tf.nn.max_pool3d

tf.nn.max_pool3d(
    input,
    ksize,
    strides,
    padding,
    data_format='NDHWC',
    name=None
)

Defined in tensorflow/python/ops/gen_nn_ops.py.

See the guide: Neural Network > Pooling

Performs 3D max pooling on the input.

Args:

• input: A Tensor. Must be one of the following types: half, bfloat16, float32. Shape [batch, depth, rows, cols, channels] tensor to pool over.
• ksize: A list of ints that has length >= 5. 1-D tensor of length 5. The size of the window for each dimension of the input tensor. Must have ksize[0] = ksize[4] = 1.
• strides: A list of ints that has length >= 5. 1-D tensor of length 5. The stride of the sliding window for each dimension of input. Must have strides[0] = strides[4] = 1.
• padding: A string from: "SAME", "VALID". The type of padding algorithm to use.
• data_format: An optional string from: "NDHWC", "NCDHW". Defaults to "NDHWC". The data format of the input and output data. With the default format "NDHWC", the data is stored in the order of: [batch, in_depth, in_height, in_width, in_channels]. Alternatively, the format could be "NCDHW", the data storage order is: [batch, in_channels, in_depth, in_height, in_width].
• name: A name for the operation (optional).

Returns:

A Tensor. Has the same type as input.