code: def dawsn(x, name=None):
      """Computes Dawson's integral of `x` element-wise.
  
      Dawson's integral is defined as `exp(-x**2)` times the integral of
      `exp(t**2)` from `0` to `x`, with the domain of definition all real numbers.
  
      Dawson's function is odd.
      >>> tf.math.special.dawsn([-1., -0.5, 0.5, 1.]).numpy()
      array([-0.5380795, -0.4244364, 0.4244364,  0.5380795], dtype=float32)
  
      This implementation is based off of the Cephes math library.
  
      Args:
        x: A `Tensor` or `SparseTensor`. Must be one of the following types:
          `float32`, `float64`.
        name: A name for the operation (optional).
  
      Returns:
        A `Tensor` or `SparseTensor`, respectively. Has the same type as `x`.
  
      @compatibility(scipy)
      Equivalent to scipy.special.dawsn
      @end_compatibility
      """
      with ops.name_scope(name, "dawsn", [x]):
          return gen_special_math_ops.dawsn(x)
  
imports: import collections
  import functools
  import re
  import string
  import numpy
  import opt_einsum
  from tensorflow.compiler.tf2xla.ops import gen_xla_ops
  from tensorflow.python.framework import ops
  from tensorflow.python.framework import tensor
  from tensorflow.python.framework import tensor_shape
  from tensorflow.python.ops import array_ops
  from tensorflow.python.ops import control_flow_ops
  from tensorflow.python.ops import gen_linalg_ops
  from tensorflow.python.ops import gen_special_math_ops
  from tensorflow.python.ops import math_ops
  from tensorflow.python.platform import tf_logging
  from tensorflow.python.util import deprecation
  from tensorflow.python.util import dispatch
  from tensorflow.python.util.tf_export import tf_export
label_desc: Use image node_id 2 for calling a global function with example usage: dawsn(x, name) and returns: gen_special_math_ops