code: def _randomDiag(
      self, n, batch_shape, low, high, forcemin=None, seed=42
  ):
      np.random.seed(seed)
      shape = batch_shape + [n]
      diag = np.random.uniform(low, high, size=shape)
      if forcemin:
          assert forcemin < low
          diag = np.where(
              diag == np.min(diag, axis=-1)[..., np.newaxis],
              forcemin,
              diag,
          )
      return diag
  
file_path: probability/tensorflow_probability/python/experimental/linalg/no_pivot_ldl_test.py
imports: import numpy
  import tensorflow.compat.v2
  from tensorflow_probability.python.experimental.linalg.no_pivot_ldl import no_pivot_ldl
  from tensorflow_probability.python.experimental.linalg.no_pivot_ldl import simple_robustified_cholesky
  from tensorflow_probability.python.internal import test_util
label_desc: Use image node_id 1 for calling the NoPivotLDLTest obj's underlying member method code with example usage: obj._randomDiag(n, batch_shape, low, high, forcemin, seed) and returns: diag