* You may obtain a copy of the License at
 *
 * http://www.apache.org/licenses/LICENSE-2.0
 *
 * Unless required by applicable law or agreed to in writing, software
 * distributed under the License is distributed on an "AS IS" BASIS,
 * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
 * See the License for the specific language governing permissions and
 * limitations under the License.
 */

    model: CIBuildModel,
    stage: Stage,
) : OsAwareBaseGradleBuildType(os = Os.LINUX, stage = stage, init = {
        id(buildTypeId(model))
        name = "Build-logic checks"
        description = "Run check on all build-logic builds"

        features {
            publishBuildStatusToGithub(model)
        }

        applyDefaults(
            model,
            this,
            "checkBuildLogic",

# This file contains SHAs of changes that should be ignored when e.g.
# running `git blame` on a file. Do not edit any of the existing commits.
#
# Use this file by running:
#
#     git blame --ignore-revs-file=.git-blame-ignore-rev <file>
#
# or by configuring `blame.ignoreRevsFile`. The latter ought to also work
# with IDEs such as IntelliJ.


# Format snapshot / restore directories in server
1afe4b914301a23fa37c41c78185b7575a431cc4

 * You may obtain a copy of the License at
 *
 * http://www.apache.org/licenses/LICENSE-2.0
 *
 * Unless required by applicable law or agreed to in writing, software
 * distributed under the License is distributed on an "AS IS" BASIS,
 * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
 * See the License for the specific language governing permissions and
 * limitations under the License.
 */

)

# To avoid duplication, check that the C++ or python library does not depend on
# the stream executor cuda plugins. Targets that want to use cuda APIs should
# instead depend on the dummy plugins in //tensorflow/compiler/xla/tsl/platform/default/build_config
# and use header only targets.
# TODO(ddunleavy): This seems completely broken. :tensorflow_cc depends on
# cuda_platform from tf_additional_binary_deps and this doesn't break.

 * You may obtain a copy of the License at
 *
 * http://www.apache.org/licenses/LICENSE-2.0
 *
 * Unless required by applicable law or agreed to in writing, software
 * distributed under the License is distributed on an "AS IS" BASIS,
 * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
 * See the License for the specific language governing permissions and
 * limitations under the License.
 */

 * Note that each chaining method returns a new ordering instance which is backed by the previous
 * instance, but has the chance to act on values <i>before</i> handing off to that backing instance.
 * As a result, it usually helps to read chained ordering expressions <i>backwards</i>. For example,
 * when {@code compare} is called on the above ordering:
 *
 * <ol>
 *   <li>First, if only one {@code Foo} is null, that null value is treated as <i>greater</i>

  @Retention(RetentionPolicy.RUNTIME)
  @Target(ElementType.METHOD)
  @Keep
  @interface TestSubtype {
    /** Suppresses the assertion on {@link TypeToken#getSubtype}. */
    boolean suppressGetSubtype() default false;

    /** Suppresses the assertion on {@link TypeToken#getSupertype}. */
    boolean suppressGetSupertype() default false;
  }

  private @Nullable Method method = null;

 * You may obtain a copy of the License at
 *
 *     http://www.apache.org/licenses/LICENSE-2.0
 *
 * Unless required by applicable law or agreed to in writing, software
 * distributed under the License is distributed on an "AS IS" BASIS,
 * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND,
 * either express or implied. See the License for the specific language
 * governing permissions and limitations under the License.
 */

   open, and any responsibility can be carried by a contributor who demonstrates the required
   capacity and competence.

 * **Be considerate**: People use our work, and we depend on the work of others. Consider users and
   colleagues before taking action. For example, changes to code, infrastructure, policy, and
   documentation may negatively impact others.