code: def test_pass_with_batched_input_features(self):
      input_features = BatchFeature(
          {
              "input_features": torch.rand((220, 70, 512)).type(
                  torch.float32
              ),
              "beatsteps": torch.randint(
                  size=(5, 955), low=0, high=100
              ).type(torch.float32),
              "extrapolated_beatstep": torch.randint(
                  size=(5, 900), low=0, high=100
              ).type(torch.float32),
              "attention_mask": torch.concatenate(
                  [
                      torch.ones([120, 70], dtype=torch.int32),
                      torch.zeros([1, 70], dtype=torch.int32),
                      torch.ones([50, 70], dtype=torch.int32),
                      torch.zeros([1, 70], dtype=torch.int32),
                      torch.ones([47, 70], dtype=torch.int32),
                      torch.zeros([1, 70], dtype=torch.int32),
                  ],
                  axis=0,
              ),
              "attention_mask_beatsteps": torch.ones((5, 955)).type(
                  torch.int32
              ),
              "attention_mask_extrapolated_beatstep": torch.ones(
                  (5, 900)
              ).type(torch.int32),
          }
      )
      model = Pop2PianoForConditionalGeneration.from_pretrained(
          "sweetcocoa/pop2piano"
      )
      model_opts = model.generate(
          input_features=input_features["input_features"],
          attention_mask=input_features["attention_mask"],
          return_dict_in_generate=True,
      )
  
      self.assertEqual(model_opts.sequences.ndim, 2)
  
imports: import copy
  import tempfile
  import unittest
  import numpy
  from datasets import load_dataset
  from transformers import Pop2PianoConfig
  from transformers.feature_extraction_utils import BatchFeature
  from transformers.testing_utils import require_essentia, require_librosa, require_onnx, require_scipy, require_torch, slow, torch_device
  from transformers.utils import is_essentia_available, is_librosa_available, is_scipy_available, is_torch_available
  from ...generation.test_utils import GenerationTesterMixin
  from ...test_configuration_common import ConfigTester
  from ...test_modeling_common import ModelTesterMixin, ids_tensor
  from ...test_pipeline_mixin import PipelineTesterMixin
label_desc: Use image node_id 18 for calling the Pop2PianoModelTest obj's underlying member method code with example usage: obj.test_pass_with_batched_input_features() without return types