marcoabreu commented on a change in pull request #14836: Refactor AGInfo and
Imperative
URL: https://github.com/apache/incubator-mxnet/pull/14836#discussion_r304786785
##########
File path: src/imperative/imperative.cc
##########
@@ -124,29 +124,34 @@ void Imperative::MarkVariables(
const std::vector<NDArray*>& variables,
const std::vector<mx_uint>& grad_reqs,
const std::vector<NDArray*>& gradients) {
- for (uint32_t i = 0; i < variables.size(); ++i) {
+ for (size_t i = 0; i < variables.size(); ++i) {
std::string str_c(std::to_string(variable_count_++));
-
- variables[i]->entry_ = nnvm::NodeEntry{
- nnvm::Symbol::CreateVariable("var" + str_c).outputs[0].node, 0, 0};
- AGInfo& info = AGInfo::Create(variables[i]->entry_.node);
- info.outputs.emplace_back(variables[i]->Detach());
- info.out_grads.emplace_back(gradients[i]->Detach());
- info.grad_req = static_cast<OpReqType>(grad_reqs[i]);
- info.ctx = variables[i]->ctx();
-
- gradients[i]->entry_ = nnvm::NodeEntry{
- nnvm::Symbol::CreateVariable("grad" + str_c).outputs[0].node, 0, 0};
- AGInfo& grad_info = AGInfo::Create(gradients[i]->entry_.node);
- grad_info.outputs.emplace_back(gradients[i]->Detach());
- grad_info.ctx = gradients[i]->ctx();
+ {
+ variables[i]->entry_ = nnvm::NodeEntry{
+ nnvm::Symbol::CreateVariable("var" + str_c).outputs[0].node, 0, 0};
+ AGInfo &info = AGInfo::Create(variables[i]->entry_.node);
+ info.outputs.emplace_back(variables[i]->Detach());
+ info.out_grads.emplace_back(gradients[i]->Detach());
+ info.grad_req = static_cast<OpReqType>(grad_reqs[i]);
+ info.ctx = variables[i]->ctx();
+ }
+ {
+ gradients[i]->entry_ = nnvm::NodeEntry{
+ nnvm::Symbol::CreateVariable("grad" + str_c).outputs[0].node, 0, 0};
+ AGInfo &grad_info = AGInfo::Create(gradients[i]->entry_.node);
+ grad_info.outputs.emplace_back(gradients[i]->Detach());
+ grad_info.ctx = gradients[i]->ctx();
+ }
}
}
+
+
+
Review comment:
This is a refactor already. I don't see any point for a subsequent PR if
this PR is doing the actual refactor already. Please address the comments from
@anirudhacharya and @apeforest .
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