class_docstr: Applies max pooling operation for 3D data (spatial or spatio-temporal).
  Data format currently supported for this layer is dim_ordering='th' (Channel First).
  Border mode currently supported for this layer is 'valid'.
  The input of this layer should be 5D.
  
  When you use this layer as the first layer of a model, you need to provide the argument
  input_shape (a shape tuple, does not include the batch dimension).
  
  # Arguments
  pool_size: Int tuple of length 3. Factors by which to downscale (dim1, dim2, dim3).
             Default is (2, 2, 2), which will halve the image in each dimension.
  strides: Int tuple of length 3. Stride values.
           Default is None, and in this case it will be equal to pool_size.
  border_mode: Only 'valid' is supported for now.
  dim_ordering: Format of input data. Only 'th' (Channel First) is supported for now.
  input_shape: A shape tuple, not including batch.
  name: String to set the name of the layer.
        If not specified, its name will by default to be a generated string.
  
  >>> maxpooling3d = MaxPooling3D((2, 1, 3), input_shape=(3, 32, 32, 32))
  creating: createZooKerasMaxPooling3D
code: def __init__(
      self,
      pool_size=(2, 2, 2),
      strides=None,
      border_mode="valid",
      dim_ordering="th",
      input_shape=None,
      **kwargs,
  ):
      if border_mode != "valid":
          raise ValueError(
              "For MaxPooling3D, only border_mode='valid' is supported for now"
          )
      super(MaxPooling3D, self).__init__(
          None,
          pool_size,
          strides,
          dim_ordering,
          list(input_shape) if input_shape else None,
          **kwargs,
      )
  
imports: import sys
  from ..engine.topology import ZooKerasLayer
label_desc: Use image node_id 1 to create a new MaxPooling3D object from inherited base classes: ZooKerasLayer with example: obj = MaxPooling3D(pool_size, strides, border_mode, dim_ordering, input_shape)