class_docstr: Parses features in the TFDS NSynth dataset.
  
  If running on Cloud, it is recommended you set `data_dir` to
  'gs://tfds-data/datasets' to avoid unnecessary downloads.
class_docstr_tok: ["Parses","features","in","the","TFDS","NSynth","dataset",".","If","running","on","Cloud",",","it","is","recommended","you","set","`","data_dir","`","to","'gs",":","\/\/tfds-data\/datasets","'","to","avoid","unnecessary","downloads","."]
docstr: TfdsProvider constructor.
  
  Args:
    name: TFDS dataset name (with optional config and version).
    split: Dataset split to use of the TFDS dataset.
    data_dir: The directory to read the prepared NSynth dataset from. Defaults
      to the public TFDS GCS bucket.
    sample_rate: Sample rate of audio in the dataset.
    frame_rate: Frame rate of features in the dataset.
    include_note_labels: Return dataset without note-level labels
      (pitch, instrument).
code: def __init__(
      self,
      name="nsynth/gansynth_subset.f0_and_loudness:2.3.0",
      split="train",
      data_dir="gs://tfds-data/datasets",
      sample_rate=16000,
      frame_rate=250,
      include_note_labels=True,
  ):
      """TfdsProvider constructor.
  
      Args:
        name: TFDS dataset name (with optional config and version).
        split: Dataset split to use of the TFDS dataset.
        data_dir: The directory to read the prepared NSynth dataset from. Defaults
          to the public TFDS GCS bucket.
        sample_rate: Sample rate of audio in the dataset.
        frame_rate: Frame rate of features in the dataset.
        include_note_labels: Return dataset without note-level labels
          (pitch, instrument).
      """
      self._include_note_labels = include_note_labels
      if data_dir == "gs://tfds-data/datasets":
          logging.warning(
              "Using public TFDS GCS bucket to load NSynth. If not running on "
              "GCP, this will be very slow, and it is recommended you prepare "
              "the dataset locally with TFDS and set the data_dir appropriately."
          )
      super().__init__(name, split, data_dir, sample_rate, frame_rate)
  
imports: import os
  from absl import logging
  from ddsp.spectral_ops import CREPE_FRAME_SIZE
  from ddsp.spectral_ops import CREPE_SAMPLE_RATE
  from ddsp.spectral_ops import get_framed_lengths
  import gin
  import tensorflow.compat.v2
  import tensorflow_datasets
label_desc: Use image node_id 1 to create a new NSynthTfds object from inherited base classes: TfdsProvider with example: obj = NSynthTfds(name, split, data_dir, sample_rate, frame_rate, include_note_labels)