import org.gradle.api.artifacts.transform.TransformAction
            import org.gradle.api.artifacts.transform.TransformOutputs
            import org.gradle.api.artifacts.transform.TransformParameters
            import org.gradle.api.file.FileSystemLocation
            import org.gradle.api.provider.Provider

            abstract class FileSizer implements TransformAction<TransformParameters.None> {
                FileSizer() {

        projectDir.file("build.gradle") << resolveTask << """
            import org.gradle.api.artifacts.transform.TransformParameters
        """ << declareAttributes() << """
            abstract class FileSizer implements TransformAction<TransformParameters.None> {
                @PathSensitive(PathSensitivity.NAME_ONLY)
                @InputArtifact
                abstract Provider<FileSystemLocation> getInputArtifact()

See the License for the specific language governing permissions and
limitations under the License.
==============================================================================*/

// This transformation pass takes operations in TensorFlowLite dialect and
// optimizes them to resulting operations in TensorFlowLite dialect.

#include <algorithm>
#include <array>
#include <climits>
#include <cstddef>

            ClosingFunction<? super V, U> transformation, @ParametricNullness V input)
            throws Exception {
      // TODO(dpb): Consider ways to defer closing without creating a separate CloseableList.
      CloseableList newCloseables = new CloseableList();
      try {
        return immediateFuture(transformation.apply(newCloseables.closer, input));
      } finally {

            ClosingFunction<? super V, U> transformation, @ParametricNullness V input)
            throws Exception {
      // TODO(dpb): Consider ways to defer closing without creating a separate CloseableList.
      CloseableList newCloseables = new CloseableList();
      try {
        return immediateFuture(transformation.apply(newCloseables.closer, input));
      } finally {

  let summary = "Convert unified compilation and replication attributes back to legacy attributes.";

  let description = [{
    This transformation pass converts unified compilation and replication
    attributes (`_replication_info` and `_xla_compile_device_type`) into legacy
    attributes. This ensures the unified attributes do not get exposed outside

    return new TransformedEntriesNavigableMap<>(fromMap, transformer);
  }

  /**
   * A transformation of the value of a key-value pair, using both key and value as inputs. To apply
   * the transformation to a map, use {@link Maps#transformEntries(Map, EntryTransformer)}.
   *
   * @param <K> the key type of the input and output entries

    return new TransformedEntriesNavigableMap<>(fromMap, transformer);
  }

  /**
   * A transformation of the value of a key-value pair, using both key and value as inputs. To apply
   * the transformation to a map, use {@link Maps#transformEntries(Map, EntryTransformer)}.
   *
   * @param <K> the key type of the input and output entries

  /** @prop {Boolean} enabled=true - Whether the modifier is enabled or not */\n    enabled: true,\n    /** @prop {ModifierFn} */\n    fn: computeStyle,\n    /**\n     * @prop {Boolean} gpuAcceleration=true\n     * If true, it uses the CSS 3D transformation to position the popper.\n     * Otherwise, it will use the `top` and `left` properties\n     */\n    gpuAcceleration: true,\n    /**\n     * @prop {string} [x='bottom']\n     * Where to anchor the X axis (`bottom` or `top`). AKA X offset origin.\n...

        /*value=*/constant_op.getValue());
  }
}

// Creates a new `tfl.qconst` op for the bias. The bias values are 0s, because
// this bias a dummy bias (note that bias fusion is not considered for this
// transformation). The quantization scale for the bias is input scale *
// filter scale. `filter_const_op` is used to retrieve the filter scales and
// the size of the bias constant.
TFL::QConstOp CreateTflConstOpForDummyBias(