code: def convert_to_numpy(x):
      if isinstance(x, tf.SparseTensor):
          x_shape = x.shape
          x = tf.sparse.to_dense(x)
          x.set_shape(x_shape)
      elif isinstance(x, tf.IndexedSlices):
          x = tf.convert_to_tensor(x)
      return np.array(x)
  
imports: import types
  import numpy
  import tensorflow
  from tensorflow.compiler.tf2xla.python.xla import dynamic_update_slice
  from keras.backend.common import KerasVariable
  from keras.backend.common import global_state
  from keras.backend.common import standardize_dtype
  from keras.backend.common.keras_tensor import KerasTensor
  from keras.backend.common.name_scope import name_scope
  from keras.backend.common.stateless_scope import StatelessScope
  from keras.backend.common.stateless_scope import in_stateless_scope
  from keras.utils.naming import auto_name
label_desc: Use image node_id 2 for calling a global function with example usage: convert_to_numpy(x) and returns: np