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https://github.com/ml-explore/mlx.git
synced 2025-12-16 01:49:05 +08:00
Fix for captured state
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@@ -395,7 +395,16 @@ struct PyCompiledFun {
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nb::object captured_inputs;
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nb::object captured_outputs;
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bool shapeless;
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mutable size_t num_outputs{0};
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// Data to attach to the compiled function that contains the python output
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// structure and the number of arrays in said structure.
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struct AttachedData {
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nb::object output_structure;
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int num_outputs;
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AttachedData(nb::object output_structure_, int num_outputs_)
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: output_structure(output_structure_), num_outputs(num_outputs_) {}
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};
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PyCompiledFun(
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const nb::callable& fun,
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@@ -418,7 +427,6 @@ struct PyCompiledFun {
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captured_inputs = std::move(other.captured_inputs);
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captured_outputs = std::move(other.captured_outputs);
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shapeless = other.shapeless;
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num_outputs = other.num_outputs;
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};
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nb::object call_impl(const nb::args& args, const nb::kwargs& kwargs) {
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@@ -502,12 +510,9 @@ struct PyCompiledFun {
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auto [outputs, py_outputs] =
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tree_flatten_with_structure(std::move(tree_outputs), false);
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std::shared_ptr<void> py_outputs_void(
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py_outputs.release().ptr(), [](void* handle) {
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nb::steal(reinterpret_cast<PyObject*>(handle)).reset();
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});
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std::shared_ptr<void> extra_data =
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std::make_shared<AttachedData>(py_outputs, outputs.size());
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num_outputs = outputs.size();
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if (!captured_outputs.is_none()) {
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auto flat_out_captures = tree_flatten(captured_outputs, false);
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outputs.insert(
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@@ -520,7 +525,7 @@ struct PyCompiledFun {
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if (!captured_inputs.is_none()) {
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tree_replace(captured_inputs, trace_captures, flat_in_captures);
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}
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return mx::detail::ArraysAndExtra{outputs, py_outputs_void};
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return mx::detail::ArraysAndExtra{outputs, extra_data};
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};
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if (!captured_inputs.is_none()) {
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@@ -532,8 +537,14 @@ struct PyCompiledFun {
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}
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// Compile and call
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auto [outputs, py_outputs_void] =
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auto [outputs, extra_data] =
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mx::detail::compile(compile_fun, fun_id, shapeless, constants)(inputs);
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int num_outputs =
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reinterpret_cast<AttachedData*>(extra_data.get())->num_outputs;
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nb::object py_outputs =
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reinterpret_cast<AttachedData*>(extra_data.get())->output_structure;
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if (!captured_outputs.is_none()) {
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std::vector<mx::array> captures(
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std::make_move_iterator(outputs.begin() + num_outputs),
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@@ -542,9 +553,7 @@ struct PyCompiledFun {
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}
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// Put the outputs back in the container
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nb::object py_outputs =
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nb::borrow(reinterpret_cast<PyObject*>(py_outputs_void.get()));
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return tree_unflatten_from_structure(py_outputs, outputs);
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return tree_unflatten_from_structure(std::move(py_outputs), outputs);
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}
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nb::object operator()(const nb::args& args, const nb::kwargs& kwargs) const {
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@@ -1096,6 +1096,25 @@ class TestCompile(mlx_tests.MLXTestCase):
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d = fun(False, mx.array(1.0))
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self.assertTrue(d is None)
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def test_compile_changing_outputs_with_state(self):
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state = [mx.array(1.0)]
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@partial(mx.compile, inputs=state, outputs=state)
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def fun(y):
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x = state[0]
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if y.dtype == mx.float32:
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state[0] = 2 * y
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return [x, y, x + y]
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elif y.dtype == mx.int32:
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state[0] *= 2
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return x + y
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for i in range(10):
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fun(mx.array(1.0))
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fun(mx.array(1))
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self.assertEqual(state[0].item(), 4)
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if __name__ == "__main__":
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mlx_tests.MLXTestRunner()
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