def test_cache(composers):
all_pieces = dict()
for composer in composers:
start = time.time()
pieces = data.getpices(path="../midis", composer=composer)
print("Loading {} {} pieces took {} seconds".format(
composer, len(pieces),
time.time() - start))
all_pieces.update(pieces)
midi_cache = data.initialize_cache(all_pieces)
gen = data.generate_batch(midi_cache, batch_size=10)
for i in range(5):
pre_start = time.time()
batch_in, batch_out = next(gen)
print("One batch took {}".format(time.time() - pre_start))
print("Batch iput is size: ({}, {}, {})".format(
len(batch_in), len(batch_in[0]), len(batch_in[0][0])))
print("Batch output is size: ({}, {}, {})".format(
len(batch_out), len(batch_out[0]), len(batch_out[0][0])))
import model
import data
if __name__ == '__main__':
# load midi files as statematrix, if no file will download from "http://www.piano-midi.de"
pieces = data.getpices(mode='all')
# Building model
print('Building model')
music_model = model.biaxial_model(t_layer_sizes=[300, 300],
n_layer_sizes=[100, 50],
trainer=tf.train.AdamOptimizer())
print('Start training')
music_model.train(pieces, batch_size=10, max_epoch=10000, predict_freq=200)
required=True)
parser.add_argument("--cache_dir",
help="Path to cache file",
default='cache.pkl')
args = parser.parse_args()
cache_name = args.cache_dir
model_name = args.model_name
if not os.path.exists(cache_name):
composers = input("Enter composers separated by spaces: ").split()
all_pieces = {}
if len(composers) == 0:
all_pieces.update(data.getpices(path="midis", mode='all'))
else:
for c in composers:
all_pieces.update(data.getpices(path="../midis", composer=c))
cache = data.initialize_cache(all_pieces, save_loc=cache_name)
else:
with open(cache_name, 'rb') as f:
cache = pickle.load(f)
# Building model
print('Building model')
music_model = model.biaxial_model(t_layer_sizes=[300, 300],
n_layer_sizes=[100, 50],
trainer=tf.train.RMSPropOptimizer(0.005))
help="Path to cache file",
default='../output/cache.pkl')
args = parser.parse_args()
cache_name = args.cache_dir
model_name = args.model_name
if not os.path.exists(cache_name):
composers = input(
"Enter composers separated by spaces, no input means all music: "
).split()
all_pieces = {}
if len(composers) == 0:
all_pieces.update(data.getpices(path="../data/midis", mode='all'))
elif composers[0] == 'pop':
all_pieces.update(
data.getpices(path='../data/pop_midis', mode='all'))
else:
for c in composers:
all_pieces.update(
data.getpices(path="../data/midis", composer=c))
cache = data.initialize_cache(all_pieces, save_loc=cache_name)
else:
with open(cache_name, 'rb') as f:
cache = pickle.load(f)
# Building model
print('Building model')