class_docstr: LabelEncoder over string data types.
  When the ONNX backend is selected, this operator only works for PyTorch => 1.8.0.
code: def forward(self, x):
      x = x.view(-1, 1, self.max_word_length)
      result = torch.prod(self.condition_tensors == x, dim=2).nonzero(
          as_tuple=True
      )[1]
      assert (
          result.shape[0] == x.shape[0]
      ), "x ({}) contains previously unseen labels. condition_tensors: {}".format(
          x, self.condition_tensors
      )
      return result
  
file_path: hummingbird/hummingbird/ml/operator_converters/_label_encoder_implementations.py
imports: import torch
  import numpy
  from ._physical_operator import PhysicalOperator
  from .None import constants
label_desc: Use image node_id 2 for calling the StringLabelEncoder obj's underlying member method code with example usage: obj.forward(x) and returns: result