From e4a319d3e4092092be388b7fb953a8bb6036f2a3 Mon Sep 17 00:00:00 2001 From: Steffy-zxf <48793257+Steffy-zxf@users.noreply.github.com> Date: Fri, 29 May 2020 15:39:50 +0800 Subject: [PATCH] add ernie-skep (chnsenticorp) (#627) --- .../efficientnetb0_small_imagenet/module.py | 2 +- .../module.py | 2 +- .../mobilenet_v2_animals/module.py | 2 +- .../mobilenet_v2_dishes/module.py | 2 +- .../mobilenet_v2_imagenet_ssld/module.py | 2 +- .../module.py | 2 +- .../module.py | 2 +- .../resnet18_vd_imagenet/module.py | 2 +- .../resnet50_vd_animals/module.py | 2 +- .../resnet50_vd_dishes/module.py | 2 +- .../resnet50_vd_imagenet_ssld/module.py | 2 +- .../resnet50_vd_wildanimals/module.py | 2 +- .../se_resnet18_vd_imagenet/module.py | 2 +- .../pyramidbox_face_detection/module.py | 2 +- .../pyramidbox_lite_mobile/module.py | 2 +- .../pyramidbox_lite_mobile_mask/module.py | 2 +- .../pyramidbox_lite_server/module.py | 2 +- .../pyramidbox_lite_server_mask/module.py | 2 +- .../module.py | 2 +- .../module.py | 2 +- .../face_landmark_localization/module.py | 2 +- .../faster_rcnn_resnet50_coco2017/module.py | 2 +- .../module.py | 2 +- .../retinanet_resnet50_fpn_coco2017/module.py | 2 +- .../ssd_mobilenet_v1_pascal/module.py | 2 +- .../ssd_vgg16_512_coco2017/module.py | 2 +- .../yolov3_darknet53_coco2017/module.py | 2 +- .../yolov3_darknet53_pedestrian/module.py | 2 +- .../yolov3_darknet53_vehicles/module.py | 2 +- .../yolov3_mobilenet_v1_coco2017/module.py | 2 +- .../yolov3_resnet34_coco2017/module.py | 2 +- .../yolov3_resnet50_vd_coco2017/module.py | 2 +- .../semantic_segmentation/ace2p/module.py | 2 +- .../deeplabv3p_xception65_humanseg/module.py | 2 +- .../stylepro_artistic/module.py | 2 +- .../ernie_skep_sentiment_analysis/README.md | 152 + .../assets/ernie_1.0_large_ch.config.json | 14 + .../assets/ernie_1.0_large_ch.vocab.txt | 12089 ++++++++++++++++ .../model/__init__.py | 0 .../model/ernie.py | 377 + .../model/transformer_encoder.py | 501 + .../ernie_skep_sentiment_analysis/module.py | 258 + .../configs/ernie_skep_sentiment_analysis.yml | 9 + .../test_ernie_skep_sentiment_analysis.py | 129 + paddlehub/module/nlp_module.py | 2 - 45 files changed, 13564 insertions(+), 37 deletions(-) create mode 100644 hub_module/modules/text/sentiment_analysis/ernie_skep_sentiment_analysis/README.md create mode 100644 hub_module/modules/text/sentiment_analysis/ernie_skep_sentiment_analysis/assets/ernie_1.0_large_ch.config.json create mode 100644 hub_module/modules/text/sentiment_analysis/ernie_skep_sentiment_analysis/assets/ernie_1.0_large_ch.vocab.txt create mode 100644 hub_module/modules/text/sentiment_analysis/ernie_skep_sentiment_analysis/model/__init__.py create mode 100644 hub_module/modules/text/sentiment_analysis/ernie_skep_sentiment_analysis/model/ernie.py create mode 100644 hub_module/modules/text/sentiment_analysis/ernie_skep_sentiment_analysis/model/transformer_encoder.py create mode 100644 hub_module/modules/text/sentiment_analysis/ernie_skep_sentiment_analysis/module.py create mode 100644 hub_module/scripts/configs/ernie_skep_sentiment_analysis.yml create mode 100644 hub_module/tests/unittests/test_ernie_skep_sentiment_analysis.py diff --git a/hub_module/modules/image/classification/efficientnetb0_small_imagenet/module.py b/hub_module/modules/image/classification/efficientnetb0_small_imagenet/module.py index efd069f3..393092cb 100644 --- a/hub_module/modules/image/classification/efficientnetb0_small_imagenet/module.py +++ b/hub_module/modules/image/classification/efficientnetb0_small_imagenet/module.py @@ -175,7 +175,7 @@ class EfficientNetB0ImageNet(hub.Module): int(_places[0]) except: raise RuntimeError( - "Attempt to use GPU for prediction, but environment variable CUDA_VISIBLE_DEVICES was not set correctly." + "Environment Variable CUDA_VISIBLE_DEVICES is not set correctly. If you wanna use gpu, please set CUDA_VISIBLE_DEVICES as cuda_device_id." ) all_data = list() diff --git a/hub_module/modules/image/classification/fix_resnext101_32x48d_wsl_imagenet/module.py b/hub_module/modules/image/classification/fix_resnext101_32x48d_wsl_imagenet/module.py index 40a12edf..ffd4d064 100644 --- a/hub_module/modules/image/classification/fix_resnext101_32x48d_wsl_imagenet/module.py +++ b/hub_module/modules/image/classification/fix_resnext101_32x48d_wsl_imagenet/module.py @@ -161,7 +161,7 @@ class FixResnext10132x48dwslImagenet(hub.Module): int(_places[0]) except: raise RuntimeError( - "Attempt to use GPU for prediction, but environment variable CUDA_VISIBLE_DEVICES was not set correctly." + "Environment Variable CUDA_VISIBLE_DEVICES is not set correctly. If you wanna use gpu, please set CUDA_VISIBLE_DEVICES as cuda_device_id." ) if not self.predictor_set: diff --git a/hub_module/modules/image/classification/mobilenet_v2_animals/module.py b/hub_module/modules/image/classification/mobilenet_v2_animals/module.py index 87f6f53a..b8afcae0 100644 --- a/hub_module/modules/image/classification/mobilenet_v2_animals/module.py +++ b/hub_module/modules/image/classification/mobilenet_v2_animals/module.py @@ -161,7 +161,7 @@ class MobileNetV2Animals(hub.Module): int(_places[0]) except: raise RuntimeError( - "Attempt to use GPU for prediction, but environment variable CUDA_VISIBLE_DEVICES was not set correctly." + "Environment Variable CUDA_VISIBLE_DEVICES is not set correctly. If you wanna use gpu, please set CUDA_VISIBLE_DEVICES as cuda_device_id." ) all_data = list() diff --git a/hub_module/modules/image/classification/mobilenet_v2_dishes/module.py b/hub_module/modules/image/classification/mobilenet_v2_dishes/module.py index 3b9abdd5..f1be00a3 100644 --- a/hub_module/modules/image/classification/mobilenet_v2_dishes/module.py +++ b/hub_module/modules/image/classification/mobilenet_v2_dishes/module.py @@ -161,7 +161,7 @@ class MobileNetV2Dishes(hub.Module): int(_places[0]) except: raise RuntimeError( - "Attempt to use GPU for prediction, but environment variable CUDA_VISIBLE_DEVICES was not set correctly." + "Environment Variable CUDA_VISIBLE_DEVICES is not set correctly. If you wanna use gpu, please set CUDA_VISIBLE_DEVICES as cuda_device_id." ) all_data = list() diff --git a/hub_module/modules/image/classification/mobilenet_v2_imagenet_ssld/module.py b/hub_module/modules/image/classification/mobilenet_v2_imagenet_ssld/module.py index 598d7112..a2bacc74 100644 --- a/hub_module/modules/image/classification/mobilenet_v2_imagenet_ssld/module.py +++ b/hub_module/modules/image/classification/mobilenet_v2_imagenet_ssld/module.py @@ -184,7 +184,7 @@ class MobileNetV2ImageNetSSLD(hub.Module): int(_places[0]) except: raise RuntimeError( - "Attempt to use GPU for prediction, but environment variable CUDA_VISIBLE_DEVICES was not set correctly." + "Environment Variable CUDA_VISIBLE_DEVICES is not set correctly. If you wanna use gpu, please set CUDA_VISIBLE_DEVICES as cuda_device_id." ) all_data = list() diff --git a/hub_module/modules/image/classification/mobilenet_v3_large_imagenet_ssld/module.py b/hub_module/modules/image/classification/mobilenet_v3_large_imagenet_ssld/module.py index fcbe7374..07dd93a7 100644 --- a/hub_module/modules/image/classification/mobilenet_v3_large_imagenet_ssld/module.py +++ b/hub_module/modules/image/classification/mobilenet_v3_large_imagenet_ssld/module.py @@ -161,7 +161,7 @@ class MobileNetV3Large(hub.Module): int(_places[0]) except: raise RuntimeError( - "Attempt to use GPU for prediction, but environment variable CUDA_VISIBLE_DEVICES was not set correctly." + "Environment Variable CUDA_VISIBLE_DEVICES is not set correctly. If you wanna use gpu, please set CUDA_VISIBLE_DEVICES as cuda_device_id." ) all_data = list() diff --git a/hub_module/modules/image/classification/mobilenet_v3_small_imagenet_ssld/module.py b/hub_module/modules/image/classification/mobilenet_v3_small_imagenet_ssld/module.py index 4c447dbf..5e24ce93 100644 --- a/hub_module/modules/image/classification/mobilenet_v3_small_imagenet_ssld/module.py +++ b/hub_module/modules/image/classification/mobilenet_v3_small_imagenet_ssld/module.py @@ -161,7 +161,7 @@ class MobileNetV3Small(hub.Module): int(_places[0]) except: raise RuntimeError( - "Attempt to use GPU for prediction, but environment variable CUDA_VISIBLE_DEVICES was not set correctly." + "Environment Variable CUDA_VISIBLE_DEVICES is not set correctly. If you wanna use gpu, please set CUDA_VISIBLE_DEVICES as cuda_device_id." ) all_data = list() diff --git a/hub_module/modules/image/classification/resnet18_vd_imagenet/module.py b/hub_module/modules/image/classification/resnet18_vd_imagenet/module.py index 9870a5db..8171f3f0 100644 --- a/hub_module/modules/image/classification/resnet18_vd_imagenet/module.py +++ b/hub_module/modules/image/classification/resnet18_vd_imagenet/module.py @@ -161,7 +161,7 @@ class ResNet18vdImageNet(hub.Module): int(_places[0]) except: raise RuntimeError( - "Attempt to use GPU for prediction, but environment variable CUDA_VISIBLE_DEVICES was not set correctly." + "Environment Variable CUDA_VISIBLE_DEVICES is not set correctly. If you wanna use gpu, please set CUDA_VISIBLE_DEVICES as cuda_device_id." ) if not self.predictor_set: diff --git a/hub_module/modules/image/classification/resnet50_vd_animals/module.py b/hub_module/modules/image/classification/resnet50_vd_animals/module.py index 5c555eba..ed6abe6a 100644 --- a/hub_module/modules/image/classification/resnet50_vd_animals/module.py +++ b/hub_module/modules/image/classification/resnet50_vd_animals/module.py @@ -161,7 +161,7 @@ class ResNet50vdAnimals(hub.Module): int(_places[0]) except: raise RuntimeError( - "Attempt to use GPU for prediction, but environment variable CUDA_VISIBLE_DEVICES was not set correctly." + "Environment Variable CUDA_VISIBLE_DEVICES is not set correctly. If you wanna use gpu, please set CUDA_VISIBLE_DEVICES as cuda_device_id." ) all_data = list() diff --git a/hub_module/modules/image/classification/resnet50_vd_dishes/module.py b/hub_module/modules/image/classification/resnet50_vd_dishes/module.py index fb2f3de8..b554a8fc 100644 --- a/hub_module/modules/image/classification/resnet50_vd_dishes/module.py +++ b/hub_module/modules/image/classification/resnet50_vd_dishes/module.py @@ -161,7 +161,7 @@ class ResNet50vdDishes(hub.Module): int(_places[0]) except: raise RuntimeError( - "Attempt to use GPU for prediction, but environment variable CUDA_VISIBLE_DEVICES was not set correctly." + "Environment Variable CUDA_VISIBLE_DEVICES is not set correctly. If you wanna use gpu, please set CUDA_VISIBLE_DEVICES as cuda_device_id." ) all_data = list() diff --git a/hub_module/modules/image/classification/resnet50_vd_imagenet_ssld/module.py b/hub_module/modules/image/classification/resnet50_vd_imagenet_ssld/module.py index 9464a722..380eb839 100644 --- a/hub_module/modules/image/classification/resnet50_vd_imagenet_ssld/module.py +++ b/hub_module/modules/image/classification/resnet50_vd_imagenet_ssld/module.py @@ -161,7 +161,7 @@ class ResNet50vdDishes(hub.Module): int(_places[0]) except: raise RuntimeError( - "Attempt to use GPU for prediction, but environment variable CUDA_VISIBLE_DEVICES was not set correctly." + "Environment Variable CUDA_VISIBLE_DEVICES is not set correctly. If you wanna use gpu, please set CUDA_VISIBLE_DEVICES as cuda_device_id." ) all_data = list() diff --git a/hub_module/modules/image/classification/resnet50_vd_wildanimals/module.py b/hub_module/modules/image/classification/resnet50_vd_wildanimals/module.py index 14fd2f9c..3a8d811a 100644 --- a/hub_module/modules/image/classification/resnet50_vd_wildanimals/module.py +++ b/hub_module/modules/image/classification/resnet50_vd_wildanimals/module.py @@ -161,7 +161,7 @@ class ResNet50vdWildAnimals(hub.Module): int(_places[0]) except: raise RuntimeError( - "Attempt to use GPU for prediction, but environment variable CUDA_VISIBLE_DEVICES was not set correctly." + "Environment Variable CUDA_VISIBLE_DEVICES is not set correctly. If you wanna use gpu, please set CUDA_VISIBLE_DEVICES as cuda_device_id." ) all_data = list() diff --git a/hub_module/modules/image/classification/se_resnet18_vd_imagenet/module.py b/hub_module/modules/image/classification/se_resnet18_vd_imagenet/module.py index ec219bd8..4e6d6db7 100644 --- a/hub_module/modules/image/classification/se_resnet18_vd_imagenet/module.py +++ b/hub_module/modules/image/classification/se_resnet18_vd_imagenet/module.py @@ -161,7 +161,7 @@ class SEResNet18vdImageNet(hub.Module): int(_places[0]) except: raise RuntimeError( - "Attempt to use GPU for prediction, but environment variable CUDA_VISIBLE_DEVICES was not set correctly." + "Environment Variable CUDA_VISIBLE_DEVICES is not set correctly. If you wanna use gpu, please set CUDA_VISIBLE_DEVICES as cuda_device_id." ) if not self.predictor_set: diff --git a/hub_module/modules/image/face_detection/pyramidbox_face_detection/module.py b/hub_module/modules/image/face_detection/pyramidbox_face_detection/module.py index de0354e2..c62b8f43 100644 --- a/hub_module/modules/image/face_detection/pyramidbox_face_detection/module.py +++ b/hub_module/modules/image/face_detection/pyramidbox_face_detection/module.py @@ -83,7 +83,7 @@ class PyramidBoxFaceDetection(hub.Module): int(_places[0]) except: raise RuntimeError( - "Attempt to use GPU for prediction, but environment variable CUDA_VISIBLE_DEVICES was not set correctly." + "Environment Variable CUDA_VISIBLE_DEVICES is not set correctly. If you wanna use gpu, please set CUDA_VISIBLE_DEVICES as cuda_device_id." ) # compatibility with older versions diff --git a/hub_module/modules/image/face_detection/pyramidbox_lite_mobile/module.py b/hub_module/modules/image/face_detection/pyramidbox_lite_mobile/module.py index 9e30c589..77d05bc3 100644 --- a/hub_module/modules/image/face_detection/pyramidbox_lite_mobile/module.py +++ b/hub_module/modules/image/face_detection/pyramidbox_lite_mobile/module.py @@ -81,7 +81,7 @@ class PyramidBoxLiteMobile(hub.Module): int(_places[0]) except: raise RuntimeError( - "Attempt to use GPU for prediction, but environment variable CUDA_VISIBLE_DEVICES was not set correctly." + "Environment Variable CUDA_VISIBLE_DEVICES is not set correctly. If you wanna use gpu, please set CUDA_VISIBLE_DEVICES as cuda_device_id." ) # compatibility with older versions diff --git a/hub_module/modules/image/face_detection/pyramidbox_lite_mobile_mask/module.py b/hub_module/modules/image/face_detection/pyramidbox_lite_mobile_mask/module.py index 391aaedf..91b1adfa 100644 --- a/hub_module/modules/image/face_detection/pyramidbox_lite_mobile_mask/module.py +++ b/hub_module/modules/image/face_detection/pyramidbox_lite_mobile_mask/module.py @@ -107,7 +107,7 @@ class PyramidBoxLiteMobileMask(hub.Module): int(_places[0]) except: raise RuntimeError( - "Attempt to use GPU for prediction, but environment variable CUDA_VISIBLE_DEVICES was not set correctly." + "Environment Variable CUDA_VISIBLE_DEVICES is not set correctly. If you wanna use gpu, please set CUDA_VISIBLE_DEVICES as cuda_device_id." ) # compatibility with older versions diff --git a/hub_module/modules/image/face_detection/pyramidbox_lite_server/module.py b/hub_module/modules/image/face_detection/pyramidbox_lite_server/module.py index fe9b3b84..739739b7 100644 --- a/hub_module/modules/image/face_detection/pyramidbox_lite_server/module.py +++ b/hub_module/modules/image/face_detection/pyramidbox_lite_server/module.py @@ -81,7 +81,7 @@ class PyramidBoxLiteServer(hub.Module): int(_places[0]) except: raise RuntimeError( - "Attempt to use GPU for prediction, but environment variable CUDA_VISIBLE_DEVICES was not set correctly." + "Environment Variable CUDA_VISIBLE_DEVICES is not set correctly. If you wanna use gpu, please set CUDA_VISIBLE_DEVICES as cuda_device_id." ) # compatibility with older versions diff --git a/hub_module/modules/image/face_detection/pyramidbox_lite_server_mask/module.py b/hub_module/modules/image/face_detection/pyramidbox_lite_server_mask/module.py index 8fd45be7..59270c64 100644 --- a/hub_module/modules/image/face_detection/pyramidbox_lite_server_mask/module.py +++ b/hub_module/modules/image/face_detection/pyramidbox_lite_server_mask/module.py @@ -106,7 +106,7 @@ class PyramidBoxLiteServerMask(hub.Module): int(_places[0]) except: raise RuntimeError( - "Attempt to use GPU for prediction, but environment variable CUDA_VISIBLE_DEVICES was not set correctly." + "Environment Variable CUDA_VISIBLE_DEVICES is not set correctly. If you wanna use gpu, please set CUDA_VISIBLE_DEVICES as cuda_device_id." ) # compatibility with older versions diff --git a/hub_module/modules/image/face_detection/ultra_light_fast_generic_face_detector_1mb_320/module.py b/hub_module/modules/image/face_detection/ultra_light_fast_generic_face_detector_1mb_320/module.py index dafd8525..8237b7f3 100644 --- a/hub_module/modules/image/face_detection/ultra_light_fast_generic_face_detector_1mb_320/module.py +++ b/hub_module/modules/image/face_detection/ultra_light_fast_generic_face_detector_1mb_320/module.py @@ -107,7 +107,7 @@ class FaceDetector320(hub.Module): int(_places[0]) except: raise RuntimeError( - "Attempt to use GPU for prediction, but environment variable CUDA_VISIBLE_DEVICES was not set correctly." + "Environment Variable CUDA_VISIBLE_DEVICES is not set correctly. If you wanna use gpu, please set CUDA_VISIBLE_DEVICES as cuda_device_id." ) # compatibility with older versions diff --git a/hub_module/modules/image/face_detection/ultra_light_fast_generic_face_detector_1mb_640/module.py b/hub_module/modules/image/face_detection/ultra_light_fast_generic_face_detector_1mb_640/module.py index 32075ed6..16352378 100644 --- a/hub_module/modules/image/face_detection/ultra_light_fast_generic_face_detector_1mb_640/module.py +++ b/hub_module/modules/image/face_detection/ultra_light_fast_generic_face_detector_1mb_640/module.py @@ -106,7 +106,7 @@ class FaceDetector640(hub.Module): int(_places[0]) except: raise RuntimeError( - "Attempt to use GPU for prediction, but environment variable CUDA_VISIBLE_DEVICES was not set correctly." + "Environment Variable CUDA_VISIBLE_DEVICES is not set correctly. If you wanna use gpu, please set CUDA_VISIBLE_DEVICES as cuda_device_id." ) # compatibility with older versions diff --git a/hub_module/modules/image/keypoint_detection/face_landmark_localization/module.py b/hub_module/modules/image/keypoint_detection/face_landmark_localization/module.py index 7c8d25d6..5b21ad79 100644 --- a/hub_module/modules/image/keypoint_detection/face_landmark_localization/module.py +++ b/hub_module/modules/image/keypoint_detection/face_landmark_localization/module.py @@ -133,7 +133,7 @@ class FaceLandmarkLocalization(hub.Module): int(_places[0]) except: raise RuntimeError( - "Attempt to use GPU for prediction, but environment variable CUDA_VISIBLE_DEVICES was not set correctly." + "Environment Variable CUDA_VISIBLE_DEVICES is not set correctly. If you wanna use gpu, please set CUDA_VISIBLE_DEVICES as cuda_device_id." ) # get all data diff --git a/hub_module/modules/image/object_detection/faster_rcnn_resnet50_coco2017/module.py b/hub_module/modules/image/object_detection/faster_rcnn_resnet50_coco2017/module.py index b65aa88e..c61cc84a 100644 --- a/hub_module/modules/image/object_detection/faster_rcnn_resnet50_coco2017/module.py +++ b/hub_module/modules/image/object_detection/faster_rcnn_resnet50_coco2017/module.py @@ -323,7 +323,7 @@ class FasterRCNNResNet50(hub.Module): int(_places[0]) except: raise RuntimeError( - "Attempt to use GPU for prediction, but environment variable CUDA_VISIBLE_DEVICES was not set correctly." + "Environment Variable CUDA_VISIBLE_DEVICES is not set correctly. If you wanna use gpu, please set CUDA_VISIBLE_DEVICES as cuda_device_id." ) paths = paths if paths else list() if data and 'image' in data: diff --git a/hub_module/modules/image/object_detection/faster_rcnn_resnet50_fpn_coco2017/module.py b/hub_module/modules/image/object_detection/faster_rcnn_resnet50_fpn_coco2017/module.py index c64f1297..f84521ac 100644 --- a/hub_module/modules/image/object_detection/faster_rcnn_resnet50_fpn_coco2017/module.py +++ b/hub_module/modules/image/object_detection/faster_rcnn_resnet50_fpn_coco2017/module.py @@ -333,7 +333,7 @@ class FasterRCNNResNet50RPN(hub.Module): int(_places[0]) except: raise RuntimeError( - "Attempt to use GPU for prediction, but environment variable CUDA_VISIBLE_DEVICES was not set correctly." + "Environment Variable CUDA_VISIBLE_DEVICES is not set correctly. If you wanna use gpu, please set CUDA_VISIBLE_DEVICES as cuda_device_id." ) paths = paths if paths else list() diff --git a/hub_module/modules/image/object_detection/retinanet_resnet50_fpn_coco2017/module.py b/hub_module/modules/image/object_detection/retinanet_resnet50_fpn_coco2017/module.py index 4025bb87..83effbdb 100644 --- a/hub_module/modules/image/object_detection/retinanet_resnet50_fpn_coco2017/module.py +++ b/hub_module/modules/image/object_detection/retinanet_resnet50_fpn_coco2017/module.py @@ -240,7 +240,7 @@ class RetinaNetResNet50FPN(hub.Module): int(_places[0]) except: raise RuntimeError( - "Attempt to use GPU for prediction, but environment variable CUDA_VISIBLE_DEVICES was not set correctly." + "Environment Variable CUDA_VISIBLE_DEVICES is not set correctly. If you wanna use gpu, please set CUDA_VISIBLE_DEVICES as cuda_device_id." ) all_images = list() diff --git a/hub_module/modules/image/object_detection/ssd_mobilenet_v1_pascal/module.py b/hub_module/modules/image/object_detection/ssd_mobilenet_v1_pascal/module.py index 315bb2dd..a433d779 100644 --- a/hub_module/modules/image/object_detection/ssd_mobilenet_v1_pascal/module.py +++ b/hub_module/modules/image/object_detection/ssd_mobilenet_v1_pascal/module.py @@ -194,7 +194,7 @@ class SSDMobileNetv1(hub.Module): int(_places[0]) except: raise RuntimeError( - "Attempt to use GPU for prediction, but environment variable CUDA_VISIBLE_DEVICES was not set correctly." + "Environment Variable CUDA_VISIBLE_DEVICES is not set correctly. If you wanna use gpu, please set CUDA_VISIBLE_DEVICES as cuda_device_id." ) paths = paths if paths else list() diff --git a/hub_module/modules/image/object_detection/ssd_vgg16_512_coco2017/module.py b/hub_module/modules/image/object_detection/ssd_vgg16_512_coco2017/module.py index a0514153..bdf252ad 100644 --- a/hub_module/modules/image/object_detection/ssd_vgg16_512_coco2017/module.py +++ b/hub_module/modules/image/object_detection/ssd_vgg16_512_coco2017/module.py @@ -200,7 +200,7 @@ class SSDVGG16_512(hub.Module): int(_places[0]) except: raise RuntimeError( - "Attempt to use GPU for prediction, but environment variable CUDA_VISIBLE_DEVICES was not set correctly." + "Environment Variable CUDA_VISIBLE_DEVICES is not set correctly. If you wanna use gpu, please set CUDA_VISIBLE_DEVICES as cuda_device_id." ) paths = paths if paths else list() diff --git a/hub_module/modules/image/object_detection/yolov3_darknet53_coco2017/module.py b/hub_module/modules/image/object_detection/yolov3_darknet53_coco2017/module.py index 9ffe7022..f3ebbda1 100644 --- a/hub_module/modules/image/object_detection/yolov3_darknet53_coco2017/module.py +++ b/hub_module/modules/image/object_detection/yolov3_darknet53_coco2017/module.py @@ -186,7 +186,7 @@ class YOLOv3DarkNet53Coco2017(hub.Module): int(_places[0]) except: raise RuntimeError( - "Attempt to use GPU for prediction, but environment variable CUDA_VISIBLE_DEVICES was not set correctly." + "Environment Variable CUDA_VISIBLE_DEVICES is not set correctly. If you wanna use gpu, please set CUDA_VISIBLE_DEVICES as cuda_device_id." ) paths = paths if paths else list() diff --git a/hub_module/modules/image/object_detection/yolov3_darknet53_pedestrian/module.py b/hub_module/modules/image/object_detection/yolov3_darknet53_pedestrian/module.py index 6f76e25c..1258b757 100644 --- a/hub_module/modules/image/object_detection/yolov3_darknet53_pedestrian/module.py +++ b/hub_module/modules/image/object_detection/yolov3_darknet53_pedestrian/module.py @@ -199,7 +199,7 @@ class YOLOv3DarkNet53Pedestrian(hub.Module): int(_places[0]) except: raise RuntimeError( - "Attempt to use GPU for prediction, but environment variable CUDA_VISIBLE_DEVICES was not set correctly." + "Environment Variable CUDA_VISIBLE_DEVICES is not set correctly. If you wanna use gpu, please set CUDA_VISIBLE_DEVICES as cuda_device_id." ) paths = paths if paths else list() diff --git a/hub_module/modules/image/object_detection/yolov3_darknet53_vehicles/module.py b/hub_module/modules/image/object_detection/yolov3_darknet53_vehicles/module.py index 685afbff..e1a064cd 100644 --- a/hub_module/modules/image/object_detection/yolov3_darknet53_vehicles/module.py +++ b/hub_module/modules/image/object_detection/yolov3_darknet53_vehicles/module.py @@ -199,7 +199,7 @@ class YOLOv3DarkNet53Vehicles(hub.Module): int(_places[0]) except: raise RuntimeError( - "Attempt to use GPU for prediction, but environment variable CUDA_VISIBLE_DEVICES was not set correctly." + "Environment Variable CUDA_VISIBLE_DEVICES is not set correctly. If you wanna use gpu, please set CUDA_VISIBLE_DEVICES as cuda_device_id." ) paths = paths if paths else list() diff --git a/hub_module/modules/image/object_detection/yolov3_mobilenet_v1_coco2017/module.py b/hub_module/modules/image/object_detection/yolov3_mobilenet_v1_coco2017/module.py index 03bde930..674e6aa5 100644 --- a/hub_module/modules/image/object_detection/yolov3_mobilenet_v1_coco2017/module.py +++ b/hub_module/modules/image/object_detection/yolov3_mobilenet_v1_coco2017/module.py @@ -189,7 +189,7 @@ class YOLOv3MobileNetV1Coco2017(hub.Module): int(_places[0]) except: raise RuntimeError( - "Attempt to use GPU for prediction, but environment variable CUDA_VISIBLE_DEVICES was not set correctly." + "Environment Variable CUDA_VISIBLE_DEVICES is not set correctly. If you wanna use gpu, please set CUDA_VISIBLE_DEVICES as cuda_device_id." ) paths = paths if paths else list() diff --git a/hub_module/modules/image/object_detection/yolov3_resnet34_coco2017/module.py b/hub_module/modules/image/object_detection/yolov3_resnet34_coco2017/module.py index 98712df2..54f4f427 100644 --- a/hub_module/modules/image/object_detection/yolov3_resnet34_coco2017/module.py +++ b/hub_module/modules/image/object_detection/yolov3_resnet34_coco2017/module.py @@ -191,7 +191,7 @@ class YOLOv3ResNet34Coco2017(hub.Module): int(_places[0]) except: raise RuntimeError( - "Attempt to use GPU for prediction, but environment variable CUDA_VISIBLE_DEVICES was not set correctly." + "Environment Variable CUDA_VISIBLE_DEVICES is not set correctly. If you wanna use gpu, please set CUDA_VISIBLE_DEVICES as cuda_device_id." ) paths = paths if paths else list() diff --git a/hub_module/modules/image/object_detection/yolov3_resnet50_vd_coco2017/module.py b/hub_module/modules/image/object_detection/yolov3_resnet50_vd_coco2017/module.py index 4e5a4d05..2e65abfe 100644 --- a/hub_module/modules/image/object_detection/yolov3_resnet50_vd_coco2017/module.py +++ b/hub_module/modules/image/object_detection/yolov3_resnet50_vd_coco2017/module.py @@ -193,7 +193,7 @@ class YOLOv3ResNet50Coco2017(hub.Module): int(_places[0]) except: raise RuntimeError( - "Attempt to use GPU for prediction, but environment variable CUDA_VISIBLE_DEVICES was not set correctly." + "Environment Variable CUDA_VISIBLE_DEVICES is not set correctly. If you wanna use gpu, please set CUDA_VISIBLE_DEVICES as cuda_device_id." ) paths = paths if paths else list() diff --git a/hub_module/modules/image/semantic_segmentation/ace2p/module.py b/hub_module/modules/image/semantic_segmentation/ace2p/module.py index 149b981e..d8908525 100644 --- a/hub_module/modules/image/semantic_segmentation/ace2p/module.py +++ b/hub_module/modules/image/semantic_segmentation/ace2p/module.py @@ -86,7 +86,7 @@ class ACE2P(hub.Module): int(_places[0]) except: raise RuntimeError( - "Attempt to use GPU for prediction, but environment variable CUDA_VISIBLE_DEVICES was not set correctly." + "Environment Variable CUDA_VISIBLE_DEVICES is not set correctly. If you wanna use gpu, please set CUDA_VISIBLE_DEVICES as cuda_device_id." ) # compatibility with older versions diff --git a/hub_module/modules/image/semantic_segmentation/deeplabv3p_xception65_humanseg/module.py b/hub_module/modules/image/semantic_segmentation/deeplabv3p_xception65_humanseg/module.py index 84c4b762..b6f0f227 100644 --- a/hub_module/modules/image/semantic_segmentation/deeplabv3p_xception65_humanseg/module.py +++ b/hub_module/modules/image/semantic_segmentation/deeplabv3p_xception65_humanseg/module.py @@ -82,7 +82,7 @@ class DeeplabV3pXception65HumanSeg(hub.Module): int(_places[0]) except: raise RuntimeError( - "Attempt to use GPU for prediction, but environment variable CUDA_VISIBLE_DEVICES was not set correctly." + "Environment Variable CUDA_VISIBLE_DEVICES is not set correctly. If you wanna use gpu, please set CUDA_VISIBLE_DEVICES as cuda_device_id." ) # compatibility with older versions diff --git a/hub_module/modules/image/style_transfer/stylepro_artistic/module.py b/hub_module/modules/image/style_transfer/stylepro_artistic/module.py index 86373516..7fc14612 100644 --- a/hub_module/modules/image/style_transfer/stylepro_artistic/module.py +++ b/hub_module/modules/image/style_transfer/stylepro_artistic/module.py @@ -104,7 +104,7 @@ class StyleProjection(hub.Module): int(_places[0]) except: raise RuntimeError( - "Attempt to use GPU for prediction, but environment variable CUDA_VISIBLE_DEVICES was not set correctly." + "Environment Variable CUDA_VISIBLE_DEVICES is not set correctly. If you wanna use gpu, please set CUDA_VISIBLE_DEVICES as cuda_device_id." ) im_output = [] diff --git a/hub_module/modules/text/sentiment_analysis/ernie_skep_sentiment_analysis/README.md b/hub_module/modules/text/sentiment_analysis/ernie_skep_sentiment_analysis/README.md new file mode 100644 index 00000000..46417e6f --- /dev/null +++ b/hub_module/modules/text/sentiment_analysis/ernie_skep_sentiment_analysis/README.md @@ -0,0 +1,152 @@ +## 概述 + +SKEP（Sentiment Knowledge Enhanced Pre-training for Sentiment Analysis）是百度研究团队在2020年提出的基于情感知识增强的情感预训练算法，此算法采用无监督方法自动挖掘情感知识，然后利用情感知识构建预训练目标，从而让机器学会理解情感语义，在14项中英情感分析典型任务上全面超越SOTA，相关工作已经被ACL 2020录用。SKEP为各类情感分析任务提供统一且强大的情感语义表示。ernie_skep_sentiment_analysis Module可用于句子级情感分析任务预测。其在预训练时使用ERNIE 1.0 large预训练参数作为其网络参数初始化继续预训练。同时，该Module支持完成句子级情感分析任务迁移学习Fine-tune。 + +

+
+

+ +更多详情参考ACL 2020论文[SKEP: Sentiment Knowledge Enhanced Pre-training for Sentiment Analysis](https://arxiv.org/abs/2005.05635) + +## 命令行预测 + +```shell +$ hub run ernie_skep_sentiment_analysis --input_text='虽然小明很努力，但是他还是没有考100分' +``` + +## API + +```python +def predict_sentiment(texts=[], use_gpu=False) +``` + +预测API，分类输入文本的情感极性。 + +**参数** + +* texts (list\[str\]): 待预测文本； +* use\_gpu (bool): 是否使用 GPU；**若使用GPU，请先设置CUDA_VISIBLE_DEVICES环境变量**； + +**返回** + +* res (list\[dict\]): 情感分类结果的列表，列表中每一个元素为 dict，各字段为： + * text(str): 输入预测文本 + * sentiment_label(str): 情感分类结果，或为positive或为negative + * positive_probs: 输入预测文本情感极性属于positive的概率 + * negative_probs: 输入预测文本情感极性属于negative的概率 + +```python +def context(trainable=True, max_seq_len=128) +``` +用于获取Module的上下文信息，得到输入、输出以及预训练的Paddle Program副本 + +**参数** +* trainable(bool): 设置为True时，Module中的参数在Fine-tune时也会随之训练，否则保持不变。 +* max_seq_len(int): SKEP模型的最大序列长度，若序列长度不足，会通过padding方式补到**max_seq_len**, 若序列长度大于该值，则会以截断方式让序列长度为**max_seq_len**，max_seq_len可取值范围为0～512； + +**返回** +* inputs: dict类型，各字段为： + * input_ids(Variable): Token Embedding，shape为\[batch_size, max_seq_len\]，dtype为int64类型； + * position_id(Variable): Position Embedding，shape为\[batch_size, max_seq_len\]，dtype为int64类型； + * segment_ids(Variable): Sentence Embedding，shape为\[batch_size, max_seq_len\]，dtype为int64类型； + * input_mask(Variable): token是否为padding的标识，shape为\[batch_size, max_seq_len\]，dtype为int64类型； + +* outputs：dict类型，Module的输出特征，各字段为： + * pooled_output(Variable): 句子粒度的特征，可用于文本分类等任务，shape为 \[batch_size, 768\]，dtype为int64类型； + * sequence_output(Variable): 字粒度的特征，可用于序列标注等任务，shape为 \[batch_size, seq_len, 768\]，dtype为int64类型； + +* program：包含该Module计算图的Program。 + +```python +def get_embedding(texts, use_gpu=False, batch_size=1) +``` + +用于获取输入文本的句子粒度特征与字粒度特征 + +**参数** + +* texts(list)：输入文本列表，格式为\[\[sample\_a\_text\_a, sample\_a\_text\_b\], \[sample\_b\_text\_a, sample\_b\_text\_b\],…,\]，其中每个元素都是一个样例，每个样例可以包含text\_a与text\_b。 +* use_gpu(bool)：是否使用gpu，默认为False。对于GPU用户，建议开启use_gpu。**若使用GPU，请先设置CUDA_VISIBLE_DEVICES环境变量**； + +**返回** + +* results(list): embedding特征，格式为\[\[sample\_a\_pooled\_feature, sample\_a\_seq\_feature\], \[sample\_b\_pooled\_feature, sample\_b\_seq\_feature\],…,\]，其中每个元素都是对应样例的特征输出，每个样例都有句子粒度特征pooled\_feature与字粒度特征seq\_feature。 + +```python +def get_params_layer() +``` + +用于获取参数层信息，该方法与ULMFiTStrategy联用可以严格按照层数设置分层学习率与逐层解冻。 + +**参数** + +* 无 + +**返回** + +* params_layer(dict): key为参数名，值为参数所在层数 + +**代码示例** + +情感极性预测代码示例： + +```python +import paddlehub as hub + +# Load ernie_skep_sentiment_analysis module. +module = hub.Module(name="ernie_skep_sentiment_analysis") + +# Predict sentiment label +test_texts = ['你不是不聪明，而是不认真', '虽然小明很努力，但是他还是没有考100分'] +results = module.predict_sentiment(test_texts, use_gpu=False) +``` + +## 服务部署 + +PaddleHub Serving 可以部署一个目标检测的在线服务。 + +### 第一步：启动PaddleHub Serving + +运行启动命令： +```shell +$ hub serving start -m ernie_skep_sentiment_analysis +``` + +这样就完成了一个目标检测的服务化API的部署，默认端口号为8866。 + +**NOTE:** 如使用GPU预测，则需要在启动服务之前，请设置CUDA\_VISIBLE\_DEVICES环境变量，否则不用设置。 + +### 第二步：发送预测请求 + +配置好服务端，以下数行代码即可实现发送预测请求，获取预测结果 + +```python +import requests +import json + +# 发送HTTP请求 +data = {'texts':['你不是不聪明，而是不认真', '虽然小明很努力，但是他还是没有考100分']} +headers = {"Content-type": "application/json"} +url = "http://127.0.0.1:8866/predict/ernie_skep_sentiment_analysis" +r = requests.post(url=url, headers=headers, data=json.dumps(data)) + +# 打印预测结果 +print(r.json()["results"]) +``` + +## 查看代码 + +https://github.com/baidu/Senta + +### 依赖 + +paddlepaddle >= 1.8.0 + +paddlehub >= 1.7.0 + + +## 更新历史 + +* 1.0.0 + + 初始发布 diff --git a/hub_module/modules/text/sentiment_analysis/ernie_skep_sentiment_analysis/assets/ernie_1.0_large_ch.config.json b/hub_module/modules/text/sentiment_analysis/ernie_skep_sentiment_analysis/assets/ernie_1.0_large_ch.config.json new file mode 100644 index 00000000..75c3303b --- /dev/null +++ b/hub_module/modules/text/sentiment_analysis/ernie_skep_sentiment_analysis/assets/ernie_1.0_large_ch.config.json @@ -0,0 +1,14 @@ +{ + "attention_probs_dropout_prob": 0.1, + "hidden_act": "relu", + "hidden_dropout_prob": 0.1, + "hidden_size": 1024, + "initializer_range": 0.02, + "max_position_embeddings": 512, + "num_attention_heads": 16, + "num_hidden_layers": 24, + "sent_type_vocab_size": 4, + "task_type_vocab_size": 16, + "vocab_size": 12800, + "use_task_id": false +} diff --git a/hub_module/modules/text/sentiment_analysis/ernie_skep_sentiment_analysis/assets/ernie_1.0_large_ch.vocab.txt b/hub_module/modules/text/sentiment_analysis/ernie_skep_sentiment_analysis/assets/ernie_1.0_large_ch.vocab.txt new file mode 100644 index 00000000..e9604e7a --- /dev/null +++ b/hub_module/modules/text/sentiment_analysis/ernie_skep_sentiment_analysis/assets/ernie_1.0_large_ch.vocab.txt @@ -0,0 +1,12089 @@ +[PAD] 0 +[CLS] 1 +[SEP] 2 +[MASK] 3 +， 4 +的 5 +、 6 +一 7 +人 8 +有 9 +是 10 +在 11 +中 12 +为 13 +和 14 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11966 +apt 11967 +##pass 11968 +jing 11969 +##rix 11970 +rich 11971 +niusnews 11972 +##ello 11973 +bag 11974 +##eting 11975 +##mobile 11976 +##ience 11977 +details 11978 +universal 11979 +silver 11980 +dit 11981 +private 11982 +ddd 11983 +u11 11984 +kanshu 11985 +##ified 11986 +fung 11987 +##nny 11988 +dx 11989 +##520 11990 +tai 11991 +023 11992 +##fr 11993 +##lean 11994 +##pin 11995 +##rin 11996 +ly 11997 +rick 11998 +##bility 11999 +banner 12000 +##baru 12001 +##gion 12002 +vdf 12003 +qualcomm 12004 +bear 12005 +oldid 12006 +ian 12007 +jo 12008 +##tors 12009 +population 12010 +##ernel 12011 +##mv 12012 +##bike 12013 +ww 12014 +##ager 12015 +exhibition 12016 +##del 12017 +##pods 12018 +fpx 12019 +structure 12020 +##free 12021 +##tings 12022 +kl 12023 +##rley 12024 +##copyright 12025 +##mma 12026 +orange 12027 +yoga 12028 +4l 12029 +canmake 12030 +honey 12031 +##anda 12032 +nikkie 12033 +dhl 12034 +publishing 12035 +##mall 12036 +##gnet 12037 +e88 12038 +##dog 12039 +fishbase 12040 +### 12041 +##[ 12042 +。 12043 +！ 12044 +？ 12045 +! 12046 +? 12047 +； 12048 +: 12049 +; 12050 +- 12051 +( 12052 +) 12053 +/ 12054 ++ 12055 +" 12056 +_ 12057 +… 12058 +~ 12059 += 12060 +' 12061 +% 12062 +& 12063 +· 12064 +* 12065 +@ 12066 +\ 12067 +] 12068 +— 12069 +～ 12070 +^ 12071 +> 12072 +丨 12073 +| 12074 +< 12075 +】 12076 +の 12077 +【 12078 +〔 12079 +〕 12080 +ー 12081 +★ 12082 +’ 12083 +$ 12084 +{ 12085 +} 12086 +‘ 12087 +[UNK] 12088 diff --git a/hub_module/modules/text/sentiment_analysis/ernie_skep_sentiment_analysis/model/__init__.py b/hub_module/modules/text/sentiment_analysis/ernie_skep_sentiment_analysis/model/__init__.py new file mode 100644 index 00000000..e69de29b diff --git a/hub_module/modules/text/sentiment_analysis/ernie_skep_sentiment_analysis/model/ernie.py b/hub_module/modules/text/sentiment_analysis/ernie_skep_sentiment_analysis/model/ernie.py new file mode 100644 index 00000000..5846878c --- /dev/null +++ b/hub_module/modules/text/sentiment_analysis/ernie_skep_sentiment_analysis/model/ernie.py @@ -0,0 +1,377 @@ +# -*- coding:utf-8 -** +# Copyright (c) 2019 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. +"""ERNIE""" + +from __future__ import absolute_import +from __future__ import division +from __future__ import print_function +from __future__ import unicode_literals + +import json +import logging + +import paddle.fluid as fluid +import six + +from .transformer_encoder import encoder, pre_process_layer +from .transformer_encoder import gelu + + +class ErnieModel(object): + """ + ErnieModel + """ + + def __init__(self, + src_ids, + position_ids, + sentence_ids, + input_mask, + config, + weight_sharing=True, + use_fp16=False): + """ + :param src_ids: + :param position_ids: + :param sentence_ids: + :param input_mask: + :param config: + :param weight_sharing: + :param use_fp16: + """ + self._hidden_size = config.get('hidden_size', 768) + self._emb_size = config.get('emb_size', self._hidden_size) + self._n_layer = config.get('num_hidden_layers', 12) + self._n_head = config.get('num_attention_heads', 12) + self._voc_size = config.get('vocab_size', 30522) + self._max_position_seq_len = config.get('max_position_embeddings', 512) + self._param_share = config.get('param_share', "normal") + self._pre_encoder_cmd = config.get('pre_encoder_cmd', "nd") + self._preprocess_cmd = config.get('preprocess_cmd', "") + self._postprocess_cmd = config.get('postprocess_cmd', "dan") + self._epsilon = config.get('epsilon', 1e-05) + self._emb_mapping_in = config.get('emb_mapping_in', False) + self._n_layer_per_block = config.get('n_layer_per_block', 1) + + if config.has('sent_type_vocab_size'): + self._sent_types = config['sent_type_vocab_size'] + else: + self._sent_types = config.get('type_vocab_size', 2) + + self._use_sentence_id = config.get('use_sentence_id', True) + self._use_task_id = config.get('use_task_id', False) + if self._use_task_id: + self._task_types = config.get('task_type_vocab_size', 3) + self._hidden_act = config.get('hidden_act', 'gelu') + self._prepostprocess_dropout = config.get('hidden_dropout_prob', 0.1) + self._attention_dropout = config.get('attention_probs_dropout_prob', + 0.1) + self._weight_sharing = weight_sharing + + self._word_emb_name = "word_embedding" + self._pos_emb_name = "pos_embedding" + self._sent_emb_name = "sent_embedding" + self._task_emb_name = "task_embedding" + self._dtype = "float16" if use_fp16 else "float32" + self._emb_dtype = "float32" + # Initialize all weigths by truncated normal initializer, and all biases + # will be initialized by constant zero by default. + self._param_initializer = fluid.initializer.TruncatedNormal( + scale=config.get('initializer_range', 0.02)) + + self._build_model(src_ids, position_ids, sentence_ids, input_mask) + + def _build_model(self, src_ids, position_ids, sentence_ids, input_mask): + """ + :param src_ids: + :param position_ids: + :param sentence_ids: + :param input_mask: + :return: + """ + # padding id in vocabulary must be set to 0 + emb_out = fluid.layers.embedding( + input=src_ids, + dtype=self._emb_dtype, + size=[self._voc_size, self._emb_size], + param_attr=fluid.ParamAttr( + name=self._word_emb_name, initializer=self._param_initializer), + is_sparse=False) + + position_emb_out = fluid.layers.embedding( + input=position_ids, + dtype=self._emb_dtype, + size=[self._max_position_seq_len, self._emb_size], + param_attr=fluid.ParamAttr( + name=self._pos_emb_name, initializer=self._param_initializer)) + + emb_out = emb_out + position_emb_out + + if self._use_sentence_id: + sent_emb_out = fluid.layers.embedding( + sentence_ids, + dtype=self._emb_dtype, + size=[self._sent_types, self._emb_size], + param_attr=fluid.ParamAttr( + name=self._sent_emb_name, + initializer=self._param_initializer)) + + emb_out = emb_out + sent_emb_out + + emb_out = pre_process_layer( + emb_out, + self._pre_encoder_cmd, + self._prepostprocess_dropout, + name='pre_encoder', + epsilon=self._epsilon) + + if self._emb_mapping_in: + emb_out = fluid.layers.fc( + input=emb_out, + num_flatten_dims=2, + size=self._hidden_size, + param_attr=fluid.ParamAttr( + name='emb_hidden_mapping', + initializer=self._param_initializer), + bias_attr='emb_hidden_mapping_bias') + + if self._dtype == "float16": + emb_out = fluid.layers.cast(x=emb_out, dtype=self._dtype) + input_mask = fluid.layers.cast(x=input_mask, dtype=self._dtype) + self_attn_mask = fluid.layers.matmul( + x=input_mask, y=input_mask, transpose_y=True) + + self_attn_mask = fluid.layers.scale( + x=self_attn_mask, scale=10000.0, bias=-1.0, bias_after_scale=False) + n_head_self_attn_mask = fluid.layers.stack( + x=[self_attn_mask] * self._n_head, axis=1) + n_head_self_attn_mask.stop_gradient = True + + self._enc_out, self._checkpoints = encoder( + enc_input=emb_out, + attn_bias=n_head_self_attn_mask, + n_layer=self._n_layer, + n_head=self._n_head, + d_key=self._hidden_size // self._n_head, + d_value=self._hidden_size // self._n_head, + d_model=self._hidden_size, + d_inner_hid=self._hidden_size * 4, + prepostprocess_dropout=self._prepostprocess_dropout, + attention_dropout=self._attention_dropout, + relu_dropout=0, + hidden_act=self._hidden_act, + preprocess_cmd=self._preprocess_cmd, + postprocess_cmd=self._postprocess_cmd, + param_initializer=self._param_initializer, + name='encoder', + param_share=self._param_share, + epsilon=self._epsilon, + n_layer_per_block=self._n_layer_per_block) + if self._dtype == "float16": + self._enc_out = fluid.layers.cast( + x=self._enc_out, dtype=self._emb_dtype) + + def get_sequence_output(self): + """ + :return: + """ + return self._enc_out + + def get_pooled_output(self): + """Get the first feature of each sequence for classification""" + next_sent_feat = fluid.layers.slice( + input=self._enc_out, axes=[1], starts=[0], ends=[1]) + """ + if self._dtype == "float16": + next_sent_feat = fluid.layers.cast( + x=next_sent_feat, dtype=self._emb_dtype) + + next_sent_feat = fluid.layers.fc( + input=next_sent_feat, + size=self._emb_size, + param_attr=fluid.ParamAttr( + name="mask_lm_trans_fc.w_0", initializer=self._param_initializer), + bias_attr="mask_lm_trans_fc.b_0") + """ + """ + next_sent_feat = fluid.layers.fc( + input=next_sent_feat, + size=self._emb_size, + param_attr=fluid.ParamAttr( + name="mask_lm_trans_fc.w_0", initializer=self._param_initializer), + bias_attr="mask_lm_trans_fc.b_0") + + """ + next_sent_feat = fluid.layers.fc( + input=next_sent_feat, + size=self._hidden_size, + act="tanh", + param_attr=fluid.ParamAttr( + name="pooled_fc.w_0", initializer=self._param_initializer), + bias_attr="pooled_fc.b_0") + return next_sent_feat + + def get_lm_output(self, mask_label, mask_pos): + """Get the loss & accuracy for pretraining""" + mask_pos = fluid.layers.cast(x=mask_pos, dtype='int32') + # extract the first token feature in each sentence + self.next_sent_feat = self.get_pooled_output() + reshaped_emb_out = fluid.layers.reshape( + x=self._enc_out, shape=[-1, self._hidden_size]) + # extract masked tokens' feature + mask_feat = fluid.layers.gather(input=reshaped_emb_out, index=mask_pos) + + if self._dtype == "float16": + mask_feat = fluid.layers.cast(x=mask_feat, dtype=self._emb_dtype) + + # transform: fc + if self._hidden_act == 'gelu' or self._hidden_act == 'gelu.precise': + _hidden_act = 'gelu' + elif self._hidden_act == 'gelu.approximate': + _hidden_act = None + else: + _hidden_act = self._hidden_act + mask_trans_feat = fluid.layers.fc( + input=mask_feat, + size=self._emb_size, + act=_hidden_act, + param_attr=fluid.ParamAttr( + name='mask_lm_trans_fc.w_0', + initializer=self._param_initializer), + bias_attr=fluid.ParamAttr(name='mask_lm_trans_fc.b_0')) + if self._hidden_act == 'gelu.approximate': + mask_trans_feat = gelu(mask_trans_feat) + else: + pass + # transform: layer norm + mask_trans_feat = fluid.layers.layer_norm( + mask_trans_feat, + begin_norm_axis=len(mask_trans_feat.shape) - 1, + param_attr=fluid.ParamAttr( + name='mask_lm_trans_layer_norm_scale', + initializer=fluid.initializer.Constant(1.)), + bias_attr=fluid.ParamAttr( + name='mask_lm_trans_layer_norm_bias', + initializer=fluid.initializer.Constant(1.))) + # transform: layer norm + # mask_trans_feat = pre_process_layer( + # mask_trans_feat, 'n', name='mask_lm_trans') + + mask_lm_out_bias_attr = fluid.ParamAttr( + name="mask_lm_out_fc.b_0", + initializer=fluid.initializer.Constant(value=0.0)) + if self._weight_sharing: + fc_out = fluid.layers.matmul( + x=mask_trans_feat, + y=fluid.default_main_program().global_block().var( + self._word_emb_name), + transpose_y=True) + fc_out += fluid.layers.create_parameter( + shape=[self._voc_size], + dtype=self._emb_dtype, + attr=mask_lm_out_bias_attr, + is_bias=True) + + else: + fc_out = fluid.layers.fc( + input=mask_trans_feat, + size=self._voc_size, + param_attr=fluid.ParamAttr( + name="mask_lm_out_fc.w_0", + initializer=self._param_initializer), + bias_attr=mask_lm_out_bias_attr) + + mask_lm_loss = fluid.layers.softmax_with_cross_entropy( + logits=fc_out, label=mask_label) + mean_mask_lm_loss = fluid.layers.mean(mask_lm_loss) + + return mean_mask_lm_loss + + def get_task_output(self, task, task_labels): + """ + :param task: + :param task_labels: + :return: + """ + task_fc_out = fluid.layers.fc( + input=self.next_sent_feat, + size=task["num_labels"], + param_attr=fluid.ParamAttr( + name=task["task_name"] + "_fc.w_0", + initializer=self._param_initializer), + bias_attr=task["task_name"] + "_fc.b_0") + task_loss, task_softmax = fluid.layers.softmax_with_cross_entropy( + logits=task_fc_out, label=task_labels, return_softmax=True) + task_acc = fluid.layers.accuracy(input=task_softmax, label=task_labels) + mean_task_loss = fluid.layers.mean(task_loss) + return mean_task_loss, task_acc + + +class ErnieConfig(object): + """parse ernie config""" + + def __init__(self, config_path): + """ + :param config_path: + """ + self._config_dict = self._parse(config_path) + + def _parse(self, config_path): + """ + :param config_path: + :return: + """ + try: + with open(config_path, 'r') as json_file: + config_dict = json.load(json_file) + except Exception: + raise IOError( + "Error in parsing Ernie model config file '%s'" % config_path) + else: + return config_dict + + def __getitem__(self, key): + """ + :param key: + :return: + """ + return self._config_dict.get(key, None) + + def has(self, key): + """ + :param key: + :return: + """ + if key in self._config_dict: + return True + return False + + def get(self, key, default_value): + """ + :param key,default_value: + :retrun: + """ + if key in self._config_dict: + return self._config_dict[key] + else: + return default_value + + def print_config(self): + """ + :return: + """ + for arg, value in sorted(six.iteritems(self._config_dict)): + logging.info('%s: %s' % (arg, value)) + logging.info('------------------------------------------------') diff --git a/hub_module/modules/text/sentiment_analysis/ernie_skep_sentiment_analysis/model/transformer_encoder.py b/hub_module/modules/text/sentiment_analysis/ernie_skep_sentiment_analysis/model/transformer_encoder.py new file mode 100644 index 00000000..80f7a775 --- /dev/null +++ b/hub_module/modules/text/sentiment_analysis/ernie_skep_sentiment_analysis/model/transformer_encoder.py @@ -0,0 +1,501 @@ +# -*- coding:utf-8 -** +# Copyright (c) 2019 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. +"""Transformer encoder.""" + +from __future__ import absolute_import +from __future__ import division +from __future__ import print_function + +from functools import partial + +import paddle.fluid as fluid +import paddle.fluid.layers as layers +import numpy as np + + +def gelu(x): + """Gaussian Error Linear Unit. + + This is a smoother version of the RELU. + Original paper: https://arxiv.org/abs/1606.08415 + Args: + x: float Tensor to perform activation. + + Returns: + `x` with the GELU activation applied. + """ + cdf = 0.5 * (1.0 + fluid.layers.tanh( + (np.sqrt(2.0 / np.pi) * (x + 0.044715 * fluid.layers.pow(x, 3.0))))) + return x * cdf + + +def multi_head_attention(queries, + keys, + values, + attn_bias, + d_key, + d_value, + d_model, + n_head=1, + dropout_rate=0., + cache=None, + param_initializer=None, + name='multi_head_att'): + """ + Multi-Head Attention. Note that attn_bias is added to the logit before + computing softmax activiation to mask certain selected positions so that + they will not considered in attention weights. + """ + keys = queries if keys is None else keys + values = keys if values is None else values + if not (len(queries.shape) == len(keys.shape) == len(values.shape) == 3): + raise ValueError( + "Inputs: quries, keys and values should all be 3-D tensors. but {} v.s. {} v.s. {}"\ + .format(queries.shape, keys.shape, values.shape)) + + def __compute_qkv(queries, keys, values, n_head, d_key, d_value): + """ + Add linear projection to queries, keys, and values. + """ + q = layers.fc( + input=queries, + size=d_key * n_head, + num_flatten_dims=2, + param_attr=fluid.ParamAttr( + name=name + '_query_fc.w_0', initializer=param_initializer), + bias_attr=name + '_query_fc.b_0') + k = layers.fc( + input=keys, + size=d_key * n_head, + num_flatten_dims=2, + param_attr=fluid.ParamAttr( + name=name + '_key_fc.w_0', initializer=param_initializer), + bias_attr=name + '_key_fc.b_0') + v = layers.fc( + input=values, + size=d_value * n_head, + num_flatten_dims=2, + param_attr=fluid.ParamAttr( + name=name + '_value_fc.w_0', initializer=param_initializer), + bias_attr=name + '_value_fc.b_0') + return q, k, v + + def __split_heads(x, n_head): + """ + Reshape the last dimension of inpunt tensor x so that it becomes two + dimensions and then transpose. Specifically, input a tensor with shape + [bs, max_sequence_length, n_head * hidden_dim] then output a tensor + with shape [bs, n_head, max_sequence_length, hidden_dim]. + """ + hidden_size = x.shape[-1] + # The value 0 in shape attr means copying the corresponding dimension + # size of the input as the output dimension size. + reshaped = layers.reshape( + x=x, shape=[0, 0, n_head, hidden_size // n_head], inplace=True) + + # permuate the dimensions into: + # [batch_size, n_head, max_sequence_len, hidden_size_per_head] + return layers.transpose(x=reshaped, perm=[0, 2, 1, 3]) + + def __combine_heads(x): + """ + Transpose and then reshape the last two dimensions of inpunt tensor x + so that it becomes one dimension, which is reverse to __split_heads. + """ + if len(x.shape) == 3: return x + if len(x.shape) != 4: + raise ValueError("Input(x) should be a 4-D Tensor.") + + trans_x = layers.transpose(x, perm=[0, 2, 1, 3]) + # The value 0 in shape attr means copying the corresponding dimension + # size of the input as the output dimension size. + return layers.reshape( + x=trans_x, + shape=[0, 0, trans_x.shape[2] * trans_x.shape[3]], + inplace=True) + + def scaled_dot_product_attention(q, k, v, attn_bias, d_key, dropout_rate): + """ + Scaled Dot-Product Attention + """ + scaled_q = layers.scale(x=q, scale=d_key**-0.5) + product = layers.matmul(x=scaled_q, y=k, transpose_y=True) + if attn_bias: + product += attn_bias + weights = layers.softmax(product) + if dropout_rate: + weights = layers.dropout( + weights, + dropout_prob=dropout_rate, + dropout_implementation="upscale_in_train", + is_test=False) + out = layers.matmul(weights, v) + return out + + q, k, v = __compute_qkv(queries, keys, values, n_head, d_key, d_value) + + if cache is not None: # use cache and concat time steps + # Since the inplace reshape in __split_heads changes the shape of k and + # v, which is the cache input for next time step, reshape the cache + # input from the previous time step first. + k = cache["k"] = layers.concat( + [layers.reshape(cache["k"], shape=[0, 0, d_model]), k], axis=1) + v = cache["v"] = layers.concat( + [layers.reshape(cache["v"], shape=[0, 0, d_model]), v], axis=1) + + q = __split_heads(q, n_head) + k = __split_heads(k, n_head) + v = __split_heads(v, n_head) + + ctx_multiheads = scaled_dot_product_attention(q, k, v, attn_bias, d_key, + dropout_rate) + + out = __combine_heads(ctx_multiheads) + + # Project back to the model size. + proj_out = layers.fc( + input=out, + size=d_model, + num_flatten_dims=2, + param_attr=fluid.ParamAttr( + name=name + '_output_fc.w_0', initializer=param_initializer), + bias_attr=name + '_output_fc.b_0') + return proj_out + + +def positionwise_feed_forward(x, + d_inner_hid, + d_hid, + dropout_rate, + hidden_act, + param_initializer=None, + name='ffn'): + """ + Position-wise Feed-Forward Networks. + This module consists of two linear transformations with a ReLU activation + in between, which is applied to each position separately and identically. + """ + if hidden_act == 'gelu' or hidden_act == 'gelu.precise': + _hidden_act = 'gelu' + elif hidden_act == 'gelu.approximate': + _hidden_act = None + else: + _hidden_act = hidden_act + hidden = layers.fc( + input=x, + size=d_inner_hid, + num_flatten_dims=2, + act=_hidden_act, + param_attr=fluid.ParamAttr( + name=name + '_fc_0.w_0', initializer=param_initializer), + bias_attr=name + '_fc_0.b_0') + if hidden_act == 'gelu.approximate': + hidden = gelu(hidden) + + if dropout_rate: + hidden = layers.dropout( + hidden, + dropout_prob=dropout_rate, + dropout_implementation="upscale_in_train", + is_test=False) + out = layers.fc( + input=hidden, + size=d_hid, + num_flatten_dims=2, + param_attr=fluid.ParamAttr( + name=name + '_fc_1.w_0', initializer=param_initializer), + bias_attr=name + '_fc_1.b_0') + return out + + +def pre_post_process_layer(prev_out, + out, + process_cmd, + dropout_rate=0., + epsilon=1e-12, + name=''): + """ + Add residual connection, layer normalization and droput to the out tensor + optionally according to the value of process_cmd. + This will be used before or after multi-head attention and position-wise + feed-forward networks. + """ + for cmd in process_cmd: + if cmd == "a": # add residual connection + out = out + prev_out if prev_out else out + elif cmd == "n": # add layer normalization + out_dtype = out.dtype + if out_dtype == fluid.core.VarDesc.VarType.FP16: + out = layers.cast(x=out, dtype="float32") + out = layers.layer_norm( + out, + begin_norm_axis=len(out.shape) - 1, + param_attr=fluid.ParamAttr( + name=name + '_layer_norm_scale', + initializer=fluid.initializer.Constant(1.)), + bias_attr=fluid.ParamAttr( + name=name + '_layer_norm_bias', + initializer=fluid.initializer.Constant(0.)), + epsilon=epsilon) + if out_dtype == fluid.core.VarDesc.VarType.FP16: + out = layers.cast(x=out, dtype="float16") + elif cmd == "d": # add dropout + if dropout_rate: + out = layers.dropout( + out, + dropout_prob=dropout_rate, + dropout_implementation="upscale_in_train", + is_test=False) + return out + + +pre_process_layer = partial(pre_post_process_layer, None) +post_process_layer = pre_post_process_layer + + +def encoder_layer( + enc_input, + attn_bias, + n_head, + d_key, + d_value, + d_model, + d_inner_hid, + prepostprocess_dropout, + attention_dropout, + relu_dropout, + hidden_act, + preprocess_cmd="n", + postprocess_cmd="da", + param_initializer=None, + name='', + epsilon=1e-12, +): + """The encoder layers that can be stacked to form a deep encoder. + This module consits of a multi-head (self) attention followed by + position-wise feed-forward networks and both the two components companied + with the post_process_layer to add residual connection, layer normalization + and droput. + """ + + attn_output = multi_head_attention( + enc_input, + None, + None, + attn_bias, + d_key, + d_value, + d_model, + n_head, + attention_dropout, + param_initializer=param_initializer, + name=name + '_multi_head_att') + + attn_output = post_process_layer( + enc_input, + attn_output, + postprocess_cmd, + prepostprocess_dropout, + name=name + '_post_att', + epsilon=epsilon) + + ffd_output = positionwise_feed_forward( + attn_output, + d_inner_hid, + d_model, + relu_dropout, + hidden_act, + param_initializer=param_initializer, + name=name + '_ffn') + + return post_process_layer( + attn_output, + ffd_output, + postprocess_cmd, + prepostprocess_dropout, + name=name + '_post_ffn', + epsilon=epsilon), ffd_output + + +def encoder_inner_share(enc_input, + attn_bias, + n_head, + d_key, + d_value, + d_model, + d_inner_hid, + prepostprocess_dropout, + attention_dropout, + relu_dropout, + hidden_act, + preprocess_cmd, + postprocess_cmd, + epsilon, + param_initializer=None, + name='', + n_layer_per_block=1): + """ + The encoder_inner_share is composed of n_layer_per_block layers returned by calling + encoder_layer. + """ + _checkpoints = [] + for i in range(n_layer_per_block): + enc_output, cp = encoder_layer( + enc_input, + attn_bias, + n_head, + d_key, + d_value, + d_model, + d_inner_hid, + prepostprocess_dropout, + attention_dropout, + relu_dropout, + hidden_act, + preprocess_cmd, + postprocess_cmd, + param_initializer=param_initializer, + name=name + '_layer_' + str(i), + epsilon=epsilon, + ) + _checkpoints.append(cp) + enc_input = enc_output + + return enc_output, _checkpoints + + +def encoder_outer_share(enc_input, + attn_bias, + n_head, + d_key, + d_value, + d_model, + d_inner_hid, + prepostprocess_dropout, + attention_dropout, + relu_dropout, + hidden_act, + preprocess_cmd, + postprocess_cmd, + epsilon, + param_initializer=None, + name='', + n_layer_per_block=1): + """ + The encoder_outer_share is composed of n_layer_per_block layers returned by calling + encoder_layer. + """ + _checkpoints = [] + for i in range(n_layer_per_block): + enc_output, cp = encoder_layer( + enc_input, + attn_bias, + n_head, + d_key, + d_value, + d_model, + d_inner_hid, + prepostprocess_dropout, + attention_dropout, + relu_dropout, + hidden_act, + preprocess_cmd, + postprocess_cmd, + param_initializer=param_initializer, + name=name, + epsilon=epsilon) + _checkpoints.append(cp) + enc_input = enc_output + + return enc_output, _checkpoints + + +def encoder(enc_input, + attn_bias, + n_layer, + n_head, + d_key, + d_value, + d_model, + d_inner_hid, + prepostprocess_dropout, + attention_dropout, + relu_dropout, + hidden_act, + preprocess_cmd, + postprocess_cmd, + epsilon, + n_layer_per_block, + param_initializer=None, + name='', + param_share=None): + """ + The encoder is composed of a stack of identical layers returned by calling + encoder_layer . + """ + checkpoints = [] + # for outer_share it will share same param in one block, + # and for inner_share it will share param across blocks, rather than in one same block + # + # outer-share inner-share + # [1] [1] ----\ 1st block + # [1] [2] ----/ + # [2] [1] ----\ 2nd block + # [2] [2] ----/ + + if param_share == "normal" or param_share == 'outer_share': + #n_layer_per_block=1, n_layer=24 for bert-large + #n_layer_per_block=1, n_layer=12 for bert-base + #n_layer_per_block=12, n_layer=12 for albert-xxlarge + #n_layer_per_block=6, n_layer=12 for albert-xxlarge-outershare + enc_fn = encoder_outer_share + name_fn = lambda i: name + '_layer_' + str(i) + elif param_share == "inner_share": + #n_layer_per_block = 2 + enc_fn = encoder_inner_share + name_fn = lambda i: name + else: + raise ValueError('unsupported param share mode') + + for i in range(n_layer // n_layer_per_block): + enc_output, cp = enc_fn( + enc_input, + attn_bias, + n_head, + d_key, + d_value, + d_model, + d_inner_hid, + prepostprocess_dropout, + attention_dropout, + relu_dropout, + hidden_act, + preprocess_cmd, + postprocess_cmd, + param_initializer=param_initializer, + name=name_fn(i), + n_layer_per_block=n_layer_per_block, + epsilon=epsilon, + ) + checkpoints.extend(cp) + enc_input = enc_output + enc_output = pre_process_layer( + enc_output, + preprocess_cmd, + prepostprocess_dropout, + name="post_encoder", + epsilon=epsilon) + + return enc_output, checkpoints diff --git a/hub_module/modules/text/sentiment_analysis/ernie_skep_sentiment_analysis/module.py b/hub_module/modules/text/sentiment_analysis/ernie_skep_sentiment_analysis/module.py new file mode 100644 index 00000000..87187836 --- /dev/null +++ b/hub_module/modules/text/sentiment_analysis/ernie_skep_sentiment_analysis/module.py @@ -0,0 +1,258 @@ +# coding:utf-8 +# Copyright (c) 2020 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. +from __future__ import absolute_import +from __future__ import division +from __future__ import print_function + +import argparse +import ast +import os + +from paddle.fluid.core import PaddleTensor, AnalysisConfig, create_paddle_predictor +from paddlehub import TransformerModule +from paddlehub.module.module import moduleinfo, runnable, serving +from paddlehub.reader.tokenization import convert_to_unicode, FullTokenizer +from paddlehub.reader.batching import pad_batch_data +import numpy as np + +from ernie_skep_sentiment_analysis.model.ernie import ErnieModel, ErnieConfig + + +@moduleinfo( + name="ernie_skep_sentiment_analysis", + version="1.0.0", + summary= + "SKEP: Sentiment Knowledge Enhanced Pre-training for Sentiment Analysis. Ernie_skep_sentiment_analysis module is initialize with enie_1.0_chn_large when pretraining. This module is finetuned on ChnSentiCorp dataset to do sentiment claasification. It can do sentiment analysis prediction directly, label as positive or negative.", + author="baidu-nlp", + author_email="", + type="nlp/sentiment_analysis", +) +class ErnieSkepSentimentAnalysis(TransformerModule): + """ + Ernie_skep_sentiment_analysis module is initialize with enie_1.0_chn_large when pretraining. + This module is finetuned on ChnSentiCorp dataset to do sentiment claasification. + It can do sentiment analysis prediction directly, label as positive or negative. + """ + + def _initialize(self): + ernie_config_path = os.path.join(self.directory, "assets", + "ernie_1.0_large_ch.config.json") + self.ernie_config = ErnieConfig(ernie_config_path) + self.MAX_SEQ_LEN = 512 + self.vocab_path = os.path.join(self.directory, "assets", + "ernie_1.0_large_ch.vocab.txt") + self.params_path = os.path.join(self.directory, "assets", "params") + + self.infer_model_path = os.path.join(self.directory, "assets", + "inference_step_601") + self.tokenizer = FullTokenizer(vocab_file=self.vocab_path) + + self.vocab = self.tokenizer.vocab + self.pad_id = self.vocab["[PAD]"] + self.label_map = {0: 'negative', 1: 'positive'} + + self._set_config() + + def _set_config(self): + """ + predictor config setting + """ + model_file_path = os.path.join(self.infer_model_path, 'model') + params_file_path = os.path.join(self.infer_model_path, 'params') + + config = AnalysisConfig(model_file_path, params_file_path) + try: + _places = os.environ["CUDA_VISIBLE_DEVICES"] + int(_places[0]) + use_gpu = True + except: + use_gpu = False + + if use_gpu: + config.enable_use_gpu(8000, 0) + else: + config.disable_gpu() + + config.disable_glog_info() + + self.predictor = create_paddle_predictor(config) + + def net(self, input_ids, position_ids, segment_ids, input_mask): + """ + create neural network. + Args: + input_ids (tensor): the word ids. + position_ids (tensor): the position ids. + segment_ids (tensor): the segment ids. + input_mask (tensor): the padding mask. + + Returns: + pooled_output (tensor): sentence-level output for classification task. + sequence_output (tensor): token-level output for sequence task. + """ + ernie = ErnieModel( + src_ids=input_ids, + position_ids=position_ids, + sentence_ids=segment_ids, + input_mask=input_mask, + config=self.ernie_config, + use_fp16=False) + + pooled_output = ernie.get_pooled_output() + sequence_output = ernie.get_sequence_output() + return pooled_output, sequence_output + + def array2tensor(self, arr_data): + """ + convert numpy array to PaddleTensor + """ + tensor_data = PaddleTensor(arr_data) + return tensor_data + + @serving + def predict_sentiment(self, texts=[], use_gpu=False): + """ + Get the sentiment label for the predicted texts. It will be classified as positive and negative. + Args: + texts (list(str)): the data to be predicted. + use_gpu (bool): Whether to use gpu or not. + Returns: + res (list): The result of sentiment label and probabilties. + """ + + if use_gpu: + try: + _places = os.environ["CUDA_VISIBLE_DEVICES"] + int(_places[0]) + except: + raise RuntimeError( + "Environment Variable CUDA_VISIBLE_DEVICES is not set correctly. If you wanna use gpu, please set CUDA_VISIBLE_DEVICES as cuda_device_id." + ) + + results = [] + for text in texts: + feature = self._convert_text_to_feature(text) + inputs = [self.array2tensor(ndarray) for ndarray in feature] + output = self.predictor.run(inputs) + probilities = np.array(output[0].data.float_data()) + label = self.label_map[np.argmax(probilities)] + result = { + 'text': text, + 'sentiment_label': label, + 'positive_probs': probilities[1], + 'negative_probs': probilities[0] + } + results.append(result) + + return results + + def _convert_text_to_feature(self, text): + """ + Convert the raw text to feature which is needed to run program (feed_vars). + """ + text_a = convert_to_unicode(text) + tokens_a = self.tokenizer.tokenize(text_a) + max_seq_len = 512 + + # Account for [CLS] and [SEP] with "- 2" + if len(tokens_a) > max_seq_len - 2: + tokens_a = tokens_a[0:(max_seq_len - 2)] + + tokens = [] + text_type_ids = [] + tokens.append("[CLS]") + text_type_ids.append(0) + for token in tokens_a: + tokens.append(token) + text_type_ids.append(0) + tokens.append("[SEP]") + text_type_ids.append(0) + + token_ids = self.tokenizer.convert_tokens_to_ids(tokens) + position_ids = list(range(len(token_ids))) + task_ids = [0] * len(token_ids) + + padded_token_ids, input_mask = pad_batch_data([token_ids], + max_seq_len=max_seq_len, + pad_idx=self.pad_id, + return_input_mask=True) + padded_text_type_ids = pad_batch_data([text_type_ids], + max_seq_len=max_seq_len, + pad_idx=self.pad_id) + padded_position_ids = pad_batch_data([position_ids], + max_seq_len=max_seq_len, + pad_idx=self.pad_id) + padded_task_ids = pad_batch_data([task_ids], + max_seq_len=max_seq_len, + pad_idx=self.pad_id) + + feature = [ + padded_token_ids, padded_position_ids, padded_text_type_ids, + input_mask, padded_task_ids + ] + return feature + + @runnable + def run_cmd(self, argvs): + """ + Run as a command + """ + self.parser = argparse.ArgumentParser( + description="Run the %s module." % self.name, + prog='hub run %s' % self.name, + usage='%(prog)s', + add_help=True) + + self.arg_input_group = self.parser.add_argument_group( + title="Input options", description="Input data. Required") + self.arg_config_group = self.parser.add_argument_group( + title="Config options", + description= + "Run configuration for controlling module behavior, not required.") + + self.add_module_config_arg() + self.add_module_input_arg() + + args = self.parser.parse_args(argvs) + results = self.predict_sentiment( + texts=[args.input_text], use_gpu=args.use_gpu) + return results + + def add_module_config_arg(self): + """ + Add the command config options + """ + self.arg_config_group.add_argument( + '--use_gpu', + type=ast.literal_eval, + default=False, + help="whether use GPU or not") + + def add_module_input_arg(self): + """ + Add the command input options + """ + self.arg_input_group.add_argument( + '--input_text', type=str, default=None, help="data to be predicted") + + +if __name__ == '__main__': + test_module = ErnieSkepSentimentAnalysis() + test_texts = ['你不是不聪明，而是不认真', '虽然小明很努力，但是他还是没有考100分'] + results = test_module.predict_sentiment(test_texts, use_gpu=False) + print(results) + test_module.context(max_seq_len=128) + print(test_module.get_embedding(texts=[['你不是不聪明，而是不认真']])) + print(test_module.get_params_layer()) diff --git a/hub_module/scripts/configs/ernie_skep_sentiment_analysis.yml b/hub_module/scripts/configs/ernie_skep_sentiment_analysis.yml new file mode 100644 index 00000000..a50edc19 --- /dev/null +++ b/hub_module/scripts/configs/ernie_skep_sentiment_analysis.yml @@ -0,0 +1,9 @@ +name: ernie_skep_sentiment_analysis +dir: "modules/text/sentiment_analysis/ernie_skep_sentiment_analysis" +exclude: + - README.md +resources: + - + url: https://paddlehub.bj.bcebos.com/model/nlp/ernie_skep_sentiment_analysis/assets.tar.gz + dest: assets + uncompress: True diff --git a/hub_module/tests/unittests/test_ernie_skep_sentiment_analysis.py b/hub_module/tests/unittests/test_ernie_skep_sentiment_analysis.py new file mode 100644 index 00000000..bcceb238 --- /dev/null +++ b/hub_module/tests/unittests/test_ernie_skep_sentiment_analysis.py @@ -0,0 +1,129 @@ +# Copyright (c) 2020 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 os +from unittest import TestCase, main +os.environ['CUDA_VISIBLE_DEVICES'] = '1' + +import numpy as np +import paddlehub as hub + + +class ErnieSkepSentimentAnalysisTestCase(TestCase): + def setUp(self): + self.module = hub.Module(name='ernie_skep_sentiment_analysis') + self.test_text = [[ + '飞桨（PaddlePaddle）是国内开源产业级深度学习平台', 'PaddleHub是飞桨生态的预训练模型应用工具' + ], ["飞浆PaddleHub"]] + self.test_data = ['你不是不聪明，而是不认真', '虽然小明很努力，但是他还是没有考100分'] + self.results = [{ + 'text': '你不是不聪明，而是不认真', + 'sentiment_label': 'negative', + 'positive_probs': 0.10738213360309601, + 'negative_probs': 0.8926178216934204 + }, + { + 'text': '虽然小明很努力，但是他还是没有考100分', + 'sentiment_label': 'negative', + 'positive_probs': 0.053915347903966904, + 'negative_probs': 0.9460846185684204 + }] + + def test_predict_sentiment(self): + results_1 = self.module.predict_sentiment(self.test_data, use_gpu=False) + results_2 = self.module.predict_sentiment(self.test_data, use_gpu=True) + + for index, res in enumerate(results_1): + self.assertEqual(res['text'], self.results[index]['text']) + self.assertEqual(res['sentiment_label'], + self.results[index]['sentiment_label']) + self.assertTrue( + abs(res['positive_probs'] - + self.results[index]['positive_probs']) < 1e-6) + self.assertTrue( + abs(res['negative_probs'] - + self.results[index]['negative_probs']) < 1e-6) + + self.assertEqual(res['text'], results_2[index]['text']) + self.assertEqual(res['sentiment_label'], + results_2[index]['sentiment_label']) + self.assertTrue( + abs(res['positive_probs'] - + results_2[index]['positive_probs']) < 1e-6) + self.assertTrue( + abs(res['negative_probs'] - + results_2[index]['negative_probs']) < 1e-6) + + def test_get_embedding(self): + # test batch_size + max_seq_len = 128 + results = self.module.get_embedding( + texts=self.test_text, + use_gpu=False, + batch_size=1, + max_seq_len=max_seq_len) + results_2 = self.module.get_embedding( + texts=self.test_text, + use_gpu=False, + batch_size=10, + max_seq_len=max_seq_len) + # 2 sample results + self.assertEqual(len(results), 2) + self.assertEqual(len(results_2), 2) + # sequence embedding and token embedding results per sample + self.assertEqual(len(results[0]), 2) + self.assertEqual(len(results_2[0]), 2) + # sequence embedding shape + self.assertEqual(results[0][0].shape, (1024, )) + self.assertEqual(results_2[0][0].shape, (1024, )) + # token embedding shape + self.assertEqual(results[0][1].shape, (max_seq_len, 1024)) + self.assertEqual(results_2[0][1].shape, (max_seq_len, 1024)) + + # test gpu + results_3 = self.module.get_embedding( + texts=self.test_text, + use_gpu=True, + batch_size=1, + max_seq_len=max_seq_len) + diff = np.abs(results[0][0] - results_3[0][0]) + self.assertTrue((diff < 1e-6).all) + diff = np.abs(results[0][1] - results_3[0][1]) + self.assertTrue((diff < 1e-6).all) + diff = np.abs(results[1][0] - results_3[1][0]) + self.assertTrue((diff < 1e-6).all) + diff = np.abs(results[1][1] - results_3[1][1]) + self.assertTrue((diff < 1e-6).all) + + def test_get_params_layer(self): + self.module.context() + layers = self.module.get_params_layer() + layers = list(set(layers.values())) + true_layers = [i for i in range(24)] + self.assertEqual(layers, true_layers) + + def test_get_spm_path(self): + self.assertEqual(self.module.get_spm_path(), None) + + def test_get_word_dict_path(self): + self.assertEqual(self.module.get_word_dict_path(), None) + + def test_get_vocab_path(self): + vocab_path = self.module.get_vocab_path() + true_vocab_path = os.path.join(self.module.directory, "assets", + "ernie_1.0_large_ch.vocab.txt") + self.assertEqual(vocab_path, true_vocab_path) + + +if __name__ == '__main__': + main() diff --git a/paddlehub/module/nlp_module.py b/paddlehub/module/nlp_module.py index 55a3a533..211f7313 100644 --- a/paddlehub/module/nlp_module.py +++ b/paddlehub/module/nlp_module.py @@ -319,8 +319,6 @@ class TransformerModule(NLPBaseModule): pretraining_params_path, main_program=main_program, predicate=existed_params) - logger.info("Load pretraining parameters from {}.".format( - pretraining_params_path)) def param_prefix(self): return "@HUB_%s@" % self.name -- GitLab