add classifier_pytorch ocnli

.gitignore

@@ -15,4 +15,7 @@ prev_trained_model
 .idea
 .idea/CLUE.iml
 .idea/misc.iml
-__pycache__
+baselines/models_pytorch/classifier_pytorch/CLUEdatasets
+baselines/models_pytorch/classifier_pytorch/*output
+baselines/models/bert/*output
+__pycache__

baselines/models/bert/run_classifier.py

@@ -29,6 +29,7 @@
 import tokenization
 import tensorflow as tf
 import sys
+import pdb
 sys.path.append('..')
 from classifier_utils import *
 
@@ -772,6 +773,7 @@ def main(_):
   num_warmup_steps = None
   if FLAGS.do_train:
     print("data_dir:", FLAGS.data_dir)
+    pdb.set_trace()
     train_examples = processor.get_train_examples(FLAGS.data_dir)
     num_train_steps = int(
         len(train_examples) / FLAGS.train_batch_size * FLAGS.num_train_epochs)

baselines/models_pytorch/classifier_pytorch/metrics/clue_compute_metrics.py

@@ -39,6 +39,8 @@ def compute_metrics(task_name, preds, labels):
         return {"acc": simple_accuracy(preds, labels)}
     elif task_name == "cmnli":
         return {"acc": simple_accuracy(preds, labels)}
+    elif task_name == "ocnli":
+        return {"acc": simple_accuracy(preds, labels)}
     elif task_name == "iflytek":
         return {"acc": simple_accuracy(preds, labels)}
     elif task_name == "wsc":

baselines/models_pytorch/classifier_pytorch/processors/clue.py

@@ -250,6 +250,41 @@ def _create_examples(self, lines, set_type):
                 InputExample(guid=guid, text_a=text_a, text_b=text_b, label=label))
         return examples
 
+class OcnliProcessor(DataProcessor):
+    """Processor for the CMNLI data set (CLUE version)."""
+
+    def get_train_examples(self, data_dir):
+        """See base class."""
+        return self._create_examples(
+            self._read_json(os.path.join(data_dir, "train.json")), "train")
+
+    def get_dev_examples(self, data_dir):
+        """See base class."""
+        return self._create_examples(
+            self._read_json(os.path.join(data_dir, "dev.json")), "dev")
+
+    def get_test_examples(self, data_dir):
+        """See base class."""
+        return self._create_examples(
+            self._read_json(os.path.join(data_dir, "test.json")), "test")
+
+    def get_labels(self):
+        """See base class."""
+        return ["contradiction", "entailment", "neutral"]
+
+    def _create_examples(self, lines, set_type):
+        """Creates examples for the training and dev sets."""
+        examples = []
+        for (i, line) in enumerate(lines):
+            guid = "%s-%s" % (set_type, i)
+            text_a = line["sentence1"]
+            text_b = line["sentence2"]
+            label = str(line["label"]) if set_type != 'test' else 'neutral'
+            if label.strip()=='-':
+                continue
+            examples.append(
+                InputExample(guid=guid, text_a=text_a, text_b=text_b, label=label))
+        return examples
 
 class CmnliProcessor(DataProcessor):
     """Processor for the CMNLI data set (CLUE version)."""
@@ -280,7 +315,9 @@ def _create_examples(self, lines, set_type):
             guid = "%s-%s" % (set_type, i)
             text_a = line["sentence1"]
             text_b = line["sentence2"]
-            label = str(line["gold_label"]) if set_type != 'test' else 'neutral'
+            label = str(line["label"]) if set_type != 'test' else 'neutral'
+            if label.strip()=='-':
+                continue
             examples.append(
                 InputExample(guid=guid, text_a=text_a, text_b=text_b, label=label))
         return examples
@@ -446,6 +483,7 @@ def _create_examples_version2(self, lines, set_type):
 clue_tasks_num_labels = {
     'iflytek': 119,
     'cmnli': 3,
+    'ocnli': 3,
     'afqmc': 2,
     'csl': 2,
     'wsc': 2,
@@ -457,6 +495,7 @@ def _create_examples_version2(self, lines, set_type):
     'tnews': TnewsProcessor,
     'iflytek': IflytekProcessor,
     'cmnli': CmnliProcessor,
+    'ocnli': OcnliProcessor,
     'afqmc': AfqmcProcessor,
     'csl': CslProcessor,
     'wsc': WscProcessor,
@@ -467,6 +506,7 @@ def _create_examples_version2(self, lines, set_type):
     'tnews': "classification",
     'iflytek': "classification",
     'cmnli': "classification",
+    'ocnli': "classification",
     'afqmc': "classification",
     'csl': "classification",
     'wsc': "classification",

baselines/models_pytorch/classifier_pytorch/run_classifier_ocnli.sh

@@ -0,0 +1,85 @@
+#!/usr/bin/env bash
+# @Author: bo.shi
+# @Date:   2019-11-04 09:56:36
+# @Last Modified by:   bo.shi
+# @Last Modified time: 2020-01-01 11:40:23
+
+TASK_NAME="ocnli"
+MODEL_NAME="bert-base-chinese"
+CURRENT_DIR=$(cd -P -- "$(dirname -- "$0")" && pwd -P)
+export CUDA_VISIBLE_DEVICES="0"
+export BERT_PRETRAINED_MODELS_DIR=$CURRENT_DIR/prev_trained_model
+export BERT_WWM_DIR=$BERT_PRETRAINED_MODELS_DIR/$MODEL_NAME
+export GLUE_DATA_DIR=$CURRENT_DIR/CLUEdatasets
+
+# download and unzip dataset
+if [ ! -d $GLUE_DATA_DIR ]; then
+  mkdir -p $GLUE_DATA_DIR
+  echo "makedir $GLUE_DATA_DIR"
+fi
+cd $GLUE_DATA_DIR
+if [ ! -d $TASK_NAME ]; then
+  mkdir $TASK_NAME
+  echo "makedir $GLUE_DATA_DIR/$TASK_NAME"
+fi
+cd $TASK_NAME
+if [ ! -f "train.json" ] || [ ! -f "dev.json" ] || [ ! -f "test.json" ]; then
+  rm *
+  wget https://storage.googleapis.com/cluebenchmark/tasks/cmnli_public.zip
+  unzip cmnli_public.zip
+  rm cmnli_public.zip
+else
+  echo "data exists"
+fi
+echo "Finish download dataset."
+
+# make output dir
+if [ ! -d $CURRENT_DIR/${TASK_NAME}_output ]; then
+  mkdir -p $CURRENT_DIR/${TASK_NAME}_output
+  echo "makedir $CURRENT_DIR/${TASK_NAME}_output"
+fi
+
+# run task
+cd $CURRENT_DIR
+echo "Start running..."
+if [ $# == 0 ]; then
+    python run_classifier.py \
+      --model_type=bert \
+      --model_name_or_path=$MODEL_NAME \
+      --task_name=$TASK_NAME \
+      --do_train \
+      --do_eval \
+      --do_lower_case \
+      --data_dir=$GLUE_DATA_DIR/${TASK_NAME}/ \
+      --max_seq_length=128 \
+      --per_gpu_train_batch_size=16 \
+      --per_gpu_eval_batch_size=16 \
+      --learning_rate=3e-5 \
+      --num_train_epochs=2.0 \
+      --logging_steps=24487 \
+      --save_steps=24487 \
+      --output_dir=$CURRENT_DIR/${TASK_NAME}_output/ \
+      --overwrite_output_dir \
+      --seed=42
+elif [ $1 == "predict" ]; then
+    echo "Start predict..."
+    python run_classifier.py \
+      --model_type=bert \
+      --model_name_or_path=$MODEL_NAME \
+      --task_name=$TASK_NAME \
+      --do_predict \
+      --do_lower_case \
+      --data_dir=$GLUE_DATA_DIR/${TASK_NAME}/ \
+      --max_seq_length=128 \
+      --per_gpu_train_batch_size=16 \
+      --per_gpu_eval_batch_size=16 \
+      --learning_rate=3e-5 \
+      --num_train_epochs=2.0 \
+      --logging_steps=24487 \
+      --save_steps=24487 \
+      --output_dir=$CURRENT_DIR/${TASK_NAME}_output/ \
+      --overwrite_output_dir \
+      --seed=42
+fi
+
+