forked from mindspore-Ecosystem/mindspore
[MSLITE] Fix bug of tf model‘s output names.
This commit is contained in:
parent
db19c60581
commit
f0828412bb
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@ -167,8 +167,7 @@ int NPUInsertTransformPass::InsertNode(NPUOp *op, NPUOp *post_op, size_t post_in
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} else {
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// post_op nullptr mean output, we remain graph output tensor name unchanged
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auto graph_output_name = in_tensor.Name();
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in_tensor.SetTensorName(graph_output_name + "_before_" + name_);
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nc2nh_tensor->SetTensorName(graph_output_name);
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nc2nh_tensor->SetTensorName(graph_output_name + "_after_" + name_);
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}
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return RET_OK;
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}
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@ -16,5 +16,5 @@ deconvs_model
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# onnx
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ml_2012_ocr_cn.onnx
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# aware_training
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Modify_Out_video_infer2.tflite;;;;aware_training
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video_infer2.tflite;;;;aware_training
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mobilenet_v1_1.0_224_quant.tflite;;;;aware_training
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@ -1,6 +1,6 @@
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mobilenet_v1_1.0_224.tflite
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mobilenet_v2_1.0_224.tflite
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Modify_Out_mtk_age_gender_fp16.tflite
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mtk_age_gender_fp16.tflite
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mtk_isface.tflite
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mtk_landmark.tflite
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mtk_new_detect.tflite
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@ -25,7 +25,7 @@ Q_face_recognition.onnx
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Q888_iris_detect.onnx
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Q_iMaxDN_RGB_385_p_RGB_RGB_pb2tflite.tflite
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Q_iMaxSR_RGB_385_p_pb2tflite.tflite
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Modify_Out_Q_detect_fpn_add_inception-1448650.tflite
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Q_detect_fpn_add_inception-1448650.tflite
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Q888_face_dress_mv3y.tflite
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Q888_HADB_AADB_MBV2_model_fp32.tflite
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Q888_landmark.tflite
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@ -58,4 +58,4 @@ mtk_detect_mbv1_640_480_nopostprocess_simplified
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mtk_model_normalize_object_scene_ps_20200519_f16.tflite
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mtk_AADB_HADB_MBV2_model_f16.tflite
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mtk_model_emotions_0725_fp16.tflite
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Modify_Out_Q888_age_gender_orderd.tflite
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Q888_age_gender_orderd.tflite
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@ -6,10 +6,10 @@ resnet.tflite
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squeezenet.tflite
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mtk_AADB_HADB_MBV2_model_fp32.tflite
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hiai_cn_recognize_modify_padv2.tflite
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Modify_Out_hiai_cv_focusShootOCRModel_08.tflite
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hiai_cv_focusShootOCRModel_08.tflite
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hiai_model_normalize_object_scene_ps_20200519.tflite
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inception_v3.tflite
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Modify_Out_mtk_age_gender_fp16.tflite
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mtk_age_gender_fp16.tflite
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mtk_isface.tflite
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mtk_landmark.tflite
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mtk_new_detect.tflite
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@ -102,7 +102,7 @@ Q_crnn_ori_v2_405001_notrans_nopre.pb
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bolt_segment.pb
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ml_location_lane_counter.onnx 2
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gts_detect_5k_tf115.tflite
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Modify_Out_smartreply.tflite
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smartreply.tflite
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ml_text_correction.tflite
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ml_ocr_jk_pb2tflite.tflite
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scan_hms_angle_pb2tflite.tflite
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@ -111,21 +111,21 @@ ml_face_openclose_tflite.tflite
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unet_mbv2_05_104pts.tflite
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hiai_AADB_HADB_MBV2_model_f16.tflite
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hiai_AADB_HADB_MBV2_model_fp32.tflite
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Modify_Out_hiai_detect_curve_model_float32.tflite
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Modify_Out_hiai_detectmodel_06_23_960_480_1180700.tflite
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Modify_Out_lite-model_aiy_vision_classifier_food_V1_1.tflite
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hiai_detect_curve_model_float32.tflite
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hiai_detectmodel_06_23_960_480_1180700.tflite
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lite-model_aiy_vision_classifier_food_V1_1.tflite
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lite-model_disease-classification_1.tflite
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lite-model_models_mushroom-identification_v1_1.tflite
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Modify_Out_smartreply_1_default_1.tflite
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smartreply_1_default_1.tflite
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text_classification.tflite
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Modify_Out_Q_detect_fpn_add_inception-1448650.tflite
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Modify_Out_Q_hand_0812_pb2tflite.tflite
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Q_detect_fpn_add_inception-1448650.tflite
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Q_hand_0812_pb2tflite.tflite
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bloom_landmark.tflite
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Q888_face_dress_mv3y.tflite
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Q888_HADB_AADB_MBV2_model_fp32.tflite
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Q888_landmark.tflite
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Q888_pose.tflite
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Modify_Out_Q888_lapa158_unet_0924.tflite
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Q888_lapa158_unet_0924.tflite
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Q888_isface.tflite
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Q888_new_detect.tflite
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Q888_model_normalize_object_scene_ps_20200826_f32_no_softmax.tflite
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@ -156,7 +156,7 @@ hiai_model_0909_kd_rot_ps_softmax.tflite
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hiai_chinese_english_recognize_model_float32.tflite
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hiai_bigmodel_ghost_2_1_no_normalized_no_trans_tflite.tflite
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hiai_bigmodel_ghost_5_1_no_normalized_no_trans_tflite.tflite
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Modify_Out_hiai_detectmodel_desnet_256_128_64_32.tflite
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hiai_detectmodel_desnet_256_128_64_32.tflite
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mtk_AADB_HADB_MBV3_model_fp32.tflite
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Q888_face_recognition.onnx
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mobilenet_v1_0.25_128.tflite
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@ -201,7 +201,7 @@ mtk_AADB_HADB_MBV2_model_f16.tflite
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mtk_AADB_HADB_MBV3_model_f16.tflite
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mtk_model_emotions_0725_fp16.tflite
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mtk_face_features_v1_fp16.tflite
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Modify_Out_Q888_age_gender_orderd.tflite
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Q888_age_gender_orderd.tflite
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emotion
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gender_res_large_deploy
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glasses
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@ -38,7 +38,7 @@ multi_person_mobilenet_v1_075_float.tflite
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ide_label_base.tflite
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ide_label_retrained.tflite
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ml_ei_headpose.tflite
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Modify_Out_ml_ei_landmark.tflite
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ml_ei_landmark.tflite
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mnist.tflite
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mobilenet.tflite
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resnet.tflite
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@ -58,7 +58,7 @@ hiai_cv_focusShootOCRModel_02.tflite
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hiai_cv_poseEstimation.tflite
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inception_v4.tflite
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mtk_model_normalize_object_scene_ps_20200519_f16.tflite
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Modify_Out_mtk_age_gender_fp16.tflite
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mtk_age_gender_fp16.tflite
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mtk_model_face_dress_fp16.tflite
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mtk_AADB_HADB_MBV2_model_f16.tflite
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mtk_AADB_HADB_MBV3_model_f16.tflite
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@ -77,7 +77,7 @@ hiai_cpu_face_emotion.tflite
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hiai_cpu_face_gazing.tflite
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hiai_cpu_face_headpose.tflite
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hiai_humanDetection.tflite
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Modify_Out_hiai_cv_focusShootOCRModel_08.tflite
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hiai_cv_focusShootOCRModel_08.tflite
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ml_face_openclose.tflite
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hiai_face_model_npu.tflite
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hiai_ctpn_feature_map.tflite
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@ -122,13 +122,13 @@ mtk_model_normalize_object_scene_ps_20200826_f32_no_softmax.tflite
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mtk_276landmark_0913.tflite
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mtk_face_recognition.tflite
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mtk_convert_model.tflite
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Modify_Out_smartreply.tflite
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smartreply.tflite
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mindspore_text_classification_tflite.tflite
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# ml_location.tflite
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ml_text_correction.tflite
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ml_pic_shopping.tflite
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ml_vision_guide_detection3_pb2tflite.tflite
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Modify_Out_ml_vision_guide_detection1_pb2tflite.tflite
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ml_vision_guide_detection1_pb2tflite.tflite
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ml_pic_shopping_pb2tflite.tflite
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ml_ocr_jk_pb2tflite.tflite
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ml_ocr_latin_pb2tflite.tflite
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@ -152,27 +152,27 @@ Q_language_model_hrmini_Q4_b4_17w.tflite
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Q_new_detect.tflite
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Q_object_scene.tflite
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Q_pose.tflite
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Modify_Out_ml_ei_landmark_pb2tflite.tflite
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ml_ei_landmark_pb2tflite.tflite
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unet_mbv2_05_104pts.tflite
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hiai_AADB_HADB_MBV2_model_f16.tflite
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hiai_AADB_HADB_MBV2_model_fp32.tflite
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Modify_Out_hiai_detect_curve_model_float32.tflite
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Modify_Out_hiai_detectmodel_06_23_960_480_1180700.tflite
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Modify_Out_hiai_detectmodel_desnet_256_128_64_32.tflite
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Modify_Out_lite-model_aiy_vision_classifier_food_V1_1.tflite
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hiai_detect_curve_model_float32.tflite
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hiai_detectmodel_06_23_960_480_1180700.tflite
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hiai_detectmodel_desnet_256_128_64_32.tflite
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lite-model_aiy_vision_classifier_food_V1_1.tflite
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lite-model_disease-classification_1.tflite
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lite-model_models_mushroom-identification_v1_1.tflite
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Modify_Out_smartreply_1_default_1.tflite
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smartreply_1_default_1.tflite
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text_classification.tflite
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Modify_Out_Q_detect_fpn_add_inception-1448650.tflite
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Modify_Out_Q_hand_0812_pb2tflite.tflite
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Q_detect_fpn_add_inception-1448650.tflite
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Q_hand_0812_pb2tflite.tflite
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bloom_landmark.tflite
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Modify_Out_Q888_age_gender_orderd.tflite
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Q888_age_gender_orderd.tflite
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Q888_face_dress_mv3y.tflite
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Q888_HADB_AADB_MBV2_model_fp32.tflite
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Q888_landmark.tflite
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Q888_pose.tflite
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Modify_Out_Q888_lapa158_unet_0924.tflite
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Q888_lapa158_unet_0924.tflite
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Q888_isface.tflite
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Q888_new_detect.tflite
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Q888_model_normalize_object_scene_ps_20200826_f32_no_softmax.tflite
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@ -180,7 +180,7 @@ Q888_face_emo_dress_mv3_orderd.tflite
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Q_iMaxDN_RGB_385_p_RGB_RGB_pb2tflite.tflite
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Q_iMaxSR_RGB_385_p_pb2tflite.tflite
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bloom_new_detect.tflite
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Modify_Out_bloom_model_age_gender.tflite
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bloom_model_age_gender.tflite
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bloom_isface.tflite
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hiai_object_detect_814.tflite
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hiai_object_tflite_graph_8bit.tflite
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@ -193,10 +193,10 @@ ml_video_edit_img_segment_adaptise_pb2tflite.tflite;2:2,1
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ml_video_edit_video_segment_gauss_adaptis_part2_pb2tflite.tflite;2:2,1
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hdc_tb_cn_neg.tflite;3:3,1,2 0.5
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hiai_cv_labelDetectorModel_v3.tflite;2:2,1
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Modify_Out_ml_tacotron_decoder_step_stf.tflite;9;1,80:1,256:1,1024:1,1024:1,1024:1,1024:1,8:1,1,256:1
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ml_tacotron_decoder_step_stf.tflite;9;1,80:1,256:1,1024:1,1024:1,1024:1,1024:1,8:1,1,256:1
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ml_headpose_pb2tflite.tflite;3:2,3,1;1,64,64,3:16:16
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ml_ei_headpose_pb2tflite.tflite;3:2,3,1;1,64,64,3:16:16
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lite-model_albert_lite_base_squadv1_metadata_1.tflite;3:2,3,1
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lite-model_mobilebert_1_metadata_1.tflite;3
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Modify_Out_hiai_vad.tflite;2
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hiai_vad.tflite;2
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add_uint8.tflite;2
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@ -1,4 +1,4 @@
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Modify_Out_video_infer2.tflite
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video_infer2.tflite
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mobilenet_v1_0.25_128_quant.tflite
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mobilenet_v1_0.25_160_quant.tflite
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mobilenet_v1_0.25_192_quant.tflite
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@ -49,7 +49,7 @@ ide_label_base.tflite 22
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# dividing 0 in the following operator.
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#ide_label_retrained.tflite
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ml_ei_headpose.tflite 3
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Modify_Out_ml_ei_landmark.tflite 3
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ml_ei_landmark.tflite 3
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mnist.tflite 4
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mobilenet.tflite 0.1
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resnet.tflite 120
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@ -131,7 +131,7 @@ mtk_model_normalize_object_scene_ps_20200826_f32_no_softmax.tflite 22
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mtk_276landmark_0913.tflite 16
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mtk_face_recognition.tflite 8
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mtk_convert_model.tflite 5
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Modify_Out_smartreply.tflite 0.1
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smartreply.tflite 0.1
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mindspore_text_classification_tflite.tflite 9.2 # small output causes big bias
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#ml_location.tflite 0.1
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ml_text_correction.tflite 1
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@ -141,7 +141,7 @@ ml_text_correction.tflite 1
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# fp16: 27.6 - 27.4 = 0.2
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#ml_pic_shopping.tflite 0.1
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ml_vision_guide_detection3_pb2tflite.tflite 0.5
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Modify_Out_ml_vision_guide_detection1_pb2tflite.tflite 0.5
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ml_vision_guide_detection1_pb2tflite.tflite 0.5
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ml_pic_shopping_pb2tflite.tflite 95
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ml_ocr_jk_pb2tflite.tflite 0.5
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ml_ocr_latin_pb2tflite.tflite 11.5
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@ -158,17 +158,17 @@ lite-model_on_device_vision_classifier_landmarks_classifier_asia_V1_1.tflite 25
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lite-model_on_device_vision_classifier_landmarks_classifier_oceania_antarctica_V1_1.tflite 11
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lite-model_on_device_vision_classifier_landmarks_classifier_europe_V1_1.tflite 32
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lite-model_on_device_vision_classifier_landmarks_classifier_south_america_V1_1.tflite 14
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Modify_Out_ml_ei_landmark_pb2tflite.tflite 2
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ml_ei_landmark_pb2tflite.tflite 2
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unet_mbv2_05_104pts.tflite 17
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hiai_AADB_HADB_MBV2_model_f16.tflite 3.5
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hiai_AADB_HADB_MBV2_model_fp32.tflite 4.5
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Modify_Out_mtk_age_gender_fp16.tflite 26
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Modify_Out_hiai_detect_curve_model_float32.tflite 9
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mtk_age_gender_fp16.tflite 26
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hiai_detect_curve_model_float32.tflite 9
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Q_language_model_hrmini_Q4_b4_17w.tflite 3.5
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Modify_Out_lite-model_aiy_vision_classifier_food_V1_1.tflite 47.5
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lite-model_aiy_vision_classifier_food_V1_1.tflite 47.5
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lite-model_disease-classification_1.tflite 70
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lite-model_models_mushroom-identification_v1_1.tflite 5
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Modify_Out_smartreply_1_default_1.tflite 0.5
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smartreply_1_default_1.tflite 0.5
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text_classification.tflite 0.5
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Q_AADB_HADB_MBV2_model.tflite 5
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# the input of Q_convert model is between 0-255
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@ -190,16 +190,16 @@ Q_new_detect.tflite 3.5
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# the input of Q_object_scene model is between 0-255
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Q_object_scene.tflite 3
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Q_pose.tflite 4.1
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Modify_Out_Q_detect_fpn_add_inception-1448650.tflite 1
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Q_detect_fpn_add_inception-1448650.tflite 1
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bloom_landmark.tflite 0.5
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# input data: 0~255
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Modify_Out_Q888_age_gender_orderd.tflite 1.5
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Q888_age_gender_orderd.tflite 1.5
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Q888_face_dress_mv3y.tflite 0.5
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Q888_HADB_AADB_MBV2_model_fp32.tflite 2.5
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Q888_landmark.tflite 0.5
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Q888_pose.tflite 6.1
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# the output contains value less than e-7
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Modify_Out_Q888_lapa158_unet_0924.tflite 19
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Q888_lapa158_unet_0924.tflite 19
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Q888_isface.tflite 1.0
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Q888_new_detect.tflite 1.5
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Q888_model_normalize_object_scene_ps_20200826_f32_no_softmax.tflite 2
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@ -208,7 +208,7 @@ Q888_face_emo_dress_mv3_orderd.tflite 2.5
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Q_iMaxDN_RGB_385_p_RGB_RGB_pb2tflite.tflite 1
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Q_iMaxSR_RGB_385_p_pb2tflite.tflite 5
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bloom_new_detect.tflite 3.5
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Modify_Out_bloom_model_age_gender.tflite 0.5
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bloom_model_age_gender.tflite 0.5
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bloom_isface.tflite 0.5
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# The output values of conv layers range from -e±5 to e±5, which almost reaches the representation limit of fp16. In
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# this range, the fp16 data will has big bias. And the accumulation of this bias lowers the final precision.
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@ -1,6 +1,6 @@
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Stack-8 5 1 1 8 4 2
|
||||
output 5 1 1 8 4 2
|
||||
0.115831 0.11307496 0.24593274 0.34630755 -0.156871 0.21111916 -0.1046219 0.01590158 0.2745127 0.17317073 0.1787783 0.36557162 -0.13658395 0.2911819 -0.17356569 0.06825469 0.30655888 0.29681587 0.0078597255 0.3846875 -0.09266291 0.26170188 -0.15063931 0.04322962 0.25661856 0.25256 0.023097975 0.32573196 -0.043139715 0.25530565 -0.17270242 0.06442319 0.16240332 0.14648464 0.09654196 0.31037596 -0.0539147 0.23819281 -0.15090092 0.048991375 0.11573871 0.078725 0.19393174 0.26017824 -0.053352155 0.23836473 -0.15971972 0.054956935 0.19800682 0.17823274 0.17631978 0.3600948 -0.057391744 0.30457845 -0.19889072 0.05244953 0.090213075 0.17350613 0.044377614 0.29630166 -0.06999667 0.28462386 -0.17194743 0.093742274
|
||||
Stack-10 5 1 1 8 4 1
|
||||
output2 5 1 1 8 4 1
|
||||
0.06387864 0.22883008 0.23308714 0.045865785 0.06820235 0.26621705 0.29714558 0.112830795 0.1669129 0.33512616 0.25788227 0.08388044 0.14331667 0.27875048 0.23716372 0.10920572 0.07898582 0.24287388 0.22543576 0.08901558 0.03376824 0.16912283 0.225415 0.09693983 0.09598104 0.26216167 0.28474298 0.10668853 0.12471523 0.24643728 0.27107987 0.13469991
|
||||
Stack-13 3 1 8 4
|
||||
output3 3 1 8 4
|
||||
-0.16171767 -0.3828573 0.08357508 0.10217983 -0.34800848 -0.3206381 0.03284559 0.15394436 -0.42709222 -0.15115751 -0.0015709695 0.13956246 -0.35903975 -0.14498001 -0.050358675 0.15447712 -0.22225751 -0.21515054 -0.03286325 0.13769037 -0.1488501 -0.29710612 -0.033508375 0.14458355 -0.27084687 -0.31606156 -0.053954814 0.18598628 -0.15771987 -0.15602258 -0.0335121 0.14279547
|
||||
|
|
|
|||
|
|
@ -20,6 +20,7 @@
|
|||
#undef __STDC_FORMAT_MACROS
|
||||
#include <utility>
|
||||
#include <functional>
|
||||
#include <algorithm>
|
||||
#include "include/context.h"
|
||||
#include "include/ms_tensor.h"
|
||||
#include "include/version.h"
|
||||
|
|
@ -115,7 +116,7 @@ int Benchmark::ReadTensorData(std::ifstream &in_file_stream, const std::string &
|
|||
if (this->benchmark_data_.find(tensor_name) != this->benchmark_data_.end()) {
|
||||
return RET_OK;
|
||||
}
|
||||
tensor::MSTensor *tensor = GetTensorByNameOrShape(tensor_name, dims);
|
||||
tensor::MSTensor *tensor = session_->GetOutputByTensorName(tensor_name);
|
||||
if (tensor == nullptr) {
|
||||
MS_LOG(ERROR) << "Get tensor failed, tensor name: " << tensor_name;
|
||||
return RET_ERROR;
|
||||
|
|
@ -175,17 +176,17 @@ int Benchmark::CompareOutput() {
|
|||
float total_bias = 0;
|
||||
int total_size = 0;
|
||||
for (const auto &calib_tensor : benchmark_data_) {
|
||||
std::string node_or_tensor_name = calib_tensor.first;
|
||||
tensor::MSTensor *tensor = GetTensorByNameOrShape(node_or_tensor_name, calib_tensor.second->shape);
|
||||
std::string tensor_name = calib_tensor.first;
|
||||
tensor::MSTensor *tensor = session_->GetOutputByTensorName(tensor_name);
|
||||
if (tensor == nullptr) {
|
||||
MS_LOG(ERROR) << "Get tensor failed, tensor name: " << node_or_tensor_name;
|
||||
MS_LOG(ERROR) << "Get tensor failed, tensor name: " << tensor_name;
|
||||
return RET_ERROR;
|
||||
}
|
||||
int ret;
|
||||
if (tensor->data_type() == kObjectTypeString) {
|
||||
ret = CompareStringData(node_or_tensor_name, tensor);
|
||||
ret = CompareStringData(tensor_name, tensor);
|
||||
} else {
|
||||
ret = CompareDataGetTotalBiasAndSize(node_or_tensor_name, tensor, &total_bias, &total_size);
|
||||
ret = CompareDataGetTotalBiasAndSize(tensor_name, tensor, &total_bias, &total_size);
|
||||
}
|
||||
if (ret != RET_OK) {
|
||||
MS_LOG(ERROR) << "Error in CompareData";
|
||||
|
|
@ -212,41 +213,6 @@ int Benchmark::CompareOutput() {
|
|||
return RET_OK;
|
||||
}
|
||||
|
||||
tensor::MSTensor *Benchmark::GetTensorByNodeShape(const std::vector<size_t> &node_shape) {
|
||||
std::vector<tensor::MSTensor *> match_tensors;
|
||||
std::vector<int> shape_vector;
|
||||
(void)std::transform(node_shape.begin(), node_shape.end(), std::back_inserter(shape_vector),
|
||||
[](const size_t &value) { return static_cast<int>(value); });
|
||||
auto tensors = session_->GetOutputs();
|
||||
for (auto &out_tensor_pair : tensors) {
|
||||
if (out_tensor_pair.second->shape() == shape_vector) {
|
||||
match_tensors.emplace_back(out_tensor_pair.second);
|
||||
}
|
||||
}
|
||||
if (match_tensors.empty() || match_tensors.size() != 1) {
|
||||
MS_LOG(ERROR) << "get tensor by node shape failed";
|
||||
return nullptr;
|
||||
}
|
||||
return match_tensors.front();
|
||||
}
|
||||
|
||||
tensor::MSTensor *Benchmark::GetTensorByNameOrShape(const std::string &node_or_tensor_name,
|
||||
const std::vector<size_t> &dims) {
|
||||
tensor::MSTensor *tensor = nullptr;
|
||||
auto tensors = session_->GetOutputsByNodeName(node_or_tensor_name);
|
||||
if (tensors.empty() || tensors.size() != 1) {
|
||||
MS_LOG(INFO) << "Cannot find output node: " << node_or_tensor_name
|
||||
<< " or node has more than one output tensor, switch to GetOutputByTensorName";
|
||||
tensor = session_->GetOutputByTensorName(node_or_tensor_name);
|
||||
if (tensor == nullptr) {
|
||||
return GetTensorByNodeShape(dims);
|
||||
}
|
||||
} else {
|
||||
tensor = tensors.front();
|
||||
}
|
||||
return tensor;
|
||||
}
|
||||
|
||||
int Benchmark::CompareDataGetTotalBiasAndSize(const std::string &name, tensor::MSTensor *tensor, float *total_bias,
|
||||
int *total_size) {
|
||||
float bias = 0;
|
||||
|
|
|
|||
|
|
@ -60,10 +60,6 @@ class MS_API Benchmark : public BenchmarkBase {
|
|||
|
||||
int CompareOutput() override;
|
||||
|
||||
tensor::MSTensor *GetTensorByNameOrShape(const std::string &node_or_tensor_name, const std::vector<size_t> &dims);
|
||||
|
||||
tensor::MSTensor *GetTensorByNodeShape(const std::vector<size_t> &node_shape);
|
||||
|
||||
int CompareDataGetTotalBiasAndSize(const std::string &name, tensor::MSTensor *tensor, float *total_bias,
|
||||
int *total_size);
|
||||
|
||||
|
|
|
|||
|
|
@ -120,7 +120,7 @@ int BenchmarkUnifiedApi::ReadTensorData(std::ifstream &in_file_stream, const std
|
|||
if (this->benchmark_data_.find(tensor_name) != this->benchmark_data_.end()) {
|
||||
return RET_OK;
|
||||
}
|
||||
mindspore::MSTensor tensor = GetMSTensorByNameOrShape(tensor_name, dims);
|
||||
mindspore::MSTensor tensor = ms_model_.GetOutputByTensorName(tensor_name);
|
||||
if (tensor == nullptr) {
|
||||
MS_LOG(ERROR) << "Get tensor failed, tensor name: " << tensor_name;
|
||||
return RET_ERROR;
|
||||
|
|
@ -178,10 +178,10 @@ int BenchmarkUnifiedApi::CompareOutput() {
|
|||
float total_bias = 0;
|
||||
int total_size = 0;
|
||||
for (const auto &calib_tensor : benchmark_data_) {
|
||||
std::string node_or_tensor_name = calib_tensor.first;
|
||||
mindspore::MSTensor tensor = GetMSTensorByNameOrShape(node_or_tensor_name, calib_tensor.second->shape);
|
||||
std::string tensor_name = calib_tensor.first;
|
||||
mindspore::MSTensor tensor = ms_model_.GetOutputByTensorName(tensor_name);
|
||||
if (tensor == nullptr) {
|
||||
MS_LOG(ERROR) << "Get tensor failed, tensor name: " << node_or_tensor_name;
|
||||
MS_LOG(ERROR) << "Get tensor failed, tensor name: " << tensor_name;
|
||||
return RET_ERROR;
|
||||
}
|
||||
int ret;
|
||||
|
|
@ -190,7 +190,7 @@ int BenchmarkUnifiedApi::CompareOutput() {
|
|||
MS_LOG(ERROR) << "Unsupported kObjectTypeString:";
|
||||
return RET_ERROR;
|
||||
} else {
|
||||
ret = CompareDataGetTotalBiasAndSize(node_or_tensor_name, &tensor, &total_bias, &total_size);
|
||||
ret = CompareDataGetTotalBiasAndSize(tensor_name, &tensor, &total_bias, &total_size);
|
||||
}
|
||||
if (ret != RET_OK) {
|
||||
MS_LOG(ERROR) << "Error in CompareData";
|
||||
|
|
@ -217,36 +217,6 @@ int BenchmarkUnifiedApi::CompareOutput() {
|
|||
return RET_OK;
|
||||
}
|
||||
|
||||
mindspore::MSTensor BenchmarkUnifiedApi::GetMSTensorByNodeShape(const std::vector<size_t> &node_shape) {
|
||||
std::vector<mindspore::MSTensor> match_tensors;
|
||||
std::vector<int64_t> shape_vector = ConverterToInt64Vector<size_t>(node_shape);
|
||||
auto tensors = ms_model_.GetOutputs();
|
||||
for (auto &out_tensor_pair : tensors) {
|
||||
if (out_tensor_pair.Shape() == shape_vector) {
|
||||
match_tensors.emplace_back(out_tensor_pair);
|
||||
}
|
||||
}
|
||||
|
||||
return match_tensors.front();
|
||||
}
|
||||
|
||||
mindspore::MSTensor BenchmarkUnifiedApi::GetMSTensorByNameOrShape(const std::string &node_or_tensor_name,
|
||||
const std::vector<size_t> &dims) {
|
||||
mindspore::MSTensor tensor;
|
||||
auto tensors = ms_model_.GetOutputsByNodeName(node_or_tensor_name);
|
||||
if (tensors.empty() || tensors.size() != 1) {
|
||||
MS_LOG(INFO) << "Cannot find output node: " << node_or_tensor_name
|
||||
<< " or node has more than one output tensor, switch to GetOutputByTensorName";
|
||||
tensor = ms_model_.GetOutputByTensorName(node_or_tensor_name);
|
||||
if (tensor == nullptr) {
|
||||
return GetMSTensorByNodeShape(dims);
|
||||
}
|
||||
} else {
|
||||
tensor = tensors.front();
|
||||
}
|
||||
return tensor;
|
||||
}
|
||||
|
||||
int BenchmarkUnifiedApi::CompareDataGetTotalBiasAndSize(const std::string &name, mindspore::MSTensor *tensor,
|
||||
float *total_bias, int *total_size) {
|
||||
float bias = 0;
|
||||
|
|
|
|||
|
|
@ -52,8 +52,6 @@ class MS_API BenchmarkUnifiedApi : public BenchmarkBase {
|
|||
int CompareDataGetTotalBiasAndSize(const std::string &name, mindspore::MSTensor *tensor, float *total_bias,
|
||||
int *total_size);
|
||||
void InitContext(const std::shared_ptr<mindspore::Context> &context);
|
||||
mindspore::MSTensor GetMSTensorByNodeShape(const std::vector<size_t> &node_shape);
|
||||
mindspore::MSTensor GetMSTensorByNameOrShape(const std::string &node_or_tensor_name, const std::vector<size_t> &dims);
|
||||
|
||||
// call GenerateRandomData to fill inputTensors
|
||||
int GenerateInputData() override;
|
||||
|
|
|
|||
Loading…
Reference in New Issue