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https://github.com/zebrajr/pytorch.git
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d67a265881
Summary: This merges changes that have already been reviewed/landed onto lazy_tensor_staging branch. It combines changes from multiple PRs into one diff. updated from lazy_tensor_staging on 3/16 Pull Request resolved: https://github.com/pytorch/pytorch/pull/74311 Test Plan: Run CI to ensure compilation on various platforms Run unit tests on lazy_tensor_staging branch with source version of all these diffs Reviewed By: desertfire Differential Revision: D34929235 fbshipit-source-id: babbc3bbeabc5b8107ee9284ed7765887a148622 (cherry picked from commit d91577a6557343ec536f6859e4808ec1a8a9b685)
103 lines
3.0 KiB
C++
103 lines
3.0 KiB
C++
#include <gtest/gtest.h>
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#include <c10/util/Exception.h>
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#include <torch/csrc/lazy/core/cache.h>
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#include <torch/csrc/lazy/core/hash.h>
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#include <torch/csrc/lazy/core/ir.h>
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#include <torch/csrc/lazy/core/shape.h>
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#include <torch/csrc/lazy/ts_backend/ts_node.h>
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namespace torch {
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namespace lazy {
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class CacheNode : public Node {
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public:
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explicit CacheNode(const std::string& str)
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: Node(OpKind(), /* num_outputs */ 1, /* hash_func */ [&](bool /*bakeInSizes*/) -> hash_t { return Hash(str); }),
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str_(str) {}
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~CacheNode() override = default;
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const std::vector<Output>& operands() const override {
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TORCH_INTERNAL_ASSERT(false, "Can't access operands of test node");
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}
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const Output& operand(size_t i) const override {
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TORCH_INTERNAL_ASSERT(false, "Can't access operand[i] of test node");
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}
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const Shape& shape(size_t i) const override { return shape_; }
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c10::ArrayRef<Shape> shapes() const override { return {shape_}; }
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private:
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std::string str_;
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Shape shape_;
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};
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TEST(CacheTest, BasicTest) {
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std::shared_ptr<CacheNode> a = std::make_shared<CacheNode>("a");
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std::shared_ptr<CacheNode> b = std::make_shared<CacheNode>("b");
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std::shared_ptr<CacheNode> c = std::make_shared<CacheNode>("c");
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Cache<hash_t, CacheNode, HashReducer> cache(2);
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cache.Add(a->node_hash(), a);
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EXPECT_EQ(cache.Get(a->node_hash()), a);
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EXPECT_EQ(cache.Get(b->node_hash()), nullptr);
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EXPECT_EQ(cache.Get(c->node_hash()), nullptr);
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cache.Add(b->node_hash(), b);
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EXPECT_EQ(cache.Get(a->node_hash()), a);
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EXPECT_EQ(cache.Get(b->node_hash()), b);
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EXPECT_EQ(cache.Get(c->node_hash()), nullptr);
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cache.Add(c->node_hash(), c);
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EXPECT_EQ(cache.Get(a->node_hash()), nullptr); // a has been evicted
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EXPECT_EQ(cache.Get(b->node_hash()), b);
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EXPECT_EQ(cache.Get(c->node_hash()), c);
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cache.Erase(c->node_hash());
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EXPECT_EQ(cache.Get(a->node_hash()), nullptr);
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EXPECT_EQ(cache.Get(b->node_hash()), b);
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EXPECT_EQ(cache.Get(c->node_hash()), nullptr); // c has been removed
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cache.Clear();
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EXPECT_EQ(cache.Get(a->node_hash()), nullptr);
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EXPECT_EQ(cache.Get(b->node_hash()), nullptr);
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EXPECT_EQ(cache.Get(c->node_hash()), nullptr);
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}
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class CacheNodeWithShape : public TsNode {
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public:
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explicit CacheNodeWithShape(const Shape& shape)
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: TsNode(OpKind(), shape, /* num_outputs */ 1, /* seed */ 0),
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shape_(shape) {}
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const Shape& getShape() const {
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return shape_;
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}
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private:
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Shape shape_;
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};
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TEST(CacheTest, ShapeCacheTestForDynamicShape) {
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// enable dynamic shape
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FLAGS_ltc_enable_dynamic_shapes = true;
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CacheNodeWithShape nodes[] = {
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CacheNodeWithShape(Shape(c10::kFloat, {2, 4})),
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CacheNodeWithShape(Shape(c10::kFloat, {4, 2})) };
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/*
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* Make sure the cached shape for node (2, 4) is not used for node (4, 2)
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*/
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for (auto& node : nodes) {
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EXPECT_EQ(node.getShape(), node.GetOpShape([&]() {
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return node.getShape();
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}));
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}
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// reset the flag
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FLAGS_ltc_enable_dynamic_shapes = false;
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}
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} // namespace lazy
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} // namespace torch
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