fix bugs in doccano.py and task.py (#2417)

* optimize code

* optimize code

Author: linjieccc

model_zoo/uie/doccano.py

@@ -16,6 +16,7 @@
 import time
 import argparse
 import json
+from decimal import Decimal
 import numpy as np
 from paddlenlp.utils.log import logger
 
@@ -35,7 +36,11 @@ def do_convert():
     if len(args.splits) != 0 and len(args.splits) != 3:
         raise ValueError("Only []/ len(splits)==3 accepted for splits.")
 
-    if args.splits and sum(args.splits) != 1:
+    def _check_sum(splits):
+        return Decimal(str(splits[0])) + Decimal(str(splits[1])) + Decimal(
+            str(splits[2])) == Decimal("1")
+
+    if len(args.splits) == 3 and not _check_sum(args.splits):
         raise ValueError(
             "Please set correct splits, sum of elements in splits should be equal to 1."
         )

paddlenlp/taskflow/task.py

@@ -208,15 +208,10 @@ def _prepare_onnx_mode(self):
         sess_options.inter_op_num_threads = self._num_threads
         self.predictor = ort.InferenceSession(
             fp16_model_file, sess_options=sess_options, providers=providers)
-        try:
-            assert 'CUDAExecutionProvider' in self.predictor.get_providers()
-        except AssertionError:
-            raise AssertionError(
-                f"The environment for GPU inference is not set properly. "
-                "A possible cause is that you had installed both onnxruntime and onnxruntime-gpu. "
-                "Please run the following commands to reinstall: \n "
-                "1) pip uninstall -y onnxruntime onnxruntime-gpu \n 2) pip install onnxruntime-gpu"
-            )
+        assert 'CUDAExecutionProvider' in self.predictor.get_providers(), f"The environment for GPU inference is not set properly. " \
+            "A possible cause is that you had installed both onnxruntime and onnxruntime-gpu. " \
+            "Please run the following commands to reinstall: \n " \
+            "1) pip uninstall -y onnxruntime onnxruntime-gpu \n 2) pip install onnxruntime-gpu"
 
     def _get_inference_model(self):
         """