class_docstr: A class representing a tensor, which could have arbitrary dimensions.
  A batch of these tensors are padded to the max dimension length in the batch
  for each dimension.
class_docstr_tok: ["A","class","representing","a","tensor",",","which","could","have","arbitrary","dimensions",".","A","batch","of","these","tensors","are","padded","to","the","max","dimension","length","in","the","batch","for","each","dimension","."]
code: def __len__(self):
      return 1 if len(self.tensor.size()) <= 0 else self.tensor.size(0)
  
file_path: allennlp/allennlp/data/fields/tensor_field.py
imports: from typing import Dict, Any, Union, Optional
  import torch
  import numpy
  from allennlp.data.fields.field import Field
  from allennlp.common.util import JsonDict
label_desc: Use image node_id 6 for calling the TensorField obj's underlying member method code with example usage: obj.__len__() and returns: unknown