def main():
# load midi
dirpath = '../'
pieces = loadPieces(dirpath)
# divide train valid
valid_pieces = pieces[:num_valid]
train_pieces = pieces[num_valid:]
valid_gen = BatchGenerator(pieces[0], valid_batch_size, 1)
train_gen = MixedGenarator(pieces, batch_size, num_unrolling)
# create model ans start training
model = LSTM_model(layer_size, batch_size, num_unrolling)
model.train(train_gen, valid_gen, train_step=10000, summary_frequency=100)
df = pd.io.gbq.read_gbq(query, project_id=project_id)
dataset = dataset(df,
table='snp',
min_date=dt.datetime(2010,
1,
1,
0,
0,
0,
tzinfo=dt.timezone.utc),
max_date=dt.datetime(2020,
6,
1,
0,
0,
0,
tzinfo=dt.timezone.utc))
dataset.prepare_dataset()
model = LSTM_model(1, 'snp')
train_data_generator = datagen(df=dataset.traindata,
gen_length=model.model_params['SEQ_LEN'],
batch_size=model.model_params['batch_size'],
shuffle=False)
test_data_generator = datagen(df=dataset.testdata,
gen_length=model.model_params['SEQ_LEN'],
batch_size=model.model_params['batch_size'],
shuffle=False)
model.train(train_gen=train_data_generator, validation_gen=test_data_generator)