code: def _von_mises_sample_fwd(shape, concentration, seed):
      """Compute output, aux (collaborates with _von_mises_sample_bwd)."""
      samples = _von_mises_sample_no_gradient(
          shape, concentration, seed
      )
      return samples, (concentration, samples)
  
imports: import numpy
  import tensorflow.compat.v2
  from tensorflow_probability.python.bijectors import sigmoid
  from tensorflow_probability.python.bijectors import softplus
  from tensorflow_probability.python.distributions import distribution
  from tensorflow_probability.python.distributions import kullback_leibler
  from tensorflow_probability.python.distributions import normal
  from tensorflow_probability.python.internal import assert_util
  from tensorflow_probability.python.internal import custom_gradient
  from tensorflow_probability.python.internal import distribution_util
  from tensorflow_probability.python.internal import dtype_util
  from tensorflow_probability.python.internal import parameter_properties
  from tensorflow_probability.python.internal import prefer_static
  from tensorflow_probability.python.internal import reparameterization
  from tensorflow_probability.python.internal import samplers
  from tensorflow_probability.python.internal import tensor_util
  from tensorflow_probability.python.internal import tensorshape_util
  from tensorflow_probability.python.math.gradient import value_and_gradient
label_desc: Use image node_id 7 for calling a global function with example usage: _von_mises_sample_fwd(shape, concentration, seed) and returns: samples,  concentration,  samples