Skip to content
This repository was archived by the owner on Jan 25, 2023. It is now read-only.

[MLIR] Some numpy operators support #192

Merged
Hardcode84 merged 6 commits into from
Feb 27, 2021
Merged

[MLIR] Some numpy operators support #192

Changes from 1 commit
Commits
Show all changes
6 commits
Select commit Hold shift + click to select a range
e283cca
use std::function
Feb 26, 2021
023be34
refac test
Feb 26, 2021
53d9a36
numpy operator add
Feb 26, 2021
eb2c087
fix plier binop
Feb 26, 2021
cdd668e
numpy subtract
Feb 26, 2021
1e6a885
numpy multiply
Feb 26, 2021
File filter

Filter by extension

Filter by extension
Conversations
Failed to load comments.
Loading
Jump to
Jump to file
Failed to load files.
Loading
Diff view
Diff view
Prev Previous commit
Next Next commit
refac test
  • Loading branch information
Butygin
Butygin committed Feb 27, 2021
commit 023be341baf3299280e1980abdf6789cd650a3f1
28 changes: 10 additions & 18 deletions numba/mlir/tests/test_numpy.py
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -4,6 +4,7 @@
import numpy as np
from numba.tests.support import TestCase
import unittest
import itertools

_arr_1d_int = [1,2,3,4,5,6,7,8]
_arr_1d_float = [1.0,2.1,3.2,4.3,5.4,6.5,7.6,8.7]
Expand Down Expand Up @@ -46,8 +47,6 @@ def test_unary(self):
lambda a: a.size,
# lambda a: a.T, TODO: need fortran layout support
lambda a: a.T.T,
lambda a: np.add(a, 1),
lambda a: np.add(a, 2.5),
]

for py_func in funcs:
Expand All @@ -56,23 +55,16 @@ def test_unary(self):
arr = np.array(a)
assert_equal(py_func(arr), jit_func(arr))

def test_add(self):
def py_func(a, b):
return np.add(a, b)

jit_func = njit(py_func)
arr1 = np.array([1,2,3])
arr2 = np.array([4,5,6])
assert_equal(py_func(arr1,arr2), jit_func(arr1,arr2))

def test_add_scalar(self):
def py_func(a, b):
return np.add(a, b)
def test_binary(self):
funcs = [
lambda a, b: np.add(a, b),
]

jit_func = njit(py_func)
arr1 = 1
arr2 = 2
assert_equal(py_func(arr1, arr2), jit_func(arr1, arr2))
test_data = [1, 2.5, np.array([1,2,3]), np.array([4.4,5.5,6.6])]
for py_func in funcs:
jit_func = njit(py_func)
for a1, a2 in itertools.product(test_data, test_data):
assert_equal(py_func(a1,a2), jit_func(a1,a2))

def test_sum_axis(self):
funcs = [
Expand Down