code: def _svd(tensor, full_matrices=False, compute_uv=True, name=None):
      del name
      ret = np.linalg.svd(
          tensor, full_matrices=full_matrices, compute_uv=compute_uv
      )
      if compute_uv:
          u, s, vh = ret
          # Batched matrix transpose.
          return s, u, np.conj(np.swapaxes(vh, -2, -1))
      return ret
  
imports: import collections
  import functools
  import numpy
  from tensorflow_probability.python.internal.backend.numpy import _utils
  from tensorflow_probability.python.internal.backend.numpy import ops
label_desc: Use image node_id 20 for calling a global function with example usage: _svd(tensor, full_matrices, compute_uv, name) and returns: ret, s,  u,  np