code: def testSolveBatchBroadcastLargerBatches(self):
      # 1 x 10 x 10
      matrix = np.random.uniform(low=1, high=2.0, size=[1, 10, 10])
      # 10 x 1
      rhs = np.random.uniform(size=[10, 1])
      # 1 x 10 x 1
      self._verifySolveAllWaysReal(matrix, rhs)
  
      # 2 x 10 x 10
      matrix = np.random.uniform(low=1, high=2.0, size=[2, 10, 10])
      # 10 x 1
      rhs = np.random.uniform(size=[10, 1])
      # 2 x 10 x 1
      self._verifySolveAllWaysReal(matrix, rhs)
  
      # 2 x 257 x 257
      matrix = np.random.uniform(low=1, high=2.0, size=[2, 257, 257])
      # Also ensure the matrix is well conditioned by making it diagonally
      # dominant.
      np.fill_diagonal(matrix[0, ...], 257 * 2)
      np.fill_diagonal(matrix[1, ...], 257 * 2)
      # 257 x 1
      rhs = np.random.uniform(size=[257, 1])
      # 2 x 257 x 1
      self._verifySolveAllWaysReal(matrix, rhs)
  
imports: import numpy
  from tensorflow.python.framework import test_util
  from tensorflow.python.ops import array_ops
  from tensorflow.python.ops import linalg_ops
  from tensorflow.python.platform import test
label_desc: Use image node_id 9 for calling the MatrixTriangularSolveOpTest obj's underlying member method code with example usage: obj.testSolveBatchBroadcastLargerBatches() without return types