def chord_encoding(chord): index = mm.TriadChordOneHotEncoding().encode_event(chord) c = np.zeros([TOTAL_STEPS, CHORD_DEPTH]) c[0,0] = 1.0 c[1:,index] = 1.0 return c
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=mm.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],
def chord_encoding(chord, total_steps, chord_depth):
index = mm.TriadChordOneHotEncoding().encode_event(chord)
c = np.zeros([total_steps, chord_depth])
c[0,0] = 1.0
c[1:,index] = 1.0
return c
