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Solve the following problem using Python, implementing the functions described below, one line at a time
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Description:
 def cast_like(x, y):
 """Cast x to y's dtype, if necessary."""

  x = tf.convert_to_tensor(x)
  y = tf.convert_to_tensor(y)

  if x.dtype.base_dtype == y.dtype.base_dtype:
    return x

  cast_x = tf.cast(x, y.dtype)
  if cast_x.device != x.device:
    x_name = "(eager Tensor)"
    try:
      x_name = x.name
    except AttributeError:
      pass
    tf.logging.warning("Cast for %s may induce copy from '%s' to '%s'", x_name,
                       x.device, cast_x.device)
  return cast_x