Mass text summarization fix bug.

model_zoo/mass/scripts/run.sh

@@ -18,7 +18,7 @@ export DEVICE_ID=0
 export RANK_ID=0
 export RANK_SIZE=1
 
-options=`getopt -u -o ht:n:i:j:c:o:v: -l help,task:,device_num:,device_id:,hccl_json:,config:,output:,vocab -- "$@"`
+options=`getopt -u -o ht:n:i:j:c:o:v: -l help,task:,device_num:,device_id:,hccl_json:,config:,output:,vocab: -- "$@"`
 eval set -- "$options"
 echo $options
 
@@ -129,6 +129,7 @@ do
 esac
 done
 
+file_path=$(cd "$(dirname $0)" || exit; pwd)
 for((i=0; i < $RANK_SIZE; i++))
 do
   if [ $RANK_SIZE -gt 1 ]
@@ -139,7 +140,6 @@ do
   fi
   echo "Working on device $i"
 
-  file_path=$(cd "$(dirname $0)" || exit; pwd)
   cd $file_path || exit
   cd ../ || exit
 

model_zoo/mass/src/dataset/load_dataset.py

@@ -13,7 +13,6 @@
 # limitations under the License.
 # ============================================================================
 """Dataset loader to feed into model."""
-import os
 import mindspore.common.dtype as mstype
 import mindspore.dataset.engine as de
 import mindspore.dataset.transforms.c_transforms as deC
@@ -40,12 +39,6 @@ def _load_dataset(input_files, batch_size, epoch_count=1,
     if not input_files:
         raise FileNotFoundError("Require at least one dataset.")
 
-    if not (schema_file and
-            os.path.exists(schema_file)
-            and os.path.isfile(schema_file)
-            and os.path.basename(schema_file).endswith(".json")):
-        raise FileNotFoundError("`dataset_schema` must be a existed json file.")
-
     if not isinstance(sink_mode, bool):
         raise ValueError("`sink` must be type of bool.")
 

model_zoo/mass/src/utils/rouge_score.py

@@ -47,7 +47,7 @@ def rouge(hypothesis: List[str], target: List[str]):
         edited_ref.append(r + "\n")
 
     _rouge = Rouge()
-    scores = _rouge.get_scores(edited_hyp, target, avg=True)
+    scores = _rouge.get_scores(edited_hyp, edited_ref, avg=True)
     print(" | ROUGE Score:")
     print(f" | RG-1(F): {scores['rouge-1']['f'] * 100:8.2f}")
     print(f" | RG-2(F): {scores['rouge-2']['f'] * 100:8.2f}")

model_zoo/mass/train.py

@@ -120,6 +120,7 @@ def _build_training_pipeline(config: TransformerConfig,
         test_dataset (Dataset): Test dataset.
     """
     net_with_loss = TransformerNetworkWithLoss(config, is_training=True)
+    net_with_loss.init_parameters_data()
 
     if config.existed_ckpt:
         if config.existed_ckpt.endswith(".npz"):