rename mkldnn to onednn (#1183)

Author: HydrogenSulfate

README.md

@@ -166,7 +166,7 @@ PaddleScience 是一个基于深度学习框架 PaddlePaddle 开发的科学计
 ### 安装 PaddlePaddle
 
 <!-- --8<-- [start:paddle_install] -->
-请根据您的运行环境，访问 [PaddlePaddle](https://www.paddlepaddle.org.cn/install/quick?docurl=/documentation/docs/zh/develop/install/pip/linux-pip.html) 官网，安装 <font color="red"><b>3.0 或 develop</b></font> 版的 PaddlePaddle。
+请根据您的运行环境，访问 [PaddlePaddle](https://www.paddlepaddle.org.cn/install/quick?docurl=/documentation/docs/zh/develop/install/pip/linux-pip.html) 官网，建议安装 PaddlePaddle <font color="red"><b>3.0 以上稳定版，或最新的 develop 开发版</b></font>。
 
 安装完毕之后，运行以下命令，验证 Paddle 是否安装成功。
 

deploy/python_infer/base.py

@@ -39,7 +39,7 @@ class Predictor:
         pdmodel_path (Optional[str]): Path to the PaddlePaddle model file. Defaults to None.
         pdiparams_path (Optional[str]): Path to the PaddlePaddle model parameters file. Defaults to None.
         device (Literal["cpu", "gpu", "npu", "xpu", "sdaa"], optional): Device to use for inference. Defaults to "cpu".
-        engine (Literal["native", "tensorrt", "onnx", "mkldnn"], optional): Inference engine to use. Defaults to "native".
+        engine (Literal["native", "tensorrt", "onnx", "onednn"], optional): Inference engine to use. Defaults to "native".
         precision (Literal["fp32", "fp16", "int8"], optional): Precision to use for inference. Defaults to "fp32".
         onnx_path (Optional[str], optional): Path to the ONNX model file. Defaults to None.
         ir_optim (bool, optional): Whether to use IR optimization. Defaults to True.
@@ -55,7 +55,7 @@ def __init__(
         pdiparams_path: Optional[str] = None,
         *,
         device: Literal["cpu", "gpu", "npu", "xpu", "sdaa"] = "cpu",
-        engine: Literal["native", "tensorrt", "onnx", "mkldnn"] = "native",
+        engine: Literal["native", "tensorrt", "onnx", "onednn"] = "native",
         precision: Literal["fp32", "fp16", "int8"] = "fp32",
         onnx_path: Optional[str] = None,
         ir_optim: bool = True,
@@ -157,11 +157,11 @@ def _create_paddle_predictor(
             config.enable_xpu(10 * 1024 * 1024)
         else:
             config.disable_gpu()
-            if self.engine == "mkldnn":
+            if self.engine == "onednn":
                 # 'set_mkldnn_cache_capatity' is not available on macOS
                 if platform.system() != "Darwin":
                     ...
-                    # cache 10 different shapes for mkldnn to avoid memory leak
+                    # cache 10 different shapes for onednn to avoid memory leak
                     # config.set_mkldnn_cache_capacity(10)
                 config.enable_mkldnn()
 
@@ -170,6 +170,11 @@ def _create_paddle_predictor(
 
                 config.set_cpu_math_library_num_threads(self.num_cpu_threads)
 
+            elif self.engine == "mkldnn":
+                raise ValueError(
+                    "The 'mkldnn' engine is deprecated. Please use 'onednn' instead."
+                )
+
         # enable memory optim
         config.enable_memory_optim()
         # config.disable_glog_info()
@@ -221,9 +226,9 @@ def _check_device(self, device: str):
             )
 
     def _check_engine(self, engine: str):
-        if engine not in ["native", "tensorrt", "onnx", "mkldnn"]:
+        if engine not in ["native", "tensorrt", "onnx", "onednn"]:
             raise ValueError(
-                "Inference only supports 'native', 'tensorrt', 'onnx' and 'mkldnn' "
+                "Inference only supports 'native', 'tensorrt', 'onnx' and 'onednn' "
                 f"engines, but got {engine}."
             )
 

docs/zh/user_guide.md

@@ -464,7 +464,7 @@ ppsci MESSAGE: Visualization result is saved to: ./aneurysm_pred.vtu
 
 PaddleScience 提供了多种推理配置组合，可通过命令行进行组合，目前支持的推理配置如下：
 
-|  | Native | ONNX | TensorRT | macaRT | MKLDNN |
+|  | Native | ONNX | TensorRT | macaRT | oneDNN |
 | :--- | :--- | :--- | :--- | :--- | :--- |
 | Intel(CPU) | ✅ | ✅ | / | / | ✅ |
 | NVIDIA | ✅ | ✅ | ✅ | / | / |
@@ -576,31 +576,31 @@ PaddleScience 提供了多种推理配置组合，可通过命令行进行组合
         INFER.engine=onnx
     ```
 
-=== "使用 MKLDNN 推理"
+=== "使用 oneDNN 推理"
 
-    MKLDNN 是英特尔推出的高性能推理引擎，适用于 CPU 推理加速，PaddleScience 支持了 MKLDNN 推理功能。
+    oneDNN 是英特尔推出的高性能推理引擎，适用于 CPU 推理加速，PaddleScience 支持了 oneDNN 推理功能。
 
     运行以下命令进行推理：
 
     ``` sh
     python aneurysm.py mode=infer \
         INFER.device=cpu \
-        INFER.engine=mkldnn
+        INFER.engine=onednn
     ```
 
 !!! info "完整推理配置参数"
 
     | 参数 | 默认值 | 说明 |
     | :--- | :--- | :--- |
     | `INFER.device` | `cpu` | 推理设备，目前支持 `cpu` 和 `gpu` |
-    | `INFER.engine` | `native` | 推理引擎，目前支持 `native`, `tensorrt`, `onnx` 和 `mkldnn` |
+    | `INFER.engine` | `native` | 推理引擎，目前支持 `native`, `tensorrt`, `onnx` 和 `onednn` |
     | `INFER.precision` | `fp32` | 推理精度，目前支持 `fp32`, `fp16` |
     | `INFER.ir_optim` | `True` | 是否启用 IR 优化 |
     | `INFER.min_subgraph_size` | `30` | TensorRT 中最小子图 size，当子图的 size 大于该值时，才会尝试对该子图使用 TensorRT 计算 |
     | `INFER.gpu_mem` | `2000` | 初始显存大小 |
     | `INFER.gpu_id` | `0` | GPU 逻辑设备号 |
     | `INFER.max_batch_size` | `1024` | 推理时的最大 batch_size |
-    | `INFER.num_cpu_threads` | `10` | MKLDNN 和 ONNX 在 CPU 推理时的线程数 |
+    | `INFER.num_cpu_threads` | `10` | oneDNN 和 ONNX 在 CPU 推理时的线程数 |
     | `INFER.batch_size` | `256` | 推理时的 batch_size |
 
 ### 1.4 断点继续训练

ppsci/solver/solver.py

@@ -477,16 +477,15 @@ def dist_wrapper(model: nn.Layer) -> paddle.DataParallel:
 
         # log paddlepaddle's version
         if version.Version(paddle.__version__) != version.Version("0.0.0"):
-            paddle_version = paddle.__version__
             if version.Version(paddle.__version__) < version.Version("2.6.0"):
                 logger.warning(
-                    f"Detected paddlepaddle version is '{paddle_version}', "
+                    f"Detected paddlepaddle version is '{paddle.__version__}', "
                     "currently it is recommended to use paddlepaddle >= 2.6 or develop version."
                 )
-        else:
-            paddle_version = f"develop({paddle.version.commit[:7]})"
 
-        logger.info(f"Using paddlepaddle {paddle_version} on device {self.device}")
+        logger.info(
+            f"Using paddlepaddle {paddle.version.full_version}({paddle.version.commit[:7]}) on device {self.device}"
+        )
 
         self.forward_helper = expression.ExpressionSolver()
 

ppsci/utils/config.py

@@ -213,7 +213,7 @@ class InferConfig(BaseModel):
             pdiparams_path: Optional[str] = None
             onnx_path: Optional[str] = None
             device: Literal["cpu", "gpu", "npu", "xpu", "sdaa"] = "cpu"
-            engine: Literal["native", "tensorrt", "onnx", "mkldnn"] = "native"
+            engine: Literal["native", "tensorrt", "onnx", "onednn"] = "native"
             precision: Literal["fp32", "fp16", "int8"] = "fp32"
             ir_optim: bool = True
             min_subgraph_size: int = 30
@@ -226,14 +226,18 @@ class InferConfig(BaseModel):
             # Fine-grained validator(s) below
             @field_validator("engine")
             def engine_check(cls, v, info: ValidationInfo):
+                if v == "mkldnn":
+                    raise ValueError(
+                        "The 'mkldnn' engine is deprecated. Please use 'onednn' instead."
+                    )
                 if v == "tensorrt" and info.data["device"] != "gpu":
                     raise ValueError(
                         "'INFER.device' should be 'gpu' when 'INFER.engine' is 'tensorrt', "
                         f"but got '{info.data['device']}'"
                     )
-                if v == "mkldnn" and info.data["device"] != "cpu":
+                if v == "onednn" and info.data["device"] != "cpu":
                     raise ValueError(
-                        "'INFER.device' should be 'cpu' when 'INFER.engine' is 'mkldnn', "
+                        "'INFER.device' should be 'cpu' when 'INFER.engine' is 'onednn', "
                         f"but got '{info.data['device']}'"
                     )