class_docstr: Simple test for tf.matmul where Tout is different from T.
class_docstr_tok: ["Simple","test","for","tf.matmul","where","Tout","is","different","from","T","."]
code: def testBatchMatMulV3MixedPrec(self):
      # TODO(shivaniagrawal): uint8 is not supported for mixed matmul type in XLA.
      np_bf16 = dtypes.bfloat16.as_numpy_dtype
      a = np.array([[1, 2], [3, 4]], dtype=np.int8)
      b = np.array([[1, 2], [3, 4]], dtype=np_bf16)
      c = math_ops.batch_mat_mul_v3(a, b, adj_y=True, Tout=np_bf16)
      self.assertAllEqual((2, 2), c.shape)
      self.assertAllEqual([[5, 11], [11, 25]], c)
  
imports: import operator
  import numpy
  from tensorflow.python import tf2
  from tensorflow.python.framework import constant_op
  from tensorflow.python.framework import dtypes
  from tensorflow.python.framework import ops
  from tensorflow.python.framework import test_util
  from tensorflow.python.ops import array_ops
  from tensorflow.python.ops import gradient_checker_v2
  from tensorflow.python.ops import math_ops
  from tensorflow.python.platform import test
label_desc: Use image node_id 2 for calling the MatMulMixedType obj's underlying member method code with example usage: obj.testBatchMatMulV3MixedPrec() without return types