class_docstr: TorchScript implementation of ScriptFloatListSeqTensorizer in pytext/data/tensorizers.py
code: def tensorize(
      self, floatLists: List[List[List[float]]], seq_lens: List[int]
  ) -> Tuple[torch.Tensor, torch.Tensor]:
      floatListTensor = torch.tensor(
          pad_3d_float(
              floatLists, seq_lens=seq_lens, pad_val=self.pad_val
          ),
          dtype=torch.float,
      )
      seqLensTensor = torch.tensor(seq_lens, dtype=torch.long)
      return (floatListTensor, seqLensTensor)
  
imports: from typing import List, Optional, Tuple
  import torch
  from pytext.torchscript.utils import pad_2d_float, pad_3d_float, validate_padding_control
  from pytext.torchscript.vocab import ScriptVocabulary
  from pytorch.text.fb.utils.transform_utils import pad_2d
label_desc: Use image node_id 3 for calling the ScriptFloatListSeqTensorizer obj's underlying member method code with example usage: obj.tensorize(floatLists, seq_lens) and returns: floatListTensor,  seqLensTensor