【PaddlePaddle Hackathon 2】8、为 Paddle 新增 nanmean API#40472
【PaddlePaddle Hackathon 2】8、为 Paddle 新增 nanmean API#40472jeff41404 merged 49 commits intoPaddlePaddle:developfrom
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| return sum(tmp_tensor, axis, dtype, keepdim, name) | ||
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| def nanmean(x,axis=None,keepdim=None,name=None): |
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keepdim=False is better？keep same with other API？
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thank you for your suggestion! keep same with other API is the better way. i will update this
| axis = [axis] | ||
| if axis == None: | ||
| return paddle.mean(x[~paddle.isnan(x)], keepdim=keepdim,name=name) | ||
| check_variable_and_dtype(x, 'x/input', |
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just 'x' instead of 'x/input'?
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this is refer to the code of paddle.mean.
'x/input' seems to be used only as a input name when raise a type/dtype error.
| if axis == None: | ||
| return paddle.mean(x[~paddle.isnan(x)], keepdim=keepdim,name=name) | ||
| check_variable_and_dtype(x, 'x/input', | ||
| ['uint16', 'float16', 'float32', 'float64'], |
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dtype should be the same to description of x above. eg: 'uint16' is not in "x (Tensor): The input Tensor with data type float32, float64."
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This is refer to the code of paddle.mean
Although it require the input tensor must with data type of float32/64, but it also check allow data type of 'uint16' and 'float16' code is here.
Because of the issus describe here(paddle.nanmean extends the functionality of the paddle.mean API), so i just follow the code of paddle.mean
| if axis == None: | ||
| return paddle.mean(x[~paddle.isnan(x)], keepdim=keepdim,name=name) |
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can the logic of code L1041~L1042 below cover this branch? we need to handle the condition 'axis == None' alone?
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thank you for your suggestion!
the logic of code L1041~L1042 below can cover this branch.
we don't need handle this condition alone.
i will take this advise and update this problem.
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| def setUp(self): | ||
| self.x_shape = [2, 3, 4, 5] | ||
| self.x = np.random.uniform(-1, 1, self.x_shape).astype(np.float32) |
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self.x does not have 'nan', we should cover all the test case in rfcs
also should include check gradient
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thanks for your suggestion! i will cover all the test case in next update.
but i am confused in check gradient, because i can't find the example of check gradient in the paddle.mean test file test_mean_op.py .
I will appreciate it if you can give me a example.
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hi~有些细节需要注意一下 @Li-fAngyU |
Li-fAngyU
changed the title
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@Ligoml Done! |
修改了nanmean的axis参数的文档描述。
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updata nanmean's sample code (:name: code-example1)
修改nanmean的example code 错误
update example code
update example code of nanmean
5 participants
PR types
New features
PR changes
APIs
Describe
ISSUE链接:#40327
RFC的PR链接:PaddlePaddle/community#48
中文文档PR链接:PaddlePaddle/docs#4294
为 Paddle 新增 nanmean API
paddle.nanmean 扩展了 paddle.mean API 的功能，如果输入Tensor中有nan值， paddle.mean在计算中会将涉及nan值的结果都置为nan，而 paddle.nanmean 会跳过nan值。比如输入数据 x = [[nan, 1. , 2. ], [3. , 4. , 5. ]]，x.mean() 得到 [nan]，x.mean(0) 得到 [nan, 2.5, 3.5]，x.nanmean() 得到 [3.]，x.nanmean(0) 得到 [3., 2.5, 3.5]。此API需支持的调用路径为：paddle.nanmean 和 Tensor.nanmean 。