# coding: utf-8
from __future__ import division

import server.punctuator2.models as models
import server.punctuator2.data as data

import theano
import sys
import codecs

import theano.tensor as T
import numpy as np

from zope.interface import Interface, implementer
from server.adapter import *

MAX_SUBSEQUENCE_LEN = 200

def to_array(arr, dtype=np.int32):
    # minibatch of 1 sequence as column
    return np.array([arr], dtype=dtype).T

def convert_punctuation_to_readable(punct_token):
    if punct_token == data.SPACE:
        return " "
    else:
        return punct_token[0]

def restore_with_pauses(output_file, text, pauses, word_vocabulary, reverse_punctuation_vocabulary, predict_function):
    i = 0
    with codecs.open(output_file, 'w', 'utf-8') as f_out:
        while True:

            subsequence = text[i:i+MAX_SUBSEQUENCE_LEN]
            subsequence_pauses = pauses[i:i+MAX_SUBSEQUENCE_LEN]

            if len(subsequence) == 0:
                break

            converted_subsequence = [word_vocabulary.get(w, word_vocabulary[data.UNK]) for w in subsequence]

            y = predict_function(to_array(converted_subsequence), to_array(subsequence_pauses, dtype=theano.config.floatX))

            f_out.write(subsequence[0])

            last_eos_idx = 0
            punctuations = []
            for y_t in y:

                p_i = np.argmax(y_t.flatten())
                punctuation = reverse_punctuation_vocabulary[p_i]

                punctuations.append(punctuation)

                if punctuation in data.EOS_TOKENS:
                    last_eos_idx = len(punctuations) # we intentionally want the index of next element

            if subsequence[-1] == data.END:
                step = len(subsequence) - 1
            elif last_eos_idx != 0:
                step = last_eos_idx
            else:
                step = len(subsequence) - 1

            for j in range(step):
                f_out.write(" " + punctuations[j] + " " if punctuations[j] != data.SPACE else " ")
                if j < step - 1:
                    f_out.write(subsequence[1+j])

            if subsequence[-1] == data.END:
                break

            i += step

def restore(text, word_vocabulary, reverse_punctuation_vocabulary, predict_function):
    result = ""
    i = 0
    #with codecs.open(output_file, 'w', 'utf-8') as f_out:
    while True:

        subsequence = text[i:i+MAX_SUBSEQUENCE_LEN]

        if len(subsequence) == 0:
            break

        converted_subsequence = [word_vocabulary.get(w, word_vocabulary[data.UNK]) for w in subsequence]

        y = predict_function(to_array(converted_subsequence))

        result += subsequence[0]
        #print(subsequence[0])

        last_eos_idx = 0
        punctuations = []
        for y_t in y:

            p_i = np.argmax(y_t.flatten())
            punctuation = reverse_punctuation_vocabulary[p_i]

            punctuations.append(punctuation)

            if punctuation in data.EOS_TOKENS:
                last_eos_idx = len(punctuations) # we intentionally want the index of next element

        if subsequence[-1] == data.END:
            step = len(subsequence) - 1
        elif last_eos_idx != 0:
            step = last_eos_idx
        else:
            step = len(subsequence) - 1

        for j in range(step):
            result += " " + punctuations[j] + " " if punctuations[j] != data.SPACE else " "
            if j < step - 1:
                #print(subsequence[1+j])
                result += subsequence[1+j]

        if subsequence[-1] == data.END:
            return result

        i += step

@implementer(PunctuatorService)
class theanoPunctuator(object):

    def __init__(self, model_file):
        self.model_file = model_file

    def punctuate(self, input_text):

        output_file=""
        use_pauses = False

        x = T.imatrix('x')

        if use_pauses:

            p = T.matrix('p')

            print ("Loading model parameters...")
            net, _ = models.load(self.model_file, 1, x, p)

            print ("Building model...")
            predict = theano.function(
                inputs=[x, p],
                outputs=net.y
            )

        else:

            print ("Loading model parameters...")
            net, _ = models.load(self.model_file, 1, x)

            print ("Building model...")
            predict = theano.function(
                inputs=[x],
                outputs=net.y
            )

        word_vocabulary = net.x_vocabulary
        punctuation_vocabulary = net.y_vocabulary

        reverse_word_vocabulary = {v:k for k,v in word_vocabulary.items()}
        reverse_punctuation_vocabulary = {v:k for k,v in punctuation_vocabulary.items()}

        #input_text = input()

        if len(input_text) == 0:
            sys.exit("Input text missing.")

        text = [w for w in input_text.split() if w not in punctuation_vocabulary and w not in data.PUNCTUATION_MAPPING and not w.startswith(data.PAUSE_PREFIX)] + [data.END]
        pauses = [float(s.replace(data.PAUSE_PREFIX,"").replace(">","")) for s in input_text.split() if s.startswith(data.PAUSE_PREFIX)]

        if not use_pauses:
            return restore(text, word_vocabulary, reverse_punctuation_vocabulary, predict)
        else:
            if not pauses:
                pauses = [0.0 for _ in range(len(text)-1)]
            restore_with_pauses(output_file, text, pauses, word_vocabulary, reverse_punctuation_vocabulary, predict)
