def test_call(self):
expected = np.zeros([10], dtype=[('x', np.float32), ('y', np.float32)])
expected['x'] = np.arange(10)
expected['y'] = np.sin(expected['x'] / 10)
program = Program(ctx, source=source)
program.build()
generate_sin = program.kernel('generate_sin')
generate_sin.argtypes = [global_memory(), ctypes.c_float]
buf = empty(ctx, [10], ctype=cl.cl_float2)
queue = Queue(ctx, ctx.devices[0])
size = [buf.size]
with self.assertRaises(TypeError):
generate_sin(queue, buf, 1.0)
generate_sin(queue, buf, 1.0, global_work_size=size)
with buf.map(queue) as host:
self.assertTrue(np.all(expected['x'] == np.asarray(host)[:, 0]))
self.assertTrue(np.allclose(expected['y'], np.asarray(host)[:, 1]))
generate_sin.global_work_size = lambda a, scale: [a.size]
generate_sin(queue, buf, 1.0)
with buf.map(queue) as host:
self.assertTrue(np.all(expected['x'] == np.asarray(host)[:, 0]))
self.assertTrue(np.allclose(expected['y'], np.asarray(host)[:, 1]))
def test_name(self):
program = Program(ctx, source=source)
program.build()
generate_sin = program.kernel('generate_sin')
self.assertEqual(generate_sin.name, 'generate_sin')
def test_argtypes(self):
program = Program(ctx, source=source)
program.build()
generate_sin = program.kernel('generate_sin')
generate_sin.argtypes = [DeviceMemoryView, ctypes.c_float]
with self.assertRaises(TypeError):
generate_sin.argtypes = [DeviceMemoryView, ctypes.c_float, ctypes.c_float]
def test_binaries(self):
program = Program(ctx, source=source)
self.assertEqual(program.binaries, dict.fromkeys(ctx.devices))
program.build()
binaries = program.binaries
self.assertIsNotNone(binaries[ctx.devices[0]])
self.assertEqual(len(binaries[ctx.devices[0]]), program.binary_sizes[0])
program2 = Program(ctx, binaries=binaries)
self.assertIsNone(program2.source)
self.assertEqual(program2.binaries, binaries)
def test_set_args(self):
program = Program(ctx, source=source)
program.build()
generate_sin = program.kernel('generate_sin')
generate_sin.argtypes = [global_memory(), ctypes.c_float]
buf = empty(ctx, [10], ctype=cl.cl_float2)
queue = Queue(ctx, ctx.devices[0])
generate_sin.set_args(buf, 1.0)
queue.enqueue_nd_range_kernel(generate_sin, 1, global_work_size=[buf.size])
expected = np.zeros([10], dtype=[('x', np.float32), ('y', np.float32)])
expected['x'] = np.arange(10)
expected['y'] = np.sin(expected['x'] / 10)
with buf.map(queue) as host:
self.assertTrue(np.all(expected['x'] == np.asarray(host)[:, 0]))
self.assertTrue(np.allclose(expected['y'], np.asarray(host)[:, 1]))
generate_sin.argnames = ['a', 'scale']
generate_sin.set_args(a=buf, scale=1.0)
queue.enqueue_nd_range_kernel(generate_sin, 1, global_work_size=[buf.size])
with buf.map(queue) as host:
self.assertTrue(np.all(expected['x'] == np.asarray(host)[:, 0]))
self.assertTrue(np.allclose(expected['y'], np.asarray(host)[:, 1]))
with self.assertRaises(TypeError):
generate_sin.set_args(a=buf)
generate_sin.__defaults__ = [1.0]
generate_sin.set_args(a=buf)
queue.enqueue_nd_range_kernel(generate_sin, 1, global_work_size=[buf.size])
with buf.map(queue) as host:
self.assertTrue(np.all(expected['x'] == np.asarray(host)[:, 0]))
self.assertTrue(np.allclose(expected['y'], np.asarray(host)[:, 1]))
def test_devices(self):
program = Program(ctx, source=source)
program.build()
def test_program(self):
program = Program(ctx, source=source)
program.build()
