class_docstr: Instrument based filter and mapper provider.
docstr: Load waveform for given sample.
docstr_tok: ["Load","waveform","for","given","sample","."]
code: def load_waveform(self, sample: Dict) -> Dict:
      """Load waveform for given sample."""
      return dict(
          sample,
          **self._parent._audio_adapter.load_waveform(
              sample[f"{self._instrument}_path"],
              offset=sample["start"],
              duration=self._parent._chunk_duration,
              sample_rate=self._parent._sample_rate,
              waveform_name="waveform",
          ),
      )
  
imports: import os
  import time
  from os.path import exists
  from os.path import sep
  from typing import Any, Dict, List, Optional, Tuple
  import tensorflow
  from .audio.adapter import AudioAdapter
  from .audio.convertor import db_uint_spectrogram_to_gain, spectrogram_to_db_uint
  from .audio.spectrogram import compute_spectrogram_tf, random_pitch_shift, random_time_stretch
  from .utils.logging import logger
  from .utils.tensor import check_tensor_shape, dataset_from_csv, set_tensor_shape, sync_apply
label_desc: Use image node_id 2 for calling the InstrumentDatasetBuilder obj's underlying member method code with example usage: obj.load_waveform(sample) and returns: dict