From 869d45a89da3a0c68c9f071576b58009043645f9 Mon Sep 17 00:00:00 2001
From: =?UTF-8?q?Mario=20Sa=CC=88nger?= <mario.saenger@student.hu-berlin.de>
Date: Fri, 4 May 2018 23:53:19 +0200
Subject: [PATCH] Save program arguments to file
---
code_mario/clef18_task1.py | 16 +++++++++++++---
1 file changed, 13 insertions(+), 3 deletions(-)
diff --git a/code_mario/clef18_task1.py b/code_mario/clef18_task1.py
index 600866b..425ca4f 100644
--- a/code_mario/clef18_task1.py
+++ b/code_mario/clef18_task1.py
@@ -516,6 +516,15 @@ class Clef18Task1V2(LoggingMixin):
result_writer.write("%s\t%s\t%s\t%s\n" % (r.target_label, r.classifier_name, r.data_set_name, r.accuracy))
result_writer.close()
+ def save_arguments(self, arguments: Namespace):
+ arguments_file = os.path.join(AppContext.default().log_dir, "arguments.txt")
+ self.logger.info("Saving arguments to " + arguments_file)
+
+ with open(arguments_file, 'w', encoding="utf8") as writer:
+ for key, value in arguments.__dict__.items():
+ writer.write("%s=%s\n" % (str(key), str(value)))
+ writer.close()
+
def save_configuration(self, configuration: Configuration):
label_encoder_file = os.path.join(AppContext.default().output_dir, "label_encoder.pk")
self.logger.info("Saving label encoder to " + label_encoder_file)
@@ -547,7 +556,6 @@ class Clef18Task1V2(LoggingMixin):
self.logger.info("Reloading embedding model from " + emb_model_file)
return k.models.load_model(args.emb_model)
-
def create_dnn_classifier(self, model_name, label: str, val_data: Tuple, **kwargs):
if val_data is not None:
monitor_loss = "val_loss"
@@ -677,14 +685,16 @@ if __name__ == "__main__":
ft_model = ft_embeddings.load_embeddings_by_language(args.lang)
clef18_task1 = Clef18Task1V2()
- neg_sampling = NegativeSampling()
+ clef18_task1.save_arguments(args)
if args.mode == "train-emb":
configuration = clef18_task1.prepare_data_set(certificates, dictionary, ft_model, args.train_ratio, args.val_ratio,args.strat_column,
args.samples, args.strat_splits)
- neg_sampling_strategy = neg_sampling.get_strategy_by_name(args.neg_sampling, args)
clef18_task1.save_configuration(configuration)
+ neg_sampling = NegativeSampling()
+ neg_sampling_strategy = neg_sampling.get_strategy_by_name(args.neg_sampling, args)
+
embedding_model = clef18_task1.train_embedding_model(configuration, ft_model, neg_sampling_strategy, args.epochs, args.batch_size)
elif args.mode == "eval-cl":
--
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