parameters: (inputs,
                    pool_size, strides,
                    padding='valid', data_format='channels_last',
                    name=None)
return_statement: return layer.apply(inputs)
docstring: Max pooling layer for 3D inputs (e.g. volumes).
  
    Arguments:
      inputs: The tensor over which to pool. Must have rank 5.
      pool_size: An integer or tuple/list of 3 integers:
        (pool_depth, pool_height, pool_width)
        specifying the size of the pooling window.
        Can be a single integer to specify the same value for
        all spatial dimensions.
      strides: An integer or tuple/list of 3 integers,
        specifying the strides of the pooling operation.
        Can be a single integer to specify the same value for
        all spatial dimensions.
      padding: A string. The padding method, either 'valid' or 'same'.
        Case-insensitive.
      data_format: A string. The ordering of the dimensions in the inputs.
        `channels_last` (default) and `channels_first` are supported.
        `channels_last` corresponds to inputs with shape
        `(batch, depth, height, width, channels)` while `channels_first`
        corresponds to inputs with shape
        `(batch, channels, depth, height, width)`.
      name: A string, the name of the layer.
  
    Returns:
      Output tensor.
docstring_summary: Max pooling layer for 3D inputs (e.g. volumes).
docstring_tokens: Max pooling layer for 3D inputs ( e . g . volumes ) .
function: def max_pooling3d(inputs,
                    pool_size, strides,
                    padding='valid', data_format='channels_last',
                    name=None):
    """Max pooling layer for 3D inputs (e.g. volumes).
  
    Arguments:
      inputs: The tensor over which to pool. Must have rank 5.
      pool_size: An integer or tuple/list of 3 integers:
        (pool_depth, pool_height, pool_width)
        specifying the size of the pooling window.
        Can be a single integer to specify the same value for
        all spatial dimensions.
      strides: An integer or tuple/list of 3 integers,
        specifying the strides of the pooling operation.
        Can be a single integer to specify the same value for
        all spatial dimensions.
      padding: A string. The padding method, either 'valid' or 'same'.
        Case-insensitive.
      data_format: A string. The ordering of the dimensions in the inputs.
        `channels_last` (default) and `channels_first` are supported.
        `channels_last` corresponds to inputs with shape
        `(batch, depth, height, width, channels)` while `channels_first`
        corresponds to inputs with shape
        `(batch, channels, depth, height, width)`.
      name: A string, the name of the layer.
  
    Returns:
      Output tensor.
    """
    layer = MaxPooling3D(pool_size=pool_size, strides=strides,
                         padding=padding, data_format=data_format,
                         name=name)
    return layer.apply(inputs)
function_tokens: def max_pooling3d ( inputs , pool_size , strides , padding = 'valid' , data_format = 'channels_last' , name = None ) : layer = MaxPooling3D ( pool_size = pool_size , strides = strides , padding = padding , data_format = data_format , name = name ) return layer . apply ( inputs )