Activated train log statements in run.py

batzner · Aug 25, 2017 · 487c2fb · 487c2fb
1 parent a82ced2
commit 487c2fb
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Showing 4 changed files with 9 additions and 2 deletions.
diff --git a/aws-clipboard.txt b/aws-clipboard.txt
@@ -10,4 +10,9 @@ scp -i ~/dev/pems/tensorflow.pem ~/dev/python-hacks/tensorlm/datasets/sherlock/t
 scp -i ~/dev/pems/tensorflow.pem ~/dev/python-hacks/tensorlm/datasets/sherlock/valid.txt ubuntu@54.149.27.213:~/tensorlm/datasets/sherlock/valid.txt
 
 # Train
+screen
 python3 -m tensorlm.run --train=True --level=word --max_vocab_size=10000 --neurons_per_layer=250 --num_layers=3 --max_batch_size=100 --num_timesteps=160 --save_dir=out/model --evaluate_text_path=datasets/sherlock/valid.txt --train_text_path=datasets/sherlock/train.txt --max_epochs=30 --save_interval_hours=1
+
+# ctrl-a d
+
+python3 -m tensorlm.run --train=True --log_interval=1 --level=word --max_vocab_size=1000 --neurons_per_layer=250 --num_layers=3 --max_batch_size=100 --num_timesteps=160 --save_dir=out/model-small --evaluate_text_path=datasets/sherlock/valid.txt --train_text_path=datasets/sherlock/train.txt --max_epochs=30 --save_interval_hours=1
diff --git a/tensorlm/dataset.py b/tensorlm/dataset.py
@@ -194,7 +194,7 @@ def load_from_dir(save_dir, level="char"):
 
     @staticmethod
     def create_from_text(text_path, max_vocab_size, level="char"):
-        LOGGER.info("Creating vocabulary from {}", text_path)
+        LOGGER.info("Creating vocabulary from %s", text_path)
 
         # Get the most common tokens from the text
         token_counter = Counter()

diff --git a/tensorlm/run.py b/tensorlm/run.py
@@ -92,7 +92,8 @@ def main(_):
                         evaluate_text_path=FLAGS.evaluate_text_path,
                         sample_interval=FLAGS.train_sample_interval,
                         sample_prime=FLAGS.train_sample_prime,
-                        save_interval_hours=FLAGS.save_interval_hours)
+                        save_interval_hours=FLAGS.save_interval_hours,
+                        print_logs=True)
 
         elif FLAGS.evaluate:
             loss = model.evaluate(session, FLAGS.evaluate_text_path)

diff --git a/tensorlm/wrappers.py b/tensorlm/wrappers.py
@@ -56,6 +56,7 @@ def train(self, tf_session, max_epochs=10, max_steps=None, batch_size=None, text
         train_set = Dataset(text_path, self.vocab, batch_size,
                             self.num_timesteps)
 
+        LOGGER.info()
         while (train_state.epoch <= max_epochs and
                    (not max_steps or train_state.global_step <= max_steps)):