mindspore.nn.MaxUnpool1d

class mindspore.nn.MaxUnpool1d(kernel_size, stride=None, padding=0)[source]

Computes the inverse of mindspore.nn.MaxPool1d.

MaxUnpool1d keeps the maximal value and set all position of non-maximal values to zero. Typically the input is of shape $(N, C, H_{i n})$ or $(C, H_{i n})$ , and the output is of shape $(N, C, H_{o u t})$ or $(C, H_{o u t})$ . The operation is as follows.

\begin{array}{r} \begin{array}{ll} H_{o u t} = (H_{i n} - 1) \times s t r i d e [0] - 2 \times p a d d i n g [0] + k e r n e l_s i z e [0] \end{array} \end{array}

Parameters

kernel_size (Union[int, tuple[int]]) – The size of kernel used to take the maximum value.
stride (Union[int, tuple[int]]) – The distance of kernel moving, If stride is None, then stride equal to kernel_size. Default: None .
padding (Union[int, tuple[int]]) – The pad value to be filled. Default: 0 .

Inputs:

x (Tensor) - The input Tensor to invert. Tensor of shape $(N, C, H_{i n})$ or $(C, H_{i n})$ .
indices (Tensor) - Max values' index represented by the indices. Tensor of shape must be same with input 'x'. Values of indices must belong to $[0, H_{i n} - 1]$ . Data type must be in int32 or int64.
output_size (tuple[int], optional) - The output size. Default: None . If output_size is None, then the shape of output computed by kernel_size, stride and padding. If output_size is not None, then output_size must be $(N, C, H)$ , $(C, H)$ or $(H)$ and output_size must belong to $[(N, C, H_{o u t} - s t r i d e [0]), (N, C, H_{o u t} + s t r i d e [0])]$ .

Outputs:

Tensor, with shape $(N, C, H_{o u t})$ or $(C, H_{o u t})$ , with the same data type with x.

Raises

TypeError – If data type of x or indices is not supported.
TypeError – If kernel_size, stride or padding is neither an int nor a tuple.
ValueError – If numbers in stride, padding (also support 0 and (0)) or kernel_size is not positive.
ValueError – If the shapes of x and indices are not equal.
ValueError – If x whose length is not 2 or 3.
ValueError – If type of output_size is not tuple.
ValueError – If output_size whose length is not 0, 2 or 3.
ValueError – If output_size is not close to output size computed by attr kernel_size, stride, padding.

Supported Platforms:: GPU CPU

Examples

>>> import mindspore as ms
>>> import numpy as np
>>> x = ms.Tensor(np.array([[2, 4, 6, 8]]).astype(np.float32))
>>> indices = ms.Tensor(np.array([[1, 3, 5, 7]]).astype(np.int64))
>>> maxunpool1d = ms.nn.MaxUnpool1d(kernel_size =2, stride=2, padding=0)
>>> output = maxunpool1d(x, indices)
>>> print(output.asnumpy())
[[0. 2. 0. 4. 0. 6. 0. 8.]]