code: def __init__(
      self,
      max_res: int = 224,
      num_bands: int = 64,
      concat_grid=True,
      keep_spatial=False,
  ):
      super().__init__()
      self.max_res = max_res
      self.num_bands = num_bands
      self.concat_grid = concat_grid
      self.keep_spatial = keep_spatial
      self.register_buffer(
          "bands",
          pixel_freq_bands(max_res, num_bands),
          persistent=False,
      )
  
imports: import math
  import warnings
  from collections import OrderedDict
  from typing import List, Optional, Tuple, Union
  import torch
  import torch.nn
  from torch import nn
  from lavis.models.clip_models.utils import freeze_batch_norm_2d
label_desc: Use image node_id 1 to create a new FourierEmbed object from inherited base classes: nn with example: obj = FourierEmbed(max_res, num_bands, concat_grid, keep_spatial)