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d8ea0168
编写于
8月 24, 2022
作者:
M
Megvii Engine Team
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docs(mge): update AvgPool2d & functional.nn.max_pool2d docstring
GitOrigin-RevId: d69c5b024f6b298b829dcfecdaf872d822b1dd00
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12 deletion
+11
-12
imperative/python/megengine/functional/nn.py
imperative/python/megengine/functional/nn.py
+5
-6
imperative/python/megengine/module/pooling.py
imperative/python/megengine/module/pooling.py
+6
-6
未找到文件。
imperative/python/megengine/functional/nn.py
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d8ea0168
...
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@@ -697,20 +697,19 @@ def avg_pool2d(
Refer to :class:`~.AvgPool2d` for more information.
Args:
inp: input tensor of shape :math:`(N, C, H_{
in}, W_{in})`
.
inp: input tensor of shape :math:`(N, C, H_{
\text{in}}, W_{\text{in}})`
.
kernel_size: size of the window used to calculate the average value.
stride: stride of the window. If not provided, its value is set to ``kernel_size``.
Default: ``None``
padding: implicit zero padding added on both sides. Default: :math:`0`
stride: stride of the window. Default value is ``kernel_size``.
padding: implicit zero padding added on both sides. Default: 0.
mode: whether to include the padding values while calculating the average, set
to "average" will do counting.
Default: "average_count_exclude_padding"
Returns:
output tensor of shape
`(N, C, H_{out}, W_{out
})`.
output tensor of shape
:math:`(N, C, H_{\text{out}}, W_{\text{out}
})`.
Examples:
>>> input =
t
ensor(np.arange(1 * 1 * 3 * 4).astype(np.float32).reshape(1, 1, 3, 4))
>>> input =
T
ensor(np.arange(1 * 1 * 3 * 4).astype(np.float32).reshape(1, 1, 3, 4))
>>> F.avg_pool2d(input, kernel_size=2, stride=2, padding=[1,0], mode="average")
Tensor([[[[0.25 1.25]
[6.5 8.5 ]]]], device=xpux:0)
...
...
imperative/python/megengine/module/pooling.py
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d8ea0168
...
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@@ -69,9 +69,9 @@ class MaxPool2d(_PoolNd):
class
AvgPool2d
(
_PoolNd
):
r
"""Applies a 2D average pooling over an input.
For instance, given an input of the size :math:`(N, C, H
, W
)` and
For instance, given an input of the size :math:`(N, C, H
_{\text{in}}, W_{\text{in}}
)` and
:attr:`kernel_size` :math:`(kH, kW)`, this layer generates the output of
the size :math:`(N, C, H_{
out}, W_{out
})` through a process described as:
the size :math:`(N, C, H_{
\text{out}}, W_{\text{out}
})` through a process described as:
.. math::
...
...
@@ -83,10 +83,10 @@ class AvgPool2d(_PoolNd):
Args:
kernel_size: the size of the window.
stride: the stride of the window. Default value is
kernel_size。
padding: implicit zero padding to be added on both sides.
mode: whether to
count padding values. "average" mode will do counting and
"average_count_exclude_padding" mode won't
do counting.
stride: the stride of the window. Default value is
``kernel_size``.
padding: implicit zero padding to be added on both sides.
Default: 0.
mode: whether to
include the padding values while calculating the average, set
to "average" will
do counting.
Default: "average_count_exclude_padding"
"""
...
...
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