[NeuralChat] Fix ner nightly ut bug (#822)

intel_extension_for_transformers/neural_chat/chatbot.py

@@ -101,9 +101,6 @@ def build_chatbot(config: PipelineConfig=None):
                 elif plugin_name == "ner":
                     from .pipeline.plugins.ner.ner import NamedEntityRecognition
                     plugins[plugin_name]['class'] = NamedEntityRecognition
-                elif plugin_name == "ner_int":
-                    from .pipeline.plugins.ner.ner_int import NamedEntityRecognitionINT
-                    plugins[plugin_name]['class'] = NamedEntityRecognitionINT
                 elif plugin_name == "face_animation": # pragma: no cover
                     from .pipeline.plugins.video.face_animation.sadtalker import SadTalker
                     plugins[plugin_name]['class'] = SadTalker

intel_extension_for_transformers/neural_chat/pipeline/plugins/ner/ner.py

@@ -15,20 +15,13 @@
 # See the License for the specific language governing permissions and
 # limitations under the License.
 
-from threading import Thread
-import re
 import time
-import torch
 import spacy
-from transformers import (
-    TextIteratorStreamer,
-)
 from .utils.utils import (
     enforce_stop_tokens,
     get_current_time
 )
 from .utils.process_text import process_time, process_entities
-from intel_extension_for_transformers.neural_chat.prompts import PromptTemplate
 
 
 class NamedEntityRecognition():

intel_extension_for_transformers/neural_chat/plugins.py

@@ -31,7 +31,6 @@ def reset_plugins(self):
             "cache": {"enable": False, "class": None, "args": {}, "instance": None},
             "safety_checker": {"enable": False, "class": None, "args": {}, "instance": None},
             "ner": {"enable": False, "class": None, "args": {}, "instance": None},
-            "ner_int": {"enable": False, "class": None, "args": {}, "instance": None},
             "face_animation": {"enable": False, "class": None, "args": {}, "instance": None}
         })
 

intel_extension_for_transformers/neural_chat/tests/nightly/plugins/test_ner.py

@@ -28,6 +28,7 @@ def setUp(self):
 
     def tearDown(self) -> None:
         for filename in os.getcwd():
+            import re
             if re.match(r'ne_.*_fp32.bin', filename) or re.match(r'ne_.*_q.bin', filename):
                 file_path = os.path.join(os.getcwd(), filename)
                 try:
@@ -37,55 +38,11 @@ def tearDown(self) -> None:
                     print(f"Error deleting file {filename}: {str(e)}")
         return super().tearDown()
 
-    def test_fp32(self):
+    def test_ner(self):
         os.system('python -m spacy download en_core_web_lg')
-        ner_obj = NamedEntityRecognition(model_path="/tf_dataset2/models/nlp_toolkit/mpt-7b")
+        ner_obj = NamedEntityRecognition()
         query = "Show me photos taken in Shanghai."
-        result = ner_obj.inference(query=query)
-        _result = {
-            'period': [], 
-            'time': [], 
-            'location': ['Shanghai'], 
-            'name': [], 
-            'organization': []
-        }
-        self.assertEqual(result, _result)
-
-    def test_bf16(self):
-        os.system('python -m spacy download en_core_web_lg')
-        ner_obj = NamedEntityRecognition(model_path="/tf_dataset2/models/nlp_toolkit/mpt-7b", bf16=True)
-        query = "Show me photos taken in Shanghai."
-        result = ner_obj.inference(query=query)
-        _result = {
-            'period': [], 
-            'time': [], 
-            'location': ['Shanghai'], 
-            'name': [], 
-            'organization': []
-        }
-        self.assertEqual(result, _result)
-
-    def test_int8(self):
-        os.system('python -m spacy download en_core_web_lg')
-        ner_obj = NamedEntityRecognitionINT(model_path="/tf_dataset2/models/nlp_toolkit/mpt-7b")
-        query = "Show me photos taken in Shanghai."
-        result = ner_obj.inference(query=query, threads=8)
-        _result = {
-            'period': [], 
-            'time': [], 
-            'location': ['Shanghai'], 
-            'name': [], 
-            'organization': []
-        }
-        self.assertEqual(result, _result)
-
-    def test_int4(self):
-        os.system('python -m spacy download en_core_web_lg')
-        ner_obj = NamedEntityRecognitionINT(model_path="/tf_dataset2/models/nlp_toolkit/mpt-7b", 
-                                            compute_dtype="int8", 
-                                            weight_dtype="int4")
-        query = "Show me photos taken in Shanghai."
-        result = ner_obj.inference(query=query, threads=8)
+        result = ner_obj.ner_inference(query)
         _result = {
             'period': [], 
             'time': [],