chris-propeller/transformers-inference-endpoint-fail

1from typing import Dict, Any, List2import torch3import numpy as np4from PIL import Image5import base646import io7import cv28 9# Test importing the problematic packages10from transformers import Sam3Model, Sam3Processor11 12 13class EndpointHandler:14    """15    Minimal test handler to isolate dependency loading issues16    This handler imports all the same dependencies but doesn't execute SAM3 inference17    """18 19    def __init__(self, path: str = ""):20        """21        Initialize the handler - test dependency loading without heavy model loading22 23        Args:24            path: Path to model weights (unused in this test)25        """26        self.device = "cuda" if torch.cuda.is_available() else "cpu"27        print(f"✅ Test handler initialized successfully on device: {self.device}")28 29        # Test that we can import the SAM3 classes without loading the model30        print(f"✅ Successfully imported Sam3Model: {Sam3Model}")31        print(f"✅ Successfully imported Sam3Processor: {Sam3Processor}")32 33        # Test other dependencies34        print(f"✅ PyTorch version: {torch.__version__}")35        print(f"✅ NumPy version: {np.__version__}")36        print(f"✅ PIL (Pillow) available: {Image}")37        print(f"✅ OpenCV available: {cv2.__version__}")38 39        # Don't actually load the model to avoid memory/download issues40        self.model = None41        self.processor = None42 43        print("✅ Minimal test handler ready - all dependencies loaded successfully!")44 45    def __call__(self, data: Dict[str, Any]) -> Dict[str, Any]:46        """47        Minimal test endpoint that returns success without actual inference48 49        Args:50            data: Input data (will be ignored in this test)51 52        Returns:53            Simple success response to verify the handler works54        """55        try:56            print("📝 Test handler called with data keys:", list(data.keys()) if data else "No data")57 58            # Test basic operations with imported libraries59            test_array = np.array([1, 2, 3])60            test_tensor = torch.tensor([1.0, 2.0, 3.0])61 62            print(f"✅ NumPy test array: {test_array}")63            print(f"✅ PyTorch test tensor: {test_tensor}")64            print(f"✅ Device available: {self.device}")65 66            # Return a successful test response67            return {68                "status": "success",69                "message": "✅ All dependencies loaded and working correctly!",70                "test_results": {71                    "numpy_test": test_array.tolist(),72                    "torch_test": test_tensor.tolist(),73                    "device": self.device,74                    "torch_version": torch.__version__,75                    "numpy_version": np.__version__,76                    "opencv_version": cv2.__version__,77                    "transformers_classes_available": {78                        "Sam3Model": str(Sam3Model),79                        "Sam3Processor": str(Sam3Processor)80                    }81                },82                "input_data_received": data is not None,83                "handler_type": "minimal_test_handler"84            }85 86        except Exception as e:87            print(f"❌ Error in test handler: {str(e)}")88            return {89                "status": "error",90                "message": f"Test handler failed: {str(e)}",91                "error_type": type(e).__name__,92                "handler_type": "minimal_test_handler"93            }