code: def test_tensorflow_wrapper_keras_subclass_decorator_capture_args_kwargs(
      X, Y, input_size, n_classes, answer
  ):
      import tensorflow as tf
  
      @keras_subclass(
          "TestModel",
          X=numpy.array([0.0, 0.0]),
          Y=numpy.array([0.5]),
          input_shape=(2,),
      )
      class TestModel(tf.keras.Model):
          def __init__(self, custom=False, **kwargs):
              super().__init__(self)
              # This is to force the mode to pass the captured arguments
              # or fail.
              assert custom is True
              assert kwargs.get("other", None) is not None
  
          def call(self, inputs):
              return inputs
  
      # Can wrap an decorated keras subclass model
      model = TensorFlowWrapper(TestModel(True, other=1337))
  
      assert hasattr(model.shims[0]._model, "eg_args")
      args_kwargs = model.shims[0]._model.eg_args
      assert True in args_kwargs.args
      assert "other" in args_kwargs.kwargs
  
      # Raises an error if the args/kwargs is not serializable
      obj = {}
      obj["key"] = obj
      with pytest.raises(ValueError):
          TensorFlowWrapper(TestModel(True, other=obj))
  
      # Provides the same arguments when copying a capture model
      model = model.from_bytes(model.to_bytes())
  
imports: import numpy
  import pytest
  from thinc.api import Adam, ArgsKwargs, Linear, Model, TensorFlowWrapper, get_current_ops, keras_subclass, tensorflow2xp, xp2tensorflow
  from thinc.compat import has_cupy_gpu, has_tensorflow
  from thinc.util import to_categorical
  from ..util import check_input_converters, make_tempdir
label_desc: Use image node_id 18 for calling a global function with example usage: test_tensorflow_wrapper_keras_subclass_decorator_capture_args_kwargs(X, Y, input_size, n_classes, answer) and returns: inputs