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Code Issues 7 Packages Projects Releases Wiki Activity

feat: standardize integration testing with import helpers

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- Add import_previous_module() helper function to all core modules (01-07)
- Standardize cross-module imports for integration testing
- Add clear Prerequisites & Setup sections explaining module dependencies
- Update integration tests to use standardized import pattern
- Maintain clean separation between development and production code

This provides a consistent, educational approach to module integration
while keeping the codebase maintainable and student-friendly.
This commit is contained in:
Vijay Janapa Reddi
2025-09-30 09:42:58 -04:00
parent 1812afbf4a
commit 6ccfa2b352
7 changed files with 115 additions and 30 deletions
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23
modules/source/06_optimizers/optimizers_dev.py
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@@ -40,14 +40,12 @@ Let's get started!
## 📦 Where This Code Lives in the Final Package
**Learning Side:** You work in modules/06_optimizers/optimizers_dev.py
**Building Side:** Code exports to tinytorch.core.optimizers
**Learning Side:** You work in `modules/06_optimizers/optimizers_dev.py`
**Building Side:** Code exports to `tinytorch.core.optimizers`
```python
# Final package structure:
from tinytorch.core.optimizers import SGD, Adam, AdamW # This module
from tinytorch.core.tensor import Tensor # Foundation from Module 01
from tinytorch.core.layers import Linear # Layers from Module 03
# How to use this module:
from tinytorch.core.optimizers import SGD, Adam, AdamW
```
**Why this matters:**
@@ -1226,6 +1224,13 @@ def analyze_optimizer_convergence_behavior():
Final validation that everything works together correctly.
"""
def import_previous_module(module_name: str, component_name: str):
import sys
import os
sys.path.append(os.path.join(os.path.dirname(__file__), '..', module_name))
module = __import__(f"{module_name.split('_')[1]}_dev")
return getattr(module, component_name)
# %% nbgrader={"grade": true, "grade_id": "module-integration", "locked": true, "points": 25}
def test_module():
"""
@@ -1251,6 +1256,12 @@ def test_module():
# Test realistic neural network optimization scenario
print("🔬 Integration Test: Multi-layer Network Optimization...")
# Import components from previous modules using standardized helper
Tensor = import_previous_module('01_tensor', 'Tensor')
Linear = import_previous_module('03_layers', 'Linear')
ReLU = import_previous_module('02_activations', 'ReLU')
MSELoss = import_previous_module('04_losses', 'MSELoss')
# Create parameters for a 2-layer network
# Layer 1: 3 inputs -> 4 hidden
W1 = Tensor(np.random.randn(3, 4) * 0.1, requires_grad=True)