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【Hackathon 5th No.35】为 Paddle 新增 histogramdd API（update） #753

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merged 18 commits into from
Dec 5, 2023
Merged

【Hackathon 5th No.35】为 Paddle 新增 histogramdd API（update） #753

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7d2e856
add copysign rfc
cocoshe Sep 13, 2023
4c0022d
fix input args, add backward kernel, fix python api
cocoshe Sep 15, 2023
5fff675
fix types
cocoshe Sep 15, 2023
bfa46fe
fix Number types
cocoshe Sep 15, 2023
8ddbed9
Merge branch 'master' of https://github.com/PaddlePaddle/community
cocoshe Sep 26, 2023
72fbcfc
add pdist api design
cocoshe Sep 26, 2023
9d2918b
fix typo
cocoshe Sep 27, 2023
3b3e350
fix
cocoshe Sep 27, 2023
ab440c2
add bitwise_shift rfc
cocoshe Sep 27, 2023
e3fe25c
update
cocoshe Sep 27, 2023
68d27cf
add bitwise rfc
cocoshe Sep 27, 2023
7aff2eb
update
cocoshe Sep 27, 2023
703a1db
update jax shift doc
cocoshe Sep 28, 2023
23a6b8d
add histogramdd rfc
cocoshe Oct 1, 2023
d377093
add some detail
cocoshe Oct 4, 2023
1e2562f
add test path, fix args desc
cocoshe Oct 7, 2023
04ff241
modify params in api: sample to x, range to rangs.
cocoshe Nov 20, 2023
9797add
Merge branch 'master' into histogramdd_rfc_update
cocoshe Nov 20, 2023
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7 changes: 4 additions & 3 deletions rfcs/APIs/20231001_api_design_for_histogramdd.md
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Expand Up @@ -381,13 +381,14 @@ PyTorch底层用cpp实现kernel，Numpy通过API在Python层直接实现。

API的设计为:

- paddle.histogramdd(sample, bins, range=None, density=False, weights=None，name=None)
- paddle.histogramdd(x, bins, ranges=None, density=False, weights=None，name=None)

其中

+ sample(Tensor) - 输入的多维 tensor
+ x(Tensor) - 输入的多维 tensor
+ bins(Tensor[], int[], int) 若为`Tensor[]`，则定义了bin的边缘序列；若为`int[]`，则每个值分别定义了每个维度的等宽bin的数量；若为`int`，则定义了所有维度的等宽bin的数量。
+ range(*sequence of python:float*)：规定了bin的最左端和最右端，也就是范围。若为None则以所有输入的最小值和最大值作为边界。
+ ranges(*sequence of python:float*)：规定了bin的最左端和最右端，也就是范围。若为None则以所有输入的最小值和最大值作为边界。

+ density (bool) – 默认为 False , 结果将包含每个bin中的计数。如果设置为 True ，则每个计数（重量）将除以总计数，然后除以其所在bin的范围宽度。
+ weight(Tensor): 默认所有输入权重为1，他的shape必须与输入sample除去最内部维度的shape相同，例如当sample的shape为[M,N]时，weight的shape必须为[M]。
+ name(str, 可选）- 操作的名称(默认值为None）。
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