code: def __init__(
      self,
      parent,
      batch_size=13,
      patch_size=2,
      max_length=24,
      num_mel_bins=16,
      is_training=True,
      use_labels=True,
      hidden_size=32,
      num_hidden_layers=2,
      num_attention_heads=4,
      intermediate_size=37,
      hidden_act="gelu",
      hidden_dropout_prob=0.1,
      attention_probs_dropout_prob=0.1,
      type_sequence_label_size=10,
      initializer_range=0.02,
      scope=None,
      frequency_stride=2,
      time_stride=2,
  ):
      self.parent = parent
      self.batch_size = batch_size
      self.patch_size = patch_size
      self.max_length = max_length
      self.num_mel_bins = num_mel_bins
      self.is_training = is_training
      self.use_labels = use_labels
      self.hidden_size = hidden_size
      self.num_hidden_layers = num_hidden_layers
      self.num_attention_heads = num_attention_heads
      self.intermediate_size = intermediate_size
      self.hidden_act = hidden_act
      self.hidden_dropout_prob = hidden_dropout_prob
      self.attention_probs_dropout_prob = attention_probs_dropout_prob
      self.type_sequence_label_size = type_sequence_label_size
      self.initializer_range = initializer_range
      self.scope = scope
      self.frequency_stride = frequency_stride
      self.time_stride = time_stride
  
      # in AST, the seq length equals the number of patches + 2 (we add 2 for the [CLS] and distillation tokens)
      frequency_out_dimension = (
          self.num_mel_bins - self.patch_size
      ) // self.frequency_stride + 1
      time_out_dimension = (
          self.max_length - self.patch_size
      ) // self.time_stride + 1
      num_patches = frequency_out_dimension * time_out_dimension
      self.seq_length = num_patches + 2
  
imports: import inspect
  import unittest
  from huggingface_hub import hf_hub_download
  from transformers import ASTConfig
  from transformers.testing_utils import require_torch, require_torchaudio, slow, torch_device
  from transformers.utils import cached_property, is_torch_available, is_torchaudio_available
  from ...test_configuration_common import ConfigTester
  from ...test_modeling_common import ModelTesterMixin, floats_tensor, ids_tensor
  from ...test_pipeline_mixin import PipelineTesterMixin
label_desc: Use image node_id 1 to create a new ASTModelTester object  with example: obj = ASTModelTester(parent, batch_size, patch_size, max_length, num_mel_bins, is_training, use_labels, hidden_size, num_hidden_layers, num_attention_heads, intermediate_size, hidden_act, hidden_dropout_prob, attention_probs_dropout_prob, type_sequence_label_size, initializer_range, scope, frequency_stride, time_stride)