class_docstr: Dispatcher to automatically select
  the best operator in :attr:`xformers.ops.swiglu`
class_docstr_tok: ["Dispatcher","to","automatically","select","the","best","operator","in",":","attr",":","`","xformers.ops.swiglu","`"]
docstr: Computes the best operator
  
  Returns:
      SwiGLUOp: The best operator for the configuration
docstr_tok: ["Computes","the","best","operator","Returns",":","SwiGLUOp",":","The","best","operator","for","the","configuration"]
code: def op(self) -> SwiGLUOp:
      """Computes the best operator
  
      Returns:
          SwiGLUOp: The best operator for the configuration
      """
      priorities: Sequence[SwiGLUOp] = [
          SwiGLUPackedFusedOp,
          SwiGLUFusedOp,
      ]
      for op in priorities:
          if op.supports(self):
              return op
      return SwiGLUEagerOp
  
imports: from dataclasses import dataclass
  from typing import Dict, Optional, Sequence, Tuple, Union
  import torch
  import torch.nn.functional
  from torch import nn
  from .common import BaseOperator, get_xformers_operator, register_operator
  from .unbind import stack_or_none, unbind
label_desc: Use image node_id 1 for calling the SwiGLUOpDispatch obj's underlying member method code with example usage: obj.op() and returns: SwiGLUEagerOp, op