TAO v5.5.0
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从 TAO 4.0.x 迁移到 TAO 5.0.0

要迁移到 TAO 5.0.0，您必须首先将 TAO 工作流程升级到 TAO 4.0.0。请按照这些说明从旧版本的 TAO（以前名为“Transfer Learning Toolkit”）升级到 4.0.x 版本。

在 5.0.0 版本中，TAO 引入了 task_group 的概念，它是一个可以与特定模态关联的任务集合。以下是支持的模态：

  • 模型

  • 数据集

  • 部署

在 4.0.x 版本之前作为任务包含的所有模型现在都归类在 model 任务组下。作为 tao-deploy CLI 一部分包含的所有任务现在都归类在 deploy 任务组下。

task_group dataset 已在 TAO 5.0.0 中引入。它包括任务和相关的子任务，这些任务和子任务有助于从原始图像生成标签 (autolabel)、检查和验证预先存在的已标注数据集 (analytics)、将预先存在的已标注数据集 (annotation) 从一种格式转换为另一种格式（例如，从 KITTI 转换为 COCO），以及通过运行离线增强 (augmentation) 来增强数据集。

有关 dataset 任务组的更多信息，请参阅数据服务章节。

下表总结了 CLI 中预期的更改。这不是所有操作的详尽列表，但这些更改可以推广到作为 TAO 4.0.x 一部分包含的所有网络。

网络

TAO 4.0.x

TAO 5.0.x
分类
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tao classification_tf1 export \
        -m $USER_EXPERIMENT_DIR/output_retrain/weights/resnet_$EPOCH.tlt \
        -o $USER_EXPERIMENT_DIR/export/final_model.etlt \
        -k $KEY \
        --classmap_json $USER_EXPERIMENT_DIR/output_retrain/classmap.json \
        --gen_ds_config

tao-deploy classification_tf1 gen_trt_engine \
        -m $USER_EXPERIMENT_DIR/export/final_model.etlt \
        -e $SPECS_DIR/classification_retrain_spec.cfg \
        -k $KEY \
        --batch_size 64 \
        --max_batch_size 64 \
        --batches 10 \
        --data_type int8 \
        --cal_data_file $USER_EXPERIMENT_DIR/export/calibration.tensor \
        --cal_cache_file $USER_EXPERIMENT_DIR/export/final_model_int8_cache.bin \
        --cal_image_dir $DATA_DOWNLOAD_DIR/split/test/ \
        --engine_file $USER_EXPERIMENT_DIR/export/final_model.trt
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tao model classification_tf1 export \
        -m $USER_EXPERIMENT_DIR/output_retrain/weights/resnet_$EPOCH.hdf5 \
        -o $USER_EXPERIMENT_DIR/export/final_model.onnx \
        -k $KEY \
        --classmap_json $USER_EXPERIMENT_DIR/output_retrain/classmap.json \
        --gen_ds_config

tao deploy classification_tf1 gen_trt_engine \
        -m $USER_EXPERIMENT_DIR/export/final_model.onnx \
        -e $SPECS_DIR/classification_retrain_spec.cfg \
        -k $KEY \
        --batch_size 64 \
        --max_batch_size 64 \
        --batches 10 \
        --data_type int8 \
        --cal_data_file $USER_EXPERIMENT_DIR/export/calibration.tensor \
        --cal_cache_file $USER_EXPERIMENT_DIR/export/final_model_int8_cache.bin \
        --cal_image_dir $DATA_DOWNLOAD_DIR/split/test/ \
        --engine_file $USER_EXPERIMENT_DIR/export/final_model.trt
DetectNet_v2
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tao detectnet_v2 export \
              -m $USER_EXPERIMENT_DIR/experiment_dir_retrain/weights/resnet18_detector_pruned.tlt \
              -e $SPECS_DIR/detectnet_v2_retrain_resnet18_kitti.txt \
              -o $USER_EXPERIMENT_DIR/experiment_dir_final/resnet18_detector.etlt \
              -k $KEY \
              --gen_ds_config

tao-deploy detectnet_v2 gen_trt_engine \
              -m $USER_EXPERIMENT_DIR/experiment_dir_final/resnet18_detector.etlt \
              -k $KEY  \
              --data_type int8 \
              --batches 10 \
              --batch_size 4 \
              --max_batch_size 64 \
              --engine_file $USER_EXPERIMENT_DIR/experiment_dir_final/resnet18_detector.trt.int8 \
              --cal_cache_file $USER_EXPERIMENT_DIR/experiment_dir_final/calibration.bin \
              -e $SPECS_DIR/detectnet_v2_retrain_resnet18_kitti.txt \
              --verbose
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tao model detectnet_v2 export \
              -m $USER_EXPERIMENT_DIR/experiment_dir_retrain/weights/resnet18_detector_pruned.hdf5 \
              -e $SPECS_DIR/detectnet_v2_retrain_resnet18_kitti.txt \
              -o $USER_EXPERIMENT_DIR/experiment_dir_final/resnet18_detector.onnx \
              -k $KEY \
              --gen_ds_config

tao deploy detectnet_v2 gen_trt_engine \
              -m $USER_EXPERIMENT_DIR/experiment_dir_final/resnet18_detector.onnx \
              -k $KEY  \
              --data_type int8 \
              --batches 10 \
              --batch_size 4 \
              --max_batch_size 64 \
              --engine_file $USER_EXPERIMENT_DIR/experiment_dir_final/resnet18_detector.trt.int8 \
              --cal_cache_file $USER_EXPERIMENT_DIR/experiment_dir_final/calibration.bin \
              -e $SPECS_DIR/detectnet_v2_retrain_resnet18_kitti.txt \
              --verbose
EfficientDet
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tao efficientdet_tf1 export -m $USER_EXPERIMENT_DIR/experiment_dir_retrain/model.step-$NUM_STEP.tlt \
                     -o $USER_EXPERIMENT_DIR/experiment_dir_retrain/model.step-$NUM_STEP.etlt \
                     -k $KEY \
                     -e $SPECS_DIR/efficientdet_d0_retrain.txt

tao-deploy efficientdet_tf1 gen_trt_engine -m $USER_EXPERIMENT_DIR/experiment_dir_retrain/model.step-$NUM_STEP.etlt \
                                        -k $KEY \
                                        --batch_size 8 \
                                        --data_type int8 \
                                        --cal_image_dir $DATA_DOWNLOAD_DIR/raw-data/val2017 \
                                        --batches 10 \
                                        --min_batch_size 1 \
                                        --opt_batch_size 8 \
                                        --max_batch_size 16 \
                                        --cal_cache_file $USER_EXPERIMENT_DIR/export/efficientdet_d0.cal \
                                        --engine_file $USER_EXPERIMENT_DIR/export/trt.int8.engine
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tao model efficientdet_tf1 export -m $USER_EXPERIMENT_DIR/experiment_dir_retrain/model.step-$NUM_STEP.hdf5 \
                     -o $USER_EXPERIMENT_DIR/experiment_dir_retrain/model.step-$NUM_STEP.onnx \
                     -k $KEY \
                     -e $SPECS_DIR/efficientdet_d0_retrain.txt

tao deploy efficientdet_tf1 gen_trt_engine -m $USER_EXPERIMENT_DIR/experiment_dir_retrain/model.step-$NUM_STEP.onnx \
                                        -k $KEY \
                                        --batch_size 8 \
                                        --data_type int8 \
                                        --cal_image_dir $DATA_DOWNLOAD_DIR/raw-data/val2017 \
                                        --batches 10 \
                                        --min_batch_size 1 \
                                        --opt_batch_size 8 \
                                        --max_batch_size 16 \
                                        --cal_cache_file $USER_EXPERIMENT_DIR/export/efficientdet_d0.cal \
                                        --engine_file $USER_EXPERIMENT_DIR/export/trt.int8.engine
SSD
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tao ssd export --gpu_index=$GPU_INDEX \
            -m $USER_EXPERIMENT_DIR/experiment_dir_retrain/weights/ssd_resnet18_epoch_$EPOCH.tlt \
            -k $KEY \
            -o $USER_EXPERIMENT_DIR/export/ssd_resnet18_epoch_$EPOCH.etlt \
            -e $SPECS_DIR/ssd_retrain_resnet18_kitti.txt \
            --batch_size 16 \
            --gen_ds_config

tao-deploy ssd gen_trt_engine --gpu_index=$GPU_INDEX \
                           -m $USER_EXPERIMENT_DIR/export/ssd_resnet18_epoch_$EPOCH.etlt \
                           -k $KEY \
                           -e $SPECS_DIR/ssd_retrain_resnet18_kitti.txt \
                           --engine_file $USER_EXPERIMENT_DIR/export/trt.engine \
                           --cal_image_dir $DATA_DOWNLOAD_DIR/testing/image_2 \
                           --data_type int8 \
                           --max_batch_size 16 \
                           --batch_size 16 \
                           --batches 10 \
                           --cal_cache_file $USER_EXPERIMENT_DIR/export/cal.bin \
                           --cal_data_file $USER_EXPERIMENT_DIR/export/cal.tensorfile
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tao model ssd export --gpu_index=$GPU_INDEX \
            -m $USER_EXPERIMENT_DIR/experiment_dir_retrain/weights/ssd_resnet18_epoch_$EPOCH.hdf5 \
            -k $KEY \
            -o $USER_EXPERIMENT_DIR/export/ssd_resnet18_epoch_$EPOCH.onnx \
            -e $SPECS_DIR/ssd_retrain_resnet18_kitti.txt \
            --batch_size 16 \
            --gen_ds_config

tao deploy ssd gen_trt_engine --gpu_index=$GPU_INDEX \
                           -m $USER_EXPERIMENT_DIR/export/ssd_resnet18_epoch_$EPOCH.onnx \
                           -k $KEY \
                           -e $SPECS_DIR/ssd_retrain_resnet18_kitti.txt \
                           --engine_file $USER_EXPERIMENT_DIR/export/trt.engine \
                           --cal_image_dir $DATA_DOWNLOAD_DIR/testing/image_2 \
                           --data_type int8 \
                           --max_batch_size 16 \
                           --batch_size 16 \
                           --batches 10 \
                           --cal_cache_file $USER_EXPERIMENT_DIR/export/cal.bin \
                           --cal_data_file $USER_EXPERIMENT_DIR/export/cal.tensorfile
UNet
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tao unet export --gpu_index=$GPU_INDEX -m $USER_EXPERIMENT_DIR/isbi_experiment_retrain/weights/model_isbi_retrained.tlt \
           -k $KEY \
           -e $SPECS_DIR/unet_train_resnet_unet_isbi_retrain.txt \
           --gen_ds_config

tao-deploy unet gen_trt_engine --gpu_index=$GPU_INDEX -m $USER_EXPERIMENT_DIR/isbi_experiment_retrain/weights/model_isbi_retrained.etlt \
                            -k $KEY \
                            -e $SPECS_DIR/unet_train_resnet_unet_isbi_retrain.txt \
                            --data_type int8 \
                            --engine_file $USER_EXPERIMENT_DIR/export/int8.isbi.retrained.engine \
                            --data_type int8 \
                            --cal_data_file $USER_EXPERIMENT_DIR/export/isbi_cal_data_file.txt \
                            --cal_cache_file $USER_EXPERIMENT_DIR/export/isbi_cal.bin \
                            --cal_image_dir $DATA_DOWNLOAD_DIR/isbi/images/val \
                            --max_batch_size 3 \
                            --batch_size 1
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tao model unet export --gpu_index=$GPU_INDEX -m $USER_EXPERIMENT_DIR/isbi_experiment_retrain/weights/model_isbi_retrained.tlt \
           -k $KEY \
           -e $SPECS_DIR/unet_train_resnet_unet_isbi_retrain.txt \
           --gen_ds_config

tao deploy unet gen_trt_engine --gpu_index=$GPU_INDEX -m $USER_EXPERIMENT_DIR/isbi_experiment_retrain/weights/model_isbi_retrained.onnx \
                            -k $KEY \
                            -e $SPECS_DIR/unet_train_resnet_unet_isbi_retrain.txt \
                            --data_type int8 \
                            --engine_file $USER_EXPERIMENT_DIR/export/int8.isbi.retrained.engine \
                            --data_type int8 \
                            --cal_data_file $USER_EXPERIMENT_DIR/export/isbi_cal_data_file.txt \
                            --cal_cache_file $USER_EXPERIMENT_DIR/export/isbi_cal.bin \
                            --cal_image_dir $DATA_DOWNLOAD_DIR/isbi/images/val \
                            --max_batch_size 3 \
                            --batch_size 1
YOLOv3
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tao yolo_v3 export -m $USER_EXPERIMENT_DIR/experiment_dir_retrain/weights/yolov3_resnet18_epoch_$EPOCH.tlt \
                -k $KEY \
                -o $USER_EXPERIMENT_DIR/export/yolov3_resnet18_epoch_$EPOCH.etlt \
                -e $SPECS_DIR/yolo_v3_retrain_resnet18_tfrecord.txt \
                --gen_ds_config

tao-deploy yolo_v3 gen_trt_engine -m $USER_EXPERIMENT_DIR/export/yolov3_resnet18_epoch_$EPOCH.etlt \
                               -k $KEY \
                               -e $SPECS_DIR/yolo_v3_retrain_resnet18_tfrecord.txt \
                               --cal_image_dir $DATA_DOWNLOAD_DIR/testing/image_2 \
                               --data_type int8 \
                               --batch_size 16 \
                               --min_batch_size 1 \
                               --opt_batch_size 8 \
                               --max_batch_size 16 \
                               --batches 10 \
                               --cal_cache_file $USER_EXPERIMENT_DIR/export/cal.bin  \
                               --cal_data_file $USER_EXPERIMENT_DIR/export/cal.tensorfile \
                               --engine_file $USER_EXPERIMENT_DIR/export/trt.engine.int8
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tao model yolo_v3 export -m $USER_EXPERIMENT_DIR/experiment_dir_retrain/weights/yolov3_resnet18_epoch_$EPOCH.hdf5 \
                -k $KEY \
                -o $USER_EXPERIMENT_DIR/export/yolov3_resnet18_epoch_$EPOCH.onnx \
                -e $SPECS_DIR/yolo_v3_retrain_resnet18_tfrecord.txt \
                --gen_ds_config

tao deploy yolo_v3 gen_trt_engine -m $USER_EXPERIMENT_DIR/export/yolov3_resnet18_epoch_$EPOCH.onnx \
                               -k $KEY \
                               -e $SPECS_DIR/yolo_v3_retrain_resnet18_tfrecord.txt \
                               --cal_image_dir $DATA_DOWNLOAD_DIR/testing/image_2 \
                               --data_type int8 \
                               --batch_size 16 \
                               --min_batch_size 1 \
                               --opt_batch_size 8 \
                               --max_batch_size 16 \
                               --batches 10 \
                               --cal_cache_file $USER_EXPERIMENT_DIR/export/cal.bin  \
                               --cal_data_file $USER_EXPERIMENT_DIR/export/cal.tensorfile \
                               --engine_file $USER_EXPERIMENT_DIR/export/trt.engine.int8
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