docstr: ivy.Container static method variant of ivy.make_svd_non_negative.
  This method simply wraps the function, and so the docstring for
  ivy.make_svd_non_negative also applies to this method with minimal
  changes.
  
  Parameters
  ----------
  x
      tensor being decomposed.
  U
      left singular matrix from SVD.
  S
      diagonal matrix from SVD.
  V
      right singular matrix from SVD.
  nntype
      whether to fill small values with 0.0 (nndsvd),
      or the tensor mean (nndsvda, default).
  
  [1]: Boutsidis & Gallopoulos. Pattern Recognition, 41(4): 1350-1362, 2008.
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code: def static_make_svd_non_negative(
      x: Union[ivy.Array, ivy.NativeArray, ivy.Container],
      U: Union[ivy.Array, ivy.NativeArray, ivy.Container],
      S: Union[ivy.Array, ivy.NativeArray, ivy.Container],
      V: Union[ivy.Array, ivy.NativeArray, ivy.Container],
      /,
      *,
      nntype: Optional[
          Union[Literal["nndsvd", "nndsvda"], ivy.Container]
      ] = "nndsvd",
      key_chains: Optional[
          Union[List[str], Dict[str, str], ivy.Container]
      ] = None,
      to_apply: Union[bool, ivy.Container] = True,
      prune_unapplied: Union[bool, ivy.Container] = False,
      map_sequences: Union[bool, ivy.Container] = False,
  ) -> Tuple[ivy.Container, ivy.Container]:
      """ivy.Container static method variant of ivy.make_svd_non_negative.
      This method simply wraps the function, and so the docstring for
      ivy.make_svd_non_negative also applies to this method with minimal
      changes.
  
      Parameters
      ----------
      x
          tensor being decomposed.
      U
          left singular matrix from SVD.
      S
          diagonal matrix from SVD.
      V
          right singular matrix from SVD.
      nntype
          whether to fill small values with 0.0 (nndsvd),
          or the tensor mean (nndsvda, default).
  
      [1]: Boutsidis & Gallopoulos. Pattern Recognition, 41(4): 1350-1362, 2008.
      """
      return ContainerBase.cont_multi_map_in_function(
          "make_svd_non_negative",
          x,
          U,
          S,
          V,
          nntype=nntype,
          key_chains=key_chains,
          to_apply=to_apply,
          prune_unapplied=prune_unapplied,
          map_sequences=map_sequences,
      )
  
imports: from typing import Union, Optional, List, Dict, Tuple, Sequence, Literal
  from ivy.data_classes.container.base import ContainerBase
  import ivy
label_desc: Use image node_id 25 for calling the _ContainerWithLinearAlgebraExperimental obj's underlying member method code with example usage: obj.static_make_svd_non_negative() and returns: ContainerBase