From dbda817c1011f269cccf427eeeab44f7aac3dc8a Mon Sep 17 00:00:00 2001 From: Adam Roberts Date: Tue, 30 Apr 2019 17:57:07 -0700 Subject: [PATCH] Add Groove to TFDS. Take 2 PiperOrigin-RevId: 246058528 --- setup.py | 1 + tensorflow_datasets/audio/__init__.py | 1 + tensorflow_datasets/audio/groove.py | 246 ++++++++++++++++++ tensorflow_datasets/audio/groove_test.py | 67 +++++ tensorflow_datasets/core/lazy_imports.py | 5 + tensorflow_datasets/core/lazy_imports_test.py | 1 + .../session1/23_jazz_120_beat_4-4.mid | Bin 0 -> 727 bytes .../session1/23_jazz_120_beat_4-4.wav | Bin 0 -> 709494 bytes .../session1/44_rock_120_beat_4-4.mid | Bin 0 -> 271 bytes .../session1/44_rock_120_beat_4-4.wav | Bin 0 -> 355288 bytes .../drummer7/session1/3_rock_86_fill_4-4.mid | Bin 0 -> 467 bytes .../drummer7/session1/3_rock_86_fill_4-4.wav | Bin 0 -> 1234392 bytes .../session2/116_jazz-fusion_96_fill_4-4.mid | Bin 0 -> 305 bytes .../test_data/fake_examples/groove/info.csv | 5 + tensorflow_datasets/url_checksums/groove.txt | 2 + 15 files changed, 328 insertions(+) create mode 100644 tensorflow_datasets/audio/groove.py create mode 100644 tensorflow_datasets/audio/groove_test.py create mode 100644 tensorflow_datasets/testing/test_data/fake_examples/groove/drummer3/session1/23_jazz_120_beat_4-4.mid create mode 100644 tensorflow_datasets/testing/test_data/fake_examples/groove/drummer3/session1/23_jazz_120_beat_4-4.wav create mode 100644 tensorflow_datasets/testing/test_data/fake_examples/groove/drummer3/session1/44_rock_120_beat_4-4.mid create mode 100644 tensorflow_datasets/testing/test_data/fake_examples/groove/drummer3/session1/44_rock_120_beat_4-4.wav create mode 100644 tensorflow_datasets/testing/test_data/fake_examples/groove/drummer7/session1/3_rock_86_fill_4-4.mid create mode 100644 tensorflow_datasets/testing/test_data/fake_examples/groove/drummer7/session1/3_rock_86_fill_4-4.wav create mode 100644 tensorflow_datasets/testing/test_data/fake_examples/groove/drummer7/session2/116_jazz-fusion_96_fill_4-4.mid create mode 100644 tensorflow_datasets/testing/test_data/fake_examples/groove/info.csv create mode 100644 tensorflow_datasets/url_checksums/groove.txt diff --git a/setup.py b/setup.py index 79cf225a631..2a086a3fb1f 100644 --- a/setup.py +++ b/setup.py @@ -93,6 +93,7 @@ 'scikit-image', 'scipy' ], + 'groove': ['pretty_midi', 'pydub'], 'librispeech': ['pydub'], # and ffmpeg installed 'svhn': ['scipy'], 'wikipedia': ['mwparserfromhell', 'apache_beam'], diff --git a/tensorflow_datasets/audio/__init__.py b/tensorflow_datasets/audio/__init__.py index 38085a67af0..d7b339b5999 100644 --- a/tensorflow_datasets/audio/__init__.py +++ b/tensorflow_datasets/audio/__init__.py @@ -15,6 +15,7 @@ """Audio datasets.""" +from tensorflow_datasets.audio.groove import Groove from tensorflow_datasets.audio.librispeech import Librispeech from tensorflow_datasets.audio.librispeech import LibrispeechConfig from tensorflow_datasets.audio.nsynth import Nsynth diff --git a/tensorflow_datasets/audio/groove.py b/tensorflow_datasets/audio/groove.py new file mode 100644 index 00000000000..1f0ec882d19 --- /dev/null +++ b/tensorflow_datasets/audio/groove.py @@ -0,0 +1,246 @@ +# coding=utf-8 +# Copyright 2019 The TensorFlow Datasets Authors. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + +"""Groove Midi Dataset (GMD).""" + +from __future__ import absolute_import +from __future__ import division +from __future__ import print_function + +import collections +import copy +import csv +import io +import os + +from absl import logging +import numpy as np +import tensorflow as tf +import tensorflow_datasets.public_api as tfds + +_DESCRIPTION = """\ +The Groove MIDI Dataset (GMD) is composed of 13.6 hours of aligned MIDI and +(synthesized) audio of human-performed, tempo-aligned expressive drumming +captured on a Roland TD-11 V-Drum electronic drum kit. +""" + +_CITATION = """ +@inproceedings{groove2019, + Author = {Jon Gillick and Adam Roberts and Jesse Engel and Douglas Eck and David Bamman}, + Title = {Learning to Groove with Inverse Sequence Transformations}, + Booktitle = {International Conference on Machine Learning (ICML)} + Year = {2019}, +} +""" + +_PRIMARY_STYLES = [ + "afrobeat", "afrocuban", "blues", "country", "dance", "funk", "gospel", + "highlife", "hiphop", "jazz", "latin", "middleeastern", "neworleans", "pop", + "punk", "reggae", "rock", "soul"] + +_TIME_SIGNATURES = ["3-4", "4-4", "5-4", "5-8", "6-8"] + +_DOWNLOAD_URL = "https://storage.googleapis.com/magentadata/datasets/groove/groove-v1.0.0.zip" +_DOWNLOAD_URL_MIDI_ONLY = "https://storage.googleapis.com/magentadata/datasets/groove/groove-v1.0.0-midionly.zip" + + +class GrooveConfig(tfds.core.BuilderConfig): + """BuilderConfig for Groove Dataset.""" + + def __init__(self, split_bars=None, include_audio=True, audio_rate=16000, + **kwargs): + """Constructs a GrooveConfig. + + Args: + split_bars: int, number of bars to include per example using a sliding + window across the raw data, or will not split if None. + include_audio: bool, whether to include audio in the examples. If True, + examples with missing audio will be excluded. + audio_rate: int, sample rate to use for audio. + **kwargs: keyword arguments forwarded to super. + """ + name_parts = [("%dbar" % split_bars) if split_bars else "full"] + if include_audio: + name_parts.append("%dhz" % audio_rate) + else: + name_parts.append("midionly") + + super(GrooveConfig, self).__init__(name="-".join(name_parts), **kwargs) + self.split_bars = split_bars + self.include_audio = include_audio + self.audio_rate = audio_rate + + +class Groove(tfds.core.GeneratorBasedBuilder): + """The Groove MIDI Dataset (GMD) of drum performances.""" + + BUILDER_CONFIGS = [ + GrooveConfig( + include_audio=False, + version="1.0.0", + description="Groove dataset without audio, unsplit." + ), + GrooveConfig( + include_audio=True, + version="1.0.0", + description="Groove dataset with audio, unsplit." + ), + GrooveConfig( + include_audio=False, + split_bars=2, + version="1.0.0", + description="Groove dataset without audio, split into 2-bar chunks." + ), + GrooveConfig( + include_audio=True, + split_bars=2, + version="1.0.0", + description="Groove dataset with audio, split into 2-bar chunks." + ), + GrooveConfig( + include_audio=False, + split_bars=4, + version="1.0.0", + description="Groove dataset without audio, split into 4-bar chunks." + ), + ] + + def _info(self): + features_dict = { + "id": tf.string, + "drummer": + tfds.features.ClassLabel( + names=["drummer%d" % i for i in range(1, 11)]), + "type": tfds.features.ClassLabel(names=["beat", "fill"]), + "bpm": tf.int32, + "time_signature": tfds.features.ClassLabel(names=_TIME_SIGNATURES), + "style": { + "primary": tfds.features.ClassLabel(names=_PRIMARY_STYLES), + "secondary": tf.string, + }, + "midi": tf.string + } + if self.builder_config.include_audio: + features_dict["audio"] = tfds.features.Tensor( + shape=[None], dtype=tf.float32) + return tfds.core.DatasetInfo( + builder=self, + description=_DESCRIPTION, + features=tfds.features.FeaturesDict(features_dict), + urls=["https://g.co/magenta/groove-dataset"], + citation=_CITATION, + ) + + def _split_generators(self, dl_manager): + """Returns splits.""" + # Download data. + data_dir = os.path.join( + dl_manager.download_and_extract( + _DOWNLOAD_URL if self._builder_config.include_audio else + _DOWNLOAD_URL_MIDI_ONLY), + "groove") + + rows = collections.defaultdict(list) + with tf.io.gfile.GFile(os.path.join(data_dir, "info.csv")) as f: + reader = csv.DictReader(f) + for row in reader: + rows[row["split"]].append(row) + + return [ + tfds.core.SplitGenerator( # pylint: disable=g-complex-comprehension + name=split, + num_shards=10 if split == "train" else 1, + gen_kwargs={"rows": split_rows, "data_dir": data_dir}) + for split, split_rows in rows.items()] + + def _generate_examples(self, rows, data_dir): + split_bars = self._builder_config.split_bars + for row in rows: + split_genre = row["style"].split("/") + with tf.io.gfile.GFile( + os.path.join(data_dir, row["midi_filename"]), "rb") as midi_f: + midi = midi_f.read() + audio = None + if self._builder_config.include_audio: + if not row["audio_filename"]: + # Skip examples with no audio. + logging.warning("Skipping example with no audio: %s", row["id"]) + continue + wav_path = os.path.join(data_dir, row["audio_filename"]) + audio = _load_wav(wav_path, self._builder_config.audio_rate) + + example = { + "id": row["id"], + "drummer": row["drummer"], + "type": row["beat_type"], + "bpm": int(row["bpm"]), + "time_signature": row["time_signature"], + "style": { + "primary": split_genre[0], + "secondary": split_genre[1] if len(split_genre) == 2 else "" + }, + } + if not split_bars: + # Yield full example. + example["midi"] = midi + if audio is not None: + example["audio"] = audio + yield example + else: + # Yield split examples. + bpm = int(row["bpm"]) + beats_per_bar = int(row["time_signature"].split("-")[0]) + bar_duration = 60 / bpm * beats_per_bar + audio_rate = self._builder_config.audio_rate + + pm = tfds.core.lazy_imports.pretty_midi.PrettyMIDI(io.BytesIO(midi)) + total_duration = pm.get_end_time() + + # Pad final bar if at least half filled. + total_bars = int(round(total_duration / bar_duration)) + total_frames = int(total_bars * bar_duration * audio_rate) + if audio is not None and len(audio) < total_frames: + audio = np.pad(audio, [0, total_frames - len(audio)], "constant") + + for i in range(total_bars - split_bars + 1): + time_range = [i * bar_duration, (i + split_bars) * bar_duration] + + # Split MIDI. + pm_split = copy.deepcopy(pm) + pm_split.adjust_times(time_range, [0, split_bars * bar_duration]) + pm_split.time_signature_changes = pm.time_signature_changes + midi_split = io.BytesIO() + pm_split.write(midi_split) + example["midi"] = midi_split.getvalue() + + # Split audio. + if audio is not None: + example["audio"] = audio[ + int(time_range[0] * audio_rate): + int(time_range[1] * audio_rate)] + + example["id"] += ":%03d" % i + yield example + + +def _load_wav(path, sample_rate): + with tf.io.gfile.GFile(path, "rb") as audio_f: + audio_segment = tfds.core.lazy_imports.pydub.AudioSegment.from_file( + audio_f, format="wav").set_channels(1).set_frame_rate(sample_rate) + audio = np.array(audio_segment.get_array_of_samples()).astype(np.float32) + # Convert from int to float representation. + audio /= 2**(8 * audio_segment.sample_width) + return audio + diff --git a/tensorflow_datasets/audio/groove_test.py b/tensorflow_datasets/audio/groove_test.py new file mode 100644 index 00000000000..c7fbb99d625 --- /dev/null +++ b/tensorflow_datasets/audio/groove_test.py @@ -0,0 +1,67 @@ +# coding=utf-8 +# Copyright 2019 The TensorFlow Datasets Authors. +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + +"""Tests for Groove dataset module.""" + +from __future__ import absolute_import +from __future__ import division +from __future__ import print_function + +from tensorflow_datasets import testing +from tensorflow_datasets.audio import groove + + +class GrooveFullTest(testing.DatasetBuilderTestCase): + DATASET_CLASS = groove.Groove + BUILDER_CONFIG_NAMES_TO_TEST = ["full-16000hz"] + SPLITS = { + "train": 2, + "test": 1, + } + DL_EXTRACT_RESULT = ".." + + +class GrooveFullMidiOnlyTest(testing.DatasetBuilderTestCase): + DATASET_CLASS = groove.Groove + BUILDER_CONFIG_NAMES_TO_TEST = ["full-midionly"] + SPLITS = { + "train": 3, + "test": 1, + } + DL_EXTRACT_RESULT = ".." + + +class Groove2BarTest(testing.DatasetBuilderTestCase): + DATASET_CLASS = groove.Groove + BUILDER_CONFIG_NAMES_TO_TEST = ["2bar-16000hz"] + SPLITS = { + "train": 5, # 3, 2 + "test": 1, + } + DL_EXTRACT_RESULT = ".." + + +class Groove2BarMidiOnlyTest(testing.DatasetBuilderTestCase): + DATASET_CLASS = groove.Groove + BUILDER_CONFIG_NAMES_TO_TEST = ["2bar-midionly"] + SPLITS = { + "train": 6, # 3, 2, 1 + "test": 1, + } + DL_EXTRACT_RESULT = ".." + + +if __name__ == "__main__": + testing.test_main() diff --git a/tensorflow_datasets/core/lazy_imports.py b/tensorflow_datasets/core/lazy_imports.py index b1ddfa304f4..843adf090a0 100644 --- a/tensorflow_datasets/core/lazy_imports.py +++ b/tensorflow_datasets/core/lazy_imports.py @@ -77,6 +77,11 @@ def PIL_Image(cls): # pylint: disable=invalid-name _try_import("PIL.TiffImagePlugin") return _try_import("PIL.Image") + @utils.classproperty + @classmethod + def pretty_midi(cls): + return _try_import("pretty_midi") + @utils.classproperty @classmethod def 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