print("Total sequence trained:", (idx-(80*freq))*(stride/freq), "seconds")
# saving and printing
plt.plot(vals)
plt.savefig(graphFileName)
f = open(modelFileName, 'wb')
pickle.dump(vals, f)
f.close()
elif mode == "generate":
# load parameters
f = open(modelFileName, 'rb')
lstm.params = pickle.load(f) #load params from file
f.close()
start = 0;
print("generation begin...")
print("Input Size:", batchSize)
print("minibatches:", miniBatches)
print("Sequence length:", sequenceSize/freq, "s")
print("stride:", stride)
print("hidden units:", hiddenUnits)
print("learning rate:", learningRate)
for batch_stream in data_stream.get_epoch_iterator():
# Start somewhere
if idx>idxBegin:
if start == 0:
