code: def __init__(
      self, input_dim, dimensions, activation="relu", dropout=0.0
  ):
      super().__init__()
      self.input_dim = input_dim
      self.dimensions = dimensions
      self.activation = activation
      self.dropout = dropout
      self.linears = nn.ModuleList(
          [nn.Linear(input_dim, dimensions[0])]
      )
      for din, dout in zip(dimensions[:-1], dimensions[1:]):
          self.linears.append(nn.Linear(din, dout))
  
imports: import torch
  import torch.nn
  import torch.nn.functional
  from mmf.common.registry import registry
  from mmf.utils.general import get_chunks, get_sizes_list, irfft, rfft
  from mmf.utils.logger import log_class_usage
label_desc: Use image node_id 1 to create a new MLP object from inherited base classes: nn with example: obj = MLP(input_dim, dimensions, activation, dropout)