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.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=19910318&assignment_repo_type=AssignmentRepo)
 # MiniTorch Module 0
 
 <img src="https://minitorch.github.io/minitorch.svg" width="50%">

minitorch/datasets.py

@@ -67,19 +67,29 @@ def circle(N):
 
 
 def spiral(N):
-
     def x(t):
         return t * math.cos(t) / 20.0
 
     def y(t):
         return t * math.sin(t) / 20.0
-    X = [(x(10.0 * (float(i) / (N // 2))) + 0.5, y(10.0 * (float(i) / (N //
-        2))) + 0.5) for i in range(5 + 0, 5 + N // 2)]
-    X = X + [(y(-10.0 * (float(i) / (N // 2))) + 0.5, x(-10.0 * (float(i) /
-        (N // 2))) + 0.5) for i in range(5 + 0, 5 + N // 2)]
+
+    X = [
+        (x(10.0 * (float(i) / (N // 2))) + 0.5, y(10.0 * (float(i) / (N // 2))) + 0.5)
+        for i in range(5 + 0, 5 + N // 2)
+    ]
+    X = X + [
+        (y(-10.0 * (float(i) / (N // 2))) + 0.5, x(-10.0 * (float(i) / (N // 2))) + 0.5)
+        for i in range(5 + 0, 5 + N // 2)
+    ]
     y2 = [0] * (N // 2) + [1] * (N // 2)
     return Graph(N, X, y2)
 
 
-datasets = {'Simple': simple, 'Diag': diag, 'Split': split, 'Xor': xor,
-    'Circle': circle, 'Spiral': spiral}
+datasets = {
+    "Simple": simple,
+    "Diag": diag,
+    "Split": split,
+    "Xor": xor,
+    "Circle": circle,
+    "Spiral": spiral,
+}

minitorch/operators.py

@@ -32,7 +32,71 @@
 # $f(x) = |x - y| < 1e-2$
 
 
-# TODO: Implement for Task 0.1.
+def mul(x: float, y: float) -> float:
+    return x * y
+
+
+def id(x: float) -> float:
+    return x
+
+
+def add(x: float, y: float) -> float:
+    return x + y
+
+
+def neg(x: float) -> float:
+    return -x
+
+
+def lt(x: float, y: float) -> bool:
+    return x < y
+
+
+def eq(x: float, y: float) -> bool:
+    return x == y
+
+
+def max(x: float, y: float) -> float:
+    return x if x > y else y
+
+
+def is_close(x: float, y: float) -> bool:
+    return abs(x - y) < 1e-2
+
+
+def sigmoid(x: float) -> float:
+    if x >= 0:
+        return 1.0 / (1.0 + math.exp(-x))
+    else:
+        return math.exp(x) / (1.0 + math.exp(x))
+
+
+def relu(x: float) -> float:
+    return x if x > 0 else 0.0
+
+
+def log(x: float) -> float:
+    return math.log(x)
+
+
+def exp(x: float) -> float:
+    return math.exp(x)
+
+
+def log_back(x: float, y: float) -> float:
+    return y / x
+
+
+def inv(x: float) -> float:
+    return 1.0 / x
+
+
+def inv_back(x: float, y: float) -> float:
+    return -y / (x * x)
+
+
+def relu_back(x: float, y: float) -> float:
+    return y if x > 0 else 0.0
 
 
 # ## Task 0.3
@@ -51,4 +115,36 @@
 # - prod: take the product of lists
 
 
-# TODO: Implement for Task 0.3.
+def map(fn: Callable[[float], float], ls: Iterable[float]) -> Iterable[float]:
+    return [fn(x) for x in ls]
+
+
+def zipWith(
+    fn: Callable[[float, float], float], ls1: Iterable[float], ls2: Iterable[float]
+) -> Iterable[float]:
+    return [fn(x, y) for x, y in zip(ls1, ls2)]
+
+
+def reduce(
+    fn: Callable[[float, float], float], ls: Iterable[float], start: float
+) -> float:
+    res = start
+    for x in ls:
+        res = fn(res, x)
+    return res
+
+
+def negList(ls: Iterable[float]) -> Iterable[float]:
+    return map(neg, ls)
+
+
+def addLists(ls1: Iterable[float], ls2: Iterable[float]) -> Iterable[float]:
+    return zipWith(add, ls1, ls2)
+
+
+def sum(ls: Iterable[float]) -> float:
+    return reduce(add, ls, 0.0)
+
+
+def prod(ls: Iterable[float]) -> float:
+    return reduce(mul, ls, 1.0)

tests/test_operators.py

@@ -107,41 +107,42 @@ def test_sigmoid(a: float) -> None:
     * 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")
+    assert 0.0 <= sigmoid(a) <= 1.0
+    assert_close(sigmoid(-a), 1.0 - sigmoid(a))
+    assert_close(sigmoid(0.0), 0.5)
+    assert sigmoid(a) >= sigmoid(a - 1.0)
 
 
 @pytest.mark.task0_2
 @given(small_floats, small_floats, small_floats)
 def test_transitive(a: float, b: float, c: float) -> None:
     """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")
+    if lt(a, b) and lt(b, c):
+        assert lt(a, c)
 
 
 @pytest.mark.task0_2
-def test_symmetric() -> None:
+@given(small_floats, small_floats)
+def test_symmetric(a: float, b: float) -> None:
     """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")
+    assert_close(mul(a, b), mul(b, a))
 
 
 @pytest.mark.task0_2
-def test_distribute() -> None:
+@given(small_floats, small_floats, small_floats)
+def test_distribute(x: float, y: float, z: float) -> None:
     r"""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")
+    assert_close(mul(z, add(x, y)), add(mul(z, x), mul(z, y)))
 
 
 @pytest.mark.task0_2
 def test_other() -> None:
     """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")
+    assert_close(mul(0.0, 0.0), 0.0)
 
 
 # ## Task 0.3  - Higher-order functions
@@ -168,8 +169,7 @@ def test_sum_distribute(ls1: List[float], ls2: List[float]) -> None:
     """Write a test that ensures that the sum of `ls1` plus the sum of `ls2`
     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")
+    assert_close(sum(addLists(ls1, ls2)), sum(ls1) + sum(ls2))
 
 
 @pytest.mark.task0_3