pre-commit success

Author: ADchampion3

graph_net/test/vision_model_extract_test.py

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+import argparse
+import os
+import torch
+from torchvision import transforms
+import graph_net
+
+
+def extract_visio_graph(model_name: str, model_path: str):
+    # Normalization parameters for ImageNet
+    normalize = transforms.Normalize(
+        mean=[0.485, 0.456, 0.406], std=[0.229, 0.224, 0.225]
+    )
+
+    # Create dummy input
+    batch_size = 1
+    height, width = 224, 224  # Standard ImageNet size
+    num_channels = 3
+    random_input = torch.rand(batch_size, num_channels, height, width)
+    normalized_input = normalize(random_input)
+
+    # 使用get_model下载模型
+    # all_models = list_models(module=torchvision.models)
+    # if(model_path not in all_models):
+    #     print("不存在该模型, 请校验模型名称是否相同")
+    #     return
+    # model = get_model(model_path, weights="DEFAULT")
+
+    # 使用torch.hub下载模型
+    # 相关使用办法见https://docs.pytorch.org/docs/stable/hub.html
+    torch.hub.set_dir("../../../test")  # 缓存目录默认为$TORCH_HOME/hub 如果没有设置环境变量则为 ~/.cache
+    endpoints = torch.hub.list("pytorch/vision")
+    if model_path not in endpoints:
+        print("Model not found")
+        return
+    model = torch.hub.load("pytorch/vision", model_path)
+
+    device = torch.device("cuda" if torch.cuda.is_available() else "cpu")
+    model.to(device)
+    normalized_input = normalized_input.to(device)
+
+    model = graph_net.torch.extract(name=model_name, dynamic=True)(model)
+
+    print("Running inference...")
+    print("Input shape:", normalized_input.shape)
+    output = model(normalized_input)
+    print("Inference finished. Output shape:", output.shape)
+
+
+if __name__ == "__main__":
+    # get parameters from command line
+    workspace_default = os.environ.get("GRAPH_NET_EXTRACT_WORKSPACE", "../../workspace")
+
+    parser = argparse.ArgumentParser()
+    parser.add_argument(
+        "--model_name", type=str, default="resnet18"
+    )  # 模型名称(自定义,推荐与官网相同或者简写)
+    parser.add_argument("--model_path", type=str, default="resnet18")  # 官网定义模型名称
+    parser.add_argument("--workspace", type=str, default=workspace_default)
+    args = parser.parse_args()
+
+    os.environ["GRAPH_NET_EXTRACT_WORKSPACE"] = args.workspace
+
+    extract_visio_graph(args.model_name, args.model_path)