How to get or use network from nnp about nnabla HOT 3 CLOSED

def image():
     :
    x = nn.Variable((1,1,28,28))
    x.d = np.array(img) * (1.0 / 255.0)
    y = network(x, test=True)
    y.forward()
     :

def network(x, test=False):
    # Input:x -> 1,28,28
    # MaxPooling -> 1,14,14
    h = F.max_pooling(x, (2,2), (2,2))
    # Affine -> 100
    h = PF.affine(h, (100,), name='Affine')
    # ReLU
    h = F.relu(h, True)
    # Affine_2
    h = PF.affine(h, (1,), name='Affine_2')
    # Sigmoid
    h = F.sigmoid(h)
    return h

import nnabla as nn
import nnabla.functions as F
import nnabla.parametric_functions as PF
from nnabla.utils import nnp_graph

nnp = nnp_graph.NnpLoader('./result.nnp')
print(nnp.get_network_names())
graph = nnp.get_network('MainRuntime', batch_size=1)
x = graph.inputs['Input'][0]
print(x)
y = graph.outputs
print(y)

from nnabla.utils import nnp_graph
import numpy as np
from PIL import Image

nnp = nnp_graph.NnpLoader('./result.nnp')
graph = nnp.get_network('MainRuntime', batch_size=1)
# Input variable name
input = list(graph.inputs.keys())[0]
# Output variable name
output = list(graph.outputs.keys())[0]
# Get input and output
x = graph.inputs[input]
y = graph.outputs[output]
# Open image
img = Image.open('001.png')
# Transform
x.d = np.array(img) * (1.0 / 255.0)
# Forward
y.forward(clear_buffer=True)
print(y.d)