update

tutorial-contents/403_RNN_regressor.py

@@ -16,7 +16,7 @@ import matplotlib.pyplot as plt
 torch.manual_seed(1)    # reproducible
 
 # Hyper Parameters
-TIME_STEP = 5       # rnn time step
+TIME_STEP = 10      # rnn time step
 INPUT_SIZE = 1      # rnn input size
 LR = 0.02           # learning rate
 
@@ -69,7 +69,7 @@ plt.show()
 for step in range(60):
     start, end = step * np.pi, (step+1)*np.pi   # time steps
     # use sin predicts cos
-    steps = np.linspace(start, end, 10, dtype=np.float32)
+    steps = np.linspace(start, end, TIME_STEP, dtype=np.float32)
     x_np = np.sin(steps)    # float32 for converting torch FloatTensor
     y_np = np.cos(steps)