code: def is_adapter_available(self) -> bool:
      return any(
          [
              conformer_layer.is_adapter_available()
              for conformer_layer in self.layers
          ]
      )
  
imports: import math
  from collections import OrderedDict
  from typing import List, Optional, Set
  import torch
  import torch.distributed
  import torch.nn
  from omegaconf import DictConfig
  from nemo.collections.asr.parts.submodules.multi_head_attention import PositionalEncoding, RelPositionalEncoding
  from nemo.collections.asr.parts.submodules.squeezeformer_modules import SqueezeformerLayer
  from nemo.collections.asr.parts.submodules.subsampling import ConvSubsampling, StackingSubsampling, TimeReductionModule
  from nemo.collections.asr.parts.utils import adapter_utils
  from nemo.core.classes.common import typecheck
  from nemo.core.classes.exportable import Exportable
  from nemo.core.classes.mixins import AccessMixin, adapter_mixins
  from nemo.core.classes.module import NeuralModule
  from nemo.core.neural_types import AcousticEncodedRepresentation, LengthsType, NeuralType, SpectrogramType
label_desc: Use image node_id 2 for calling the SqueezeformerEncoderAdapter obj's underlying member method code with example usage: obj.is_adapter_available() and returns: any