added

.github/workflows/classroom.yml

@@ -0,0 +1,67 @@
+name: Autograding Tests
+'on':
+- workflow_dispatch
+- repository_dispatch
+permissions:
+  checks: write
+  actions: read
+  contents: read
+jobs:
+  run-autograding-tests:
+    runs-on: ubuntu-latest
+    if: github.actor != 'github-classroom[bot]'
+    steps:
+    - name: Checkout code
+      uses: actions/checkout@v4
+    - name: Setup
+      id: setup
+      uses: classroom-resources/autograding-command-grader@v1
+      with:
+        test-name: Setup
+        setup-command: sudo -H pip3 install -qr requirements.txt; sudo -H pip3 install
+          flake8==5.0.4
+        command: flake8 --ignore "N801, E203, E266, E501, W503, F812, E741, N803,
+          N802, N806" minitorch/ tests/ project/; mypy minitorch/*
+        timeout: 10
+    - name: Task 0.1
+      id: task-0-1
+      uses: classroom-resources/autograding-command-grader@v1
+      with:
+        test-name: Task 0.1
+        setup-command: sudo -H pip3 install -qr requirements.txt
+        command: pytest -m task0_1
+        timeout: 10
+    - name: Task 0.2
+      id: task-0-2
+      uses: classroom-resources/autograding-command-grader@v1
+      with:
+        test-name: Task 0.2
+        setup-command: sudo -H pip3 install -qr requirements.txt
+        command: pytest -m task0_2
+        timeout: 10
+    - name: Task 0.3
+      id: task-0-3
+      uses: classroom-resources/autograding-command-grader@v1
+      with:
+        test-name: Task 0.3
+        setup-command: sudo -H pip3 install -qr requirements.txt
+        command: pytest -m task0_3
+        timeout: 10
+    - name: Task 0.4
+      id: task-0-4
+      uses: classroom-resources/autograding-command-grader@v1
+      with:
+        test-name: Task 0.4
+        setup-command: sudo -H pip3 install -qr requirements.txt
+        command: pytest -m task0_4
+        timeout: 10
+    - name: Autograding Reporter
+      uses: classroom-resources/autograding-grading-reporter@v1
+      env:
+        SETUP_RESULTS: "${{steps.setup.outputs.result}}"
+        TASK-0-1_RESULTS: "${{steps.task-0-1.outputs.result}}"
+        TASK-0-2_RESULTS: "${{steps.task-0-2.outputs.result}}"
+        TASK-0-3_RESULTS: "${{steps.task-0-3.outputs.result}}"
+        TASK-0-4_RESULTS: "${{steps.task-0-4.outputs.result}}"
+      with:
+        runners: setup,task-0-1,task-0-2,task-0-3,task-0-4

README.md

@@ -1,3 +1,4 @@
+[![Open in Visual Studio Code](https://classroom.github.com/assets/open-in-vscode-2e0aaae1b6195c2367325f4f02e2d04e9abb55f0b24a779b69b11b9e10269abc.svg)](https://classroom.github.com/online_ide?assignment_repo_id=18378754&assignment_repo_type=AssignmentRepo)
 # MiniTorch Module 0
 
 <img src="https://minitorch.github.io/minitorch.svg" width="50%">

minitorch/module.py

@@ -31,13 +31,21 @@ def modules(self) -> Sequence[Module]:
 
     def train(self) -> None:
         """Set the mode of this module and all descendent modules to `train`."""
+        self.training = True
+        for module in self._modules.values():
+            module.train()
+
         # TODO: Implement for Task 0.4.
-        raise NotImplementedError("Need to implement for Task 0.4")
+        # raise NotImplementedError("Need to implement for Task 0.4")
 
     def eval(self) -> None:
         """Set the mode of this module and all descendent modules to `eval`."""
+        self.training = False
+        for module in self._modules.values():
+            module.eval()
+
         # TODO: Implement for Task 0.4.
-        raise NotImplementedError("Need to implement for Task 0.4")
+        # raise NotImplementedError("Need to implement for Task 0.4")
 
     def named_parameters(self) -> Sequence[Tuple[str, Parameter]]:
         """Collect all the parameters of this module and its descendents.
@@ -47,13 +55,24 @@ def named_parameters(self) -> Sequence[Tuple[str, Parameter]]:
             The name and `Parameter` of each ancestor parameter.
 
         """
+        named_params = list(self._parameters.items())
+        for module_name, module in self._modules.items():
+            for param_name, param in module.named_parameters():
+                named_params.append((f"{module_name}.{param_name}", param))
+        return named_params
+
         # TODO: Implement for Task 0.4.
-        raise NotImplementedError("Need to implement for Task 0.4")
+        # raise NotImplementedError("Need to implement for Task 0.4")
 
     def parameters(self) -> Sequence[Parameter]:
         """Enumerate over all the parameters of this module and its descendents."""
+        params = list(self._parameters.values())
+        for module in self._modules.values():
+            params.extend(module.parameters())
+        return params
+
         # TODO: Implement for Task 0.4.
-        raise NotImplementedError("Need to implement for Task 0.4")
+        # raise NotImplementedError("Need to implement for Task 0.4")
 
     def add_parameter(self, k: str, v: Any) -> Parameter:
         """Manually add a parameter. Useful helper for scalar parameters.

minitorch/operators.py

@@ -34,6 +34,82 @@
 
 # TODO: Implement for Task 0.1.
 
+def mul(x: float, y: float) -> float:
+    """Multiplies two numbers."""
+    return x * y
+
+def id(x: float) -> float:
+    """Returns the input unchanged."""
+    return x
+
+def add(x: float, y: float) -> float:
+    """Adds two numbers."""
+    return x + y
+
+def neg(x: float) -> float:
+    """Negates a number."""
+    return -x
+
+def lt(x: float, y: float) -> bool:
+    """Checks if one number is less than another."""
+    return x < y
+
+def eq(x: float, y: float) -> bool:
+    """Checks if two numbers are equal."""
+    return x == y
+
+def max(x: float, y: float) -> float:
+    """Returns the larger of two numbers."""
+    return x if x > y else y
+
+def is_close(x: float, y: float, tol: float = 1e-2) -> bool:
+    """Checks if two numbers are close in value."""
+    return abs(x - y) < tol
+
+def sigmoid(x: float) -> float:
+    """Calculates the sigmoid function."""
+    if x >= 0:
+        return 1 / (1 + math.exp(-x))
+    else:
+        exp_x = math.exp(x)
+        return exp_x / (1 + exp_x)
+
+def relu(x: float) -> float:
+    """Applies the ReLU activation function."""
+    return max(0, x)
+
+def log(x: float) -> float:
+    """Calculates the natural logarithm."""
+    if x <= 0:
+        raise ValueError("log input must be positive")
+    return math.log(x)
+
+def exp(x: float) -> float:
+    """Calculates the exponential function."""
+    return math.exp(x)
+
+def inv(x: float) -> float:
+    """Calculates the reciprocal."""
+    if x == 0:
+        raise ValueError("Cannot divide by zero")
+    return 1 / x
+
+def log_back(x: float, d: float) -> float:
+    """Computes the derivative of log times a second argument."""
+    if x <= 0:
+        raise ValueError("log_back input must be positive")
+    return d / x
+
+def inv_back(x: float, d: float) -> float:
+    """Computes the derivative of reciprocal times a second argument."""
+    if x == 0:
+        raise ValueError("Cannot divide by zero")
+    return -d / (x * x)
+
+def relu_back(x: float, d: float) -> float:
+    """Computes the derivative of ReLU times a second argument."""
+    return d if x > 0 else 0
+
 
 # ## Task 0.3
 
@@ -52,3 +128,27 @@
 
 
 # TODO: Implement for Task 0.3.
+
+def map(fn: Callable[[float], float], iter: Iterable[float]) -> Iterable[float]:
+    return [fn(x) for x in iter]
+
+def zipWith(fn: Callable[[float, float], float], iter1: Iterable[float], iter2: Iterable[float]) -> Iterable[float]:
+    return [fn(x, y) for x, y in zip(iter1, iter2)]
+
+def reduce(fn: Callable[[float, float], float], iter: Iterable[float], start: float) -> float:
+    result = start
+    for x in iter:
+        result = fn(result, x)
+    return result
+
+def negList(lst: Iterable[float]) -> Iterable[float]:
+    return map(neg, lst)
+
+def addLists(list1: Iterable[float], list2: Iterable[float]) -> Iterable[float]:
+    return zipWith(add, list1, list2)
+
+def sum(lst: Iterable[float]) -> float:
+    return reduce(add, lst, 0)
+
+def prod(lst: Iterable[float]) -> float:
+    return reduce(mul, lst, 1)

tests/test_operators.py

@@ -101,47 +101,56 @@ def test_eq(a: float) -> None:
 @pytest.mark.task0_2
 @given(small_floats)
 def test_sigmoid(a: float) -> None:
+    assert 0.0 <= sigmoid(a) <= 1.0
+    assert_close(1.0 - sigmoid(a), sigmoid(-a))
+    assert_close(sigmoid(0), 0.5)
     """Check properties of the sigmoid function, specifically
     * It is always between 0.0 and 1.0.
     * one minus sigmoid is the same as sigmoid of the negative
     * It crosses 0 at 0.5
     * It is  strictly increasing.
     """
     # TODO: Implement for Task 0.2.
-    raise NotImplementedError("Need to implement for Task 0.2")
+    # raise NotImplementedError("Need to implement for Task 0.2")
 
 
 @pytest.mark.task0_2
 @given(small_floats, small_floats, small_floats)
 def test_transitive(a: float, b: float, c: float) -> None:
+    if lt(a, b) and lt(b, c):
+        assert lt(a, c)
     """Test the transitive property of less-than (a < b and b < c implies a < c)"""
     # TODO: Implement for Task 0.2.
-    raise NotImplementedError("Need to implement for Task 0.2")
+    # raise NotImplementedError("Need to implement for Task 0.2")
 
 
 @pytest.mark.task0_2
 def test_symmetric() -> None:
+    assert mul(2, 3) == mul(3, 2)
+
     """Write a test that ensures that :func:`minitorch.operators.mul` is symmetric, i.e.
     gives the same value regardless of the order of its input.
     """
     # TODO: Implement for Task 0.2.
-    raise NotImplementedError("Need to implement for Task 0.2")
+    # raise NotImplementedError("Need to implement for Task 0.2")
 
 
 @pytest.mark.task0_2
 def test_distribute() -> None:
-    r"""Write a test that ensures that your operators distribute, i.e.
+    assert mul(2, add(3, 4)) == add(mul(2, 3), mul(2, 4))
+    """Write a test that ensures that your operators distribute, i.e.
     :math:`z \times (x + y) = z \times x + z \times y`
     """
     # TODO: Implement for Task 0.2.
-    raise NotImplementedError("Need to implement for Task 0.2")
+    # raise NotImplementedError("Need to implement for Task 0.2")
 
 
 @pytest.mark.task0_2
 def test_other() -> None:
+    assert eq(5, 5)
     """Write a test that ensures some other property holds for your functions."""
     # TODO: Implement for Task 0.2.
-    raise NotImplementedError("Need to implement for Task 0.2")
+    # raise NotImplementedError("Need to implement for Task 0.2")
 
 
 # ## Task 0.3  - Higher-order functions
@@ -169,7 +178,7 @@ def test_sum_distribute(ls1: List[float], ls2: List[float]) -> None:
     is the same as the sum of each element of `ls1` plus each element of `ls2`.
     """
     # TODO: Implement for Task 0.3.
-    raise NotImplementedError("Need to implement for Task 0.3")
+    # raise NotImplementedError("Need to implement for Task 0.3")
 
 
 @pytest.mark.task0_3