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mindspore.nn.MaxPool2d

class mindspore.nn.MaxPool2d(kernel_size=1, stride=1, pad_mode='valid', data_format='NCHW')

Applies a 2D max pooling over an input Tensor which can be regarded as a composition of 2D planes.

Typically the input is of shape $(N_{in},C_{in},H_{in},W_{in})$, MaxPool2d outputs regional maximum in the $(H_{in},W_{in})$-dimension. Given kernel size $ks=(h_{ker},w_{ker})$ and stride $s=(s_0,s_1)$, the operation is as follows.

$$\text{output}(N_i,C_j,h,w)=\underset{m=0,\dots ,h_{ker}-1}{max}\underset{n=0,\dots ,w_{ker}-1}{max}\text{input}(N_i,C_j,s_0\times h+m,s_1\times w+n)$$

Note

pad_mode for training only supports “same” and “valid”.

Parameters

• kernel_size (Union[int, tuple[int]]) – The size of kernel used to take the max value, is an int number that represents height and width are both kernel_size, or a tuple of two int numbers that represent height and width respectively. Default: 1.

• stride (Union[int, tuple[int]]) – The distance of kernel moving, an int number that represents the height and width of movement are both stride, or a tuple of two int numbers that represent height and width of movement respectively. Default: 1.

• pad_mode (str) –

  The optional value for pad mode, is “same” or “valid”, not case sensitive. Default: “valid”.

  • same: The output shape is the same as the input shape evenly divided by stride.

  • valid: The possible largest height and width of output will be returned without padding. Extra pixels will be discarded.

• data_format (str) – The optional value for data format, is ‘NHWC’ or ‘NCHW’. Default: ‘NCHW’.

Inputs:

• x (Tensor) - Tensor of shape $(N,C_{in},H_{in},W_{in})$.

Outputs:

Tensor of shape $(N,C_{out},H_{out},W_{out})$.

Raises

• TypeError – If kernel_size or stride is neither int nor tuple.

• ValueError – If pad_mode is neither ‘valid’ nor ‘same’ with not case sensitive.

• ValueError – If data_format is neither ‘NCHW’ nor ‘NHWC’.

• ValueError – If kernel_size or stride is less than 1.

• ValueError – If length of shape of x is not equal to 4.

Supported Platforms:

Ascend GPU CPU

Examples

>>> pool = nn.MaxPool2d(kernel_size=3, stride=1)
>>> x = Tensor(np.random.randint(0, 10, [1, 2, 4, 4]), mindspore.float32)
>>> output = pool(x)
>>> print(output.shape)
(1, 2, 2, 2)