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55280837
编写于
6月 07, 2022
作者:
W
wangguanzhong
提交者:
GitHub
6月 07, 2022
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fix conv3d doc, test=document_fix (#43253)
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aec49361
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python/paddle/nn/functional/conv.py
python/paddle/nn/functional/conv.py
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python/paddle/nn/functional/conv.py
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@@ -1244,10 +1244,10 @@ def conv3d(x,
where M is the number of filters(output channels), g is the number of groups,
kD, kH, kW are the filter's depth, height and width respectively.
bias (Tensor, optional): The bias, a Tensor of shape [M, ].
stride (int|list|tuple): The stride size. It means the stride in convolution. If stride is a
stride (int|list|tuple
, optional
): The stride size. It means the stride in convolution. If stride is a
list/tuple, it must contain three integers, (stride_depth, stride_height, stride_width).
Otherwise, stride_depth = stride_height = stride_width = stride. Default: stride = 1.
padding (string|int|list|tuple): The padding size. It means the number of zero-paddings
padding (string|int|list|tuple
, optional
): The padding size. It means the number of zero-paddings
on both sides for each dimension. If `padding` is a string, either 'VALID' or
'SAME' which is the padding algorithm. If padding size is a tuple or list,
it could be in three forms: `[pad_depth, pad_height, pad_width]` or
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@@ -1257,20 +1257,20 @@ def conv3d(x,
when `data_format` is `"NDHWC"`, `padding` can be in the form
`[[0,0], [pad_depth_front, pad_depth_back], [pad_height_top, pad_height_bottom], [pad_width_left, pad_width_right], [0,0]]`.
Default: padding = 0.
dilation (int|list|tuple): The dilation size. It means the spacing between the kernel points.
dilation (int|list|tuple
, optional
): The dilation size. It means the spacing between the kernel points.
If dilation is a list/tuple, it must contain three integers, (dilation_depth, dilation_height,
dilation_width). Otherwise, dilation_depth = dilation_height = dilation_width = dilation.
Default: dilation = 1.
groups (int): The groups number of the Conv3D Layer. According to grouped
groups (int
, optional
): The groups number of the Conv3D Layer. According to grouped
convolution in Alex Krizhevsky's Deep CNN paper: when group=2,
the first half of the filters is only connected to the first half
of the input channels, while the second half of the filters is only
connected to the second half of the input channels. Default: groups=1
data_format (str, optional): Specify the data format of the input, and the data format of the output
will be consistent with that of the input. An optional string from: `"NC
HW"`, `"N
HWC"`.
The default is `"NC
HW"`. When it is `"NC
HW"`, the data is stored in the order of:
`[batch_size, input_channels, input_height, input_width]`.
name(str|None): For detailed information, please refer
will be consistent with that of the input. An optional string from: `"NC
DHW"`, `"ND
HWC"`.
The default is `"NC
DHW"`. When it is `"NCD
HW"`, the data is stored in the order of:
`[batch_size, input_channels, input_
depth, input_
height, input_width]`.
name(str|None
, optional
): For detailed information, please refer
to :ref:`api_guide_Name`. Usually name is no need to set and
None by default.
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