def DQN(height, width):
model = keras.models.Sequential([
keras.layers.Input(shape = (height*width*3)),
keras.layers.Dense(100, activation = "relu", kernel_initializer='he_uniform'),
keras.layers.Dense(50, activation = "relu", kernel_initializer='he_uniform'),
keras.layers.Dense(25, activation = "relu", kernel_initializer='he_uniform'),
keras.layers.Dense(2, activation = "softmax", kernel_initializer='he_uniform')
])
return model
policy_net = DQN(180, 360)
policy_net.compile(optimizer = 'Adam', loss = 'mse')
policy_net.fit(states[batch].reshape(1, 194400), target_q_values, epochs = 1)
and this error raised:
ValueError: Failed to find data adapter that can handle input: <class 'numpy.ndarray'>, <class 'numpy.float64'>
print("target_q_values : ", target_q_values)
1.5188535671234131
print("states[batch] : ", states[batch])
states[batch] : [[0. 0. 0. ... 0. 0. 0.]]
print("target_q_values : ", target_q_values.dtype)
print("states[batch] : ", states[batch].reshape(1, 194400).dtype)
target_q_values : float64
states[batch] : float64
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