avg_pool3d

paddle.nn.functional. avg_pool3d ( x, kernel_size: Size3, stride: Size3 | None = None, padding: _PaddingSizeMode | Size3 | Size6 = 0, ceil_mode: bool = False, exclusive: bool = True, divisor_override: float | None = None, data_format: DataLayout3D = 'NCDHW', name: str | None = None ) → Tensor [source]

This API implements average pooling 3d operation. See more details in AvgPool3D .

Parameters

  • x (Tensor) – The input tensor of pooling operator, which is a 5-D tensor with shape [N, C, D, H, W], where N represents the batch size, C represents the number of channels, D, H and W represent the depth, height and width of the feature respectively.

  • kernel_size (int|list|tuple) – The pool kernel size. If pool kernel size is a tuple or list, it must contain three integers, (kernel_size_Depth, kernel_size_Height, kernel_size_Width). Otherwise, the pool kernel size will be the cube of an int.

  • stride (int|list|tuple) – The pool stride size. If pool stride size is a tuple or list, it must contain three integers, [stride_Depth, stride_Height, stride_Width). Otherwise, the pool stride size will be a cube of an int.

  • padding (string|int|list|tuple) – The padding size. Padding could be in one of the following forms. 1. A string in [‘valid’, ‘same’]. 2. An int, which means the feature map is zero padded by size of padding on every sides. 3. A list[int] or tuple(int) whose length is 3, [pad_depth, pad_height, pad_weight] whose value means the padding size of each dimension. 4. A list[int] or tuple(int) whose length is 6. [pad_depth_front, pad_depth_back, pad_height_top, pad_height_bottom, pad_width_left, pad_width_right] whose value means the padding size of each side. 5. A list or tuple of pairs of integers. It has the form [[pad_before, pad_after], [pad_before, pad_after], …]. Note that, the batch dimension and channel dimension should be [0,0] or (0,0). The default value is 0.

  • ceil_mode (bool) – ${ceil_mode_comment}

  • exclusive (bool) – Whether to exclude padding points in average pooling mode, default is True.

  • divisor_override (int|float) –

  • data_format (string) – The data format of the input and output data. An optional string from: “NCDHW”, “NDHWC”. The default is “NCDHW”. When it is “NCDHW”, the data is stored in the order of: [batch_size, input_channels, input_depth, input_height, input_width].

  • name (str|None, optional) – For detailed information, please refer to api_guide_Name. Usually name is no need to set and None by default.

Returns

The output tensor of pooling result. The data type is same as input tensor.

Return type

Tensor

Examples

>>> import paddle

>>> x = paddle.uniform([1, 3, 32, 32, 32], paddle.float32)
>>> # avg pool3d
>>> out = paddle.nn.functional.avg_pool3d(x,
...                                       kernel_size = 2,
...                                       stride = 2,
...                                       padding=0)
>>> print(out.shape)
[1, 3, 16, 16, 16]