mlx/python/tests/test_linalg.py
2023-12-26 19:40:34 -08:00

68 lines
2.8 KiB
Python

# Copyright © 2023 Apple Inc.
import itertools
import math
import unittest
import mlx.core as mx
import mlx_tests
import numpy as np
class TestLinalg(mlx_tests.MLXTestCase):
def test_norm(self):
vector_ords = [None, 0.5, 0, 1, 2, 3, -1, float("inf"), -float("inf")]
matrix_ords = [None, "fro", -1, 1, float("inf"), -float("inf")]
for shape in [(3,), (2, 3), (2, 3, 3)]:
x_mx = mx.arange(1, math.prod(shape) + 1).reshape(shape)
x_np = np.arange(1, math.prod(shape) + 1).reshape(shape)
# Test when at least one axis is provided
for num_axes in range(1, len(shape)):
if num_axes == 1:
ords = vector_ords
else:
ords = matrix_ords
for axis in itertools.combinations(range(len(shape)), num_axes):
for keepdims in [True, False]:
for o in ords:
out_np = np.linalg.norm(
x_np, ord=o, axis=axis, keepdims=keepdims
)
out_mx = mx.linalg.norm(
x_mx, ord=o, axis=axis, keepdims=keepdims
)
with self.subTest(
shape=shape, ord=o, axis=axis, keepdims=keepdims
):
self.assertTrue(
np.allclose(out_np, out_mx, atol=1e-5, rtol=1e-6)
)
# Test only ord provided
for shape in [(3,), (2, 3)]:
x_mx = mx.arange(1, math.prod(shape) + 1).reshape(shape)
x_np = np.arange(1, math.prod(shape) + 1).reshape(shape)
for o in [None, 1, -1, float("inf"), -float("inf")]:
for keepdims in [True, False]:
out_np = np.linalg.norm(x_np, ord=o, keepdims=keepdims)
out_mx = mx.linalg.norm(x_mx, ord=o, keepdims=keepdims)
with self.subTest(shape=shape, ord=o, keepdims=keepdims):
self.assertTrue(
np.allclose(out_np, out_mx, atol=1e-5, rtol=1e-6)
)
# Test no ord and no axis provided
for shape in [(3,), (2, 3), (2, 3, 3)]:
x_mx = mx.arange(1, math.prod(shape) + 1).reshape(shape)
x_np = np.arange(1, math.prod(shape) + 1).reshape(shape)
for keepdims in [True, False]:
out_np = np.linalg.norm(x_np, keepdims=keepdims)
out_mx = mx.linalg.norm(x_mx, keepdims=keepdims)
with self.subTest(shape=shape, keepdims=keepdims):
self.assertTrue(np.allclose(out_np, out_mx, atol=1e-5, rtol=1e-6))
if __name__ == "__main__":
unittest.main()