import cPickle

import gzip

import os

import sys

sys.setrecursionlimit(6000)

import time

import numpy as np

import theano

import theano.tensor as T

from theano.sandbox.rng_mrg import MRG_RandomStreams as RandomStreams

import random

from logistic_sgd import LogisticRegression

from mlp import HiddenLayer

from theano.tensor.signal import downsample

from random import shuffle

from term_def_seek.extract_term_def_wildly import load_concept_def

from scipy.stats import mode

from load_data import load_word2id,parse_individual_termPair,load_SNLI_dataset, write_predictions_to_analysis,load_wordnet_hyper_vs_all_with_words,load_word2vec, load_word2vec_to_init, load_EVAlution_hyper_vs_all_with_words

from common_functions import load_model_from_file,apk, Conv_for_Pair,dropout_layer, store_model_to_file, elementwise_is_two,Conv_with_Mask_with_Gate, Conv_with_Mask, create_conv_para, L2norm_paraList, ABCNN, create_ensemble_para, cosine_matrix1_matrix2_rowwise, Diversify_Reg, Gradient_Cost_Para, GRU_Batch_Tensor_Input_with_Mask, create_LSTM_para

'''

1, word tokenized the definition sentences, not good

2, use maxpool and attentive_maxpool

'''

def evaluate_lenet5(term1_str, term2_str):

print pred_i, prob_i

if __name__ == '__main__':

evaluate_lenet5(sys.argv[1], sys.argv[2])