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feat: Add numpy constants (#428)

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* add numpy constants

* feat: add unittests

* add newaxis

* add test for newaxis transformation

* refactor
This commit is contained in:
Avikant Srivastava 2024-01-11 20:17:29 +05:30 committed by GitHub
parent c92a134b0d
commit 975e265f74
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4 changed files with 86 additions and 0 deletions
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1
python/src/CMakeLists.txt
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@ -12,6 +12,7 @@ pybind11_add_module(
${CMAKE_CURRENT_SOURCE_DIR}/transforms.cpp
${CMAKE_CURRENT_SOURCE_DIR}/random.cpp
${CMAKE_CURRENT_SOURCE_DIR}/linalg.cpp
${CMAKE_CURRENT_SOURCE_DIR}/constants.cpp
)
if (NOT MLX_PYTHON_BINDINGS_OUTPUT_DIRECTORY)

24
python/src/constants.cpp Normal file
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@ -0,0 +1,24 @@
// init_constants.cpp
#include <pybind11/pybind11.h>
#include <limits>
namespace py = pybind11;
void init_constants(py::module_& m) {
m.attr("Inf") = std::numeric_limits<double>::infinity();
m.attr("Infinity") = std::numeric_limits<double>::infinity();
m.attr("NAN") = NAN;
m.attr("NINF") = -std::numeric_limits<double>::infinity();
m.attr("NZERO") = -0.0;
m.attr("NaN") = NAN;
m.attr("PINF") = std::numeric_limits<double>::infinity();
m.attr("PZERO") = 0.0;
m.attr("e") = 2.71828182845904523536028747135266249775724709369995;
m.attr("euler_gamma") = 0.5772156649015328606065120900824024310421;
m.attr("inf") = std::numeric_limits<double>::infinity();
m.attr("infty") = std::numeric_limits<double>::infinity();
m.attr("nan") = NAN;
m.attr("newaxis") = pybind11::none();
m.attr("pi") = 3.1415926535897932384626433;
}

2
python/src/mlx.cpp
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@ -16,6 +16,7 @@ void init_transforms(py::module_&);
void init_random(py::module_&);
void init_fft(py::module_&);
void init_linalg(py::module_&);
void init_constants(py::module_&);
PYBIND11_MODULE(core, m) {
m.doc() = "mlx: A framework for machine learning on Apple silicon.";
@ -31,5 +32,6 @@ PYBIND11_MODULE(core, m) {
init_random(m);
init_fft(m);
init_linalg(m);
init_constants(m);
m.attr("__version__") = TOSTRING(_VERSION_);
}

59
python/tests/test_constants.py Normal file
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@ -0,0 +1,59 @@
# Copyright © 2023 Apple Inc.
import unittest
import mlx.core as mx
import mlx_tests
import numpy as np
class TestConstants(mlx_tests.MLXTestCase):
def test_constants_values(self):
# Check if mlx constants match expected values
self.assertAlmostEqual(mx.Inf, float("inf"))
self.assertAlmostEqual(mx.Infinity, float("inf"))
self.assertTrue(np.isnan(mx.NAN))
self.assertAlmostEqual(mx.NINF, float("-inf"))
self.assertEqual(mx.NZERO, -0.0)
self.assertTrue(np.isnan(mx.NaN))
self.assertAlmostEqual(mx.PINF, float("inf"))
self.assertEqual(mx.PZERO, 0.0)
self.assertAlmostEqual(
mx.e, 2.71828182845904523536028747135266249775724709369995
)
self.assertAlmostEqual(
mx.euler_gamma, 0.5772156649015328606065120900824024310421
)
self.assertAlmostEqual(mx.inf, float("inf"))
self.assertAlmostEqual(mx.infty, float("inf"))
self.assertTrue(np.isnan(mx.nan))
self.assertIsNone(mx.newaxis)
self.assertAlmostEqual(mx.pi, 3.1415926535897932384626433)
def test_constants_availability(self):
# Check if mlx constants are available
self.assertTrue(hasattr(mx, "Inf"))
self.assertTrue(hasattr(mx, "Infinity"))
self.assertTrue(hasattr(mx, "NAN"))
self.assertTrue(hasattr(mx, "NINF"))
self.assertTrue(hasattr(mx, "NaN"))
self.assertTrue(hasattr(mx, "PINF"))
self.assertTrue(hasattr(mx, "NZERO"))
self.assertTrue(hasattr(mx, "PZERO"))
self.assertTrue(hasattr(mx, "e"))
self.assertTrue(hasattr(mx, "euler_gamma"))
self.assertTrue(hasattr(mx, "inf"))
self.assertTrue(hasattr(mx, "infty"))
self.assertTrue(hasattr(mx, "nan"))
self.assertTrue(hasattr(mx, "newaxis"))
self.assertTrue(hasattr(mx, "pi"))
def test_newaxis_for_reshaping_arrays(self):
arr_1d = mx.array([1, 2, 3, 4, 5])
arr_2d_column = arr_1d[:, mx.newaxis]
expected_result = mx.array([[1], [2], [3], [4], [5]])
self.assertTrue(mx.array_equal(arr_2d_column, expected_result))
if __name__ == "__main__":
unittest.main()