forked from pytorch/pytorch
-
Notifications
You must be signed in to change notification settings - Fork 0
/
forward_grad.cpp
80 lines (68 loc) · 2.55 KB
/
forward_grad.cpp
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
#include <torch/csrc/autograd/forward_grad.h>
namespace torch {
namespace autograd {
namespace {
// See discussion in forward_grad.h for why these are global variables and not
// thread local
std::mutex all_forward_levels_mutex_;
std::vector<std::shared_ptr<ForwardADLevel>> all_forward_levels_;
const static at::Tensor singleton_undefined_tensor;
} // namespace
uint64_t ForwardADLevel::get_next_idx() {
std::lock_guard<std::mutex> lock(all_forward_levels_mutex_);
auto next_idx = all_forward_levels_.size();
TORCH_CHECK(
next_idx == 0, "Nested forward mode AD is not supported at the moment");
all_forward_levels_.push_back(std::make_shared<ForwardADLevel>(next_idx));
return next_idx;
}
void ForwardADLevel::release_idx(uint64_t idx) {
std::unique_lock<std::mutex> lock(all_forward_levels_mutex_);
TORCH_CHECK(
idx + 1 == all_forward_levels_.size(),
"Exiting a forward AD level that is not the "
"last that was created is not support. Ensure they are released in the reverse "
"order they were created.");
TORCH_INTERNAL_ASSERT(all_forward_levels_.size() > 0);
// Keep the level alive until we have released the lock
auto lvl = all_forward_levels_.back();
all_forward_levels_.pop_back();
lock.unlock();
}
std::shared_ptr<ForwardADLevel> ForwardADLevel::get_by_idx(uint64_t idx) {
std::lock_guard<std::mutex> lock(all_forward_levels_mutex_);
TORCH_CHECK(
idx < all_forward_levels_.size(),
"Trying to access a forward AD level with an invalid index. "
"This index was either not created or is already deleted.");
return all_forward_levels_[idx];
}
std::shared_ptr<ForwardADLevel> ForwardADLevel::try_get_by_idx(uint64_t idx) {
std::lock_guard<std::mutex> lock(all_forward_levels_mutex_);
if (idx < all_forward_levels_.size()) {
return all_forward_levels_[idx];
} else {
return nullptr;
}
}
ForwardADLevel::~ForwardADLevel() {
std::lock_guard<std::mutex> lock(mutex_);
auto it = grads_.begin();
while (it != grads_.end()) {
// Warning this will lock *it mutex
// This is ok as this function is the *only* one to call back into another
// class's method.
(*it)->reset(idx_, /* update_level */ false);
it = grads_.erase(it);
}
}
const at::Tensor& ForwardGrad::value(uint64_t level) const {
std::lock_guard<std::mutex> lock(mutex_);
const auto& it = content_.find(level);
return it == content_.end() ? singleton_undefined_tensor : (*it).second;
}
const at::Tensor& ForwardGrad::undef_grad() {
return singleton_undefined_tensor;
}
} // namespace autograd
} // namespace torch