[BigFix] Fix the bool parameter inputting problem

applications/information_extraction/label_studio.py

@@ -33,6 +33,16 @@ def set_seed(seed):
     np.random.seed(seed)
 
 
+def str2bool(v):
+    """Support bool type for argparse."""
+    if v.lower() in ("yes", "true", "t", "y", "1"):
+        return True
+    elif v.lower() in ("no", "false", "f", "n", "0"):
+        return False
+    else:
+        raise argparse.ArgumentTypeError("Unsupported value encountered.")
+
+
 def do_convert():
     set_seed(args.seed)
 
@@ -125,7 +135,7 @@ def _save_examples(save_dir, file_name, examples):
     parser.add_argument("--task_type", choices=['ext', 'cls'], default="ext", type=str, help="Select task type, ext for the extraction task and cls for the classification task, defaults to ext.")
     parser.add_argument("--options", default=["正向", "负向"], type=str, nargs="+", help="Used only for the classification task, the options for classification")
     parser.add_argument("--prompt_prefix", default="情感倾向", type=str, help="Used only for the classification task, the prompt prefix for classification")
-    parser.add_argument("--is_shuffle", default=True, type=bool, help="Whether to shuffle the labeled dataset, defaults to True.")
+    parser.add_argument("--is_shuffle", default="True", type=str2bool, help="Whether to shuffle the labeled dataset, defaults to True.")
     parser.add_argument("--layout_analysis", default=False, type=bool, help="Enable layout analysis to optimize the order of OCR result.")
     parser.add_argument("--seed", type=int, default=1000, help="Random seed for initialization")
     parser.add_argument("--separator", type=str, default='##', help="Used only for entity/aspect-level classification task, separator for entity label and classification label")

applications/sentiment_analysis/unified_sentiment_extraction/label_studio.py

@@ -23,7 +23,7 @@
 
 import numpy as np
 import paddle
-from utils import load_txt
+from utils import load_txt, str2bool
 
 from paddlenlp.utils.log import logger
 
@@ -727,7 +727,7 @@ def _save_examples(save_dir, file_name, examples):
     parser.add_argument("--splits", default=[0.8, 0.1, 0.1], type=float, nargs="*", help="The ratio of samples in datasets. [0.6, 0.2, 0.2] means 60% samples used for training, 20% for evaluation and 20% for test.")
     parser.add_argument("--task_type", choices=['ext', 'cls'], default="ext", type=str, help="Two task types [ext, cls] are supported, ext represents the aspect-based extraction task and cls represents the sentence-level classification task, defaults to ext.")
     parser.add_argument("--options", type=str, nargs="+", help="Used only for the classification task, the options for classification")
-    parser.add_argument("--is_shuffle", default=True, type=bool, help="Whether to shuffle the labeled dataset, defaults to True.")
+    parser.add_argument("--is_shuffle", type=str2bool, default="True", help="Whether to shuffle the labeled dataset, defaults to True.")
     parser.add_argument("--seed", type=int, default=1000, help="Random seed for initialization")
 
     args = parser.parse_args()

applications/sentiment_analysis/unified_sentiment_extraction/utils.py

@@ -12,6 +12,7 @@
 # See the License for the specific language governing permissions and
 # limitations under the License.
 
+import argparse
 import json
 import random
 import re
@@ -50,6 +51,16 @@ def write_json_file(examples, save_path):
             f.write(line + "\n")
 
 
+def str2bool(v):
+    """Support bool type for argparse."""
+    if v.lower() in ("yes", "true", "t", "y", "1"):
+        return True
+    elif v.lower() in ("no", "false", "f", "n", "0"):
+        return False
+    else:
+        raise argparse.ArgumentTypeError("Unsupported value encountered.")
+
+
 def create_data_loader(dataset, mode="train", batch_size=1, trans_fn=None):
     """
     Create dataloader.

model_zoo/uie/doccano.py

@@ -13,15 +13,16 @@
 # See the License for the specific language governing permissions and
 # limitations under the License.
 
-import os
-import time
 import argparse
 import json
+import os
+import time
 from decimal import Decimal
+
 import numpy as np
-from paddlenlp.utils.log import logger
+from utils import convert_cls_examples, convert_ext_examples, set_seed, str2bool
 
-from utils import set_seed, convert_ext_examples, convert_cls_examples
+from paddlenlp.utils.log import logger
 
 
 def do_convert():
@@ -100,6 +101,8 @@ def _save_examples(save_dir, file_name, examples):
             indexes = np.random.permutation(len(raw_examples))
             index_list = indexes.tolist()
             raw_examples = [raw_examples[i] for i in indexes]
+        else:
+            index_list = list(range(len(raw_examples)))
 
         i1, i2, _ = args.splits
         p1 = int(len(raw_examples) * i1)
@@ -164,7 +167,7 @@ def _save_examples(save_dir, file_name, examples):
     parser.add_argument("--task_type", choices=['ext', 'cls'], default="ext", type=str, help="Select task type, ext for the extraction task and cls for the classification task, defaults to ext.")
     parser.add_argument("--options", default=["正向", "负向"], type=str, nargs="+", help="Used only for the classification task, the options for classification")
     parser.add_argument("--prompt_prefix", default="情感倾向", type=str, help="Used only for the classification task, the prompt prefix for classification")
-    parser.add_argument("--is_shuffle", default=True, type=bool, help="Whether to shuffle the labeled dataset, defaults to True.")
+    parser.add_argument("--is_shuffle", default="True", type=str2bool, help="Whether to shuffle the labeled dataset, defaults to True.")
     parser.add_argument("--seed", type=int, default=1000, help="Random seed for initialization")
     parser.add_argument("--separator", type=str, default='##', help="Used only for entity/aspect-level classification task, separator for entity label and classification label")
     parser.add_argument("--schema_lang", choices=["ch", "en"], default="ch", help="Select the language type for schema.")

model_zoo/uie/utils.py

@@ -12,6 +12,7 @@
 # See the License for the specific language governing permissions and
 # limitations under the License.
 
+import argparse
 import json
 import math
 import random
@@ -30,6 +31,16 @@ def set_seed(seed):
     np.random.seed(seed)
 
 
+def str2bool(v):
+    """Support bool type for argparse."""
+    if v.lower() in ("yes", "true", "t", "y", "1"):
+        return True
+    elif v.lower() in ("no", "false", "f", "n", "0"):
+        return False
+    else:
+        raise argparse.ArgumentTypeError("Unsupported value encountered.")
+
+
 def create_data_loader(dataset, mode="train", batch_size=1, trans_fn=None):
     """
     Create dataloader.