[New Sample] Add "swin_t" Model Computational Graph

graph_net/test/swin_t_extract_test.py

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+import argparse
+import os
+
+import torch
+from torchvision import transforms
+from torchvision.models import get_model, get_model_weights
+
+import graph_net
+
+
+def extract_swin_t_graph(model_name: str, model_path: str):
+    normalize = transforms.Normalize(
+        mean=[0.485, 0.456, 0.406], std=[0.229, 0.224, 0.225]
+    )
+
+    batch_size = 1
+    height, width = 224, 224
+    num_channels = 3
+    random_input = torch.rand(batch_size, num_channels, height, width)
+    normalized_input = normalize(random_input)
+
+    weights = None
+    try:
+        w = get_model_weights(model_path)
+        weights = w.DEFAULT
+    except Exception:
+        pass
+
+    model = get_model(model_path, weights=weights)
+    model.eval()
+
+    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=False)(model)
+
+    print("Running inference...")
+    print("Input shape:", normalized_input.shape)
+    with torch.no_grad():
+        output = model(normalized_input)
+    print("Inference finished. Output shape:", output.shape)
+
+
+if __name__ == "__main__":
+    workspace_default = os.environ.get("GRAPH_NET_EXTRACT_WORKSPACE", "workspace")
+
+    parser = argparse.ArgumentParser()
+    parser.add_argument("--model_name", type=str, default="swin_t")
+    parser.add_argument("--model_path", type=str, default="swin_t")
+    parser.add_argument("--workspace", type=str, default=workspace_default)
+    args = parser.parse_args()
+
+    os.environ["GRAPH_NET_EXTRACT_WORKSPACE"] = args.workspace
+
+    extract_swin_t_graph(args.model_name, args.model_path)

samples/torchvision/swin_t/graph_hash.txt

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+7d17ac7dfc2ce690ae08f3a44dc915b308b8995d29b685a1d4e1a51741d03ffc

samples/torchvision/swin_t/graph_net.json

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+{
+    "framework": "torch",
+    "num_devices_required": 1,
+    "num_nodes_required": 1,
+    "dynamic": false,
+    "model_name": "swin_t"
+}