code: def _vec(x):
      # Vec takes in a (batch) of matrices of shape B1 + [n, k] and returns
      # a (batch) of vectors of shape B1 + [n * k].
      return tf.reshape(x, ps.concat([ps.shape(x)[:-2], [-1]], axis=0))
  
imports: import functools
  import tensorflow.compat.v2
  from tensorflow_probability.python.distributions import cholesky_util
  from tensorflow_probability.python.distributions import distribution
  from tensorflow_probability.python.distributions import mvn_linear_operator
  from tensorflow_probability.python.distributions.internal import stochastic_process_util
  from tensorflow_probability.python.experimental.linalg import linear_operator_unitary
  from tensorflow_probability.python.experimental.psd_kernels import multitask_kernel
  from tensorflow_probability.python.internal import batch_shape_lib
  from tensorflow_probability.python.internal import distribution_util
  from tensorflow_probability.python.internal import dtype_util
  from tensorflow_probability.python.internal import nest_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 tensor_util
  from tensorflow_probability.python.internal import tensorshape_util
  from tensorflow.python.util import nest
label_desc: Use image node_id 1 for calling a global function with example usage: _vec(x) and returns: tf