class_docstr: Pad `samples` by adding padding by chunks of size `seq_len`
class_docstr_tok: ["Pad","`","samples","`","by","adding","padding","by","chunks","of","size","`","seq_len","`"]
docstr: Set `self.max_len` before encodes
docstr_tok: ["Set","`","self.max_len","`","before","encodes"]
code: def before_call(self, b):
      "Set `self.max_len` before encodes"
      self.max_len = max(
          [
              x.shape[0]
              for xs in b
              for x in xs
              if isinstance(x, TensorText)
          ]
      )
  
imports: from __future__ import annotations
  from ..torch_basics import *
  from ..data.all import *
  from .core import *
label_desc: Use image node_id 2 for calling the Pad_Chunk obj's underlying member method code with example usage: obj.before_call(b) without return types