class_docstr: Tests the correctness of the Y = X @ X.T transformation.
class_docstr_tok: ["Tests","the","correctness","of","the","Y","=","X","@","X.T","transformation","."]
code: def testBatchStatic(self):
      x = np.array(
          [[[1.0, 0], [2, 1]], [[3.0, 0], [1, 2]]]
      )  # np.linalg.cholesky(y)
      y = np.array(
          [[[1.0, 2], [2, 5]], [[9.0, 3], [3, 5]]]
      )  # np.matmul(x, x.T)
      y_actual = cholesky_outer_product.CholeskyOuterProduct().forward(
          x=x
      )
      x_actual = cholesky_outer_product.CholeskyOuterProduct().inverse(
          y=y
      )
      [y_actual_, x_actual_] = self.evaluate([y_actual, x_actual])
      self.assertEqual([2, 2, 2], y_actual.shape)
      self.assertEqual([2, 2, 2], x_actual.shape)
      self.assertAllClose(y, y_actual_)
      self.assertAllClose(x, x_actual_)
  
file_path: probability/tensorflow_probability/python/bijectors/cholesky_outer_product_test.py
imports: import numpy
  import tensorflow.compat.v1
  import tensorflow.compat.v2
  from tensorflow_probability.python.bijectors import cholesky_outer_product
  from tensorflow_probability.python.internal import test_util
label_desc: Use image node_id 7 for calling the CholeskyOuterProductBijectorTest obj's underlying member method code with example usage: obj.testBatchStatic() without return types