From 76a72b769b1390bd663ba2ed56927ca694cadab3 Mon Sep 17 00:00:00 2001
From: Alexandru Fikl <alexfikl@gmail.com>
Date: Tue, 18 Feb 2025 20:54:10 +0200
Subject: [PATCH] feat: port to using np.random.Generator
---
pyproject.toml | 1 -
test/test_callables.py | 53 +++++++++++++++++++++++++----------------
test/test_diff.py | 7 +++---
test/test_einsum.py | 30 +++++++++++++----------
test/test_expression.py | 5 ++--
test/test_fusion.py | 5 ++--
test/test_loopy.py | 25 ++++++++++++-------
test/test_reduction.py | 10 ++++----
test/test_scan.py | 13 +++++-----
test/test_target.py | 5 ++--
test/test_transform.py | 18 +++++++++-----
11 files changed, 104 insertions(+), 68 deletions(-)
diff --git a/pyproject.toml b/pyproject.toml
index 077cf126..d03048fc 100644
--- a/pyproject.toml
+++ b/pyproject.toml
@@ -114,7 +114,6 @@ extend-ignore = [
"N817", # CamelCase `SubstitutionRuleMappingContext` imported as acronym `SRMC`
# FIXME
- "NPY002", # numpy rng
"UP031", # .format instead of %s
"UP032", # .format instead of %s
]
diff --git a/test/test_callables.py b/test/test_callables.py
index 06014785..eabba3fe 100644
--- a/test/test_callables.py
+++ b/test/test_callables.py
@@ -39,10 +39,11 @@ from loopy.version import LOOPY_USE_LANGUAGE_VERSION_2018_2 # noqa: F401
def test_register_function_lookup(ctx_factory):
ctx = ctx_factory()
queue = cl.CommandQueue(ctx)
+ rng = np.random.default_rng(seed=42)
from testlib import Log2Callable
- x = np.random.rand(10)
+ x = rng.random(size=10)
queue = cl.CommandQueue(ctx)
prog = lp.make_kernel(
@@ -61,10 +62,11 @@ def test_register_function_lookup(ctx_factory):
def test_register_knl(ctx_factory, inline):
ctx = ctx_factory()
queue = cl.CommandQueue(ctx)
- n = 4
+ rng = np.random.default_rng(seed=42)
- x = np.random.rand(n, n, n, n, n)
- y = np.random.rand(n, n, n, n, n)
+ n = 4
+ x = rng.random(size=(n, n, n, n, n))
+ y = rng.random(size=(n, n, n, n, n))
grandchild_knl = lp.make_function(
"{[i, j]:0<= i, j< 4}",
@@ -108,10 +110,11 @@ def test_register_knl(ctx_factory, inline):
def test_slices_with_negative_step(ctx_factory, inline):
ctx = ctx_factory()
queue = cl.CommandQueue(ctx)
- n = 4
+ rng = np.random.default_rng(seed=42)
- x = np.random.rand(n, n, n, n, n)
- y = np.random.rand(n, n, n, n, n)
+ n = 4
+ x = rng.random(size=(n, n, n, n, n))
+ y = rng.random(size=(n, n, n, n, n))
child_knl = lp.make_function(
"{[i, j]:0<=i, j < 4}",
@@ -245,12 +248,16 @@ def test_shape_translation_through_sub_array_ref(ctx_factory, inline):
def test_multi_arg_array_call(ctx_factory):
ctx = ctx_factory()
queue = cl.CommandQueue(ctx)
+ rng = np.random.default_rng(seed=42)
+
import pymbolic.primitives as p
+
n = 10
acc_i = p.Variable("acc_i")
i = p.Variable("i")
index = p.Variable("index")
a_i = p.Subscript(p.Variable("a"), p.Variable("i"))
+
argmin_kernel = lp.make_function(
"{[i]: 0 <= i < n}",
[
@@ -281,9 +288,9 @@ def test_multi_arg_array_call(ctx_factory):
knl = lp.fix_parameters(knl, n=n)
knl = lp.set_options(knl, return_dict=True)
-
knl = lp.merge([knl, argmin_kernel])
- b = np.random.randn(n)
+
+ b = rng.normal(size=n)
_evt, out_dict = knl(queue, b=b)
tol = 1e-15
from numpy.linalg import norm
@@ -346,9 +353,10 @@ def test_empty_sub_array_refs(ctx_factory, inline):
# See: https://github.com/OP2/PyOP2/pull/559#discussion_r272208618
ctx = ctx_factory()
queue = cl.CommandQueue(ctx)
+ rng = np.random.default_rng(seed=42)
- x = np.random.randn(10)
- y = np.random.randn(10)
+ x = rng.normal(size=10)
+ y = rng.normal(size=10)
callee = lp.make_function(
"{[d]:0<=d<1}",
@@ -375,10 +383,11 @@ def test_empty_sub_array_refs(ctx_factory, inline):
def test_array_inputs_to_callee_kernels(ctx_factory, inline):
ctx = ctx_factory()
queue = cl.CommandQueue(ctx)
- n = 2 ** 3
+ rng = np.random.default_rng(seed=42)
- x = np.random.rand(n, n)
- y = np.random.rand(n, n)
+ n = 2 ** 3
+ x = rng.normal(size=(n, n))
+ y = rng.normal(size=(n, n))
child_knl = lp.make_function(
"{[i, j]:0<=i, j < 8}",
@@ -469,6 +478,8 @@ def test_unknown_stride_to_callee(ctx_factory):
def test_argument_matching_for_inplace_update(ctx_factory):
ctx = ctx_factory()
queue = cl.CommandQueue(ctx)
+ rng = np.random.default_rng(seed=42)
+
twice = lp.make_function(
"{[i]: 0<=i<10}",
"""
@@ -483,7 +494,7 @@ def test_argument_matching_for_inplace_update(ctx_factory):
knl = lp.merge([knl, twice])
- x = np.random.randn(10)
+ x = rng.normal(size=10)
_evt, (out, ) = knl(queue, x=np.copy(x))
assert np.allclose(2*x, out)
@@ -492,6 +503,8 @@ def test_argument_matching_for_inplace_update(ctx_factory):
def test_non_zero_start_in_subarray_ref(ctx_factory):
ctx = ctx_factory()
queue = cl.CommandQueue(ctx)
+ rng = np.random.default_rng(seed=42)
+
twice = lp.make_function(
"{[i]: 0<=i<10}",
"""
@@ -503,10 +516,9 @@ def test_non_zero_start_in_subarray_ref(ctx_factory):
"""
[i]:y[i+5] = twice([j]: x[j])
""", [lp.GlobalArg("x, y", shape=(10,), dtype=np.float64)])
-
knl = lp.merge([knl, twice])
- x = np.random.randn(10)
+ x = rng.normal(size=10)
_evt, (out, ) = knl(queue, x=np.copy(x))
assert np.allclose(2*x, out)
@@ -710,7 +722,7 @@ def test_passing_and_getting_scalar_in_clbl_knl(ctx_factory, inline):
def test_passing_scalar_as_indexed_subcript_in_clbl_knl(ctx_factory, inline):
ctx = cl.create_some_context()
cq = cl.CommandQueue(ctx)
- x_in = np.random.rand()
+ rng = np.random.default_rng(seed=42)
twice = lp.make_function(
"{ : }",
@@ -731,6 +743,7 @@ def test_passing_scalar_as_indexed_subcript_in_clbl_knl(ctx_factory, inline):
if inline:
knl = lp.inline_callable_kernel(knl, "twice")
+ x_in = rng.random()
_evt, (out,) = knl(cq, X=x_in)
np.testing.assert_allclose(out.get(), 2*x_in)
@@ -1312,8 +1325,7 @@ def test_c_instruction_in_callee(ctx_factory, inline):
ctx = ctx_factory()
cq = cl.CommandQueue(ctx)
-
- n = np.random.randint(3, 8)
+ rng = np.random.default_rng(seed=42)
knl = lp.make_function(
"{[i]: 0<=i<10}",
@@ -1338,6 +1350,7 @@ def test_c_instruction_in_callee(ctx_factory, inline):
if inline:
t_unit = lp.inline_callable_kernel(t_unit, "circuit_breaker")
+ n = rng.integers(3, 8)
_, (out,) = t_unit(cq, N=n)
assert out.get() == (n-1)
diff --git a/test/test_diff.py b/test/test_diff.py
index 0f9694cc..d1d81b13 100644
--- a/test/test_diff.py
+++ b/test/test_diff.py
@@ -56,6 +56,7 @@ from loopy.version import LOOPY_USE_LANGUAGE_VERSION_2018_2 # noqa
def test_diff(ctx_factory):
ctx = ctx_factory()
queue = cl.CommandQueue(ctx)
+ rng = np.random.default_rng(seed=42)
knl = lp.make_kernel(
"""{ [i,j]: 0<=i,j<n }""",
@@ -78,10 +79,10 @@ def test_diff(ctx_factory):
print(dknl)
n = 50
- x = np.random.randn(n)
- y = np.random.randn(n)
+ x = rng.normal(size=n)
+ y = rng.normal(size=n)
- dx = np.random.randn(n)
+ dx = rng.normal(size=n)
fac = 1e-1
h1 = 1e-4
diff --git a/test/test_einsum.py b/test/test_einsum.py
index 65624ba5..b641e3b0 100644
--- a/test/test_einsum.py
+++ b/test/test_einsum.py
@@ -51,9 +51,10 @@ def test_make_einsum_error_handling():
def test_einsum_array_manipulation(ctx_factory, spec):
ctx = ctx_factory()
queue = cl.CommandQueue(ctx)
+ rng = np.random.default_rng(seed=42)
n = 4
- a = np.random.rand(n, n)
+ a = rng.random(size=(n, n))
arg_names = ("a",)
knl = lp.make_einsum(spec, arg_names)
@@ -69,10 +70,11 @@ def test_einsum_array_manipulation(ctx_factory, spec):
def test_einsum_array_matvec(ctx_factory, spec):
ctx = ctx_factory()
queue = cl.CommandQueue(ctx)
+ rng = np.random.default_rng(seed=42)
n = 4
- a = np.random.rand(n, n)
- b = np.random.rand(n)
+ a = rng.random(size=(n, n))
+ b = rng.random(size=n)
arg_names = ("a", "b")
knl = lp.make_einsum(spec, arg_names)
@@ -90,10 +92,11 @@ def test_einsum_array_matvec(ctx_factory, spec):
def test_einsum_array_ops_same_dims(ctx_factory, spec):
ctx = ctx_factory()
queue = cl.CommandQueue(ctx)
+ rng = np.random.default_rng(seed=42)
n = 4
- a = np.random.rand(n, n)
- b = np.random.rand(n, n)
+ a = rng.random(size=(n, n))
+ b = rng.random(size=(n, n))
arg_names = ("a", "b")
knl = lp.make_einsum(spec, arg_names)
@@ -109,12 +112,13 @@ def test_einsum_array_ops_same_dims(ctx_factory, spec):
def test_einsum_array_ops_diff_dims(ctx_factory, spec):
ctx = ctx_factory()
queue = cl.CommandQueue(ctx)
+ rng = np.random.default_rng(seed=42)
n = 4
m = 3
o = 5
- a = np.random.rand(n, m)
- b = np.random.rand(m, o)
+ a = rng.random(size=(n, m))
+ b = rng.random(size=(m, o))
arg_names = ("a", "b")
knl = lp.make_einsum(spec, arg_names)
@@ -130,11 +134,12 @@ def test_einsum_array_ops_diff_dims(ctx_factory, spec):
def test_einsum_array_ops_triple_prod(ctx_factory, spec):
ctx = ctx_factory()
queue = cl.CommandQueue(ctx)
+ rng = np.random.default_rng(seed=42)
n = 3
- a = np.random.rand(n, n)
- b = np.random.rand(n, n)
- c = np.random.rand(n, n)
+ a = rng.random(size=(n, n))
+ b = rng.random(size=(n, n))
+ c = rng.random(size=(n, n))
arg_names = ("a", "b", "c")
knl = lp.make_einsum(spec, arg_names)
@@ -147,13 +152,14 @@ def test_einsum_array_ops_triple_prod(ctx_factory, spec):
def test_einsum_with_variable_strides(ctx_factory):
ctx = ctx_factory()
queue = cl.CommandQueue(ctx)
+ rng = np.random.default_rng(seed=42)
spec = "ijk,jl->il"
knl = lp.make_einsum(spec, ("a", "b"),
default_order=lp.auto, default_offset=lp.auto)
- a_untransposed = np.random.randn(3, 5, 4)
- b = np.random.randn(4, 5)
+ a_untransposed = rng.normal(size=(3, 5, 4))
+ b = rng.normal(size=(4, 5))
a = a_untransposed.transpose((0, 2, 1))
a_dev = cl.array.to_device(queue, a_untransposed).transpose((0, 2, 1))
diff --git a/test/test_expression.py b/test/test_expression.py
index aa60f8a5..ca033cbf 100644
--- a/test/test_expression.py
+++ b/test/test_expression.py
@@ -557,9 +557,10 @@ def test_complex_support(ctx_factory, target):
knl = lp.set_options(knl, return_dict=True)
n = 10
+ rng = np.random.default_rng(seed=42)
- in1 = np.random.rand(n)
- in2 = np.random.rand(n)
+ in1 = rng.random(n)
+ in2 = rng.random(n)
kwargs = {"in1": in1, "in2": in2}
diff --git a/test/test_fusion.py b/test/test_fusion.py
index ab3b4e74..715de89c 100644
--- a/test/test_fusion.py
+++ b/test/test_fusion.py
@@ -67,6 +67,7 @@ def test_write_block_matrix_fusion(ctx_factory):
ctx = ctx_factory()
queue = cl.CommandQueue(ctx)
+ rng = np.random.default_rng(seed=42)
def init_global_mat_prg():
return lp.make_kernel(
@@ -124,8 +125,8 @@ def test_write_block_matrix_fusion(ctx_factory):
# and zeros elsewhere
n = 10
block_n = 5
- mat1 = np.random.randn(block_n, block_n)
- mat2 = np.random.randn(block_n, block_n)
+ mat1 = rng.normal(size=(block_n, block_n))
+ mat2 = rng.normal(size=(block_n, block_n))
answer = np.block([[mat1, np.zeros((block_n, block_n))],
[np.zeros((block_n, block_n)), mat2]])
kwargs = {"n": n, "m": n}
diff --git a/test/test_loopy.py b/test/test_loopy.py
index d9d16818..83440034 100644
--- a/test/test_loopy.py
+++ b/test/test_loopy.py
@@ -58,9 +58,11 @@ from loopy.version import LOOPY_USE_LANGUAGE_VERSION_2018_2 # noqa
def test_globals_decl_once_with_multi_subprogram(ctx_factory):
ctx = ctx_factory()
queue = cl.CommandQueue(ctx)
- np.random.seed(17)
- a = np.random.randn(16)
- cnst = np.random.randn(16)
+
+ rng = np.random.default_rng(seed=17)
+
+ a = rng.normal(size=16)
+ cnst = rng.normal(size=16)
knl = lp.make_kernel(
"{[i, ii]: 0<=i, ii<n}",
"""
@@ -781,7 +783,8 @@ def test_make_copy_kernel(ctx_factory):
intermediate_format = "f,f,sep"
- a1 = np.random.randn(1024, 4, 3)
+ rng = np.random.default_rng(seed=42)
+ a1 = rng.normal(size=(1024, 4, 3))
cknl1 = lp.make_copy_kernel(intermediate_format)
@@ -802,7 +805,8 @@ def test_make_copy_kernel_with_offsets(ctx_factory):
ctx = ctx_factory()
queue = cl.CommandQueue(ctx)
- a1 = np.random.randn(3, 1024, 4)
+ rng = np.random.default_rng(seed=42)
+ a1 = rng.normal(size=(3, 1024, 4))
a1_dev = cl.array.to_device(queue, a1)
cknl1 = lp.make_copy_kernel("c,c,c", "sep,c,c")
@@ -1821,7 +1825,8 @@ def test_constant_array_args(ctx_factory):
@pytest.mark.parametrize("src_order", ["C"])
@pytest.mark.parametrize("tmp_order", ["C", "F"])
def test_temp_initializer(ctx_factory, src_order, tmp_order):
- a = np.random.randn(3, 3).copy(order=src_order)
+ rng = np.random.default_rng(seed=42)
+ a = rng.normal(size=(3, 3)).copy(order=src_order)
ctx = ctx_factory()
queue = cl.CommandQueue(ctx)
@@ -2091,12 +2096,13 @@ def test_unscheduled_insn_detection():
def test_integer_reduction(ctx_factory):
ctx = ctx_factory()
queue = cl.CommandQueue(ctx)
+ rng = np.random.default_rng(seed=42)
from loopy.types import to_loopy_type
n = 200
for vtype in [np.int32, np.int64]:
- var_int = np.random.randint(1000, size=n).astype(vtype)
+ var_int = rng.integers(1000, size=n, dtype=vtype)
var_lp = lp.TemporaryVariable("var", initializer=var_int,
read_only=True,
address_space=lp.AddressSpace.PRIVATE,
@@ -2753,14 +2759,15 @@ def test_temp_var_type_deprecated_usage():
def test_shape_mismatch_check(ctx_factory):
ctx = ctx_factory()
queue = cl.CommandQueue(ctx)
+ rng = np.random.default_rng(seed=42)
t_unit = lp.make_kernel(
"{[i,j]: 0 <= i < n and 0 <= j < m}",
"c[i] = sum(j, a[i,j]*b[j])",
default_order="F")
- a = np.random.rand(10, 10).astype(np.float32)
- b = np.random.rand(10).astype(np.float32)
+ a = rng.random((10, 10), dtype=np.float32)
+ b = rng.random(10, dtype=np.float32)
if t_unit["loopy_kernel"].options.skip_arg_checks:
pytest.skip("args checks disabled, cannot check")
diff --git a/test/test_reduction.py b/test/test_reduction.py
index 125d247d..7b2a98c5 100644
--- a/test/test_reduction.py
+++ b/test/test_reduction.py
@@ -297,9 +297,9 @@ def test_global_mc_parallel_reduction(ctx_factory, size):
def test_argmax(ctx_factory):
logging.basicConfig(level=logging.INFO)
- dtype = np.dtype(np.float32)
ctx = ctx_factory()
queue = cl.CommandQueue(ctx)
+ rng = np.random.default_rng(seed=42)
n = 10000
@@ -313,7 +313,7 @@ def test_argmax(ctx_factory):
print(lp.preprocess_kernel(knl))
knl = lp.set_options(knl, write_code=True, allow_terminal_colors=True)
- a = np.random.randn(10000).astype(dtype)
+ a = rng.normal(size=10000).astype(np.float32)
_evt, (max_idx, max_val) = knl(queue, a=a, out_host=True)
assert max_val == np.max(np.abs(a))
assert max_idx == np.where(np.abs(a) == max_val)[-1]
@@ -349,6 +349,7 @@ def test_simul_reduce(ctx_factory):
def test_reduction_library(ctx_factory, op_name, np_op):
ctx = ctx_factory()
queue = cl.CommandQueue(ctx)
+ rng = np.random.default_rng(seed=42)
knl = lp.make_kernel(
"{[i,j]: 0<=i<n and 0<=j<m }",
@@ -357,7 +358,7 @@ def test_reduction_library(ctx_factory, op_name, np_op):
],
assumptions="n>=1")
- a = np.random.randn(20, 10)
+ a = rng.normal(size=(20, 10))
_evt, (res,) = knl(queue, a=a)
assert np.allclose(res, np_op(a, axis=1))
@@ -412,9 +413,10 @@ def test_parallel_multi_output_reduction(ctx_factory):
knl = lp.add_dtypes(knl, {"a": np.float64})
ctx = ctx_factory()
+ rng = np.random.default_rng(seed=42)
with cl.CommandQueue(ctx) as queue:
- a = np.random.rand(128)
+ a = rng.random(128)
_out, (max_index, max_val) = knl(queue, a=a)
assert max_val == np.max(a)
diff --git a/test/test_scan.py b/test/test_scan.py
index 47c2e04b..36deb9f6 100644
--- a/test/test_scan.py
+++ b/test/test_scan.py
@@ -293,13 +293,14 @@ def test_scan_with_outer_parallel_iname(ctx_factory, sweep_iname_tag):
def test_scan_data_types(ctx_factory, dtype):
ctx = ctx_factory()
queue = cl.CommandQueue(ctx)
+ rng = np.random.default_rng(seed=42)
knl = lp.make_kernel(
"{[i,j]: 0<=i<n and 0<=j<=i }",
"res[i] = reduce(sum, j, a[j])",
assumptions="n>=1")
- a = np.random.randn(20).astype(dtype)
+ a = rng.normal(size=20).astype(dtype)
knl = lp.add_dtypes(knl, {"a": dtype})
knl = lp.realize_reduction(knl, force_scan=True)
_evt, (res,) = knl(queue, a=a)
@@ -316,13 +317,14 @@ def test_scan_data_types(ctx_factory, dtype):
def test_scan_library(ctx_factory, op_name, np_op):
ctx = ctx_factory()
queue = cl.CommandQueue(ctx)
+ rng = np.random.default_rng(seed=42)
knl = lp.make_kernel(
"{[i,j]: 0<=i<n and 0<=j<=i }",
"res[i] = reduce(%s, j, a[j])" % op_name,
assumptions="n>=1")
- a = np.random.randn(20)
+ a = rng.normal(size=20)
knl = lp.add_dtypes(knl, {"a": np.float64})
knl = lp.realize_reduction(knl, force_scan=True)
_evt, (res,) = knl(queue, a=a)
@@ -337,14 +339,11 @@ def test_scan_unsupported_tags():
@pytest.mark.parametrize("i_tag", ["for", "l.0"])
def test_argmax(ctx_factory, i_tag):
- logging.basicConfig(level=logging.INFO)
-
- dtype = np.dtype(np.float32)
ctx = ctx_factory()
queue = cl.CommandQueue(ctx)
+ rng = np.random.default_rng(seed=42)
n = 128
-
knl = lp.make_kernel(
"{[i,j]: 0<=i<%d and 0<=j<=i}" % n,
"""
@@ -355,7 +354,7 @@ def test_argmax(ctx_factory, i_tag):
knl = lp.add_and_infer_dtypes(knl, {"a": np.float32})
knl = lp.realize_reduction(knl, force_scan=True)
- a = np.random.randn(n).astype(dtype)
+ a = rng.normal(size=n).astype(np.float32)
_evt, (max_indices, max_vals) = knl(queue, a=a, out_host=True)
assert (max_vals == [np.max(np.abs(a)[0:i+1]) for i in range(n)]).all()
diff --git a/test/test_target.py b/test/test_target.py
index a3c4356b..f29fbeec 100644
--- a/test/test_target.py
+++ b/test/test_target.py
@@ -684,15 +684,16 @@ def test_empty_array_output(ctx_factory):
def test_empty_array_stride_check(ctx_factory):
ctx = ctx_factory()
cq = cl.CommandQueue(ctx)
+ rng = np.random.default_rng(seed=42)
einsum = lp.make_einsum("mij,j->mi", ["a", "x"])
- einsum(cq, a=np.random.randn(3, 0, 5), x=np.random.randn(5))
+ einsum(cq, a=rng.normal(size=(3, 0, 5)), x=rng.normal(size=5))
if einsum.default_entrypoint.options.skip_arg_checks:
pytest.skip("args checks disabled, cannot check")
with pytest.raises(ValueError):
- einsum(cq, a=np.random.randn(3, 2, 5).copy(order="F"), x=np.random.randn(5))
+ einsum(cq, a=rng.normal(size=(3, 2, 5)).copy(order="F"), x=rng.normal(size=5))
def test_no_op_with_predicate(ctx_factory):
diff --git a/test/test_transform.py b/test/test_transform.py
index 3e3aabf1..4c42b4dc 100644
--- a/test/test_transform.py
+++ b/test/test_transform.py
@@ -124,6 +124,7 @@ def test_collect_common_factors(ctx_factory):
def test_to_batched(ctx_factory):
ctx = ctx_factory()
queue = cl.CommandQueue(ctx)
+ rng = np.random.default_rng(seed=42)
knl = lp.make_kernel(
""" { [i,j]: 0<=i,j<n } """,
@@ -141,8 +142,8 @@ def test_to_batched(ctx_factory):
"x": np.float32,
"a": np.float32})
- a = np.random.randn(5, 5).astype(np.float32)
- x = np.random.randn(7, 5).astype(np.float32)
+ a = rng.normal(size=(5, 5)).astype(np.float32)
+ x = rng.normal(size=(7, 5)).astype(np.float32)
# Running both the kernels
_evt, (out1, ) = bknl(queue, a=a, x=x, n=5, nbatches=7)
@@ -154,6 +155,7 @@ def test_to_batched(ctx_factory):
def test_to_batched_temp(ctx_factory):
ctx = ctx_factory()
+ rng = np.random.default_rng(seed=42)
knl = lp.make_kernel(
""" { [i,j]: 0<=i,j<n } """,
@@ -180,8 +182,8 @@ def test_to_batched_temp(ctx_factory):
# checking that cnst is not being bathced
assert bknl["loopy_kernel"].temporary_variables["cnst"].shape == ()
- a = np.random.randn(5, 5)
- x = np.random.randn(7, 5)
+ a = rng.normal(size=(5, 5))
+ x = rng.normal(size=(7, 5))
# Checking that the program compiles and the logic is correct
lp.auto_test_vs_ref(
@@ -192,6 +194,8 @@ def test_to_batched_temp(ctx_factory):
def test_add_barrier(ctx_factory):
ctx = ctx_factory()
queue = cl.CommandQueue(ctx)
+ rng = np.random.default_rng(seed=42)
+
knl = lp.make_kernel(
"{[i, j, ii, jj]: 0<=i,j, ii, jj<n}",
"""
@@ -203,7 +207,8 @@ def test_add_barrier(ctx_factory):
...
]
)
- a = np.random.randn(16, 16)
+
+ a = rng.normal(size=(16, 16))
knl = lp.add_barrier(knl, "id:transpose", "id:double", "gb1")
knl = lp.split_iname(knl, "i", 2, outer_tag="g.0", inner_tag="l.0")
@@ -1139,6 +1144,7 @@ def test_rename_argument_with_auto_stride(ctx_factory):
ctx = ctx_factory()
queue = cl.CommandQueue(ctx)
+ rng = np.random.default_rng(seed=42)
knl = lp.make_kernel(
"{[i]: 0<=i<10}",
@@ -1154,7 +1160,7 @@ def test_rename_argument_with_auto_stride(ctx_factory):
assert code_str.find("double const *__restrict__ x_new,") != -1
assert code_str.find("double const *__restrict__ x,") == -1
- _evt, (_out, ) = knl(queue, x_new=np.random.rand(10))
+ _evt, (_out, ) = knl(queue, x_new=rng.random(10))
def test_rename_argument_with_assumptions():
--
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