【Hackathon 5th No.7】为 Paddle 新增 apply API #635
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jeff41404
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Sep 18, 2023
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| 1. **Python层**: 在 Python 层，我们将获取用户的 callable，然后将其传递给 C++ 层。 | ||
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| 2. **C++层**: 在 C++ 层，我们将遍历 Tensor 的每个元素，并使用 Pybind11 调用用户提供的 Python 函数。对于 `apply_` 方法，我们将直接在原Tensor上修改值。对于 `apply` 方法，我们将创建一个新的 Tensor 来存放结果。 |
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C++中的实现方案是此文档的重点，最好有demo 或者 稍微展开描述下其中的一些关键细节，比如：是否需要实现OP和kernel，如何调用用户提供的 Python 函数进行计算，Tensor在GPU上如何调用Python 函数，是否要实现反向逻辑，是否要实现静态图逻辑，及说明这样设计和考虑的原因
jeff41404
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Sep 18, 2023
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| 参考：[飞桨API 设计及命名规范](https://www.paddlepaddle.org.cn/documentation/docs/zh/develop/dev_guides/api_contributing_guides/api_design_guidelines_standard_cn.html) | ||
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| API将被命名为 `apply` 和 `apply_`，其中 `apply_` 表示原地操作。 |
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需要写出完整的 API签名，包括 接口名称 和 参数
jeff41404
reviewed
Sep 18, 2023
| # 六、测试和验收的考量 | ||
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| - 单测代码，位于Paddle repo的 `test/` 目录。 | ||
| - 在 `paddle/test/legacy_test/test_inpalce.py` 中新增对应的inplace api单测。 |
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要说明主要的测试用例，比如 要测试哪些功能，期望得到什么结果；异常的测试有哪些，期望得到什么异常
jeff41404
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Sep 18, 2023
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| - **TensorFlow**: `tf.map_fn` 方法提供了强大的功能，但其接口相对复杂，不太适合初学者。 | ||
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| - **PyTorch**: 虽然 `torch.Tensor.apply_` 方法提供了所需的功能，但由于其局限性，它在新代码中不被推荐使用。 | ||
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| - **NumPy**: `numpy.vectorize` 是一个简单且强大的工具，但它在某些情况下可能不如专门设计的函数高效。 |
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最好把这些接口的签名都列出来，特别是参数方面的比较，会影响到下面的设计
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已经有 RFC 合入了，如果需要更新和完善，可以在原来的 RFC 上进行修改，感谢！ |
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