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Fix deep recursion with siblings (#1462)
* fix recursion with siblings * fix * add test * increase tol
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@ -242,25 +242,35 @@ array::ArrayDesc::~ArrayDesc() {
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// This calls recursively the destructor and can result in stack overflow, we
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// instead put them in a vector and destroy them one at a time resulting in a
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// max stack depth of 2.
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if (inputs.empty()) {
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return;
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}
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std::vector<std::shared_ptr<ArrayDesc>> for_deletion;
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for (array& a : inputs) {
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if (a.array_desc_.use_count() == 1) {
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auto append_deletable_inputs = [&for_deletion](ArrayDesc& ad) {
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std::unordered_map<std::uintptr_t, array> input_map;
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for (array& a : ad.inputs) {
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if (a.array_desc_) {
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input_map.insert({a.id(), a});
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}
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}
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ad.inputs.clear();
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for (auto& [_, a] : input_map) {
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if (a.array_desc_.use_count() <= a.siblings().size() + 1) {
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for_deletion.push_back(std::move(a.array_desc_));
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}
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}
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};
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append_deletable_inputs(*this);
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while (!for_deletion.empty()) {
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// top is going to be deleted at the end of the block *after* the arrays
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// with inputs have been moved into the vector
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auto top = std::move(for_deletion.back());
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for_deletion.pop_back();
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for (array& a : top->inputs) {
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if (a.array_desc_.use_count() == 1) {
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for_deletion.push_back(std::move(a.array_desc_));
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}
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}
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append_deletable_inputs(*top);
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}
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}
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@ -1868,6 +1868,33 @@ class TestArray(mlx_tests.MLXTestCase):
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with self.assertRaises(ValueError):
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int(a)
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def test_deep_graphs(self):
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# The following tests should simply run cleanly without a segfault or
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# crash due to exceeding recursion depth limits.
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# Deep graph destroyed without eval
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x = mx.array([1.0, 2.0])
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for _ in range(100_000):
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x = mx.sin(x)
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del x
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# Duplicate input deep graph destroyed without eval
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x = mx.array([1.0, 2.0])
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for _ in range(100_000):
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x = x + x
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# Deep graph with siblings destroyed without eval
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x = mx.array([1, 2])
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for _ in range(100_000):
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x = mx.concatenate(mx.split(x, 2))
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del x
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# Deep graph with eval
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x = mx.array([1.0, 2.0])
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for _ in range(100_000):
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x = mx.sin(x)
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mx.eval(x)
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if __name__ == "__main__":
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unittest.main()
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@ -902,7 +902,7 @@ class TestConv(mlx_tests.MLXTestCase):
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dw10 = (cotan[1::s, :-1:s] * x).sum()
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dw11 = (cotan[1::s, 1::s] * x).sum()
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expected = mx.array([[dw00, dw01], [dw10, dw11]])
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self.assertTrue(mx.allclose(dw, expected))
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self.assertTrue(mx.allclose(dw, expected, rtol=1e-5, atol=1e-5))
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def test_conv_groups_grad(self):
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def fn(x, w):
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