Hello everyone!
My question seems common but I have not found the solution yet…
I have implemented MADDPG algorithm and I receive this error message

RuntimeError: size mismatch, m1: [20 x 20], m2: [40 x 64] at …\aten\src\TH/generic/THTensorMath.cpp:41

This is the code

class Actor(nn.Module):
def __init__(self, state_size, action_size, seed, fc1_units=400, fc2_units=300, use_bn=False):
    
    super(Actor, self).__init__()
    self.seed = torch.manual_seed(seed)
    self.use_bn = use_bn
    
    self.fc1 = nn.Linear(state_size, fc1_units)
    self.fc2 = nn.Linear(fc1_units, fc2_units)            
    self.fc3 = nn.Linear(fc2_units, action_size)
    if self.use_bn:
        self.bn1 = nn.BatchNorm1d(state_size)
        self.bn2 = nn.BatchNorm1d(fc1_units)
        self.bn3 = nn.BatchNorm1d(fc2_units)

    self.reset_parameters()



def forward(self, state):
    print('state shape',state.shape)
    
    if self.use_bn:
        x = self.fc1(self.bn1(state))
    else:
        x = self.fc1(state)

    x = F.relu(x)
    if self.use_bn:
        x = self.bn2(x)
    x = self.fc2(x)
    x = F.relu(x)
    if self.use_bn:
        x = self.bn3(x)
    return F.relu(self.fc3(x))



class Critic(nn.Module):
def __init__(self, state_size, action_size, seed, fc1_units=400, fc2_units=300, use_bn=False):
   
    super(Critic, self).__init__()
    self.seed = torch.manual_seed(seed)
    self.use_bn = use_bn
    self.fc1 = nn.Linear(state_size, fc1_units)
    self.fc2 = nn.Linear(fc1_units + action_size, fc2_units)
    self.fc3 = nn.Linear(fc2_units, 1)
    if self.use_bn:
        self.bn1 = nn.BatchNorm1d(fc1_units)
        self.bn2 = nn.BatchNorm1d(fc2_units)

def forward(self, state, action):
x  = self.fc1(state)
xs = F.relu(x)
if self.use_bn:
x = self.bn1(x)
x = torch.cat((xs, action), dim=1)
x = self.fc2(x)
x = F.relu(x)
if self.use_bn:
x = self.bn2(x)
return self.fc3(x)

The error is when I call this

Q = self.critic(states, actions)

states = 10
actions = 10
Can someone help me!!!