def METHOD_NAME(self, moe_type='standard', enable_training=False):
    from deepspeed.moe.utils import has_moe_layers
    moe, _ = has_moe_layers(self.client_module)
    if moe:
        moe_experts = self.client_module.METHOD_NAME.deepspeed_moe.experts.deepspeed_experts if moe_type == 'standard' else \
                        self.client_module.METHOD_NAME.moe.deepspeed_moe.experts.deepspeed_experts
        num_experts = len(moe_experts)
        if moe_type == 'standard':
            return [moe_experts[i].dense_h_to_4h.weight for i in range(num_experts)], \
                   [moe_experts[i].dense_h_to_4h.bias for i in range(num_experts)], \
                   [moe_experts[i].dense_4h_to_h.weight for i in range(num_experts)], \
                   [moe_experts[i].dense_4h_to_h.bias for i in range(num_experts)]
        else:
            return [moe_experts[i].dense_h_to_4h.weight for i in range(num_experts)], \
                   [moe_experts[i].dense_h_to_4h.bias for i in range(num_experts)], \
                   [moe_experts[i].dense_4h_to_h.weight for i in range(num_experts)], \
                   [moe_experts[i].dense_4h_to_h.bias for i in range(num_experts)], \
                   self.client_module.METHOD_NAME.METHOD_NAME.dense_h_to_4h.weight, \
                   self.client_module.METHOD_NAME.METHOD_NAME.dense_h_to_4h.bias, \
                   self.client_module.METHOD_NAME.METHOD_NAME.dense_4h_to_h.weight, \
                   self.client_module.METHOD_NAME.METHOD_NAME.dense_4h_to_h.bias, \
                   self.client_module.METHOD_NAME.coefficient.weight
    else:
        return self.client_module.METHOD_NAME.dense_h_to_4h.weight, \
               self.client_module.METHOD_NAME.dense_h_to_4h.bias, \
               self.client_module.METHOD_NAME.dense_4h_to_h.weight, \
               self.client_module.METHOD_NAME.dense_4h_to_h.bias