code: def __init__(
      self,
      patch_size,
      channels,
      output_channel_bits,
      max_pixel_val,
      mean,
      std,
  ):
      super().__init__()
      self.patch_size = patch_size
      self.channels = channels
      self.output_channel_bits = output_channel_bits
      self.max_pixel_val = max_pixel_val
  
      self.mean = torch.tensor(mean).view(-1, 1, 1) if mean else None
      self.std = torch.tensor(std).view(-1, 1, 1) if std else None
  
file_path: vit-pytorch/vit_pytorch/mpp.py
imports: import math
  import torch
  from torch import nn
  import torch.nn.functional
  from einops import rearrange, repeat, reduce
label_desc: Use image node_id 1 to create a new MPPLoss object from inherited base classes: nn with example: obj = MPPLoss(patch_size, channels, output_channel_bits, max_pixel_val, mean, std)