Update task_template.py

task_template.py

@@ -0,0 +1,149 @@
+import os
+import sys
+import requests
+
+BASE_URL  = "http://35.192.205.84"
+API_KEY   = "YOUR_API_KEY_HERE"
+
+TASK_ID   = "11-duci"
+FILE_PATH = "sample_submission.csv"
+
+
+"""
+MODEL_ID = model_{0i} ---> ResNet18
+MODEL_ID = model_{1i} ---> ResNet50
+MODEL_ID = model_{2i} ---> ResNet152
+"""
+
+# ── Model loading ──────────────────────────────────────────────────────────────
+import torch
+import torchvision.models as models
+
+NUM_CLASSES = 100
+
+ARCHITECTURE_MAP = {
+    "0": models.resnet18,
+    "1": models.resnet50,
+    "2": models.resnet152,
+}
+
+def build_model(model_id: str) -> torch.nn.Module:
+    """
+    Build a model from a MODEL_ID string like 'model_00', 'model_12', etc.
+
+    Naming convention:
+        model_{arch}{instance}
+        arch     0 → ResNet18  |  1 → ResNet50  |  2 → ResNet152
+        instance 0, 1, 2  (three independently trained seeds per architecture)
+
+    Examples:
+        model_00, model_01, model_02  → ResNet18
+        model_10, model_11, model_12  → ResNet50
+        model_20, model_21, model_22  → ResNet152
+    """
+    # strip optional "model_" prefix
+    key = model_id.removeprefix("model_")   # e.g. "12"
+    arch_digit = key[0]                      # first digit encodes architecture
+
+    if arch_digit not in ARCHITECTURE_MAP:
+        raise ValueError(
+            f"Unknown architecture digit '{arch_digit}' in model_id '{model_id}'. "
+            f"Expected 0 (ResNet18), 1 (ResNet50), or 2 (ResNet152)."
+        )
+
+    model_fn = ARCHITECTURE_MAP[arch_digit]
+    model = model_fn(weights=None, num_classes=NUM_CLASSES)
+    return model
+
+
+def load_model(model_id: str, weights_path: str,
+               device: str = "cpu") -> torch.nn.Module:
+    """
+    Instantiate the correct architecture for *model_id* and load weights
+    from *weights_path*.
+
+    Args:
+        model_id:     e.g. 'model_00', 'model_12', 'model_21'
+        weights_path: path to the saved state-dict (.pth / .pt file)
+        device:       'cpu', 'cuda', 'cuda:0', etc.
+
+    Returns:
+        model in eval mode with weights loaded.
+    """
+    model = build_model(model_id)
+    state_dict = torch.load(weights_path, map_location=device)
+    # support both raw state-dicts and checkpoint dicts
+    if isinstance(state_dict, dict) and "state_dict" in state_dict:
+        state_dict = state_dict["state_dict"]
+    model.load_state_dict(state_dict)
+    model.to(device)
+    model.eval()
+    return model
+
+
+# ── Example usage ──────────────────────────────────────────────────────────────
+# Replace the paths below with the actual locations of your weight files.
+#
+# MODEL_WEIGHTS = {
+#     "model_00": "/path/to/weights/model_00.pth",
+#     "model_01": "/path/to/weights/model_01.pth",
+#     "model_02": "/path/to/weights/model_02.pth",
+#     "model_10": "/path/to/weights/model_10.pth",
+#     "model_11": "/path/to/weights/model_11.pth",
+#     "model_12": "/path/to/weights/model_12.pth",
+#     "model_20": "/path/to/weights/model_20.pth",
+#     "model_21": "/path/to/weights/model_21.pth",
+#     "model_22": "/path/to/weights/model_22.pth",
+# }
+#
+# for model_id, path in MODEL_WEIGHTS.items():
+#     model = load_model(model_id, path, device="cpu")
+#     print(f"Loaded {model_id}: {model.__class__.__name__}")
+# ──────────────────────────────────────────────────────────────────────────────
+
+
+
+def die(msg):
+    print(f"{msg}", file=sys.stderr)
+    sys.exit(1)
+
+
+if not os.path.isfile(FILE_PATH):
+    die(f"File not found: {FILE_PATH}")
+
+try:
+    with open(FILE_PATH, "rb") as f:
+        files = {
+            "file": (os.path.basename(FILE_PATH), f, "csv"),
+        }
+        resp = requests.post(
+            f"{BASE_URL}/submit/{TASK_ID}",
+            headers={"X-API-Key": API_KEY},
+            files=files,
+            timeout=(10, 120),
+        )
+    try:
+        body = resp.json()
+    except Exception:
+        body = {"raw_text": resp.text}
+
+    if resp.status_code == 413:
+        die("Upload rejected: file too large (HTTP 413). Reduce size and try again.")
+
+    resp.raise_for_status()
+
+    submission_id = body.get("submission_id")
+    print("Successfully submitted.")
+    print("Server response:", body)
+    if submission_id:
+        print(f"Submission ID: {submission_id}")
+
+except requests.exceptions.RequestException as e:
+    detail = getattr(e, "response", None)
+    print(f"Submission error: {e}")
+    if detail is not None:
+        try:
+            print("Server response:", detail.json())
+        except Exception:
+            print("Server response (text):", detail.text)
+    sys.exit(1)