for i := 0; i < b.N; i++ {
					Trim(x[:k], cs[:j])
				}
			})
		}
	}
}

func BenchmarkTrimByte(b *testing.B) {
	x := []byte("  the quick brown fox   ")
	for i := 0; i < b.N; i++ {
		Trim(x, " ")
	}
}

func BenchmarkIndexPeriodic(b *testing.B) {
	key := []byte{1, 1}
	for _, skip := range [...]int{2, 4, 8, 16, 32, 64} {

  }
}

TEST(CAPI, TensorEncodeDecodeStrings) {
  TestEncodeDecode(__LINE__, {});
  TestEncodeDecode(__LINE__, {"hello"});
  TestEncodeDecode(__LINE__,
                   {"the", "quick", "brown", "fox", "jumped", "over"});

  string big(1000, 'a');
  TestEncodeDecode(__LINE__, {"small", big, "small2"});
}

TEST(CAPI, SessionOptions) {
  TF_SessionOptions* opt = TF_NewSessionOptions();

     * cause a concurrent read operation to see inconsistent data. This is made easier by the
     * nature of the read operations in Map. For example, no operation can reveal that the table
     * has grown but the threshold has not yet been updated, so there are no atomicity requirements
     * for this with respect to reads.
     *
     * As a guide, all critical volatile reads and writes to the count field are marked in code