}

  /**
   * Anonymous cipher suites were disabled in OpenJDK because they're rarely used and permit
   * man-in-the-middle attacks. https://bugs.openjdk.java.net/browse/JDK-8212823
   */
  @Test
  fun anonCipherSuiteUnsupported() {
    platform.assumeNotConscrypt()
    platform.assumeNotBouncyCastle()

  }
}

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();

     * 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.
     *

     * 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.
     *

        layers and happens to work before TF 2.4. These will explicitly be
        unsupported now. Converting these ops to Functional API op layers was
        unreliable before TF 2.4, and prone to erroring incomprehensibly or
        being silently buggy.
    *   Code that directly asserts on a Keras symbolic value in cases where ops
        like `tf.rank` used to return a static or symbolic value depending on if