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mindspore.ops.max_pool3d

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mindspore.ops.max_pool3d(x, kernel_size, stride=None, padding=0, dilation=1, ceil_mode=False, return_indices=False)[source]

Performs a 3D max pooling on the input Tensor.

Typically the input is a Tensor with shape (Nin,Cin,Din,Hin,Win), outputs regional maximum in the (Din,Hin,Win)-dimension. Given kernel_size ks=(dker,hker,wker) and stride s=(s0,s1,s2), the operation is as follows:

output(Ni,Cj,d,h,w)=maxl=0,,dker1maxm=0,,hker1maxn=0,,wker1input(Ni,Cj,s0×d+l,s1×h+m,s2×w+n)
Parameters
  • x (Tensor) – Tensor of shape (Nin,Cin,Din,Hin,Win) with data type of int8, int16, int32, int64, uint8, uint16, uint32, uint64, float16, float32 or float64.

  • kernel_size (Union[int, tuple[int]]) – The size of kernel used to take the maximum value and arg value, is an int number that represents depth, height and width of the kernel, or a tuple of three int numbers that represent depth, height and width respectively.

  • stride (Union[int, tuple[int]]) – The distance of kernel moving, an int number that represents the depth, height and width of movement are both stride, or a tuple of three int numbers that represent depth, height and width of movement respectively. Default: None , which indicates the moving step is kernel_size .

  • padding (Union[int, tuple[int]]) – An int number that represents the depth, height and width of movement are both strides, or a tuple of three int numbers that represent depth, height and width of movement respectively. Default: 0 .

  • dilation (Union[int, tuple[int]]) – Control the stride of elements in the kernel. Default: 1 .

  • ceil_mode (bool) – Whether to use ceil instead of floor to calculate output shape. Default: False .

  • return_indices (bool) – Whether to output the indices of max value. Default: False .

Returns

If return_indices is False, return a Tensor output, else return a tuple (output, argmax).

  • output (Tensor) - Maxpooling result, with shape (Nout,Cout,Dout,Hout,Wout). It has the same data type as x.

Dout=Din+2×padding[0]dilation[0]×(kernel_size[0]1)1stride[0]+1
Hout=Hin+2×padding[1]dilation[1]×(kernel_size[1]1)1stride[1]+1
Wout=Win+2×padding[2]dilation[2]×(kernel_size[2]1)1stride[2]+1
  • argmax (Tensor) - Index corresponding to the maximum value. Data type is int64. It will be returned only when return_indices is True .

Raises
  • TypeError – If x is not a Tensor.

  • ValueError – If length of shape of x is not equal to 5.

  • TypeError – If kernel_size , stride , padding or dilation is not int or tuple.

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

  • ValueError – If padding is less than 0.

Supported Platforms:

Ascend GPU CPU

Examples

>>> import mindspore
>>> import numpy as np
>>> from mindspore import Tensor, ops
>>> x = Tensor(np.arange(2 * 1 * 2 * 2 * 2).reshape((2, 1, 2, 2, 2)), mindspore.float32)
>>> output_tensor, argmax = ops.max_pool3d(x, kernel_size=2, stride=1, padding=1, return_indices=True)
>>> print(output_tensor.shape)
(2, 1, 3, 3, 3)
>>> print(argmax.shape)
(2, 1, 3, 3, 3)