comment out test set submission procedure

tasks/R2R/train.py

@@ -221,14 +221,15 @@ def train_setup(args, batch_size=BATCH_SIZE):
  return agent, train_env, val_envs
 
 
-def test_setup(args, batch_size=BATCH_SIZE):
- train_env, test_envs, encoder, decoder = make_env_and_models(
- args, TRAINVAL_VOCAB, ['train', 'val_seen', 'val_unseen'], ['test'],
- batch_size=batch_size)
- agent = Seq2SeqAgent(
- None, "", encoder, decoder, max_episode_len,
- max_instruction_length=MAX_INPUT_LENGTH)
- return agent, train_env, test_envs
+# Test set prediction will be handled separately
+# def test_setup(args, batch_size=BATCH_SIZE):
+# train_env, test_envs, encoder, decoder = make_env_and_models(
+# args, TRAINVAL_VOCAB, ['train', 'val_seen', 'val_unseen'], ['test'],
+# batch_size=batch_size)
+# agent = Seq2SeqAgent(
+# None, "", encoder, decoder, max_episode_len,
+# max_instruction_length=MAX_INPUT_LENGTH)
+# return agent, train_env, test_envs
 
 
 def train_val(args):
@@ -237,21 +238,22 @@ def train_val(args):
  train(args, train_env, agent, val_envs=val_envs)
 
 
-def test_submission(args):
- ''' Train on combined training and validation sets, and generate test
- submission. '''
- agent, train_env, test_envs = test_setup(args)
- train(args, train_env, agent)
-
- test_env = test_envs['test']
- agent.env = test_env
-
- agent.results_path = '%s%s_%s_iter_%d.json' % (
- RESULT_DIR, get_model_prefix(args, train_env.image_features_list),
- 'test', args.n_iters)
- agent.test(use_dropout=False, feedback='argmax')
- if not args.no_save:
- agent.write_results()
+# Test set prediction will be handled separately
+# def test_submission(args):
+# ''' Train on combined training and validation sets, and generate test
+# submission. '''
+# agent, train_env, test_envs = test_setup(args)
+# train(args, train_env, agent)
+#
+# test_env = test_envs['test']
+# agent.env = test_env
+#
+# agent.results_path = '%s%s_%s_iter_%d.json' % (
+# RESULT_DIR, get_model_prefix(args, train_env.image_features_list),
+# 'test', args.n_iters)
+# agent.test(use_dropout=False, feedback='argmax')
+# if not args.no_save:
+# agent.write_results()
 
 
 def make_arg_parser():

tasks/R2R/train_speaker.py

@@ -220,13 +220,14 @@ def train_setup(args):
  return agent, train_env, val_envs
 
 
-def test_setup(args):
- train_env, test_envs, encoder, decoder = make_env_and_models(
- args, TRAINVAL_VOCAB, ['train', 'val_seen', 'val_unseen'], ['test'])
- agent = Seq2SeqSpeaker(
- None, "", encoder, decoder, MAX_INSTRUCTION_LENGTH,
- max_episode_len=max_episode_len)
- return agent, train_env, test_envs
+# Test set prediction will be handled separately
+# def test_setup(args):
+# train_env, test_envs, encoder, decoder = make_env_and_models(
+# args, TRAINVAL_VOCAB, ['train', 'val_seen', 'val_unseen'], ['test'])
+# agent = Seq2SeqSpeaker(
+# None, "", encoder, decoder, MAX_INSTRUCTION_LENGTH,
+# max_episode_len=max_episode_len)
+# return agent, train_env, test_envs
 
 
 def train_val(args):
@@ -235,21 +236,22 @@ def train_val(args):
  train(args, train_env, agent, val_envs=val_envs)
 
 
-def test_submission(args):
- ''' Train on combined training and validation sets, and generate test
- submission. '''
- agent, train_env, test_envs = test_setup(args)
- train(args, train_env, agent)
-
- test_env = test_envs['test']
- agent.env = test_env
-
- agent.results_path = '%s%s_%s_iter_%d.json' % (
- args.result_dir, get_model_prefix(args, train_env.image_features_list),
- 'test', n_iters)
- agent.test(use_dropout=False, feedback='argmax')
- if not args.no_save:
- agent.write_results()
+# Test set prediction will be handled separately
+# def test_submission(args):
+# ''' Train on combined training and validation sets, and generate test
+# submission. '''
+# agent, train_env, test_envs = test_setup(args)
+# train(args, train_env, agent)
+#
+# test_env = test_envs['test']
+# agent.env = test_env
+#
+# agent.results_path = '%s%s_%s_iter_%d.json' % (
+# args.result_dir, get_model_prefix(args, train_env.image_features_list),
+# 'test', n_iters)
+# agent.test(use_dropout=False, feedback='argmax')
+# if not args.no_save:
+# agent.write_results()
 
 
 def make_arg_parser():