assertThat(min(2, 1, reverse)).isEqualTo(2);
    assertThat(max(1, 2, reverse)).isEqualTo(1);
    assertThat(max(2, 1, reverse)).isEqualTo(1);
  }

  /**
   * Fails compilation if the signature of min and max is changed to take {@code Comparator<T>}
   * instead of {@code Comparator<? super T>}.
   */
  public void testMinMaxWithSupertypeComparator() {

should be used with caution when working with untrusted models.

### Saved graphs and checkpoints

When loading untrusted serialized computation graphs (in form of a `GraphDef`,
`SavedModel`, or equivalent on-disk format), the set of computation primitives
available to TensorFlow is powerful enough that you should assume that the
TensorFlow process effectively executes arbitrary code.

            "errorprone",
            project.objects.property<Boolean>()
        ).apply {
            // Enable it only for the main source set by default, as incremental Groovy
            // joint-compilation doesn't work with the Error Prone annotation processor
            enabled.convention(isMainSourceSet)
        }

        if (isMainSourceSet) {

                        classLoader.close();
                    } catch (final IOException closeEx) {
                        logger.warn("Failed to close GroovyClassLoader after compilation failure", closeEx);
                    }
                    throw e;
                }
            });
        } catch (final ExecutionException e) {
            throw (RuntimeException) e.getCause();

    "groups" : [ {
      "testProject" : "largeJavaMultiProject",
      "comment" : "We only test the multi-project here since for the monolithic project we would have no cache hits. This would mean we actually would test incremental compilation.",
      "coverage" : {
        "per_commit" : [ "linux" ]
      }
    } ]
  }, {

                    writer.write(newContent);
                }
            } catch (IOException e) {
                logError("Failed to write to file", e);
                throw e; // Re-throw to ensure the compilation fails
            }
        } else {
            logMessage(Diagnostic.Kind.NOTE, "Content unchanged. Skipping file update.");
        }
    }

    /**

- plugin dependency metadata missing
- plugin dependency metadata retrieval problem
- plugin configuration problem
- plugin execution failure due to something that is known to possibly go wrong (like compilation failure)
- plugin execution error due to something that is not expected to go wrong (the compiler executable missing)
- asking to use a plugin for which you do not have a version defined - tools to easily select versions

      True, ('Would you like to override eigen strong inline for some C++ '
             'compilation to reduce the compilation time?'),
      'Eigen strong inline overridden.', 'Not overriding eigen strong inline, '
      'some compilations could take more than 20 mins.'):
    # Due to a known MSVC compiler issue
    # https://github.com/tensorflow/tensorflow/issues/10521

    work need not make them do so.

  A compilation of a covered work with other separate and independent
works, which are not by their nature extensions of the covered work,
and which are not combined with it such as to form a larger program,
in or on a volume of a storage or distribution medium, is called an
"aggregate" if the compilation and its resulting copyright are not

#ifdef __cplusplus
extern "C" {
#endif

// When `enable` is true, set
// tensorflow.ConfigProto.OptimizerOptions.global_jit_level to ON_1, and also
// set XLA flag values to prepare for XLA compilation. Otherwise set
// global_jit_level to OFF.
//
// This and the next API are syntax sugar over TF_SetConfig(), and is used by
// clients that cannot read/write the tensorflow.ConfigProto proto.