i want to use pytorch instead of keras but i failed to do it my self
def _model(self):
model = Sequential()
model.add(Dense(units=64, input_dim=self.state_size,
activation="relu"))
model.add(Dense(units=32, activation="relu"))
model.add(Dense(units=8, activation="relu"))
model.add(Dense(self.action_size, activation="linear"))
model.compile(loss="mse", optimizer=Adam(lr=0.001))
return model
class Model(nn.Module):
def __init__(self, input_dim):
super(Model, self).__init__()
self.fc1 = nn.ReLU(input_dim, 64)
self.fc2 = nn.ReLU(64,32)
self.fc3 = nn.Relu(32, 8)
self.fc4 = nn.Linear(8, 3)
model = Model()
criterion = nn.MSELoss()
optimizer = torch.optim.Adam(model.parameters(), lr=0.001)
model = Model()
You need to provide an argument when you call Model()
since your __init__(self, input_dims)
requires an argument.
It should be this:
model = Model(<integer dimensions for your network>)
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