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README.md

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@@ -260,7 +260,6 @@ You can do MindSpore Lite inference in MindOCR using **MindOCR models** or **Thi
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- [x] [MASTER](configs/rec/master/README.md) (PR'2019)
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- [x] [VISIONLAN](configs/rec/visionlan/README.md) (ICCV'2021)
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- [x] [RobustScanner](configs/rec/robustscanner/README.md) (ECCV'2020)
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- [x] [ABINet](configs/rec/abinet/README.md) (CVPR'2021)
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</details>
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@@ -382,7 +381,7 @@ Frequently asked questions about configuring environment and mindocr, please ref
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- [PP-OCRv3 DBNet](configs/det/dbnet/db_mobilenetv3_ppocrv3.yaml) for text detection and [PP-OCRv3 SVTR](configs/rec/svtr/svtr_ppocrv3_ch.yaml) for recognition, supporting online inferece and finetuning
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2. Add more benchmark datasets and their results
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- [XFUND](configs/kie/vi_layoutxlm/README_CN.md)
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3. Multiple specifications support for Ascend 910: DBNet ResNet-50, DBNet++ ResNet-50, CRNN VGG7, SVTR-Tiny, FCENet, ABINet
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3. Multiple specifications support for Ascend 910: DBNet ResNet-50, DBNet++ ResNet-50, CRNN VGG7, SVTR-Tiny, FCENet
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- 2023/11/28
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1. Add offline inference support for PP-OCRv4
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- [PP-OCRv4 DBNet](deploy/py_infer/src/configs/det/ppocr/ch_PP-OCRv4_det_cml.yaml) for text detection and [PP-OCRv4 CRNN](deploy/py_infer/src/configs/rec/ppocr/ch_PP-OCRv4_rec_distillation.yaml) for text recognition, supporting offline inferece

README_CN.md

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@@ -263,7 +263,6 @@ python tools/infer/text/predict_system.py --image_dir {path_to_img or dir_to_img
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- [x] [MASTER](configs/rec/master/README_CN.md) (PR'2019)
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- [x] [VISIONLAN](configs/rec/visionlan/README_CN.md) (ICCV'2021)
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- [x] [RobustScanner](configs/rec/robustscanner/README_CN.md) (ECCV'2020)
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- [x] [ABINet](configs/rec/abinet/README_CN.md) (CVPR'2021)
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</details>
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<details open markdown>
@@ -385,7 +384,7 @@ MindOCR提供了[数据格式转换工具](https://github.com/mindspore-lab/mind
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- 文本检测[PP-OCRv3 DBNet](configs/det/dbnet/db_mobilenetv3_ppocrv3.yaml)和文本识别[PP-OCRv3 SVTR](configs/rec/svtr/svtr_ppocrv3_ch.yaml),支持在线推理和微调训练
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2. 添加更多基准数据集及其结果
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- [XFUND](configs/kie/vi_layoutxlm/README_CN.md)
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3. 昇腾910硬件多规格支持:DBNet ResNet-50、DBNet++ ResNet-50、CRNN VGG7、SVTR-Tiny、FCENet、ABINet
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3. 昇腾910硬件多规格支持:DBNet ResNet-50、DBNet++ ResNet-50、CRNN VGG7、SVTR-Tiny、FCENet
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- 2023/11/28
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1. 增加支持PP-OCRv4模型离线推理
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- 文本检测 [PP-OCRv4 DBNet](deploy/py_infer/src/configs/det/ppocr/ch_PP-OCRv4_det_cml.yaml)和文本识别 [PP-OCRv4 CRNN](deploy/py_infer/src/configs/rec/ppocr/ch_PP-OCRv4_rec_distillation.yaml),支持离线推理

configs/rec/abinet/README.md

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configs/rec/abinet/README_CN.md

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configs/rec/abinet/abinet_resnet45_en.yaml

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docs/en/mkdocs/modelzoo_training.md

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| visionlan_resnet45| IC03,13,15,IIIT,etc | 192| 4 | 90.61 | 417 | 1840 | O2 | [mindocr_visionlan](https://github.com/mindspore-lab/mindocr/blob/main/configs/rec/visionlan) |
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| master_resnet31 | IC03,13,15,IIIT,etc | 512 | 4 | 90.37 | 747 | 2741 | O2 | [mindocr_master](https://github.com/mindspore-lab/mindocr/tree/main/configs/rec/master) |
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| robustscanner_resnet31 | IC13,15,IIIT,SVT,etc | 256 | 4 | 87.86 | 825 | 310 | O0 | [mindocr_robustscanner](https://github.com/mindspore-lab/mindocr/blob/main/configs/rec/robustscanner) |
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| abinet_resnet45 | IC03,13,15,IIIT,etc | 768 | 8 | 91.35 | 718 | 628.11 | O0 | [mindocr_abinet](https://github.com/mindspore-lab/mindocr/tree/main/configs/rec/abinet) |
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### Text Direction Classification
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docs/en/tutorials/frequently_asked_questions.md

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- [Problems related to inference](#q8-problems-related-to-inference)
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- [Training speed of DBNet not as fast as expexted](#q9-training-speed-of-dbnet-not-as-fast-as-expexted)
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- [Error about libgomp-d22c30c5.so.1.0.0](#q10-error-about-libgomp-d22c30c5so100)
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- [Dataset Pipeline Error when training abinet on lmdb dataset](#q11-dataset-pipeline-error-when-training-abinet-on-lmdb-dataset)
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- [Runtime Error when training dbnet on synthtext dataset](#q12-runtime-error-when-training-dbnet-on-synthtext-dataset)
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- [Failed to install seqeval](#q13-failed-to-install-seqeval)
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- [Failed to install lanms](#q14-failed-to-install-lanms)
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- [Runtime Error when training dbnet on synthtext dataset](#q11-runtime-error-when-training-dbnet-on-synthtext-dataset)
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- [Failed to install seqeval](#q12-failed-to-install-seqeval)
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- [Failed to install lanms](#q13-failed-to-install-lanms)
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### Q1 Undefined symbol
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export LD_PRELOAD=/root/mindocr_env/lib/python3.8/site-packages/scikit_learn.libs/libgomp-d22c30c5.so.1.0.0:$LD_PRELOAD
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```
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### Q11 Dataset Pipeline Error when training abinet on lmdb dataset
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The following error may occur when training abinet on lmdb dataset
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```bash
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mindocr.data.rec_lmdb_dataset WARNING - Error occurred during preprocess.
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Exception thrown from dataset pipeline. Refer to 'Dataset Pipeline Error Message'.
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------------------------------------------------------------------
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- Dataset Pipeline Error Message:
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------------------------------------------------------------------
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[ERROR] No cast for the specified DataType was found.
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------------------------------------------------------------------
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- C++ Call Stack: (For framework developers)
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------------------------------------------------------------------
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mindspore/ccsrc/minddata/dataset/kernels/py_func_op.cc(143).
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```
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You can try the following steps to fix it:
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- find the folder of mindspore package
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- open file: `mindspore/dataset/transforms/transform.py`
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- switch to line 93:
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```bash
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93 if key in EXECUTORS_LIST:
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94 # get the executor by process id and thread id
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95 executor = EXECUTORS_LIST[key]
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96 # remove the old transform which in executor and update the new transform
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97 executor.UpdateOperation(self.parse())
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98 else:
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99 # create a new executor by process id and thread_id
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100 executor = cde.Execute(self.parse())
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101 # add the executor the global EXECUTORS_LIST
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102 EXECUTORS_LIST[key] = executor
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```
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- replace line 97 with `executor = cde.Execute(self.parse())`, and get
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```bash
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93 if key in EXECUTORS_LIST:
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94 # get the executor by process id and thread id
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95 executor = EXECUTORS_LIST[key]
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96 # remove the old transform which in executor and update the new transform
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97 executor = cde.Execute(self.parse())
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98 else:
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99 # create a new executor by process id and thread_id
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100 executor = cde.Execute(self.parse())
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101 # add the executor the global EXECUTORS_LIST
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102 EXECUTORS_LIST[key] = executor
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```
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- save the file, and try to train the model.
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### Q12 Runtime Error when training dbnet on synthtext dataset
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### Q11 Runtime Error when training dbnet on synthtext dataset
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Runtime Error occur as following when training dbnet on synthtext dataset:
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```bash
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Traceback (most recent call last):
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Please update CANN to 7.1 version.
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### Q13 Failed to install seqeval
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### Q12 Failed to install seqeval
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The following error occur when run `pip install -r requirements.txt`
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```bash
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Collecting seqeval>=1.2.2 (from -r requirements.txt (line 19))
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- Install `seqeval`: `pip3 install seqeval -i https://pypi.tuna.tsinghua.edu.cn/simple`
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### Q14 Failed to install lanms
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### Q13 Failed to install lanms
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The following error occur when installing lanms
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```bash
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ImportError: Python version mismatch: module was compiled for version 3.8, while the interpreter is running version 3.7.

docs/zh/mkdocs/modelzoo_training.md

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| visionlan_resnet45| IC03,13,15,IIIT,etc | 192| 4 | 90.61 | 417 | 1840 | O2 | [mindocr_visionlan](https://github.com/mindspore-lab/mindocr/blob/main/configs/rec/visionlan) |
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| master_resnet31 | IC03,13,15,IIIT,etc | 512 | 4 | 90.37 | 747 | 2741 | O2 | [mindocr_master](https://github.com/mindspore-lab/mindocr/tree/main/configs/rec/master) |
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| robustscanner_resnet31 | IC13,15,IIIT,SVT,etc | 256 | 4 | 87.86 | 825 | 310 | O0 | [mindocr_robustscanner](https://github.com/mindspore-lab/mindocr/blob/main/configs/rec/robustscanner) |
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| abinet_resnet45 | IC03,13,15,IIIT,etc | 768 | 8 | 91.35 | 718 | 628.11 | O0 | [mindocr_abinet](https://github.com/mindspore-lab/mindocr/tree/main/configs/rec/abinet) |
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### 文本方向分类
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docs/zh/tutorials/frequently_asked_questions.md

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- [推理相关问题](#q8)
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- [DBNet训练速率不及预期](#q9)
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- [libgomp-d22c30c5.so.1.0.0 相关错误](#q10)
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- [当在lmdb dataset上训练abinet报数据管道错误](#q11)
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- [当在synthtext数据集上训练dbnet报运行时错误](#q12)
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- [安装seqeval相关错误](#q13)
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- [安装lanms相关错误](#q14)
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- [当在synthtext数据集上训练dbnet报运行时错误](#q11)
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- [安装seqeval相关错误](#q12)
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- [安装lanms相关错误](#q13)
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### <span id="q1">Q1 未定义符号</span>
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export LD_PRELOAD=/root/mindocr_env/lib/python3.8/site-packages/scikit_learn.libs/libgomp-d22c30c5.so.1.0.0:$LD_PRELOAD
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```
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### <span id="q11">Q11 当在lmdb dataset上训练abinet报数据管道错误</span>
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当在lmdb dataset上训练abinet报以下数据管道错误
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```bash
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mindocr.data.rec_lmdb_dataset WARNING - Error occurred during preprocess.
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Exception thrown from dataset pipeline. Refer to 'Dataset Pipeline Error Message'.
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------------------------------------------------------------------
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- Dataset Pipeline Error Message:
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------------------------------------------------------------------
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[ERROR] No cast for the specified DataType was found.
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------------------------------------------------------------------
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- C++ Call Stack: (For framework developers)
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------------------------------------------------------------------
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mindspore/ccsrc/minddata/dataset/kernels/py_func_op.cc(143).
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```
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可以尝试用如下步骤修复:
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- 找到mindspore的包路径
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- 打开文件: `mindspore/dataset/transforms/transform.py`
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- 跳转到93行,可以得到如下内容:
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```bash
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93 if key in EXECUTORS_LIST:
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94 # get the executor by process id and thread id
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95 executor = EXECUTORS_LIST[key]
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96 # remove the old transform which in executor and update the new transform
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97 executor.UpdateOperation(self.parse())
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98 else:
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99 # create a new executor by process id and thread_id
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100 executor = cde.Execute(self.parse())
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101 # add the executor the global EXECUTORS_LIST
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102 EXECUTORS_LIST[key] = executor
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```
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- 使用`executor = cde.Execute(self.parse())`替换97行, 得到如下内容:
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```bash
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93 if key in EXECUTORS_LIST:
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94 # get the executor by process id and thread id
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95 executor = EXECUTORS_LIST[key]
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96 # remove the old transform which in executor and update the new transform
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97 executor = cde.Execute(self.parse())
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98 else:
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99 # create a new executor by process id and thread_id
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100 executor = cde.Execute(self.parse())
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101 # add the executor the global EXECUTORS_LIST
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102 EXECUTORS_LIST[key] = executor
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```
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- 保存后再次尝试训练即可
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### <span id="q12">Q12 当在synthtext数据集上训练dbnet报运行时错误</span>
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### <span id="q11">Q11 当在synthtext数据集上训练dbnet报运行时错误</span>
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当在synthtext数据集上训练dbnet报以下数据管道错误
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```bash
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Traceback (most recent call last):
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请尝试将CANN更新到7.1。
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### <span id="q13">Q13 安装seqeval相关错误</span>
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### <span id="q12">Q12 安装seqeval相关错误</span>
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当运行`pip install -r requirements.txt`时,报以下错误
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```bash
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Collecting seqeval>=1.2.2 (from -r requirements.txt (line 19))
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- 安装`seqeval``pip3 install seqeval -i https://pypi.tuna.tsinghua.edu.cn/simple`
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### <span id="q14">Q14 安装lanms相关错误</span>
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### <span id="q13">Q13 安装lanms相关错误</span>
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当安装lanms时,报
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```bash
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ImportError: Python version mismatch: module was compiled for version 3.8, while the interpreter is running version 3.7.

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