#!/usr/bin/python
# -*- coding: utf-8 -*-
u"""
Copyright (c) 2016 Masaru Morita

This software is released under the MIT License.
See LICENSE file included in this repository.
"""

import csv
import sys
import random

sys.path.append('../util')
from ActivationFunction import Softmax
from GaussianDistribution import GaussianDistribution

class MutliLayerPerceptrons:
    u"""
    Class for MutliLayerPerceptrons
    """

    def __init__(self, dim_input_signal, dim_hidden, dim_output_signal, rand_obj):

        self.dim_input_signal = dim_input_signal
        self.dim_hidden = dim_hidden
        self.dim_output_signal = dim_output_signal

        self.weights = [[0] * dim_input_signal for i in range(dim_output_signal)]
        self.biases = [0] * dim_output_signal

        if rand_obj is None:
            rand_obj = random()

        self.rand_obj = rand_obj

if __name__ == '__main__':
    CNT_PATTERN = 2
    CNT_TRAIN_DATA = 4 # number of training data
    CNT_TEST_DATA = 4 # number of test data
    DIM_INPUT_SIGNAL = 2 # dimensions of input data
    DIM_HIDDEN = 3 # dimensions of hidden
    DIM_OUTPUT_SIGNAL = CNT_PATTERN # dimensions of output data

    rand_obj = random.Random()
    rand_obj.seed(1234)

    classifier = MutliLayerPerceptrons(DIM_INPUT_SIGNAL, DIM_HIDDEN, DIM_OUTPUT_SIGNAL, rand_obj)



@@ -241,101 +241,8 @@
 il')
-%0Afrom ActivationFunction import Softmax%0Afrom GaussianDistribution import GaussianDistribution
 %0A%0Acl

Delete unnecessary import modules