### Major Features and Improvements

*   Add `is_cpu_target_available`, which indicates whether or not TensorFlow was built with support for a given CPU target. This can be useful for skipping target-specific tests if a target is not supported.

*   `tf.data`

continue } k, v, _ := strings.Cut(line, " = ") switch k { case "GCD": GCD = v case "A": A = v case "B": B = v case "LCM": LCM = v t.Run(fmt.Sprintf("line %d", lineNum), func(t *testing.T) { if A == "0" || B == "0" { t.Skip("skipping test with zero input") } if LCM == "1" { t.Skip("skipping test with LCM=1") } p, _ := bigmod.NewModulus(addOne(decodeHex(t, A))) a, _ := bigmod.NewNat().SetBytes(decodeHex(t, A), p) q, _ := bigmod.NewModulus(addOne(decodeHex(t, B))) b, _ := bigmod.NewNat().SetBytes(decodeHex(t,...