From 839d712467b83a6bea1aab0b90e95f1432fc3ba6 Mon Sep 17 00:00:00 2001
From: yh_cc <poemsmileyh@gmail.com>
Date: Mon, 17 Jun 2019 16:46:39 +0800
Subject: [PATCH] =?UTF-8?q?=E5=A2=9E=E5=BC=BAfield=E4=B8=AD=E7=9A=84value?=
 =?UTF-8?q?=5Fcount=E6=94=AF=E6=8C=81=E5=AF=B9nested=E7=9A=84field?=
 =?UTF-8?q?=E7=9A=84=E6=94=AF=E6=8C=81?=
MIME-Version: 1.0
Content-Type: text/plain; charset=UTF-8
Content-Transfer-Encoding: 8bit

---
 fastNLP/core/field.py                | 9 ++++++++-
 fastNLP/modules/encoder/embedding.py | 1 -
 reproduction/utils.py                | 2 +-
 test/test_tutorials.py               | 6 +++---
 4 files changed, 12 insertions(+), 6 deletions(-)

diff --git a/fastNLP/core/field.py b/fastNLP/core/field.py
index faa306f3..b0a36765 100644
--- a/fastNLP/core/field.py
+++ b/fastNLP/core/field.py
@@ -350,8 +350,15 @@ class FieldArray:
         :return: Counter, key是label，value是出现次数
         """
         count = Counter()
+
+        def cum(cell):
+            if _is_iterable(cell) and not isinstance(cell, str):
+                for cell_ in cell:
+                    cum(cell_)
+            else:
+                count[cell] += 1
         for cell in self.content:
-            count[cell] += 1
+            cum(cell)
         return count
 
     def _after_process(self, new_contents, inplace):
diff --git a/fastNLP/modules/encoder/embedding.py b/fastNLP/modules/encoder/embedding.py
index 631f57e9..5f0b6c3b 100644
--- a/fastNLP/modules/encoder/embedding.py
+++ b/fastNLP/modules/encoder/embedding.py
@@ -326,7 +326,6 @@ class ElmoEmbedding(ContextualEmbedding):
 
         # 根据model_dir_or_name检查是否存在并下载
         PRETRAIN_URL = _get_base_url('elmo')
-        # TODO 把baidu云上的加上去
         PRETRAINED_ELMO_MODEL_DIR = {'en': 'elmo_en-d39843fe.tar.gz',
                                      'cn': 'elmo_cn-5e9b34e2.tar.gz'}
 
diff --git a/reproduction/utils.py b/reproduction/utils.py
index 58883b43..0d06c99c 100644
--- a/reproduction/utils.py
+++ b/reproduction/utils.py
@@ -24,7 +24,7 @@ def check_dataloader_paths(paths:Union[str, Dict[str, str]])->Dict[str, str]:
             if not os.path.isfile(train_fp):
                 raise FileNotFoundError(f"train.txt is not found in folder {paths}.")
             files = {'train': train_fp}
-            for filename in ['test.txt', 'dev.txt']:
+            for filename in ['dev.txt', 'test.txt']:
                 fp = os.path.join(paths, filename)
                 if os.path.isfile(fp):
                     files[filename.split('.')[0]] = fp
diff --git a/test/test_tutorials.py b/test/test_tutorials.py
index a38d5ae1..2e971a4f 100644
--- a/test/test_tutorials.py
+++ b/test/test_tutorials.py
@@ -80,7 +80,7 @@ class TestTutorial(unittest.TestCase):
         test_data.rename_field('label', 'label_seq')
 
         loss = CrossEntropyLoss(pred="output", target="label_seq")
-        metric = AccuracyMetric(pred="predict", target="label_seq")
+        metric = AccuracyMetric(target="label_seq")
 
         # 实例化Trainer，传入模型和数据，进行训练
         # 先在test_data拟合（确保模型的实现是正确的）
@@ -96,7 +96,7 @@ class TestTutorial(unittest.TestCase):
         # 用train_data训练，在test_data验证
         trainer = Trainer(model=model, train_data=train_data, dev_data=test_data,
                           loss=CrossEntropyLoss(pred="output", target="label_seq"),
-                          metrics=AccuracyMetric(pred="predict", target="label_seq"),
+                          metrics=AccuracyMetric(target="label_seq"),
                           save_path=None,
                           batch_size=32,
                           n_epochs=5)
@@ -106,7 +106,7 @@ class TestTutorial(unittest.TestCase):
         # 调用Tester在test_data上评价效果
         from fastNLP import Tester
 
-        tester = Tester(data=test_data, model=model, metrics=AccuracyMetric(pred="predict", target="label_seq"),
+        tester = Tester(data=test_data, model=model, metrics=AccuracyMetric(target="label_seq"),
                         batch_size=4)
         acc = tester.test()
         print(acc)