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@volkancirik
volkancirik / download_gcc.sh
Last active Apr 21, 2019
Download Google Conceptual Captions Data
View download_gcc.sh
#!/usr/bin/bash
# Download split TSV files here https://ai.google.com/research/ConceptualCaptions/download
# create split folodrs val/ and trn/
# run as follows
# cd val/; bash ../download_gcc.sh ../val.tsv
# cd trn/; bash ../download_gcc.sh ../trn.tsv
@volkancirik
volkancirik / treernn.py
Last active Oct 9, 2018
Pytorch TreeRNN
View treernn.py
"""
TreeLSTM[1] implementation in Pytorch
Based on dynet benchmarks :
https://github.com/neulab/dynet-benchmark/blob/master/dynet-py/treenn.py
https://github.com/neulab/dynet-benchmark/blob/master/chainer/treenn.py
Other References:
https://github.com/pytorch/examples/tree/master/word_language_model
https://github.com/pfnet/chainer/blob/29c67fe1f2140fa8637201505b4c5e8556fad809/chainer/functions/activation/slstm.py
https://github.com/stanfordnlp/treelstm
@volkancirik
volkancirik / caffe_cnn.py
Created Jun 8, 2016
extract cnn features
View caffe_cnn.py
# Make sure that caffe is on the python path:
caffe_root = '/usr0/bin/caffe/' # this file is expected to be in {caffe_root}/examples
import sys
sys.path.insert(0, caffe_root + 'python')
import caffe
from images import crop_image
import numpy as np
mean = 'caffedata/ilsvrc_2012_mean.npy'
@volkancirik
volkancirik / extract_from_vgg.py
Last active Mar 13, 2017
Extract Features from VGG
View extract_from_vgg.py
'''
Extract Features from a pre-trained caffe CNN Layer
based on https://github.com/karpathy/neuraltalk/blob/master/python_features/extract_features.py
'''
import sys
import os.path
import argparse
import numpy as np
from scipy.misc import imread, imresize
@volkancirik
volkancirik / gist:f4240ff34687eb2829df
Last active Aug 29, 2015
eParse deneylerini nasil calistiririm?
View gist:f4240ff34687eb2829df

eParse deneylerini nasil calistiririm?


Bu tutorialin amaci eParse deneylerinin tekrarlamak ya da yeni deneyler yapabilmek icin bir referans olusturmak.

Parser’in repository’si burada. Burada oldukca aciklayici bir README mevcut. Bu dokumana devam etmeden mutlaka okunmasini oneririm.

0- Kelime Vektorleri

Kelime vektorleri @ai-ku servers:/ai/home/vcirik/embeddings** altinda. Orada bir README

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