style: apply consistent whitespace and formatting across codebase

tinytorch/tests/integration/test_module_integration.py

@@ -6,7 +6,7 @@ These tests focus on inter-module compatibility, not individual module functiona
 
 Integration test categories:
 1. Core module integration (tensor + autograd + layers)
-2. Training pipeline integration (optimizers + training + data)  
+2. Training pipeline integration (optimizers + training + data)
 3. Optimization module integration (profiler + quantization + pruning)
 4. End-to-end integration (complete model training)
 """
@@ -19,61 +19,61 @@ def test_core_module_integration():
     """Test that core modules work together: tensor → autograd → layers"""
     print("🔧 Testing Core Module Integration")
     print("-" * 40)
-    
+
     try:
         # Test tensor + autograd integration
         from tinytorch.core.tensor import Tensor
         from tinytorch.core.autograd import Variable
-        
+
         # Create tensor and wrap in Variable
         t = Tensor([1.0, 2.0, 3.0])
         v = Variable(t, requires_grad=True)
         print("✅ Tensor + Autograd integration working")
-        
+
         # Test tensor + layers integration
         from tinytorch.nn import Linear
         layer = Linear(3, 2)
-        
+
         # This tests that layers can accept tensor inputs
         # result = layer(t)  # Simplified test
         print("✅ Tensor + Layers integration working")
-        
+
         return True
-        
+
     except Exception as e:
         print(f"❌ Core module integration failed: {e}")
         return False
 
 def test_training_pipeline_integration():
     """Test training pipeline: data → model → optimizer → training"""
-    print("\n🏋️ Testing Training Pipeline Integration")  
+    print("\n🏋️ Testing Training Pipeline Integration")
     print("-" * 40)
-    
+
     try:
         # Test data + model integration
         from tinytorch.utils.data import DataLoader, SimpleDataset
         from tinytorch.nn import Linear
         from tinytorch.core.optimizers import SGD
-        
+
         # Create simple dataset
         dataset = SimpleDataset([(i, i*2) for i in range(10)])
         dataloader = DataLoader(dataset, batch_size=2)
         print("✅ Data loading integration working")
-        
+
         # Create model
         model = Linear(1, 1)
         optimizer = SGD([model.weight], lr=0.01)
         print("✅ Model + Optimizer integration working")
-        
+
         # Test that training components work together
         for batch_data, batch_labels in dataloader:
             # output = model(batch_data)  # Simplified
             # optimizer.step()  # Simplified
             break
         print("✅ Training pipeline integration working")
-        
+
         return True
-        
+
     except Exception as e:
         print(f"❌ Training pipeline integration failed: {e}")
         return False
@@ -82,31 +82,31 @@ def test_optimization_module_integration():
     """Test optimization modules work with core modules"""
     print("\n⚡ Testing Optimization Module Integration")
     print("-" * 40)
-    
+
     try:
         # Test profiler + core modules
         from tinytorch.core.tensor import Tensor
         import tinytorch.profiler
-        
+
         # Test that profiler can analyze core operations
         def tensor_operation():
             t1 = Tensor([1, 2, 3])
             t2 = Tensor([4, 5, 6])
             return t1, t2
-        
+
         # This tests that profiler can measure core operations
         print("✅ Profiler + Core integration working")
-        
+
         # Test quantization + models (when available)
         import tinytorch.quantization
         from tinytorch.nn import Linear
-        
+
         model = Linear(10, 5)
         # quantized_model = tinytorch.quantization.quantize(model)  # When implemented
         print("✅ Quantization + Models integration ready")
-        
+
         return True
-        
+
     except Exception as e:
         print(f"❌ Optimization module integration failed: {e}")
         return False
@@ -115,7 +115,7 @@ def test_import_compatibility():
     """Test that all import paths work and don't conflict"""
     print("\n📦 Testing Import Compatibility")
     print("-" * 40)
-    
+
     try:
         # Test PyTorch-style imports don't conflict with core
         import tinytorch.profiler
@@ -123,17 +123,17 @@ def test_import_compatibility():
         import tinytorch.backends
         import tinytorch.experimental
         from tinytorch.nn.utils import prune
-        
+
         # Test core imports still work
         from tinytorch.core import tensor, autograd
         from tinytorch.nn import Linear, functional
         from tinytorch.utils.data import DataLoader
-        
+
         print("✅ All import paths compatible")
         print("✅ No namespace conflicts detected")
-        
+
         return True
-        
+
     except Exception as e:
         print(f"❌ Import compatibility failed: {e}")
         return False
@@ -142,26 +142,26 @@ def test_cross_module_data_flow():
     """Test data can flow between different modules correctly"""
     print("\n🌊 Testing Cross-Module Data Flow")
     print("-" * 40)
-    
+
     try:
         from tinytorch.core.tensor import Tensor
         from tinytorch.nn import Linear
         from tinytorch.utils.data import SimpleDataset
-        
+
         # Create data
         data = [(Tensor([i]), Tensor([i*2])) for i in range(5)]
         dataset = SimpleDataset(data)
-        
+
         # Test data flows through model
         model = Linear(1, 1)
         sample_input, sample_target = dataset[0]
-        
+
         # Test that tensor from data works with model
         # output = model(sample_input)  # Simplified
         print("✅ Data flows correctly between modules")
-        
+
         return True
-        
+
     except Exception as e:
         print(f"❌ Cross-module data flow failed: {e}")
         return False
@@ -170,30 +170,30 @@ def run_all_integration_tests():
     """Run all module integration tests"""
     print("🧪 TINYTORCH MODULE INTEGRATION TESTS")
     print("=" * 60)
-    
+
     tests = [
         test_core_module_integration,
-        test_training_pipeline_integration, 
+        test_training_pipeline_integration,
         test_optimization_module_integration,
         test_import_compatibility,
         test_cross_module_data_flow
     ]
-    
+
     passed = 0
     total = len(tests)
-    
+
     for test in tests:
         try:
             if test():
                 passed += 1
         except Exception as e:
             print(f"❌ Test {test.__name__} crashed: {e}")
-    
+
     print(f"\n📊 INTEGRATION TEST RESULTS")
     print("=" * 40)
     print(f"Passed: {passed}/{total}")
     print(f"Success Rate: {passed/total*100:.1f}%")
-    
+
     if passed == total:
         print("🎉 ALL INTEGRATION TESTS PASSED!")
         print("✅ Modules integrate correctly with each other")
@@ -204,4 +204,4 @@ def run_all_integration_tests():
         return False
 
 if __name__ == "__main__":
-    run_all_integration_tests()
+    run_all_integration_tests()