let description = [{
This operation computes

    # Scalar indices
    ref[indices, ...] = max(ref[indices, ...], updates[...])

    # Vector indices (for each i)
    ref[indices[i], ...] = max(ref[indices[i], ...], updates[i, ...])

    # High rank indices (for each i, ..., j)
    ref[indices[i, ..., j], ...] = max(ref[indices[i, ..., j], ...], updates[i, ..., j, ...])

public final class ProjectIndex {

    private final Map<String, MavenProject> projects;

    private final Map<String, Integer> indices;

    public ProjectIndex(List<MavenProject> projects) {
        this.projects = new HashMap<>(projects.size() * 2);
        this.indices = new HashMap<>(projects.size() * 2);

        for (int i = 0; i < projects.size(); i++) {
            MavenProject project = projects.get(i);

  auto indices = Const(scope_, {{0, 0}, {1, 1}});
  TensorShape y_shape({2});
  auto y = GatherNd(scope_, x, indices);
  RunTest(x, x_shape, y, y_shape);
}

TEST_F(ArrayGradTest, GatherNdGrad_SliceIndexing) {
  TensorShape shape({2, 2});
  auto x = Placeholder(scope_, DT_FLOAT, Placeholder::Shape(shape));
  auto indices = Const(scope_, {{1}, {0}});

                         std::vector<Output>* grad_outputs) {
  // Running example:
  // indices = {2, [1, 0]}
  // data = {[d_1, d_2], [[d_3, d_4], [d_5, d_6]]}
  // out = [[d_5, d_6], [d_3, d_4], [d_1, d_2]]
  // grad = [[g_1, g_2], [g_3, g_4], [g_5, g_6]]

  // indices and data are two equal-sized lists passed
  // into DynamicStitch.
  // num_values = 2

import java.util.List;

import org.codelibs.fess.suggest.settings.AnalyzerSettings;
import org.codelibs.fess.suggest.settings.SuggestSettings;
import org.opensearch.action.admin.indices.analyze.AnalyzeAction;
import org.opensearch.action.admin.indices.analyze.AnalyzeAction.AnalyzeToken;
import org.opensearch.client.Client;
import org.opensearch.core.common.Strings;

import com.ibm.icu.text.Transliterator;

// CHECK-NEXT: tfrt.return [[out_chain]], [[res]] : !tfrt.chain, !tfrt_fallback.tf_tensor
func.func @gather(%indices: tensor<?xi32>,
             %resource: tensor<*x!tf_type.resource>) -> tensor<*xi32> {
  %0 = "tf.ResourceGather"(%resource, %indices) {batch_dims = 0 : i64, device = "/device:CPU:0", validate_indices = true}: (tensor<*x!tf_type.resource>, tensor<?xi32>) -> (tensor<*xi32>)

    indices = rewriter.create<mhlo::ReshapeOp>(parent_op->getLoc(),
                                               indices_type, indices);
  } else if (index_vector_dim != indices_type.getRank() - 1) {
    // If index_vector_dim isn't the last dimension in indices then it isn't
    // supported yet.
    // TODO(tberghammer): Transpose indices to support this usecase.

	_ = a[:10:10]
	_ = a[:11 /* ERRORx `index .* out of bounds` */ :10]
	_ = a[:10:11 /* ERRORx `index .* out of bounds` */ ]
	_ = a[10:0 /* ERROR "invalid slice indices" */ :10]
	_ = a[0:10:0 /* ERROR "invalid slice indices" */ ]
	_ = a[10:0 /* ERROR "invalid slice indices" */:0]
	_ = &a /* ERROR "cannot take address" */ [:10]

	pa := &a
	_ = pa[9]
	_ = pa[10 /* ERRORx `index .* out of bounds` */ ]

def LegalizeGather: Pat<
  (TF_GatherOp $params, $indices, $ignored_validate_indices),
  (TFL_GatherOp $params, $indices, ConstantAttr<I32Attr, "0">,
     ConstantAttr<I32Attr, "0">)>;

def LegalizeGatherNd : Pat<(TF_GatherNdOp $params, $indices, $bad_indices_policy),
                           (TFL_GatherNdOp $params, $indices)>;

def LegalizeGatherV2 : Pat<
  (TF_GatherV2Op $params, $indices, (Arith_ConstantOp ElementsAttr:$axis), $batch_dims),

  // CHECK-NOT: tf.HashTableV2
  // CHECK-NOT: tf.LookupTableSizeV2
  // CHECK-DAG: [[v0:%.*]] = "tf._TfrtGetResource"() <{container = [""], indices = [[[handle_id]]], shared_name = [{{.*}}]}> {device = "/job:localhost/replica:0/task:0/device:CPU:0"}
  // CHECK-DAG: [[v1:%.*]] = "tf._TfrtGetResource"() <{container = [""], indices = [[[size_id]]], shared_name = [{{.*}}]}> {device = "/job:localhost/replica:0/task:0/device:CPU:0"}