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Summary: Pull Request resolved: https://github.com/pytorch/pytorch/pull/44238 Refactor create_autodiff_subgraphs to use the same updating of output aliasing properties logic as tensorexpr fuser, and factor that out to a common function in subgraph utils. Test Plan: Imported from OSS Reviewed By: Krovatkin, robieta Differential Revision: D23871565 Pulled By: eellison fbshipit-source-id: 72df253b16baf8e4aabf3d68b103b29e6a54d44c
384 lines
13 KiB
C++
384 lines
13 KiB
C++
#include <torch/csrc/jit/passes/utils/subgraph_utils.h>
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#include <torch/csrc/jit/passes/canonicalize.h>
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namespace torch {
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namespace jit {
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namespace SubgraphUtils {
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namespace {
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bool hasSubgraph(Node* n) {
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return n->hasAttribute(attr::Subgraph);
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}
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std::vector<c10::optional<const Use>> gatherLastUses(
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at::ArrayRef<Value*> values) {
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return fmap(values, [&](Value* v) -> c10::optional<const Use> {
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return firstOrLastUse(v, /*find_first*/ false);
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});
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}
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// When merging a node into a subgraph, we wish to preserve all of the
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// aliasing properties of the node's outputs. It is difficult to track
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// the node or its contained nodes through all of the ir manipulation
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// involved in merging; it is pretty easy to uniquely identify the value
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// based on its uses. We can identify the value by its last use in the graph.
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// Values which do not have uses or which do not have a last use
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// outside of the subgraph to be merged into we do not need to track.
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struct ValueMapper {
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ValueMapper(Node* to_merge, AliasDb& db, size_t subgraph_num_outputs) {
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last_uses_ = gatherLastUses(to_merge->outputs());
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subgraph_num_outputs_ = subgraph_num_outputs;
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WithInsertPoint guard(to_merge);
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auto g = to_merge->owningGraph();
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// temporary node to put the aliasing properties of the node before its
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// merged and destroyed
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placeholder_node_ = g->insertNode(g->create(prim::Uninitialized, 0));
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for (size_t i = 0; i < to_merge->outputs().size(); ++i) {
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Value* existing = to_merge->outputs().at(i);
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Value* new_value = placeholder_node_->insertOutput(i)->copyMetadata(
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to_merge->outputs().at(i));
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db.replaceWithNewValue(existing, new_value);
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}
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}
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bool usesEqual(const Use& a, const Use& b) {
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return a.user == b.user && a.offset == b.offset;
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}
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void copyAliasing(Node* merged_node, AliasDb& db) {
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auto num_outputs = merged_node->outputs().size();
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auto new_outputs = merged_node->outputs().slice(
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subgraph_num_outputs_, num_outputs - subgraph_num_outputs_);
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for (Value* v : new_outputs) {
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auto maybe_last_use = firstOrLastUse(v, /*find_first*/ false);
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// if it doesnt have a use it shouldnt have been added as output
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TORCH_INTERNAL_ASSERT(maybe_last_use);
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const Use last_use = *maybe_last_use;
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size_t i = 0;
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while (i < last_uses_.size() && last_uses_.at(i).has_value() &&
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!usesEqual(*last_uses_.at(i), last_use)) {
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++i;
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}
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TORCH_INTERNAL_ASSERT(i != last_uses_.size());
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db.replaceWithNewValue(placeholder_node_->outputs().at(i), v);
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}
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placeholder_node_->destroy();
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}
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std::vector<c10::optional<const Use>> last_uses_;
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size_t subgraph_num_outputs_;
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Node* placeholder_node_;
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};
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Node* executeSubgraphMergeAndUpdateAliasing(
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Node* to_merge,
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c10::optional<Node*> existing,
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AliasDb& db,
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const std::function<Node*(void)>& merge_fn) {
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// When we merge a node into a subgraph, the new subgraph outputs
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// have the same aliasing properties as the original node's outputs.
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// Here we create a placeholder node, transfer the aliasing properties
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// to the placeholder, execute the merge, and transfer the aliasing
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// properties to the appropriate fusion group outputs
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ValueMapper vm(to_merge, db, existing ? (*existing)->outputs().size() : 0);
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Node* fusion_group = merge_fn();
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vm.copyAliasing(fusion_group, db);
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return fusion_group;
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}
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// Combine the nodes in two subgraph together. The nodes will end up in
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// `mergeTo`, and `mergeFrom` is destroyed.
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void mergeSubgraph(
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Node* mergeTo,
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Node* mergeFrom,
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std::unordered_map<Value*, Value*>& vmap) {
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Node* nodeBeforeMergeFrom = mergeFrom->prev();
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Node* nodeAfterMergeFrom = mergeFrom->next();
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// will be used later to map the node outputs -> new subgraph values
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std::unordered_map<Value*, Value*> node_outputs_to_subgraph_values;
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for (size_t i = 0; i < mergeFrom->outputs().size(); ++i) {
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node_outputs_to_subgraph_values[mergeFrom->output(i)] =
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getSubgraph(mergeFrom)->outputs().at(i);
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}
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// unmerge_map will contain mapping from values from the mergeTo's subgraph
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// (we will call them "original" values) to the corresponding values that we
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// created in the main graph (we will call them "unmerged" values) as we
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// unmerged the mergeTo's subgraph.
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std::unordered_map<Value*, Value*> unmerge_vmap;
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unmergeSubgraph(mergeFrom, unmerge_vmap);
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std::vector<Node*> nodes;
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const auto end_it = nodeBeforeMergeFrom->reverseIterator();
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auto it = nodeAfterMergeFrom->reverseIterator();
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++it;
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// Now we're merging the "unmerged" nodes into the mergeFrom subgraph. That
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// will give us a new map: "unmerged" -> "merged".
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std::unordered_map<Value*, Value*> merge_vmap;
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while (it != end_it) {
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// NB: mergeNodeIntoSubgraph destroys node, hence the complications
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Node* node = *it;
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++it;
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mergeNodeIntoSubgraph(node, mergeTo, merge_vmap);
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}
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// Vmap should contain "original" -> "merged" mapping, thus we basically need
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// to perform the following transformation:
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// vmap[x] = merge_vmap[unmerge_map[x]]
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for (auto& kv : unmerge_vmap) {
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if (merge_vmap.count(kv.second)) {
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vmap[kv.first] = merge_vmap.at(kv.second);
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} else {
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vmap[kv.first] = kv.second;
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}
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}
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// fill the value mapping with node output -> new subgraph value
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for (const auto& mapping : node_outputs_to_subgraph_values) {
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vmap[mapping.first] = vmap[mapping.second];
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}
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}
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// Combine the nodes in two subgraph together. The nodes will end up in
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// `mergeTo`, and `mergeFrom` is destroyed.
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void mergeSubgraph(Node* mergeTo, Node* mergeFrom) {
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std::unordered_map<Value*, Value*> vmap;
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mergeSubgraph(mergeTo, mergeFrom, vmap);
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}
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} // namespace
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std::shared_ptr<Graph> getSubgraph(Node* n) {
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return n->g(attr::Subgraph);
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}
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void unmergeSubgraph(
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Node* subgraphNode,
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std::unordered_map<Value*, Value*>& vmap) {
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// Inline the graph, replace uses of node outputs and destroy the node
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auto outerGraph = subgraphNode->owningGraph();
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WithInsertPoint guard(subgraphNode);
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const auto subgraphOutputs = insertGraph(
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*outerGraph, *getSubgraph(subgraphNode), subgraphNode->inputs(), vmap);
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AT_ASSERT(subgraphOutputs.size() >= subgraphNode->outputs().size());
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for (size_t i = 0; i < subgraphNode->outputs().size(); ++i) {
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subgraphNode->outputs()[i]->replaceAllUsesWith(subgraphOutputs[i]);
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}
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subgraphNode->destroy();
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}
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void unmergeSubgraph(Node* subgraphNode) {
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std::unordered_map<Value*, Value*> vmap;
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unmergeSubgraph(subgraphNode, vmap);
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}
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void collectNestedUses(
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std::unordered_set<Value*>& closed_over_values,
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std::unordered_set<Value*>& new_values,
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std::unordered_map<Value*, Value*>& inputsMap,
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Node* input_node) {
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for (auto input : input_node->inputs()) {
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if (inputsMap.count(input) == 0 && new_values.count(input) == 0) {
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closed_over_values.insert(input);
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}
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}
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if (input_node->kind() == prim::If) {
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for (Block* block : input_node->blocks()) {
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for (Node* node : block->nodes()) {
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collectNestedUses(closed_over_values, new_values, inputsMap, node);
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}
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for (Value* v : block->outputs()) {
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if (inputsMap.count(v) == 0 && new_values.count(v) == 0) {
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closed_over_values.insert(v);
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}
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}
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}
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} else if (input_node->kind() == prim::Loop) {
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for (Value* v : input_node->inputs()) {
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if (inputsMap.count(v) == 0 && new_values.count(v) == 0) {
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closed_over_values.insert(v);
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}
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}
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Block* block = input_node->blocks().at(0);
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for (Value* v : block->inputs()) {
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new_values.insert(v);
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}
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for (Node* node : block->nodes()) {
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collectNestedUses(closed_over_values, new_values, inputsMap, node);
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}
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} else if (input_node->blocks().size() != 0) {
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TORCH_INTERNAL_ASSERT(false, input_node, " kind not handled yet");
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}
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for (Value* output : input_node->outputs()) {
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new_values.insert(output);
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}
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}
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std::unordered_set<Value*> closedOverValues(
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Node* toMerge,
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std::unordered_map<Value*, Value*>& inputsMap) {
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std::unordered_set<Value*> closed_over_values;
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std::unordered_set<Value*> new_values;
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collectNestedUses(closed_over_values, new_values, inputsMap, toMerge);
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return closed_over_values;
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}
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void mergeNodeIntoSubgraph(
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Node* toMerge,
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Node* subgraphNode,
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std::unordered_map<Value*, Value*>& vmap) {
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AT_ASSERT(hasSubgraph(subgraphNode) && toMerge != subgraphNode);
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if (hasSubgraph(toMerge)) {
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return mergeSubgraph(subgraphNode, toMerge, vmap);
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}
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auto subgraph = getSubgraph(subgraphNode);
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// Map from values in the surrounding graph to inputs in the subgraph
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std::unordered_map<Value*, Value*> inputsMap;
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AT_ASSERT(subgraphNode->inputs().size() == subgraph->inputs().size());
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size_t idx = 0;
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for (auto input : subgraphNode->inputs()) {
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inputsMap[input] = subgraph->inputs()[idx];
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idx++;
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}
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// Add n's inputs to the group's input list if we don't already have them
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WithInsertPoint guard(*subgraph->nodes().begin());
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std::unordered_set<Value*> closedValues =
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closedOverValues(toMerge, inputsMap);
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// There are currently downstream usage that relies on a fixed ordering
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// of graph inputs. TODO: remove
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std::vector<Value*> orderedClosedValues;
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std::unordered_set<Value*> orderedSeenValues;
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for (Value* input : toMerge->inputs()) {
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orderedClosedValues.push_back(input);
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orderedSeenValues.insert(input);
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}
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for (Value* closedValue : closedValues) {
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if (!orderedSeenValues.count(closedValue)) {
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orderedClosedValues.push_back(closedValue);
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orderedSeenValues.insert(closedValue);
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}
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}
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for (auto input : orderedClosedValues) {
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if (inputsMap.count(input) == 0) {
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// Clone constants inside the subgraph instead of referencing them, to
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// enable more optimizations
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if (auto value = toIValue(input)) {
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auto nv = subgraph->insertConstant(*value);
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nv->setType(input->type()); // Need to retain type information on Nones
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inputsMap[input] = nv;
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} else {
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// The common case: this is a regular input, so just register it with
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// the group node and inner subgraph
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subgraphNode->addInput(input);
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auto inputToGraph = subgraph->addInput();
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inputToGraph->setType(input->type());
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inputsMap[input] = inputToGraph;
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}
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}
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}
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// Merge the node into the graph
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auto mergedNode = subgraph->insertNode(
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subgraph->createClone(toMerge, [&](Value* v) { return inputsMap[v]; }));
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for (size_t idx = 0; idx < toMerge->outputs().size(); idx++) {
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vmap[toMerge->output(idx)] = mergedNode->output(idx);
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}
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for (size_t idx = 0; idx < toMerge->inputs().size(); idx++) {
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vmap[toMerge->input(idx)] = mergedNode->input(idx);
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}
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// If n's outputs were inputs to `group`, remove them since we just merged
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// n in.
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//
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// i.e.,
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// x = f(w); group(x, y, z) becomes group(w, y, z).
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// x, y, z = f(w); group(x, y, z) becomes group(w).
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auto inputs = subgraphNode->inputs();
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for (size_t i = 0; i < toMerge->outputs().size(); ++i) {
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auto it = std::find(inputs.begin(), inputs.end(), toMerge->outputs()[i]);
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if (it != inputs.end()) {
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size_t p = it - inputs.begin();
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subgraphNode->removeInput(p);
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subgraph->inputs()[p]->replaceAllUsesWith(mergedNode->outputs()[i]);
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vmap[subgraph->inputs()[p]] = mergedNode->output(i);
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subgraph->eraseInput(p);
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}
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}
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// Add n's outputs to the group node and inner subgraph outputs.
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for (size_t i = 0; i < toMerge->outputs().size(); i++) {
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auto oldOutput = toMerge->outputs()[i];
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// Only register the output in the group node if it's actually used
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// outside the subgraph.
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const auto hasUsesOutsideSubgraph = std::any_of(
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oldOutput->uses().cbegin(),
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oldOutput->uses().cend(),
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[&](const Use& use) { return use.user->isAfter(subgraphNode); });
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if (hasUsesOutsideSubgraph) {
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auto newOutput = mergedNode->outputs()[i];
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subgraph->registerOutput(newOutput);
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auto groupOutput = subgraphNode->addOutput();
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groupOutput->copyMetadata(oldOutput);
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oldOutput->replaceAllUsesWith(groupOutput);
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}
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}
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// Remove the original node now that the merge is complete
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toMerge->destroy();
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}
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void mergeNodeIntoSubgraph(Node* toMerge, Node* subgraphNode) {
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std::unordered_map<Value*, Value*> vmap;
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mergeNodeIntoSubgraph(toMerge, subgraphNode, vmap);
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}
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Node* createSingletonSubgraph(
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Node* n,
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Symbol subgraphKind,
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std::unordered_map<Value*, Value*>& vmap) {
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auto graph = n->owningGraph();
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auto subgraph = graph->create(subgraphKind, 0);
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subgraph->g_(attr::Subgraph, std::make_shared<Graph>(graph->current_scope()));
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subgraph->insertBefore(n);
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mergeNodeIntoSubgraph(n, subgraph, vmap);
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return subgraph;
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}
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Node* createSingletonSubgraph(Node* n, Symbol subgraphKind) {
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std::unordered_map<Value*, Value*> vmap;
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return createSingletonSubgraph(n, subgraphKind, vmap);
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}
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void mergeNodeIntoSubgraphAndUpdateAliasing(
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Node* to_merge,
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Node* subgraphNode,
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AliasDb& db) {
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executeSubgraphMergeAndUpdateAliasing(to_merge, subgraphNode, db, [&]() {
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mergeNodeIntoSubgraph(to_merge, subgraphNode);
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return subgraphNode;
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});
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}
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Node* createSingletonSubgraphAndUpdateAliasing(
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Node* to_merge,
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Symbol subgraphKind,
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AliasDb& db) {
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return executeSubgraphMergeAndUpdateAliasing(
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to_merge, c10::nullopt, db, [&]() {
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return createSingletonSubgraph(to_merge, subgraphKind);
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});
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}
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} // namespace SubgraphUtils
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} // namespace jit
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} // namespace torch
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