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update doc about CINN

gaotingquan 7 months ago
parent
commit
c6094e3b3e
68 changed files with 146 additions and 92 deletions
  1. 2 1
      docs/module_usage/tutorials/cv_modules/3d_bev_detection.en.md
  2. 2 1
      docs/module_usage/tutorials/cv_modules/3d_bev_detection.md
  3. 2 2
      docs/module_usage/tutorials/cv_modules/anomaly_detection.en.md
  4. 2 1
      docs/module_usage/tutorials/cv_modules/anomaly_detection.md
  5. 2 2
      docs/module_usage/tutorials/cv_modules/face_detection.en.md
  6. 2 1
      docs/module_usage/tutorials/cv_modules/face_detection.md
  7. 2 1
      docs/module_usage/tutorials/cv_modules/face_feature.en.md
  8. 2 1
      docs/module_usage/tutorials/cv_modules/face_feature.md
  9. 2 1
      docs/module_usage/tutorials/cv_modules/human_detection.en.md
  10. 2 1
      docs/module_usage/tutorials/cv_modules/human_detection.md
  11. 2 1
      docs/module_usage/tutorials/cv_modules/human_keypoint_detection.en.md
  12. 2 1
      docs/module_usage/tutorials/cv_modules/human_keypoint_detection.md
  13. 3 1
      docs/module_usage/tutorials/cv_modules/image_classification.en.md
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      docs/module_usage/tutorials/cv_modules/image_classification.md
  15. 2 1
      docs/module_usage/tutorials/cv_modules/image_feature.en.md
  16. 2 1
      docs/module_usage/tutorials/cv_modules/image_feature.md
  17. 2 1
      docs/module_usage/tutorials/cv_modules/image_multilabel_classification.en.md
  18. 2 1
      docs/module_usage/tutorials/cv_modules/image_multilabel_classification.md
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      docs/module_usage/tutorials/cv_modules/instance_segmentation.en.md
  20. 2 1
      docs/module_usage/tutorials/cv_modules/instance_segmentation.md
  21. 2 1
      docs/module_usage/tutorials/cv_modules/mainbody_detection.en.md
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      docs/module_usage/tutorials/cv_modules/mainbody_detection.md
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      docs/module_usage/tutorials/cv_modules/object_detection.en.md
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      docs/module_usage/tutorials/cv_modules/object_detection.md
  25. 2 1
      docs/module_usage/tutorials/cv_modules/pedestrian_attribute_recognition.en.md
  26. 2 1
      docs/module_usage/tutorials/cv_modules/pedestrian_attribute_recognition.md
  27. 2 1
      docs/module_usage/tutorials/cv_modules/rotated_object_detection.en.md
  28. 2 1
      docs/module_usage/tutorials/cv_modules/rotated_object_detection.md
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      docs/module_usage/tutorials/cv_modules/semantic_segmentation.en.md
  30. 2 1
      docs/module_usage/tutorials/cv_modules/semantic_segmentation.md
  31. 2 1
      docs/module_usage/tutorials/cv_modules/small_object_detection.en.md
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      docs/module_usage/tutorials/cv_modules/small_object_detection.md
  33. 2 1
      docs/module_usage/tutorials/cv_modules/vehicle_attribute_recognition.en.md
  34. 2 1
      docs/module_usage/tutorials/cv_modules/vehicle_attribute_recognition.md
  35. 2 1
      docs/module_usage/tutorials/cv_modules/vehicle_detection.en.md
  36. 2 1
      docs/module_usage/tutorials/cv_modules/vehicle_detection.md
  37. 2 4
      docs/module_usage/tutorials/ocr_modules/doc_img_orientation_classification.en.md
  38. 2 1
      docs/module_usage/tutorials/ocr_modules/doc_img_orientation_classification.md
  39. 2 1
      docs/module_usage/tutorials/ocr_modules/formula_recognition.en.md
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      docs/module_usage/tutorials/ocr_modules/formula_recognition.md
  41. 2 2
      docs/module_usage/tutorials/ocr_modules/layout_detection.en.md
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      docs/module_usage/tutorials/ocr_modules/layout_detection.md
  43. 2 2
      docs/module_usage/tutorials/ocr_modules/seal_text_detection.en.md
  44. 2 1
      docs/module_usage/tutorials/ocr_modules/seal_text_detection.md
  45. 2 1
      docs/module_usage/tutorials/ocr_modules/table_cells_detection.en.md
  46. 2 1
      docs/module_usage/tutorials/ocr_modules/table_cells_detection.md
  47. 2 1
      docs/module_usage/tutorials/ocr_modules/table_classification.en.md
  48. 2 1
      docs/module_usage/tutorials/ocr_modules/table_classification.md
  49. 3 2
      docs/module_usage/tutorials/ocr_modules/table_structure_recognition.en.md
  50. 2 1
      docs/module_usage/tutorials/ocr_modules/table_structure_recognition.md
  51. 2 1
      docs/module_usage/tutorials/ocr_modules/text_detection.en.md
  52. 2 1
      docs/module_usage/tutorials/ocr_modules/text_detection.md
  53. 1 1
      docs/module_usage/tutorials/ocr_modules/text_image_unwarping.md
  54. 2 2
      docs/module_usage/tutorials/ocr_modules/text_recognition.en.md
  55. 2 2
      docs/module_usage/tutorials/ocr_modules/text_recognition.md
  56. 2 1
      docs/module_usage/tutorials/ocr_modules/textline_orientation_classification.en.md
  57. 3 2
      docs/module_usage/tutorials/ocr_modules/textline_orientation_classification.md
  58. 2 1
      docs/module_usage/tutorials/speech_modules/multilingual_speech_recognition.en.md
  59. 2 2
      docs/module_usage/tutorials/time_series_modules/time_series_anomaly_detection.en.md
  60. 3 2
      docs/module_usage/tutorials/time_series_modules/time_series_anomaly_detection.md
  61. 2 2
      docs/module_usage/tutorials/time_series_modules/time_series_classification.en.md
  62. 3 2
      docs/module_usage/tutorials/time_series_modules/time_series_classification.md
  63. 2 2
      docs/module_usage/tutorials/time_series_modules/time_series_forecasting.en.md
  64. 3 2
      docs/module_usage/tutorials/time_series_modules/time_series_forecasting.md
  65. 3 2
      docs/module_usage/tutorials/video_modules/video_classification.en.md
  66. 2 1
      docs/module_usage/tutorials/video_modules/video_classification.md
  67. 3 3
      docs/module_usage/tutorials/video_modules/video_detection.en.md
  68. 3 2
      docs/module_usage/tutorials/video_modules/video_detection.md

+ 2 - 1
docs/module_usage/tutorials/cv_modules/3d_bev_detection.en.md

@@ -393,7 +393,8 @@ python main.py -c paddlex/configs/modules/3d_bev_detection/BEVFusion.yaml \
 * Specify the path of the model's `.yaml` configuration file (here it is `bevf_pp_2x8_1x_nusc.yaml`. When training other models, you need to specify the corresponding configuration file. The correspondence between models and configuration files can be found in [PaddleX Model List (CPU/GPU)](../../../support_list/models_list.en.md)).
 * Specify the path of the model's `.yaml` configuration file (here it is `bevf_pp_2x8_1x_nusc.yaml`. When training other models, you need to specify the corresponding configuration file. The correspondence between models and configuration files can be found in [PaddleX Model List (CPU/GPU)](../../../support_list/models_list.en.md)).
 * Set the mode to model training: `-o Global.mode=train`
 * Set the mode to model training: `-o Global.mode=train`
 * Specify the training dataset path: `-o Global.dataset_dir`
 * Specify the training dataset path: `-o Global.dataset_dir`
-Other related parameters can be set by modifying the fields under `Global` and `Train` in the `.yaml` configuration file, or by appending parameters in the command line. For example, to specify training on the first 2 GPUs: `-o Global.device=gpu:0,1`; to set the number of training epochs to 10: `-o Train.epochs_iters=10`. For more modifiable parameters and their detailed explanations, refer to the configuration file instructions for the corresponding model task module [PaddleX Common Model Configuration Parameters](../../instructions/config_parameters_common.en.md).
+* Other related parameters can be set by modifying the fields under `Global` and `Train` in the `.yaml` configuration file, or by appending parameters in the command line. For example, to specify training on the first 2 GPUs: `-o Global.device=gpu:0,1`; to set the number of training epochs to 10: `-o Train.epochs_iters=10`. For more modifiable parameters and their detailed explanations, refer to the configuration file instructions for the corresponding model task module [PaddleX Common Model Configuration Parameters](../../instructions/config_parameters_common.en.md).
+* New Feature: Paddle 3.0 support CINN (Compiler Infrastructure for Neural Networks) to accelerate training speed when using GPU device. Please specify `-o Train.dy2st=True` to enable it.
 
 
 <details><summary>👉 <b>More Information (Click to Expand)</b></summary>
 <details><summary>👉 <b>More Information (Click to Expand)</b></summary>
 
 

+ 2 - 1
docs/module_usage/tutorials/cv_modules/3d_bev_detection.md

@@ -406,7 +406,8 @@ python main.py -c paddlex/configs/modules/3d_bev_detection/BEVFusion.yaml \
 * 指定模型的`.yaml` 配置文件路径(此处为`bevf_pp_2x8_1x_nusc.yaml`,训练其他模型时,需要的指定相应的配置文件,模型和配置的文件的对应关系,可以查阅[PaddleX模型列表(CPU/GPU)](../../../support_list/models_list.md))
 * 指定模型的`.yaml` 配置文件路径(此处为`bevf_pp_2x8_1x_nusc.yaml`,训练其他模型时,需要的指定相应的配置文件,模型和配置的文件的对应关系,可以查阅[PaddleX模型列表(CPU/GPU)](../../../support_list/models_list.md))
 * 指定模式为模型训练:`-o Global.mode=train`
 * 指定模式为模型训练:`-o Global.mode=train`
 * 指定训练数据集路径:`-o Global.dataset_dir`
 * 指定训练数据集路径:`-o Global.dataset_dir`
-其他相关参数均可通过修改`.yaml`配置文件中的`Global`和`Train`下的字段来进行设置,也可以通过在命令行中追加参数来进行调整。如指定前 2 卡 gpu 训练:`-o Global.device=gpu:0,1`;设置训练轮次数为 10:`-o Train.epochs_iters=10`。更多可修改的参数及其详细解释,可以查阅模型对应任务模块的配置文件说明[PaddleX通用模型配置文件参数说明](../../instructions/config_parameters_common.md)。
+* 其他相关参数均可通过修改`.yaml`配置文件中的`Global`和`Train`下的字段来进行设置,也可以通过在命令行中追加参数来进行调整。如指定前 2 卡 gpu 训练:`-o Global.device=gpu:0,1`;设置训练轮次数为 10:`-o Train.epochs_iters=10`。更多可修改的参数及其详细解释,可以查阅模型对应任务模块的配置文件说明[PaddleX通用模型配置文件参数说明](../../instructions/config_parameters_common.md)
+* 新特性:Paddle 3.0 版本支持了 CINN 神经网络编译器,在使用 GPU 设备训练时,不同模型有不同程度的训练加速效果。在 PaddleX 中训练模型时,可通过指定参数 `-o Train.dy2st=True` 开启。
 
 
 <details><summary>👉 <b>更多说明(点击展开)</b></summary>
 <details><summary>👉 <b>更多说明(点击展开)</b></summary>
 
 

+ 2 - 2
docs/module_usage/tutorials/cv_modules/anomaly_detection.en.md

@@ -344,8 +344,8 @@ The steps required are:
 * Specify the path to the `.yaml` configuration file of the model (here it is `STFPM.yaml`,When training other models, you need to specify the corresponding configuration files. The relationship between the model and configuration files can be found in the [PaddleX Model List (CPU/GPU)](../../../support_list/models_list.en.md))
 * Specify the path to the `.yaml` configuration file of the model (here it is `STFPM.yaml`,When training other models, you need to specify the corresponding configuration files. The relationship between the model and configuration files can be found in the [PaddleX Model List (CPU/GPU)](../../../support_list/models_list.en.md))
 * Specify the mode as model training: `-o Global.mode=train`
 * Specify the mode as model training: `-o Global.mode=train`
 * Specify the path to the training dataset: `-o Global.dataset_dir`
 * Specify the path to the training dataset: `-o Global.dataset_dir`
-
-Other related parameters can be set by modifying the `Global` and `Train` fields in the `.yaml` configuration file, or adjusted by appending parameters in the command line. For example, to specify training on the first two GPUs: `-o Global.device=gpu:0,1`; to set the number of training epochs to 10: `-o Train.epochs_iters=10`. For more modifiable parameters and their detailed explanations, refer to the [PaddleX Common Configuration Parameters for Model Tasks](../../instructions/config_parameters_common.en.md).
+* Other related parameters can be set by modifying the `Global` and `Train` fields in the `.yaml` configuration file, or adjusted by appending parameters in the command line. For example, to specify training on the first two GPUs: `-o Global.device=gpu:0,1`; to set the number of training epochs to 10: `-o Train.epochs_iters=10`. For more modifiable parameters and their detailed explanations, refer to the [PaddleX Common Configuration Parameters for Model Tasks](../../instructions/config_parameters_common.en.md).
+* New Feature: Paddle 3.0 support CINN (Compiler Infrastructure for Neural Networks) to accelerate training speed when using GPU device. Please specify `-o Train.dy2st=True` to enable it.
 
 
 <details><summary>👉 <b>More Details (Click to Expand)</b></summary>
 <details><summary>👉 <b>More Details (Click to Expand)</b></summary>
 
 

+ 2 - 1
docs/module_usage/tutorials/cv_modules/anomaly_detection.md

@@ -347,7 +347,8 @@ python main.py -c paddlex/configs/modules/image_anomaly_detection/STFPM.yaml \
 * 指定模型的`.yaml` 配置文件路径(此处为`STFPM.yaml`,训练其他模型时,需要的指定相应的配置文件,模型和配置的文件的对应关系,可以查阅[PaddleX模型列表(CPU/GPU)](../../../support_list/models_list.md))
 * 指定模型的`.yaml` 配置文件路径(此处为`STFPM.yaml`,训练其他模型时,需要的指定相应的配置文件,模型和配置的文件的对应关系,可以查阅[PaddleX模型列表(CPU/GPU)](../../../support_list/models_list.md))
 * 指定模式为模型训练:`-o Global.mode=train`
 * 指定模式为模型训练:`-o Global.mode=train`
 * 指定训练数据集路径:`-o Global.dataset_dir`
 * 指定训练数据集路径:`-o Global.dataset_dir`
-其他相关参数均可通过修改`.yaml`配置文件中的`Global`和`Train`下的字段来进行设置,也可以通过在命令行中追加参数来进行调整。如指定前 2 卡 gpu 训练:`-o Global.device=gpu:0,1`;设置训练轮次数为 10:`-o Train.epochs_iters=10`。更多可修改的参数及其详细解释,可以查阅模型对应任务模块的配置文件说明[PaddleX通用模型配置文件参数说明](../../instructions/config_parameters_common.md)。
+* 其他相关参数均可通过修改`.yaml`配置文件中的`Global`和`Train`下的字段来进行设置,也可以通过在命令行中追加参数来进行调整。如指定前 2 卡 gpu 训练:`-o Global.device=gpu:0,1`;设置训练轮次数为 10:`-o Train.epochs_iters=10`。更多可修改的参数及其详细解释,可以查阅模型对应任务模块的配置文件说明[PaddleX通用模型配置文件参数说明](../../instructions/config_parameters_common.md)
+* 新特性:Paddle 3.0 版本支持了 CINN 神经网络编译器,在使用 GPU 设备训练时,不同模型有不同程度的训练加速效果。在 PaddleX 中训练模型时,可通过指定参数 `-o Train.dy2st=True` 开启。
 
 
 <details><summary>👉 <b>更多说明(点击展开)</b></summary>
 <details><summary>👉 <b>更多说明(点击展开)</b></summary>
 
 

+ 2 - 2
docs/module_usage/tutorials/cv_modules/face_detection.en.md

@@ -453,8 +453,8 @@ The steps required are:
 * Specify the path to the `.yaml` configuration file of the model (here it is `PicoDet_LCNet_x2_5_face.yaml`,When training other models, you need to specify the corresponding configuration files. The relationship between the model and configuration files can be found in the [PaddleX Model List (CPU/GPU)](../../../support_list/models_list.en.md))
 * Specify the path to the `.yaml` configuration file of the model (here it is `PicoDet_LCNet_x2_5_face.yaml`,When training other models, you need to specify the corresponding configuration files. The relationship between the model and configuration files can be found in the [PaddleX Model List (CPU/GPU)](../../../support_list/models_list.en.md))
 * Specify the mode as model training: `-o Global.mode=train`
 * Specify the mode as model training: `-o Global.mode=train`
 * Specify the path to the training dataset: `-o Global.dataset_dir`
 * Specify the path to the training dataset: `-o Global.dataset_dir`
-
-Other related parameters can be set by modifying the `Global` and `Train` fields in the `.yaml` configuration file, or adjusted by appending parameters in the command line. For example, to specify training on the first two GPUs: `-o Global.device=gpu:0,1`; to set the number of training epochs to 10: `-o Train.epochs_iters=10`. For more modifiable parameters and their detailed explanations, refer to the [PaddleX Common Configuration Parameters for Model Tasks](../../instructions/config_parameters_common.en.md).
+* Other related parameters can be set by modifying the `Global` and `Train` fields in the `.yaml` configuration file, or adjusted by appending parameters in the command line. For example, to specify training on the first two GPUs: `-o Global.device=gpu:0,1`; to set the number of training epochs to 10: `-o Train.epochs_iters=10`. For more modifiable parameters and their detailed explanations, refer to the [PaddleX Common Configuration Parameters for Model Tasks](../../instructions/config_parameters_common.en.md).
+* New Feature: Paddle 3.0 support CINN (Compiler Infrastructure for Neural Networks) to accelerate training speed when using GPU device. Please specify `-o Train.dy2st=True` to enable it.
 
 
 <details><summary>👉 <b>More Details (Click to Expand)</b></summary>
 <details><summary>👉 <b>More Details (Click to Expand)</b></summary>
 <ul>
 <ul>

+ 2 - 1
docs/module_usage/tutorials/cv_modules/face_detection.md

@@ -443,7 +443,8 @@ python main.py -c paddlex/configs/modules/face_detection/PicoDet_LCNet_x2_5_face
 * 指定模型的`.yaml` 配置文件路径(此处为`PicoDet_LCNet_x2_5_face.yaml`,训练其他模型时,需要的指定相应的配置文件,模型和配置的文件的对应关系,可以查阅[PaddleX模型列表(CPU/GPU)](../../../support_list/models_list.md))
 * 指定模型的`.yaml` 配置文件路径(此处为`PicoDet_LCNet_x2_5_face.yaml`,训练其他模型时,需要的指定相应的配置文件,模型和配置的文件的对应关系,可以查阅[PaddleX模型列表(CPU/GPU)](../../../support_list/models_list.md))
 * 指定模式为模型训练:`-o Global.mode=train`
 * 指定模式为模型训练:`-o Global.mode=train`
 * 指定训练数据集路径:`-o Global.dataset_dir`
 * 指定训练数据集路径:`-o Global.dataset_dir`
-其他相关参数均可通过修改`.yaml`配置文件中的`Global`和`Train`下的字段来进行设置,也可以通过在命令行中追加参数来进行调整。如指定前 2 卡 gpu 训练:`-o Global.device=gpu:0,1`;设置训练轮次数为 10:`-o Train.epochs_iters=10`。更多可修改的参数及其详细解释,可以查阅模型对应任务模块的配置文件说明[PaddleX通用模型配置文件参数说明](../../instructions/config_parameters_common.md)。
+* 其他相关参数均可通过修改`.yaml`配置文件中的`Global`和`Train`下的字段来进行设置,也可以通过在命令行中追加参数来进行调整。如指定前 2 卡 gpu 训练:`-o Global.device=gpu:0,1`;设置训练轮次数为 10:`-o Train.epochs_iters=10`。更多可修改的参数及其详细解释,可以查阅模型对应任务模块的配置文件说明[PaddleX通用模型配置文件参数说明](../../instructions/config_parameters_common.md)
+* 新特性:Paddle 3.0 版本支持了 CINN 神经网络编译器,在使用 GPU 设备训练时,不同模型有不同程度的训练加速效果。在 PaddleX 中训练模型时,可通过指定参数 `-o Train.dy2st=True` 开启。
 
 
 <details><summary>👉 <b>更多说明(点击展开)</b></summary>
 <details><summary>👉 <b>更多说明(点击展开)</b></summary>
 <ul>
 <ul>

+ 2 - 1
docs/module_usage/tutorials/cv_modules/face_feature.en.md

@@ -402,7 +402,8 @@ The steps required are:
 * Specify the path to the `.yaml` configuration file for the model (here it is `MobileFaceNet.yaml`)
 * Specify the path to the `.yaml` configuration file for the model (here it is `MobileFaceNet.yaml`)
 * Specify the mode as model training: `-o Global.mode=train`
 * Specify the mode as model training: `-o Global.mode=train`
 * Specify the path to the training dataset: `-o Global.dataset_dir`
 * Specify the path to the training dataset: `-o Global.dataset_dir`
-Other related parameters can be set by modifying the `Global` and `Train` fields in the `.yaml` configuration file or by appending parameters in the command line. For example, to specify the first two GPUs for training: `-o Global.device=gpu:0,1`; to set the number of training epochs to 10: `-o Train.epochs_iters=10`. For more modifiable parameters and their detailed explanations, refer to the configuration file instructions for the corresponding task module [PaddleX Common Configuration Parameters for Model Tasks](../../instructions/config_parameters_common.en.md).
+* Other related parameters can be set by modifying the `Global` and `Train` fields in the `.yaml` configuration file or by appending parameters in the command line. For example, to specify the first two GPUs for training: `-o Global.device=gpu:0,1`; to set the number of training epochs to 10: `-o Train.epochs_iters=10`. For more modifiable parameters and their detailed explanations, refer to the configuration file instructions for the corresponding task module [PaddleX Common Configuration Parameters for Model Tasks](../../instructions/config_parameters_common.en.md).
+* New Feature: Paddle 3.0 support CINN (Compiler Infrastructure for Neural Networks) to accelerate training speed when using GPU device. Please specify `-o Train.dy2st=True` to enable it.
 
 
 <details><summary>👉 <b>More Details (Click to Expand)</b></summary>
 <details><summary>👉 <b>More Details (Click to Expand)</b></summary>
 <ul>
 <ul>

+ 2 - 1
docs/module_usage/tutorials/cv_modules/face_feature.md

@@ -425,7 +425,8 @@ python main.py -c paddlex/configs/modules/face_feature/MobileFaceNet.yaml \
 * 指定模型的`.yaml` 配置文件路径(此处为`MobileFaceNet.yaml`)
 * 指定模型的`.yaml` 配置文件路径(此处为`MobileFaceNet.yaml`)
 * 指定模式为模型训练:`-o Global.mode=train`
 * 指定模式为模型训练:`-o Global.mode=train`
 * 指定训练数据集路径:`-o Global.dataset_dir`
 * 指定训练数据集路径:`-o Global.dataset_dir`
-其他相关参数均可通过修改`.yaml`配置文件中的`Global`和`Train`下的字段来进行设置,也可以通过在命令行中追加参数来进行调整。如指定前 2 卡 gpu 训练:`-o Global.device=gpu:0,1`;设置训练轮次数为 10:`-o Train.epochs_iters=10`。更多可修改的参数及其详细解释,可以查阅模型对应任务模块的配置文件说明[PaddleX通用模型配置文件参数说明](../../instructions/config_parameters_common.md)。
+* 其他相关参数均可通过修改`.yaml`配置文件中的`Global`和`Train`下的字段来进行设置,也可以通过在命令行中追加参数来进行调整。如指定前 2 卡 gpu 训练:`-o Global.device=gpu:0,1`;设置训练轮次数为 10:`-o Train.epochs_iters=10`。更多可修改的参数及其详细解释,可以查阅模型对应任务模块的配置文件说明[PaddleX通用模型配置文件参数说明](../../instructions/config_parameters_common.md)
+* 新特性:Paddle 3.0 版本支持了 CINN 神经网络编译器,在使用 GPU 设备训练时,不同模型有不同程度的训练加速效果。在 PaddleX 中训练模型时,可通过指定参数 `-o Train.dy2st=True` 开启。
 
 
 <details><summary>👉 <b>更多说明(点击展开)</b></summary>
 <details><summary>👉 <b>更多说明(点击展开)</b></summary>
 <ul>
 <ul>

+ 2 - 1
docs/module_usage/tutorials/cv_modules/human_detection.en.md

@@ -424,7 +424,8 @@ The steps required are:
 * Specify the `.yaml` configuration file path for the model (here it is `PP-YOLOE-S_human.yaml`,When training other models, you need to specify the corresponding configuration files. The relationship between the model and configuration files can be found in the [PaddleX Model List (CPU/GPU)](../../../support_list/models_list.en.md))
 * Specify the `.yaml` configuration file path for the model (here it is `PP-YOLOE-S_human.yaml`,When training other models, you need to specify the corresponding configuration files. The relationship between the model and configuration files can be found in the [PaddleX Model List (CPU/GPU)](../../../support_list/models_list.en.md))
 * Specify the mode as model training: `-o Global.mode=train`
 * Specify the mode as model training: `-o Global.mode=train`
 * Specify the training dataset path: `-o Global.dataset_dir`
 * Specify the training dataset path: `-o Global.dataset_dir`
-Other related parameters can be set by modifying the `Global` and `Train` fields in the `.yaml` configuration file, or adjusted by appending parameters in the command line. For example, to specify training on the first two GPUs: `-o Global.device=gpu:0,1`; to set the number of training epochs to 10: `-o Train.epochs_iters=10`. For more modifiable parameters and their detailed explanations, refer to the [PaddleX Common Configuration Parameters for Model Tasks](../../instructions/config_parameters_common.en.md).
+* Other related parameters can be set by modifying the `Global` and `Train` fields in the `.yaml` configuration file, or adjusted by appending parameters in the command line. For example, to specify training on the first two GPUs: `-o Global.device=gpu:0,1`; to set the number of training epochs to 10: `-o Train.epochs_iters=10`. For more modifiable parameters and their detailed explanations, refer to the [PaddleX Common Configuration Parameters for Model Tasks](../../instructions/config_parameters_common.en.md).
+* New Feature: Paddle 3.0 support CINN (Compiler Infrastructure for Neural Networks) to accelerate training speed when using GPU device. Please specify `-o Train.dy2st=True` to enable it.
 
 
 <details><summary>👉 <b>More Details (Click to Expand)</b></summary>
 <details><summary>👉 <b>More Details (Click to Expand)</b></summary>
 <ul>
 <ul>

+ 2 - 1
docs/module_usage/tutorials/cv_modules/human_detection.md

@@ -422,7 +422,8 @@ python main.py -c paddlex/configs/modules/human_detection/PP-YOLOE-S_human.yaml
 * 指定模型的`.yaml` 配置文件路径(此处为`PP-YOLOE-S_human.yaml`,训练其他模型时,需要的指定相应的配置文件,模型和配置的文件的对应关系,可以查阅[PaddleX模型列表(CPU/GPU)](../../../support_list/models_list.md))
 * 指定模型的`.yaml` 配置文件路径(此处为`PP-YOLOE-S_human.yaml`,训练其他模型时,需要的指定相应的配置文件,模型和配置的文件的对应关系,可以查阅[PaddleX模型列表(CPU/GPU)](../../../support_list/models_list.md))
 * 指定模式为模型训练:`-o Global.mode=train`
 * 指定模式为模型训练:`-o Global.mode=train`
 * 指定训练数据集路径:`-o Global.dataset_dir`
 * 指定训练数据集路径:`-o Global.dataset_dir`
-其他相关参数均可通过修改`.yaml`配置文件中的`Global`和`Train`下的字段来进行设置,也可以通过在命令行中追加参数来进行调整。如指定前 2 卡 gpu 训练:`-o Global.device=gpu:0,1`;设置训练轮次数为 10:`-o Train.epochs_iters=10`。更多可修改的参数及其详细解释,可以查阅模型对应任务模块的配置文件说明[PaddleX通用模型配置文件参数说明](../../instructions/config_parameters_common.md)。
+* 其他相关参数均可通过修改`.yaml`配置文件中的`Global`和`Train`下的字段来进行设置,也可以通过在命令行中追加参数来进行调整。如指定前 2 卡 gpu 训练:`-o Global.device=gpu:0,1`;设置训练轮次数为 10:`-o Train.epochs_iters=10`。更多可修改的参数及其详细解释,可以查阅模型对应任务模块的配置文件说明[PaddleX通用模型配置文件参数说明](../../instructions/config_parameters_common.md)
+* 新特性:Paddle 3.0 版本支持了 CINN 神经网络编译器,在使用 GPU 设备训练时,不同模型有不同程度的训练加速效果。在 PaddleX 中训练模型时,可通过指定参数 `-o Train.dy2st=True` 开启。
 
 
 <details><summary>👉 <b>更多说明(点击展开)</b></summary>
 <details><summary>👉 <b>更多说明(点击展开)</b></summary>
 <ul>
 <ul>

+ 2 - 1
docs/module_usage/tutorials/cv_modules/human_keypoint_detection.en.md

@@ -438,7 +438,8 @@ Similar to model training, the process involves the following steps:
 * Specify the path to the `.yaml` configuration file for the model(here it's `MobileFaceNet.yaml`)
 * Specify the path to the `.yaml` configuration file for the model(here it's `MobileFaceNet.yaml`)
 * Set the mode to model evaluation: `-o Global.mode=evaluate`
 * Set the mode to model evaluation: `-o Global.mode=evaluate`
 * Specify the path to the validation dataset: `-o Global.dataset_dir`
 * Specify the path to the validation dataset: `-o Global.dataset_dir`
-Other related parameters can be configured by modifying the fields under `Global` and `Evaluate` in the `.yaml` configuration file. For detailed information, please refer to [PaddleX Common Configuration Parameters for Models](../../instructions/config_parameters_common.en.md)。
+* Other related parameters can be configured by modifying the fields under `Global` and `Evaluate` in the `.yaml` configuration file. For detailed information, please refer to [PaddleX Common Configuration Parameters for Models](../../instructions/config_parameters_common.en.md).
+* New Feature: Paddle 3.0 support CINN (Compiler Infrastructure for Neural Networks) to accelerate training speed when using GPU device. Please specify `-o Train.dy2st=True` to enable it.
 
 
 <details>
 <details>
 <summary>👉 <b>More Details (Click to Expand)</b></summary>
 <summary>👉 <b>More Details (Click to Expand)</b></summary>

+ 2 - 1
docs/module_usage/tutorials/cv_modules/human_keypoint_detection.md

@@ -454,7 +454,8 @@ python main.py -c paddlex/configs/modules/keypoint_detection/PP-TinyPose_128x96.
 * 指定模型的`.yaml` 配置文件路径(此处为`PP-TinyPose_128x96.yaml`,训练其他模型时,需要的指定相应的配置文件,模型和配置的文件的对应关系,可以查阅[PaddleX模型列表(CPU/GPU)](../../../support_list/models_list.md))
 * 指定模型的`.yaml` 配置文件路径(此处为`PP-TinyPose_128x96.yaml`,训练其他模型时,需要的指定相应的配置文件,模型和配置的文件的对应关系,可以查阅[PaddleX模型列表(CPU/GPU)](../../../support_list/models_list.md))
 * 指定模式为模型训练:`-o Global.mode=train`
 * 指定模式为模型训练:`-o Global.mode=train`
 * 指定训练数据集路径:`-o Global.dataset_dir`
 * 指定训练数据集路径:`-o Global.dataset_dir`
-其他相关参数均可通过修改`.yaml`配置文件中的`Global`和`Train`下的字段来进行设置,也可以通过在命令行中追加参数来进行调整。如指定前 2 卡 gpu 训练:`-o Global.device=gpu:0,1`;设置训练轮次数为 10:`-o Train.epochs_iters=10`。更多可修改的参数及其详细解释,可以查阅模型对应任务模块的配置文件说明[PaddleX通用模型配置文件参数说明](../../instructions/config_parameters_common.md)。
+* 其他相关参数均可通过修改`.yaml`配置文件中的`Global`和`Train`下的字段来进行设置,也可以通过在命令行中追加参数来进行调整。如指定前 2 卡 gpu 训练:`-o Global.device=gpu:0,1`;设置训练轮次数为 10:`-o Train.epochs_iters=10`。更多可修改的参数及其详细解释,可以查阅模型对应任务模块的配置文件说明[PaddleX通用模型配置文件参数说明](../../instructions/config_parameters_common.md)
+* 新特性:Paddle 3.0 版本支持了 CINN 神经网络编译器,在使用 GPU 设备训练时,不同模型有不同程度的训练加速效果。在 PaddleX 中训练模型时,可通过指定参数 `-o Train.dy2st=True` 开启。
 
 
 <details>
 <details>
   <summary>👉 <b>更多说明(点击展开)</b></summary>
   <summary>👉 <b>更多说明(点击展开)</b></summary>

+ 3 - 1
docs/module_usage/tutorials/cv_modules/image_classification.en.md

@@ -1062,7 +1062,9 @@ Similar to model training, the following steps are required:
 
 
 * Specify the path of the model's `.yaml` configuration file (here it is `PP-LCNet_x1_0.yaml`)
 * Specify the path of the model's `.yaml` configuration file (here it is `PP-LCNet_x1_0.yaml`)
 * Specify the mode as model evaluation: `-o Global.mode=evaluate`
 * Specify the mode as model evaluation: `-o Global.mode=evaluate`
-* Specify the path of the validation dataset: `-o Global.dataset_dir`. Other related parameters can be set by modifying the fields under `Global` and `Evaluate` in the `.yaml` configuration. Other related parameters can be set by modifying the fields under `Global` and `Evaluate` in the `.yaml` configuration file. For details, please refer to [PaddleX Common Model Configuration File Parameter Description](../../instructions/config_parameters_common.en.md).
+* Specify the path of the validation dataset: `-o Global.dataset_dir`
+* Other related parameters can be set by modifying the fields under `Global` and `Evaluate` in the `.yaml` configuration. Other related parameters can be set by modifying the fields under `Global` and `Evaluate` in the `.yaml` configuration file. For details, please refer to [PaddleX Common Model Configuration File Parameter Description](../../instructions/config_parameters_common.en.md).
+* New Feature: Paddle 3.0 support CINN (Compiler Infrastructure for Neural Networks) to accelerate training speed when using GPU device. Please specify `-o Train.dy2st=True` to enable it.
 
 
 <details><summary>👉 <b>More Details (Click to Expand)</b></summary>
 <details><summary>👉 <b>More Details (Click to Expand)</b></summary>
 <p>When evaluating the model, you need to specify the model weight file path. Each configuration file has a default weight save path built-in. If you need to change it, simply set it by appending a command line parameter, such as <code>-o Evaluate.weight_path=./output/best_model/best_model.pdparams</code>.</p>
 <p>When evaluating the model, you need to specify the model weight file path. Each configuration file has a default weight save path built-in. If you need to change it, simply set it by appending a command line parameter, such as <code>-o Evaluate.weight_path=./output/best_model/best_model.pdparams</code>.</p>

+ 2 - 1
docs/module_usage/tutorials/cv_modules/image_classification.md

@@ -1051,7 +1051,8 @@ python main.py -c paddlex/configs/modules/image_classification/PP-LCNet_x1_0.yam
 * 指定模型的`.yaml` 配置文件路径(此处为`PP-LCNet_x1_0.yaml`,训练其他模型时,需要的指定相应的配置文件,模型和配置的文件的对应关系,可以查阅[PaddleX模型列表(CPU/GPU)](../../../support_list/models_list.md))
 * 指定模型的`.yaml` 配置文件路径(此处为`PP-LCNet_x1_0.yaml`,训练其他模型时,需要的指定相应的配置文件,模型和配置的文件的对应关系,可以查阅[PaddleX模型列表(CPU/GPU)](../../../support_list/models_list.md))
 * 指定模式为模型训练:`-o Global.mode=train`
 * 指定模式为模型训练:`-o Global.mode=train`
 * 指定训练数据集路径:`-o Global.dataset_dir`
 * 指定训练数据集路径:`-o Global.dataset_dir`
-其他相关参数均可通过修改`.yaml`配置文件中的`Global`和`Train`下的字段来进行设置,也可以通过在命令行中追加参数来进行调整。如指定前 2 卡 gpu 训练:`-o Global.device=gpu:0,1`;设置训练轮次数为 10:`-o Train.epochs_iters=10`。更多可修改的参数及其详细解释,可以查阅模型对应任务模块的配置文件说明[PaddleX通用模型配置文件参数说明](../../instructions/config_parameters_common.md)。
+* 其他相关参数均可通过修改`.yaml`配置文件中的`Global`和`Train`下的字段来进行设置,也可以通过在命令行中追加参数来进行调整。如指定前 2 卡 gpu 训练:`-o Global.device=gpu:0,1`;设置训练轮次数为 10:`-o Train.epochs_iters=10`。更多可修改的参数及其详细解释,可以查阅模型对应任务模块的配置文件说明[PaddleX通用模型配置文件参数说明](../../instructions/config_parameters_common.md)
+* 新特性:Paddle 3.0 版本支持了 CINN 神经网络编译器,在使用 GPU 设备训练时,不同模型有不同程度的训练加速效果。在 PaddleX 中训练模型时,可通过指定参数 `-o Train.dy2st=True` 开启。
 
 
 <details><summary>👉 <b>更多说明(点击展开)</b></summary>
 <details><summary>👉 <b>更多说明(点击展开)</b></summary>
 <ul>
 <ul>

+ 2 - 1
docs/module_usage/tutorials/cv_modules/image_feature.en.md

@@ -440,7 +440,8 @@ The following steps are required:
 * Specify the `.yaml` configuration file path for the model (here it is `PP-ShiTuV2_rec.yaml`,When training other models, you need to specify the corresponding configuration files. The relationship between the model and configuration files can be found in the [PaddleX Model List (CPU/GPU)](../../../support_list/models_list.en.md))
 * Specify the `.yaml` configuration file path for the model (here it is `PP-ShiTuV2_rec.yaml`,When training other models, you need to specify the corresponding configuration files. The relationship between the model and configuration files can be found in the [PaddleX Model List (CPU/GPU)](../../../support_list/models_list.en.md))
 * Set the mode to model training: `-o Global.mode=train`
 * Set the mode to model training: `-o Global.mode=train`
 * Specify the path to the training dataset: `-o Global.dataset_dir`.
 * Specify the path to the training dataset: `-o Global.dataset_dir`.
-Other related parameters can be set by modifying the `Global` and `Train` fields in the `.yaml` configuration file, or adjusted by appending parameters in the command line. For example, to specify training on the first two GPUs: `-o Global.device=gpu:0,1`; to set the number of training epochs to 10: `-o Train.epochs_iters=10`. For more modifiable parameters and their detailed explanations, refer to the configuration file instructions for the corresponding task module of the model [PaddleX Common Configuration File Parameters](../../instructions/config_parameters_common.en.md).
+* Other related parameters can be set by modifying the `Global` and `Train` fields in the `.yaml` configuration file, or adjusted by appending parameters in the command line. For example, to specify training on the first two GPUs: `-o Global.device=gpu:0,1`; to set the number of training epochs to 10: `-o Train.epochs_iters=10`. For more modifiable parameters and their detailed explanations, refer to the configuration file instructions for the corresponding task module of the model [PaddleX Common Configuration File Parameters](../../instructions/config_parameters_common.en.md).
+* New Feature: Paddle 3.0 support CINN (Compiler Infrastructure for Neural Networks) to accelerate training speed when using GPU device. Please specify `-o Train.dy2st=True` to enable it.
 
 
 <details><summary>👉 <b>More Details (Click to Expand)</b></summary>
 <details><summary>👉 <b>More Details (Click to Expand)</b></summary>
 <ul>
 <ul>

+ 2 - 1
docs/module_usage/tutorials/cv_modules/image_feature.md

@@ -440,7 +440,8 @@ python main.py -c paddlex/configs/modules/image_feature/PP-ShiTuV2_rec.yaml \
 * 指定模型的`.yaml` 配置文件路径(此处为`PP-ShiTuV2_rec.yaml`,训练其他模型时,需要的指定相应的配置文件,模型和配置的文件的对应关系,可以查阅[PaddleX模型列表(CPU/GPU)](../../../support_list/models_list.md))
 * 指定模型的`.yaml` 配置文件路径(此处为`PP-ShiTuV2_rec.yaml`,训练其他模型时,需要的指定相应的配置文件,模型和配置的文件的对应关系,可以查阅[PaddleX模型列表(CPU/GPU)](../../../support_list/models_list.md))
 * 指定模式为模型训练:`-o Global.mode=train`
 * 指定模式为模型训练:`-o Global.mode=train`
 * 指定训练数据集路径:`-o Global.dataset_dir`
 * 指定训练数据集路径:`-o Global.dataset_dir`
-其他相关参数均可通过修改`.yaml`配置文件中的`Global`和`Train`下的字段来进行设置,也可以通过在命令行中追加参数来进行调整。如指定前 2 卡 gpu 训练:`-o Global.device=gpu:0,1`;设置训练轮次数为 10:`-o Train.epochs_iters=10`。更多可修改的参数及其详细解释,可以查阅模型对应任务模块的配置文件说明[PaddleX通用模型配置文件参数说明](../../instructions/config_parameters_common.md)。
+* 其他相关参数均可通过修改`.yaml`配置文件中的`Global`和`Train`下的字段来进行设置,也可以通过在命令行中追加参数来进行调整。如指定前 2 卡 gpu 训练:`-o Global.device=gpu:0,1`;设置训练轮次数为 10:`-o Train.epochs_iters=10`。更多可修改的参数及其详细解释,可以查阅模型对应任务模块的配置文件说明[PaddleX通用模型配置文件参数说明](../../instructions/config_parameters_common.md)
+* 新特性:Paddle 3.0 版本支持了 CINN 神经网络编译器,在使用 GPU 设备训练时,不同模型有不同程度的训练加速效果。在 PaddleX 中训练模型时,可通过指定参数 `-o Train.dy2st=True` 开启。
 
 
 <details><summary>👉 <b>更多说明(点击展开)</b></summary>
 <details><summary>👉 <b>更多说明(点击展开)</b></summary>
 <ul>
 <ul>

+ 2 - 1
docs/module_usage/tutorials/cv_modules/image_multilabel_classification.en.md

@@ -503,7 +503,8 @@ Similar to model training, the following steps are required:
 * Specify the `.yaml` configuration file path for the model (here it's `PP-LCNet_x1_0_ML.yaml`)
 * Specify the `.yaml` configuration file path for the model (here it's `PP-LCNet_x1_0_ML.yaml`)
 * Specify the mode as model evaluation: `-o Global.mode=evaluate`
 * Specify the mode as model evaluation: `-o Global.mode=evaluate`
 * Specify the path to the validation dataset: `-o Global.dataset_dir`
 * Specify the path to the validation dataset: `-o Global.dataset_dir`
-Other related parameters can be set by modifying the `Global` and `Evaluate` fields in the `.yaml` configuration file. For details, refer to [PaddleX Common Model Configuration File Parameter Description](../../instructions/config_parameters_common.en.md).
+* Other related parameters can be set by modifying the `Global` and `Evaluate` fields in the `.yaml` configuration file. For details, refer to [PaddleX Common Model Configuration File Parameter Description](../../instructions/config_parameters_common.en.md).
+* New Feature: Paddle 3.0 support CINN (Compiler Infrastructure for Neural Networks) to accelerate training speed when using GPU device. Please specify `-o Train.dy2st=True` to enable it.
 
 
 <details><summary>👉 <b>More Details (Click to Expand)</b></summary>
 <details><summary>👉 <b>More Details (Click to Expand)</b></summary>
 <p>When evaluating the model, you need to specify the model weights file path. Each configuration file has a default weight save path. If you need to change it, simply append the command line parameter to set it, such as <code>-o Evaluate.weight_path=./output/best_model/best_model.pdparams</code>.</p>
 <p>When evaluating the model, you need to specify the model weights file path. Each configuration file has a default weight save path. If you need to change it, simply append the command line parameter to set it, such as <code>-o Evaluate.weight_path=./output/best_model/best_model.pdparams</code>.</p>

+ 2 - 1
docs/module_usage/tutorials/cv_modules/image_multilabel_classification.md

@@ -493,7 +493,8 @@ python main.py -c paddlex/configs/modules/image_multilabel_classification/PP-LCN
 * 指定模型的`.yaml` 配置文件路径(此处为`PP-LCNet_x1_0_ML.yaml`,训练其他模型时,需要的指定相应的配置文件,模型和配置的文件的对应关系,可以查阅[PaddleX模型列表(CPU/GPU)](../../../support_list/models_list.md))
 * 指定模型的`.yaml` 配置文件路径(此处为`PP-LCNet_x1_0_ML.yaml`,训练其他模型时,需要的指定相应的配置文件,模型和配置的文件的对应关系,可以查阅[PaddleX模型列表(CPU/GPU)](../../../support_list/models_list.md))
 * 指定模式为模型训练:`-o Global.mode=train`
 * 指定模式为模型训练:`-o Global.mode=train`
 * 指定训练数据集路径:`-o Global.dataset_dir`
 * 指定训练数据集路径:`-o Global.dataset_dir`
-其他相关参数均可通过修改`.yaml`配置文件中的`Global`和`Train`下的字段来进行设置,也可以通过在命令行中追加参数来进行调整。如指定前 2 卡 gpu 训练:`-o Global.device=gpu:0,1`;设置训练轮次数为 10:`-o Train.epochs_iters=10`。更多可修改的参数及其详细解释,可以查阅模型对应任务模块的配置文件说明[PaddleX通用模型配置文件参数说明](../../instructions/config_parameters_common.md)。
+* 其他相关参数均可通过修改`.yaml`配置文件中的`Global`和`Train`下的字段来进行设置,也可以通过在命令行中追加参数来进行调整。如指定前 2 卡 gpu 训练:`-o Global.device=gpu:0,1`;设置训练轮次数为 10:`-o Train.epochs_iters=10`。更多可修改的参数及其详细解释,可以查阅模型对应任务模块的配置文件说明[PaddleX通用模型配置文件参数说明](../../instructions/config_parameters_common.md)
+* 新特性:Paddle 3.0 版本支持了 CINN 神经网络编译器,在使用 GPU 设备训练时,不同模型有不同程度的训练加速效果。在 PaddleX 中训练模型时,可通过指定参数 `-o Train.dy2st=True` 开启。
 
 
 <details><summary>👉 <b>更多说明(点击展开)</b></summary>
 <details><summary>👉 <b>更多说明(点击展开)</b></summary>
 <ul>
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+ 3 - 2
docs/module_usage/tutorials/cv_modules/instance_segmentation.en.md

@@ -572,8 +572,9 @@ The following steps are required:
 
 
 * Specify the path to the `.yaml` configuration file of the model (here it is `Mask-RT-DETR-L.yaml`,When training other models, you need to specify the corresponding configuration files. The relationship between the model and configuration files can be found in the [PaddleX Model List (CPU/GPU)](../../../support_list/models_list.en.md))
 * Specify the path to the `.yaml` configuration file of the model (here it is `Mask-RT-DETR-L.yaml`,When training other models, you need to specify the corresponding configuration files. The relationship between the model and configuration files can be found in the [PaddleX Model List (CPU/GPU)](../../../support_list/models_list.en.md))
 * Specify the mode as model training: `-o Global.mode=train`
 * Specify the mode as model training: `-o Global.mode=train`
-* Specify the path to the training dataset: `-o Global.dataset_dir`.
-Other related parameters can be set by modifying the fields under `Global` and `Train` in the `.yaml` configuration file, or adjusted by appending parameters in the command line. For example, to specify the first 2 GPUs for training: `-o Global.device=gpu:0,1`; to set the number of training epochs to 10: `-o Train.epochs_iters=10`. For more modifiable parameters and their detailed explanations, refer to the [PaddleX Common Configuration File Parameters Instructions](../../instructions/config_parameters_common.en.md).
+* Specify the path to the training dataset: `-o Global.dataset_dir`
+* Other related parameters can be set by modifying the fields under `Global` and `Train` in the `.yaml` configuration file, or adjusted by appending parameters in the command line. For example, to specify the first 2 GPUs for training: `-o Global.device=gpu:0,1`; to set the number of training epochs to 10: `-o Train.epochs_iters=10`. For more modifiable parameters and their detailed explanations, refer to the [PaddleX Common Configuration File Parameters Instructions](../../instructions/config_parameters_common.en.md).
+* New Feature: Paddle 3.0 support CINN (Compiler Infrastructure for Neural Networks) to accelerate training speed when using GPU device. Please specify `-o Train.dy2st=True` to enable it.
 
 
 <details><summary>👉 <b>More Details (Click to Expand)</b></summary>
 <details><summary>👉 <b>More Details (Click to Expand)</b></summary>
 <ul>
 <ul>

+ 2 - 1
docs/module_usage/tutorials/cv_modules/instance_segmentation.md

@@ -577,7 +577,8 @@ python main.py -c paddlex/configs/modules/instance_segmentation/Mask-RT-DETR-L.y
 * 指定模型的`.yaml` 配置文件路径(此处为 `Mask-RT-DETR-L.yaml`,训练其他模型时,需要的指定相应的配置文件,模型和配置的文件的对应关系,可以查阅[PaddleX模型列表(CPU/GPU)](../../../support_list/models_list.md))
 * 指定模型的`.yaml` 配置文件路径(此处为 `Mask-RT-DETR-L.yaml`,训练其他模型时,需要的指定相应的配置文件,模型和配置的文件的对应关系,可以查阅[PaddleX模型列表(CPU/GPU)](../../../support_list/models_list.md))
 * 指定模式为模型训练:`-o Global.mode=train`
 * 指定模式为模型训练:`-o Global.mode=train`
 * 指定训练数据集路径:`-o Global.dataset_dir`
 * 指定训练数据集路径:`-o Global.dataset_dir`
-其他相关参数均可通过修改`.yaml`配置文件中的`Global`和`Train`下的字段来进行设置,也可以通过在命令行中追加参数来进行调整。如指定前 2 卡 gpu 训练:`-o Global.device=gpu:0,1`;设置训练轮次数为 10:`-o Train.epochs_iters=10`。更多可修改的参数及其详细解释,可以查阅模型对应任务模块的配置文件说明[PaddleX通用模型配置文件参数说明](../../instructions/config_parameters_common.md)。
+* 其他相关参数均可通过修改`.yaml`配置文件中的`Global`和`Train`下的字段来进行设置,也可以通过在命令行中追加参数来进行调整。如指定前 2 卡 gpu 训练:`-o Global.device=gpu:0,1`;设置训练轮次数为 10:`-o Train.epochs_iters=10`。更多可修改的参数及其详细解释,可以查阅模型对应任务模块的配置文件说明[PaddleX通用模型配置文件参数说明](../../instructions/config_parameters_common.md)
+* 新特性:Paddle 3.0 版本支持了 CINN 神经网络编译器,在使用 GPU 设备训练时,不同模型有不同程度的训练加速效果。在 PaddleX 中训练模型时,可通过指定参数 `-o Train.dy2st=True` 开启。
 
 
 <details><summary>👉 <b>更多说明(点击展开)</b></summary>
 <details><summary>👉 <b>更多说明(点击展开)</b></summary>
 <ul>
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+ 2 - 1
docs/module_usage/tutorials/cv_modules/mainbody_detection.en.md

@@ -415,7 +415,8 @@ The steps required are:
 * Specify the `.yaml` configuration file path for the model (here it is `PP-ShiTuV2_det.yaml`,When training other models, you need to specify the corresponding configuration files. The relationship between the model and configuration files can be found in the [PaddleX Model List (CPU/GPU)](../../../support_list/models_list.en.md))
 * Specify the `.yaml` configuration file path for the model (here it is `PP-ShiTuV2_det.yaml`,When training other models, you need to specify the corresponding configuration files. The relationship between the model and configuration files can be found in the [PaddleX Model List (CPU/GPU)](../../../support_list/models_list.en.md))
 * Specify the mode as model training: `-o Global.mode=train`
 * Specify the mode as model training: `-o Global.mode=train`
 * Specify the training dataset path: `-o Global.dataset_dir`
 * Specify the training dataset path: `-o Global.dataset_dir`
-Other related parameters can be set by modifying the `Global` and `Train` fields in the `.yaml` configuration file, or adjusted by appending parameters in the command line. For example, to specify training on the first two GPUs: `-o Global.device=gpu:0,1`; to set the number of training epochs to 10: `-o Train.epochs_iters=10`. For more modifiable parameters and their detailed explanations, refer to the [PaddleX Common Configuration Parameters for Model Tasks](../../instructions/config_parameters_common.en.md).
+* Other related parameters can be set by modifying the `Global` and `Train` fields in the `.yaml` configuration file, or adjusted by appending parameters in the command line. For example, to specify training on the first two GPUs: `-o Global.device=gpu:0,1`; to set the number of training epochs to 10: `-o Train.epochs_iters=10`. For more modifiable parameters and their detailed explanations, refer to the [PaddleX Common Configuration Parameters for Model Tasks](../../instructions/config_parameters_common.en.md).
+* New Feature: Paddle 3.0 support CINN (Compiler Infrastructure for Neural Networks) to accelerate training speed when using GPU device. Please specify `-o Train.dy2st=True` to enable it.
 
 
 <details><summary>👉 <b>More Details (Click to Expand)</b></summary>
 <details><summary>👉 <b>More Details (Click to Expand)</b></summary>
 <ul>
 <ul>

+ 2 - 1
docs/module_usage/tutorials/cv_modules/mainbody_detection.md

@@ -410,7 +410,8 @@ python main.py -c paddlex/configs/modules/mainbody_detection/PP-ShiTuV2_det.yaml
 * 指定模型的`.yaml` 配置文件路径(此处为`PP-ShiTuV2_det.yaml`,训练其他模型时,需要的指定相应的配置文件,模型和配置的文件的对应关系,可以查阅[PaddleX模型列表(CPU/GPU)](../../../support_list/models_list.md))
 * 指定模型的`.yaml` 配置文件路径(此处为`PP-ShiTuV2_det.yaml`,训练其他模型时,需要的指定相应的配置文件,模型和配置的文件的对应关系,可以查阅[PaddleX模型列表(CPU/GPU)](../../../support_list/models_list.md))
 * 指定模式为模型训练:`-o Global.mode=train`
 * 指定模式为模型训练:`-o Global.mode=train`
 * 指定训练数据集路径:`-o Global.dataset_dir`
 * 指定训练数据集路径:`-o Global.dataset_dir`
-其他相关参数均可通过修改`.yaml`配置文件中的`Global`和`Train`下的字段来进行设置,也可以通过在命令行中追加参数来进行调整。如指定前 2 卡 gpu 训练:`-o Global.device=gpu:0,1`;设置训练轮次数为 10:`-o Train.epochs_iters=10`。更多可修改的参数及其详细解释,可以查阅模型对应任务模块的配置文件说明[PaddleX通用模型配置文件参数说明](../../instructions/config_parameters_common.md)。
+* 其他相关参数均可通过修改`.yaml`配置文件中的`Global`和`Train`下的字段来进行设置,也可以通过在命令行中追加参数来进行调整。如指定前 2 卡 gpu 训练:`-o Global.device=gpu:0,1`;设置训练轮次数为 10:`-o Train.epochs_iters=10`。更多可修改的参数及其详细解释,可以查阅模型对应任务模块的配置文件说明[PaddleX通用模型配置文件参数说明](../../instructions/config_parameters_common.md)
+* 新特性:Paddle 3.0 版本支持了 CINN 神经网络编译器,在使用 GPU 设备训练时,不同模型有不同程度的训练加速效果。在 PaddleX 中训练模型时,可通过指定参数 `-o Train.dy2st=True` 开启。
 
 
 <details><summary>👉 <b>更多说明(点击展开)</b></summary>
 <details><summary>👉 <b>更多说明(点击展开)</b></summary>
 <ul>
 <ul>

+ 3 - 2
docs/module_usage/tutorials/cv_modules/object_detection.en.md

@@ -790,8 +790,9 @@ The following steps are required:
 
 
 * Specify the `.yaml` configuration file path for the model (here it is `PicoDet-S.yaml`,When training other models, you need to specify the corresponding configuration files. The relationship between the model and configuration files can be found in the [PaddleX Model List (CPU/GPU)](../../../support_list/models_list.en.md))
 * Specify the `.yaml` configuration file path for the model (here it is `PicoDet-S.yaml`,When training other models, you need to specify the corresponding configuration files. The relationship between the model and configuration files can be found in the [PaddleX Model List (CPU/GPU)](../../../support_list/models_list.en.md))
 * Set the mode to model training: `-o Global.mode=train`
 * Set the mode to model training: `-o Global.mode=train`
-* Specify the path to the training dataset: `-o Global.dataset_dir`.
-Other related parameters can be set by modifying the `Global` and `Train` fields in the `.yaml` configuration file, or adjusted by appending parameters in the command line. For example, to specify training on the first two GPUs: `-o Global.device=gpu:0,1`; to set the number of training epochs to 10: `-o Train.epochs_iters=10`. For more modifiable parameters and their detailed explanations, refer to the configuration file instructions for the corresponding task module of the model [PaddleX Common Configuration File Parameters](../../instructions/config_parameters_common.en.md).
+* Specify the path to the training dataset: `-o Global.dataset_dir`
+* Other related parameters can be set by modifying the `Global` and `Train` fields in the `.yaml` configuration file, or adjusted by appending parameters in the command line. For example, to specify training on the first two GPUs: `-o Global.device=gpu:0,1`; to set the number of training epochs to 10: `-o Train.epochs_iters=10`. For more modifiable parameters and their detailed explanations, refer to the configuration file instructions for the corresponding task module of the model [PaddleX Common Configuration File Parameters](../../instructions/config_parameters_common.en.md).
+* New Feature: Paddle 3.0 support CINN (Compiler Infrastructure for Neural Networks) to accelerate training speed when using GPU device. Please specify `-o Train.dy2st=True` to enable it.
 
 
 <details><summary>👉 <b>More Details (Click to Expand)</b></summary>
 <details><summary>👉 <b>More Details (Click to Expand)</b></summary>
 <ul>
 <ul>

+ 2 - 1
docs/module_usage/tutorials/cv_modules/object_detection.md

@@ -809,7 +809,8 @@ python main.py -c paddlex/configs/modules/object_detection/PicoDet-S.yaml \
 * 指定模型的`.yaml` 配置文件路径(此处为`PicoDet-S.yaml`,训练其他模型时,需要的指定相应的配置文件,模型和配置的文件的对应关系,可以查阅[PaddleX模型列表(CPU/GPU)](../../../support_list/models_list.md))
 * 指定模型的`.yaml` 配置文件路径(此处为`PicoDet-S.yaml`,训练其他模型时,需要的指定相应的配置文件,模型和配置的文件的对应关系,可以查阅[PaddleX模型列表(CPU/GPU)](../../../support_list/models_list.md))
 * 指定模式为模型训练:`-o Global.mode=train`
 * 指定模式为模型训练:`-o Global.mode=train`
 * 指定训练数据集路径:`-o Global.dataset_dir`
 * 指定训练数据集路径:`-o Global.dataset_dir`
-其他相关参数均可通过修改`.yaml`配置文件中的`Global`和`Train`下的字段来进行设置,也可以通过在命令行中追加参数来进行调整。如指定前 2 卡 gpu 训练:`-o Global.device=gpu:0,1`;设置训练轮次数为 10:`-o Train.epochs_iters=10`。更多可修改的参数及其详细解释,可以查阅模型对应任务模块的配置文件说明[PaddleX通用模型配置文件参数说明](../../instructions/config_parameters_common.md)。
+* 其他相关参数均可通过修改`.yaml`配置文件中的`Global`和`Train`下的字段来进行设置,也可以通过在命令行中追加参数来进行调整。如指定前 2 卡 gpu 训练:`-o Global.device=gpu:0,1`;设置训练轮次数为 10:`-o Train.epochs_iters=10`。更多可修改的参数及其详细解释,可以查阅模型对应任务模块的配置文件说明[PaddleX通用模型配置文件参数说明](../../instructions/config_parameters_common.md)
+* 新特性:Paddle 3.0 版本支持了 CINN 神经网络编译器,在使用 GPU 设备训练时,不同模型有不同程度的训练加速效果。在 PaddleX 中训练模型时,可通过指定参数 `-o Train.dy2st=True` 开启。
 
 
 <details><summary>👉 <b>更多说明(点击展开)</b></summary>
 <details><summary>👉 <b>更多说明(点击展开)</b></summary>
 <ul>
 <ul>

+ 2 - 1
docs/module_usage/tutorials/cv_modules/pedestrian_attribute_recognition.en.md

@@ -480,7 +480,8 @@ Similar to model training, the following steps are required:
 * Specify the path to the model's `.yaml` configuration file (here it is `PP-LCNet_x1_0_pedestrian_attribute.yaml`)
 * Specify the path to the model's `.yaml` configuration file (here it is `PP-LCNet_x1_0_pedestrian_attribute.yaml`)
 * Specify the mode as model evaluation: `-o Global.mode=evaluate`
 * Specify the mode as model evaluation: `-o Global.mode=evaluate`
 * Specify the path to the validation dataset: `-o Global.dataset_dir`
 * Specify the path to the validation dataset: `-o Global.dataset_dir`
-Other related parameters can be set by modifying the `Global` and `Evaluate` fields in the `.yaml` configuration file. For details, refer to [PaddleX Common Model Configuration File Parameter Description](../../instructions/config_parameters_common.en.md).
+* Other related parameters can be set by modifying the `Global` and `Evaluate` fields in the `.yaml` configuration file. For details, refer to [PaddleX Common Model Configuration File Parameter Description](../../instructions/config_parameters_common.en.md).
+* New Feature: Paddle 3.0 support CINN (Compiler Infrastructure for Neural Networks) to accelerate training speed when using GPU device. Please specify `-o Train.dy2st=True` to enable it.
 
 
 <details><summary>👉 <b>More Details (Click to Expand)</b></summary>
 <details><summary>👉 <b>More Details (Click to Expand)</b></summary>
 <p>When evaluating the model, you need to specify the model weights file path. Each configuration file has a default weight save path built-in. If you need to change it, simply set it by appending a command line parameter, such as <code>-o Evaluate.weight_path=./output/best_model/best_model.pdparams</code>.</p>
 <p>When evaluating the model, you need to specify the model weights file path. Each configuration file has a default weight save path built-in. If you need to change it, simply set it by appending a command line parameter, such as <code>-o Evaluate.weight_path=./output/best_model/best_model.pdparams</code>.</p>

+ 2 - 1
docs/module_usage/tutorials/cv_modules/pedestrian_attribute_recognition.md

@@ -448,7 +448,8 @@ python main.py -c paddlex/configs/modules/pedestrian_attribute_recognition/PP-LC
 * 指定模型的`.yaml` 配置文件路径(此处为`PP-LCNet_x1_0_pedestrian_attribute.yaml`,训练其他模型时,需要的指定相应的配置文件,模型和配置的文件的对应关系,可以查阅[PaddleX模型列表(CPU/GPU)](../../../support_list/models_list.md))
 * 指定模型的`.yaml` 配置文件路径(此处为`PP-LCNet_x1_0_pedestrian_attribute.yaml`,训练其他模型时,需要的指定相应的配置文件,模型和配置的文件的对应关系,可以查阅[PaddleX模型列表(CPU/GPU)](../../../support_list/models_list.md))
 * 指定模式为模型训练:`-o Global.mode=train`
 * 指定模式为模型训练:`-o Global.mode=train`
 * 指定训练数据集路径:`-o Global.dataset_dir`
 * 指定训练数据集路径:`-o Global.dataset_dir`
-其他相关参数均可通过修改`.yaml`配置文件中的`Global`和`Train`下的字段来进行设置,也可以通过在命令行中追加参数来进行调整。如指定前 2 卡 gpu 训练:`-o Global.device=gpu:0,1`;设置训练轮次数为 10:`-o Train.epochs_iters=10`。更多可修改的参数及其详细解释,可以查阅模型对应任务模块的配置文件说明[PaddleX通用模型配置文件参数说明](../../instructions/config_parameters_common.md)。
+* 其他相关参数均可通过修改`.yaml`配置文件中的`Global`和`Train`下的字段来进行设置,也可以通过在命令行中追加参数来进行调整。如指定前 2 卡 gpu 训练:`-o Global.device=gpu:0,1`;设置训练轮次数为 10:`-o Train.epochs_iters=10`。更多可修改的参数及其详细解释,可以查阅模型对应任务模块的配置文件说明[PaddleX通用模型配置文件参数说明](../../instructions/config_parameters_common.md)
+* 新特性:Paddle 3.0 版本支持了 CINN 神经网络编译器,在使用 GPU 设备训练时,不同模型有不同程度的训练加速效果。在 PaddleX 中训练模型时,可通过指定参数 `-o Train.dy2st=True` 开启。
 
 
 <details><summary>👉 <b>更多说明(点击展开)</b></summary>
 <details><summary>👉 <b>更多说明(点击展开)</b></summary>
 <ul>
 <ul>

+ 2 - 1
docs/module_usage/tutorials/cv_modules/rotated_object_detection.en.md

@@ -451,7 +451,8 @@ The following steps are required:
 * Specify the path of the model's `.yaml` configuration file (here it is `PP-YOLOE-R-L.yaml`. When training other models, you need to specify the corresponding configuration file. The correspondence between models and configuration files can be found in [PaddleX Model List (CPU/GPU))](../../../support_list/models_list.en.md))
 * Specify the path of the model's `.yaml` configuration file (here it is `PP-YOLOE-R-L.yaml`. When training other models, you need to specify the corresponding configuration file. The correspondence between models and configuration files can be found in [PaddleX Model List (CPU/GPU))](../../../support_list/models_list.en.md))
 * Specify the mode as model training: `-o Global.mode=train`
 * Specify the mode as model training: `-o Global.mode=train`
 * Specify the training dataset path: `-o Global.dataset_dir`
 * Specify the training dataset path: `-o Global.dataset_dir`
-Other related parameters can be set by modifying the fields under Global and Train in the `.yaml` configuration file, or by adding parameters in the command line. For example, specify the first 2 GPU cards for training: `-o Global.device=gpu:0,1`; set the number of training epochs to 10: `-o Train.epochs_iters=10`. For more modifiable parameters and detailed explanations, please refer to the configuration file instructions for the corresponding task module [PaddleX Common Model Configuration File Parameter Instructions.](../../instructions/config_parameters_common.en.md).
+* Other related parameters can be set by modifying the fields under Global and Train in the `.yaml` configuration file, or by adding parameters in the command line. For example, specify the first 2 GPU cards for training: `-o Global.device=gpu:0,1`; set the number of training epochs to 10: `-o Train.epochs_iters=10`. For more modifiable parameters and detailed explanations, please refer to the configuration file instructions for the corresponding task module [PaddleX Common Model Configuration File Parameter Instructions.](../../instructions/config_parameters_common.en.md).
+* New Feature: Paddle 3.0 support CINN (Compiler Infrastructure for Neural Networks) to accelerate training speed when using GPU device. Please specify `-o Train.dy2st=True` to enable it.
 
 
 <details><summary>👉 <b>More Explanations (Click to Expand)</b></summary>
 <details><summary>👉 <b>More Explanations (Click to Expand)</b></summary>
 
 

+ 2 - 1
docs/module_usage/tutorials/cv_modules/rotated_object_detection.md

@@ -446,7 +446,8 @@ python main.py -c paddlex/configs/modules/rotated_object_detection/PP-YOLOE-R-L.
 * 指定模型的`.yaml` 配置文件路径(此处为`PP-YOLOE-R-L.yaml`,训练其他模型时,需要的指定相应的配置文件,模型和配置的文件的对应关系,可以查阅[PaddleX模型列表(CPU/GPU)](../../../support_list/models_list.md))
 * 指定模型的`.yaml` 配置文件路径(此处为`PP-YOLOE-R-L.yaml`,训练其他模型时,需要的指定相应的配置文件,模型和配置的文件的对应关系,可以查阅[PaddleX模型列表(CPU/GPU)](../../../support_list/models_list.md))
 * 指定模式为模型训练:`-o Global.mode=train`
 * 指定模式为模型训练:`-o Global.mode=train`
 * 指定训练数据集路径:`-o Global.dataset_dir`
 * 指定训练数据集路径:`-o Global.dataset_dir`
-其他相关参数均可通过修改`.yaml`配置文件中的`Global`和`Train`下的字段来进行设置,也可以通过在命令行中追加参数来进行调整。如指定前 2 卡 gpu 训练:`-o Global.device=gpu:0,1`;设置训练轮次数为 10:`-o Train.epochs_iters=10`。更多可修改的参数及其详细解释,可以查阅模型对应任务模块的配置文件说明[PaddleX通用模型配置文件参数说明](../../instructions/config_parameters_common.md)。
+* 其他相关参数均可通过修改`.yaml`配置文件中的`Global`和`Train`下的字段来进行设置,也可以通过在命令行中追加参数来进行调整。如指定前 2 卡 gpu 训练:`-o Global.device=gpu:0,1`;设置训练轮次数为 10:`-o Train.epochs_iters=10`。更多可修改的参数及其详细解释,可以查阅模型对应任务模块的配置文件说明[PaddleX通用模型配置文件参数说明](../../instructions/config_parameters_common.md)
+* 新特性:Paddle 3.0 版本支持了 CINN 神经网络编译器,在使用 GPU 设备训练时,不同模型有不同程度的训练加速效果。在 PaddleX 中训练模型时,可通过指定参数 `-o Train.dy2st=True` 开启。
 
 
 <details><summary>👉 <b>更多说明(点击展开)</b></summary>
 <details><summary>👉 <b>更多说明(点击展开)</b></summary>
 
 

+ 2 - 2
docs/module_usage/tutorials/cv_modules/semantic_segmentation.en.md

@@ -624,8 +624,8 @@ You need to follow these steps:
 * Specify the `.yaml` configuration file path for the model (here it's `PP-LiteSeg-T.yaml`,When training other models, you need to specify the corresponding configuration files. The relationship between the model and configuration files can be found in the [PaddleX Model List (CPU/GPU)](../../../support_list/models_list.en.md)).
 * Specify the `.yaml` configuration file path for the model (here it's `PP-LiteSeg-T.yaml`,When training other models, you need to specify the corresponding configuration files. The relationship between the model and configuration files can be found in the [PaddleX Model List (CPU/GPU)](../../../support_list/models_list.en.md)).
 * Set the mode to model training: `-o Global.mode=train`
 * Set the mode to model training: `-o Global.mode=train`
 * Specify the training dataset path: `-o Global.dataset_dir`
 * Specify the training dataset path: `-o Global.dataset_dir`
-
-Other related parameters can be set by modifying the `Global` and `Train` fields in the `.yaml` configuration file, or adjusted by appending parameters in the command line. For example, to train using the first two GPUs: `-o Global.device=gpu:0,1`; to set the number of training epochs to 10: `-o Train.epochs_iters=10`. For more modifiable parameters and their detailed explanations, refer to the [PaddleX Common Configuration Parameters Documentation](../../instructions/config_parameters_common.en.md).
+* Other related parameters can be set by modifying the `Global` and `Train` fields in the `.yaml` configuration file, or adjusted by appending parameters in the command line. For example, to train using the first two GPUs: `-o Global.device=gpu:0,1`; to set the number of training epochs to 10: `-o Train.epochs_iters=10`. For more modifiable parameters and their detailed explanations, refer to the [PaddleX Common Configuration Parameters Documentation](../../instructions/config_parameters_common.en.md).
+* New Feature: Paddle 3.0 support CINN (Compiler Infrastructure for Neural Networks) to accelerate training speed when using GPU device. Please specify `-o Train.dy2st=True` to enable it.
 
 
 <details><summary>👉 <b>More Details (Click to Expand)</b></summary>
 <details><summary>👉 <b>More Details (Click to Expand)</b></summary>
 <ul>
 <ul>

+ 2 - 1
docs/module_usage/tutorials/cv_modules/semantic_segmentation.md

@@ -616,7 +616,8 @@ python main.py -c paddlex/configs/modules/semantic_segmentation/PP-LiteSeg-T.yam
 * 指定模型的.yaml 配置文件路径(此处为 `PP-LiteSeg-T.yam`,训练其他模型时,需要的指定相应的配置文件,模型和配置的文件的对应关系,可以查阅[PaddleX模型列表(CPU/GPU)](../../../support_list/models_list.md))
 * 指定模型的.yaml 配置文件路径(此处为 `PP-LiteSeg-T.yam`,训练其他模型时,需要的指定相应的配置文件,模型和配置的文件的对应关系,可以查阅[PaddleX模型列表(CPU/GPU)](../../../support_list/models_list.md))
 * 指定模式为模型训练:`-o Global.mode=train`
 * 指定模式为模型训练:`-o Global.mode=train`
 * 指定训练数据集路径:`-o Global.dataset_dir`
 * 指定训练数据集路径:`-o Global.dataset_dir`
-其他相关参数均可通过修改`.yaml`配置文件中的`Global`和`Train`下的字段来进行设置,也可以通过在命令行中追加参数来进行调整。如指定前 2 卡 gpu 训练:`-o Global.device=gpu:0,1`;设置训练轮次数为 10:`-o Train.epochs_iters=10`。更多可修改的参数及其详细解释,可以查阅模型对应任务模块的配置文件说明[PaddleX通用模型配置文件参数说明](../../instructions/config_parameters_common.md)。
+* 其他相关参数均可通过修改`.yaml`配置文件中的`Global`和`Train`下的字段来进行设置,也可以通过在命令行中追加参数来进行调整。如指定前 2 卡 gpu 训练:`-o Global.device=gpu:0,1`;设置训练轮次数为 10:`-o Train.epochs_iters=10`。更多可修改的参数及其详细解释,可以查阅模型对应任务模块的配置文件说明[PaddleX通用模型配置文件参数说明](../../instructions/config_parameters_common.md)
+* 新特性:Paddle 3.0 版本支持了 CINN 神经网络编译器,在使用 GPU 设备训练时,不同模型有不同程度的训练加速效果。在 PaddleX 中训练模型时,可通过指定参数 `-o Train.dy2st=True` 开启。
 
 
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 <details><summary>👉 <b>更多说明(点击展开)</b></summary>
 <ul>
 <ul>

+ 2 - 1
docs/module_usage/tutorials/cv_modules/small_object_detection.en.md

@@ -463,7 +463,8 @@ The steps required are:
 * Specify the `.yaml` configuration file path for the model (here it is `PP-YOLOE_plus_SOD-S.yaml`,When training other models, you need to specify the corresponding configuration files. The relationship between the model and configuration files can be found in the [PaddleX Model List (CPU/GPU)](../../../support_list/models_list.en.md))
 * Specify the `.yaml` configuration file path for the model (here it is `PP-YOLOE_plus_SOD-S.yaml`,When training other models, you need to specify the corresponding configuration files. The relationship between the model and configuration files can be found in the [PaddleX Model List (CPU/GPU)](../../../support_list/models_list.en.md))
 * Specify the mode as model training: `-o Global.mode=train`
 * Specify the mode as model training: `-o Global.mode=train`
 * Specify the training dataset path: `-o Global.dataset_dir`
 * Specify the training dataset path: `-o Global.dataset_dir`
-Other related parameters can be set by modifying the `Global` and `Train` fields in the `.yaml` configuration file, or adjusted by appending parameters in the command line. For example, to specify training on the first two GPUs: `-o Global.device=gpu:0,1`; to set the number of training epochs to 10: `-o Train.epochs_iters=10`. For more modifiable parameters and their detailed explanations, refer to the [PaddleX Common Configuration Parameters for Model Tasks](../../instructions/config_parameters_common.en.md).
+* Other related parameters can be set by modifying the `Global` and `Train` fields in the `.yaml` configuration file, or adjusted by appending parameters in the command line. For example, to specify training on the first two GPUs: `-o Global.device=gpu:0,1`; to set the number of training epochs to 10: `-o Train.epochs_iters=10`. For more modifiable parameters and their detailed explanations, refer to the [PaddleX Common Configuration Parameters for Model Tasks](../../instructions/config_parameters_common.en.md).
+* New Feature: Paddle 3.0 support CINN (Compiler Infrastructure for Neural Networks) to accelerate training speed when using GPU device. Please specify `-o Train.dy2st=True` to enable it.
 
 
 <details><summary>👉 <b>More Details (Click to Expand)</b></summary>
 <details><summary>👉 <b>More Details (Click to Expand)</b></summary>
 <ul>
 <ul>

+ 2 - 1
docs/module_usage/tutorials/cv_modules/small_object_detection.md

@@ -457,7 +457,8 @@ python main.py -c paddlex/configs/modules/small_object_detection/PP-YOLOE_plus_S
 * 指定模型的`.yaml` 配置文件路径(此处为`PP-YOLOE_plus_SOD-S.yaml`,训练其他模型时,需要的指定相应的配置文件,模型和配置的文件的对应关系,可以查阅[PaddleX模型列表(CPU/GPU)](../../../support_list/models_list.md))
 * 指定模型的`.yaml` 配置文件路径(此处为`PP-YOLOE_plus_SOD-S.yaml`,训练其他模型时,需要的指定相应的配置文件,模型和配置的文件的对应关系,可以查阅[PaddleX模型列表(CPU/GPU)](../../../support_list/models_list.md))
 * 指定模式为模型训练:`-o Global.mode=train`
 * 指定模式为模型训练:`-o Global.mode=train`
 * 指定训练数据集路径:`-o Global.dataset_dir`
 * 指定训练数据集路径:`-o Global.dataset_dir`
-其他相关参数均可通过修改`.yaml`配置文件中的`Global`和`Train`下的字段来进行设置,也可以通过在命令行中追加参数来进行调整。如指定前 2 卡 gpu 训练:`-o Global.device=gpu:0,1`;设置训练轮次数为 10:`-o Train.epochs_iters=10`。更多可修改的参数及其详细解释,可以查阅模型对应任务模块的配置文件说明[PaddleX通用模型配置文件参数说明](../../instructions/config_parameters_common.md)。
+* 其他相关参数均可通过修改`.yaml`配置文件中的`Global`和`Train`下的字段来进行设置,也可以通过在命令行中追加参数来进行调整。如指定前 2 卡 gpu 训练:`-o Global.device=gpu:0,1`;设置训练轮次数为 10:`-o Train.epochs_iters=10`。更多可修改的参数及其详细解释,可以查阅模型对应任务模块的配置文件说明[PaddleX通用模型配置文件参数说明](../../instructions/config_parameters_common.md)
+* 新特性:Paddle 3.0 版本支持了 CINN 神经网络编译器,在使用 GPU 设备训练时,不同模型有不同程度的训练加速效果。在 PaddleX 中训练模型时,可通过指定参数 `-o Train.dy2st=True` 开启。
 
 
 <details><summary>👉 <b>更多说明(点击展开)</b></summary>
 <details><summary>👉 <b>更多说明(点击展开)</b></summary>
 <ul>
 <ul>

+ 2 - 1
docs/module_usage/tutorials/cv_modules/vehicle_attribute_recognition.en.md

@@ -431,7 +431,8 @@ The steps required are:
 * Specify the path to the model's `.yaml` configuration file (here it's `PP-LCNet_x1_0_vehicle_attribute.yaml`,When training other models, you need to specify the corresponding configuration files. The relationship between the model and configuration files can be found in the [PaddleX Model List (CPU/GPU)](../../../support_list/models_list.en.md))
 * Specify the path to the model's `.yaml` configuration file (here it's `PP-LCNet_x1_0_vehicle_attribute.yaml`,When training other models, you need to specify the corresponding configuration files. The relationship between the model and configuration files can be found in the [PaddleX Model List (CPU/GPU)](../../../support_list/models_list.en.md))
 * Set the mode to model training: `-o Global.mode=train`
 * Set the mode to model training: `-o Global.mode=train`
 * Specify the path to the training dataset: `-o Global.dataset_dir`
 * Specify the path to the training dataset: `-o Global.dataset_dir`
-Other related parameters can be set by modifying the `Global` and `Train` fields in the `.yaml` configuration file, or adjusted by appending parameters in the command line. For example, to specify training on the first two GPUs: `-o Global.device=gpu:0,1`; to set the number of training epochs to 10: `-o Train.epochs_iters=10`. For more modifiable parameters and their detailed explanations, refer to the [PaddleX Common Configuration Parameters](../../instructions/config_parameters_common.en.md).
+* Other related parameters can be set by modifying the `Global` and `Train` fields in the `.yaml` configuration file, or adjusted by appending parameters in the command line. For example, to specify training on the first two GPUs: `-o Global.device=gpu:0,1`; to set the number of training epochs to 10: `-o Train.epochs_iters=10`. For more modifiable parameters and their detailed explanations, refer to the [PaddleX Common Configuration Parameters](../../instructions/config_parameters_common.en.md).
+* New Feature: Paddle 3.0 support CINN (Compiler Infrastructure for Neural Networks) to accelerate training speed when using GPU device. Please specify `-o Train.dy2st=True` to enable it.
 
 
 <details><summary>👉 <b>More Details (Click to Expand)</b></summary>
 <details><summary>👉 <b>More Details (Click to Expand)</b></summary>
 <ul>
 <ul>

+ 2 - 1
docs/module_usage/tutorials/cv_modules/vehicle_attribute_recognition.md

@@ -428,7 +428,8 @@ python main.py -c paddlex/configs/modules/vehicle_attribute_recognition/PP-LCNet
 * 指定模型的`.yaml` 配置文件路径(此处为`PP-LCNet_x1_0_vehicle_attribute.yaml`,训练其他模型时,需要的指定相应的配置文件,模型和配置的文件的对应关系,可以查阅[PaddleX模型列表(CPU/GPU)](../../../support_list/models_list.md))
 * 指定模型的`.yaml` 配置文件路径(此处为`PP-LCNet_x1_0_vehicle_attribute.yaml`,训练其他模型时,需要的指定相应的配置文件,模型和配置的文件的对应关系,可以查阅[PaddleX模型列表(CPU/GPU)](../../../support_list/models_list.md))
 * 指定模式为模型训练:`-o Global.mode=train`
 * 指定模式为模型训练:`-o Global.mode=train`
 * 指定训练数据集路径:`-o Global.dataset_dir`
 * 指定训练数据集路径:`-o Global.dataset_dir`
-其他相关参数均可通过修改`.yaml`配置文件中的`Global`和`Train`下的字段来进行设置,也可以通过在命令行中追加参数来进行调整。如指定前 2 卡 gpu 训练:`-o Global.device=gpu:0,1`;设置训练轮次数为 10:`-o Train.epochs_iters=10`。更多可修改的参数及其详细解释,可以查阅模型对应任务模块的配置文件说明[PaddleX通用模型配置文件参数说明](../../instructions/config_parameters_common.md)。
+* 其他相关参数均可通过修改`.yaml`配置文件中的`Global`和`Train`下的字段来进行设置,也可以通过在命令行中追加参数来进行调整。如指定前 2 卡 gpu 训练:`-o Global.device=gpu:0,1`;设置训练轮次数为 10:`-o Train.epochs_iters=10`。更多可修改的参数及其详细解释,可以查阅模型对应任务模块的配置文件说明[PaddleX通用模型配置文件参数说明](../../instructions/config_parameters_common.md)
+* 新特性:Paddle 3.0 版本支持了 CINN 神经网络编译器,在使用 GPU 设备训练时,不同模型有不同程度的训练加速效果。在 PaddleX 中训练模型时,可通过指定参数 `-o Train.dy2st=True` 开启。
 
 
 <details><summary>👉 <b>更多说明(点击展开)</b></summary>
 <details><summary>👉 <b>更多说明(点击展开)</b></summary>
 <ul>
 <ul>

+ 2 - 1
docs/module_usage/tutorials/cv_modules/vehicle_detection.en.md

@@ -419,7 +419,8 @@ The steps required are:
 * Specify the `.yaml` configuration file path for the model (here it is `PP-YOLOE-S_vehicle.yaml`,When training other models, you need to specify the corresponding configuration files. The relationship between the model and configuration files can be found in the [PaddleX Model List (CPU/GPU)](../../../support_list/models_list.en.md))
 * Specify the `.yaml` configuration file path for the model (here it is `PP-YOLOE-S_vehicle.yaml`,When training other models, you need to specify the corresponding configuration files. The relationship between the model and configuration files can be found in the [PaddleX Model List (CPU/GPU)](../../../support_list/models_list.en.md))
 * Specify the mode as model training: `-o Global.mode=train`
 * Specify the mode as model training: `-o Global.mode=train`
 * Specify the training dataset path: `-o Global.dataset_dir`
 * Specify the training dataset path: `-o Global.dataset_dir`
-Other related parameters can be set by modifying the `Global` and `Train` fields in the `.yaml` configuration file, or adjusted by appending parameters in the command line. For example, to specify training on the first two GPUs: `-o Global.device=gpu:0,1`; to set the number of training epochs to 10: `-o Train.epochs_iters=10`. For more modifiable parameters and their detailed explanations, refer to the [PaddleX Common Configuration Parameters for Model Tasks](../../instructions/config_parameters_common.en.md).
+* Other related parameters can be set by modifying the `Global` and `Train` fields in the `.yaml` configuration file, or adjusted by appending parameters in the command line. For example, to specify training on the first two GPUs: `-o Global.device=gpu:0,1`; to set the number of training epochs to 10: `-o Train.epochs_iters=10`. For more modifiable parameters and their detailed explanations, refer to the [PaddleX Common Configuration Parameters for Model Tasks](../../instructions/config_parameters_common.en.md).
+* New Feature: Paddle 3.0 support CINN (Compiler Infrastructure for Neural Networks) to accelerate training speed when using GPU device. Please specify `-o Train.dy2st=True` to enable it.
 
 
 <details><summary>👉 <b>More Details (Click to Expand)</b></summary>
 <details><summary>👉 <b>More Details (Click to Expand)</b></summary>
 <ul>
 <ul>

+ 2 - 1
docs/module_usage/tutorials/cv_modules/vehicle_detection.md

@@ -416,7 +416,8 @@ python main.py -c paddlex/configs/modules/vehicle_detection/PP-YOLOE-S_vehicle.y
 * 指定模型的`.yaml` 配置文件路径(此处为`PP-YOLOE-S_vehicle.yaml`,训练其他模型时,需要的指定相应的配置文件,模型和配置的文件的对应关系,可以查阅[PaddleX模型列表(CPU/GPU)](../../../support_list/models_list.md))
 * 指定模型的`.yaml` 配置文件路径(此处为`PP-YOLOE-S_vehicle.yaml`,训练其他模型时,需要的指定相应的配置文件,模型和配置的文件的对应关系,可以查阅[PaddleX模型列表(CPU/GPU)](../../../support_list/models_list.md))
 * 指定模式为模型训练:`-o Global.mode=train`
 * 指定模式为模型训练:`-o Global.mode=train`
 * 指定训练数据集路径:`-o Global.dataset_dir`
 * 指定训练数据集路径:`-o Global.dataset_dir`
-其他相关参数均可通过修改`.yaml`配置文件中的`Global`和`Train`下的字段来进行设置,也可以通过在命令行中追加参数来进行调整。如指定前 2 卡 gpu 训练:`-o Global.device=gpu:0,1`;设置训练轮次数为 10:`-o Train.epochs_iters=10`。更多可修改的参数及其详细解释,可以查阅模型对应任务模块的配置文件说明[PaddleX通用模型配置文件参数说明](../../instructions/config_parameters_common.md)。
+* 其他相关参数均可通过修改`.yaml`配置文件中的`Global`和`Train`下的字段来进行设置,也可以通过在命令行中追加参数来进行调整。如指定前 2 卡 gpu 训练:`-o Global.device=gpu:0,1`;设置训练轮次数为 10:`-o Train.epochs_iters=10`。更多可修改的参数及其详细解释,可以查阅模型对应任务模块的配置文件说明[PaddleX通用模型配置文件参数说明](../../instructions/config_parameters_common.md)
+* 新特性:Paddle 3.0 版本支持了 CINN 神经网络编译器,在使用 GPU 设备训练时,不同模型有不同程度的训练加速效果。在 PaddleX 中训练模型时,可通过指定参数 `-o Train.dy2st=True` 开启。
 
 
 <details><summary>👉 <b>更多说明(点击展开)</b></summary>
 <details><summary>👉 <b>更多说明(点击展开)</b></summary>
 <ul>
 <ul>

+ 2 - 4
docs/module_usage/tutorials/ocr_modules/doc_img_orientation_classification.en.md

@@ -475,12 +475,10 @@ python main.py -c paddlex/configs/modules/doc_text_orientation/PP-LCNet_x1_0_doc
 Similar to model training and evaluation, the following steps are required:
 Similar to model training and evaluation, the following steps are required:
 
 
 * Specify the `.yaml` configuration file path of the model (here it's `PP-LCNet_x1_0_doc_ori.yaml`)
 * Specify the `.yaml` configuration file path of the model (here it's `PP-LCNet_x1_0_doc_ori.yaml`)
-
 * Set the mode to model inference prediction: `-o Global.mode=predict`
 * Set the mode to model inference prediction: `-o Global.mode=predict`
-
 * Specify the model weights path: -o Predict.model_dir="./output/best_accuracy/inference"
 * Specify the model weights path: -o Predict.model_dir="./output/best_accuracy/inference"
-
-Specify the input data path: `-o Predict.input="..."` Other related parameters can be set by modifying the fields under Global and Predict in the `.yaml` configuration file. For details, refer to PaddleX Common Model Configuration File Parameter Description.
+* Specify the input data path: `-o Predict.input="..."` Other related parameters can be set by modifying the fields under Global and Predict in the `.yaml` configuration file. For details, refer to PaddleX Common Model Configuration File Parameter Description.
+* New Feature: Paddle 3.0 support CINN (Compiler Infrastructure for Neural Networks) to accelerate training speed when using GPU device. Please specify `-o Train.dy2st=True` to enable it.
 
 
 Alternatively, you can use the PaddleX wheel package for inference, easily integrating the model into your own projects.
 Alternatively, you can use the PaddleX wheel package for inference, easily integrating the model into your own projects.
 
 

+ 2 - 1
docs/module_usage/tutorials/ocr_modules/doc_img_orientation_classification.md

@@ -405,7 +405,8 @@ python main.py -c paddlex/configs/modules/doc_text_orientation/PP-LCNet_x1_0_doc
 * 指定模型的`.yaml` 配置文件路径(此处为`PP-LCNet_x1_0_doc_ori.yaml`,训练其他模型时,需要的指定相应的配置文件,模型和配置的文件的对应关系,可以查阅[PaddleX模型列表(CPU/GPU)](../../../support_list/models_list.md))
 * 指定模型的`.yaml` 配置文件路径(此处为`PP-LCNet_x1_0_doc_ori.yaml`,训练其他模型时,需要的指定相应的配置文件,模型和配置的文件的对应关系,可以查阅[PaddleX模型列表(CPU/GPU)](../../../support_list/models_list.md))
 * 指定模式为模型训练:`-o Global.mode=train`
 * 指定模式为模型训练:`-o Global.mode=train`
 * 指定训练数据集路径:`-o Global.dataset_dir`
 * 指定训练数据集路径:`-o Global.dataset_dir`
-其他相关参数均可通过修改`.yaml`配置文件中的`Global`和`Train`下的字段来进行设置,也可以通过在命令行中追加参数来进行调整。如指定前 2 卡 gpu 训练:`-o Global.device=gpu:0,1`;设置训练轮次数为 10:`-o Train.epochs_iters=10`。更多可修改的参数及其详细解释,可以查阅模型对应任务模块的配置文件说明[PaddleX通用模型配置文件参数说明](../../instructions/config_parameters_common.md)。
+* 其他相关参数均可通过修改`.yaml`配置文件中的`Global`和`Train`下的字段来进行设置,也可以通过在命令行中追加参数来进行调整。如指定前 2 卡 gpu 训练:`-o Global.device=gpu:0,1`;设置训练轮次数为 10:`-o Train.epochs_iters=10`。更多可修改的参数及其详细解释,可以查阅模型对应任务模块的配置文件说明[PaddleX通用模型配置文件参数说明](../../instructions/config_parameters_common.md)。
+* 新特性:Paddle 3.0 版本支持了 CINN 神经网络编译器,在使用 GPU 设备训练时,不同模型有不同程度的训练加速效果。在 PaddleX 中训练模型时,可通过指定参数 `-o Train.dy2st=True` 开启。
 
 
 <details><summary>👉 <b>更多说明(点击展开)</b></summary>
 <details><summary>👉 <b>更多说明(点击展开)</b></summary>
 
 

+ 2 - 1
docs/module_usage/tutorials/ocr_modules/formula_recognition.en.md

@@ -455,9 +455,10 @@ The following steps are required:
 * Specify the `.yaml` configuration file path for the model (here it is `PP-FormulaNet-S.yaml`,When training other models, you need to specify the corresponding configuration files. The relationship between the model and configuration files can be found in the [PaddleX Model List (CPU/GPU)](../../../support_list/models_list.en.md))
 * Specify the `.yaml` configuration file path for the model (here it is `PP-FormulaNet-S.yaml`,When training other models, you need to specify the corresponding configuration files. The relationship between the model and configuration files can be found in the [PaddleX Model List (CPU/GPU)](../../../support_list/models_list.en.md))
 * Set the mode to model training: `-o Global.mode=train`
 * Set the mode to model training: `-o Global.mode=train`
 * Specify the path to the training dataset: `-o Global.dataset_dir`.
 * Specify the path to the training dataset: `-o Global.dataset_dir`.
-Other related parameters can be set by modifying the `Global` and `Train` fields in the `.yaml` configuration file, or adjusted by appending parameters in the command line. For example, to specify training on the first two GPUs: `-o Global.device=gpu:0,1`; to set the number of training epochs to 10: `-o Train.epochs_iters=10`. For more modifiable parameters and their detailed explanations, refer to the configuration file instructions for the corresponding task module of the model [PaddleX Common Configuration File Parameters](../../instructions/config_parameters_common.en.md).
+* Other related parameters can be set by modifying the `Global` and `Train` fields in the `.yaml` configuration file, or adjusted by appending parameters in the command line. For example, to specify training on the first two GPUs: `-o Global.device=gpu:0,1`; to set the number of training epochs to 10: `-o Train.epochs_iters=10`. For more modifiable parameters and their detailed explanations, refer to the configuration file instructions for the corresponding task module of the model [PaddleX Common Configuration File Parameters](../../instructions/config_parameters_common.en.md).
 *  Except for LaTeX_OCR_rec, the formula recognition models only support exporting models in JSON format. Therefore, during training, you need to set the parameter `FLAGS_json_format_model=1`.
 *  Except for LaTeX_OCR_rec, the formula recognition models only support exporting models in JSON format. Therefore, during training, you need to set the parameter `FLAGS_json_format_model=1`.
 *  For the PP-FormulaNet-S, PP-FormulaNet-L, and UniMERNet models, additional Linux packages need to be installed during training. The specific command is as follows:
 *  For the PP-FormulaNet-S, PP-FormulaNet-L, and UniMERNet models, additional Linux packages need to be installed during training. The specific command is as follows:
+* New Feature: Paddle 3.0 support CINN (Compiler Infrastructure for Neural Networks) to accelerate training speed when using GPU device. Please specify `-o Train.dy2st=True` to enable it.
 
 
 ```bash
 ```bash
 sudo apt-get update
 sudo apt-get update

+ 2 - 1
docs/module_usage/tutorials/ocr_modules/formula_recognition.md

@@ -451,7 +451,7 @@ FLAGS_json_format_model=1 python main.py -c paddlex/configs/modules/formula_reco
 * 指定模型的`.yaml` 配置文件路径(此处为`PP-FormulaNet-S.yaml`,训练其他模型时,需要的指定相应的配置文件,模型和配置的文件的对应关系,可以查阅[PaddleX模型列表(CPU/GPU)](../../../support_list/models_list.md))
 * 指定模型的`.yaml` 配置文件路径(此处为`PP-FormulaNet-S.yaml`,训练其他模型时,需要的指定相应的配置文件,模型和配置的文件的对应关系,可以查阅[PaddleX模型列表(CPU/GPU)](../../../support_list/models_list.md))
 * 指定模式为模型训练:`-o Global.mode=train`
 * 指定模式为模型训练:`-o Global.mode=train`
 * 指定训练数据集路径:`-o Global.dataset_dir`
 * 指定训练数据集路径:`-o Global.dataset_dir`
-其他相关参数均可通过修改`.yaml`配置文件中的`Global`和`Train`下的字段来进行设置,也可以通过在命令行中追加参数来进行调整。如指定前 2 卡 gpu 训练:`-o Global.device=gpu:0,1`;设置训练轮次数为 10:`-o Train.epochs_iters=10`。更多可修改的参数及其详细解释,可以查阅模型对应任务模块的配置文件说明[PaddleX通用模型配置文件参数说明](../../instructions/config_parameters_common.md)。
+* 其他相关参数均可通过修改`.yaml`配置文件中的`Global`和`Train`下的字段来进行设置,也可以通过在命令行中追加参数来进行调整。如指定前 2 卡 gpu 训练:`-o Global.device=gpu:0,1`;设置训练轮次数为 10:`-o Train.epochs_iters=10`。更多可修改的参数及其详细解释,可以查阅模型对应任务模块的配置文件说明[PaddleX通用模型配置文件参数说明](../../instructions/config_parameters_common.md)。
 * 除 LaTeX_OCR_rec外, 公式识别模型只支持导出json格式的模型,因此训练时需要设置参数`FLAGS_json_format_model=1`。
 * 除 LaTeX_OCR_rec外, 公式识别模型只支持导出json格式的模型,因此训练时需要设置参数`FLAGS_json_format_model=1`。
 * 对于 PP-FormulaNet-S、PP-FormulaNet-L、UniMERNet 模型,在训练还需要安装额外的Linux包,具体命令如下:
 * 对于 PP-FormulaNet-S、PP-FormulaNet-L、UniMERNet 模型,在训练还需要安装额外的Linux包,具体命令如下:
 ```bash
 ```bash
@@ -459,6 +459,7 @@ sudo apt-get update
 sudo apt-get install libmagickwand-dev
 sudo apt-get install libmagickwand-dev
 python -m pip install Wand
 python -m pip install Wand
 ```
 ```
+* 新特性:Paddle 3.0 版本支持了 CINN 神经网络编译器,在使用 GPU 设备训练时,不同模型有不同程度的训练加速效果。在 PaddleX 中训练模型时,可通过指定参数 `-o Train.dy2st=True` 开启。
 
 
 <details><summary>👉 <b>更多说明(点击展开)</b></summary>
 <details><summary>👉 <b>更多说明(点击展开)</b></summary>
 
 

+ 2 - 2
docs/module_usage/tutorials/ocr_modules/layout_detection.en.md

@@ -607,8 +607,8 @@ The steps required are:
 * Specify the path to the `.yaml` configuration file of the model (here it is `PP-DocLayout-L.yaml`,When training other models, you need to specify the corresponding configuration files. The relationship between the model and configuration files can be found in the [PaddleX Model List (CPU/GPU)](../../../support_list/models_list.en.md))
 * Specify the path to the `.yaml` configuration file of the model (here it is `PP-DocLayout-L.yaml`,When training other models, you need to specify the corresponding configuration files. The relationship between the model and configuration files can be found in the [PaddleX Model List (CPU/GPU)](../../../support_list/models_list.en.md))
 * Specify the mode as model training: `-o Global.mode=train`
 * Specify the mode as model training: `-o Global.mode=train`
 * Specify the path to the training dataset: `-o Global.dataset_dir`
 * Specify the path to the training dataset: `-o Global.dataset_dir`
-
-Other related parameters can be set by modifying the `Global` and `Train` fields in the `.yaml` configuration file, or adjusted by appending parameters in the command line. For example, to specify training on the first two GPUs: `-o Global.device=gpu:0,1`; to set the number of training epochs to 10: `-o Train.epochs_iters=10`. For more modifiable parameters and their detailed explanations, refer to the [PaddleX Common Configuration Parameters for Model Tasks](../../instructions/config_parameters_common.en.md).
+* Other related parameters can be set by modifying the `Global` and `Train` fields in the `.yaml` configuration file, or adjusted by appending parameters in the command line. For example, to specify training on the first two GPUs: `-o Global.device=gpu:0,1`; to set the number of training epochs to 10: `-o Train.epochs_iters=10`. For more modifiable parameters and their detailed explanations, refer to the [PaddleX Common Configuration Parameters for Model Tasks](../../instructions/config_parameters_common.en.md).
+* New Feature: Paddle 3.0 support CINN (Compiler Infrastructure for Neural Networks) to accelerate training speed when using GPU device. Please specify `-o Train.dy2st=True` to enable it.
 
 
 <details><summary>👉 <b>More Details (Click to Expand)</b></summary>
 <details><summary>👉 <b>More Details (Click to Expand)</b></summary>
 <ul>
 <ul>

+ 2 - 1
docs/module_usage/tutorials/ocr_modules/layout_detection.md

@@ -668,7 +668,8 @@ python main.py -c paddlex/configs/modules/layout_detection/PP-DocLayout-L.yaml \
 * 指定模型的`.yaml` 配置文件路径(此处为`PP-DocLayout-L.yaml`,训练其他模型时,需要的指定相应的配置文件,模型和配置的文件的对应关系,可以查阅[PaddleX模型列表(CPU/GPU)](../../../support_list/models_list.md))
 * 指定模型的`.yaml` 配置文件路径(此处为`PP-DocLayout-L.yaml`,训练其他模型时,需要的指定相应的配置文件,模型和配置的文件的对应关系,可以查阅[PaddleX模型列表(CPU/GPU)](../../../support_list/models_list.md))
 * 指定模式为模型训练:`-o Global.mode=train`
 * 指定模式为模型训练:`-o Global.mode=train`
 * 指定训练数据集路径:`-o Global.dataset_dir`
 * 指定训练数据集路径:`-o Global.dataset_dir`
-其他相关参数均可通过修改`.yaml`配置文件中的`Global`和`Train`下的字段来进行设置,也可以通过在命令行中追加参数来进行调整。如指定前 2 卡 gpu 训练:`-o Global.device=gpu:0,1`;设置训练轮次数为 10:`-o Train.epochs_iters=10`。更多可修改的参数及其详细解释,可以查阅模型对应任务模块的配置文件说明[PaddleX通用模型配置文件参数说明](../../instructions/config_parameters_common.md)。
+* 其他相关参数均可通过修改`.yaml`配置文件中的`Global`和`Train`下的字段来进行设置,也可以通过在命令行中追加参数来进行调整。如指定前 2 卡 gpu 训练:`-o Global.device=gpu:0,1`;设置训练轮次数为 10:`-o Train.epochs_iters=10`。更多可修改的参数及其详细解释,可以查阅模型对应任务模块的配置文件说明[PaddleX通用模型配置文件参数说明](../../instructions/config_parameters_common.md)。
+* 新特性:Paddle 3.0 版本支持了 CINN 神经网络编译器,在使用 GPU 设备训练时,不同模型有不同程度的训练加速效果。在 PaddleX 中训练模型时,可通过指定参数 `-o Train.dy2st=True` 开启。
 
 
 <details><summary>👉 <b>更多说明(点击展开)</b></summary>
 <details><summary>👉 <b>更多说明(点击展开)</b></summary>
 <ul>
 <ul>

+ 2 - 2
docs/module_usage/tutorials/ocr_modules/seal_text_detection.en.md

@@ -563,8 +563,8 @@ You need to follow these steps:
 * Specify the `.yaml` configuration file path for the model (here it's `PP-OCRv4_server_seal_det.yaml`,When training other models, you need to specify the corresponding configuration files. The relationship between the model and configuration files can be found in the [PaddleX Model List (CPU/GPU)](../../../support_list/models_list.en.md)).
 * Specify the `.yaml` configuration file path for the model (here it's `PP-OCRv4_server_seal_det.yaml`,When training other models, you need to specify the corresponding configuration files. The relationship between the model and configuration files can be found in the [PaddleX Model List (CPU/GPU)](../../../support_list/models_list.en.md)).
 * Set the mode to model training: `-o Global.mode=train`
 * Set the mode to model training: `-o Global.mode=train`
 * Specify the training dataset path: `-o Global.dataset_dir`
 * Specify the training dataset path: `-o Global.dataset_dir`
-
-Other related parameters can be set by modifying the `Global` and `Train` fields in the `.yaml` configuration file, or adjusted by appending parameters in the command line. For example, to train using the first two GPUs: `-o Global.device=gpu:0,1`; to set the number of training epochs to 10: `-o Train.epochs_iters=10`. For more modifiable parameters and their detailed explanations, refer to the [PaddleX Common Configuration Parameters Documentation](../../instructions/config_parameters_common.en.md).
+* Other related parameters can be set by modifying the `Global` and `Train` fields in the `.yaml` configuration file, or adjusted by appending parameters in the command line. For example, to train using the first two GPUs: `-o Global.device=gpu:0,1`; to set the number of training epochs to 10: `-o Train.epochs_iters=10`. For more modifiable parameters and their detailed explanations, refer to the [PaddleX Common Configuration Parameters Documentation](../../instructions/config_parameters_common.en.md).
+* New Feature: Paddle 3.0 support CINN (Compiler Infrastructure for Neural Networks) to accelerate training speed when using GPU device. Please specify `-o Train.dy2st=True` to enable it.
 
 
 <details><summary>👉 <b>More Details (Click to Expand)</b></summary>
 <details><summary>👉 <b>More Details (Click to Expand)</b></summary>
 <ul>
 <ul>

+ 2 - 1
docs/module_usage/tutorials/ocr_modules/seal_text_detection.md

@@ -555,7 +555,8 @@ python main.py -c paddlex/configs/modules/seal_text_detection/PP-OCRv4_server_se
 * 指定模型的`.yaml` 配置文件路径(此处为`PP-OCRv4_server_seal_det.yaml`,训练其他模型时,需要的指定相应的配置文件,模型和配置的文件的对应关系,可以查阅[PaddleX模型列表(CPU/GPU)](../../../support_list/models_list.md))
 * 指定模型的`.yaml` 配置文件路径(此处为`PP-OCRv4_server_seal_det.yaml`,训练其他模型时,需要的指定相应的配置文件,模型和配置的文件的对应关系,可以查阅[PaddleX模型列表(CPU/GPU)](../../../support_list/models_list.md))
 * 指定模式为模型训练:`-o Global.mode=train`
 * 指定模式为模型训练:`-o Global.mode=train`
 * 指定训练数据集路径:`-o Global.dataset_dir`
 * 指定训练数据集路径:`-o Global.dataset_dir`
-其他相关参数均可通过修改`.yaml`配置文件中的`Global`和`Train`下的字段来进行设置,也可以通过在命令行中追加参数来进行调整。如指定前 2 卡 gpu 训练:`-o Global.device=gpu:0,1`;设置训练轮次数为 10:`-o Train.epochs_iters=10`。更多可修改的参数及其详细解释,可以查阅模型对应任务模块的配置文件说明[PaddleX通用模型配置文件参数说明](../../instructions/config_parameters_common.md)。
+* 其他相关参数均可通过修改`.yaml`配置文件中的`Global`和`Train`下的字段来进行设置,也可以通过在命令行中追加参数来进行调整。如指定前 2 卡 gpu 训练:`-o Global.device=gpu:0,1`;设置训练轮次数为 10:`-o Train.epochs_iters=10`。更多可修改的参数及其详细解释,可以查阅模型对应任务模块的配置文件说明[PaddleX通用模型配置文件参数说明](../../instructions/config_parameters_common.md)。
+* 新特性:Paddle 3.0 版本支持了 CINN 神经网络编译器,在使用 GPU 设备训练时,不同模型有不同程度的训练加速效果。在 PaddleX 中训练模型时,可通过指定参数 `-o Train.dy2st=True` 开启。
 
 
 <details><summary>👉 <b>更多说明(点击展开)</b></summary>
 <details><summary>👉 <b>更多说明(点击展开)</b></summary>
 <ul>
 <ul>

+ 2 - 1
docs/module_usage/tutorials/ocr_modules/table_cells_detection.en.md

@@ -481,7 +481,8 @@ The following steps are required:
 * Specify the path to the model's `.yaml` configuration file (here it is `RT-DETR-L_wired_table_cell_det.yaml`). When training other models, the corresponding configuration file must be specified. The correspondence between models and configuration files can be found in the [PaddleX Model List (CPU/GPU)](../../../support_list/models_list.en.md)).
 * Specify the path to the model's `.yaml` configuration file (here it is `RT-DETR-L_wired_table_cell_det.yaml`). When training other models, the corresponding configuration file must be specified. The correspondence between models and configuration files can be found in the [PaddleX Model List (CPU/GPU)](../../../support_list/models_list.en.md)).
 * Specify the mode as model training: `-o Global.mode=train`
 * Specify the mode as model training: `-o Global.mode=train`
 * Specify the path to the training dataset: `-o Global.dataset_dir`
 * Specify the path to the training dataset: `-o Global.dataset_dir`
-Other related parameters can be set by modifying the fields under `Global` and `Train` in the `.yaml` configuration file, or by adding parameters in the command line. For example, to train on the first two GPUs: `-o Global.device=gpu:0,1`; to set the number of training epochs to 10: `-o Train.epochs_iters=10`. For more modifiable parameters and their detailed explanations, refer to the configuration file instructions for the corresponding model task module in [PaddleX Common Model Configuration Parameters](../../instructions/config_parameters_common.en.md).
+* Other related parameters can be set by modifying the fields under `Global` and `Train` in the `.yaml` configuration file, or by adding parameters in the command line. For example, to train on the first two GPUs: `-o Global.device=gpu:0,1`; to set the number of training epochs to 10: `-o Train.epochs_iters=10`. For more modifiable parameters and their detailed explanations, refer to the configuration file instructions for the corresponding model task module in [PaddleX Common Model Configuration Parameters](../../instructions/config_parameters_common.en.md).
+* New Feature: Paddle 3.0 support CINN (Compiler Infrastructure for Neural Networks) to accelerate training speed when using GPU device. Please specify `-o Train.dy2st=True` to enable it.
 
 
 <details><summary>👉 <b>More Information (Click to Expand)</b></summary>
 <details><summary>👉 <b>More Information (Click to Expand)</b></summary>
 
 

+ 2 - 1
docs/module_usage/tutorials/ocr_modules/table_cells_detection.md

@@ -480,7 +480,8 @@ python main.py -c paddlex/configs/modules/table_cells_detection/RT-DETR-L_wired_
 * 指定模型的`.yaml` 配置文件路径(此处为`RT-DETR-L_wired_table_cell_det.yaml`),训练其他模型时,需要的指定相应的配置文件,模型和配置的文件的对应关系,可以查阅[PaddleX模型列表(CPU/GPU)](../../../support_list/models_list.md))
 * 指定模型的`.yaml` 配置文件路径(此处为`RT-DETR-L_wired_table_cell_det.yaml`),训练其他模型时,需要的指定相应的配置文件,模型和配置的文件的对应关系,可以查阅[PaddleX模型列表(CPU/GPU)](../../../support_list/models_list.md))
 * 指定模式为模型训练:`-o Global.mode=train`
 * 指定模式为模型训练:`-o Global.mode=train`
 * 指定训练数据集路径:`-o Global.dataset_dir`
 * 指定训练数据集路径:`-o Global.dataset_dir`
-其他相关参数均可通过修改`.yaml`配置文件中的`Global`和`Train`下的字段来进行设置,也可以通过在命令行中追加参数来进行调整。如指定前 2 卡 gpu 训练:`-o Global.device=gpu:0,1`;设置训练轮次数为 10:`-o Train.epochs_iters=10`。更多可修改的参数及其详细解释,可以查阅模型对应任务模块的配置文件说明[PaddleX通用模型配置文件参数说明](../../instructions/config_parameters_common.md)。
+* 其他相关参数均可通过修改`.yaml`配置文件中的`Global`和`Train`下的字段来进行设置,也可以通过在命令行中追加参数来进行调整。如指定前 2 卡 gpu 训练:`-o Global.device=gpu:0,1`;设置训练轮次数为 10:`-o Train.epochs_iters=10`。更多可修改的参数及其详细解释,可以查阅模型对应任务模块的配置文件说明[PaddleX通用模型配置文件参数说明](../../instructions/config_parameters_common.md)。
+* 新特性:Paddle 3.0 版本支持了 CINN 神经网络编译器,在使用 GPU 设备训练时,不同模型有不同程度的训练加速效果。在 PaddleX 中训练模型时,可通过指定参数 `-o Train.dy2st=True` 开启。
 
 
 <details><summary>👉 <b>更多说明(点击展开)</b></summary>
 <details><summary>👉 <b>更多说明(点击展开)</b></summary>
 
 

+ 2 - 1
docs/module_usage/tutorials/ocr_modules/table_classification.en.md

@@ -387,7 +387,8 @@ python main.py -c paddlex/configs/modules/table_classification/PP-LCNet_x1_0_tab
 * Specify the `.yaml` configuration file path for the model (here it is `PP-LCNet_x1_0_table_cls.yaml`. When training other models, the corresponding configuration file needs to be specified. The correspondence between models and configurations can be found in [PaddleX Model List (CPU/GPU)](../../../support_list/models_list.en.md)).
 * Specify the `.yaml` configuration file path for the model (here it is `PP-LCNet_x1_0_table_cls.yaml`. When training other models, the corresponding configuration file needs to be specified. The correspondence between models and configurations can be found in [PaddleX Model List (CPU/GPU)](../../../support_list/models_list.en.md)).
 * Set the mode to model training: `-o Global.mode=train`
 * Set the mode to model training: `-o Global.mode=train`
 * Specify the training dataset path: `-o Global.dataset_dir`
 * Specify the training dataset path: `-o Global.dataset_dir`
-Other related parameters can be set by modifying the fields under `Global` and `Train` in the `.yaml` configuration file, or by appending parameters in the command line. For example, to specify training on the first 2 GPUs: `-o Global.device=gpu:0,1`; to set the number of training epochs to 10: `-o Train.epochs_iters=10`. For more modifiable parameters and their detailed explanations, refer to the configuration file description of the corresponding model task module [PaddleX General Model Configuration Parameters](../../instructions/config_parameters_common.en.md).
+* Other related parameters can be set by modifying the fields under `Global` and `Train` in the `.yaml` configuration file, or by appending parameters in the command line. For example, to specify training on the first 2 GPUs: `-o Global.device=gpu:0,1`; to set the number of training epochs to 10: `-o Train.epochs_iters=10`. For more modifiable parameters and their detailed explanations, refer to the configuration file description of the corresponding model task module [PaddleX General Model Configuration Parameters](../../instructions/config_parameters_common.en.md).
+* New Feature: Paddle 3.0 support CINN (Compiler Infrastructure for Neural Networks) to accelerate training speed when using GPU device. Please specify `-o Train.dy2st=True` to enable it.
 
 
 <details><summary>👉 <b>More Details (Click to Expand)</b></summary>
 <details><summary>👉 <b>More Details (Click to Expand)</b></summary>
 
 

+ 2 - 1
docs/module_usage/tutorials/ocr_modules/table_classification.md

@@ -389,7 +389,8 @@ python main.py -c paddlex/configs/modules/table_classification/PP-LCNet_x1_0_tab
 * 指定模型的`.yaml` 配置文件路径(此处为`PP-LCNet_x1_0_table_cls.yaml`,训练其他模型时,需要的指定相应的配置文件,模型和配置的文件的对应关系,可以查阅[PaddleX模型列表(CPU/GPU)](../../../support_list/models_list.md))
 * 指定模型的`.yaml` 配置文件路径(此处为`PP-LCNet_x1_0_table_cls.yaml`,训练其他模型时,需要的指定相应的配置文件,模型和配置的文件的对应关系,可以查阅[PaddleX模型列表(CPU/GPU)](../../../support_list/models_list.md))
 * 指定模式为模型训练:`-o Global.mode=train`
 * 指定模式为模型训练:`-o Global.mode=train`
 * 指定训练数据集路径:`-o Global.dataset_dir`
 * 指定训练数据集路径:`-o Global.dataset_dir`
-其他相关参数均可通过修改`.yaml`配置文件中的`Global`和`Train`下的字段来进行设置,也可以通过在命令行中追加参数来进行调整。如指定前 2 卡 gpu 训练:`-o Global.device=gpu:0,1`;设置训练轮次数为 10:`-o Train.epochs_iters=10`。更多可修改的参数及其详细解释,可以查阅模型对应任务模块的配置文件说明[PaddleX通用模型配置文件参数说明](../../instructions/config_parameters_common.md)。
+* 其他相关参数均可通过修改`.yaml`配置文件中的`Global`和`Train`下的字段来进行设置,也可以通过在命令行中追加参数来进行调整。如指定前 2 卡 gpu 训练:`-o Global.device=gpu:0,1`;设置训练轮次数为 10:`-o Train.epochs_iters=10`。更多可修改的参数及其详细解释,可以查阅模型对应任务模块的配置文件说明[PaddleX通用模型配置文件参数说明](../../instructions/config_parameters_common.md)。
+* 新特性:Paddle 3.0 版本支持了 CINN 神经网络编译器,在使用 GPU 设备训练时,不同模型有不同程度的训练加速效果。在 PaddleX 中训练模型时,可通过指定参数 `-o Train.dy2st=True` 开启。
 
 
 <details><summary>👉 <b>更多说明(点击展开)</b></summary>
 <details><summary>👉 <b>更多说明(点击展开)</b></summary>
 
 

+ 3 - 2
docs/module_usage/tutorials/ocr_modules/table_structure_recognition.en.md

@@ -392,8 +392,9 @@ the following steps are required:
 
 
 * Specify the path of the model's `.yaml` configuration file (here it is `SLANet.yaml`,When training other models, you need to specify the corresponding configuration files. The relationship between the model and configuration files can be found in the [PaddleX Model List (CPU/GPU)](../../../support_list/models_list.en.md))
 * Specify the path of the model's `.yaml` configuration file (here it is `SLANet.yaml`,When training other models, you need to specify the corresponding configuration files. The relationship between the model and configuration files can be found in the [PaddleX Model List (CPU/GPU)](../../../support_list/models_list.en.md))
 * Specify the mode as model training: `-o Global.mode=train`
 * Specify the mode as model training: `-o Global.mode=train`
-* Specify the path of the training dataset: `-o Global.dataset_dir`. Other related parameters can be set by modifying the fields under `Global` and `Train` in the `.yaml` configuration file, or adjusted by appending parameters in the command line. For example, to specify training on the first 2 GPUs: `-o Global.device=gpu:0,1`; to set the number of training epochs to 10: `-o Train.epochs_iters=10`. For more modifiable parameters and their detailed explanations, refer to the configuration file parameter instructions for the corresponding task module of the model [PaddleX Common Model Configuration File Parameters](../../instructions/config_parameters_common.en.md).
-
+* Specify the path of the training dataset: `-o Global.dataset_dir`.
+* Other related parameters can be set by modifying the fields under `Global` and `Train` in the `.yaml` configuration file, or adjusted by appending parameters in the command line. For example, to specify training on the first 2 GPUs: `-o Global.device=gpu:0,1`; to set the number of training epochs to 10: `-o Train.epochs_iters=10`. For more modifiable parameters and their detailed explanations, refer to the configuration file parameter instructions for the corresponding task module of the model [PaddleX Common Model Configuration File Parameters](../../instructions/config_parameters_common.en.md).
+* New Feature: Paddle 3.0 support CINN (Compiler Infrastructure for Neural Networks) to accelerate training speed when using GPU device. Please specify `-o Train.dy2st=True` to enable it.
 
 
 <details><summary>👉 <b>More Details (Click to Expand)</b></summary>
 <details><summary>👉 <b>More Details (Click to Expand)</b></summary>
 <ul>
 <ul>

+ 2 - 1
docs/module_usage/tutorials/ocr_modules/table_structure_recognition.md

@@ -387,7 +387,8 @@ python main.py -c paddlex/configs/modules/table_structure_recognition/SLANet.yam
 * 指定模型的`.yaml` 配置文件路径(此处为`SLANet.yaml`,训练其他模型时,需要的指定相应的配置文件,模型和配置的文件的对应关系,可以查阅[PaddleX模型列表(CPU/GPU)](../../../support_list/models_list.md))
 * 指定模型的`.yaml` 配置文件路径(此处为`SLANet.yaml`,训练其他模型时,需要的指定相应的配置文件,模型和配置的文件的对应关系,可以查阅[PaddleX模型列表(CPU/GPU)](../../../support_list/models_list.md))
 * 指定模式为模型训练:`-o Global.mode=train`
 * 指定模式为模型训练:`-o Global.mode=train`
 * 指定训练数据集路径:`-o Global.dataset_dir`
 * 指定训练数据集路径:`-o Global.dataset_dir`
-其他相关参数均可通过修改`.yaml`配置文件中的`Global`和`Train`下的字段来进行设置,也可以通过在命令行中追加参数来进行调整。如指定前 2 卡 gpu 训练:`-o Global.device=gpu:0,1`;设置训练轮次数为 10:`-o Train.epochs_iters=10`。更多可修改的参数及其详细解释,可以查阅模型对应任务模块的配置文件说明[PaddleX通用模型配置文件参数说明](../../instructions/config_parameters_common.md)。
+* 其他相关参数均可通过修改`.yaml`配置文件中的`Global`和`Train`下的字段来进行设置,也可以通过在命令行中追加参数来进行调整。如指定前 2 卡 gpu 训练:`-o Global.device=gpu:0,1`;设置训练轮次数为 10:`-o Train.epochs_iters=10`。更多可修改的参数及其详细解释,可以查阅模型对应任务模块的配置文件说明[PaddleX通用模型配置文件参数说明](../../instructions/config_parameters_common.md)。
+* 新特性:Paddle 3.0 版本支持了 CINN 神经网络编译器,在使用 GPU 设备训练时,不同模型有不同程度的训练加速效果。在 PaddleX 中训练模型时,可通过指定参数 `-o Train.dy2st=True` 开启。
 
 
 <details><summary>👉 <b>更多说明(点击展开)</b></summary>
 <details><summary>👉 <b>更多说明(点击展开)</b></summary>
 <ul>
 <ul>

+ 2 - 1
docs/module_usage/tutorials/ocr_modules/text_detection.en.md

@@ -508,7 +508,8 @@ The steps required are:
 * Specify the path to the model's `.yaml` configuration file (here it's `PP-OCRv4_mobile_det.yaml`. When training other models, you need to specify the corresponding configuration files. The relationship between the model and configuration files can be found in the [PaddleX Model List (CPU/GPU)](../../../support_list/models_list.en.md))
 * Specify the path to the model's `.yaml` configuration file (here it's `PP-OCRv4_mobile_det.yaml`. When training other models, you need to specify the corresponding configuration files. The relationship between the model and configuration files can be found in the [PaddleX Model List (CPU/GPU)](../../../support_list/models_list.en.md))
 * Set the mode to model training: `-o Global.mode=train`
 * Set the mode to model training: `-o Global.mode=train`
 * Specify the path to the training dataset: `-o Global.dataset_dir`
 * Specify the path to the training dataset: `-o Global.dataset_dir`
-Other related parameters can be set by modifying the `Global` and `Train` fields in the `.yaml` configuration file or adjusted by appending parameters in the command line. For example, to specify training on the first two GPUs: `-o Global.device=gpu:0,1`; to set the number of training epochs to 10: `-o Train.epochs_iters=10`. For more modifiable parameters and their detailed explanations, refer to the [PaddleX Common Configuration Parameters Documentation](../../../module_usage/instructions/config_parameters_common.en.md).
+* Other related parameters can be set by modifying the `Global` and `Train` fields in the `.yaml` configuration file or adjusted by appending parameters in the command line. For example, to specify training on the first two GPUs: `-o Global.device=gpu:0,1`; to set the number of training epochs to 10: `-o Train.epochs_iters=10`. For more modifiable parameters and their detailed explanations, refer to the [PaddleX Common Configuration Parameters Documentation](../../../module_usage/instructions/config_parameters_common.en.md).
+* New Feature: Paddle 3.0 support CINN (Compiler Infrastructure for Neural Networks) to accelerate training speed when using GPU device. Please specify `-o Train.dy2st=True` to enable it.
 
 
 <details><summary>👉 <b>More Information (Click to Expand)</b></summary>
 <details><summary>👉 <b>More Information (Click to Expand)</b></summary>
 <ul>
 <ul>

+ 2 - 1
docs/module_usage/tutorials/ocr_modules/text_detection.md

@@ -523,7 +523,8 @@ python main.py -c paddlex/configs/modules/text_detection/PP-OCRv4_mobile_det.yam
 * 指定模型的`.yaml` 配置文件路径(此处为`PP-OCRv4_mobile_det.yaml`,训练其他模型时,需要的指定相应的配置文件,模型和配置的文件的对应关系,可以查阅[PaddleX模型列表(CPU/GPU)](../../../support_list/models_list.md))
 * 指定模型的`.yaml` 配置文件路径(此处为`PP-OCRv4_mobile_det.yaml`,训练其他模型时,需要的指定相应的配置文件,模型和配置的文件的对应关系,可以查阅[PaddleX模型列表(CPU/GPU)](../../../support_list/models_list.md))
 * 指定模式为模型训练:`-o Global.mode=train`
 * 指定模式为模型训练:`-o Global.mode=train`
 * 指定训练数据集路径:`-o Global.dataset_dir`
 * 指定训练数据集路径:`-o Global.dataset_dir`
-其他相关参数均可通过修改`.yaml`配置文件中的`Global`和`Train`下的字段来进行设置,也可以通过在命令行中追加参数来进行调整。如指定前 2 卡 gpu 训练:`-o Global.device=gpu:0,1`;设置训练轮次数为 10:`-o Train.epochs_iters=10`。更多可修改的参数及其详细解释,可以查阅模型对应任务模块的配置文件说明 [PaddleX通用模型配置文件参数说明](../../../module_usage/instructions/config_parameters_common.md)。
+* 其他相关参数均可通过修改`.yaml`配置文件中的`Global`和`Train`下的字段来进行设置,也可以通过在命令行中追加参数来进行调整。如指定前 2 卡 gpu 训练:`-o Global.device=gpu:0,1`;设置训练轮次数为 10:`-o Train.epochs_iters=10`。更多可修改的参数及其详细解释,可以查阅模型对应任务模块的配置文件说明 [PaddleX通用模型配置文件参数说明](../../../module_usage/instructions/config_parameters_common.md)。
+* 新特性:Paddle 3.0 版本支持了 CINN 神经网络编译器,在使用 GPU 设备训练时,不同模型有不同程度的训练加速效果。在 PaddleX 中训练模型时,可通过指定参数 `-o Train.dy2st=True` 开启。
 
 
 <details><summary>👉 <b>更多说明(点击展开)</b></summary>
 <details><summary>👉 <b>更多说明(点击展开)</b></summary>
 <ul>
 <ul>

+ 1 - 1
docs/module_usage/tutorials/ocr_modules/text_image_unwarping.md

@@ -16,7 +16,7 @@ comments: true
 <tr>
 <tr>
 <th>模型</th><th>模型下载链接</th>
 <th>模型</th><th>模型下载链接</th>
 <th>CER </th>
 <th>CER </th>
-<th>模型存储大小(M)</th>
+<th>模型存储大小(M</th>
 <th>介绍</th>
 <th>介绍</th>
 </tr>
 </tr>
 </thead>
 </thead>

+ 2 - 2
docs/module_usage/tutorials/ocr_modules/text_recognition.en.md

@@ -644,8 +644,8 @@ The steps required are:
 * Specify the path to the model's `.yaml` configuration file (here it's `PP-OCRv4_mobile_rec.yaml`,When training other models, you need to specify the corresponding configuration files. The relationship between the model and configuration files can be found in the [PaddleX Model List (CPU/GPU)](../../../support_list/models_list.en.md))
 * Specify the path to the model's `.yaml` configuration file (here it's `PP-OCRv4_mobile_rec.yaml`,When training other models, you need to specify the corresponding configuration files. The relationship between the model and configuration files can be found in the [PaddleX Model List (CPU/GPU)](../../../support_list/models_list.en.md))
 * Specify the mode as model training: `-o Global.mode=train`
 * Specify the mode as model training: `-o Global.mode=train`
 * Specify the path to the training dataset: `-o Global.dataset_dir`.
 * Specify the path to the training dataset: `-o Global.dataset_dir`.
-Other related parameters can be set by modifying the `Global` and `Train` fields in the `.yaml` configuration file or adjusted by appending parameters in the command line. For example, to specify training on the first 2 GPUs: `-o Global.device=gpu:0,1`; to set the number of training epochs to 10: `-o Train.epochs_iters=10`. For more modifiable parameters and their detailed explanations, refer to the [PaddleX Common Configuration File Parameters](../../instructions/config_parameters_common.en.md).
-
+* Other related parameters can be set by modifying the `Global` and `Train` fields in the `.yaml` configuration file or adjusted by appending parameters in the command line. For example, to specify training on the first 2 GPUs: `-o Global.device=gpu:0,1`; to set the number of training epochs to 10: `-o Train.epochs_iters=10`. For more modifiable parameters and their detailed explanations, refer to the [PaddleX Common Configuration File Parameters](../../instructions/config_parameters_common.en.md).
+* New Feature: Paddle 3.0 support CINN (Compiler Infrastructure for Neural Networks) to accelerate training speed when using GPU device. Please specify `-o Train.dy2st=True` to enable it.
 
 
 <details><summary>👉 <b>More Information (Click to Expand)</b></summary>
 <details><summary>👉 <b>More Information (Click to Expand)</b></summary>
 <ul>
 <ul>

+ 2 - 2
docs/module_usage/tutorials/ocr_modules/text_recognition.md

@@ -662,8 +662,8 @@ python main.py -c paddlex/configs/modules/text_recognition/PP-OCRv4_mobile_rec.y
 * 指定模型的`.yaml` 配置文件路径(此处为`PP-OCRv4_mobile_rec.yaml`,训练其他模型时,需要的指定相应的配置文件,模型和配置的文件的对应关系,可以查阅[PaddleX模型列表(CPU/GPU)](../../../support_list/models_list.md))
 * 指定模型的`.yaml` 配置文件路径(此处为`PP-OCRv4_mobile_rec.yaml`,训练其他模型时,需要的指定相应的配置文件,模型和配置的文件的对应关系,可以查阅[PaddleX模型列表(CPU/GPU)](../../../support_list/models_list.md))
 * 指定模式为模型训练:`-o Global.mode=train`
 * 指定模式为模型训练:`-o Global.mode=train`
 * 指定训练数据集路径:`-o Global.dataset_dir`
 * 指定训练数据集路径:`-o Global.dataset_dir`
-其他相关参数均可通过修改`.yaml`配置文件中的`Global`和`Train`下的字段来进行设置,也可以通过在命令行中追加参数来进行调整。如指定前 2 卡 gpu 训练:`-o Global.device=gpu:0,1`;设置训练轮次数为 10:`-o Train.epochs_iters=10`。更多可修改的参数及其详细解释,可以查阅模型对应任务模块的配置文件说明[PaddleX通用模型配置文件参数说明](../../instructions/config_parameters_common.md)。
-
+* 其他相关参数均可通过修改`.yaml`配置文件中的`Global`和`Train`下的字段来进行设置,也可以通过在命令行中追加参数来进行调整。如指定前 2 卡 gpu 训练:`-o Global.device=gpu:0,1`;设置训练轮次数为 10:`-o Train.epochs_iters=10`。更多可修改的参数及其详细解释,可以查阅模型对应任务模块的配置文件说明[PaddleX通用模型配置文件参数说明](../../instructions/config_parameters_common.md)。
+* 新特性:Paddle 3.0 版本支持了 CINN 神经网络编译器,在使用 GPU 设备训练时,不同模型有不同程度的训练加速效果。在 PaddleX 中训练模型时,可通过指定参数 `-o Train.dy2st=True` 开启。
 
 
 
 
 <details><summary>👉 <b>更多说明(点击展开)</b></summary>
 <details><summary>👉 <b>更多说明(点击展开)</b></summary>

+ 2 - 1
docs/module_usage/tutorials/ocr_modules/textline_orientation_classification.en.md

@@ -404,7 +404,8 @@ The following steps are required:
 * Specify the path to the `.yaml` configuration file for the model (here it is `PP-LCNet_x0_25_textline_ori.yaml`. When training other models, you need to specify the corresponding configuration file. The correspondence between models and configuration files can be found in the [PaddleX Model List (CPU/GPU)](../../../support_list/models_list.en.md)).
 * Specify the path to the `.yaml` configuration file for the model (here it is `PP-LCNet_x0_25_textline_ori.yaml`. When training other models, you need to specify the corresponding configuration file. The correspondence between models and configuration files can be found in the [PaddleX Model List (CPU/GPU)](../../../support_list/models_list.en.md)).
 * Specify the mode as model training: `-o Global.mode=train`
 * Specify the mode as model training: `-o Global.mode=train`
 * Specify the path to the training dataset: `-o Global.dataset_dir`
 * Specify the path to the training dataset: `-o Global.dataset_dir`
-Other related parameters can be set by modifying the fields under `Global` and `Train` in the `.yaml` configuration file or by appending parameters in the command line. For example, to specify the first two GPUs for training: `-o Global.device=gpu:0,1`; to set the number of training epochs to 10: `-o Train.epochs_iters=10`. For more modifiable parameters and their detailed explanations, refer to the configuration file description for the corresponding task module of the model [PaddleX Common Model Configuration Parameters](../../instructions/config_parameters_common.en.md).
+* Other related parameters can be set by modifying the fields under `Global` and `Train` in the `.yaml` configuration file or by appending parameters in the command line. For example, to specify the first two GPUs for training: `-o Global.device=gpu:0,1`; to set the number of training epochs to 10: `-o Train.epochs_iters=10`. For more modifiable parameters and their detailed explanations, refer to the configuration file description for the corresponding task module of the model [PaddleX Common Model Configuration Parameters](../../instructions/config_parameters_common.en.md).
+* New Feature: Paddle 3.0 support CINN (Compiler Infrastructure for Neural Networks) to accelerate training speed when using GPU device. Please specify `-o Train.dy2st=True` to enable it.
 
 
 <details><summary>👉 <b>More Details (Click to Expand)</b></summary>
 <details><summary>👉 <b>More Details (Click to Expand)</b></summary>
 
 

+ 3 - 2
docs/module_usage/tutorials/ocr_modules/textline_orientation_classification.md

@@ -18,7 +18,7 @@ comments: true
 <th>Top-1 Acc(%)</th>
 <th>Top-1 Acc(%)</th>
 <th>GPU推理耗时(ms)</th>
 <th>GPU推理耗时(ms)</th>
 <th>CPU推理耗时 (ms)</th>
 <th>CPU推理耗时 (ms)</th>
-<th>模型存储大小(M)</th>
+<th>模型存储大小(M</th>
 <th>介绍</th>
 <th>介绍</th>
 </tr>
 </tr>
 </thead>
 </thead>
@@ -407,7 +407,8 @@ python main.py -c paddlex/configs/modules/textline_orientation/PP-LCNet_x0_25_te
 * 指定模型的`.yaml` 配置文件路径(此处为`PP-LCNet_x0_25_textline_ori.yaml`,训练其他模型时,需要的指定相应的配置文件,模型和配置的文件的对应关系,可以查阅[PaddleX模型列表(CPU/GPU)](../../../support_list/models_list.md))
 * 指定模型的`.yaml` 配置文件路径(此处为`PP-LCNet_x0_25_textline_ori.yaml`,训练其他模型时,需要的指定相应的配置文件,模型和配置的文件的对应关系,可以查阅[PaddleX模型列表(CPU/GPU)](../../../support_list/models_list.md))
 * 指定模式为模型训练:`-o Global.mode=train`
 * 指定模式为模型训练:`-o Global.mode=train`
 * 指定训练数据集路径:`-o Global.dataset_dir`
 * 指定训练数据集路径:`-o Global.dataset_dir`
-其他相关参数均可通过修改`.yaml`配置文件中的`Global`和`Train`下的字段来进行设置,也可以通过在命令行中追加参数来进行调整。如指定前 2 卡 gpu 训练:`-o Global.device=gpu:0,1`;设置训练轮次数为 10:`-o Train.epochs_iters=10`。更多可修改的参数及其详细解释,可以查阅模型对应任务模块的配置文件说明[PaddleX通用模型配置文件参数说明](../../instructions/config_parameters_common.md)。
+* 其他相关参数均可通过修改`.yaml`配置文件中的`Global`和`Train`下的字段来进行设置,也可以通过在命令行中追加参数来进行调整。如指定前 2 卡 gpu 训练:`-o Global.device=gpu:0,1`;设置训练轮次数为 10:`-o Train.epochs_iters=10`。更多可修改的参数及其详细解释,可以查阅模型对应任务模块的配置文件说明[PaddleX通用模型配置文件参数说明](../../instructions/config_parameters_common.md)。
+* 新特性:Paddle 3.0 版本支持了 CINN 神经网络编译器,在使用 GPU 设备训练时,不同模型有不同程度的训练加速效果。在 PaddleX 中训练模型时,可通过指定参数 `-o Train.dy2st=True` 开启。
 
 
 <details><summary>👉 <b>更多说明(点击展开)</b></summary>
 <details><summary>👉 <b>更多说明(点击展开)</b></summary>
 
 

+ 2 - 1
docs/module_usage/tutorials/speech_modules/multilingual_speech_recognition.en.md

@@ -223,7 +223,8 @@ the following steps are required for model inference:
 * Specify the `.yaml` configuration file path for the model (here it is `whisper_large.yaml`)
 * Specify the `.yaml` configuration file path for the model (here it is `whisper_large.yaml`)
 * Specify the mode as model inference prediction: `-o Global.mode=predict`
 * Specify the mode as model inference prediction: `-o Global.mode=predict`
 * Specify the input data path: `-o Predict.input="..."`
 * Specify the input data path: `-o Predict.input="..."`
-Other related parameters can be set by modifying the `Global` and `Predict` fields in the `.yaml` configuration file. For details, refer to [PaddleX Common Model Configuration File Parameter Description](../../instructions/config_parameters_common.en.md).
+* Other related parameters can be set by modifying the `Global` and `Predict` fields in the `.yaml` configuration file. For details, refer to [PaddleX Common Model Configuration File Parameter Description](../../instructions/config_parameters_common.en.md).
+* New Feature: Paddle 3.0 support CINN (Compiler Infrastructure for Neural Networks) to accelerate training speed when using GPU device. Please specify `-o Train.dy2st=True` to enable it.
 
 
 #### 4.4.2 Model Integration
 #### 4.4.2 Model Integration
 Models can be directly integrated into the PaddleX pipelines or into your own projects.
 Models can be directly integrated into the PaddleX pipelines or into your own projects.

+ 2 - 2
docs/module_usage/tutorials/time_series_modules/time_series_anomaly_detection.en.md

@@ -472,8 +472,8 @@ You need to follow these steps:
 * Specify the `.yaml` configuration file path for the model (here it's `AutoEncoder_ad.yaml`,When training other models, you need to specify the corresponding configuration files. The relationship between the model and configuration files can be found in the [PaddleX Model List (CPU/GPU)](../../../support_list/models_list.en.md)).
 * Specify the `.yaml` configuration file path for the model (here it's `AutoEncoder_ad.yaml`,When training other models, you need to specify the corresponding configuration files. The relationship between the model and configuration files can be found in the [PaddleX Model List (CPU/GPU)](../../../support_list/models_list.en.md)).
 * Set the mode to model training: `-o Global.mode=train`
 * Set the mode to model training: `-o Global.mode=train`
 * Specify the training dataset path: `-o Global.dataset_dir`
 * Specify the training dataset path: `-o Global.dataset_dir`
-
-Other related parameters can be set by modifying the `Global` and `Train` fields in the `.yaml` configuration file, or adjusted by appending parameters in the command line. For example, to train using the first two GPUs: `-o Global.device=gpu:0,1`; to set the number of training epochs to 10: `-o Train.epochs_iters=10`. For more modifiable parameters and their detailed explanations, refer to the [PaddleX TS Configuration Parameters Documentation](../../instructions/config_parameters_time_series.en.md).
+* Other related parameters can be set by modifying the `Global` and `Train` fields in the `.yaml` configuration file, or adjusted by appending parameters in the command line. For example, to train using the first two GPUs: `-o Global.device=gpu:0,1`; to set the number of training epochs to 10: `-o Train.epochs_iters=10`. For more modifiable parameters and their detailed explanations, refer to the [PaddleX TS Configuration Parameters Documentation](../../instructions/config_parameters_time_series.en.md).
+* New Feature: Paddle 3.0 support CINN (Compiler Infrastructure for Neural Networks) to accelerate training speed when using GPU device. Please specify `-o Train.dy2st=True` to enable it.
 
 
 <details><summary>👉 <b>More Details (Click to Expand)</b></summary>
 <details><summary>👉 <b>More Details (Click to Expand)</b></summary>
 
 

+ 3 - 2
docs/module_usage/tutorials/time_series_modules/time_series_anomaly_detection.md

@@ -17,7 +17,7 @@ comments: true
 <th>precison</th>
 <th>precison</th>
 <th>recall</th>
 <th>recall</th>
 <th>f1_score</th>
 <th>f1_score</th>
-<th>模型存储大小(M)</th>
+<th>模型存储大小(M</th>
 <th>介绍</th>
 <th>介绍</th>
 </tr>
 </tr>
 </thead>
 </thead>
@@ -474,7 +474,8 @@ python main.py -c paddlex/configs/modules/ts_anomaly_detection/AutoEncoder_ad.ya
 * 指定模型的`.yaml` 配置文件路径(此处为`AutoEncoder_ad.yaml`,训练其他模型时,需要的指定相应的配置文件,模型和配置的文件的对应关系,可以查阅[PaddleX模型列表(CPU/GPU)](../../../support_list/models_list.md))
 * 指定模型的`.yaml` 配置文件路径(此处为`AutoEncoder_ad.yaml`,训练其他模型时,需要的指定相应的配置文件,模型和配置的文件的对应关系,可以查阅[PaddleX模型列表(CPU/GPU)](../../../support_list/models_list.md))
 * 指定模式为模型训练:`-o Global.mode=train`
 * 指定模式为模型训练:`-o Global.mode=train`
 * 指定训练数据集路径:`-o Global.dataset_dir`
 * 指定训练数据集路径:`-o Global.dataset_dir`
-其他相关参数均可通过修改`.yaml`配置文件中的`Global`和`Train`下的字段来进行设置,也可以通过在命令行中追加参数来进行调整。如指定前 2 卡 gpu 训练:`-o Global.device=gpu:0,1`;设置训练轮次数为 10:`-o Train.epochs_iters=10`。更多可修改的参数及其详细解释,可以查阅模型对应任务模块的配置文件说明[PaddleX时序任务模型配置文件参数说明](../../instructions/config_parameters_time_series.md)。
+* 其他相关参数均可通过修改`.yaml`配置文件中的`Global`和`Train`下的字段来进行设置,也可以通过在命令行中追加参数来进行调整。如指定前 2 卡 gpu 训练:`-o Global.device=gpu:0,1`;设置训练轮次数为 10:`-o Train.epochs_iters=10`。更多可修改的参数及其详细解释,可以查阅模型对应任务模块的配置文件说明[PaddleX时序任务模型配置文件参数说明](../../instructions/config_parameters_time_series.md)。
+* 新特性:Paddle 3.0 版本支持了 CINN 神经网络编译器,在使用 GPU 设备训练时,不同模型有不同程度的训练加速效果。在 PaddleX 中训练模型时,可通过指定参数 `-o Train.dy2st=True` 开启。
 
 
 <details><summary>👉 <b>更多说明(点击展开)</b></summary>
 <details><summary>👉 <b>更多说明(点击展开)</b></summary>
 
 

+ 2 - 2
docs/module_usage/tutorials/time_series_modules/time_series_classification.en.md

@@ -454,8 +454,8 @@ You need to follow these steps:
 * Specify the `.yaml` configuration file path for the model (here it's `TimesNet_cls.yaml`,When training other models, you need to specify the corresponding configuration files. The relationship between the model and configuration files can be found in the [PaddleX Model List (CPU/GPU)](../../../support_list/models_list.en.md)).
 * Specify the `.yaml` configuration file path for the model (here it's `TimesNet_cls.yaml`,When training other models, you need to specify the corresponding configuration files. The relationship between the model and configuration files can be found in the [PaddleX Model List (CPU/GPU)](../../../support_list/models_list.en.md)).
 * Set the mode to model training: `-o Global.mode=train`
 * Set the mode to model training: `-o Global.mode=train`
 * Specify the training dataset path: `-o Global.dataset_dir`
 * Specify the training dataset path: `-o Global.dataset_dir`
-
-Other related parameters can be set by modifying the `Global` and `Train` fields in the `.yaml` configuration file, or adjusted by appending parameters in the command line. For example, to train using the first two GPUs: `-o Global.device=gpu:0,1`; to set the number of training epochs to 10: `-o Train.epochs_iters=10`. For more modifiable parameters and their detailed explanations, refer to the [PaddleX TS Configuration Parameters Documentation](../../instructions/config_parameters_time_series.en.md).
+* Other related parameters can be set by modifying the `Global` and `Train` fields in the `.yaml` configuration file, or adjusted by appending parameters in the command line. For example, to train using the first two GPUs: `-o Global.device=gpu:0,1`; to set the number of training epochs to 10: `-o Train.epochs_iters=10`. For more modifiable parameters and their detailed explanations, refer to the [PaddleX TS Configuration Parameters Documentation](../../instructions/config_parameters_time_series.en.md).
+* New Feature: Paddle 3.0 support CINN (Compiler Infrastructure for Neural Networks) to accelerate training speed when using GPU device. Please specify `-o Train.dy2st=True` to enable it.
 
 
 <details><summary>👉 <b>More Details (Click to Expand)</b></summary>
 <details><summary>👉 <b>More Details (Click to Expand)</b></summary>
 
 

+ 3 - 2
docs/module_usage/tutorials/time_series_modules/time_series_classification.md

@@ -15,7 +15,7 @@ comments: true
 <tr>
 <tr>
 <th>模型名称</th><th>模型下载链接</th>
 <th>模型名称</th><th>模型下载链接</th>
 <th>acc(%)</th>
 <th>acc(%)</th>
-<th>模型存储大小(M)</th>
+<th>模型存储大小(M</th>
 <th>介绍</th>
 <th>介绍</th>
 </tr>
 </tr>
 </thead>
 </thead>
@@ -453,7 +453,8 @@ python main.py -c paddlex/configs/modules/ts_classification/TimesNet_cls.yaml \
 * 指定模型的`.yaml` 配置文件路径(此处为`TimesNet_cls.yaml`,训练其他模型时,需要的指定相应的配置文件,模型和配置的文件的对应关系,可以查阅[PaddleX模型列表(CPU/GPU)](../../../support_list/models_list.md))
 * 指定模型的`.yaml` 配置文件路径(此处为`TimesNet_cls.yaml`,训练其他模型时,需要的指定相应的配置文件,模型和配置的文件的对应关系,可以查阅[PaddleX模型列表(CPU/GPU)](../../../support_list/models_list.md))
 * 指定模式为模型训练:`-o Global.mode=train`
 * 指定模式为模型训练:`-o Global.mode=train`
 * 指定训练数据集路径:`-o Global.dataset_dir`
 * 指定训练数据集路径:`-o Global.dataset_dir`
-其他相关参数均可通过修改`.yaml`配置文件中的`Global`和`Train`下的字段来进行设置,也可以通过在命令行中追加参数来进行调整。如指定前 2 卡 gpu 训练:`-o Global.device=gpu:0,1`;设置训练轮次数为 10:`-o Train.epochs_iters=10`。更多可修改的参数及其详细解释,可以查阅模型对应任务模块的配置文件说明[PaddleX时序任务模型配置文件参数说明](../../instructions/config_parameters_time_series.md)。
+* 其他相关参数均可通过修改`.yaml`配置文件中的`Global`和`Train`下的字段来进行设置,也可以通过在命令行中追加参数来进行调整。如指定前 2 卡 gpu 训练:`-o Global.device=gpu:0,1`;设置训练轮次数为 10:`-o Train.epochs_iters=10`。更多可修改的参数及其详细解释,可以查阅模型对应任务模块的配置文件说明[PaddleX时序任务模型配置文件参数说明](../../instructions/config_parameters_time_series.md)。
+* 新特性:Paddle 3.0 版本支持了 CINN 神经网络编译器,在使用 GPU 设备训练时,不同模型有不同程度的训练加速效果。在 PaddleX 中训练模型时,可通过指定参数 `-o Train.dy2st=True` 开启。
 
 
 <details><summary>👉 <b>更多说明(点击展开)</b></summary>
 <details><summary>👉 <b>更多说明(点击展开)</b></summary>
 
 

+ 2 - 2
docs/module_usage/tutorials/time_series_modules/time_series_forecasting.en.md

@@ -509,8 +509,8 @@ You need to follow these steps:
 * Specify the `.yaml` configuration file path for the model (here it's `DLinear.yaml`,When training other models, you need to specify the corresponding configuration files. The relationship between the model and configuration files can be found in the [PaddleX Model List (CPU/GPU)](../../../support_list/models_list.en.md)).
 * Specify the `.yaml` configuration file path for the model (here it's `DLinear.yaml`,When training other models, you need to specify the corresponding configuration files. The relationship between the model and configuration files can be found in the [PaddleX Model List (CPU/GPU)](../../../support_list/models_list.en.md)).
 * Set the mode to model training: `-o Global.mode=train`
 * Set the mode to model training: `-o Global.mode=train`
 * Specify the training dataset path: `-o Global.dataset_dir`
 * Specify the training dataset path: `-o Global.dataset_dir`
-
-Other related parameters can be set by modifying the `Global` and `Train` fields in the `.yaml` configuration file, or adjusted by appending parameters in the command line. For example, to train using the first two GPUs: `-o Global.device=gpu:0,1`; to set the number of training epochs to 10: `-o Train.epochs_iters=10`. For more modifiable parameters and their detailed explanations, refer to the [PaddleX TS Configuration Parameters Documentation](../../instructions/config_parameters_time_series.en.md).
+* Other related parameters can be set by modifying the `Global` and `Train` fields in the `.yaml` configuration file, or adjusted by appending parameters in the command line. For example, to train using the first two GPUs: `-o Global.device=gpu:0,1`; to set the number of training epochs to 10: `-o Train.epochs_iters=10`. For more modifiable parameters and their detailed explanations, refer to the [PaddleX TS Configuration Parameters Documentation](../../instructions/config_parameters_time_series.en.md).
+* New Feature: Paddle 3.0 support CINN (Compiler Infrastructure for Neural Networks) to accelerate training speed when using GPU device. Please specify `-o Train.dy2st=True` to enable it.
 
 
 <details><summary>👉 <b>More Details (Click to Expand)</b></summary>
 <details><summary>👉 <b>More Details (Click to Expand)</b></summary>
 
 

+ 3 - 2
docs/module_usage/tutorials/time_series_modules/time_series_forecasting.md

@@ -15,7 +15,7 @@ comments: true
 <th>模型名称</th><th>模型下载链接</th>
 <th>模型名称</th><th>模型下载链接</th>
 <th>mse</th>
 <th>mse</th>
 <th>mae</th>
 <th>mae</th>
-<th>模型存储大小(M)</th>
+<th>模型存储大小(M</th>
 <th>介绍</th>
 <th>介绍</th>
 </tr>
 </tr>
 </thead>
 </thead>
@@ -520,7 +520,8 @@ python main.py -c paddlex/configs/modules/ts_forecast/DLinear.yaml \
 * 指定模型的`.yaml` 配置文件路径(此处为`DLinear.yaml`,训练其他模型时,需要的指定相应的配置文件,模型和配置的文件的对应关系,可以查阅[PaddleX模型列表(CPU/GPU)](../../../support_list/models_list.md))
 * 指定模型的`.yaml` 配置文件路径(此处为`DLinear.yaml`,训练其他模型时,需要的指定相应的配置文件,模型和配置的文件的对应关系,可以查阅[PaddleX模型列表(CPU/GPU)](../../../support_list/models_list.md))
 * 指定模式为模型训练:`-o Global.mode=train`
 * 指定模式为模型训练:`-o Global.mode=train`
 * 指定训练数据集路径:`-o Global.dataset_dir`
 * 指定训练数据集路径:`-o Global.dataset_dir`
-其他相关参数均可通过修改`.yaml`配置文件中的`Global`和`Train`下的字段来进行设置,也可以通过在命令行中追加参数来进行调整。如指定前 2 卡 gpu 训练:`-o Global.device=gpu:0,1`;设置训练轮次数为 10:`-o Train.epochs_iters=10`。更多可修改的参数及其详细解释,可以查阅模型对应任务模块的配置文件说明[PaddleX时序任务模型配置文件参数说明](../../instructions/config_parameters_time_series.md)。
+* 其他相关参数均可通过修改`.yaml`配置文件中的`Global`和`Train`下的字段来进行设置,也可以通过在命令行中追加参数来进行调整。如指定前 2 卡 gpu 训练:`-o Global.device=gpu:0,1`;设置训练轮次数为 10:`-o Train.epochs_iters=10`。更多可修改的参数及其详细解释,可以查阅模型对应任务模块的配置文件说明[PaddleX时序任务模型配置文件参数说明](../../instructions/config_parameters_time_series.md)。
+* 新特性:Paddle 3.0 版本支持了 CINN 神经网络编译器,在使用 GPU 设备训练时,不同模型有不同程度的训练加速效果。在 PaddleX 中训练模型时,可通过指定参数 `-o Train.dy2st=True` 开启。
 
 
 <details><summary>👉 <b>更多说明(点击展开)</b></summary>
 <details><summary>👉 <b>更多说明(点击展开)</b></summary>
 
 

+ 3 - 2
docs/module_usage/tutorials/video_modules/video_classification.en.md

@@ -9,7 +9,6 @@ The Video Classification Module is a crucial component in a computer vision syst
 
 
 ## II. List of Supported Models
 ## II. List of Supported Models
 
 
-
 <table>
 <table>
 <tr>
 <tr>
 <th>Model</th><th>Model Download Link</th>
 <th>Model</th><th>Model Download Link</th>
@@ -424,7 +423,9 @@ the following steps are required:
 
 
 * Specify the path of the model's `.yaml` configuration file (here it is `PP-TSMv2-LCNetV2_8frames_uniform.yaml`. When training other models, you need to specify the corresponding configuration files. The relationship between the model and configuration files can be found in the [PaddleX Model List (CPU/GPU)](../../../support_list/models_list.en.md))
 * Specify the path of the model's `.yaml` configuration file (here it is `PP-TSMv2-LCNetV2_8frames_uniform.yaml`. When training other models, you need to specify the corresponding configuration files. The relationship between the model and configuration files can be found in the [PaddleX Model List (CPU/GPU)](../../../support_list/models_list.en.md))
 * Specify the mode as model training: `-o Global.mode=train`
 * Specify the mode as model training: `-o Global.mode=train`
-* Specify the path of the training dataset: `-o Global.dataset_dir`. Other related parameters can be set by modifying the fields under `Global` and `Train` in the `.yaml` configuration file, or adjusted by appending parameters in the command line. For example, to specify training on the first 2 GPUs: `-o Global.device=gpu:0,1`; to set the number of training epochs to 10: `-o Train.epochs_iters=10`. For more modifiable parameters and their detailed explanations, refer to the configuration file parameter instructions for the corresponding task module of the model [PaddleX Common Model Configuration File Parameters](../../instructions/config_parameters_common.en.md).
+* Specify the path of the training dataset: `-o Global.dataset_dir`.
+* Other related parameters can be set by modifying the fields under `Global` and `Train` in the `.yaml` configuration file, or adjusted by appending parameters in the command line. For example, to specify training on the first 2 GPUs: `-o Global.device=gpu:0,1`; to set the number of training epochs to 10: `-o Train.epochs_iters=10`. For more modifiable parameters and their detailed explanations, refer to the configuration file parameter instructions for the corresponding task module of the model [PaddleX Common Model Configuration File Parameters](../../instructions/config_parameters_common.en.md).
+* New Feature: Paddle 3.0 support CINN (Compiler Infrastructure for Neural Networks) to accelerate training speed when using GPU device. Please specify `-o Train.dy2st=True` to enable it.
 
 
 
 
 <details><summary>👉 <b>More Details (Click to Expand)</b></summary>
 <details><summary>👉 <b>More Details (Click to Expand)</b></summary>

+ 2 - 1
docs/module_usage/tutorials/video_modules/video_classification.md

@@ -425,7 +425,8 @@ python main.py -c paddlex/configs/modules/video_classification/PP-TSMv2-LCNetV2_
 * 指定模型的`.yaml` 配置文件路径(此处为`PP-TSMv2-LCNetV2_8frames_uniform.yaml`,训练其他模型时,需要的指定相应的配置文件,模型和配置的文件的对应关系,可以查阅[PaddleX模型列表(CPU/GPU)](../../../support_list/models_list.md))
 * 指定模型的`.yaml` 配置文件路径(此处为`PP-TSMv2-LCNetV2_8frames_uniform.yaml`,训练其他模型时,需要的指定相应的配置文件,模型和配置的文件的对应关系,可以查阅[PaddleX模型列表(CPU/GPU)](../../../support_list/models_list.md))
 * 指定模式为模型训练:`-o Global.mode=train`
 * 指定模式为模型训练:`-o Global.mode=train`
 * 指定训练数据集路径:`-o Global.dataset_dir`
 * 指定训练数据集路径:`-o Global.dataset_dir`
-其他相关参数均可通过修改`.yaml`配置文件中的`Global`和`Train`下的字段来进行设置,也可以通过在命令行中追加参数来进行调整。如指定前 2 卡 gpu 训练:`-o Global.device=gpu:0,1`;设置训练轮次数为 10:`-o Train.epochs_iters=10`。更多可修改的参数及其详细解释,可以查阅模型对应任务模块的配置文件说明[PaddleX通用模型配置文件参数说明](../../instructions/config_parameters_common.md)。
+* 其他相关参数均可通过修改`.yaml`配置文件中的`Global`和`Train`下的字段来进行设置,也可以通过在命令行中追加参数来进行调整。如指定前 2 卡 gpu 训练:`-o Global.device=gpu:0,1`;设置训练轮次数为 10:`-o Train.epochs_iters=10`。更多可修改的参数及其详细解释,可以查阅模型对应任务模块的配置文件说明[PaddleX通用模型配置文件参数说明](../../instructions/config_parameters_common.md)。
+* 新特性:Paddle 3.0 版本支持了 CINN 神经网络编译器,在使用 GPU 设备训练时,不同模型有不同程度的训练加速效果。在 PaddleX 中训练模型时,可通过指定参数 `-o Train.dy2st=True` 开启。
 
 
 <details><summary>👉 <b>更多说明(点击展开)</b></summary>
 <details><summary>👉 <b>更多说明(点击展开)</b></summary>
 
 

+ 3 - 3
docs/module_usage/tutorials/video_modules/video_detection.en.md

@@ -11,7 +11,6 @@ The output of the video detection module includes bounding boxes and class label
 
 
 ## II. List of Supported Models
 ## II. List of Supported Models
 
 
-
 <table>
 <table>
 <tr>
 <tr>
 <th>Model</th><th>Model Download Link</th>
 <th>Model</th><th>Model Download Link</th>
@@ -408,8 +407,9 @@ the following steps are required:
 
 
 * Specify the path of the model's `.yaml` configuration file (here it is `YOWO.yaml`. When training other models, you need to specify the corresponding configuration files. The relationship between the model and configuration files can be found in the [PaddleX Model List (CPU/GPU)](../../../support_list/models_list.en.md))
 * Specify the path of the model's `.yaml` configuration file (here it is `YOWO.yaml`. When training other models, you need to specify the corresponding configuration files. The relationship between the model and configuration files can be found in the [PaddleX Model List (CPU/GPU)](../../../support_list/models_list.en.md))
 * Specify the mode as model training: `-o Global.mode=train`
 * Specify the mode as model training: `-o Global.mode=train`
-* Specify the path of the training dataset: `-o Global.dataset_dir`. Other related parameters can be set by modifying the fields under `Global` and `Train` in the `.yaml` configuration file, or adjusted by appending parameters in the command line. For example, to specify training on the second GPU: `-o Global.device=gpu:2`; to set the number of training epochs to 10: `-o Train.epochs_iters=10`. For more modifiable parameters and their detailed explanations, refer to the configuration file parameter instructions for the corresponding task module of the model [PaddleX Common Model Configuration File Parameters](../../instructions/config_parameters_common.en.md).
-
+* Specify the path of the training dataset: `-o Global.dataset_dir`.
+* Other related parameters can be set by modifying the fields under `Global` and `Train` in the `.yaml` configuration file, or adjusted by appending parameters in the command line. For example, to specify training on the second GPU: `-o Global.device=gpu:2`; to set the number of training epochs to 10: `-o Train.epochs_iters=10`. For more modifiable parameters and their detailed explanations, refer to the configuration file parameter instructions for the corresponding task module of the model [PaddleX Common Model Configuration File Parameters](../../instructions/config_parameters_common.en.md).
+* New Feature: Paddle 3.0 support CINN (Compiler Infrastructure for Neural Networks) to accelerate training speed when using GPU device. Please specify `-o Train.dy2st=True` to enable it.
 
 
 <details><summary>👉 <b>More Details (Click to Expand)</b></summary>
 <details><summary>👉 <b>More Details (Click to Expand)</b></summary>
 
 

+ 3 - 2
docs/module_usage/tutorials/video_modules/video_detection.md

@@ -413,10 +413,11 @@ python main.py -c paddlex/configs/modules/video_detection/YOWO.yaml  \
 ```
 ```
 需要如下几步:
 需要如下几步:
 
 
-* 指定模型的`.yaml` 配置文件路径(此处为`YOWO.yaml`,训练其他模型时,需要的指定相应的配置文件,模型和配置的文件的对应关系,可以查阅[PaddleX模型列表(CPU/GPU)](../../../support_list/models_list.md)
+* 指定模型的`.yaml` 配置文件路径(此处为`YOWO.yaml`,训练其他模型时,需要的指定相应的配置文件,模型和配置的文件的对应关系,可以查阅[PaddleX模型列表(CPU/GPU)](../../../support_list/models_list.md)
 * 指定模式为模型训练:`-o Global.mode=train`
 * 指定模式为模型训练:`-o Global.mode=train`
 * 指定训练数据集路径:`-o Global.dataset_dir`
 * 指定训练数据集路径:`-o Global.dataset_dir`
-其他相关参数均可通过修改`.yaml`配置文件中的`Global`和`Train`下的字段来进行设置,也可以通过在命令行中追加参数来进行调整。如指定第 2 卡 gpu 训练:`-o Global.device=gpu:2`,视频检测只支持单卡训练;设置训练轮次数为 10:`-o Train.epochs_iters=10`。更多可修改的参数及其详细解释,可以查阅模型对应任务模块的配置文件说明[PaddleX通用模型配置文件参数说明](../../instructions/config_parameters_common.md)。
+* 其他相关参数均可通过修改`.yaml`配置文件中的`Global`和`Train`下的字段来进行设置,也可以通过在命令行中追加参数来进行调整。如指定第 2 卡 gpu 训练:`-o Global.device=gpu:2`,视频检测只支持单卡训练;设置训练轮次数为 10:`-o Train.epochs_iters=10`。更多可修改的参数及其详细解释,可以查阅模型对应任务模块的配置文件说明[PaddleX通用模型配置文件参数说明](../../instructions/config_parameters_common.md)。
+* 新特性:Paddle 3.0 版本支持了 CINN 神经网络编译器,在使用 GPU 设备训练时,不同模型有不同程度的训练加速效果。在 PaddleX 中训练模型时,可通过指定参数 `-o Train.dy2st=True` 开启。
 
 
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