lengths_vector.push_back(v.size());
        }
        TFE_OpSetAttrStringList(op, attr_name, values_vector.data(),
                                lengths_vector.data(), s_size);
      }

      // Int
      if (const int i_size = default_value.list().i_size()) {
        absl::InlinedVector<int64_t, 4> i_vector;
        i_vector.reserve(i_size);
        for (int i = 0; i < i_size; ++i) {

	s = 1 + 8
	if z.Disable == nil {
		s += msgp.NilSize
	} else {
		s += msgp.BoolSize
	}
	s += 6
	if z.Batch == nil {
		s += msgp.NilSize
	} else {
		s += msgp.IntSize
	}
	s += 9
	if z.InMemory == nil {
		s += msgp.NilSize
	} else {
		s += msgp.BoolSize
	}
	s += 9
	if z.Compress == nil {
		s += msgp.NilSize
	} else {
		s += msgp.BoolSize
	}

	err = syscall.Statfs(path, &s)
	if err != nil {
		return Info{}, err
	}
	reservedBlocks := uint64(s.F_bfree) - uint64(s.F_bavail)
	info = Info{
		Total:  uint64(s.F_bsize) * (uint64(s.F_blocks) - reservedBlocks),
		Free:   uint64(s.F_bsize) * uint64(s.F_bavail),
		Files:  uint64(s.F_files),
		Ffree:  uint64(s.F_ffree),
		FSType: getFSType(s.F_fstypename[:]),
	}
	if info.Free > info.Total {

		v, ok := tagsMap[k]
		if !ok || v != cv {
			mismatch = true
			break
		}
	}
	return !mismatch
}

// BySize returns true if sz satisfies one of ObjectSizeGreaterThan,
// ObjectSizeLessThan predicates or a combination of them via And.
func (f Filter) BySize(sz int64) bool {
	if f.ObjectSizeGreaterThan > 0 &&
		sz <= f.ObjectSizeGreaterThan {
		return false
	}
	if f.ObjectSizeLessThan > 0 &&

  DCHECK(tf_results->missing_unused_key_names_data.empty());

  size_t size = results.missing_unused_input_map_keys.size();
  tf_results->missing_unused_key_names.resize(size);
  tf_results->missing_unused_key_indexes.resize(size);

  for (int i = 0; i < size; ++i) {
    TensorId id = results.missing_unused_input_map_keys[i];
    tf_results->missing_unused_key_names_data.emplace_back(id.first);
    tf_results->missing_unused_key_names[i] =

  for (int device_index = 0; device_index < underlying_devices_.size();
       ++device_index) {
    DeviceThread* device_thread = device_threads_[device_index].get();
    std::vector<TFE_TensorHandle*> device_inputs;
    device_inputs.reserve(inputs.size());
    for (int input_index = 0; input_index < inputs.size(); ++input_index) {
      // Parallel tensors are divided between operations by device.

    }

    static class TestSubSearcher extends RankFusionSearcher {

        private int mainSize;
        private int inSize;
        private int outSize;

        TestSubSearcher(int mainSize, int inSize, int outSize) {
            this.mainSize = mainSize;
            this.inSize = inSize;
            this.outSize = outSize;
        }

        @Override

				err = z.Metadata[za0002].DecodeMsg(dc)
				if err != nil {
					err = msgp.WrapError(err, "Metadata", za0002)
					return
				}
			}
		case "Size":
			err = z.Size.DecodeMsg(dc)
			if err != nil {
				err = msgp.WrapError(err, "Size")
				return
			}
		case "Type":
			z.Type, err = dc.ReadString()
			if err != nil {
				err = msgp.WrapError(err, "Type")
				return
			}

else if (unit === 'vh' || unit === 'vw') {\n    // if is a vh or vw, we calculate the size based on the viewport\n    let size;\n    if (unit === 'vh') {\n      size = Math.max(\n        document.documentElement.clientHeight,\n        window.innerHeight || 0\n      );\n    } else {\n      size = Math.max(\n        document.documentElement.clientWidth,\n        window.innerWidth || 0\n      );\n    }\n    return size / 100 * value;\n  } else {\n    // if is an explicit pixel unit, we get rid of the unit...

	// if object upload fails stop the test.
	if err != nil {
		t.Fatalf("Error uploading object: <ERROR> %v", err)
	}

	// initialize httptest Recorder, this records any mutations to response writer inside the handler.
	rec := httptest.NewRecorder()
	// construct HTTP request for DELETE bucket.