# declarative mode
import numpy as np
from paddle import fluid

x = fluid.data(name="x", shape=(-1, 3), dtype="float32")
y = fluid.layers.gelu(x)

place = fluid.CPUPlace()
exe = fluid.Executor(place)
start = fluid.default_startup_program()
main = fluid.default_main_program()

data = np.random.randn(2, 3).astype("float32")
exe.run(start)

y_np, = exe.run(main, feed={"x": data}, fetch_list=[y])

data
# array([[ 0.87165993, -1.0541513 , -0.37214822],
#         [ 0.15647964,  0.32496083,  0.33045998]], dtype=float32)
y_np
# array([[ 0.70456535, -0.15380788, -0.13207214],
#        [ 0.08796856,  0.20387867,  0.2080159 ]], dtype=float32)

# imperative mode
import numpy as np
from paddle import fluid
import paddle.fluid.dygraph as dg

data = np.random.randn(2, 3).astype("float32")
place = fluid.CPUPlace()
with dg.guard(place) as g:
    x = dg.to_variable(data)
    y = fluid.layers.gelu(x)
    y_np = y.numpy()
data
# array([[ 0.87165993, -1.0541513 , -0.37214822],
#        [ 0.15647964,  0.32496083,  0.33045998]], dtype=float32)
y_np
# array([[ 0.70456535, -0.15380788, -0.13207214],
#        [ 0.08796856,  0.20387867,  0.2080159 ]], dtype=float32)