From ed7f7b1cd95a50a28c3e9e3e4db9f0b48efbffe9 Mon Sep 17 00:00:00 2001
From: yh_cc <poemsmileyh@gmail.com>
Date: Sun, 1 Mar 2020 10:41:48 +0800
Subject: [PATCH] =?UTF-8?q?1.=E4=BC=98=E5=8C=96Trainer=E4=B8=AD=E5=AF=B9ex?=
 =?UTF-8?q?ception=E7=9A=84=E5=A4=84=E7=90=86=EF=BC=9B2.=E4=BF=AE=E6=94=B9?=
 =?UTF-8?q?static=5Fembedding=E8=B4=B4=E5=90=88seq2seq?=
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---
 fastNLP/core/trainer.py                | 18 +++++++++---------
 fastNLP/embeddings/static_embedding.py |  4 ++++
 2 files changed, 13 insertions(+), 9 deletions(-)

diff --git a/fastNLP/core/trainer.py b/fastNLP/core/trainer.py
index a5fea9bf..af68158c 100644
--- a/fastNLP/core/trainer.py
+++ b/fastNLP/core/trainer.py
@@ -617,6 +617,14 @@ class Trainer(object):
                 elif on_exception == 'raise':
                     raise e
 
+            if self.dev_data is not None and self.best_dev_perf is not None and load_best_model:
+                model_name = "best_" + "_".join([self.model.__class__.__name__, self.metric_key, self.start_time])
+                load_succeed = self._load_model(self.model, model_name)
+                if load_succeed:
+                    self.logger.info("Reloaded the best model.")
+                else:
+                    self.logger.info("Fail to reload best model.")
+        finally:
             if self.dev_data is not None and self.best_dev_perf is not None:
                 self.logger.info(
                     "\nIn Epoch:{}/Step:{}, got best dev performance:".format(self.best_dev_epoch, self.best_dev_step))
@@ -624,15 +632,7 @@ class Trainer(object):
                 results['best_eval'] = self.best_dev_perf
                 results['best_epoch'] = self.best_dev_epoch
                 results['best_step'] = self.best_dev_step
-                if load_best_model:
-                    model_name = "best_" + "_".join([self.model.__class__.__name__, self.metric_key, self.start_time])
-                    load_succeed = self._load_model(self.model, model_name)
-                    if load_succeed:
-                        self.logger.info("Reloaded the best model.")
-                    else:
-                        self.logger.info("Fail to reload best model.")
-        finally:
-            pass
+
         results['seconds'] = round(time.time() - start_time, 2)
 
         return results
diff --git a/fastNLP/embeddings/static_embedding.py b/fastNLP/embeddings/static_embedding.py
index fcfb3fec..42d30bac 100644
--- a/fastNLP/embeddings/static_embedding.py
+++ b/fastNLP/embeddings/static_embedding.py
@@ -76,6 +76,10 @@ class StaticEmbedding(TokenEmbedding):
         """
         super(StaticEmbedding, self).__init__(vocab, word_dropout=word_dropout, dropout=dropout)
         if embedding_dim > 0:
+            if model_dir_or_name is not None:
+                warnings.warn(f"StaticEmbedding will ignore `model_dir_or_name`, and randomly initialize embedding with"
+                              f" dimension {embedding_dim}. If you want to use pre-trained embedding, "
+                              f"set `embedding_dim` to 0.")
             model_dir_or_name = None
         
         # 得到cache_path