Here is my code:
bsp = Input(shape = (1,3,))
V1 = Dense(2,activation = 'softmax')(bsp)
# b = Dense(5, activation = "relu")(B)
# inputs = [B]
# merges = [b]
S_input = Input(shape = (15,4))
S = Reshape((15,4,1))(S_input)
#inputs.append(S)
x2 = inception(S)
# merge and add
V2 = Dense(2, activation = 'softmax')(x2)
V = add([V1,V2])
model = Model(inputs = [bsp,S_input], outputs = V)
model.predict([observation[0],observation[1]])
Basically it's a model with 2 inputs and 1 output. In the final computation, the 2 inputs were added together and passed into the final model. However, it has error as :
Traceback (most recent call last):
File "C:/Users/User/Desktop/Learning Materials/programming/python_code/RL/LabFiles_RL/stock_market_reinforcement_learning/market_pg.py", line 157, in <module>
pg.train(verbose = 1)
File "C:/Users/User/Desktop/Learning Materials/programming/python_code/RL/LabFiles_RL/stock_market_reinforcement_learning/market_pg.py", line 66, in train
aprob = model.predict([observation[0],observation[1]])[0]
File "C:\Users\User\Anaconda3\lib\site-packages\keras\engine\training.py", line 1172, in predict
steps=steps)
File "C:\Users\User\Anaconda3\lib\site-packages\keras\engine\training_arrays.py", line 297, in predict_loop
batch_outs = f(ins_batch)
File "C:\Users\User\Anaconda3\lib\site-packages\keras\backend\tensorflow_backend.py", line 2661, in __call__
return self._call(inputs)
File "C:\Users\User\Anaconda3\lib\site-packages\keras\backend\tensorflow_backend.py", line 2614, in _call
dtype=tensor.dtype.base_dtype.name))
File "C:\Users\User\Anaconda3\lib\site-packages\numpy\core\numeric.py", line 492, in asarray
return array(a, dtype, copy=False, order=order)
ValueError: setting an array element with a sequence.
As mentioned in the other similar questions, I have ensured that the two inputs are of same dimension, in my case, which are shape of (1,1,3) and (1,15,4).
How can I fix the problem ?
