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https://github.com/MLSysBook/TinyTorch.git
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Updates markdown headers in development files
Updates markdown headers in development files to improve consistency and readability. Removes the redundant "🔧 DEVELOPMENT" headers and standardizes the subsequent headers to indicate the purpose of the following code, such as "🧪 Test Your Matrix Multiplication". This change enhances the clarity and organization of the development files.
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@@ -237,8 +237,6 @@ def matmul(A: np.ndarray, B: np.ndarray) -> np.ndarray:
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# %% [markdown]
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"""
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## 🔧 DEVELOPMENT
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### 🧪 Test Your Matrix Multiplication
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Once you implement the `matmul` function above, run this cell to test it:
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@@ -631,7 +629,7 @@ It ensures that the 'Layer' abstraction works correctly with the 'Tensor' class
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"""
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# %%
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def test_module_layer_tensor():
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def test_module_layer_tensor_integration():
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"""
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Tests that a Tensor can be passed through a Layer subclass
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and that the output is of the correct type and shape.
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@@ -658,7 +656,7 @@ def test_module_layer_tensor():
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print("✅ Integration Test Passed: Layer correctly processed Tensor.")
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# Run the integration test
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test_module_layer_tensor()
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test_module_layer_tensor_integration()
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# %% [markdown]
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"""
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@@ -578,7 +578,9 @@ plot_network_architectures()
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# %% [markdown]
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"""
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## 🔧 DEVELOPMENT
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### 🧪 Unit Test: Network Architecture Variations
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This test validates different neural network architectures created with various activation functions. It ensures that networks with ReLU, Tanh, and Softmax activations work correctly, and tests both shallow and deep network configurations for comprehensive architecture validation.
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"""
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# %%
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@@ -243,8 +243,6 @@ def scaled_dot_product_attention(Q: Tensor, K: Tensor, V: Tensor,
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# %% [markdown]
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"""
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## 🔧 DEVELOPMENT
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### 🧪 Test Your Attention Implementation
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Once you implement the `scaled_dot_product_attention` function above, run this cell to test it:
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@@ -310,8 +310,6 @@ class Variable:
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# %% [markdown]
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"""
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## 🔧 DEVELOPMENT
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### 🧪 Test Your Variable Class
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Once you implement the Variable class above, run this cell to test it:
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@@ -186,8 +186,6 @@ class MeanSquaredError:
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# %% [markdown]
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"""
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## 🔧 DEVELOPMENT
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### 🧪 Unit Test: MSE Loss
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Let's test our MSE loss implementation with known values.
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@@ -367,8 +367,6 @@ class CompressionMetrics:
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# %% [markdown]
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"""
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## 🔧 DEVELOPMENT
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### 🧪 Unit Test: Compression Metrics Analysis
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This test validates your `CompressionMetrics` class implementation, ensuring it accurately calculates model parameters, memory usage, and compression statistics for optimization analysis.
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@@ -448,8 +448,6 @@ class BenchmarkScenarios:
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# %% [markdown]
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"""
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## 🔧 DEVELOPMENT
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### 🧪 Unit Test: Benchmark Scenarios
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Let's test our benchmark scenarios with a simple mock model.
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@@ -430,8 +430,6 @@ class ModelMonitor:
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# %% [markdown]
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"""
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## 🔧 DEVELOPMENT
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### 🧪 Test Your Performance Monitor
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Once you implement the `ModelMonitor` class above, run this cell to test it:
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