Conv2dWithSamePadding¶
-
class
Conv2dWithSamePadding
(in_channels, out_channels, kernel_size, stride=1, padding=0, dilation=1, groups=1, bias=True)[source]¶ Bases:
sphinx.ext.autodoc.importer._MockObject
A Convolution which also accepts ‘same’ as valid padding to calculate the necessary padding during forward.
Note
Possible loss of throughput if
padding='same'
due to the additional padding calculationSee also
torch.nn.modules.conv.Conv2d
Parameters: - in_channels (int) – channels of convolution input
- out_channels (int) – number of filters and output channes
- kernel_size (int or Iterable) – specifies the kernel dimensions. If int: same kernel size is used for all dimensions
- stride (int or Iterable, optional) – specifies the convolution strides (default: 1) If int: same stride is used for all dimensions
- padding (int or Iterable or str, optional) –
specifies the input padding (default: 0) If int: same padding is used for all dimensions If str: only supported string is ‘same’, which calculates the
necessary padding during forward - dilation (int or Iterable, optional) – specifies the convolution dilation (default: 1) If int: same dilation is used for all dimensions
- groups (int, optional) – number of convolution groups (default: 1)
- bias (bool, optional) – whether to include a bias or not (default: True)