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Add gpu kernel for new api : linalg.lstsq #38621

Merged
merged 11 commits into from
Jan 10, 2022
Merged

Add gpu kernel for new api : linalg.lstsq #38621

merged 11 commits into from
Jan 10, 2022

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haohongxiang
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@haohongxiang haohongxiang commented Dec 30, 2021 •
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Add gpu kernel for new api : linalg.lstsq
You can see the implementation of cpu kernel in PR38585
The docs_cn of paddle.linalg.lstsq is merged by docs-PR4174

1、usage example：

import paddle
paddle.set_device("cpu")
x = paddle.to_tensor([[1, 3], [3, 2], [5, 6.]])
y = paddle.to_tensor([[3, 4, 6], [5, 3, 4], [1, 2, 1.]])
results = paddle.linalg.lstsq(x, y, driver="gelsd")

# solution
print(results[0]) 
# [[ 0.78350395, -0.22165027, -0.62371236],
# [-0.11340097,  0.78866047,  1.14948535]]

# residuals
print(results[1])
# [19.81443405, 10.43814468, 30.56185532])

# rank
print(results[2])
# 2

# singular values
print(results[3])
# [9.03455734, 1.54167950]

2、docs_cn：

image

3、docs_en：

image

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Thanks for your contribution!
Please wait for the result of CI firstly. See Paddle CI Manual for details.

dingjiaweiww
dingjiaweiww previously approved these changes Jan 6, 2022
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TCChenlong
TCChenlong reviewed Jan 6, 2022
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python/paddle/tensor/linalg.py Outdated
should be one of float32, float64.
y (Tensor): A tensor with shape ``(*, M, K)`` , the data type of the input Tensor ``y``
should be one of float32, float64.
rcond(float, optional): A float pointing number used to determine the effective rank of ``x``.
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需要说明默认值。

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已加

python/paddle/tensor/linalg.py Outdated
.. code-block:: python

import paddle
import numpy as np
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这行冗余 可以删除

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已删

qingqing01
qingqing01 reviewed Jan 7, 2022
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paddle/fluid/operators/lstsq_op.cu Outdated
auto tmp_x = dito.Transpose(new_x);
auto tmp_y = dito.Transpose(new_y);
framework::TensorCopy(tmp_x, new_x.place(), &new_x);
framework::TensorCopy(tmp_y, new_y.place(), &new_y);
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Why need this copy?

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Thank you for comments. It's not necessary so I removed it.

paddle/fluid/operators/lstsq_op.cu Outdated
auto slice_b = dito.Slice(trans_b, {-2}, {0}, {min_mn});
auto tmp_r = dito.TrilTriu(slice_r, 0, false);
framework::TensorCopy(tmp_r, new_x.place(), &new_x);
framework::TensorCopy(slice_b, new_y.place(), &new_y);
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same as above

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Thank you for comments. It's not necessary so I removed it.

TCChenlong
TCChenlong approved these changes Jan 10, 2022
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LGTM for API docs

ForFishes
ForFishes approved these changes Jan 10, 2022
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LGTM

@ForFishes ForFishes merged commit 405103d into PaddlePaddle:develop Jan 10, 2022
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@qingqing01 qingqing01 qingqing01 left review comments

@TCChenlong TCChenlong TCChenlong approved these changes

@ForFishes ForFishes ForFishes approved these changes

@lanxianghit lanxianghit lanxianghit approved these changes

@dingjiaweiww dingjiaweiww dingjiaweiww left review comments

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6 participants
@haohongxiang @qingqing01 @TCChenlong @ForFishes @dingjiaweiww @lanxianghit