feat: working matrix inverse (not integrated)

examples/linear_regression/nada-project.toml

@@ -2,6 +2,9 @@ name = "linear-regression"
 version = "0.1.0"
 authors = [""]
 
+[test_framework.nada-test]
+command = "nada-test ./tests"
+
 [[programs]]
 path = "src/linear_regression.py"
 prime_size = 64

examples/linear_regression/src/matrix_inverse.py

@@ -40,7 +40,7 @@ def public_modular_inverse(
     power = value ** Integer(
         mod - 1
     )  # value ** modulo = value ** (modulo // 2)  * modulo ** (modulo // 2)
-    power = power * power * value if rem else Integer(1)  # value ** mo
+    power = power * power * (value if rem else Integer(1))  # value ** mo
     return power
 
 
@@ -133,14 +133,7 @@ def gauss_jordan_zn(mat: na.NadaArray, modulo: int):
 
     # Forward elimination
     for i in range(rows):
-        # # Find pivot row
-        # pivot_row = i
-        # while pivot_row < rows and (mat[pivot_row][i] == Integer(0)) is Boolean(True):
-        #     pivot_row += 1
-
-        # # Swap pivot row with current row
-        # mat[[i, pivot_row]] = mat[[pivot_row, i]]
-
+
         # Scale pivot row to have leading 1
         diagonal_element = mat[i][i]
         pivot_inv = public_modular_inverse(diagonal_element, modulo)
@@ -186,7 +179,7 @@ def matrix_inverse(matrix: np.ndarray, modulo: int):
 def nada_main():
     parties = na.parties(3)
 
-    A = na.array([4, 4], parties[0], "A", nada_type=SecretInteger)
+    A = na.array([10, 10], parties[0], "A", nada_type=SecretInteger)
     A_inv = matrix_inverse(A, PRIME)
 
     result = A @ A_inv

examples/linear_regression/tests/matrix_inverse.py

@@ -0,0 +1,24 @@
+from nada_test import nada_test, NadaTest
+import sys
+import nada_numpy.client as  na
+import numpy as np
+
+# Functional style test
+@nada_test(program="matrix_inverse")
+def my_test():
+    n = 10
+    m = np.random.rand(n, n)
+    mx = np.sum(np.abs(m), axis=1)
+    np.fill_diagonal(m, mx)
+    A = na.array(m * (1 << 16), "A", nada_type=int)
+    print("INPUTS:", A, file=sys.stderr)
+    outputs = yield A
+    print(outputs, file=sys.stderr)
+    for output, value in outputs.items():
+        output = output.split("_")
+        if output[-1] == output[-2]:
+            assert value == 1, f"Expected 1 {output}, got {value}"
+        else:
+            assert value == 0, f"Expected 0 {output}, got {value}"
+
+    #assert outputs["my_output"] == a + b

pyproject.toml

@@ -14,6 +14,7 @@ nillion-python-helpers = "^0.3.0"
 black = {version="24.8.0", optional=true}
 isort = {version="^5.13.2", optional=true}
 scikit-learn = {version="^1.5.1", optional=true}
+nada-test = "^0.6.0"
 
 [tool.poetry.group.dev.dependencies]
 pytest = "^8.2.0"

tests/test_all.py

@@ -69,7 +69,7 @@
     ("linear_regression", "determinant", "determinant_2"),
     ("linear_regression", "determinant", "determinant_3"),
     ("linear_regression", "gauss_jordan", "gauss_jordan"),
-    ("linear_regression", "matrix_inverse", "matrix_inverse"),
+    ("linear_regression", "matrix_inverse", "nada-test::matrix_inverse.py:my_test"),
     ("linear_regression", "linear_regression", "linear_regression"),
     ("linear_regression", "linear_regression", "linear_regression_1"),
     ("linear_regression", "linear_regression", "linear_regression_2"),