Removes redundant "DEVELOPMENT" headers from several notebook files.
These headers are no longer necessary and declutter the notebook content, improving readability and focus on the core content and testing sections.
✅ Standardized test explanations with consistent format
📝 Added markdown cells before all test functions
🎯 Improved educational clarity for student understanding
Changes:
- 01_setup: Added 2 test explanations (personal_info, system_info)
- 02_tensor: Added 3 test explanations (creation, properties, arithmetic)
- 12_compression: Added 8 test explanations (metrics, pruning, quantization, distillation, etc.)
All 15 modules now follow standardized test documentation pattern:
### 🧪 Unit Test: [Component Name]
[Brief explanation of validation purpose]
Ensures every test has clear educational context for students.
- Added test_unit_benchmark_scenarios() call after function definition
- Fixed test_statistical_validation() → test_unit_statistical_validation()
- Added test_unit_tinytorch_perf() call after function definition
- Fixed test_performance_reporter() → test_unit_performance_reporter()
- Fixed test_comprehensive_benchmarking() → test_module_comprehensive_benchmarking()
Ensures all test functions are executed when cells run, providing immediate feedback to students.
- Added test_unit_compression_metrics() call and fixed name mismatch
- Added test_unit_magnitude_pruning() call and fixed name mismatch
- Added test_unit_quantization() call and fixed name mismatch
- Added test_unit_distillation() call and fixed name mismatch
- Added test_unit_structured_pruning() call and fixed name mismatch
- Added test_unit_comprehensive_comparison() call and fixed name mismatch
Ensures all test functions are executed when cells run, providing immediate feedback to students.
- Added test_unit_mse_loss() call after function definition
- Added test_unit_crossentropy_loss() call after function definition
- Added test_unit_binary_crossentropy_loss() call after function definition
- Fixed test_accuracy_metric() → test_unit_accuracy_metric()
- Fixed test_trainer() → test_unit_trainer()
- Fixed test_training() → test_module_training()
Ensures all test functions are executed when cells run, providing immediate feedback to students.
- Added test_unit_gradient_descent_step() call after function definition
Ensures the gradient descent step test function is executed when cells run, providing immediate feedback to students.
- Added test_unit_variable_class() call after function definition
- Added test_unit_add_operation() call after function definition
- Added test_unit_multiply_operation() call after function definition
- Added test_unit_subtract_operation() call after function definition
- Added test_unit_chain_rule() call after function definition
- Added test_module_neural_network_training() call after function definition
- Fixed function name mismatches in existing if __name__ == '__main__' calls
Ensures all test functions are executed when cells run, providing immediate feedback to students.
- Added test_unit_attention_mechanism() call after function definition
- Added test_unit_self_attention_wrapper() call after function definition
- Added test_unit_masking_utilities() call after function definition
Ensures all test functions are executed when cells run, providing immediate feedback to students.
- Added test_unit_convolution_operation() call after function definition
- Added test_unit_conv2d_layer() call after function definition
- Added test_unit_flatten_function() call after function definition
Ensures all test functions are executed when cells run, providing immediate feedback to students.
- Fixed test_matrix_multiplication() → test_unit_matrix_multiplication()
- Fixed test_dense_layer() → test_unit_dense_layer()
- Fixed test_layer_activation() → test_unit_layer_activation()
Ensures correct function names are called to match their definitions.
- Added test_unit_tensor_creation() call after function definition
- Added test_unit_tensor_properties() call after function definition
- Added test_unit_tensor_arithmetic() call after function definition
Ensures test functions are actually executed when cells run, providing immediate feedback to students.
- Added test_unit_personal_info_basic() call after function definition
- Added test_unit_system_info_basic() call after function definition
Ensures test functions are actually executed when cells run, providing immediate feedback to students.
- Added ## 🔧 DEVELOPMENT section before Step 1 where development begins
- Added ## 🤖 AUTO TESTING section before nbgrader block
- Updated to ## 🎯 MODULE SUMMARY: MLOps Production Systems
Improves notebook organization without changing any code logic or content.
- Added ## 🔧 DEVELOPMENT section before Step 1 where development begins
- Added ## 🤖 AUTO TESTING section before nbgrader block
- Updated to ## 🎯 MODULE SUMMARY: Performance Benchmarking
Improves notebook organization without changing any code logic or content.
- Added ## 🔧 DEVELOPMENT section before Step 1 where development begins
- Added ## 🤖 AUTO TESTING section before nbgrader block
- Updated to ## 🎯 MODULE SUMMARY: Hardware-Optimized Operations
Improves notebook organization without changing any code logic or content.
- Added ## 🔧 DEVELOPMENT section before Step 1 where development begins
- Added ## 🤖 AUTO TESTING section before nbgrader block
- Updated to ## 🎯 MODULE SUMMARY: Model Compression
Improves notebook organization without changing any code logic or content.
- Added ## 🔧 DEVELOPMENT section before Step 1 where development begins
- Added ## 🤖 AUTO TESTING section before nbgrader block
- Updated to ## 🎯 MODULE SUMMARY: Neural Network Training
Improves notebook organization without changing any code logic or content.
- Added ## 🔧 DEVELOPMENT section before Step 1 where development begins
- Added ## 🤖 AUTO TESTING section before nbgrader block
- Updated to ## 🎯 MODULE SUMMARY: Optimization Algorithms
Improves notebook organization without changing any code logic or content.
- Added ## 🔧 DEVELOPMENT section before Step 1 where development begins
- Added ## 🤖 AUTO TESTING section before nbgrader block
- Updated to ## 🎯 MODULE SUMMARY: Automatic Differentiation
Improves notebook organization without changing any code logic or content.
- Added ## 🔧 DEVELOPMENT section before Step 1 where development begins
- Added ## 🤖 AUTO TESTING section before auto testing block
- Updated to ## 🎯 MODULE SUMMARY: Data Loading Systems
Improves notebook organization without changing any code logic or content.
- Added ## 🔧 DEVELOPMENT section before Step 1 where development begins
- Added ## 🤖 AUTO TESTING section before auto testing block
- Updated to ## 🎯 MODULE SUMMARY: Attention Mechanisms
Improves notebook organization without changing any code logic or content.
- Added ## 🔧 DEVELOPMENT section before Step 1 where development begins
- Added ## 🤖 AUTO TESTING section before auto testing block
- Updated to ## 🎯 MODULE SUMMARY: Convolutional Networks
Improves notebook organization without changing any code logic or content.
- Added ## 🔧 DEVELOPMENT section before Step 1 where development begins
- Added ## 🤖 AUTO TESTING section before auto testing block
- Updated to ## 🎯 MODULE SUMMARY: Neural Network Architectures
Improves notebook organization without changing any code logic or content.
- Added ## 🔧 DEVELOPMENT section before Step 1 where development begins
- Added ## 🤖 AUTO TESTING section before nbgrader block
- Updated to ## 🎯 MODULE SUMMARY: Neural Network Layers
Improves notebook organization without changing any code logic or content.
- Added ## 🔧 DEVELOPMENT section before Step 1 where development begins
- Added ## 🤖 AUTO TESTING section before auto testing block
- Updated to ## 🎯 MODULE SUMMARY: Activation Functions
Improves notebook organization without changing any code logic or content.
- Added ## 🔧 DEVELOPMENT section before Step 1 where development begins
- Added ## 🤖 AUTO TESTING section before nbgrader block
- Updated to ## 🎯 MODULE SUMMARY: Tensor Foundation
Improves notebook organization without changing any code logic or content.
Vijay Janapa Reddi