def example_0():
# learns to repeat simple sequence from random inputs
np.random.seed(0)
# parameters for input data dimension and lstm cell count
mem_cell_ct = 100
x_dim = 50
y_list = [-0.8333333333, 0.33333, 0.166666667, -80.8]
input_val_arr = [np.random.random(x_dim) for _ in y_list]
lstm_param = LstmParam(mem_cell_ct, x_dim)
lstm_net = LstmNetwork(lstm_param)
lstm_param2 = LstmParam(mem_cell_ct, mem_cell_ct)
lstm_net2 = LstmNetwork(lstm_param2)
loss = ToyLossLayer(mem_cell_ct)
for cur_iter in range(2000):
# print(y_list)
print("iter", "%2s" % str(cur_iter), end=": ")
for ind in range(len(y_list)):
lstm_net.x_list_add(input_val_arr[ind])
lstm_net2.x_list_add(lstm_net.lstm_node_list[ind].state.h)
print("y_pred = [" + ", ".join([
"% 2.5f" % loss.value(lstm_net2.lstm_node_list[ind].state.h)
for ind in range(len(y_list))
]) + "]",
end=", ")
lossv = lstm_net2.y_list_is(y_list, loss)
lstm_net.y_list_is2(lstm_net2)
print("loss:", "%.3e" % lossv)
lstm_param2.apply_diff(lr=0.1)
lstm_param.apply_diff(lr=0.1)
lstm_net2.x_list_clear()
lstm_net.x_list_clear()
