Example:

      For scale:

      if align_corners = True && out_size > 1 :

        scale_factor = (in_size-1.0)/(out_size-1.0)

      else:

        scale_factor = float(in_size/out_size)

      Bilinear interpolation:

        if:
            align_corners = False , align_mode = 0

            input : (N,C,D_in,H_in,W_in)
            output: (N,C,D_out,H_out,W_out) where:

            D_out = (D_{in}+0.5) * scale_{factor} - 0.5
            H_out = (H_{in}+0.5) * scale_{factor} - 0.5
            W_out = (W_{in}+0.5) * scale_{factor} - 0.5


        else:

            input : (N,C,D_in,H_in,W_in)
            output: (N,C,D_out,H_out,W_out) where:

            D_out = D_{in} * scale_{factor}
            H_out = H_{in} * scale_{factor}
            W_out = W_{in} * scale_{factor}

import paddle.fluid as fluid
input = fluid.layers.data(name="input", shape=[3,6,9,11], dtype="float32")
# input.shape = [-1, 3, 6, 9, 11], where -1 indicates batch size, and it will get the exact value in runtime.

out0 = fluid.layers.resize_trilinear(input, out_shape=[12, 12, 12])
# out0.shape = [-1, 3, 12, 12, 12], it means out0.shape[0] = input.shape[0] in runtime.

# out_shape is a list in which each element is a integer or a tensor Variable
dim1 = fluid.layers.data(name="dim1", shape=[1], dtype="int32", append_batch_size=False)
out1 = fluid.layers.resize_trilinear(input, out_shape=[12, dim1, 4])
# out1.shape = [-1, 3, 12, -1, 4]

# out_shape is a 1-D tensor Variable
shape_tensor = fluid.layers.data(name="shape_tensor", shape=[3], dtype="int32", append_batch_size=False)
out2 = fluid.layers.resize_trilinear(input, out_shape=shape_tensor)
# out2.shape = [-1, 3, -1, -1, -1]

# when use actual_shape
actual_shape_tensor = fluid.layers.data(name="actual_shape_tensor", shape=[3], dtype="int32", append_batch_size=False)
out3 = fluid.layers.resize_trilinear(input, out_shape=[4, 4, 8], actual_shape=actual_shape_tensor)
# out3.shape = [-1, 3, 4, 4, 8]

# scale is a Variable
scale_tensor = fluid.layers.data(name="scale", shape=[1], dtype="float32", append_batch_size=False)
out4 = fluid.layers.resize_trilinear(input, scale=scale_tensor)
# out4.shape = [-1, 3, -1, -1, -1]