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d04889323e
We were running into a few issues with running multithreaded backwards in aot_autograd: such as https://github.com/pytorch/pytorch/issues/86136, and `FakeTensorMode` getting into a weird state as a result of not executing functions completely sequentially. The multithreaded backwards is lost in translation when we trace out the backwards anyway, and adds a lot of additional complexity. Pull Request resolved: https://github.com/pytorch/pytorch/pull/86245 Approved by: https://github.com/albanD, https://github.com/yf225
24 lines
548 B
C++
24 lines
548 B
C++
#include <c10/core/AutogradState.h>
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namespace c10 {
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namespace {
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// By default, grad mode and mulithreading are enabled, inference mode is
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// disabled,
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thread_local AutogradState autograd_state_tls = AutogradState(
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/* grad_mode */ true,
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/* inference_mode */ false,
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/* fw_grad_mode */ true,
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/* multithreading_enabled */ true);
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} // namespace
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AutogradState& AutogradState::get_tls_state() {
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return autograd_state_tls;
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}
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void AutogradState::set_tls_state(AutogradState state) {
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autograd_state_tls = state;
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}
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} // namespace c10
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