def get_lead_encoder(self, encoder):
m, conv_f, conv_win_size, enc_lstm_size = encoder.params
lead_enc = MelodyEncoder(m=m,
conv_f=conv_f,
conv_win_size=1,
enc_lstm_size=enc_lstm_size)
return lead_enc
def init_with_Encoder(cls,
encoder_params,
rhythm_embed_size,
dec_lstm_size,
V,
enc_use_meta=False,
dec_use_meta=False,
compile_now=False):
melody_enc = MelodyEncoder(*encoder_params, compile_now=False)
return cls(melody_encoder=melody_enc,
rhythm_embed_size=rhythm_embed_size,
dec_lstm_size=dec_lstm_size,
V=V,
enc_use_meta=enc_use_meta,
dec_use_meta=dec_use_meta,
compile_now=compile_now)
def from_saved_custom(cls,
save_dir,
melody_encoder=None,
load_melody_encoder=False,
compile_now=False):
if melody_encoder and load_melody_encoder:
raise ValueError(
"MelodyEncoder *NOT* None and load_melody_encoder=True!")
if not melody_encoder and not load_melody_encoder:
raise ValueError(
"MelodyEncoder *IS* None and load_melody_encoder=False!")
if load_melody_encoder:
with open(save_dir + "/melody_encoder_parameters.json",
"r") as handle:
melody_enc_params = json.load(handle)
melody_encoder = MelodyEncoder(*melody_enc_params,
compile_now=True)
melody_encoder.load_weights(save_dir + "/melody_encoder_weights")
for l in melody_encoder.layers:
l.trainable = False
melody_encoder.compile_default()
with open(save_dir + "/chord_net_parameters.json", "r") as handle:
params = json.load(handle)
chord_net = cls(melody_encoder, *params, compile_now=compile_now)
chord_net.load_weights(save_dir + "/chord_net_weights")
return chord_net
#%%
#loaded_chord_net = ChordNetwork.from_saved_custom("Trainings/chord_test/chord",
# load_melody_encoder=True,
# compile_now=True)
ch_gen = ChordGenerator(music_dir, save_conversion_params="/".join([top_dir, save_dir]),
to_list=False, meta_prep_f=None) # None
# data_iter = ch_gen.generate_forever(batch_size=24)
x, y = ch_gen.list_data()
#%%
comb_net = CombinedNetwork.from_saved_custom("/".join([top_dir, save_dir, "weights"]),
meta_predictor,
generation=True,
compile_now=False)
melody_enc = comb_net.melody_encoder
size_1 = 1
fresh_melody_enc = MelodyEncoder(m=48, conv_f=4, conv_win_size=size_1, enc_lstm_size=52, compile_now=False)
fresh_melody_enc.set_weights(get_smaller_weights(melody_enc, conv_win_size=size_1))
# for l in fresh_melody_enc.layers:
# l.trainable = False
fresh_melody_enc.compile_default()
#%%
chord_net = ChordNetwork(fresh_melody_enc, 28, ch_gen.V, compile_now=True)
#%%
log_dir = "chord_logs"
tb = TensorBoard(log_dir="/".join([top_dir, save_dir, log_dir]))
bar_embedder = BarEmbedding(V=V_rhythm,
beat_embed_size=beat_embed_size,
embed_lstm_size=embed_lstm_size,
out_size=out_size)
rhythm_encoder = RhythmEncoder(bar_embedder=bar_embedder,
context_size=rc_size,
lstm_size=rhythm_enc_lstm_size)
rhythm_net = RhythmNetwork(rhythm_encoder=rhythm_encoder,
dec_lstm_size=rhythm_dec_lstm_size,
V=V_rhythm,
dec_use_meta=True,
compile_now=True)
# ATTENTION: conv_win_size must not be greater than context size!
melody_encoder = MelodyEncoder(m=m,
conv_f=conv_f,
conv_win_size=min(mc_size, conv_win_size),
enc_lstm_size=melody_enc_lstm_size)
melody_net = MelodyNetwork(melody_encoder=melody_encoder,
rhythm_embed_size=out_size,
dec_lstm_size=melody_dec_lstm_size,
V=V_melody,
dec_use_meta=True,
compile_now=True)
print("Individual networks set up...\n")
# COMBINED NETWORK
comb_net = CombinedNetwork(context_size,
m,
meta_embed_size,
bar_embedder,