[xdoctest] reformat example code with google style in No.36-43 #56440

yuchen202 · 2023-08-18T08:55:14Z

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Description

修改如下文件的示例代码，使其通过 xdoctest 检查：

Related links

力所能及地改了一些

paddle-bot · 2023-08-18T08:55:20Z

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megemini · 2023-08-22T10:30:59Z

把标题改一下～

另外，这个 PR 里面文件太多了～ 🤣

看看能不能拆一下，或者先改一个～

megemini · 2023-08-23T06:14:57Z

标题还是要改一下，参考：
#55834

标题统一格式，好方便以后管理、搜索之类的～

sunzhongkai588

这几个代码示例没过，还是得修改一下

另外，还有一些代码的输出结果不要用 #，请修改

注意下PR描述里要加上 @megemini @SigureMo @sunzhongkai588 。改的很不错了，大部份代码示例都通过，加油～

sunzhongkai588 · 2023-08-27T15:47:54Z

python/paddle/nn/functional/common.py

+        >>> num_classes = 20
+        >>> batch_size = 10
+        >>> num_samples = 6
+        >>> label = paddle.randint(low=0, high=num_classes, shape=[batch_size], dtype='int64')


paddle.randint 也是带有随机性的，加一个随机种子吧

Suggested change

>>> label = paddle.randint(low=0, high=num_classes, shape=[batch_size], dtype='int64')

>>> paddle.seed(2023)

>>> label = paddle.randint(low=0, high=num_classes, shape=[batch_size], dtype='int64')

下面的输出，也记得按照seed的结果同步修改

sunzhongkai588 · 2023-08-27T16:08:37Z

python/paddle/nn/functional/common.py

+        >>> # required: distributed
+        >>> # Multi GPU, test_class_center_sample.py


好像依赖外部文件 test_class_center_sample.py，这段代码skip吧

Suggested change

>>> # required: distributed

>>> # Multi GPU, test_class_center_sample.py

>>> # doctest: +SKIP('Depends on external files.')

>>> # required: distributed

>>> # Multi GPU, test_class_center_sample.py

这里改用 # doctest: +REQUIRES(env:DISTRIBUTED) 即可，因为我们 CI 没有分布式环境，使用该 requires 就是自动跳过

sunzhongkai588 · 2023-08-27T16:15:04Z

python/paddle/nn/functional/common.py

+        >>> print(label)
+        >>> print(remapped_label)
+        >>> print(sampled_class_index)
+        >>> # the output is
+        Tensor(shape=[10], dtype=int64, place=Place(cpu), stop_gradient=True,
+        [10, 3 , 11, 14, 15, 15, 7 , 12, 5 , 13])
+        Tensor(shape=[10], dtype=int64, place=Place(cpu), stop_gradient=True,
+        [3, 0, 4, 7, 8, 8, 2, 5, 1, 6])
+        Tensor(shape=[9], dtype=int64, place=Place(cpu), stop_gradient=True,
+        [3 , 5 , 7 , 10, 11, 12, 13, 14, 15])


这个形式看起来不太整洁，要不就一行print一行输出（输出的结果务必按照seed结果同步修改），如下：

Suggested change

>>> print(label)

>>> print(remapped_label)

>>> print(sampled_class_index)

>>> # the output is

Tensor(shape=[10], dtype=int64, place=Place(cpu), stop_gradient=True,

[10, 3 , 11, 14, 15, 15, 7 , 12, 5 , 13])

Tensor(shape=[10], dtype=int64, place=Place(cpu), stop_gradient=True,

[3, 0, 4, 7, 8, 8, 2, 5, 1, 6])

Tensor(shape=[9], dtype=int64, place=Place(cpu), stop_gradient=True,

[3 , 5 , 7 , 10, 11, 12, 13, 14, 15])

>>> print(label)

Tensor(shape=[10], dtype=int64, place=Place(cpu), stop_gradient=True,

[10, 3 , 11, 14, 15, 15, 7 , 12, 5 , 13])

>>> print(remapped_label)

Tensor(shape=[10], dtype=int64, place=Place(cpu), stop_gradient=True,

[3, 0, 4, 7, 8, 8, 2, 5, 1, 6])

>>> print(sampled_class_index)

Tensor(shape=[9], dtype=int64, place=Place(cpu), stop_gradient=True,

[3 , 5 , 7 , 10, 11, 12, 13, 14, 15])

sunzhongkai588 · 2023-08-27T16:18:22Z

python/paddle/nn/functional/activation.py

+            >>> import paddle
+            >>> import paddle.nn.functional as F
+
+            >>> logits = paddle.randn([4, 6])


randn有随机性，加seed

Suggested change

>>> logits = paddle.randn([4, 6])

>>> paddle.seed(2023)

>>> logits = paddle.randn([4, 6])

下面的输出也按照seed结果同步修改

sunzhongkai588 · 2023-08-27T16:18:38Z

python/paddle/nn/functional/activation.py

+            >>> temperature = 0.01
+            >>> gumbel_softmax = F.gumbel_softmax(logits, temperature)
+            >>> print(gumbel_softmax)
+            >>> #out's value is as follows:


这行有点多余，删了吧

Suggested change

>>> #out's value is as follows:

sunzhongkai588 · 2023-08-27T16:31:14Z

python/paddle/nn/functional/common.py

+            Tensor(shape=[2, 3], dtype=float32, place=Place(cpu), stop_gradient=True,
+            [[0., 0., 6.],
+            [0., 0., 0.]])


Suggested change

Tensor(shape=[2, 3], dtype=float32, place=Place(cpu), stop_gradient=True,

[[0., 0., 6.],

[0., 0., 0.]])

Tensor(shape=[2, 3], dtype=float32, place=Place(cpu), stop_gradient=True,

[[0., 0., 6.],

[0., 0., 0.]])

sunzhongkai588 · 2023-08-27T16:36:52Z

python/paddle/nn/functional/common.py

+            >>> x = paddle.randn((3, 2), dtype="float32")
+            >>> # x: [[-0.32342386 -1.200079  ]
+            >>> #     [ 0.7979031  -0.90978354]
+            >>> #     [ 0.40597573  1.8095392 ]]
+            >>> weight = paddle.full(shape=[2, 4], fill_value="0.5", dtype="float32", name="weight")
+            >>> # weight: [[0.5 0.5 0.5 0.5]
+            >>> #          [0.5 0.5 0.5 0.5]]
+            >>> bias = paddle.ones(shape=[4], dtype="float32", name="bias")
+            >>> # bias: [1. 1. 1. 1.]
+            >>> y = paddle.nn.functional.linear(x, weight, bias)
+            >>> # y: [[0.23824859 0.23824859 0.23824859 0.23824859]
+            >>> #     [0.9440598  0.9440598  0.9440598  0.9440598 ]
+            >>> #     [2.1077576  2.1077576  2.1077576  2.1077576 ]]


如无特殊情况，请勿使用 # 的注释方式提供输出值

比如 x , 若要显示输出值，则

>>> print(x） Tensor(shape=[3, 2], dtype=float32, place=Place(cpu), stop_gradient=True, [[ 0.06132207, 1.11349595], [ 0.41906244, -0.24858207], [-1.85169315, -1.50370061]])

weight, bias, y 同理。另外，在x代码前记得加上seed

sunzhongkai588 · 2023-08-27T16:40:32Z

python/paddle/nn/functional/extension.py

+            >>> final_sequences = paddle.nn.functional.gather_tree(ids, parents)
+            >>> [[[2, 2], [1, 6]], [[3, 3], [6, 1]], [[0, 1], [9, 0]]]


同理，如无特殊情况，请显性的提供输出值，如

Suggested change

>>> final_sequences = paddle.nn.functional.gather_tree(ids, parents)

>>> [[[2, 2], [1, 6]], [[3, 3], [6, 1]], [[0, 1], [9, 0]]]

>>> final_sequences = paddle.nn.functional.gather_tree(ids, parents)

>>> print(final_sequences)

Tensor(shape=[3, 2, 2], dtype=int64, place=Place(cpu), stop_gradient=True,

[[[2, 2],

[1, 6]],

[[3, 3],

[6, 1]],

[[0, 1],

[9, 0]]])

sunzhongkai588 · 2023-08-27T16:48:19Z

python/paddle/nn/initializer/uniform.py

+            >>> # linear.weight:  [[-0.46245047  0.05260676]
+            >>> #                  [ 0.38054508  0.29169726]]
+            >>> # linear.bias:  [-0.2734719   0.23939109]
+
+            >>> res = linear(data)
+            >>> # res:  [[[-0.3553773  0.5836951]]
+            >>> #        [[-0.3553773  0.5836951]]
+            >>> #        [[-0.3553773  0.5836951]]]


同理，如无特殊情况，请勿使用 # 的注释方式提供输出值

另外，paddle.nn.initializer.Uniform有随机性，请在代码开始出加seed

Suggested change

>>> # linear.weight: [[-0.46245047 0.05260676]

>>> # [ 0.38054508 0.29169726]]

>>> # linear.bias: [-0.2734719 0.23939109]

>>> res = linear(data)

>>> # res: [[[-0.3553773 0.5836951]]

>>> # [[-0.3553773 0.5836951]]

>>> # [[-0.3553773 0.5836951]]]

>>> print(linear.weight)

Parameter containing:

Tensor(shape=[2, 2], dtype=float32, place=Place(cpu), stop_gradient=False,

[[ 0.36583614, 0.02014720],

[-0.24039063, 0.40525323]])

>>> print(linear.bias)

Parameter containing:

Tensor(shape=[2], dtype=float32, place=Place(cpu), stop_gradient=False,

[-0.07599911, -0.09358713])

>>> res = linear(data)

>>> print(res)

Tensor(shape=[3, 1, 2], dtype=float32, place=Place(cpu), stop_gradient=False,

[[[0.04944640, 0.33181331]],

[[0.04944640, 0.33181331]],

[[0.04944640, 0.33181331]]])

sunzhongkai588 · 2023-08-27T16:50:07Z

python/paddle/nn/initializer/xavier.py

+            >>> # inear.weight:  [[ 0.06910077 -0.18103665]
+            >>> #                 [-0.02546741 -1.0402188 ]]
+            >>> # linear.bias:  [-0.5012929   0.12418364]
+
+            >>> res = linear(data)
+            >>> # res:  [[[-0.4576595 -1.0970719]]
+            >>> #        [[-0.4576595 -1.0970719]]
+            >>> #        [[-0.4576595 -1.0970719]]]


同理，如无特殊情况，请勿使用 # 的注释方式提供输出值，修改方式和上述的 Uniform 一样

@megemini

@megemini @SigureMo @sunzhongkai588

megemini · 2023-08-28T07:26:03Z

python/paddle/nn/functional/common.py

+            >>> for i in range(2):
+            >>>     for j in range(3):
+            >>>         print(x[i,j,:,:])
+            >>>         print(y_train[i,j,:,:]) # may all 0
+            >>>         print(y_test[i,j,:,:])


>>> for i in range(2): ... for j in range(3): ... print(x[i,j,:,:]) ... print(y_train[i,j,:,:]) # may all 0 ... print(y_test[i,j,:,:])

请问这个print的结果要放吗

不用了，for 里面这么多 print ，用注释也行～看的明白为主～

megemini · 2023-08-28T07:27:13Z

python/paddle/nn/functional/common.py

+            >>> import paddle
+
+            >>> x = paddle.randn((3, 2), dtype="float32")
+            >>> print(x)


加个 seed ～

megemini · 2023-08-28T07:29:06Z

python/paddle/nn/functional/common.py

-            # y.shape = [2,3,4,5]
+            >>> x = paddle.randn([2,3*2*2,12])
+            >>> y = F.fold(x, output_sizes=[4, 5], kernel_sizes=2)
+            >>> # y.shape = [2,3,4,5]


>>> print(y.shape) [2, 3, 4, 5]

megemini · 2023-08-28T07:38:15Z

python/paddle/nn/functional/flash_attention.py

+            >>> # required: skiptest
+            >>> import paddle

-            q = paddle.rand((1, 128, 2, 16), dtype=paddle.float16)
+            >>> q = paddle.rand((1, 128, 2, 16), dtype=paddle.float16)

-            output = paddle.nn.functional.flash_attention(q, q, q, 0.9, False, False)
-            print(output)
+            >>> output = paddle.nn.functional.flash_attention(q, q, q, 0.9, False, False)
+            >>> print(output)


这段代码没必要 skip，把旧的 skiptest 去掉。

应该没必要使用 float16, dtype 也可以去掉。

flash_attention 没有暴露出去，可以用 paddle.nn.functional.flash_attention.flash_attention 。

这个 output 有点多，可以考虑：

加 seed

改小点 q

打印 output 的其他信息

直接不用 print 了

megemini · 2023-08-28T07:38:41Z

python/paddle/nn/functional/flash_attention.py

+            >>> # required: skiptest
+            >>> import paddle

-            q = paddle.rand((1, 128, 2, 16), dtype=paddle.float16)
+            >>> q = paddle.rand((1, 128, 2, 16), dtype=paddle.float16)

-            output = paddle.nn.functional.flash_attn_unpadded(q, q, q, 0.9, False, False)
-            print(output)
+            >>> output = paddle.nn.functional.flash_attn_unpadded(q, q, q, 0.9, False, False)
+            >>> print(output)


megemini · 2023-08-28T07:41:33Z

python/paddle/nn/initializer/uniform.py

+            >>> import paddle
+
+            >>> data = paddle.ones(shape=[3, 1, 2], dtype='float32')
+            >>> weight_attr = paddle.framework.ParamAttr(
+            ...     name="linear_weight",
+            ...     initializer=paddle.nn.initializer.Uniform(low=-0.5, high=0.5))
+            >>> bias_attr = paddle.framework.ParamAttr(
+            ...     name="linear_bias",
+            ...     initializer=paddle.nn.initializer.Uniform(low=-0.5, high=0.5))
+            >>> linear = paddle.nn.Linear(2, 2, weight_attr=weight_attr, bias_attr=bias_attr)
+            >>> print(linear.weight)


Uniform 是随机的，需要加个 seed ～

megemini · 2023-08-28T07:42:16Z

python/paddle/nn/initializer/xavier.py

+            >>> import paddle
+
+            >>> data = paddle.ones(shape=[3, 1, 2], dtype='float32')
+            >>> weight_attr = paddle.framework.ParamAttr(
+            ...     name="linear_weight",
+            ...     initializer=paddle.nn.initializer.XavierNormal())
+            >>> bias_attr = paddle.framework.ParamAttr(
+            ...     name="linear_bias",
+            ...     initializer=paddle.nn.initializer.XavierNormal())
+            >>> linear = paddle.nn.Linear(2, 2, weight_attr=weight_attr, bias_attr=bias_attr)
+            >>> print(linear.weight)


megemini · 2023-08-28T07:42:41Z

python/paddle/nn/initializer/xavier.py

+            >>> import paddle
+
+            >>> data = paddle.ones(shape=[3, 1, 2], dtype='float32')
+            >>> weight_attr = paddle.framework.ParamAttr(
+            ...     name="linear_weight",
+            ...     initializer=paddle.nn.initializer.XavierUniform())
+            >>> bias_attr = paddle.framework.ParamAttr(
+            ...     name="linear_bias",
+            ...     initializer=paddle.nn.initializer.XavierUniform())
+            >>> linear = paddle.nn.Linear(2, 2, weight_attr=weight_attr, bias_attr=bias_attr)


同上～另外，输出 print 一下～

@megemini

@megemini @SigureMo @sunzhongkai588 flash_attention.pyflash_attention 没有暴露出去，可以用 paddle.nn.functional.flash_attention.flash_attention 。这个真不会改

sunzhongkai588 · 2023-08-29T10:12:49Z

python/paddle/nn/functional/common.py

+        >>> print(label)
+        Tensor(shape=[10], dtype=int64, place=Place(cpu), stop_gradient=True,
+        [10, 3 , 11, 14, 15, 15, 7 , 12, 5 , 13])
+        >>> print(remapped_label)
+        Tensor(shape=[10], dtype=int64, place=Place(cpu), stop_gradient=True,
+        [3, 0, 4, 7, 8, 8, 2, 5, 1, 6])
+        >>> print(sampled_class_index)
+        Tensor(shape=[9], dtype=int64, place=Place(cpu), stop_gradient=True,
+        [3 , 5 , 7 , 10, 11, 12, 13, 14, 15])


这里的输出结果都错了，再核对一下

sunzhongkai588 · 2023-08-29T10:15:58Z

python/paddle/nn/functional/common.py

+            >>> print(bias)
+            Tensor(shape=[4], dtype=float32, place=Place(cpu), stop_gradient=True,
+            [1., 1., 1., 1.])
+            >>> y = paddle.nn.functional.linear(x, weight, bias)


下面得加输出代码 print(y)

sunzhongkai588 · 2023-08-29T10:23:26Z

python/paddle/nn/functional/activation.py

+            >>> import paddle
+            >>> import paddle.nn.functional as F
+
+            >>> input_tensor = paddle.to_tensor([[[[-2.0,  3.0, -4.0,  5.0],


前面应该加seed，之前review的时候也提到了，rrelu是有随机性的

sunzhongkai588 · 2023-08-29T10:24:09Z

python/paddle/nn/initializer/xavier.py

-            #        [[ 1.0481861 -2.1206741]]]
+            >>> import paddle
+
+            >>> data = paddle.ones(shape=[3, 1, 2], dtype='float32')


同理，前面加seed，并检查一下输出

@megemini

@megemini @SigureMo @sunzhongkai588

sunzhongkai588 · 2023-08-30T06:22:52Z

python/paddle/nn/functional/common.py

+            Tensor(shape=[3, 4], dtype=float32, place=Place(cpu), stop_gradient=True,
+            [[1.31539762, 1.31539762, 1.31539762, 1.31539762],
+             [0.18737471, 0.18737471, 0.18737471, 0.18737471],
+             [1.23271096, 1.23271096, 1.23271096, 1.23271096]])


y的输出再校对一下，好像是错的

我测出来也应该是

Tensor(shape=[3, 4], dtype=float32, place=Place(cpu), stop_gradient=True, [[ 1.58740902, 1.58740902, 1.58740902, 1.58740902], [ 1.08524013, 1.08524013, 1.08524013, 1.08524013], [-0.67769694, -0.67769694, -0.67769694, -0.67769694]])

希望可以合入了

megemini · 2023-08-30T07:29:12Z

python/paddle/nn/functional/common.py

+            >>> y_test = paddle.nn.functional.dropout2d(x, training=False) #test
+            ... for i in range(2):


for 前面应该是 >>>

2023-08-30 10:01:40 >>> 1 sample codes ran timeout 2023-08-30 10:01:40 paddle.nn.functional.dropout2d:1 - more than 10.0s

错误分析：

因为这里用的是 ...（既可以是语句，也可以是输出），所以 xdoctest 在 parse docstring 的时候并没有报错（SyntaxError）。

当 xdoctest 实际运行检查的时候，抛出异常（SyntaxError）。

由于目前的 sampcd_processor 用的是多进程/线程的方式，所以在子进程/线程中抛出异常会卡住。

由于目前的 sampcd_processor 使用了 TIMEOUT 机制，从而在上述异常卡住运行，并超过限制时间的时候，会抛出异常。

最后，此代码被判断为 TIMEOUT，与 CI 的结果一致。

如果要捕获 run 时候的异常，得要重新设计，感觉没啥必要，毕竟有 TIMEOUT 这个机制做保护，错误信息目前也能从日志中看到～

to @megemini 记录一下，后续注意～

所以改一下是吗

将...改为>>>

sunzhongkai588

LGTM for docs

…ePaddle#56440)

yuchen202 added 2 commits August 2, 2023 10:38

赛题五：将 xdoctest 引入到飞桨框架工作流中

962513e

[xdoctest] Modify it to meet the requirements

27cd6be

力所能及地改了一些

paddle-bot bot added contributor External developers status: proposed labels Aug 18, 2023

luotao1 added the HappyOpenSource Pro 进阶版快乐开源活动，更具挑战性的任务 label Aug 21, 2023

paddle-bot bot removed the status: proposed label Aug 21, 2023

luotao1 assigned luotao1, SigureMo and sunzhongkai588 Aug 21, 2023

yuchen202 mentioned this pull request Aug 21, 2023

Xdoctest #55973

Closed

yuchen202 changed the title ~~Test~~ 修改示例代码，使其通过xdoctest检查 Aug 23, 2023

再次修改

37ca6a3

yuchen202 changed the title ~~修改示例代码，使其通过xdoctest检查~~ [xdoctest] reformat example code with google style in No.36-43 Aug 23, 2023

luotao1 mentioned this pull request Aug 23, 2023

[xdoctest] 分批次修改已有代码的示例 #55629

Closed

yuchen202 closed this Aug 23, 2023

yuchen202 reopened this Aug 25, 2023

这个是之前本地备份的时候多的文件，要删去

8e534c3

sunzhongkai588 reviewed Aug 27, 2023

View reviewed changes

谢谢孙师傅，我改了一些

0e3c484

@megemini @SigureMo @sunzhongkai588

megemini reviewed Aug 28, 2023

View reviewed changes

8.29更新

8bc617f

@megemini @SigureMo @sunzhongkai588 flash_attention.pyflash_attention 没有暴露出去，可以用 paddle.nn.functional.flash_attention.flash_attention 。这个真不会改

sunzhongkai588 reviewed Aug 29, 2023

View reviewed changes

8.30修改

63db688

@megemini @SigureMo @sunzhongkai588

sunzhongkai588 reviewed Aug 30, 2023

View reviewed changes

8.30下午修改

d9ce960

希望可以合入了

megemini reviewed Aug 30, 2023

View reviewed changes

... for i in range(2):

d2bf2a8

将...改为>>>

sunzhongkai588 approved these changes Aug 31, 2023

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luotao1 merged commit 0a15b0d into PaddlePaddle:develop Aug 31, 2023

BeingGod pushed a commit to BeingGod/Paddle that referenced this pull request Sep 9, 2023

[xdoctest] reformat example code with google style in No.36-43 (Paddl…

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[xdoctest] reformat example code with google style in No.36-43 #56440

[xdoctest] reformat example code with google style in No.36-43 #56440

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	>>> label = paddle.randint(low=0, high=num_classes, shape=[batch_size], dtype='int64')
	>>> paddle.seed(2023)
	>>> label = paddle.randint(low=0, high=num_classes, shape=[batch_size], dtype='int64')

		>>> # required: distributed
		>>> # Multi GPU, test_class_center_sample.py

	>>> logits = paddle.randn([4, 6])
	>>> paddle.seed(2023)
	>>> logits = paddle.randn([4, 6])

		>>> final_sequences = paddle.nn.functional.gather_tree(ids, parents)
		>>> [[[2, 2], [1, 6]], [[3, 3], [6, 1]], [[0, 1], [9, 0]]]

-            >>> # linear.weight:  [[-0.46245047  0.05260676]
-            >>> #                  [ 0.38054508  0.29169726]]
-            >>> # linear.bias:  [-0.2734719   0.23939109]
-            >>> res = linear(data)
-            >>> # res:  [[[-0.3553773  0.5836951]]
-            >>> #        [[-0.3553773  0.5836951]]
-            >>> #        [[-0.3553773  0.5836951]]]
+            >>> print(linear.weight)
+            Parameter containing:
+            Tensor(shape=[2, 2], dtype=float32, place=Place(cpu), stop_gradient=False,
+                   [[ 0.36583614,  0.02014720],
+                    [-0.24039063,  0.40525323]])
+            >>> print(linear.bias)
+            Parameter containing:
+            Tensor(shape=[2], dtype=float32, place=Place(cpu), stop_gradient=False,
+                   [-0.07599911, -0.09358713])
+            >>> res = linear(data)
+            >>> print(res)
+            Tensor(shape=[3, 1, 2], dtype=float32, place=Place(cpu), stop_gradient=False,
+                   [[[0.04944640, 0.33181331]],
+                    [[0.04944640, 0.33181331]],
+                    [[0.04944640, 0.33181331]]])

		>>> y_test = paddle.nn.functional.dropout2d(x, training=False) #test
		... for i in range(2):

[xdoctest] reformat example code with google style in No.36-43 #56440

[xdoctest] reformat example code with google style in No.36-43 #56440

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yuchen202 commented Aug 18, 2023

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megemini commented Aug 23, 2023

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sunzhongkai588 Aug 27, 2023 •

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