}
            );

            this.resize();
            suggestor = this;
            $(window).resize(function() {
              suggestor.resize();
            });

            $("body").append($boxElement);
          },

          suggest: function() {
            suggestingSts = true;

            this.resize();

            var suggestor = this;

      newDelegate.addAll(delegate);
      this.table = newDelegate;
      return;
    }
    int size = this.size;
    if (size < requireEntries().length) {
      resizeEntries(size);
    }
    int minimumTableSize = CompactHashing.tableSize(size);
    int mask = hashTableMask();
    if (minimumTableSize < mask) { // smaller table size will always be less than current mask

      newDelegate.addAll(delegate);
      this.table = newDelegate;
      return;
    }
    int size = this.size;
    if (size < requireEntries().length) {
      resizeEntries(size);
    }
    int minimumTableSize = CompactHashing.tableSize(size);
    int mask = hashTableMask();
    if (minimumTableSize < mask) { // smaller table size will always be less than current mask

  std::vector<int64_t>* shape_arr = &tf_dlm_tensor_ctx->shape;
  std::vector<int64_t>* stride_arr = &tf_dlm_tensor_ctx->strides;
  shape_arr->resize(ndim);
  stride_arr->resize(ndim, 1);
  for (int i = 0; i < ndim; i++) {
    (*shape_arr)[i] = tensor->dim_size(i);
  }
  for (int i = ndim - 2; i >= 0; --i) {
    (*stride_arr)[i] = (*shape_arr)[i + 1] * (*stride_arr)[i + 1];
  }

set FESS_MIN_MEM=256m
)

if "%FESS_MAX_MEM%" == "" (
set FESS_MAX_MEM=1g
)

if NOT "%FESS_HEAP_SIZE%" == "" (
set FESS_MIN_MEM=%FESS_HEAP_SIZE%
set FESS_MAX_MEM=%FESS_HEAP_SIZE%
)

REM min and max heap sizes should be set to the same value to avoid
REM stop-the-world GC pauses during resize, and so that we can lock the
REM heap in memory on startup to prevent any of it from being swapped
REM out.

    }
    int size = this.size;
    if (size < requireEntries().length) {
      resizeEntries(size);
    }
    int minimumTableSize = CompactHashing.tableSize(size);
    int mask = hashTableMask();
    if (minimumTableSize < mask) { // smaller table size will always be less than current mask
      resizeTable(mask, minimumTableSize, UNSET, UNSET);
    }
  }

  @Override
  public void clear() {

    }
    int retvals = outputs.size() - null_indices.size();
    std::vector<AbstractTensorHandle*> fn_outputs(retvals);
    TF_RETURN_IF_ERROR(fn_op->Execute(
        absl::Span<AbstractTensorHandle*>(fn_outputs.data(), fn_outputs.size()),
        &retvals));
    int skipped_indices = 0;
    for (int i = 0; i < outputs.size(); i++) {
      if (!null_indices.contains(i)) {

  private static final int ENDPOINT = -2;

  /**
   * Contains the link pointers corresponding with the entries, in the range of [0, size()). The
   * high 32 bits of each long is the "prev" pointer, whereas the low 32 bits is the "succ" pointer
   * (pointing to the next entry in the linked list). The pointers in [size(), entries.length) are
   * all "null" (UNSET).
   *

    int size = this.size;
    if (size < requireEntries().length) {
      resizeEntries(size);
    }
    int minimumTableSize = CompactHashing.tableSize(size);
    int mask = hashTableMask();
    if (minimumTableSize < mask) { // smaller table size will always be less than current mask
      resizeTable(mask, minimumTableSize, UNSET, UNSET);
    }
  }

  @Override
  public void clear() {
    if (needsAllocArrays()) {

  private static final int ENDPOINT = -2;

  /**
   * Contains the link pointers corresponding with the entries, in the range of [0, size()). The
   * high 32 bits of each long is the "prev" pointer, whereas the low 32 bits is the "succ" pointer
   * (pointing to the next entry in the linked list). The pointers in [size(), entries.length) are
   * all "null" (UNSET).
   *