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feat: implement dependencies analysis #25

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Merged
kilinchange merged 1 commit into from
Apr 24, 2025
Merged

feat: implement dependencies analysis #25

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4 changes: 3 additions & 1 deletion infini_train/include/autograd/function.h
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Original file line number Diff line number Diff line change
Expand Up @@ -24,13 +24,15 @@ class Function : public std::enable_shared_from_this<Function> {
std::vector<std::shared_ptr<Tensor>> Apply(const std::vector<std::shared_ptr<Tensor>> &input_tensors);
virtual void BackwardPartial(const std::shared_ptr<Tensor> &grad_output, int idx);

void ResetState();
void IncreaseDependenciesNumber();

protected:
std::vector<std::shared_ptr<Tensor>> saved_tensors_;

private:
std::vector<std::pair<std::shared_ptr<Function>, int>> next_functions_;
int dependencies_number_ = 0;
int dependencies_reached_ = 0;
int grad_outputs_reached_ = 0;
std::vector<std::shared_ptr<Tensor>> grad_outputs_;
const std::string type_;
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27 changes: 14 additions & 13 deletions infini_train/src/autograd/function.cc
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Expand Up @@ -64,6 +64,9 @@ std::vector<std::shared_ptr<Tensor>> Function::Apply(const std::vector<std::shar
next_functions_.emplace_back(std::make_shared<AccumulateGrad>(input_tensor->grad()), 0);
} else {
next_functions_.emplace_back(input_tensor->grad_fn(), input_tensor->output_idx());
if (input_tensor->grad_fn()) {
input_tensor->grad_fn()->IncreaseDependenciesNumber();
}
}
output_requires_grad |= input_tensor->requires_grad();
}
Expand All @@ -84,10 +87,16 @@ std::vector<std::shared_ptr<Tensor>> Function::Apply(const std::vector<std::shar

void Function::BackwardPartial(const std::shared_ptr<Tensor> &grad_output, int grad_output_idx) {
LOG(INFO) << "start backward_partial of function: " << type_;
CHECK(!grad_outputs_[grad_output_idx]);
grad_outputs_[grad_output_idx] = grad_output;
++grad_outputs_reached_;
if (grad_outputs_reached_ == grad_outputs_.size()) {
if (!grad_outputs_[grad_output_idx]) {
grad_outputs_[grad_output_idx] = grad_output;
++grad_outputs_reached_;
} else {
auto accumulate_function = std::make_shared<AccumulateGrad>(grad_outputs_[grad_output_idx]);
accumulate_function->BackwardPartial(grad_output, 0);
}
++dependencies_reached_;
if (grad_outputs_reached_ == grad_outputs_.size()
&& (dependencies_reached_ == dependencies_number_ || dependencies_number_ == 0)) {
auto grad_inputs = Backward(grad_outputs_);
CHECK_EQ(grad_inputs.size(), next_functions_.size());
for (int idx = 0; idx < grad_inputs.size(); ++idx) {
Expand All @@ -97,15 +106,7 @@ void Function::BackwardPartial(const std::shared_ptr<Tensor> &grad_output, int g
next_function->BackwardPartial(grad_input, output_idx);
}
}
// When a tensor is consumed by multiple operations, there may be multiple backward paths. As a result, the same
// function might be reused during backpropagation. Therefore, it's necessary to clear the state specific to
// this backward path.
ResetState();
}
}

void Function::ResetState() {
grad_outputs_reached_ = 0;
for (auto &tensor : grad_outputs_) { tensor.reset(); }
}
void Function::IncreaseDependenciesNumber() { ++dependencies_number_; }
} // namespace infini_train::autograd