def __init__(self):
'''
You can add more arguments for examples actions and model paths.
You need to load your model here.
actions: provides indices for actions.
it has the same order as the data/vocabs.actions file.
'''
self.index_of_words = getIndex(filename='data/vocabs.word')
self.index_of_pos = getIndex(filename='data/vocabs.pos')
self.index_of_labels = getIndex(filename='data/vocabs.labels')
self.index_of_actions = getIndex(filename='data/vocabs.actions')
index_of_actions_items = self.index_of_actions.items()
sorted_index_of_actions = sorted(index_of_actions_items,
key=lambda x: x[1])
sorted_actions = [x[0] for x in sorted_index_of_actions]
self.actions = sorted_actions
self.model = load_model('models/model3')
# -*- coding: utf-8 -*-
"""
Created on Wed Apr 24 01:57:28 2019
@author: yiwenzhang
"""
import tensorflow as tf
import numpy as np
from utils_1 import Indexing, getIndex, loadnew
import sys
from keras.models import Model
from keras.layers import Dense, Input, Embedding, Reshape, Concatenate, Lambda
import keras
index_of_words = getIndex(filename='./data/vocabs.word')
index_of_labels = getIndex(filename='./data/vocabs.labels')
index_of_pos = getIndex(filename='./data/vocabs.pos')
index_of_actions = getIndex(filename='./data/vocabs.actions')
Indexing(
file1='./data/train.data',
file2='./data/train_with_indices.data',
indices=[index_of_words, index_of_pos, index_of_labels, index_of_actions])
train_data, train_labels = loadnew(filename='./data/train_with_indices.data')
def output_shape_words(input_shape):
assert (len(list(input_shape)) == 2)
assert (input_shape[1] == 52)
return (input_shape[0], 20)