fix data distill for UIE

model_zoo/uie/data_distill/data_distill.py

@@ -23,7 +23,6 @@
 import numpy as np
 import paddle
 from paddlenlp import Taskflow
-from paddlenlp.taskflow.utils import SchemaTree
 from paddlenlp.utils.log import logger
 
 from utils import set_seed, build_tree, schema2label_maps, doccano2distill, synthetic2distill
@@ -84,7 +83,7 @@ def do_data_distill():
 
         infer_results = []
         for text in tqdm(infer_texts, desc="Predicting: ", leave=False):
-            infer_results.append(uie(text))
+            infer_results.extend(uie(text))
 
         train_synthetic_lines = synthetic2distill(texts, infer_results,
                                                   args.task_type)

model_zoo/uie/data_distill/evaluate_teacher.py

@@ -0,0 +1,101 @@
+# Copyright (c) 2022 PaddlePaddle Authors. All Rights Reserved.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+
+import argparse
+import json
+import os
+from tqdm import tqdm
+
+import paddle
+from paddlenlp.datasets import load_dataset
+from paddlenlp.transformers import AutoTokenizer, AutoModel
+from paddlenlp.utils.log import logger
+from paddlenlp.layers import GlobalPointerForEntityExtraction, GPLinkerForRelationExtraction
+from paddlenlp import Taskflow
+
+from utils import postprocess, create_dataloader, reader, get_label_maps
+from utils import get_label_maps, synthetic2distill
+from metric import get_eval
+
+
+@paddle.no_grad()
+def evaluate(uie, dataloader, task_type="relation_extraction"):
+    all_preds = ([], []) if task_type in [
+        "opinion_extraction", "relation_extraction", "event_extraction"
+    ] else []
+
+    infer_results = []
+    all_texts = []
+    for batch in tqdm(dataloader, desc="Evaluating: ", leave=False):
+        _, _, _, texts = batch
+        all_texts.extend(texts)
+        infer_results.extend(uie(texts))
+
+    infer_results = synthetic2distill(all_texts, infer_results, task_type)
+
+    for res in infer_results:
+        if task_type == "entity_extraction":
+            all_preds.append(res['entity_list'])
+        else:
+            all_preds[0].append(res['entity_list'])
+            all_preds[1].append(res['spo_list'])
+
+    eval_results = get_eval(all_preds, dataloader.dataset.raw_data, task_type)
+    return eval_results
+
+
+def do_eval():
+    # Load trained UIE model
+    uie = Taskflow("information_extraction",
+                   schema=args.schema,
+                   batch_size=args.batch_size,
+                   task_path=args.model_path)
+
+    label_maps = get_label_maps(args.task_type, args.label_maps_path)
+
+    tokenizer = AutoTokenizer.from_pretrained("ernie-3.0-base-zh")
+
+    test_ds = load_dataset(reader, data_path=args.test_path, lazy=False)
+
+    test_dataloader = create_dataloader(test_ds,
+                                        tokenizer,
+                                        max_seq_len=args.max_seq_len,
+                                        batch_size=args.batch_size,
+                                        label_maps=label_maps,
+                                        mode="test",
+                                        task_type=args.task_type)
+
+    eval_result = evaluate(uie, test_dataloader, task_type=args.task_type)
+    logger.info("Evaluation precision: " + str(eval_result))
+
+
+if __name__ == "__main__":
+    # yapf: disable
+    parser = argparse.ArgumentParser()
+
+    parser.add_argument("--model_path", type=str, default=None, help="The path of saved model that you want to load.")
+    parser.add_argument("--test_path", type=str, default=None, help="The path of test set.")
+    parser.add_argument("--label_maps_path", default="./ner_data/label_maps.json", type=str, help="The file path of the labels dictionary.")
+    parser.add_argument("--batch_size", type=int, default=8, help="Batch size per GPU/CPU for training.")
+    parser.add_argument("--max_seq_len", type=int, default=256, help="The maximum total input sequence length after tokenization.")
+    parser.add_argument("--task_type", choices=['relation_extraction', 'event_extraction', 'entity_extraction', 'opinion_extraction'], default="entity_extraction", type=str, help="Select the training task type.")
+
+    args = parser.parse_args()
+    # yapf: enable
+
+    schema = {"疾病": ["手术治疗", "实验室检查", "影像学检查"]}
+
+    args.schema = schema
+
+    do_eval()

model_zoo/uie/data_distill/utils.py

@@ -23,6 +23,7 @@
 import numpy as np
 import paddle
 from paddlenlp.utils.log import logger
+from paddlenlp.taskflow.utils import SchemaTree
 
 from data_collator import DataCollator