Fix test imports to use rock solid foundation approach

- Update all test files to import from tinytorch.core.* instead of relative paths
- Consistent with rock solid foundation principle
- Tests now use stable package imports, not local module imports
- Ensures tests validate the actual exported package functionality
- Aligns with production usage patterns

modules/00_setup/tests/test_setup.py

@@ -1,18 +1,15 @@
-#!/usr/bin/env python3
 """
-Tests for the setup module using pytest.
+Test suite for the setup module.
+This tests the student implementations to ensure they work correctly.
 """
 
 import pytest
+import numpy as np
 import sys
 import os
-from pathlib import Path
-from io import StringIO
 
-# Add the parent directory to the path so we can import setup_dev
-sys.path.insert(0, str(Path(__file__).parent.parent))
-
-from setup_dev import hello_tinytorch, add_numbers, SystemInfo, DeveloperProfile
+# Import from the main package (rock solid foundation)
+from tinytorch.core.utils import hello_tinytorch, add_numbers, SystemInfo, DeveloperProfile
 
 
 class TestSetupFunctions:

modules/01_tensor/tests/test_tensor.py

@@ -1,24 +1,15 @@
 """
-Tests for TinyTorch Tensor module.
-
-Tests the core tensor functionality including creation, arithmetic operations,
-utility methods, and edge cases.
-
-These tests work with the current implementation and provide stretch goals
-for students to implement additional methods.
+Test suite for the tensor module.
+This tests the student implementations to ensure they work correctly.
 """
 
-import sys
-import os
 import pytest
 import numpy as np
+import sys
+import os
 
-# Add the parent directory to path to import tensor_dev
-sys.path.insert(0, os.path.dirname(os.path.dirname(__file__)))
-
-# Import from the module's development file
-# Note: This imports the instructor version with full implementation
-from tensor_dev import Tensor
+# Import from the main package (rock solid foundation)
+from tinytorch.core.tensor import Tensor
 
 def safe_numpy(tensor):
     """Get numpy array from tensor, using .numpy() if available, otherwise .data"""

modules/02_activations/tests/test_activations.py

@@ -10,10 +10,7 @@ import os
 
 # Import from the main package (rock solid foundation)
 from tinytorch.core.tensor import Tensor
-
-# Import our implementations from the local module for testing
-sys.path.insert(0, os.path.join(os.path.dirname(__file__), '..'))
-from activations_dev import ReLU, Sigmoid, Tanh, Softmax
+from tinytorch.core.activations import ReLU, Sigmoid, Tanh, Softmax
 
 
 class TestReLU:

modules/03_layers/tests/test_layers.py

@@ -1,28 +1,17 @@
 """
-Tests for TinyTorch Layers module.
-
-Tests the core layer functionality including Dense layers, activation functions,
-and layer composition.
-
-These tests work with the current implementation and provide stretch goals
-for students to implement additional features.
+Test suite for the layers module.
+This tests the student implementations to ensure they work correctly.
 """
 
-import sys
-import os
 import pytest
 import numpy as np
+import sys
+import os
 
-# Add the parent directory to path to import layers_dev
-sys.path.insert(0, os.path.dirname(os.path.dirname(__file__)))
-
-# Import from the module's development file
-# Note: This imports the instructor version with full implementation
-from layers_dev import Dense, Tensor
-
-# Import activation functions from the activations module
-sys.path.insert(0, os.path.join(os.path.dirname(os.path.dirname(__file__)), '..', '02_activations'))
-from activations_dev import ReLU, Sigmoid, Tanh
+# Import from the main package (rock solid foundation)
+from tinytorch.core.tensor import Tensor
+from tinytorch.core.layers import Dense
+from tinytorch.core.activations import ReLU, Sigmoid, Tanh
 
 def safe_numpy(tensor):
     """Get numpy array from tensor, using .numpy() if available, otherwise .data"""

modules/05_dataloader/tests/test_dataloader.py

@@ -1,29 +1,20 @@
 """
-Tests for TinyTorch DataLoader module.
-
-Tests follow the "Build → Use → Understand" pattern:
-1. Build Dataset → Test with local test data
-2. Build DataLoader → Test batching test data  
-3. Build Normalizer → Test normalizing test data
-4. Build Pipeline → Test complete test pipeline
-
-These tests work with small local test data for fast, reliable testing.
+Test suite for the dataloader module.
+This tests the student implementations to ensure they work correctly.
 """
 
-import sys
-import os
 import pytest
 import numpy as np
+import sys
+import os
 import tempfile
 import shutil
-import pickle
 from pathlib import Path
+from unittest.mock import patch, MagicMock
 
-# Add the parent directory to path to import dataloader_dev
-sys.path.insert(0, os.path.dirname(os.path.dirname(__file__)))
-
-# Import from the module's development file
-from dataloader_dev import Dataset, DataLoader, CIFAR10Dataset, Normalizer, create_data_pipeline, Tensor
+# Import from the main package (rock solid foundation)
+from tinytorch.core.tensor import Tensor
+from tinytorch.core.dataloader import Dataset, DataLoader, CIFAR10Dataset, Normalizer, create_data_pipeline
 
 def safe_numpy(tensor):
     """Get numpy array from tensor, using .data attribute"""