code: def testLoadBatchEncodings(
      self, n_files, start_length, end_length, channels=16
  ):
      test_encoding = np.random.randn(start_length, channels)
      # Make temp dir
      test_dir = tf.test.get_temp_dir()
      tf.gfile.MakeDirs(test_dir)
      # Make wav files
      files = []
      for i in range(n_files):
          fname = os.path.join(
              test_dir, "test_embedding_{}.npy".format(i)
          )
          files.append(fname)
          np.save(fname, test_encoding)
      # Load the files
      batch_data = fastgen.load_batch_encodings(
          files, sample_length=end_length
      )
      self.assertEqual(
          batch_data.shape, (n_files, end_length, channels)
      )
  
file_path: magenta/magenta/models/nsynth/wavenet/fastgen_test.py
imports: import os
  from absl.testing import parameterized
  import librosa
  from magenta.models.nsynth.wavenet import fastgen
  import numpy
  import tensorflow.compat.v1
label_desc: Use image node_id 4 for calling the FastegenTest obj's underlying member method code with example usage: obj.testLoadBatchEncodings(n_files, start_length, end_length, channels) without return types