Release Notes

MindSpore Lite 2.7.1 Release Notes

主要特性及增强

MindSpore Lite与MindSpore解耦，CPU算子库等相关动态库独立于MindSpore进行演进。
支持图片生成等AIGC模型中的Cache算法基于图模式实现。

API 变更

新增MultiModelRunner、ModelExecutor接口，支持Cache算法的图模式实现。

import mindspore_lite as mslite
import numpy as np
dtype_map = {
    mslite.DataType.FLOAT32: np.float32,
    mslite.DataType.INT32: np.int32,
    mslite.DataType.FLOAT16: np.float16,
    mslite.DataType.INT8: np.int8
}
context = mslite.Context()
context.target = ["ascend"]
context.ascend.devcie_id = 0
runner = mslite.MultiModelRunner()
model_path = "path_to_model"
runner.build_from_file(model_path, mslite.ModelType.MINDIR, context)
execs = runner.get_model_executor()
for exec_ in execs:
    exec_inputs = exec_.get_inputs()
    for input_ in exec_inputs:
        data = np.random.randn(*input_.shape).astype(dtype_map[input_.dtype])
        input_.set_data_from_numpy(data)
    exec_.predict(exec_inputs)

离线转换工具conver_lite通过配置SplitGraph参数以及split_node_name参数实现子图切分。
```
[SplitGraph]
split_node_name=[[node_name_1],[node_name_2]]
```

贡献者

YeFeng_24,xiong-pan,jjfeing,liuf9,zhangzhugucheng,xu_anyue,yiguangzheng,zxx_xxz,jianghui58,hbhu_bin,chenyihang5,qll1998,yangyingchun1999,liuchengji3,cheng-chao23,gemini524,yangly,yanghui00