thunlp
diff --git a/‎dist/openprompt-1.0.0-py3-none-any.whl‎
30 Bytes b/‎dist/openprompt-1.0.0-py3-none-any.whl‎
30 Bytes
diff --git a/‎dist/openprompt-1.0.0.tar.gz‎
-236 Bytes b/‎dist/openprompt-1.0.0.tar.gz‎
-236 Bytes
diff --git a/‎docs/source/conf.py‎
Lines changed: 2 additions & 2 deletions b/‎docs/source/conf.py‎
Lines changed: 2 additions & 2 deletions
diff --git a/‎tutorial/3.1_LMBFF.py‎
Lines changed: 4 additions & 3 deletions b/‎tutorial/3.1_LMBFF.py‎
Lines changed: 4 additions & 3 deletions
@@ -31,8 +31,8 @@
 project = 'OpenPrompt'
 copyright = '{}, {}, Licenced under the Apache License, Version 2.0'.format(datetime.datetime.now().year, author)
 
-version = "v0.1.2"
-release = "v0.1.2"
+version = "v1.0.0"
+release = "v1.0.0"
 
 html_theme = 'sphinx_rtd_theme'
 html_theme_path = [sphinx_rtd_theme.get_html_theme_path()]
 
@@ -12,9 +12,9 @@
 # args = parser.parse_args()
 from openprompt.data_utils.text_classification_dataset import SST2Processor
 dataset = {}
-dataset['train'] = SST2Processor().get_train_examples("./datasets/TextClassification/SST-2/16-shot/16-13")
-dataset['validation'] = SST2Processor().get_dev_examples("./datasets/TextClassification/SST-2/16-shot/16-13")
-dataset['test'] = SST2Processor().get_test_examples("./datasets/TextClassification/SST-2/16-shot/16-13")
+dataset['train'] = SST2Processor().get_train_examples("../datasets/TextClassification/SST-2/16-shot/16-13")
+dataset['validation'] = SST2Processor().get_dev_examples("../datasets/TextClassification/SST-2/16-shot/16-13")
+dataset['test'] = SST2Processor().get_test_examples("../datasets/TextClassification/SST-2/16-shot/16-13")
 
 # %% [markdown]
 # ### 2. build initial verbalizer and template
@@ -114,6 +114,7 @@ def evaluate(model, val_dataloader):
 
 
     dataloader = PromptDataLoader(dataset['train'], template, template_generate_tokenizer, template_tokenizer_wrapper, batch_size=len(dataset['train']), decoder_max_length=128) # register all data at once
+    print('pass!')
     for data in dataloader:
         if cuda:
             data = data.cuda()