import org.gradle.api.internal.artifacts.ivyservice.resolveengine.artifact.ResolvedArtifactSet
import org.gradle.api.internal.attributes.ImmutableAttributes
import org.gradle.internal.Deferrable
import org.gradle.internal.Try
import org.gradle.internal.component.external.model.ImmutableCapabilities
import org.gradle.internal.model.CalculatedValue
import org.gradle.internal.operations.BuildOperation

    }

    @Override
    public boolean getSupportsPluginManagementBlock() {
        return supportsPluginManagementBlock;
    }

    @Override
    public void addConfiguration(Runnable runnable, boolean deferrable) {
        throw new UnsupportedOperationException();
    }

import org.gradle.api.internal.file.FileCollectionFactory;
import org.gradle.api.internal.project.ProjectInternal;
import org.gradle.api.internal.project.ProjectStateRegistry;
import org.gradle.cache.Cache;
import org.gradle.internal.Deferrable;
import org.gradle.internal.Try;
import org.gradle.internal.buildoption.InternalOptions;
import org.gradle.internal.buildoption.StringInternalOption;
import org.gradle.internal.execution.ExecutionEngine;

        # because:
        # - tensorflow/python/_pywrap_mlir.so already depends on LLVM anyway
        # - tensorflow/python/_pywrap_mlir.so always loaded as part of python
        #   binding
        # TODO: It might be still preferrable to place graph_optimization_pass
        # as part of the libtensorflow_framework.so, as it is the central
        # place for core related components.

</li>
</ul>

<p>
In all other cases, a (possibly partial) type argument list must be present.
If a type argument list is absent or partial, all missing type arguments
must be inferrable from the context in which the function is used.
</p>

<pre>
// sum returns the sum (concatenation, for strings) of its arguments.
func sum[T ~int | ~float64 | ~string](x... T) T { … }