class_docstr: Container for TorchScript models mirroring Sklearn transformers API.
class_docstr_tok: ["Container","for","TorchScript","models","mirroring","Sklearn","transformers","API","."]
code: def transform(self, *inputs):
      device = get_device(self.model)
      f = super(TorchScriptSklearnContainerTransformer, self)._transform
      f_wrapped = lambda x: _torchscript_wrapper(
          device, f, x, extra_config=self._extra_config
      )  # noqa: E731
  
      return self._run(f_wrapped, *inputs)
  
imports: import pickle
  import os
  import numpy
  import shutil
  import torch
  import warnings
  import hummingbird
  from hummingbird.ml._utils import pandas_installed, get_device, from_strings_to_ints, dump_versions, check_dumped_versions
  from hummingbird.ml.operator_converters import constants
  from hummingbird.ml.containers._sklearn_api_containers import SklearnContainer, SklearnContainerTransformer, SklearnContainerRegression, SklearnContainerClassification, SklearnContainerAnomalyDetection
label_desc: Use image node_id 1 for calling the TorchScriptSklearnContainerTransformer obj's underlying member method code with example usage: obj.transform() and returns: self