code: def create_wrapped_tensorflow(width, dropout, nI, nO):
      from tensorflow.keras.layers import Dense, Dropout
      from tensorflow.keras.models import Sequential
  
      tf_model = Sequential()
      tf_model.add(Dense(width, activation="relu", input_shape=(nI,)))
      tf_model.add(Dropout(dropout))
      tf_model.add(Dense(width, activation="relu"))
      tf_model.add(Dropout(dropout))
      tf_model.add(Dense(nO, activation=None))
      return TensorFlowWrapper(tf_model)
  
file_path: thinc/thinc/tests/layers/test_mnist.py
imports: import pytest
  from thinc.api import Adam, PyTorchWrapper, Relu, Softmax, TensorFlowWrapper, chain, clone, get_current_ops
  from thinc.compat import has_tensorflow, has_torch
label_desc: Use image node_id 4 for calling a global function with example usage: create_wrapped_tensorflow(width, dropout, nI, nO) and returns: TensorFlowWrapper