def get_loader(image_path, train=False, val=False, test=False):
""" Returns a data loader for the desired split """
assert train + val + test == 1, 'need to set exactly one of {train, val, test} to True'
split = VQA(utils.path_for(train=train, val=val, test=test, question=True),
utils.path_for(train=train, val=val, test=test, answer=True),
image_path,
answerable_only=train,
transform=utils.get_transform(config.image_size, test,
config.central_fraction))
if test:
loader = torch.utils.data.DataLoader(
split,
batch_size=config.test_batch_size,
shuffle=train, # only shuffle the data in training
pin_memory=True,
num_workers=config.data_workers,
collate_fn=collate_fn,
)
else:
loader = torch.utils.data.DataLoader(
split,
batch_size=config.batch_size,
shuffle=train, # only shuffle the data in training
pin_memory=True,
num_workers=config.data_workers,
collate_fn=collate_fn,
)
return loader
def get_loader(
train=False,
val=False,
test=False
): #TODO you need todo some changes here, this here decides what is the data thta goes into loader while train/test
""" Returns a data loader for the desired split """
assert train + val + test == 1, 'need to set exactly one of {train, val, test} to True'
split = VQA(
utils.path_for(train=train, val=val, test=test, question=True),
utils.path_for(train=train, val=val, test=test, answer=True),
config.
preprocessed_path, ## make changed here- in config file #TODO you need todo some changes here, this here decides what is the data thta goes into loader while train/test
answerable_only=train)
if train and config.orig_edit_equal_batch:
batch_size_given = int(config.batch_size * config.orig_amt)
else:
batch_size_given = config.batch_size
loader = torch.utils.data.DataLoader(
split,
batch_size=batch_size_given,
shuffle=
train, #train, #TODO vedika you dont want to shuffle train during test!! #train, #train, # only shuffle the data in training #TODO vedika comment- good idea!
pin_memory=True,
num_workers=config.data_workers,
collate_fn=collate_fn,
)
#ipdb.set_trace() ## check what the loader is retunring here #len(loader.dataset) = 8438 for what color is the- works correctly- so all good- so far
return split, loader
def main():
questions = utils.path_for(train=True, question=True)
answers = utils.path_for(train=True, answer=True)
with open(questions, 'r') as fd:
questions = json.load(fd)
with open(answers, 'r') as fd:
answers = json.load(fd)
questions = data.prepare_questions(questions)
answers = data.prepare_answers(answers)
question_vocab, question_vocabi = extract_vocab(questions, start=1)
answer_vocab, answer_vocabi = extract_vocab(answers,
top_k=config.max_answers)
vocabs = {
'question': question_vocab,
'answer': answer_vocab,
}
with open(config.vocabulary_path, 'w') as fd:
json.dump(vocabs, fd)
print(answer_vocabi)
vocabsi = {
'answeri': answer_vocabi,
}
with open(config.vocabularyi_path, 'w') as fd:
json.dump(vocabsi, fd)
def get_loader(train=False, val=False, test=False, trainval=False):
""" Returns a data loader for the desired split """
split = VQA(
utils.path_for(train=train,
val=val,
test=test,
trainval=trainval,
question=True),
utils.path_for(train=train,
val=val,
test=test,
trainval=trainval,
answer=True),
config.preprocessed_trainval_path
if not test else config.preprocessed_test_path,
answerable_only=train or trainval,
dummy_answers=test,
)
loader = torch.utils.data.DataLoader(
split,
batch_size=config.batch_size,
shuffle=train or trainval, # only shuffle the data in training
pin_memory=True,
num_workers=config.data_workers,
collate_fn=collate_fn,
)
return loader
def get_loader(train=False,
val=False,
test=False,
batch_size=config.batch_size):
""" Returns a data loader for the desired split """
assert train + val + test == 1, 'need to set exactly one of {train, val, test} to True'
if train:
im_path = config.train_path
fdict_path = config.fdict_path + 'train.npy'
elif val:
im_path = config.val_path
fdict_path = config.fdict_path + 'val.npy'
else:
im_path = config.test_path
fdict_path = config.fdict_path + 'test.npy'
split = VQA(
utils.path_for(train=train, val=val, test=test, question=True),
utils.path_for(train=train, val=val, test=test, answer=True),
im_path,
fdict_path,
answerable_only=train,
)
loader = torch.utils.data.DataLoader(
split,
batch_size=batch_size,
shuffle=train, # only shuffle the data in training
pin_memory=True,
num_workers=config.data_workers,
collate_fn=collate_fn,
)
return loader
def get_loader(train=False, val=False, test=False, batch_size=128):
""" Returns a data loader for the desired split """
assert train + val + test == 1, 'need to set exactly one of {train, val, test} to True'
if test:
# Test data doesnt have answers
split = TestVQA(
utils.path_for(train=train, val=val, test=test, question=True),
config.preprocessed_path,
answerable_only=False,
)
else:
split = VQA(
utils.path_for(train=train, val=val, test=test, question=True),
utils.path_for(train=train, val=val, test=test, answer=True),
config.preprocessed_path,
answerable_only=train,
)
loader = torch.utils.data.DataLoader(
split,
batch_size=batch_size,
shuffle=train, # only shuffle the data in training
pin_memory=True,
num_workers=8,
collate_fn=collate_fn,
)
return loader
def read_playlist(self, name):
"""Retrieve playlist data from a JSON file"""
try:
playlist = json.loads(open(os.path.join(utils.path_for('data'),
'%s' % name),'r').read())['playlist']
except Exception, e:
log.error('Error %s loading playlist "%s", attempting to fallback to default' % (e,name))
playlist = json.loads(open(os.path.join(utils.path_for('data'),
'default.json'),'r').read())['playlist']
def get_VQA(train=False, val=False, test=False):
assert train + val + test == 1, 'need to set exactly one of {train, val, test} to True'
split = VQA(
utils.path_for(train=train, val=val, test=test, question=True),
utils.path_for(train=train, val=val, test=test, answer=True),
config.preprocessed_path,
answerable_only=train,
)
return split
def read_playlist(self, name):
"""Retrieve playlist data from a JSON file"""
try:
playlist = json.loads(open(os.path.join(utils.path_for('etc'),
'%s' % name),'r').read())['playlist']
settings.content.playlist_name = playlist['name']
except Exception, e:
log.error('Error %s loading playlist "%s", attempting to fallback to default' % (e,name))
playlist = json.loads(open(os.path.join(utils.path_for('etc'),
self.filename),'r').read())['playlist']
settings.content.playlist_name = playlist['name']
def read_playlist(self, name):
"""Retrieve playlist data from a JSON file"""
try:
playlist = json.loads(
open(os.path.join(utils.path_for('etc'), '%s' % name),
'r').read())['playlist']
settings.content.playlist_name = playlist['name']
except Exception, e:
log.error(
'Error %s loading playlist "%s", attempting to fallback to default'
% (e, name))
playlist = json.loads(
open(os.path.join(utils.path_for('etc'), self.filename),
'r').read())['playlist']
settings.content.playlist_name = playlist['name']
def do_playlist(self, item):
"""Set current playlist"""
self.playlist = item['playlist']['playlist']
# persist the playlist as the default for this player
f = open(os.path.join(utils.path_for('etc'), self.filename),
'w').write(json.dumps(item['playlist'], 2))
return False
def do_playlist(self, item):
"""Set current playlist"""
self.playlist = item['playlist']['playlist']
# persist the playlist as the default for this player
f = open(os.path.join(utils.path_for('etc'),
self.filename),'w').write(json.dumps(item['playlist'], 2))
return False
def wiki(page):
s = Store(path_for(settings.content.path))
try:
result = s.get_page(page.lower())
except:
result = s.get_page('meta/EmptyPage')
return result
def get_reduced_loader(reduced_path, train=False, val=False):
assert train + val == 1
split = ReducedVQA(
reduced_path,
utils.path_for(train=train, val=val, test=False, question=True),
utils.path_for(train=train, val=val, test=False, answer=True),
config.preprocessed_path,
answerable_only=train,
)
loader = torch.utils.data.DataLoader(
split,
batch_size=config.batch_size,
shuffle=train, # only shuffle the data in training
pin_memory=True,
num_workers=config.data_workers,
collate_fn=collate_fn,
)
return loader
def wiki(page):
"""Render a wiki page"""
s = Store(path_for(settings.content.path))
try:
result = s.get_page(page.lower())
except Exception, e:
log.warn("%s rendering page %s" % (e, page))
result = s.get_page('meta/EmptyPage')
def wiki(page):
"""Render a wiki page"""
s = Store(path_for(settings.content.path))
try:
result = s.get_page(page.lower())
except Exception, e:
log.warn("%s rendering page %s" % (e, page))
result = s.get_page('meta/EmptyPage')
def get_loader(train=False, val=False, test=False):
#return：dataloader for the desired split
assert train + val + test == 1, 'need to set exactly one of {train, val, test} to True'
dataset = VQA( #传入q,a,img的路径、answerable_only；得到VQA对象的实例
utils.path_for(train=train, val=val, test=test, question=True),
utils.path_for(train=train, val=val, test=test, answer=True),
config.preprocessed_path,
answerable_only=train,
)
loader = torch.utils.data.DataLoader(
dataset,
batch_size=config.batch_size,
shuffle=train, # only shuffle the data in training
pin_memory=
True, #the data loader will copy tensors into CUDA pinned memory before returning them
num_workers=config.data_workers,
collate_fn=collate_fn,
)
return loader
def get_loader(train=False, val=False, test=False):
""" Returns a data loader for the desired split """
assert train + val + test == 1, 'need to set exactly one of {train, val, test} to True'
print('starting dataset processing, Train : {}, Val : {}'.format(
train, val))
split = VQA(
utils.path_for(train=train, val=val, test=test, question=True),
utils.path_for(train=train, val=val, test=test, answer=True),
config.preprocessed_path,
answerable_only=train,
)
loader = torch.utils.data.DataLoader(
split,
batch_size=config.batch_size,
shuffle=train, # only shuffle the data in training
pin_memory=True,
num_workers=config.data_workers,
collate_fn=collate_fn)
return loader
def main():
questions = utils.path_for(train=True, question=True)
answers = utils.path_for(train=True, answer=True)
with open(questions, 'r', encoding='utf-8') as fd:
questions = json.load(fd)
with open(answers, 'r', encoding='utf-8') as fd:
answers = json.load(fd)
questions = data.prepare_questions(questions)
answers = data.prepare_answers(answers)
question_vocab = extract_vocab(questions, start=1)
answer_vocab = extract_vocab(answers, top_k=config.max_answers)
vocabs = {
'question': question_vocab,
'answer': answer_vocab,
}
with open(config.vocabulary_path, 'w', encoding='utf-8') as fd:
json.dump(vocabs, fd, ensure_ascii=False)
def get_loader(train=False, val=False, test=False, full_batch=False):
""" Returns a data loader for the desired split """
assert train + val + test == 1, 'need to set exactly one of {train, val, test} to True'
split = VQA(
utils.path_for(train=train, val=val, test=test, question=True),
utils.path_for(train=train, val=val, test=test, answer=True),
config.preprocessed_path,
answerable_only=train,
)
# pdb.set_trace()
batch_size = config.batch_size
if full_batch:
batch_size = len(split)
loader = torch.utils.data.DataLoader(
split,
batch_size=batch_size,
shuffle=train, # only shuffle the data in training
pin_memory=True,
num_workers=config.data_workers,
collate_fn=collate_fn,
)
return loader, len(split.token_to_index) + 1
import os, sys, platform, logging.config
from utils import get_config, path_for
try:
settings
except NameError:
try:
settings = get_config(path_for(os.path.join('etc','config.json')))
except Exception as e:
print >> sys.stderr, ("Error while loading configuration file" % locals())
sys.exit(2)
logging.config.dictConfig(dict(settings.logging))
log = logging.getLogger()
log.info("Logging configured.")
import json
import sys
import os.path
from collections import defaultdict
import numpy as np
import torch
import utils
import config
q_path = utils.path_for(val=True, question=True)
with open(q_path, 'r') as fd:
q_json = json.load(fd)
a_path = utils.path_for(val=True, answer=True)
with open(a_path, 'r') as fd:
a_json = json.load(fd)
with open(
os.path.join(config.qa_path,
'v2_mscoco_val2014_complementary_pairs.json')) as fd:
pairs = json.load(fd)
question_list = q_json['questions']
question_ids = [q['question_id'] for q in question_list]
questions = [q['question'] for q in question_list]
answer_list = a_json['annotations']
categories = [a['answer_type']
for a in answer_list] # {'yes/no', 'other', 'number'}
accept_condition = {
'number': (lambda x: id_to_cat[x] == 'number'),
'yes/no': (lambda x: id_to_cat[x] == 'yes/no'),
Created by: Rui Carmo
License: MIT (see LICENSE for details)
"""
import os, sys, time, json, logging, logging.config, itertools
# Make sure our bundled libraries take precedence
sys.path.insert(
0, os.path.join(os.path.dirname(os.path.abspath(__file__)), 'lib'))
import config, utils
# read configuration file
config.settings = utils.get_config(
os.path.join(utils.path_for('etc'), 'config.json'))
# Set up logging
logging.config.dictConfig(dict(config.settings.logging))
log = logging.getLogger()
# load modules
import models, controllers
models.setup()
models.setup_index()
def grouper(n, iterable):
it = iter(iterable)
while True:
chunk = tuple(itertools.islice(it, n))
#!/usr/bin/env python
# -*- coding: utf-8 -*-
"""
Copyright (c) 2012, Rui Carmo
Description: Shared configuration data
License: MIT (see LICENSE.md for details)
"""
import os, sys, platform, logging.config
from utils import get_config, path_for, tb
try:
settings
except NameError:
for host in [platform.node(), 'default']:
try:
settings = get_config(path_for(os.path.join('etc','%s.json' % host)))
except IOError:
continue
except Exception as e:
if sys.stderr.isatty():
tb = tb()
print >> sys.stderr, ("Error while loading %(host)s.json: %(tb)s" % locals())
else:
log.error("Error while loading %(host)s.json: %(tb)s" % locals())
sys.exit(2)
logging.config.dictConfig(dict(settings.logging))
log = logging.getLogger()
log.info("Configuration for %s loaded." % host)
break
def media_asset(item):
"""Return page attachments"""
return static_file(item, root=path_for(settings.content.path))
"""
Fetcher script
Created by: Rui Carmo
License: MIT (see LICENSE for details)
"""
import os, sys, json, time, logging, logging.config
# Make sure our bundled libraries take precedence
sys.path.insert(0,os.path.join(os.path.dirname(os.path.abspath(__file__)),'lib'))
import config, utils, markup.opml
# read configuration file
config.settings = utils.get_config(os.path.join(utils.path_for('etc'),'config.json'))
# Set up logging
logging.config.dictConfig(dict(config.settings.logging))
log = logging.getLogger()
# load modules
import models, controllers
models.setup()
if __name__ == "__main__":
log.info("Starting importer.")
fc = controllers.FeedController()
uc = controllers.UserController()
user = uc.get_user('default')
def static(filepath):
"""Handles all the remanining static files"""
return static_file(filepath, root=path_for(os.path.join('themes',settings.theme,'static')))
def static(filepath):
"""Handles all the remanining static files"""
return static_file(filepath, root=path_for('static'))
sys.path.insert(0,'lib') # prefer bundled libraries to local installs
import bottle, utils
# read configuration file and setup various globals, including logging formats
from config import settings
import gtk, pygtk
# Set up logging
log = logging.getLogger()
# validate framebuffer settings
settings = utils.check_resolution(settings)
# setup static file root
staticroot = utils.path_for('static')
# check if we have a valid IP address
ip_address = utils.get_ip_address(settings.interface)
# Shared data used by other modules
version = '0.13.08.02.1'
# Flag for controlled thread termination
running = True
# Screen state sent from server
screen = {}
# Local URI Prefix
local_uri = 'http://%s:%s' % (settings.http.bind_address, settings.http.port)
window = gtk.Window()
screen = window.get_screen()
if not settings.staging:
def static(filepath):
"""Handles all the remanining static files"""
return static_file(filepath, root=path_for('static'))
def media_asset(item):
"""Return page attachments"""
return static_file(item, root=path_for(settings.content.path))
"""
Main signage client script
Created by: Rui Carmo
License: MIT (see LICENSE for details)
"""
import os, sys, re, stat, glob, time, json, logging, logging.config, threading, random
import socket, urllib, urllib2, urlparse, commands, functools, subprocess
sys.path.insert(0,'lib') # prefer bundled libraries to local installs
import bottle, utils
# read configuration file and setup various globals
config = utils.get_config(os.path.join(utils.path_for('data'),'config.json'))
# Set up logging
logging.config.dictConfig(dict(config.logging))
log = logging.getLogger()
# validate framebuffer settings
config = utils.validate_resolution(config)
# setup static file root
staticroot = utils.path_for('static')
# check if we have a valid IP address
ip_address = utils.get_ip_address(config.interface)
# Shared data used by other modules
version = '0.13.02.27.6'
# Flag for controlled thread termination
running = True
# Screen state sent from server
screen = {}
import os, sys, re, stat, glob, time, json, logging, logging.config, threading, random
import socket, urllib, urllib2, urlparse, commands, functools, subprocess
sys.path.insert(0, 'lib') # prefer bundled libraries to local installs
import bottle, utils
# read configuration file and setup various globals, including logging formats
from config import settings
# Set up logging
log = logging.getLogger()
# validate framebuffer settings
settings = utils.check_resolution(settings)
# setup static file root
staticroot = utils.path_for('static')
# check if we have a valid IP address
ip_address = utils.get_ip_address(settings.interface)
# Shared data used by other modules
version = '0.13.08.02.1'
# Flag for controlled thread termination
running = True
# Screen state sent from server
screen = {}
# Local URI Prefix
local_uri = 'http://%s:%s' % (settings.http.bind_address, settings.http.port)
# Defaults sent to templates
template_vars = {
'version': version,
'ip_address': ip_address,
import os, sys, platform, logging.config
from utils import get_config, path_for
try:
settings
except NameError:
try:
settings = get_config(path_for(os.path.join('etc', 'config.json')))
except Exception as e:
print >> sys.stderr, ("Error while loading configuration file" %
locals())
sys.exit(2)
logging.config.dictConfig(dict(settings.logging))
log = logging.getLogger()
log.info("Logging configured.")
"""
Copyright (c) 2012, Rui Carmo
Description: Shared configuration data
License: MIT (see LICENSE.md for details)
"""
import os, sys, platform, logging.config
from utils import get_config, path_for, tb
try:
settings
except NameError:
for host in [platform.node(), 'default']:
try:
settings = get_config(
path_for(os.path.join('etc', '%s.json' % host)))
except IOError:
continue
except Exception as e:
if sys.stderr.isatty():
tb = tb()
print >> sys.stderr, (
"Error while loading %(host)s.json: %(tb)s" % locals())
else:
log.error("Error while loading %(host)s.json: %(tb)s" %
locals())
sys.exit(2)
logging.config.dictConfig(dict(settings.logging))
log = logging.getLogger()
log.info("Configuration for %s loaded." % host)
break
"""
Copyright (c) 2012, Rui Carmo
Description: Shared configuration data
License: MIT (see LICENSE.md for details)
"""
import logging
import logging.config
import os
import platform
import sys
from utils import get_config, path_for, tb
for host in [platform.node(), "default"]:
try:
settings = get_config(path_for(os.path.join("etc", "%s.json" % host)))
except IOError:
continue
except Exception as e:
tb = tb()
print tb
if sys.stderr.isatty():
print >> sys.stderr, ("Error while loading %(host)s.json: %(tb)s" % locals())
else:
log.error("Error while loading %(host)s.json: %(tb)s" % locals())
sys.exit(2)
logging.config.dictConfig(dict(settings.logging))
log = logging.getLogger()
log.info("Configuration for %s loaded." % host)
break
def static(filepath):
"""Handles all the remanining static files"""
return static_file(filepath,
root=path_for(
os.path.join('themes', settings.theme, 'static')))
"""
Copyright (c) 2012, Rui Carmo
Description: Shared configuration data
License: MIT (see LICENSE.md for details)
"""
import logging
import logging.config
import os
import platform
import sys
from utils import get_config, path_for, tb
for host in [platform.node(), 'default']:
try:
settings = get_config(path_for(os.path.join('etc', '%s.json' % host)))
except IOError:
continue
except Exception as e:
tb = tb()
print tb
if sys.stderr.isatty():
print >> sys.stderr, ("Error while loading %(host)s.json: %(tb)s" %
locals())
else:
log.error("Error while loading %(host)s.json: %(tb)s" % locals())
sys.exit(2)
logging.config.dictConfig(dict(settings.logging))
log = logging.getLogger()
log.info("Configuration for %s loaded." % host)
break
# -*- coding: utf-8 -*-
"""
Main application script
Created by: Rui Carmo
"""
import os, sys, json, logging, logging.config
# Make sure our bundled libraries take precedence
sys.path.insert(0,os.path.join(os.path.dirname(os.path.abspath(__file__)),'lib'))
import config, utils, bottle
# read configuration file
config.settings = utils.get_config(os.path.join(utils.path_for('etc'),'wiki.json'))
# Set up logging
logging.config.dictConfig(dict(config.settings.logging))
log = logging.getLogger()
if __name__ == "__main__":
if config.settings.reloader:
if 'BOTTLE_CHILD' not in os.environ:
log.debug('Using reloader, spawning first child.')
else:
log.debug('Child spawned.')
if not config.settings.reloader or ('BOTTLE_CHILD' in os.environ):
Created by: Rui Carmo
"""
from gevent import monkey; monkey.patch_socket()
from gevent.server import StreamServer
import os, sys, json, logging, logging.config
# Make sure our bundled libraries take precedence
sys.path.insert(0,os.path.join(os.path.dirname(os.path.abspath(__file__)),'lib'))
import utils
from redis.server import RedisServer
# read configuration file
config = utils.get_config(os.path.join(utils.path_for('etc'),'store.json'))
# set up logging
logging.config.dictConfig(dict(config.logging))
log = logging.getLogger()
if __name__ == "__main__":
s = RedisServer(config)
try:
if config.engine == "gevent":
s.halt = False
server = StreamServer((config.net.bind_address, config.net.port), s.gevent_handler)
server.serve_forever()
else:
s.run()
except KeyboardInterrupt:
"""
Main application script
Created by: Rui Carmo
License: MIT (see LICENSE for details)
"""
import os, sys, json, logging, logging.config
# Make sure our bundled libraries take precedence
sys.path.insert(0,os.path.join(os.path.dirname(os.path.abspath(__file__)),'lib'))
import bottle, config, utils
# read configuration file
config.settings = utils.get_config(os.path.join(utils.path_for('data'),'config.json'))
# Set up logging
logging.config.dictConfig(dict(config.settings.logging))
log = logging.getLogger()
if __name__ == "__main__":
if config.settings.debug:
if 'BOTTLE_CHILD' not in os.environ:
log.debug('Using reloader, spawning first child.')
else:
log.debug('Child spawned.')
if not config.settings.debug or ('BOTTLE_CHILD' in os.environ):
log.info("Setting up application.")
def static(filepath):
"""Handles static files"""
log.debug(path_for(os.path.join('themes',settings.theme,'static')))
return static_file(filepath, root=path_for(os.path.join('themes',settings.theme,'static')))
from gevent import monkey
monkey.patch_socket()
from gevent.server import StreamServer
import os, sys, json, logging, logging.config
# Make sure our bundled libraries take precedence
sys.path.insert(
0, os.path.join(os.path.dirname(os.path.abspath(__file__)), 'lib'))
import utils
from redis.server import RedisServer
# read configuration file
config = utils.get_config(os.path.join(utils.path_for('etc'), 'store.json'))
# set up logging
logging.config.dictConfig(dict(config.logging))
log = logging.getLogger()
if __name__ == "__main__":
s = RedisServer(config)
try:
if config.engine == "gevent":
s.halt = False
server = StreamServer((config.net.bind_address, config.net.port),
s.gevent_handler)
server.serve_forever()
else:
s.run()
try:
from gevent import monkey; monkey.patch_all()
except:
print "Could not load gevent, proceeding."
import os, sys, logging, logging.config
# Make sure our bundled libraries take precedence
for f in ['lib','controllers']:
sys.path.insert(0,os.path.join(os.path.dirname(os.path.abspath(__file__)),f))
import utils, bottle, config
# read configuration file
config.indexer = utils.get_config(os.path.join(utils.path_for('etc',__file__),'indexer.json'))
# Set up logging
logging.config.dictConfig(dict(config.indexer.logging))
log = logging.getLogger()
if __name__ == "__main__":
if config.indexer.reloader:
if 'BOTTLE_CHILD' not in os.environ:
log.debug('Using reloader, spawning first child.')
else:
log.debug('Child spawned.')
if not config.indexer.reloader or ('BOTTLE_CHILD' in os.environ):