GitHub Classroom Autograding Workflow

.github/workflows/classroom.yml

@@ -0,0 +1,61 @@
+name: Autograding Tests
+'on':
+- push
+- 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: grade1
+      id: grade1
+      uses: classroom-resources/autograding-command-grader@v1
+      with:
+        test-name: grade1
+        setup-command: pip install pytest numpy
+        command: pytest grade_task1.py
+        timeout: 2
+        max-score: 1
+    - name: grade2
+      id: grade2
+      uses: classroom-resources/autograding-command-grader@v1
+      with:
+        test-name: grade2
+        setup-command: pip install numpy pytest
+        command: pytest grade_task2.py
+        timeout: 2
+        max-score: 1
+    - name: grade3
+      id: grade3
+      uses: classroom-resources/autograding-command-grader@v1
+      with:
+        test-name: grade3
+        setup-command: pip install numpy pytest
+        command: pytest grade_task3.py
+        timeout: 2
+        max-score: 1
+    - name: certificate
+      id: certificate
+      uses: classroom-resources/autograding-command-grader@v1
+      with:
+        test-name: certificate
+        setup-command: ''
+        command: if [ -f "certificate.pdf" ]; then echo "File exists"; else echo "File
+          does not exist"; exit 1; fi
+        timeout: 2
+        max-score: 1
+    - name: Autograding Reporter
+      uses: classroom-resources/autograding-grading-reporter@v1
+      env:
+        GRADE1_RESULTS: "${{steps.grade1.outputs.result}}"
+        GRADE2_RESULTS: "${{steps.grade2.outputs.result}}"
+        GRADE3_RESULTS: "${{steps.grade3.outputs.result}}"
+        CERTIFICATE_RESULTS: "${{steps.certificate.outputs.result}}"
+      with:
+        runners: grade1,grade2,grade3,certificate

grade_task2.py

@@ -1,5 +1,5 @@
 import numpy as np
-from tasks import step, ReLU
+from tasks import step, ReLu
 
 
 def test_relu_default_cutoff():

tasks.py

@@ -7,29 +7,38 @@
 # Task 1: 
 # Instructions:
 #Write a function that takes one numeric argument as input. 
-#If the number is larger than zero, the function should return 1, otherwise is should return -1.
+#If the number is larger than zero, the function should return 1, otherwise it should return -1.
 #The name of the function should be step
 
 # Your code here:
 # -----------------------------------------------
 
-def step
-
+def step(num):
+    if num > 0:
+        return 1
+    else:
+        return -1
 
 # -----------------------------------------------
 
 
 # Task 2:
 # Instructions:
 #Write a function that takes in two arguments: a numpy array, and an integer (call argument "cutoff" and set default to 0).
-#The function should return a numpy array of the same length, with all elements smaller than the cutoff being set to cutoff).
+#The function should return a numpy array of the same length, with all elements smaller than the cutoff being set to cutoff.
 #The name of the function should be ReLu
 
 
 # Your code here:
 # -----------------------------------------------
-def ReLu
-
+def ReLu(num, cutoff=0):
+    array = []
+    for i in range(len(num)):
+        if num[i] < cutoff:
+            array.append(cutoff)
+        else:
+            array.append(num[i])
+    return numpy.array(array)
 
 # -----------------------------------------------
 
@@ -44,7 +53,9 @@ def ReLu
 # Your code here:
 # -----------------------------------------------
 
-def neural_net_layer
+def neural_net_layer(array_2_dim, array_1_dim):
+    array = array_2_dim @ array_1_dim
+    return ReLu(array)
 
 
 # ------------------------------------------