code: def hardswish(input: Tensor, scale: float, zero_point: int) -> Tensor:
      r"""This is the quantized version of :func:`~torch.nn.functional.hardswish`.
  
      Args:
          input: quantized input
          scale: quantization scale of the output tensor
          zero_point: quantization zero point of the output tensor
      """
      if not input.is_quantized:
          raise ValueError(
              "Input to 'quantized.hardswish' must be quantized!"
          )
      return torch._ops.ops.quantized.hardswish(
          input, scale, zero_point
      )
  
imports: from typing import List, Optional
  import warnings
  import torch
  from torch import Tensor
  from torch.nn.modules.utils import _pair, _triple
  from torch.jit.annotations import BroadcastingList2
  from .modules.utils import _pair_from_first
label_desc: Use image node_id 15 for calling a global function with example usage: hardswish(input, scale, zero_point) and returns: torch