def __init__(self, steps_per_quarter):
"""Initialize a TextChordsEncoder object.
Encodes chord symbols using a vocabulary of triads. Indices 0 and 1 are
reserved and unused, and the remaining 48 + 1 indices represent each of 4
triad types over each of 12 roots, plus "no chord".
Args:
steps_per_quarter: Number of steps per quarter at which to quantize.
"""
self._steps_per_quarter = steps_per_quarter
self._encoding = note_seq.TriadChordOneHotEncoding()
hparams=merge_hparams(
lstm_models.get_default_hparams(),
HParams(
batch_size=512,
max_seq_len=32, # 2 bars w/ 16 steps per bar
z_size=256,
enc_rnn_size=[1024],
dec_rnn_size=[512, 512, 512],
)),
note_sequence_augmenter=data.NoteSequenceAugmenter(transpose_range=(-3,
3)),
data_converter=data.OneHotMelodyConverter(
max_bars=100,
slice_bars=2,
steps_per_quarter=4,
chord_encoding=note_seq.TriadChordOneHotEncoding()),
train_examples_path=None,
eval_examples_path=None,
)
# Drums
CONFIG_MAP['cat-drums_2bar_small'] = Config(
model=MusicVAE(lstm_models.BidirectionalLstmEncoder(),
lstm_models.CategoricalLstmDecoder()),
hparams=merge_hparams(
lstm_models.get_default_hparams(),
HParams(
batch_size=512,
max_seq_len=32, # 2 bars w/ 16 steps per bar
z_size=256,
enc_rnn_size=[512],
self.min_note = min_note
self.max_note = max_note
self.transpose_to_key = transpose_to_key
# Default configurations.
default_configs = {
'basic_improv':
ImprovRnnConfig(
generator_pb2.GeneratorDetails(
id='basic_improv',
description='Basic melody-given-chords RNN with one-hot triad '
'encoding for chords.'),
note_seq.ConditionalEventSequenceEncoderDecoder(
note_seq.OneHotEventSequenceEncoderDecoder(
note_seq.TriadChordOneHotEncoding()),
note_seq.OneHotEventSequenceEncoderDecoder(
note_seq.MelodyOneHotEncoding(min_note=DEFAULT_MIN_NOTE,
max_note=DEFAULT_MAX_NOTE))),
contrib_training.HParams(batch_size=128,
rnn_layer_sizes=[64, 64],
dropout_keep_prob=0.5,
clip_norm=5,
learning_rate=0.001)),
'attention_improv':
ImprovRnnConfig(
generator_pb2.GeneratorDetails(
id='attention_improv',
description=
'Melody-given-chords RNN with one-hot triad encoding for '
'chords, attention, and binary counters.'),
