diff options
| -rw-r--r-- | irc.py | 173 | ||||
| -rwxr-xr-x[-rw-r--r--] | ircbot.py (renamed from ircext.py) | 124 | ||||
| -rw-r--r-- | paramsaveload.py | 2 |
3 files changed, 75 insertions, 224 deletions
@@ -1,173 +0,0 @@ -#!/usr/bin/env python2 - -import logging -import sys -import importlib - -import theano - -from blocks.extensions import Printing, SimpleExtension, FinishAfter -from blocks.extensions.monitoring import DataStreamMonitoring, TrainingDataMonitoring - -from blocks.graph import ComputationGraph -from blocks.main_loop import MainLoop -from blocks.model import Model -from blocks.algorithms import GradientDescent - -try: - from blocks.extras.extensions.plot import Plot - plot_avail = False -except ImportError: - plot_avail = False - - -import datastream -from paramsaveload import SaveLoadParams -from gentext import GenText -from ircext import IRCClientExt - -logging.basicConfig(level='INFO') -logger = logging.getLogger(__name__) - -sys.setrecursionlimit(500000) - - -class ResetStates(SimpleExtension): - def __init__(self, state_vars, **kwargs): - super(ResetStates, self).__init__(**kwargs) - - self.f = theano.function( - inputs=[], outputs=[], - updates=[(v, v.zeros_like()) for v in state_vars]) - - def do(self, which_callback, *args): - self.f() - -if __name__ == "__main__": - if len(sys.argv) < 2: - print >> sys.stderr, 'Usage: %s [options] config' % sys.argv[0] - sys.exit(1) - model_name = sys.argv[-1] - config = importlib.import_module('%s' % model_name) - - - # Build datastream - train_stream = datastream.setup_datastream('data/logcompil.txt', - config.num_seqs, - config.seq_len, - config.seq_div_size) - - # Build model - m = config.Model() - m.pred.name = 'pred' - - # Train the model - saveloc = 'model_data/%s-%s' % (model_name, config.param_desc) - train_model(m, train_stream, dump_path=saveloc) - - - # Define the model - model = Model(m.sgd_cost) - - # IRC mode : just load the parameters and run an IRC server - if '--irc' in sys.argv: - try: - extensions.append(FinishAfter(before_training=True, after_n_batches=1)) - print "Initializing main loop" - main_loop.run() - print "Jumping into IRC" - irc.run_forever() - except KeyboardInterrupt: - pass - sys.exit(0) - - # Train the model - - cg = ComputationGraph(m.sgd_cost) - algorithm = GradientDescent(cost=m.sgd_cost, - step_rule=config.step_rule, - parameters=cg.parameters) - - algorithm.add_updates(m.states) - - monitor_vars = [v for p in m.monitor_vars for v in p] - extensions = [ - TrainingDataMonitoring( - monitor_vars, - prefix='train', every_n_epochs=1), - Printing(every_n_epochs=1, after_epoch=False), - - ResetStates([v for v, _ in m.states], after_epoch=True) - ] - if plot_avail: - plot_channels = [['train_' + v.name for v in p] for p in m.monitor_vars] - extensions.append( - Plot(document='text_'+model_name, - channels=plot_channels, - server_url='http://localhost:5006', - every_n_epochs=1, after_epoch=False) - ) - if config.save_freq is not None and dump_path is not None: - extensions.append( - SaveLoadParams(path=dump_path+'.pkl', - model=model, - before_training=True, - after_training=True, - after_epoch=False, - every_n_epochs=config.save_freq) - ) - if config.sample_freq is not None: - extensions.append( - GenText(m, '\nalex\ttu crois ?\n', - config.sample_len, config.sample_temperature, - every_n_epochs=config.sample_freq, - after_epoch=False, before_training=True) - ) - if config.on_irc: - irc = IRCClientExt(m, config.sample_temperature, - server='clipper.ens.fr', - port=6667, - nick='frigo', - channels=['#frigotest', '#courssysteme'], - after_batch=True) - irc.do('before_training') - extensions.append(irc) - - if config.on_irc: - irc = IRCClientExt(m, config.sample_temperature, - server='clipper.ens.fr', - port=6667, - nick='frigo', - channels=['#frigotest', '#courssysteme'], - after_batch=True) - irc.do('before_training') - extensions.append(irc) - - main_loop = MainLoop( - model=model, - data_stream=train_stream, - algorithm=algorithm, - extensions=extensions - ) - main_loop.run() - - # IRC mode : just load the parameters and run an IRC server - if '--irc' in sys.argv: - try: - extensions.append(FinishAfter(before_training=True, after_n_batches=1)) - print "Initializing main loop" - main_loop.run() - print "Jumping into IRC" - irc.run_forever() - except KeyboardInterrupt: - pass - sys.exit(0) - - - - - - - - -# vim: set sts=4 ts=4 sw=4 tw=0 et : diff --git a/ircext.py b/ircbot.py index d8580ad..ac329eb 100644..100755 --- a/ircext.py +++ b/ircbot.py @@ -1,26 +1,60 @@ -from irc.client import SimpleIRCClient +#!/usr/bin/env python2 import logging +import sys +import importlib -import numpy +from irc.client import SimpleIRCClient +import numpy import theano from theano import tensor -from blocks.extensions import SimpleExtension +from blocks.model import Model + +import datastream +from paramsaveload import SaveLoadParams from blocks.graph import ComputationGraph logging.basicConfig(level='INFO') -logger = logging.getLogger('irc_ext') +logger = logging.getLogger(__name__) + class IRCClient(SimpleIRCClient): - def __init__(self, chans, nick): + def __init__(self, model, sample_temperature, server, port, nick, channels, saveload): super(IRCClient, self).__init__() + out = model.out[:, -1, :] / numpy.float32(sample_temperature) + prob = tensor.nnet.softmax(out) + + cg = ComputationGraph([prob]) + assert(len(cg.inputs) == 1) + assert(cg.inputs[0].name == 'bytes') + + # channel functions & state + chfun = {} + for ch in channels + ['']: + logger.info("Building theano function for channel '%s'"%ch) + state_vars = [theano.shared(v[0:1, :].zeros_like().eval(), v.name+'-'+ch) + for v, _ in model.states] + givens = [(v, x) for (v, _), x in zip(model.states, state_vars)] + updates= [(x, upd) for x, (_, upd) in zip(state_vars, model.states)] + + pred = theano.function(inputs=cg.inputs, outputs=[prob], + givens=givens, updates=updates) + reset_states = theano.function(inputs=[], outputs=[], + updates=[(v, v.zeros_like()) for v in state_vars]) + chfun[ch] = (pred, reset_states) + + self.saveload = saveload + + self.chfuns = chfun + self.chans = chans self.nick = nick self.server = None + def on_welcome(self, server, ev): logger.info("Welcomed to " + repr(server)) for ch in self.chans: @@ -37,7 +71,7 @@ class IRCClient(SimpleIRCClient): s = '' while True: prob = prob / 1.00001 - pred = numpy.random.multinomial(1, prob[0, :]).nonzero()[0][0] + pred = numpy.random.multinomial(1, prob[0, :]).nonzero()[0][0].astype('int16') s = s + chr(int(pred)) @@ -64,8 +98,8 @@ class IRCClient(SimpleIRCClient): rep = None - if chan in self.chans: - pred_f, _ = self.chans[chan] + if chan in self.chfuns: + pred_f, _ = self.chfuns[chan] if s0[-2:] == '^I': prob, = pred_f(self.str2data(s0[:-2])) rep = s0[:-2] + self.pred_until(pred_f, prob) @@ -78,56 +112,46 @@ class IRCClient(SimpleIRCClient): prob, = pred_f(self.str2data(nick+': ')) rep = nick + ': ' + self.pred_until(pred_f, prob) else: - pass - + logger.warn('Recieved message on unknown channel: %s'%chan) + if rep != None: self.privmsg(chan, rep) -class IRCClientExt(SimpleExtension): - def __init__(self, model, sample_temperature, server, port, nick, channels, **kwargs): - super(IRCClientExt, self).__init__(**kwargs) - # model output - out = model.out[:, -1, :] / numpy.float32(sample_temperature) - prob = tensor.nnet.softmax(out) - - cg = ComputationGraph([prob]) - assert(len(cg.inputs) == 1) - assert(cg.inputs[0].name == 'bytes') - # channel functions & state - chfun = {} - for ch in channels + ['']: - state_vars = [theano.shared(v[0:1, :].zeros_like().eval(), v.name+'-'+ch) - for v, _ in model.states] - givens = [(v, x) for (v, _), x in zip(model.states, state_vars)] - updates= [(x, upd) for x, (_, upd) in zip(state_vars, model.states)] - - pred = theano.function(inputs=cg.inputs, outputs=[prob], - givens=givens, updates=updates) - reset_states = theano.function(inputs=[], outputs=[], - updates=[(v, v.zeros_like()) for v in state_vars]) - chfun[ch] = (pred, reset_states) +if __name__ == "__main__": + if len(sys.argv) < 2: + print >> sys.stderr, 'Usage: %s [options] config' % sys.argv[0] + sys.exit(1) + model_name = sys.argv[-1] + config = importlib.import_module('.%s' % model_name, 'config') - self.irc = IRCClient(chfun, nick) - self.irc.connect(server, port, nick) + # Build model + logger.info('Building model...') + m = config.Model(config) - def __getstate__(self): - state = dict(self.__dict__) - del state['irc'] - return state + # Define the computation graph && load parameters + logger.info('Building computation graph...') + dump_path = 'params/%s-use_on_irc.pkl' % model_name + saveload = SaveLoadParams(path=dump_path, + model=Model(m.sgd_cost)) + saveload.do_load() - def __setstate__(self, state): - irc = self.irc - self.__dict__.update(state) - self.irc = irc + # Build IRC client + server = 'clipper.ens.fr' + port = 6667 + nick = 'frigo' + chans = ['#frigotest', '#courssysteme'] - def do(self, which_callback, *args): - logger.info('Polling...') - self.irc.reactor.process_once() - - def run_forever(self): - self.irc.reactor.process_forever() + irc = IRCClient(model=m, + sample_temperature=config.sample_temperature, + server=server, + port=port, + nick=nick, + channels=chans, + saveload=saveload) + irc.connect(server, port, nick) + irc.reactor.process_forever() -# vim: set sts=4 ts=4 sw=4 tw=0 et : +# vim: set sts=4 ts=4 sw=4 tw=0 et : diff --git a/paramsaveload.py b/paramsaveload.py index 9c05926..345cfbb 100644 --- a/paramsaveload.py +++ b/paramsaveload.py @@ -27,7 +27,7 @@ class SaveLoadParams(SimpleExtension): logger.info('Loading parameters from %s...'%self.path) self.model.set_parameter_values(cPickle.load(f)) except IOError: - pass + logger.warn('No previous parameters found at %s...'%self.path) def do(self, which_callback, *args): if which_callback == 'before_training': |