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madrugado / overlap.py
Last active October 22, 2015 21:21
We have dataset of requests and vacancies titles and descriptions. We need to find similar queries and jobs.
#!/usr/bin/python
# -*- coding: utf-8 -*-
__author__ = 'madrugado'
import sys
import pymystem3
import itertools
from collections import Counter
import math
@madrugado
madrugado / longest_chain_of_substrings.cpp
Created October 22, 2015 21:18
The problem solved by this code is: we need to find a longest chain of substrings, where substring produced from string by dropping of one letter. The input reading is omitted.
#include <iostream>
#import <vector>
#import <string>
#import <set>
#import <algorithm>
#import <map>
using namespace std;
int main() {
import random
import matplotlib.pyplot as plt
from IPython import display
"""
IPython Display rc0
Try:
dsp = IDisplay()
@madrugado
madrugado / Keras_usage_example.ipynb
Last active December 13, 2022 16:51
Keras usage example, simple text classification
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@madrugado
madrugado / image_captioning.ipynb
Last active May 16, 2017 18:23
Image Captioning Homework
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def sample_gumbel(shape, eps=1e-20):
"""Sample from Gumbel(0, 1)"""
U = tf.random_uniform(shape,minval=0,maxval=1)
return -tf.log(-tf.log(U + eps) + eps)
def gumbel_softmax_sample(logits, temperature):
""" Draw a sample from the Gumbel-Softmax distribution"""
y = logits + sample_gumbel(tf.shape(logits))
return tf.nn.softmax( y / temperature)
#!/bin/sh
# this sample script translates a test set, including
# preprocessing (tokenization, truecasing, and subword segmentation),
# and postprocessing (merging subword units, detruecasing, detokenization).
# instructions: set paths to mosesdecoder, subword_nmt, and nematus,
# then run "./translate.sh < input_file > output_file"
# suffix of source language
@madrugado
madrugado / bleu.py
Created January 27, 2018 19:54
BLEU version we're using for Babel
# Copyright 2017 Google Inc. All Rights Reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
from random import random, choice
def noise_generator(string, noise_level, chars):
noised = ""
for c in string:
if random() > noise_level:
noised += c
if random() < noise_level:
noised += choice(chars)
return noised
import tensorflow as tf
from tensorflow.contrib.rnn import RNNCell
from tensorflow.contrib.rnn import LSTMStateTuple
from tensorflow.python.ops import variable_scope
from tensorflow.python.ops import array_ops
from tensorflow.python.ops.rnn_cell_impl import _linear
from tensorflow.python.ops import math_ops
from tensorflow.python.ops import nn_ops