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### What this PR does / why we need it? 1. In previous PRs https://github.com/vllm-project/vllm-ascend/pull/580 https://github.com/vllm-project/vllm-ascend/pull/784, I saved GPU memory by promptly deleting unnecessary tensors. For tensors passed from upper-layer functions, I used a list container to transfer the parameter and then popped the tensor from the list within the inner function to achieve deletion. Recently, I discovered a better implementation in sglang—the `dispose_tensor` function and I recommend adopting this approach. 2. Dispose `hidden_states` and `residual` from the previous layer once they're no longer used. 3. Avoid to generate `self.inputs_embeds` in `ModelRunnerV1` in non-multimodal scenarios. With the aforementioned optimizations, using the DeepSeek-R1-W8A8 model under the conditions of `TP=16` and `max-model-len=32768`, we can save 1.3GB of npu memory. **Reference**: https://github.com/sgl-project/sglang/pull/6147 ### Does this PR introduce _any_ user-facing change? No ### How was this patch tested? --------- Signed-off-by: ApsarasX <apsarax@outlook.com>