oneflow.nn.functional.pad¶
-
oneflow.nn.functional.
pad
()¶ Pads tensor.
- Padding size:
The padding size by which to pad some dimensions of
input
are described starting from the last dimension and moving forward. \(\left\lfloor\frac{\text{len(pad)}}{2}\right\rfloor\) dimensions ofinput
will be padded. For example, to pad only the last dimension of the input tensor, thenpad
has the form \((\text{padding_left}, \text{padding_right})\); to pad the last 2 dimensions of the input tensor, then use \((\text{padding_left}, \text{padding_right},\) \(\text{padding_top}, \text{padding_bottom})\); to pad the last 3 dimensions, use \((\text{padding_left}, \text{padding_right},\) \(\text{padding_top}, \text{padding_bottom}\) \(\text{padding_front}, \text{padding_back})\).- Padding mode:
See
oneflow.nn.ConstantPad2d
,oneflow.nn.ReflectionPad2d
, andoneflow.nn.ReplicationPad2d
for concrete examples on how each of the padding modes works. Constant padding is implemented for arbitrary dimensions. Replicate padding is implemented for padding the last 3 dimensions of 5D input tensor, or the last 2 dimensions of 4D input tensor, or the last dimension of 3D input tensor. Reflect padding is only implemented for padding the last 2 dimensions of 4D input tensor, or the last dimension of 3D input tensor.
- Parameters
For example:
>>> import oneflow as flow >>> import numpy as np >>> pad = [2, 2, 1, 1] >>> input = flow.tensor(np.arange(18).reshape((1, 2, 3, 3)).astype(np.float32)) >>> output = flow.nn.functional.pad(input, pad, mode = "replicate") >>> output.shape oneflow.Size([1, 2, 5, 7]) >>> output tensor([[[[ 0., 0., 0., 1., 2., 2., 2.], [ 0., 0., 0., 1., 2., 2., 2.], [ 3., 3., 3., 4., 5., 5., 5.], [ 6., 6., 6., 7., 8., 8., 8.], [ 6., 6., 6., 7., 8., 8., 8.]], [[ 9., 9., 9., 10., 11., 11., 11.], [ 9., 9., 9., 10., 11., 11., 11.], [12., 12., 12., 13., 14., 14., 14.], [15., 15., 15., 16., 17., 17., 17.], [15., 15., 15., 16., 17., 17., 17.]]]], dtype=oneflow.float32)
See
oneflow.nn.ConstantPad2d
,oneflow.nn.ReflectionPad2d
, andoneflow.nn.ReplicationPad2d
for concrete examples on how each of the padding modes works.