class_docstr: Interface between a MXNet model and a Thinc Model. This container is
  *not* a Thinc Model subclass itself.
class_docstr_tok: ["Interface","between","a","MXNet","model","and","a","Thinc","Model",".","This","container","is","*","not","*","a","Thinc","Model","subclass","itself","."]
docstr: Pass inputs through to the underlying MXNet model, and return the
  output. No conversions are performed. The MXNet model is set into
  evaluation mode.
docstr_tok: ["Pass","inputs","through","to","the","underlying","MXNet","model",",","and","return","the","output",".","No","conversions","are","performed",".","The","MXNet","model","is","set","into","evaluation","mode","."]
code: def predict(self, inputs: ArgsKwargs) -> Any:
      """Pass inputs through to the underlying MXNet model, and return the
      output. No conversions are performed. The MXNet model is set into
      evaluation mode.
      """
      mx.autograd.set_training(train_mode=False)
      with mx.autograd.pause():
          outputs = self._model(*inputs.args, **inputs.kwargs)
      mx.autograd.set_training(train_mode=True)
      return outputs
  
file_path: thinc/thinc/shims/mxnet.py
imports: import copy
  from typing import Any, cast
  import srsly
  from ..compat import mxnet
  from ..optimizers import Optimizer
  from ..types import ArgsKwargs, FloatsXd
  from ..util import convert_recursive, get_array_module, make_tempfile, mxnet2xp, xp2mxnet
  from .shim import Shim
label_desc: Use image node_id 2 for calling the MXNetShim obj's underlying member method code with example usage: obj.predict(inputs) and returns: outputs