测试triton可用性

Puiching-Memory · Nov 22, 2024 · 4b5600c · 4b5600c
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diff --git a/.vscode/settings.json b/.vscode/settings.json
@@ -10,5 +10,9 @@
       "tag:yaml.org,2002:python/name:material.extensions.emoji.twemoji",
       "tag:yaml.org,2002:python/name:pymdownx.superfences.fence_code_format",
       "tag:yaml.org,2002:python/object/apply:pymdownx.slugs.slugify mapping"
-    ]
+    ],
+    "files.associations": {
+      "atomic": "cpp",
+      "algorithm": "cpp"
+    }
   }
diff --git a/README.md b/README.md
@@ -56,12 +56,12 @@ conda create -n monolite python=3.12
 
 ### 前置组件
 
-| 系统    | 前置组件           | 下载URL                                                                                             | 备注                 |
-| ------- | ------------------ | --------------------------------------------------------------------------------------------------- | -------------------- |
-| windows | Visual Studio 2022 | [download](https://visualstudio.microsoft.com/zh-hans/vs/)                                             | 注意不同版本间的冲突 |
-| windows | Cmake              | [download](https://github.com/Kitware/CMake/releases/download/v3.30.5/cmake-3.30.5-windows-x86_64.msi) | 3.30.5               |
-| windows | MSbuild            | 通过VS2022下载                                                                                      |                      |
-| windows | MSVC               | 通过VS2022下载                                                                                      |                      |
+| 系统    | 组件               | 下载URL                                                                                             | 备注                   |
+| ------- | ------------------ | --------------------------------------------------------------------------------------------------- | ---------------------- |
+| windows | Visual Studio 2022 | [download](https://visualstudio.microsoft.com/zh-hans/vs/)                                             | 注意不同版本间的冲突   |
+| windows | Cmake              | [download](https://github.com/Kitware/CMake/releases/download/v3.30.5/cmake-3.30.5-windows-x86_64.msi) | 3.30.5                 |
+| windows | MSbuild            | 通过VS2022下载                                                                                      |                        |
+| windows | MSVC               | 通过VS2022下载                                                                                      | 手动添加至环境变量PATH |
 
 ### pip
 

diff --git a/docs/zh/triton_windows.md b/docs/zh/triton_windows.md
@@ -0,0 +1,35 @@
+# 头文件
+
+将
+
+```
+C:\Program Files\Microsoft Visual Studio\2022\Community\VC\Tools\MSVC\14.42.34433\include
+C:\Program Files (x86)\Windows Kits\10\Include\10.0.22621.0\shared
+C:\Program Files (x86)\Windows Kits\10\Include\10.0.22621.0\ucrt
+```
+
+
+复制到
+
+```
+C:\Users\11386\.conda\envs\monolite\Lib\site-packages\torch\include
+```
+
+
+
+# LIB
+
+将
+
+```
+C:\Program Files\Microsoft Visual Studio\2022\Community\VC\Tools\MSVC\14.42.34433\lib\onecore\x64
+C:\Program Files (x86)\Windows Kits\10\Lib\10.0.22621.0\um\x64
+C:\Program Files (x86)\Windows Kits\10\Lib\10.0.22621.0\ucrt\x64
+```
+
+
+复制到
+
+```
+C:\Users\11386\.conda\envs\monolite\Lib\site-packages\torch\lib
+```
diff --git a/lib/datasets/augmentation.py b/lib/datasets/augmentation.py
@@ -25,7 +25,7 @@ def apply_to_bboxes(
             A.HorizontalFlip(p=0.5),
             A.RandomBrightnessContrast(p=0.2),
             # A.TemplateTransform(),
-            AugTest(p=0.5),
+            AugTest(p=0.2),
         ]
     )
 

diff --git a/lib/datasets/kitti.py b/lib/datasets/kitti.py
@@ -118,7 +118,7 @@ def __getitem__(self, index):
             heatmap, (int(1280 / 8), int(384 / 8)), interpolation=cv2.INTER_AREA
         )  # 缩放至heatmap大小
         heatmap = np.expand_dims(heatmap, axis=0)  # 增加维度
-
+        
         heatmap_backgroud = np.ones_like(heatmap)  # heatmap背景
         heatmap_backgroud = heatmap_backgroud - heatmap
 

diff --git a/lib/datasets/kitti_utils.py b/lib/datasets/kitti_utils.py
@@ -2,6 +2,29 @@
 import cv2
 from typing import Union, Optional
 
+METAINFO = {
+    "classes": (
+        "Pedestrian",
+        "Cyclist",
+        "Car",
+        "Van",
+        "Truck",
+        "Person_sitting",
+        "Tram",
+        "Misc",
+    ),
+    "palette": [
+        (106, 0, 228),
+        (119, 11, 32),
+        (165, 42, 42),
+        (0, 0, 192),
+        (197, 226, 255),
+        (0, 60, 100),
+        (0, 0, 142),
+        (255, 77, 255),
+    ],
+}
+
 ################  Object3D  ##################
 
 
@@ -33,7 +56,7 @@ def __init__(self, line: str):
         )
         self.dis_to_cam = np.linalg.norm(self.pos)
         self.ry = float(label[14])
-        self.score = float(label[15]) if label.__len__() == 16 else -1.0
+        self.score = float(label[15]) if len(label) == 16 else -1.0
         self.level_str = None
         self.level = self.get_obj_level()
 
@@ -163,6 +186,39 @@ def get_calib_from_file(calib_file):
 
 
 class Calibration(object):
+    """kitti calibration class
+
+    Args:
+        calib (Union[str, dict]): calibration file path or calibration dict
+
+    3d XYZ in <label>.txt are in rect camera coord.
+    2d box xy are in image2 coord
+    Points in <lidar>.bin are in Velodyne coord.
+    y_image2 = P^2_rect * x_rect
+    y_image2 = P^2_rect * R0_rect * Tr_velo_to_cam * x_velo
+    x_ref = Tr_velo_to_cam * x_velo
+    x_rect = R0_rect * x_ref
+
+    P^2_rect = [f^2_u,  0,      c^2_u,  -f^2_u b^2_x;
+                0,      f^2_v,  c^2_v,  -f^2_v b^2_y;
+                0,      0,      1,      0]
+                = K * [1|t]
+
+    image2 coord:
+        ----> x-axis (u)
+    |
+    |
+    v y-axis (v)
+
+    velodyne coord:
+    front x, left y, up z
+
+    rect/ref camera coord:
+    right x, down y, front z
+
+    Ref (KITTI paper): http://www.cvlibs.net/publications/Geiger2013IJRR.pdf
+    """
+
     def __init__(self, calib: Union[str, dict]):
 
         if isinstance(calib, str):
@@ -184,7 +240,7 @@ def __init__(self, calib: Union[str, dict]):
         self.tx = self.P2[0, 3] / (-self.fu)
         self.ty = self.P2[1, 3] / (-self.fv)
 
-    def cart_to_hom(self, pts):
+    def cart_to_hom(self, pts: np.ndarray) -> np.ndarray:
         """
         :param pts: (N, 3 or 2)
         :return pts_hom: (N, 4 or 3)

diff --git a/tools/train.py b/tools/train.py
@@ -45,7 +45,8 @@
 pcontext = psutil.Process(pid)
 # os.environ["CUDA_LAUNCH_BLOCKING"] = "1"  # 设置同步cuda,仅debug时使用
 # os.environ["TORCH_LOGS"] = "+dynamo"
-# os.environ["TORCHDYNAMO_VERBOSE"] = "1" 
+# os.environ["TORCHDYNAMO_VERBOSE"] = "1"
+print(sys.path)
 
 def train(
     model: torch.nn.Module,
@@ -198,8 +199,10 @@ def train(
                 completed=epoch_now + 1,
                 total=trainner.get_end_epoch(),
             )
-
-            logger.info(f"epoch {epoch_now+1} finished, time: {time.time()-epoch_start_time:.2f}s")
+
+            logger.info(
+                f"epoch {epoch_now+1} finished, time: {time.time()-epoch_start_time:.2f}s"
+            )
 
     if ema_model is not None:
         logger.info("update bn with ema model, it may takes few minutes ...")
@@ -226,13 +229,21 @@ def train(
     args = parser.parse_args()
 
     # 初始化swanlab,启动$swanlab watch ./logs
-    swanlab.init(
-        project="monolite",
-        experiment_name=f"{os.path.basename(args.cfg)}_{datetime.datetime.now().strftime('%Y/%m/%d_%H:%M:%S')}",
-        # logdir="./logs", # 本地模式
-        # mode="local",
-    )
-
+    try:
+        swanlab.init(
+            project="monolite",
+            experiment_name=f"{os.path.basename(args.cfg)}_{datetime.datetime.now().strftime('%Y/%m/%d_%H:%M:%S')}",
+            # logdir="./logs", # 本地模式
+            # mode="local",
+        )
+    except Exception as e:
+        logger.error(f"{e}\nInit swanlab in local mode")
+        swanlab.init(
+            project="monolite",
+            experiment_name=f"{os.path.basename(args.cfg)}_{datetime.datetime.now().strftime('%Y/%m/%d_%H:%M:%S')}",
+            logdir="./logs",  # 本地模式
+            mode="local",
+        )
     # 添加模块搜索路径
     sys.path.append(args.cfg)