How to use the magent.c_lib.as_int32_c_array function in magent

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github geek-ai / MAgent / python / magent / builtin / rule_model / rushgather.py View on Github external
def infer_action(self, states, *args, **kwargs):
        obs_buf = as_float_c_array(states[0])
        hp_buf  = as_float_c_array(states[1])
        n, height, width, n_channel = states[0].shape
        buf = np.empty((n,), dtype=np.int32)
        act_buf = as_int32_c_array(buf)
        attack_base = self.attack_base
        
        view2attack_buf = as_int32_c_array(self.view2attack)

        _LIB.gather_infer_action(obs_buf, hp_buf, n, height, width, n_channel,
                                 act_buf, attack_base, view2attack_buf)
        return buf
github geek-ai / MAgent / python / magent / builtin / rule_model / rushgather.py View on Github external
def infer_action(self, states, *args, **kwargs):
        obs_buf = as_float_c_array(states[0])
        hp_buf  = as_float_c_array(states[1])
        n, height, width, n_channel = states[0].shape
        buf = np.empty((n,), dtype=np.int32)
        act_buf = as_int32_c_array(buf)
        attack_base = self.attack_base
        
        view2attack_buf = as_int32_c_array(self.view2attack)

        _LIB.gather_infer_action(obs_buf, hp_buf, n, height, width, n_channel,
                                 act_buf, attack_base, view2attack_buf)
        return buf
github geek-ai / MAgent / python / magent / builtin / rule_model / runaway.py View on Github external
def infer_action(self, observations, *args, **kwargs):
        obs_buf = as_float_c_array(observations[0])
        hp_buf  = as_float_c_array(observations[1])
        n, height, width, n_channel = observations[0].shape
        buf = np.empty((n,), dtype=np.int32)
        act_buf = as_int32_c_array(buf)
        _LIB.runaway_infer_action(obs_buf, hp_buf, n, height, width, n_channel,
                                  self.attack_base, act_buf, self.away_channel, self.move_back)
        return buf
github geek-ai / MAgent / python / magent / builtin / rule_model / rush.py View on Github external
def infer_action(self, observations, *args, **kwargs):
        obs_buf = as_float_c_array(observations[0])
        hp_buf  = as_float_c_array(observations[1])
        n, height, width, n_channel = observations[0].shape
        buf = np.empty((n,), dtype=np.int32)
        act_buf = as_int32_c_array(buf)
        attack_channel = self.attack_channel
        attack_base = self.attack_base
        view2attack_buf = as_int32_c_array(self.view2attack)

        _LIB.rush_prey_infer_action(obs_buf, hp_buf, n, height, width, n_channel,
                                    act_buf, attack_channel, attack_base,
                                    view2attack_buf, ctypes.c_float(100.0))
        return buf
github geek-ai / MAgent / python / magent / builtin / rule_model / rush.py View on Github external
def infer_action(self, observations, *args, **kwargs):
        obs_buf = as_float_c_array(observations[0])
        hp_buf  = as_float_c_array(observations[1])
        n, height, width, n_channel = observations[0].shape
        buf = np.empty((n,), dtype=np.int32)
        act_buf = as_int32_c_array(buf)
        attack_channel = self.attack_channel
        attack_base = self.attack_base
        view2attack_buf = as_int32_c_array(self.view2attack)

        _LIB.rush_prey_infer_action(obs_buf, hp_buf, n, height, width, n_channel,
                                    act_buf, attack_channel, attack_base,
                                    view2attack_buf, ctypes.c_float(100.0))
        return buf