var tiles []Tile

	// Plan to fetch tiles necessary to recompute tree hash.
	// If it matches, those tiles are authenticated.
	stx := subTreeIndex(0, r.tree.N, nil)
	stxTileOrder := make([]int, len(stx))
	for i, x := range stx {
		tile, _, _ := tileForIndex(h, x)
		tile = tileParent(tile, 0, r.tree.N)
		if j, ok := tileOrder[tile]; ok {
			stxTileOrder[i] = j
			continue
		}

func (r *tileReader) SaveTiles(tiles []tlog.Tile, data [][]byte) {
	c := r.c

	// Determine which tiles need saving.
	// (Tiles that came from the cache need not be saved back.)
	save := make([]bool, len(tiles))
	c.tileSavedMu.Lock()
	for i, tile := range tiles {
		if !c.tileSaved[tile] {
			save[i] = true
			c.tileSaved[tile] = true
		}
	}
	c.tileSavedMu.Unlock()

-color) .uk-heading-medium,.uk-tile-primary:not(.uk-preserve-color) .uk-heading-small,.uk-tile-primary:not(.uk-preserve-color) .uk-heading-xlarge,.uk-tile-primary:not(.uk-preserve-color) h1,.uk-tile-primary:not(.uk-preserve-color) h2,.uk-tile-primary:not(.uk-preserve-color) h3,.uk-tile-primary:not(.uk-preserve-color) h4,.uk-tile-primary:not(.uk-preserve-color) h5,.uk-tile-primary:not(.uk-preserve-color) h6,.uk-tile-secondary:not(.uk-preserve-color) .uk-h1,.uk-tile-secondary:not(.uk-preserve-color)...

	// returning the record ID.
	Lookup(ctx context.Context, m module.Version) (int64, error)

	// ReadTileData reads the content of tile t.
	// It is only invoked for hash tiles (t.L ≥ 0).
	ReadTileData(ctx context.Context, t tlog.Tile) ([]byte, error)
}

// A Server is the checksum database HTTP server,
// which implements http.Handler and should be invoked
// to serve the paths listed in [ServerPaths].

go list -x -m all  # Download go.mod files.
! stderr github
stderr proxy.golang.org/rsc.io/quote
! stderr sum.golang.org/tile
! stderr sum.golang.org/lookup/rsc.io/quote

go list -x -deps rsc.io/quote  # Download module source.
! stderr github
stderr proxy.golang.org/rsc.io/quote
! stderr sum.golang.org/tile
! stderr sum.golang.org/lookup/rsc.io/quote

cmp go.sum saved.sum


# Download again.

                const std::vector<Output>& grad_inputs,
                std::vector<Output>* grad_outputs) {
  if (op.num_inputs() != 2) {
    return errors::InvalidArgument("Tile requires 2 inputs");
  }
  if (grad_inputs.size() != 1) {
    return errors::InvalidArgument("Tile grad requires 1 grad input");
  }

  Shape::Attrs shape_attrs;
  shape_attrs.out_type_ = op.input_type(1);

	if err != nil {
		panic(err)
	}
	s.hashes = append(s.hashes, hashes...)

	return id, nil
}

func (s *TestServer) ReadTileData(ctx context.Context, t tlog.Tile) ([]byte, error) {
	s.mu.Lock()
	defer s.mu.Unlock()

	return tlog.ReadTileData(t, s.hashes)

  }

  return builder->create<mlir::TF::ConcatOp>(
      location, output_type, concat_dimension_op.getOutput(), inputs);
}

// For tile sharded inputs to TPU computation, inject split op between the
// input values and TPU computation so that tiled input values are passed in
// as inputs to TPU computations. If more than one dimension is sharded, then

  %177 = "tf.Reshape"(%176, %9) {device = ""} : (tensor<i32>, tensor<0xi32>) -> tensor<i32>
  %178 = "tf.Pack"(%7, %177) {axis = 0 : i64, device = ""} : (tensor<i32>, tensor<i32>) -> tensor<2xi32>
  %179 = "tf.Tile"(%115, %178) {device = ""} : (tensor<?x1xi64>, tensor<2xi32>) -> tensor<?x?xi64>
  %180 = "tf.Mul"(%177, %118) {device = ""} : (tensor<i32>, tensor<i32>) -> tensor<i32>

  %multiples = "tf.Const"() { device = "/device:CPU:0", value = dense<[7,3]> : tensor<2xi32> } : () -> tensor<2xi32>
  // CHECK: T = !corert.string
  %output = "tf.Tile"(%arg, %multiples) { device = "/device:CPU:0" } : (tensor<1x2x!tf_type.string>, tensor<2xi32>) -> tensor<?x6x!tf_type.string>
  func.return %output : tensor<?x6x!tf_type.string>
}

// CHECK-LABEL: func @shape