X (with X the design '
               'matrix) is not full-rank, regardless of the regularization '
               '(maximum regularization: {0}).'.format(reg_coeff))
       self.weight.copy_(coeffs.solution.flatten())