How to read the multi-layer perceptrons model in Golang written using python

[palaiya]

I am using the wrapper of scikit-learn Multilayer Perceptron in Python https://github.com/aigamedev/scikit-neuralnetwork to train the neural network and save it to a file. Now, I want to expose it on production to predict in real time. So, I was thinking to use Golang for better concurrency than Python. Hence, my question is whether can we read the model using this library written using Python or above wrapper? The code below I am using for training the model and last three lines I want to port to GOLang to expose it on production

import pickle
import numpy as np
import pandas as pd
from sknn.mlp import Classifier, Layer
from sklearn.model_selection import train_test_split
from sklearn.metrics import accuracy_score

f = open("TrainLSDataset.csv")
data = np.loadtxt(f,delimiter = ',')

x = data[:, 1:]
y = data[:, 0]
X_train, X_test, y_train, y_test = train_test_split(x, y, test_size=0.3)

nn = Classifier(
    layers=[                    
        Layer("Rectifier", units=5),
        Layer("Softmax")],
    learning_rate=0.001,
    n_iter=100)

nn.fit(X_train, y_train)
filename = 'finalized_model.txt'
pickle.dump(nn, open(filename, 'wb'))

**#Below code i want to write in GoLang for exposing it on Production** :
loaded_model = pickle.load(open(filename, 'rb'))
result = loaded_model.score(X_test, y_test)
y_pred = loaded_model.predict(X_test)