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 testBatchMatMulV3OutputType(self):
      # TODO(shivaniagrawal): uint8 is not supported for mixed matmul type in XLA.
      for a_dtype, b_dtype in [
          (np.int8, np.int8),
          (np.uint8, np.uint8),
      ]:
          a = np.array([[1, 2], [3, 4]], dtype=a_dtype)
          b = np.array([[1, 2], [3, 4]], dtype=b_dtype)
          c = math_ops.batch_mat_mul_v3(a, b, adj_y=True, Tout=np.int32)
          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 1 for calling the MatMulMixedType obj's underlying member method code with example usage: obj.testBatchMatMulV3OutputType() without return types