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# torch.nn.functional.max_pool3d

torch.nn.functional.max_pool3d(input, kernel_size, stride=None, padding=0, dilation=1, ceil_mode=False, return_indices=False)

  Applies a 3D max pooling over an input signal composed of several input planes.

  Note

  The order of `ceil_mode` and `return_indices` is different from what seen in `MaxPool3d`, and will change in a future release.

  See `MaxPool3d` for details.

  Parameters:

    - input – input tensor (minibatch,in_channels,i D,i H,i W)(\text{minibatch} , \text{in\_channels} , iD, iH , iW)(minibatch,in_channels,i D,i H,iW), minibatch dim optional.

    - kernel_size – size of the pooling region. Can be a single number or a tuple (kT, kH, kW)

    - stride – stride of the pooling operation. Can be a single number or a tuple (sT, sH, sW). Default: `kernel_size`

    - padding – Implicit negative infinity padding to be added on both sides, must be >= 0 and <= kernel_size / 2.

    - dilation – The stride between elements within a sliding window, must be > 0.

    - ceil_mode – If `True`, will use ceil instead of floor to compute the output shape. This ensures that every element in the input tensor is covered by a sliding window.

    - return_indices – If `True`, will return the argmax along with the max values. Useful for `torch.nn.functional.max_unpool3d` later

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