From 12304944033d20bbc5c1b3f5cb90cf8dedebcdff Mon Sep 17 00:00:00 2001
From: Alex Auvolat <alex@adnab.me>
Date: Wed, 17 Jun 2015 14:58:38 -0400
Subject: paramsaveload

---
 paramsaveload.py | 37 +++++++++++++++++++++++++++++++++++++
 train.py         | 49 ++++++++++++++++++++++++++++++++-----------------
 2 files changed, 69 insertions(+), 17 deletions(-)
 create mode 100644 paramsaveload.py

diff --git a/paramsaveload.py b/paramsaveload.py
new file mode 100644
index 0000000..7181e9a
--- /dev/null
+++ b/paramsaveload.py
@@ -0,0 +1,37 @@
+import logging
+
+import numpy
+
+import cPickle
+
+from blocks.extensions import SimpleExtension
+
+logging.basicConfig(level='INFO')
+logger = logging.getLogger('extensions.SaveLoadParams')
+
+class SaveLoadParams(SimpleExtension):
+	def __init__(self, path, model, **kwargs):
+		super(SaveLoadParams, self).__init__(**kwargs)
+
+		self.path = path
+		self.model = model
+	
+	def do_save(self):
+		with open(self.path, 'w') as f:
+			logger.info('Saving parameters to %s...'%self.path)
+			cPickle.dump(model.get_param_values(), f, protocol=cPickle.HIGHEST_PROTOCOL)
+	
+	def do_load(self):
+		try:
+			with open(self.path, 'r') as f:
+				logger.info('Loading parameters from %s...'%self.path)
+				model.set_parma_values(cPickle.load(f))
+		except IOError:
+			pass
+
+	def do(self, which_callback, *args):
+		if which_callback == 'before_training':
+			self.do_load()
+		else:
+			self.do_save()
+		
diff --git a/train.py b/train.py
index 79b2116..525724f 100755
--- a/train.py
+++ b/train.py
@@ -14,7 +14,7 @@ from theano.tensor.shared_randomstreams import RandomStreams
 from blocks.serialization import load_parameter_values, secure_dump, BRICK_DELIMITER
 from blocks.extensions import Printing, SimpleExtension
 from blocks.extensions.monitoring import DataStreamMonitoring, TrainingDataMonitoring
-from blocks.extras.extensions.plot import Plot
+# from blocks.extras.extensions.plot import Plot
 from blocks.extensions.saveload import Checkpoint, Load
 from blocks.graph import ComputationGraph
 from blocks.main_loop import MainLoop
@@ -22,6 +22,7 @@ from blocks.model import Model
 from blocks.algorithms import GradientDescent
 
 import datastream
+import paramsaveload
 import gentext
 import ircext
 
@@ -60,17 +61,31 @@ def train_model(m, train_stream, dump_path=None):
 
     algorithm.add_updates(m.states)
 
-    # Load the parameters from a dumped model
-    if dump_path is not None:
-        try:
-            with closing(numpy.load(dump_path)) as source:
-                logger.info('Loading parameters...')
-                param_values = {'/' + name.replace(BRICK_DELIMITER, '/'): source[name]
-                                    for name in source.keys()
-                                    if name != 'pkl' and not 'None' in name}
-                model.set_param_values(param_values)
-        except IOError:
-            pass
+    extensions = []
+    if config.save_freq is not None and dump_path is not None:
+        extensions.append(
+            SaveLoadParams(path=dump_path,
+                           model=model,
+                           before_training=True,
+                           after_epoch=False,
+                           every_n_epochs=config.save_freq)
+        )
+    if config.sample_freq is not None:
+        extensions.append(
+            gentext.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:
+        extensions.append(
+            ircext.IRCClientExt(m, config.sample_temperature,
+                                server='irc.ulminfo.fr',
+                                port=6667,
+                                nick='frigo',
+                                channels=['#frigotest', '#courssysteme'],
+                                after_batch=True)
+        )
 
     extensions = []
     if config.save_freq is not None:
@@ -106,11 +121,11 @@ def train_model(m, train_stream, dump_path=None):
                 [m.cost_reg, m.error_rate_reg, m.cost, m.error_rate],
                 prefix='train', every_n_epochs=1),
             Printing(every_n_epochs=1, after_epoch=False),
-            Plot(document='text_'+model_name+'_'+config.param_desc,
-                 channels=[['train_cost', 'train_cost_reg'],
-                           ['train_error_rate', 'train_error_rate_reg']],
-                 server_url='http://eos21:4201/',
-                 every_n_epochs=1, after_epoch=False),
+            # Plot(document='text_'+model_name+'_'+config.param_desc,
+            #      channels=[['train_cost', 'train_cost_reg'],
+            #                ['train_error_rate', 'train_error_rate_reg']],
+            #      server_url='http://eos21:4201/',
+            #      every_n_epochs=1, after_epoch=False),
 
             ResetStates([v for v, _ in m.states], after_epoch=True)
         ]
-- 
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