【Hackathon 5th No.27】为 Paddle 新增 select_scatter API #664
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zoooo0820
reviewed
Sep 28, 2023
zoooo0820
reviewed
Oct 11, 2023
| * `x (Tensor)` 表示给定张量，支持数据类型 `bool`，`float16`，`float32`，`float64`，`int32`，`int64` | ||
| * `src (Tensor)` 表示被填充等价于 `value` 的张量，支持与 `x` 相同的数据类型（可以实现 `int` 向 `float` 的转化以及 `float` 之间的转化） | ||
| * `dim (int)` 表示指定轴 | ||
| * `index (int)` 表示索引位置 |
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再对照下命名规范呢，dim -> axis ， src -> value等等。此外x支持的数据类型可以再根据依赖的api支持的数据类型验证一下，官网文档给的支持范围可能有点滞后了。
| # 将dim的切片替换为index，用于在特定维度上定位元素 | ||
| indices[dim] = index | ||
| # 使用tuple(indices)构造索引元组，将指定维度上的元素设置为value | ||
| x[tuple(indices)] = value |
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这个地方，最好不要直接调用方括号索引(setitem)，首先会有一个额外的解析过程，其次setitem会原地修改x的值，不能达到非inplace的效果，建议通过调用set_value OP实现。
| # 六、测试和验收的考量 | ||
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| 基础测试： | ||
| - 计算输出数值结果的一致性和数据类型是否正确，使用 pytorch 作为参考标准 |
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这里“参考标准”因为需要实际在单测中比较，目前单测中一般使用numpy进行，如果numpy没有提供直接对应的API，需要自行实现一个替代的函数用于单测对比。
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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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为 Paddle 新增 select_scatter API