agents/bc_cvae.py [76:84]:
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        self.max_action = max_action
        self.action_dim = action_dim
        self.discount = discount
        self.tau = tau
        self.device = device

    def sample_action(self, state):
        with torch.no_grad():
            state = torch.FloatTensor(state.reshape(1, -1)).to(self.device)
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agents/bc_mle.py [107:115]:
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        self.max_action = max_action
        self.action_dim = action_dim
        self.discount = discount
        self.tau = tau
        self.device = device

    def sample_action(self, state):
        with torch.no_grad():
            state = torch.FloatTensor(state.reshape(1, -1)).to(self.device)
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