class_docstr: Base class for any swiglu operator in :attr:`xformers.ops.swiglu`
class_docstr_tok: ["Base","class","for","any","swiglu","operator","in",":","attr",":","`","xformers.ops.swiglu","`"]
code: def __init__(self, op, packed_weights: bool, name: str, constraints):
      self.NAME = name
      self.PACKED_WEIGHTS = packed_weights
      self.op = op
      self.constraints = constraints
  
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 to create a new SwiGLUOp object  with example: obj = SwiGLUOp(op, packed_weights, name, constraints)