mirror of
https://github.com/zebrajr/pytorch.git
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00aedfc0e2
Summary: Add a pass to move all constants to the beginning of the graph, and deduplicate. This extends https://github.com/pytorch/pytorch/pull/10231 to also handle constants introduced in inlining, constant propagation, etc. Pull Request resolved: https://github.com/pytorch/pytorch/pull/12222 Reviewed By: driazati Differential Revision: D10201616 Pulled By: eellison fbshipit-source-id: bc9c5be26868c8b5414257a0d4462de025aeb9bd
114 lines
3.4 KiB
C++
114 lines
3.4 KiB
C++
#include "torch/csrc/jit/ir.h"
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#include <algorithm>
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#include <unordered_map>
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#include "torch/csrc/jit/assertions.h"
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#include "torch/csrc/jit/interned_strings.h"
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#include "torch/csrc/jit/passes/common_subexpression_elimination.h"
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#include "torch/csrc/jit/node_hashing.h"
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#include "torch/csrc/utils/functional.h"
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#include "torch/csrc/utils/hash.h"
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namespace torch { namespace jit {
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namespace {
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bool tensorEqual(const at::Tensor& lhs, const at::Tensor& rhs) {
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return &lhs.type() == &rhs.type() && lhs.equal(rhs);
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}
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bool tensorListEqual(const std::vector<at::Tensor>& lhs, const std::vector<at::Tensor>& rhs) {
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if (lhs.size() != rhs.size()) return false;
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return std::equal(lhs.begin(), lhs.end(), rhs.begin(), tensorEqual);
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}
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// Check whether two nodes have the same attributes in CSE.
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// This function may be too conservative for general use.
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// Do NOT support g/gs attributes.
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bool attributesEqualCSE(const Node* lhs, const Node* rhs) {
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JIT_ASSERT(lhs != nullptr);
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JIT_ASSERT(rhs != nullptr);
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// One has attributes, the other does not.
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if (lhs->hasAttributes() != rhs->hasAttributes()) return false;
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// Neither has attributes.
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if (!lhs->hasAttributes() && !rhs->hasAttributes()) return true;
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auto lnames = lhs->attributeNames();
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auto rnames = rhs->attributeNames();
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std::sort(lnames.begin(), lnames.end());
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std::sort(rnames.begin(), rnames.end());
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if (lnames != rnames) return false;
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for (auto name : lnames) {
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if (lhs->kindOf(name) != rhs->kindOf(name)) return false;
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#define COMPARE_ATTRIBUTEVALUE(type) \
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case AttributeKind::type: \
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{ if (lhs->type(name) != rhs->type(name)) return false; } break;
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switch(lhs->kindOf(name)) {
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COMPARE_ATTRIBUTEVALUE(f)
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COMPARE_ATTRIBUTEVALUE(fs)
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COMPARE_ATTRIBUTEVALUE(i)
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COMPARE_ATTRIBUTEVALUE(is)
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COMPARE_ATTRIBUTEVALUE(s)
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COMPARE_ATTRIBUTEVALUE(ss)
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case AttributeKind::t: {
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if (!tensorEqual(lhs->t(name), rhs->t(name))) return false;
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break;
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}
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case AttributeKind::ts: {
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if (!tensorListEqual(lhs->ts(name), rhs->ts(name))) return false;
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break;
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}
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case AttributeKind::g:
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case AttributeKind::gs:
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return false;
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}
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#undef COMPARE_ATTRIBUTEVALUE
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}
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return true;
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}
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} // anonymous namespace
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size_t HashNode::operator()(const Node* k) const {
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JIT_ASSERT(k != nullptr);
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return get_hash(k->kind(),
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fmap(k->outputs(), [](const Value *v) { return v->type()->kind(); }),
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fmap(k->inputs(), [](const Value *v) { return v->unique(); }));
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};
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bool EqualNode::operator()(const Node* lhs, const Node* rhs) const {
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if (lhs == nullptr && rhs == nullptr) return true;
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if (lhs == nullptr || rhs == nullptr) return false;
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if (lhs->kind() != rhs->kind()) return false;
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// Check whether the output types are the same.
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auto lhs_outputs = lhs->outputs();
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auto rhs_outputs = rhs->outputs();
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if (lhs_outputs.size() != rhs_outputs.size()) return false;
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for (size_t i = 0; i < lhs_outputs.size(); ++i) {
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if (*lhs_outputs[i]->type() != *rhs_outputs[i]->type())
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return false;
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}
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// Check whether the inputs are the same.
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auto lhs_inputs = lhs->inputs();
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auto rhs_inputs = rhs->inputs();
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if (lhs_inputs.size() != rhs_inputs.size()) return false;
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if (!std::equal(lhs_inputs.begin(), lhs_inputs.end(), rhs_inputs.begin())) return false;
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if (!attributesEqualCSE(lhs, rhs)) return false;
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return true;
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};
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}}
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