From 2b148e0ff3466bceda163a02224bab7aa8b6f67c Mon Sep 17 00:00:00 2001 From: Vijay Janapa Reddi Date: Wed, 16 Jul 2025 11:50:23 -0400 Subject: [PATCH] docs: Clean up whitespace and formatting in module READMEs - Fixed trailing whitespace in several module README files - Ensures consistent formatting across all documentation --- modules/source/02_tensor/README.md | 4 ++-- modules/source/03_activations/README.md | 12 ++++++------ modules/source/07_dataloader/README.md | 4 ++-- modules/source/08_autograd/README.md | 6 +++--- modules/source/10_training/README.md | 4 ++-- modules/source/11_compression/README.md | 2 +- modules/source/12_kernels/README.md | 2 +- modules/source/14_mlops/README.md | 4 ++-- 8 files changed, 19 insertions(+), 19 deletions(-) diff --git a/modules/source/02_tensor/README.md b/modules/source/02_tensor/README.md index 4b30ba95..eaa781f9 100644 --- a/modules/source/02_tensor/README.md +++ b/modules/source/02_tensor/README.md @@ -75,7 +75,7 @@ jupyter notebook tensor_dev.ipynb ### Step-by-Step Implementation 1. **Basic Tensor class** - Constructor and properties -2. **Shape management** - Understanding tensor dimensions +2. **Shape management** - Understanding tensor dimensions 3. **Arithmetic operations** - Addition, multiplication, etc. 4. **Utility methods** - Reshape, transpose, sum, mean 5. **Error handling** - Robust edge case management @@ -95,7 +95,7 @@ print(f"Sum: {x.sum()}") # Should be 10.0 # Export your tensor implementation tito export -# Test your implementation +# Test your implementation tito test --module tensor ``` diff --git a/modules/source/03_activations/README.md b/modules/source/03_activations/README.md index e321868e..2e28768f 100644 --- a/modules/source/03_activations/README.md +++ b/modules/source/03_activations/README.md @@ -66,13 +66,13 @@ output = tanh(Tensor([0, 1, -1])) # [0, 0.76, -0.76] ### Prerequisites Ensure you have completed the tensor module and understand basic tensor operations: -```bash + ```bash # Activate TinyTorch environment -source bin/activate-tinytorch.sh + source bin/activate-tinytorch.sh # Verify tensor module is working tito test --module tensor -``` + ``` ### Development Workflow 1. **Open the development file**: `modules/source/03_activations/activations_dev.py` @@ -86,9 +86,9 @@ tito test --module tensor ### Comprehensive Test Suite Run the full test suite to verify mathematical correctness: -```bash + ```bash # TinyTorch CLI (recommended) -tito test --module activations + tito test --module activations # Direct pytest execution python -m pytest tests/ -k activations -v @@ -114,7 +114,7 @@ The module includes comprehensive educational feedback: # Visual feedback with plotting 📊 Plotting ReLU behavior across range [-5, 5]... 📈 Function visualization shows expected behavior -``` + ``` ### Manual Testing Examples ```python diff --git a/modules/source/07_dataloader/README.md b/modules/source/07_dataloader/README.md index ce940ec2..b4060484 100644 --- a/modules/source/07_dataloader/README.md +++ b/modules/source/07_dataloader/README.md @@ -51,10 +51,10 @@ for batch_images, batch_labels in train_loader: ```python # Flexible interface supporting multiple datasets class Dataset: - def __getitem__(self, index): + def __getitem__(self, index): # Return (data, label) for any dataset type pass - def __len__(self): + def __len__(self): # Enable len() and iteration pass diff --git a/modules/source/08_autograd/README.md b/modules/source/08_autograd/README.md index 08d57b0f..7acee771 100644 --- a/modules/source/08_autograd/README.md +++ b/modules/source/08_autograd/README.md @@ -94,15 +94,15 @@ print(f"Complex gradient dy: {y.grad}") ### Prerequisites Ensure you understand the mathematical building blocks: -```bash + ```bash # Activate TinyTorch environment -source bin/activate-tinytorch.sh + source bin/activate-tinytorch.sh # Verify prerequisite modules tito test --module tensor tito test --module activations tito test --module layers -``` + ``` ### Development Workflow 1. **Open the development file**: `modules/source/08_autograd/autograd_dev.py` diff --git a/modules/source/10_training/README.md b/modules/source/10_training/README.md index 792f2f5c..5d724642 100644 --- a/modules/source/10_training/README.md +++ b/modules/source/10_training/README.md @@ -1,7 +1,7 @@ # 🔥 Module: Training ## 📊 Module Info -- **Difficulty**: ⭐⭐⭐⭐⭐ Expert +- **Difficulty**: ⭐⭐⭐⭐ Expert - **Time Estimate**: 8-10 hours - **Prerequisites**: Tensor, Activations, Layers, Networks, DataLoader, Autograd, Optimizers modules - **Next Steps**: Compression, Kernels, Benchmarking, MLOps modules @@ -38,7 +38,7 @@ from tinytorch.core.metrics import Accuracy # Define complete model architecture model = Sequential([ Dense(784, 128), ReLU(), - Dense(128, 64), ReLU(), + Dense(128, 64), ReLU(), Dense(64, 10), Softmax() ]) diff --git a/modules/source/11_compression/README.md b/modules/source/11_compression/README.md index 7c0b0ac6..95d5f96f 100644 --- a/modules/source/11_compression/README.md +++ b/modules/source/11_compression/README.md @@ -1,7 +1,7 @@ # 🔥 Module: Compression ## 📊 Module Info -- **Difficulty**: ⭐⭐⭐⭐⭐ Expert +- **Difficulty**: ⭐⭐⭐⭐ Expert - **Time Estimate**: 8-10 hours - **Prerequisites**: Networks, Training modules - **Next Steps**: Kernels, MLOps modules diff --git a/modules/source/12_kernels/README.md b/modules/source/12_kernels/README.md index d1ed1c3b..ae3e8d27 100644 --- a/modules/source/12_kernels/README.md +++ b/modules/source/12_kernels/README.md @@ -1,7 +1,7 @@ # 🔥 Module: Kernels ## 📊 Module Info -- **Difficulty**: ⭐⭐⭐⭐⭐ Expert +- **Difficulty**: ⭐⭐⭐⭐ Expert - **Time Estimate**: 8-10 hours - **Prerequisites**: All previous modules (01-11), especially Compression - **Next Steps**: Benchmarking, MLOps modules diff --git a/modules/source/14_mlops/README.md b/modules/source/14_mlops/README.md index 06b1b3ba..cb9abecf 100644 --- a/modules/source/14_mlops/README.md +++ b/modules/source/14_mlops/README.md @@ -1,8 +1,8 @@ # 🔥 Module: MLOps ## 📊 Module Info -- **Difficulty**: ⭐⭐⭐⭐⭐ Expert -- **Time Estimate**: 10-12 hours +- **Difficulty**: ⭐⭐⭐⭐ Expert +- **Time Estimate**: 8-10 hours - **Prerequisites**: All previous modules (01-13) - Complete TinyTorch ecosystem - **Next Steps**: **🎓 Course completion** - Deploy your complete ML system!