Delete test_full_installation.py

test_full_installation.py

@@ -1,212 +0,0 @@
-#!/usr/bin/env python3
-"""
-Comprehensive test script to verify that all dependencies are installed correctly
-and the Garment3DGen system is ready to run
-"""
-
-import sys
-import os
-import torch
-import numpy as np
-
-def test_import(module_name, package_name=None):
-    """Test if a module can be imported"""
-    try:
-        if package_name:
-            __import__(package_name)
-        else:
-            __import__(module_name)
-        print(f"✓ {module_name} imported successfully")
-        return True
-    except ImportError as e:
-        print(f"✗ Failed to import {module_name}: {e}")
-        return False
-
-def test_cuda():
-    """Test CUDA availability and functionality"""
-    try:
-        if torch.cuda.is_available():
-            print(f"✓ CUDA is available. GPU count: {torch.cuda.device_count()}")
-            print(f"  Current device: {torch.cuda.current_device()}")
-            print(f"  Device name: {torch.cuda.get_device_name()}")
-            
-            # Test basic CUDA operations
-            device = torch.device('cuda:0')
-            x = torch.randn(10, 10).to(device)
-            y = torch.randn(10, 10).to(device)
-            z = torch.mm(x, y)
-            print(f"✓ CUDA operations working correctly")
-            return True
-        else:
-            print("✗ CUDA is not available")
-            return False
-    except Exception as e:
-        print(f"✗ Error testing CUDA: {e}")
-        return False
-
-def test_torch_sparse():
-    """Test torch-sparse functionality"""
-    try:
-        import torch_sparse
-        print("✓ torch_sparse imported successfully")
-        
-        # Test basic sparse operations
-        device = torch.device('cuda:0' if torch.cuda.is_available() else 'cpu')
-        indices = torch.tensor([[0, 1, 1], [2, 0, 2]], device=device)
-        values = torch.tensor([3, 4, 5], device=device)
-        size = (2, 3)
-        
-        sparse_tensor = torch.sparse_coo_tensor(indices, values, size, device=device)
-        dense_tensor = torch.randn(3, 4, device=device)
-        
-        # Test sparse matrix multiplication
-        result = torch.sparse.mm(sparse_tensor, dense_tensor)
-        print(f"✓ torch_sparse operations working correctly")
-        return True
-    except Exception as e:
-        print(f"✗ Error testing torch_sparse: {e}")
-        return False
-
-def test_pytorch3d():
-    """Test PyTorch3D functionality"""
-    try:
-        import pytorch3d
-        from pytorch3d.structures import Meshes
-        from pytorch3d.ops import sample_points_from_meshes
-        print("✓ PyTorch3D imported successfully")
-        
-        # Test basic PyTorch3D operations
-        device = torch.device('cuda:0' if torch.cuda.is_available() else 'cpu')
-        
-        # Create a simple mesh
-        verts = torch.tensor([[0, 0, 0], [1, 0, 0], [0, 1, 0]], device=device)
-        faces = torch.tensor([[0, 1, 2]], device=device)
-        
-        mesh = Meshes(verts=[verts], faces=[faces])
-        points = sample_points_from_meshes(mesh, num_samples=100)
-        
-        print(f"✓ PyTorch3D operations working correctly")
-        return True
-    except Exception as e:
-        print(f"✗ Error testing PyTorch3D: {e}")
-        return False
-
-def test_nvdiffrast():
-    """Test nvdiffrast functionality"""
-    try:
-        import nvdiffrast.torch as dr
-        print("✓ nvdiffrast imported successfully")
-        
-        # Test basic nvdiffrast operations
-        device = torch.device('cuda:0' if torch.cuda.is_available() else 'cpu')
-        glctx = dr.RasterizeGLContext(device=device)
-        print(f"✓ nvdiffrast operations working correctly")
-        return True
-    except Exception as e:
-        print(f"✗ Error testing nvdiffrast: {e}")
-        return False
-
-def test_project_modules():
-    """Test project-specific modules"""
-    try:
-        # Test core project modules
-        from loop import loop
-        from utils import *
-        from NeuralJacobianFields import SourceMesh
-        from nvdiffmodeling.src import render
-        from utilities.camera import CameraBatch
-        from utilities.helpers import cosine_avg, create_scene, l1_avg
-        from utilities.clip_spatial import CLIPVisualEncoder
-        from utilities.resize_right import resize, cubic, linear, lanczos2, lanczos3
-        from packages.fashion_clip.fashion_clip.fashion_clip import FashionCLIP
-        from get_embeddings import *
-        
-        print("✓ All project modules imported successfully")
-        return True
-    except Exception as e:
-        print(f"✗ Error testing project modules: {e}")
-        return False
-
-def test_config_loading():
-    """Test configuration loading"""
-    try:
-        import yaml
-        with open('example_config.yml', 'r') as f:
-            config = yaml.safe_load(f)
-        print("✓ Configuration loading working correctly")
-        return True
-    except Exception as e:
-        print(f"✗ Error testing configuration loading: {e}")
-        return False
-
-def main():
-    """Main test function"""
-    print("Testing Garment3DGen Full Installation...")
-    print("=" * 60)
-    
-    # Test basic dependencies
-    print("\nTesting basic dependencies:")
-    basic_deps = [
-        ("torch", "torch"),
-        ("torchvision", "torchvision"),
-        ("numpy", "numpy"),
-        ("PIL", "Pillow"),
-        ("yaml", "yaml"),
-        ("gradio", "gradio"),
-        ("clip", "clip"),
-        ("kornia", "kornia"),
-        ("scipy", "scipy"),
-        ("trimesh", "trimesh"),
-        ("easydict", "easydict"),
-    ]
-    
-    basic_success = True
-    for module, package in basic_deps:
-        if not test_import(module, package):
-            basic_success = False
-    
-    # Test CUDA
-    print("\nTesting CUDA:")
-    cuda_success = test_cuda()
-    
-    # Test complex dependencies
-    print("\nTesting complex dependencies:")
-    complex_success = True
-    
-    if not test_torch_sparse():
-        complex_success = False
-    
-    if not test_pytorch3d():
-        complex_success = False
-    
-    if not test_nvdiffrast():
-        complex_success = False
-    
-    # Test project modules
-    print("\nTesting project modules:")
-    project_success = test_project_modules()
-    
-    # Test configuration
-    print("\nTesting configuration:")
-    config_success = test_config_loading()
-    
-    # Summary
-    print("\n" + "=" * 60)
-    print("Full Installation Test Summary:")
-    print(f"Basic dependencies: {'✓ PASS' if basic_success else '✗ FAIL'}")
-    print(f"CUDA: {'✓ PASS' if cuda_success else '✗ FAIL'}")
-    print(f"Complex dependencies: {'✓ PASS' if complex_success else '✗ FAIL'}")
-    print(f"Project modules: {'✓ PASS' if project_success else '✗ FAIL'}")
-    print(f"Configuration: {'✓ PASS' if config_success else '✗ FAIL'}")
-    
-    if basic_success and cuda_success and complex_success and project_success and config_success:
-        print("\n🎉 All tests passed! The system is ready to run.")
-        print("You can now start the Gradio interface with: python app.py")
-        return True
-    else:
-        print("\n❌ Some tests failed. Please check the installation.")
-        return False
-
-if __name__ == "__main__":
-    success = main()
-    sys.exit(0 if success else 1)