mirror of
https://github.com/MLSysBook/TinyTorch.git
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Reorganize modules with clean structure and tests/ subdirectory
- Move test_tensor.py to modules/tensor/tests/test_tensor.py
- Create tests/ directories in setup and tensor modules
- Clean up setup module: remove setup_dev.html, setup_dev_files/, __init__.py
- Establish clean module structure pattern:
* {module}_dev.py - Main development file
* {module}_dev.ipynb - Generated notebook
* README.md - Module documentation
* tests/ - Test directory with test_{module}.py
This makes it crystal clear to students where tests are located.
This commit is contained in:
Vijay Janapa Reddi
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<main class="content" id="quarto-document-content">
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<section id="module-0-setup---tinytorch-development-workflow" class="level1">
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<h1>Module 0: Setup - Tiny🔥Torch Development Workflow</h1>
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<p>Welcome to TinyTorch! This module teaches you the development workflow you’ll use throughout the course.</p>
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<section id="learning-goals" class="level2">
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<h2 class="anchored" data-anchor-id="learning-goals">Learning Goals</h2>
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<ul>
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<li>Understand the nbdev notebook-to-Python workflow</li>
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<li>Write your first TinyTorch code</li>
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<li>Run tests and use the CLI tools</li>
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<li>Get comfortable with the development rhythm</li>
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</ul>
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</section>
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<section id="the-tinytorch-development-cycle" class="level2">
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<h2 class="anchored" data-anchor-id="the-tinytorch-development-cycle">The TinyTorch Development Cycle</h2>
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<ol type="1">
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<li><strong>Write code</strong> in this notebook using <code>#| export</code></li>
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<li><strong>Export code</strong> with <code>python bin/tito.py sync</code></li>
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<li><strong>Run tests</strong> with <code>python bin/tito.py test --module setup</code></li>
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<li><strong>Check progress</strong> with <code>python bin/tito.py info</code></li>
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</ol>
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<p>Let’s get started!</p>
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<p>::: {#cell-1 .cell 0=‘d’ 1=‘e’ 2=‘f’ 3=‘a’ 4=‘u’ 5=‘l’ 6=‘t’ 7=’_’ 8=‘e’ 9=‘x’ 10=‘p’ 11=’ ’ 12=‘c’ 13=‘o’ 14=‘r’ 15=‘e’ 16=‘.’ 17=‘u’ 18=‘t’ 19=‘i’ 20=‘l’ 21=‘s’}</p>
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<div class="sourceCode cell-code" id="cb1"><pre class="sourceCode python code-with-copy"><code class="sourceCode python"><span id="cb1-1"><a href="#cb1-1" aria-hidden="true" tabindex="-1"></a><span class="co"># Setup imports and environment</span></span>
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<span id="cb1-2"><a href="#cb1-2" aria-hidden="true" tabindex="-1"></a><span class="im">import</span> sys</span>
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<span id="cb1-3"><a href="#cb1-3" aria-hidden="true" tabindex="-1"></a><span class="im">import</span> platform</span>
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<span id="cb1-4"><a href="#cb1-4" aria-hidden="true" tabindex="-1"></a><span class="im">from</span> datetime <span class="im">import</span> datetime</span>
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<span id="cb1-5"><a href="#cb1-5" aria-hidden="true" tabindex="-1"></a></span>
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<span id="cb1-6"><a href="#cb1-6" aria-hidden="true" tabindex="-1"></a><span class="bu">print</span>(<span class="st">"🔥 TinyTorch Development Environment"</span>)</span>
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<span id="cb1-7"><a href="#cb1-7" aria-hidden="true" tabindex="-1"></a><span class="bu">print</span>(<span class="ss">f"Python </span><span class="sc">{</span>sys<span class="sc">.</span>version<span class="sc">}</span><span class="ss">"</span>)</span>
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<span id="cb1-8"><a href="#cb1-8" aria-hidden="true" tabindex="-1"></a><span class="bu">print</span>(<span class="ss">f"Platform: </span><span class="sc">{</span>platform<span class="sc">.</span>system()<span class="sc">}</span><span class="ss"> </span><span class="sc">{</span>platform<span class="sc">.</span>release()<span class="sc">}</span><span class="ss">"</span>)</span>
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<span id="cb1-9"><a href="#cb1-9" aria-hidden="true" tabindex="-1"></a><span class="bu">print</span>(<span class="ss">f"Started: </span><span class="sc">{</span>datetime<span class="sc">.</span>now()<span class="sc">.</span>strftime(<span class="st">'%Y-%m-</span><span class="sc">%d</span><span class="st"> %H:%M:%S'</span>)<span class="sc">}</span><span class="ss">"</span>)</span></code><button title="Copy to Clipboard" class="code-copy-button"><i class="bi"></i></button></pre></div>
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<p>:::</p>
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</section>
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<section id="step-1-understanding-the-module-package-structure" class="level2">
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<h2 class="anchored" data-anchor-id="step-1-understanding-the-module-package-structure">Step 1: Understanding the Module → Package Structure</h2>
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<p><strong>🎓 Teaching vs. 🔧 Building</strong>: This course has two sides: - <strong>Teaching side</strong>: You work in <code>modules/setup/setup_dev.ipynb</code> (learning-focused) - <strong>Building side</strong>: Your code exports to <code>tinytorch/core/utils.py</code> (production package)</p>
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<p><strong>Key Concept</strong>: The <code>#| default_exp core.utils</code> directive at the top tells nbdev to export all <code>#| export</code> cells to <code>tinytorch/core/utils.py</code>.</p>
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<p>This separation allows us to: - Organize learning by <strong>concepts</strong> (modules)<br>
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- Organize code by <strong>function</strong> (package structure) - Build a real ML framework while learning systematically</p>
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<p>Let’s write a simple “Hello World” function with the <code>#| export</code> directive:</p>
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<p>::: {#cell-3 .cell 0=‘e’ 1=‘x’ 2=‘p’ 3=‘o’ 4=‘r’ 5=‘t’}</p>
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<div class="sourceCode cell-code" id="cb2"><pre class="sourceCode python code-with-copy"><code class="sourceCode python"><span id="cb2-1"><a href="#cb2-1" aria-hidden="true" tabindex="-1"></a><span class="kw">def</span> hello_tinytorch():</span>
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<span id="cb2-2"><a href="#cb2-2" aria-hidden="true" tabindex="-1"></a> <span class="co">"""A simple hello world function for TinyTorch."""</span></span>
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<span id="cb2-3"><a href="#cb2-3" aria-hidden="true" tabindex="-1"></a> <span class="cf">return</span> <span class="st">"Hello from TinyTorch! 🔥"</span></span>
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<span id="cb2-4"><a href="#cb2-4" aria-hidden="true" tabindex="-1"></a></span>
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<span id="cb2-5"><a href="#cb2-5" aria-hidden="true" tabindex="-1"></a><span class="kw">def</span> add_numbers(a, b):</span>
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<span id="cb2-6"><a href="#cb2-6" aria-hidden="true" tabindex="-1"></a> <span class="co">"""Add two numbers together."""</span></span>
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<span id="cb2-7"><a href="#cb2-7" aria-hidden="true" tabindex="-1"></a> <span class="cf">return</span> a <span class="op">+</span> b</span></code><button title="Copy to Clipboard" class="code-copy-button"><i class="bi"></i></button></pre></div>
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<p>:::</p>
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<div id="cell-4" class="cell">
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<div class="sourceCode cell-code" id="cb3"><pre class="sourceCode python code-with-copy"><code class="sourceCode python"><span id="cb3-1"><a href="#cb3-1" aria-hidden="true" tabindex="-1"></a><span class="co"># Test the functions in the notebook</span></span>
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<span id="cb3-2"><a href="#cb3-2" aria-hidden="true" tabindex="-1"></a><span class="bu">print</span>(hello_tinytorch())</span>
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<span id="cb3-3"><a href="#cb3-3" aria-hidden="true" tabindex="-1"></a><span class="bu">print</span>(<span class="ss">f"2 + 3 = </span><span class="sc">{</span>add_numbers(<span class="dv">2</span>, <span class="dv">3</span>)<span class="sc">}</span><span class="ss">"</span>)</span></code><button title="Copy to Clipboard" class="code-copy-button"><i class="bi"></i></button></pre></div>
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</div>
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</section>
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<section id="step-2-a-simple-class" class="level2">
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<h2 class="anchored" data-anchor-id="step-2-a-simple-class">Step 2: A Simple Class</h2>
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<p>Let’s create a simple class that will help us understand system information. This is still basic, but shows how to structure classes in TinyTorch.</p>
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<p>::: {#cell-6 .cell 0=‘e’ 1=‘x’ 2=‘p’ 3=‘o’ 4=‘r’ 5=‘t’}</p>
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<div class="sourceCode cell-code" id="cb4"><pre class="sourceCode python code-with-copy"><code class="sourceCode python"><span id="cb4-1"><a href="#cb4-1" aria-hidden="true" tabindex="-1"></a><span class="im">import</span> sys</span>
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<span id="cb4-2"><a href="#cb4-2" aria-hidden="true" tabindex="-1"></a><span class="im">import</span> platform</span>
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<span id="cb4-3"><a href="#cb4-3" aria-hidden="true" tabindex="-1"></a></span>
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<span id="cb4-4"><a href="#cb4-4" aria-hidden="true" tabindex="-1"></a><span class="kw">class</span> SystemInfo:</span>
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<span id="cb4-5"><a href="#cb4-5" aria-hidden="true" tabindex="-1"></a> <span class="co">"""Simple system information class."""</span></span>
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<span id="cb4-6"><a href="#cb4-6" aria-hidden="true" tabindex="-1"></a> </span>
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<span id="cb4-7"><a href="#cb4-7" aria-hidden="true" tabindex="-1"></a> <span class="kw">def</span> <span class="fu">__init__</span>(<span class="va">self</span>):</span>
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<span id="cb4-8"><a href="#cb4-8" aria-hidden="true" tabindex="-1"></a> <span class="va">self</span>.python_version <span class="op">=</span> sys.version_info</span>
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<span id="cb4-9"><a href="#cb4-9" aria-hidden="true" tabindex="-1"></a> <span class="va">self</span>.platform <span class="op">=</span> platform.system()</span>
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<span id="cb4-10"><a href="#cb4-10" aria-hidden="true" tabindex="-1"></a> <span class="va">self</span>.machine <span class="op">=</span> platform.machine()</span>
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<span id="cb4-11"><a href="#cb4-11" aria-hidden="true" tabindex="-1"></a> </span>
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<span id="cb4-12"><a href="#cb4-12" aria-hidden="true" tabindex="-1"></a> <span class="kw">def</span> <span class="fu">__str__</span>(<span class="va">self</span>):</span>
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<span id="cb4-13"><a href="#cb4-13" aria-hidden="true" tabindex="-1"></a> <span class="cf">return</span> <span class="ss">f"Python </span><span class="sc">{</span><span class="va">self</span><span class="sc">.</span>python_version<span class="sc">.</span>major<span class="sc">}</span><span class="ss">.</span><span class="sc">{</span><span class="va">self</span><span class="sc">.</span>python_version<span class="sc">.</span>minor<span class="sc">}</span><span class="ss"> on </span><span class="sc">{</span><span class="va">self</span><span class="sc">.</span>platform<span class="sc">}</span><span class="ss"> (</span><span class="sc">{</span><span class="va">self</span><span class="sc">.</span>machine<span class="sc">}</span><span class="ss">)"</span></span>
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<span id="cb4-14"><a href="#cb4-14" aria-hidden="true" tabindex="-1"></a> </span>
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<span id="cb4-15"><a href="#cb4-15" aria-hidden="true" tabindex="-1"></a> <span class="kw">def</span> is_compatible(<span class="va">self</span>):</span>
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<span id="cb4-16"><a href="#cb4-16" aria-hidden="true" tabindex="-1"></a> <span class="co">"""Check if system meets minimum requirements."""</span></span>
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<span id="cb4-17"><a href="#cb4-17" aria-hidden="true" tabindex="-1"></a> <span class="cf">return</span> <span class="va">self</span>.python_version <span class="op">>=</span> (<span class="dv">3</span>, <span class="dv">8</span>)</span></code><button title="Copy to Clipboard" class="code-copy-button"><i class="bi"></i></button></pre></div>
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<p>:::</p>
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<div id="cell-7" class="cell">
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<div class="sourceCode cell-code" id="cb5"><pre class="sourceCode python code-with-copy"><code class="sourceCode python"><span id="cb5-1"><a href="#cb5-1" aria-hidden="true" tabindex="-1"></a><span class="co"># Test the SystemInfo class</span></span>
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<span id="cb5-2"><a href="#cb5-2" aria-hidden="true" tabindex="-1"></a>info <span class="op">=</span> SystemInfo()</span>
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<span id="cb5-3"><a href="#cb5-3" aria-hidden="true" tabindex="-1"></a><span class="bu">print</span>(<span class="ss">f"System: </span><span class="sc">{</span>info<span class="sc">}</span><span class="ss">"</span>)</span>
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<span id="cb5-4"><a href="#cb5-4" aria-hidden="true" tabindex="-1"></a><span class="bu">print</span>(<span class="ss">f"Compatible: </span><span class="sc">{</span>info<span class="sc">.</span>is_compatible()<span class="sc">}</span><span class="ss">"</span>)</span></code><button title="Copy to Clipboard" class="code-copy-button"><i class="bi"></i></button></pre></div>
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</div>
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</section>
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<section id="step-3-try-the-export-process" class="level2">
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<h2 class="anchored" data-anchor-id="step-3-try-the-export-process">Step 3: Try the Export Process</h2>
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<p>Now let’s export our code! In your terminal, run:</p>
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<div class="sourceCode" id="cb6"><pre class="sourceCode bash code-with-copy"><code class="sourceCode bash"><span id="cb6-1"><a href="#cb6-1" aria-hidden="true" tabindex="-1"></a><span class="ex">python</span> bin/tito.py sync <span class="at">--module</span> setup</span></code><button title="Copy to Clipboard" class="code-copy-button"><i class="bi"></i></button></pre></div>
|
||||
<p>This will export the code marked with <code>#| export</code> to <code>tinytorch/core/utils.py</code>.</p>
|
||||
<p><strong>What happens during export:</strong> 1. nbdev scans this notebook for <code>#| export</code> cells 2. Extracts the Python code<br>
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3. Writes it to <code>tinytorch/core/utils.py</code> (because of <code>#| default_exp core.utils</code>) 4. Handles imports and dependencies automatically</p>
|
||||
<p><strong>🔍 Verification</strong>: After export, check <code>tinytorch/core/utils.py</code> - you’ll see your functions there with auto-generated headers pointing back to this notebook!</p>
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||||
</section>
|
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<section id="step-4-run-tests" class="level2">
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||||
<h2 class="anchored" data-anchor-id="step-4-run-tests">Step 4: Run Tests</h2>
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||||
<p>After exporting, run the tests:</p>
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||||
<div class="sourceCode" id="cb7"><pre class="sourceCode bash code-with-copy"><code class="sourceCode bash"><span id="cb7-1"><a href="#cb7-1" aria-hidden="true" tabindex="-1"></a><span class="ex">python</span> bin/tito.py test <span class="at">--module</span> setup</span></code><button title="Copy to Clipboard" class="code-copy-button"><i class="bi"></i></button></pre></div>
|
||||
<p>This will run all tests for the setup module and verify your implementation works correctly.</p>
|
||||
</section>
|
||||
<section id="step-5-check-your-progress" class="level2">
|
||||
<h2 class="anchored" data-anchor-id="step-5-check-your-progress">Step 5: Check Your Progress</h2>
|
||||
<p>See your overall progress:</p>
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||||
<div class="sourceCode" id="cb8"><pre class="sourceCode bash code-with-copy"><code class="sourceCode bash"><span id="cb8-1"><a href="#cb8-1" aria-hidden="true" tabindex="-1"></a><span class="ex">python</span> bin/tito.py info</span></code><button title="Copy to Clipboard" class="code-copy-button"><i class="bi"></i></button></pre></div>
|
||||
<p>This shows which modules are complete and which are pending.</p>
|
||||
</section>
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||||
<section id="congratulations" class="level2">
|
||||
<h2 class="anchored" data-anchor-id="congratulations">🎉 Congratulations!</h2>
|
||||
<p>You’ve learned the TinyTorch development workflow:</p>
|
||||
<ol type="1">
|
||||
<li>✅ Write code in notebooks with <code>#| export</code></li>
|
||||
<li>✅ Export with <code>tito sync</code><br>
|
||||
</li>
|
||||
<li>✅ Test with <code>tito test --module setup</code></li>
|
||||
<li>✅ Check progress with <code>tito info</code></li>
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||||
</ol>
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||||
<p><strong>This is the rhythm you’ll use for every module in TinyTorch.</strong></p>
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||||
<section id="next-steps" class="level3">
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||||
<h3 class="anchored" data-anchor-id="next-steps">Next Steps</h3>
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||||
<p>Ready for the real work? Head to <strong>Module 1: Tensor</strong> where you’ll build the core data structures that power everything else in TinyTorch.</p>
|
||||
<p><strong>Development Tips:</strong> - Always test your code in the notebook first - Export frequently to catch issues early<br>
|
||||
- Read error messages carefully - they’re designed to help - When stuck, check if your code exports cleanly first</p>
|
||||
<p>Happy building! 🔥</p>
|
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</section>
|
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</section>
|
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</section>
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</main>
|
||||
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const id = hash.replace(/^#\/?/, "");
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if (note !== null) {
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try {
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const html = processXRef(id, note.cloneNode(true));
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instance.setContent(html);
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// See if we can fetch this
|
||||
fetch(url.split('#')[0])
|
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.then(res => res.text())
|
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.then(html => {
|
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const parser = new DOMParser();
|
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||||
// This is a special case and we should probably do some content thinning / targeting
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||||
fetch(url)
|
||||
.then(res => res.text())
|
||||
.then(html => {
|
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const parser = new DOMParser();
|
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const htmlDoc = parser.parseFromString(html, "text/html");
|
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const note = htmlDoc.querySelector('main.content');
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||||
if (note !== null) {
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||||
// This should only happen for chapter cross references
|
||||
// (since there is no id in the URL)
|
||||
// remove the first header
|
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if (note.children.length > 0 && note.children[0].tagName === "HEADER") {
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instance.show();
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const selector = 'span[' + cellAttr + '][' + lineAttr + ']';
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return selector;
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}
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const lines = annoteSpan.getAttribute("data-code-lines").split(",");
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return targetCell + "-" + line;
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height = el.offsetHeight;
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parent = el.parentElement.parentElement;
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if (top !== null && height !== null && parent !== null) {
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// cook up a div (if necessary) and position it
|
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let div = window.document.getElementById("code-annotation-line-highlight");
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if (div === null) {
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div = window.document.createElement("div");
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div.setAttribute("id", "code-annotation-line-highlight");
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div.style.position = 'absolute';
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parent.appendChild(div);
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}
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div.style.top = top - 2 + "px";
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div.style.height = height + 4 + "px";
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div.style.left = 0;
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let gutterDiv = window.document.getElementById("code-annotation-line-highlight-gutter");
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if (gutterDiv === null) {
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gutterDiv = window.document.createElement("div");
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gutterDiv.setAttribute("id", "code-annotation-line-highlight-gutter");
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gutterDiv.style.position = 'absolute';
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const codeCell = window.document.getElementById(targetCell);
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const gutter = codeCell.querySelector('.code-annotation-gutter');
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gutter.appendChild(gutterDiv);
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}
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gutterDiv.style.top = top - 2 + "px";
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const elementsIds = ["code-annotation-line-highlight", "code-annotation-line-highlight-gutter"];
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const div = window.document.getElementById(elId);
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if (div) {
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}
|
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});
|
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selectedAnnoteEl = undefined;
|
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};
|
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// Handle positioning of the toggle
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window.addEventListener(
|
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"resize",
|
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throttle(() => {
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elRect = undefined;
|
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if (selectedAnnoteEl) {
|
||||
selectCodeLines(selectedAnnoteEl);
|
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}
|
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}, 10)
|
||||
);
|
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function throttle(fn, ms) {
|
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let throttle = false;
|
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let timer;
|
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return (...args) => {
|
||||
if(!throttle) { // first call gets through
|
||||
fn.apply(this, args);
|
||||
throttle = true;
|
||||
} else { // all the others get throttled
|
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if(timer) clearTimeout(timer); // cancel #2
|
||||
timer = setTimeout(() => {
|
||||
fn.apply(this, args);
|
||||
timer = throttle = false;
|
||||
}, ms);
|
||||
}
|
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};
|
||||
}
|
||||
// Attach click handler to the DT
|
||||
const annoteDls = window.document.querySelectorAll('dt[data-target-cell]');
|
||||
for (const annoteDlNode of annoteDls) {
|
||||
annoteDlNode.addEventListener('click', (event) => {
|
||||
const clickedEl = event.target;
|
||||
if (clickedEl !== selectedAnnoteEl) {
|
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unselectCodeLines();
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const activeEl = window.document.querySelector('dt[data-target-cell].code-annotation-active');
|
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if (activeEl) {
|
||||
activeEl.classList.remove('code-annotation-active');
|
||||
}
|
||||
selectCodeLines(clickedEl);
|
||||
clickedEl.classList.add('code-annotation-active');
|
||||
} else {
|
||||
// Unselect the line
|
||||
unselectCodeLines();
|
||||
clickedEl.classList.remove('code-annotation-active');
|
||||
}
|
||||
});
|
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|
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const findCites = (el) => {
|
||||
const parentEl = el.parentElement;
|
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if (parentEl) {
|
||||
const cites = parentEl.dataset.cites;
|
||||
if (cites) {
|
||||
return {
|
||||
el,
|
||||
cites: cites.split(' ')
|
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};
|
||||
} else {
|
||||
return findCites(el.parentElement)
|
||||
}
|
||||
} else {
|
||||
return undefined;
|
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}
|
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};
|
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var bibliorefs = window.document.querySelectorAll('a[role="doc-biblioref"]');
|
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for (var i=0; i<bibliorefs.length; i++) {
|
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const ref = bibliorefs[i];
|
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const citeInfo = findCites(ref);
|
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if (citeInfo) {
|
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tippyHover(citeInfo.el, function() {
|
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var popup = window.document.createElement('div');
|
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citeInfo.cites.forEach(function(cite) {
|
||||
var citeDiv = window.document.createElement('div');
|
||||
citeDiv.classList.add('hanging-indent');
|
||||
citeDiv.classList.add('csl-entry');
|
||||
var biblioDiv = window.document.getElementById('ref-' + cite);
|
||||
if (biblioDiv) {
|
||||
citeDiv.innerHTML = biblioDiv.innerHTML;
|
||||
}
|
||||
popup.appendChild(citeDiv);
|
||||
});
|
||||
return popup.innerHTML;
|
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});
|
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}
|
||||
}
|
||||
});
|
||||
</script>
|
||||
</div> <!-- /content -->
|
||||
|
||||
|
||||
|
||||
|
||||
</body></html>
|
||||
@@ -103,10 +103,10 @@ Once you implement the functions above, run this cell to test them:
|
||||
# Test the functions in the notebook (will fail until implemented)
|
||||
try:
|
||||
print("Testing hello_tinytorch():")
|
||||
print(hello_tinytorch())
|
||||
print(hello_tinytorch())
|
||||
print()
|
||||
print("Testing add_numbers():")
|
||||
print(f"2 + 3 = {add_numbers(2, 3)}")
|
||||
print(f"2 + 3 = {add_numbers(2, 3)}")
|
||||
except NotImplementedError as e:
|
||||
print(f"⚠️ {e}")
|
||||
print("Implement the functions above first!")
|
||||
@@ -180,9 +180,9 @@ Once you implement the SystemInfo class above, run this cell to test it:
|
||||
# Test the SystemInfo class (will fail until implemented)
|
||||
try:
|
||||
print("Testing SystemInfo class:")
|
||||
info = SystemInfo()
|
||||
print(f"System: {info}")
|
||||
print(f"Compatible: {info.is_compatible()}")
|
||||
info = SystemInfo()
|
||||
print(f"System: {info}")
|
||||
print(f"Compatible: {info.is_compatible()}")
|
||||
except NotImplementedError as e:
|
||||
print(f"⚠️ {e}")
|
||||
print("Implement the SystemInfo class above first!")
|
||||
|
||||
311
modules/tensor/tests/test_tensor.py
Normal file
311
modules/tensor/tests/test_tensor.py
Normal file
@@ -0,0 +1,311 @@
|
||||
"""
|
||||
Tests for TinyTorch Tensor module.
|
||||
|
||||
Tests the core tensor functionality including creation, arithmetic operations,
|
||||
utility methods, and edge cases.
|
||||
"""
|
||||
|
||||
import sys
|
||||
import os
|
||||
import pytest
|
||||
import numpy as np
|
||||
|
||||
# Add project root to path for imports
|
||||
project_root = os.path.abspath(os.path.join(os.path.dirname(__file__), '..', '..'))
|
||||
sys.path.insert(0, project_root)
|
||||
|
||||
from tinytorch.core.tensor import Tensor
|
||||
|
||||
class TestTensorCreation:
|
||||
"""Test tensor creation from different data types."""
|
||||
|
||||
def test_scalar_creation(self):
|
||||
"""Test creating tensors from scalars."""
|
||||
# Float scalar
|
||||
t1 = Tensor(5.0)
|
||||
assert t1.shape == ()
|
||||
assert t1.size == 1
|
||||
assert t1.item() == 5.0
|
||||
|
||||
# Integer scalar
|
||||
t2 = Tensor(42)
|
||||
assert t2.shape == ()
|
||||
assert t2.size == 1
|
||||
assert t2.item() == 42.0 # Should convert to float32
|
||||
|
||||
def test_vector_creation(self):
|
||||
"""Test creating 1D tensors."""
|
||||
t = Tensor([1, 2, 3, 4])
|
||||
assert t.shape == (4,)
|
||||
assert t.size == 4
|
||||
assert t.dtype == np.int32 # Integer list defaults to int32
|
||||
np.testing.assert_array_equal(t.numpy(), [1, 2, 3, 4])
|
||||
|
||||
def test_matrix_creation(self):
|
||||
"""Test creating 2D tensors."""
|
||||
t = Tensor([[1, 2], [3, 4]])
|
||||
assert t.shape == (2, 2)
|
||||
assert t.size == 4
|
||||
expected = np.array([[1.0, 2.0], [3.0, 4.0]], dtype='float32')
|
||||
np.testing.assert_array_equal(t.numpy(), expected)
|
||||
|
||||
def test_numpy_array_creation(self):
|
||||
"""Test creating tensors from numpy arrays."""
|
||||
arr = np.array([1, 2, 3], dtype='int32')
|
||||
t = Tensor(arr)
|
||||
assert t.shape == (3,)
|
||||
assert t.dtype in ['int32', 'float32'] # May convert
|
||||
|
||||
def test_dtype_specification(self):
|
||||
"""Test explicit dtype specification."""
|
||||
t = Tensor([1, 2, 3], dtype='int32')
|
||||
assert t.dtype == np.int32
|
||||
|
||||
def test_invalid_data_type(self):
|
||||
"""Test error handling for invalid data types."""
|
||||
with pytest.raises(TypeError):
|
||||
Tensor("invalid")
|
||||
with pytest.raises(TypeError):
|
||||
Tensor({"dict": "invalid"})
|
||||
|
||||
class TestTensorProperties:
|
||||
"""Test tensor properties and methods."""
|
||||
|
||||
def test_shape_property(self):
|
||||
"""Test shape property for different dimensions."""
|
||||
assert Tensor(5).shape == ()
|
||||
assert Tensor([1, 2, 3]).shape == (3,)
|
||||
assert Tensor([[1, 2], [3, 4]]).shape == (2, 2)
|
||||
assert Tensor([[[1]]]).shape == (1, 1, 1)
|
||||
|
||||
def test_size_property(self):
|
||||
"""Test size property."""
|
||||
assert Tensor(5).size == 1
|
||||
assert Tensor([1, 2, 3]).size == 3
|
||||
assert Tensor([[1, 2], [3, 4]]).size == 4
|
||||
assert Tensor([[[1, 2], [3, 4]], [[5, 6], [7, 8]]]).size == 8
|
||||
|
||||
def test_dtype_property(self):
|
||||
"""Test dtype property."""
|
||||
t1 = Tensor(5.0)
|
||||
assert t1.dtype == np.float32
|
||||
|
||||
t2 = Tensor([1, 2, 3], dtype='int32')
|
||||
assert t2.dtype == np.int32
|
||||
|
||||
def test_repr(self):
|
||||
"""Test string representation."""
|
||||
t = Tensor([1, 2, 3])
|
||||
repr_str = repr(t)
|
||||
assert 'Tensor' in repr_str
|
||||
assert 'shape=' in repr_str
|
||||
assert 'dtype=' in repr_str
|
||||
|
||||
class TestArithmeticOperations:
|
||||
"""Test tensor arithmetic operations."""
|
||||
|
||||
def test_tensor_addition(self):
|
||||
"""Test tensor + tensor addition."""
|
||||
a = Tensor([1, 2, 3])
|
||||
b = Tensor([4, 5, 6])
|
||||
result = a + b
|
||||
expected = [5.0, 7.0, 9.0]
|
||||
np.testing.assert_array_equal(result.numpy(), expected)
|
||||
|
||||
def test_scalar_addition(self):
|
||||
"""Test tensor + scalar addition."""
|
||||
a = Tensor([1, 2, 3])
|
||||
result = a + 10
|
||||
expected = [11.0, 12.0, 13.0]
|
||||
np.testing.assert_array_equal(result.numpy(), expected)
|
||||
|
||||
def test_reverse_addition(self):
|
||||
"""Test scalar + tensor addition."""
|
||||
a = Tensor([1, 2, 3])
|
||||
result = 10 + a
|
||||
expected = [11.0, 12.0, 13.0]
|
||||
np.testing.assert_array_equal(result.numpy(), expected)
|
||||
|
||||
def test_tensor_subtraction(self):
|
||||
"""Test tensor - tensor subtraction."""
|
||||
a = Tensor([5, 7, 9])
|
||||
b = Tensor([1, 2, 3])
|
||||
result = a - b
|
||||
expected = [4.0, 5.0, 6.0]
|
||||
np.testing.assert_array_equal(result.numpy(), expected)
|
||||
|
||||
def test_scalar_subtraction(self):
|
||||
"""Test tensor - scalar subtraction."""
|
||||
a = Tensor([10, 20, 30])
|
||||
result = a - 5
|
||||
expected = [5.0, 15.0, 25.0]
|
||||
np.testing.assert_array_equal(result.numpy(), expected)
|
||||
|
||||
def test_tensor_multiplication(self):
|
||||
"""Test tensor * tensor multiplication."""
|
||||
a = Tensor([2, 3, 4])
|
||||
b = Tensor([5, 6, 7])
|
||||
result = a * b
|
||||
expected = [10.0, 18.0, 28.0]
|
||||
np.testing.assert_array_equal(result.numpy(), expected)
|
||||
|
||||
def test_scalar_multiplication(self):
|
||||
"""Test tensor * scalar multiplication."""
|
||||
a = Tensor([1, 2, 3])
|
||||
result = a * 3
|
||||
expected = [3.0, 6.0, 9.0]
|
||||
np.testing.assert_array_equal(result.numpy(), expected)
|
||||
|
||||
def test_reverse_multiplication(self):
|
||||
"""Test scalar * tensor multiplication."""
|
||||
a = Tensor([1, 2, 3])
|
||||
result = 3 * a
|
||||
expected = [3.0, 6.0, 9.0]
|
||||
np.testing.assert_array_equal(result.numpy(), expected)
|
||||
|
||||
def test_tensor_division(self):
|
||||
"""Test tensor / tensor division."""
|
||||
a = Tensor([6, 8, 10])
|
||||
b = Tensor([2, 4, 5])
|
||||
result = a / b
|
||||
expected = [3.0, 2.0, 2.0]
|
||||
np.testing.assert_array_equal(result.numpy(), expected)
|
||||
|
||||
def test_scalar_division(self):
|
||||
"""Test tensor / scalar division."""
|
||||
a = Tensor([6, 8, 10])
|
||||
result = a / 2
|
||||
expected = [3.0, 4.0, 5.0]
|
||||
np.testing.assert_array_equal(result.numpy(), expected)
|
||||
|
||||
class TestUtilityMethods:
|
||||
"""Test tensor utility methods."""
|
||||
|
||||
def test_reshape(self):
|
||||
"""Test tensor reshaping."""
|
||||
t = Tensor([[1, 2], [3, 4]])
|
||||
reshaped = t.reshape(4)
|
||||
assert reshaped.shape == (4,)
|
||||
expected = [1.0, 2.0, 3.0, 4.0]
|
||||
np.testing.assert_array_equal(reshaped.numpy(), expected)
|
||||
|
||||
# Reshape to 2D
|
||||
reshaped2 = t.reshape(1, 4)
|
||||
assert reshaped2.shape == (1, 4)
|
||||
|
||||
def test_transpose(self):
|
||||
"""Test tensor transpose."""
|
||||
t = Tensor([[1, 2, 3], [4, 5, 6]])
|
||||
transposed = t.transpose()
|
||||
assert transposed.shape == (3, 2)
|
||||
expected = [[1.0, 4.0], [2.0, 5.0], [3.0, 6.0]]
|
||||
np.testing.assert_array_equal(transposed.numpy(), expected)
|
||||
|
||||
def test_sum_all(self):
|
||||
"""Test summing all elements."""
|
||||
t = Tensor([[1, 2], [3, 4]])
|
||||
result = t.sum()
|
||||
assert result.item() == 10.0
|
||||
|
||||
def test_sum_axis(self):
|
||||
"""Test summing along specific axes."""
|
||||
t = Tensor([[1, 2], [3, 4]])
|
||||
|
||||
# Sum along axis 0 (columns)
|
||||
sum0 = t.sum(axis=0)
|
||||
expected0 = [4.0, 6.0]
|
||||
np.testing.assert_array_equal(sum0.numpy(), expected0)
|
||||
|
||||
# Sum along axis 1 (rows)
|
||||
sum1 = t.sum(axis=1)
|
||||
expected1 = [3.0, 7.0]
|
||||
np.testing.assert_array_equal(sum1.numpy(), expected1)
|
||||
|
||||
def test_mean(self):
|
||||
"""Test mean calculation."""
|
||||
t = Tensor([[1, 2], [3, 4]])
|
||||
result = t.mean()
|
||||
assert result.item() == 2.5
|
||||
|
||||
def test_max(self):
|
||||
"""Test maximum value."""
|
||||
t = Tensor([[1, 2], [3, 4]])
|
||||
result = t.max()
|
||||
assert result.item() == 4.0
|
||||
|
||||
def test_min(self):
|
||||
"""Test minimum value."""
|
||||
t = Tensor([[1, 2], [3, 4]])
|
||||
result = t.min()
|
||||
assert result.item() == 1.0
|
||||
|
||||
def test_item_scalar(self):
|
||||
"""Test converting single-element tensor to scalar."""
|
||||
t = Tensor(42.0)
|
||||
assert t.item() == 42.0
|
||||
|
||||
# Single element tensor from computation
|
||||
t2 = Tensor([5]).sum()
|
||||
assert t2.item() == 5.0
|
||||
|
||||
def test_item_error(self):
|
||||
"""Test item() error for multi-element tensors."""
|
||||
t = Tensor([1, 2, 3])
|
||||
with pytest.raises(ValueError):
|
||||
t.item()
|
||||
|
||||
def test_numpy_conversion(self):
|
||||
"""Test converting tensor to numpy array."""
|
||||
t = Tensor([[1, 2], [3, 4]])
|
||||
arr = t.numpy()
|
||||
assert isinstance(arr, np.ndarray)
|
||||
assert arr.shape == (2, 2)
|
||||
expected = [[1.0, 2.0], [3.0, 4.0]]
|
||||
np.testing.assert_array_equal(arr, expected)
|
||||
|
||||
class TestEdgeCases:
|
||||
"""Test edge cases and error conditions."""
|
||||
|
||||
def test_empty_list(self):
|
||||
"""Test creating tensor from empty list."""
|
||||
t = Tensor([])
|
||||
assert t.shape == (0,)
|
||||
assert t.size == 0
|
||||
|
||||
def test_mixed_operations(self):
|
||||
"""Test combining different operations."""
|
||||
a = Tensor([[1, 2], [3, 4]])
|
||||
b = Tensor([[2, 2], [2, 2]])
|
||||
|
||||
# Complex expression
|
||||
result = (a + b) * 2 - 1
|
||||
expected = [[5.0, 7.0], [9.0, 11.0]]
|
||||
np.testing.assert_array_equal(result.numpy(), expected)
|
||||
|
||||
def test_chained_operations(self):
|
||||
"""Test chaining multiple operations."""
|
||||
t = Tensor([[1, 2, 3], [4, 5, 6]])
|
||||
result = t.sum(axis=1).mean()
|
||||
# Row sums: [6, 15], mean: 10.5
|
||||
assert result.item() == 10.5
|
||||
|
||||
def run_tensor_tests():
|
||||
"""Run all tensor tests and return results."""
|
||||
print("🧪 Running Tensor module tests...")
|
||||
|
||||
# Run tests using pytest
|
||||
test_results = pytest.main([
|
||||
__file__,
|
||||
"-v",
|
||||
"--tb=short"
|
||||
])
|
||||
|
||||
return test_results == 0
|
||||
|
||||
if __name__ == "__main__":
|
||||
success = run_tensor_tests()
|
||||
if success:
|
||||
print("✅ All tensor tests passed!")
|
||||
else:
|
||||
print("❌ Some tensor tests failed!")
|
||||
sys.exit(1)
|
||||
Reference in New Issue
Block a user