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Updated python to align with current configuration

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This commit is contained in:
Alejandro Saucedo 2021-02-28 14:53:46 +00:00
parent 7dc1f35206
commit 38f356fdae
4 changed files with 50 additions and 19 deletions
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4
python/test/test_array_multiplication.py
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@ -30,5 +30,5 @@ def test_array_multiplication():
.record(kp.OpTensorSyncLocal([tensor_out]))
.eval())
assert tensor_out.data() == [2.0, 4.0, 6.0]
assert np.all(tensor_out.numpy() == [2.0, 4.0, 6.0])
assert tensor_out.data().tolist() == [2.0, 4.0, 6.0]
assert np.all(tensor_out.data() == [2.0, 4.0, 6.0])

47
python/test/test_kompute.py
View file

@ -69,7 +69,7 @@ void main()
.record(kp.OpTensorSyncLocal(params))
.eval())
assert tensor_out.data() == [2.0, 4.0, 6.0]
assert tensor_out.data().tolist() == [2.0, 4.0, 6.0]
def test_sequence():
"""
@ -116,8 +116,8 @@ def test_sequence():
assert sq.is_init() == False
assert tensor_out.data() == [2.0, 4.0, 6.0]
assert np.all(tensor_out.numpy() == [2.0, 4.0, 6.0])
assert tensor_out.data().tolist() == [2.0, 4.0, 6.0]
assert np.all(tensor_out.data() == [2.0, 4.0, 6.0])
tensor_in_a.destroy()
tensor_in_b.destroy()
@ -127,6 +127,39 @@ def test_sequence():
assert tensor_in_b.is_init() == False
assert tensor_out.is_init() == False
def test_pushconsts():
spirv = kp.Shader.compile_source("""
#version 450
layout(push_constant) uniform PushConstants {
float x;
float y;
float z;
} pcs;
layout (local_size_x = 1) in;
layout(set = 0, binding = 0) buffer a { float pa[]; };
void main() {
pa[0] += pcs.x;
pa[1] += pcs.y;
pa[2] += pcs.z;
}
""")
mgr = kp.Manager()
tensor = mgr.tensor([0, 0, 0])
algo = mgr.algorithm([tensor], spirv, (1, 1, 1))
(mgr.sequence()
.record(kp.OpTensorSyncDevice([tensor]))
.record(kp.OpAlgoDispatch(algo, [0.1, 0.2, 0.3]))
.record(kp.OpAlgoDispatch(algo, [0.3, 0.2, 0.1]))
.record(kp.OpTensorSyncLocal([tensor]))
.eval())
assert np.all(tensor.data() == np.array([0.4, 0.4, 0.4], dtype=np.float32))
def test_workgroup():
mgr = kp.Manager(0)
@ -151,9 +184,9 @@ def test_workgroup():
.record(kp.OpTensorSyncLocal([tensor_a, tensor_b]))
.eval())
print(tensor_a.numpy())
print(tensor_b.numpy())
print(tensor_a.data())
print(tensor_b.data())
assert np.all(tensor_a.numpy() == np.stack([np.arange(16)]*8, axis=1).ravel())
assert np.all(tensor_b.numpy() == np.stack([np.arange(8)]*16, axis=0).ravel())
assert np.all(tensor_a.data() == np.stack([np.arange(16)]*8, axis=1).ravel())
assert np.all(tensor_b.data() == np.stack([np.arange(8)]*16, axis=0).ravel())