code: def to_numpy(
      x: Union[tf.Tensor, tf.Variable], /, *, copy: bool = True
  ) -> np.ndarray:
      # TensorFlow fails to convert bfloat16 tensor when it has 0 dimensions
      if (
          ivy.is_array(x)
          and get_num_dims(x) == 0
          and ivy.as_native_dtype(x.dtype) is tf.bfloat16
      ):
          x = tf.expand_dims(x, 0)
          if copy:
              return np.squeeze(np.array(tf.convert_to_tensor(x)), 0)
          else:
              return np.squeeze(np.asarray(tf.convert_to_tensor(x)), 0)
      if copy:
          return np.array(tf.convert_to_tensor(x))
      else:
          return np.asarray(tf.convert_to_tensor(x))
  
imports: from typing import Optional, Union, Sequence, Callable, Tuple
  import numpy
  import multiprocessing
  from numbers import Number
  import tensorflow
  import ivy
  from ivy.functional.ivy.gradients import _is_variable
  from ivy.func_wrapper import with_unsupported_dtypes
  from ivy.utils.exceptions import _check_inplace_update_support
  from .None import backend_version
  from ...ivy.general import _broadcast_to
label_desc: Use image node_id 7 for calling a global function with example usage: to_numpy() and returns: np, np, np, np