code: def __init__(
      self,
      dtype,
      size=None,
      dynamic_size=None,
      clear_after_read=None,
      tensor_array_name=None,
      handle=None,
      flow=None,
      infer_shape=True,
      element_shape=None,
      colocate_with_first_write_call=True,
      name=None,
  ):
      del (flow, tensor_array_name, name)
      self._handle = None
      self._flow = tf_frontend.constant(0, dtype=tf_frontend.int32)
      self._infer_shape = infer_shape
      self._element_shape = (
          ivy.Shape(element_shape)
          if element_shape is not None
          else element_shape
      )
      self._colocate_with_first_write_call = (
          colocate_with_first_write_call
      )
      self._dtype = tf_frontend.as_dtype(dtype)
      self._dynamic_size = dynamic_size or False
      self._clear_after_read = (
          True if clear_after_read is None else clear_after_read
      )
      self._previously_read_indices = []
  
      if isinstance(size, EagerTensor):
          size = size.ivy_array
      self._tensor_array = [None for _ in range(size)]
      self._parent = weakref.ref(self)
  
imports: import weakref
  import ivy
  import ivy.functional.frontends.tensorflow
  from ivy.functional.frontends.tensorflow import EagerTensor
label_desc: Use image node_id 1 to create a new TensorArray object  with example: obj = TensorArray(dtype, size, dynamic_size, clear_after_read, tensor_array_name, handle, flow, infer_shape, element_shape, colocate_with_first_write_call, name)