code: def prob_mask_like(t, prob):
      batch, seq_length, _ = t.shape
      return (
          torch.zeros((batch, seq_length)).float().uniform_(0, 1) < prob
      )
  
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 2 for calling a global function with example usage: prob_mask_like(t, prob) and returns: unknown