code: def test_tensorflow_wrapper_convert_inputs(data, n_args, kwargs_keys):
      import tensorflow as tf
  
      keras_model = tf.keras.Sequential(
          [tf.keras.layers.Dense(12, input_shape=(12,))]
      )
      model = TensorFlowWrapper(keras_model)
      convert_inputs = model.attrs["convert_inputs"]
      Y, backprop = convert_inputs(model, data, is_train=True)
      check_input_converters(
          Y, backprop, data, n_args, kwargs_keys, tf.Tensor
      )
  
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 27 for calling a global function with example usage: test_tensorflow_wrapper_convert_inputs(data, n_args, kwargs_keys) without return types