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# NVIDIA CORPORATION and its licensors retain all intellectual property
# and proprietary rights in and to this software, related documentation
# and any modifications thereto. Any use, reproduction, disclosure or
# distribution of this software and related documentation without an express
# license agreement from NVIDIA CORPORATION is strictly prohibited.
import unittest
import numpy as np
import warp as wp
from warp.tests.unittest_utils import *
wp.init()
dim_x = wp.constant(2)
dim_y = wp.constant(2)
dim_z = wp.constant(2)
dim_w = wp.constant(2)
@wp.kernel
def kernel1d(a: wp.array(dtype=int, ndim=1)):
i = wp.tid()
wp.expect_eq(a[i], i)
@wp.kernel
def kernel2d(a: wp.array(dtype=int, ndim=2)):
i, j = wp.tid()
wp.expect_eq(a[i, j], i * dim_y + j)
@wp.kernel
def kernel3d(a: wp.array(dtype=int, ndim=3)):
i, j, k = wp.tid()
wp.expect_eq(a[i, j, k], i * dim_y * dim_z + j * dim_z + k)
@wp.kernel
def kernel4d(a: wp.array(dtype=int, ndim=4)):
i, j, k, l = wp.tid()
wp.expect_eq(a[i, j, k, l], i * dim_y * dim_z * dim_w + j * dim_z * dim_w + k * dim_w + l)
def test1d(test, device):
a = np.arange(0, dim_x).reshape(dim_x)
wp.launch(kernel1d, dim=a.shape, inputs=[wp.array(a, dtype=int, device=device)], device=device)
def test2d(test, device):
a = np.arange(0, dim_x * dim_y).reshape(dim_x, dim_y)
wp.launch(kernel2d, dim=a.shape, inputs=[wp.array(a, dtype=int, device=device)], device=device)
def test3d(test, device):
a = np.arange(0, dim_x * dim_y * dim_z).reshape(dim_x, dim_y, dim_z)
wp.launch(kernel3d, dim=a.shape, inputs=[wp.array(a, dtype=int, device=device)], device=device)
def test4d(test, device):
a = np.arange(0, dim_x * dim_y * dim_z * dim_w).reshape(dim_x, dim_y, dim_z, dim_w)
wp.launch(kernel4d, dim=a.shape, inputs=[wp.array(a, dtype=int, device=device)], device=device)
@wp.struct
class Params:
a: wp.array(dtype=int)
i: int
f: float
@wp.kernel
def kernel_cmd(params: Params, i: int, f: float, v: wp.vec3, m: wp.mat33, out: wp.array(dtype=int)):
tid = wp.tid()
wp.expect_eq(params.i, i)
wp.expect_eq(params.f, f)
wp.expect_eq(i, int(f))
wp.expect_eq(v[0], f)
wp.expect_eq(v[1], f)
wp.expect_eq(v[2], f)
wp.expect_eq(m[0, 0], f)
wp.expect_eq(m[1, 1], f)
wp.expect_eq(m[2, 2], f)
out[tid] = tid + i
def test_launch_cmd(test, device):
n = 1
ref = np.arange(0, n)
out = wp.zeros(n, dtype=int, device=device)
params = Params()
params.i = 1
params.f = 1.0
v = wp.vec3(params.f, params.f, params.f)
m = wp.mat33(params.f, 0.0, 0.0, 0.0, params.f, 0.0, 0.0, 0.0, params.f)
# standard launch
wp.launch(kernel_cmd, dim=n, inputs=[params, params.i, params.f, v, m, out], device=device)
assert_np_equal(out.numpy(), ref + params.i)
# cmd launch
out.zero_()
cmd = wp.launch(kernel_cmd, dim=n, inputs=[params, params.i, params.f, v, m, out], device=device, record_cmd=True)
cmd.launch()
assert_np_equal(out.numpy(), ref + params.i)
def test_launch_cmd_set_param(test, device):
n = 1
ref = np.arange(0, n)
params = Params()
v = wp.vec3()
m = wp.mat33()
cmd = wp.launch(kernel_cmd, dim=n, inputs=[params, 0, 0.0, v, m, None], device=device, record_cmd=True)
# cmd param modification
out = wp.zeros(n, dtype=int, device=device)
params.i = 13
params.f = 13.0
v = wp.vec3(params.f, params.f, params.f)
m = wp.mat33(params.f, 0.0, 0.0, 0.0, params.f, 0.0, 0.0, 0.0, params.f)
cmd.set_param_at_index(0, params)
cmd.set_param_at_index(1, params.i)
cmd.set_param_at_index(2, params.f)
cmd.set_param_at_index(3, v)
cmd.set_param_at_index(4, m)
cmd.set_param_by_name("out", out)
cmd.launch()
assert_np_equal(out.numpy(), ref + params.i)
# test changing params after launch directly
# because we now cache the ctypes object inside the wp.struct
# instance the command buffer will be automatically updated
params.i = 14
params.f = 14.0
v = wp.vec3(params.f, params.f, params.f)
m = wp.mat33(params.f, 0.0, 0.0, 0.0, params.f, 0.0, 0.0, 0.0, params.f)
# this is the line we explicitly leave out to
# ensure that param changes are reflected in the launch
# launch.set_param_at_index(0, params)
cmd.set_param_at_index(1, params.i)
cmd.set_param_at_index(2, params.f)
cmd.set_param_at_index(3, v)
cmd.set_param_at_index(4, m)
cmd.set_param_by_name("out", out)
cmd.launch()
assert_np_equal(out.numpy(), ref + params.i)
def test_launch_cmd_set_ctype(test, device):
n = 1
ref = np.arange(0, n)
params = Params()
v = wp.vec3()
m = wp.mat33()
cmd = wp.launch(kernel_cmd, dim=n, inputs=[params, 0, 0.0, v, m, None], device=device, record_cmd=True)
# cmd param modification
out = wp.zeros(n, dtype=int, device=device)
# cmd param modification
out.zero_()
params.i = 13
params.f = 13.0
v = wp.vec3(params.f, params.f, params.f)
m = wp.mat33(params.f, 0.0, 0.0, 0.0, params.f, 0.0, 0.0, 0.0, params.f)
cmd.set_param_at_index_from_ctype(0, params.__ctype__())
cmd.set_param_at_index_from_ctype(1, params.i)
cmd.set_param_at_index_from_ctype(2, params.f)
cmd.set_param_at_index_from_ctype(3, v)
cmd.set_param_at_index_from_ctype(4, m)
cmd.set_param_by_name_from_ctype("out", out.__ctype__())
cmd.launch()
assert_np_equal(out.numpy(), ref + params.i)
@wp.kernel
def arange(out: wp.array(dtype=int)):
tid = wp.tid()
out[tid] = tid
def test_launch_cmd_set_dim(test, device):
n = 10
ref = np.arange(0, n, dtype=int)
out = wp.zeros(n, dtype=int, device=device)
cmd = wp.launch(arange, dim=n, inputs=[out], device=device, record_cmd=True)
cmd.set_dim(5)
cmd.launch()
# check first half the array is filled while rest is still zero
assert_np_equal(out.numpy()[0:5], ref[0:5])
assert_np_equal(out.numpy()[5:], np.zeros(5))
out.zero_()
cmd.set_dim(10)
cmd.launch()
# check the whole array was filled
assert_np_equal(out.numpy(), ref)
def test_launch_cmd_empty(test, device):
n = 10
ref = np.arange(0, n, dtype=int)
out = wp.zeros(n, dtype=int, device=device)
cmd = wp.Launch(arange, device)
cmd.set_dim(5)
cmd.set_param_by_name("out", out)
cmd.launch()
# check first half the array is filled while rest is still zero
assert_np_equal(out.numpy()[0:5], ref[0:5])
assert_np_equal(out.numpy()[5:], np.zeros(5))
out.zero_()
cmd.set_dim(10)
cmd.launch()
# check the whole array was filled
assert_np_equal(out.numpy(), ref)
@wp.kernel
def kernel_mul(
values: wp.array(dtype=int),
coeff: int,
out: wp.array(dtype=int),
):
tid = wp.tid()
out[tid] = values[tid] * coeff
def test_launch_tuple_args(test, device):
values = wp.array(np.arange(0, 4), dtype=int, device=device)
coeff = 3
out = wp.empty_like(values)
wp.launch(
kernel_mul,
dim=len(values),
inputs=(
values,
coeff,
),
outputs=(out,),
device=device,
)
assert_np_equal(out.numpy(), np.array((0, 3, 6, 9)))
devices = get_test_devices()
class TestLaunch(unittest.TestCase):
pass
add_function_test(TestLaunch, "test_launch_1d", test1d, devices=devices)
add_function_test(TestLaunch, "test_launch_2d", test2d, devices=devices)
add_function_test(TestLaunch, "test_launch_3d", test3d, devices=devices)
add_function_test(TestLaunch, "test_launch_4d", test4d, devices=devices)
add_function_test(TestLaunch, "test_launch_cmd", test_launch_cmd, devices=devices)
add_function_test(TestLaunch, "test_launch_cmd_set_param", test_launch_cmd_set_param, devices=devices)
add_function_test(TestLaunch, "test_launch_cmd_set_ctype", test_launch_cmd_set_ctype, devices=devices)
add_function_test(TestLaunch, "test_launch_cmd_set_dim", test_launch_cmd_set_dim, devices=devices)
add_function_test(TestLaunch, "test_launch_cmd_empty", test_launch_cmd_empty, devices=devices)
if __name__ == "__main__":
wp.build.clear_kernel_cache()
unittest.main(verbosity=2)
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