mindspore.nn.ReplicationPad1d
- class mindspore.nn.ReplicationPad1d(padding)[source]
Pad on W dimension of input x according to padding.
- Parameters
The padding size to pad the last dimension of x .
If padding is an integer, all directions will be padded with the same size.
If padding is a tuple, uses \((pad_{left}, pad_{right})\) to pad.
- Inputs:
x (Tensor) - 2D or 3D, shape: \((C, W_{in})\) or \((N, C, W_{in})\).
- Outputs:
Tensor, after padding. Shape: \((C, W_{out})\) or \((N, C, W_{out})\), where \(W_{out} = W_{in} + pad_{left} + pad_{right}\)
- Raises
TypeError – If padding is neither a tuple nor an int.
TypeError – If there is an element in padding that is not int.
ValueError – If padding is tuple and the length of padding is not divisible by 2.
ValueError – If padding is tuple and there is a dimension mismatch between the padding and the tensor.
- Supported Platforms:
GPU
Examples
>>> import numpy as np >>> import mindspore as ms >>> pad1d = ms.nn.ReplicationPad1d(2) >>> input = ms.Tensor(np.arange(0, 8).reshape(1, 2, 4), ms.float32) >>> print(input) [[[0. 1. 2. 3.] [4. 5. 6. 7.]]] >>> out = pad1d(input) >>> print(out) [[[0. 0. 0. 1. 2. 3. 3. 3.] [4. 4. 4. 5. 6. 7. 7. 7.]]] >>> pad1d = ms.nn.ReplicationPad1d((3, 1)) >>> out = pad1d(input) >>> print(out) [[[0. 0. 0. 0. 1. 2. 3. 3.] [4. 4. 4. 4. 5. 6. 7. 7.]]]