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#include <iostream>
#include <sstream>
#include <string>
#include <gtest/gtest.h>
#include <test/cpp/jit/test_utils.h>
#include <torch/csrc/jit/ir/irparser.h>
#include <torch/csrc/jit/runtime/graph_iterator.h>
#include <torch/jit.h>
#include <torch/script.h>
#include <torch/torch.h>
namespace torch {
namespace jit {
/**
* Inverts an unordered map.
*/
template <typename K, typename V>
std::unordered_map<V, K> invert_map(std::unordered_map<K, V>& map) {
std::unordered_map<V, K> inverted;
std::for_each(map.begin(), map.end(), [&inverted](const std::pair<K, V>& p) {
inverted.insert(std::make_pair(p.second, p.first));
});
return inverted;
}
/**
* Traverses the graph using the DepthFirstGraphNodeIterator and
* returns an array containing the original names in the string
* graph.
*/
std::vector<std::string> traverse_depth_first(
std::string graph_string,
int max_count = 100) {
auto graph = std::make_shared<Graph>();
std::unordered_map<std::string, Value*> vmap;
torch::jit::parseIR(graph_string, graph.get(), vmap);
auto get_name = invert_map(vmap);
std::vector<std::string> result;
DepthFirstGraphNodeIterator graph_it(graph);
Node* node = graph_it.next();
int count = 0;
while (node && count < max_count) {
std::stringstream buffer;
std::vector<const torch::jit::Node*> vec;
node->print(buffer, 0, &vec, false, true, true, false);
result.push_back(buffer.str());
node = graph_it.next();
++count;
}
return result;
}
/** Checks that the iteration order matches the expected/provided order. */
void assert_ordering(
std::vector<std::string> actual,
std::initializer_list<std::string> expected_list) {
auto expected = std::vector<std::string>(expected_list);
ASSERT_EQ(expected.size(), actual.size())
<< "Got " << actual.size() << " elements (" << actual << ")"
<< " expected " << expected.size() << " elements (" << expected << ")";
for (unsigned i = 0; i < expected.size(); i++) {
ASSERT_EQ(expected[i], actual[i])
<< "Difference at index " << i << " in " << actual << " (expected "
<< actual << ")";
}
}
TEST(GraphIteratorTest, ConstantReturnGraph) {
const auto graph_string = R"IR(
graph():
%1 : int = prim::Constant[value=0]()
return (%1))IR";
auto graph = std::make_shared<Graph>();
torch::jit::parseIR(graph_string, graph.get());
DepthFirstGraphNodeIterator graph_it(graph);
ASSERT_EQ(graph_it.next()->kind(), prim::Constant);
ASSERT_EQ(graph_it.next(), nullptr);
}
TEST(GraphIteratorTest, GraphWithParameters) {
const auto graph_string = R"IR(
graph(%0 : Double(2)):
%1 : int = prim::Constant[value=0]()
return (%0))IR";
auto ordering = traverse_depth_first(graph_string);
assert_ordering(ordering, {"%1 : int = prim::Constant[value=0]()"});
}
TEST(GraphIteratorTest, GraphWithIf) {
const auto graph_string = R"IR(
graph(%a : Tensor):
%a : int = prim::Constant[value=30]()
%b : int = prim::Constant[value=10]()
%c : bool = aten::Bool(%a)
%d : int = prim::If(%c)
block0():
-> (%a)
block1():
-> (%b)
%e : int = prim::Constant[value=20]()
return (%d)
)IR";
auto ordering = traverse_depth_first(graph_string);
assert_ordering(
ordering,
{"%1 : int = prim::Constant[value=30]()",
"%2 : int = prim::Constant[value=10]()",
"%3 : bool = aten::Bool(%1)",
"%4 : int = prim::If(%3)",
"%5 : int = prim::Constant[value=20]()"});
}
TEST(GraphIteratorTest, GraphWithNestedIf) {
const auto graph_string = R"IR(
graph(%a.1 : Tensor,
%b.1 : Tensor):
%2 : int = prim::Constant[value=10]()
%3 : int = prim::Constant[value=20]()
%4 : int = prim::Constant[value=30]()
%5 : int = prim::Constant[value=40]()
%6 : bool = aten::Bool(%a.1)
%7 : int = prim::If(%6)
block0():
%8 : bool = aten::Bool(%b.1)
%9 : int = prim::If(%8)
block0():
-> (%2)
block1():
-> (%3)
-> (%9)
block1():
%10 : bool = aten::Bool(%b.1)
%11 : int = prim::If(%10)
block0():
-> (%4)
block1():
-> (%5)
-> (%11)
%8 : bool = aten::Bool(%b.1)
%9 : int = prim::If(%8)
block0():
-> (%2)
block1():
-> (%3)
%10 : bool = aten::Bool(%b.1)
%11 : int = prim::If(%10)
block0():
-> (%4)
block1():
-> (%5)
return (%7)
)IR";
auto ordering = traverse_depth_first(graph_string);
assert_ordering(
ordering,
{"%2 : int = prim::Constant[value=10]()",
"%3 : int = prim::Constant[value=20]()",
"%4 : int = prim::Constant[value=30]()",
"%5 : int = prim::Constant[value=40]()",
"%6 : bool = aten::Bool(%a.1)",
"%7 : int = prim::If(%6)",
"%8 : bool = aten::Bool(%b.1)",
"%9 : int = prim::If(%8)",
"%10 : bool = aten::Bool(%b.1)",
"%11 : int = prim::If(%10)",
"%12 : bool = aten::Bool(%b.1)",
"%13 : int = prim::If(%12)",
"%14 : bool = aten::Bool(%b.1)",
"%15 : int = prim::If(%14)"});
}
TEST(GraphIteratorTest, GraphWithLoop) {
const auto graph_string = R"IR(
graph(%a.1 : Tensor):
%1 : bool = prim::Constant[value=1]()
%2 : int = prim::Constant[value=10]()
%3 : int = prim::Constant[value=1]()
%4 : Tensor = prim::Loop(%2, %1, %a.1)
block0(%i : int, %b.9 : Tensor):
%5 : Tensor = aten::add_(%b.9, %3, %3)
-> (%1, %5)
%6 : Tensor = prim::Loop(%2, %1, %a.1)
block0(%i : int, %b.9 : Tensor):
-> (%1, %4)
return (%6)
)IR";
auto ordering = traverse_depth_first(graph_string);
assert_ordering(
ordering,
{"%1 : bool = prim::Constant[value=1]()",
"%2 : int = prim::Constant[value=10]()",
"%3 : int = prim::Constant[value=1]()",
"%4 : Tensor = prim::Loop(%2, %1, %a.1)",
"%7 : Tensor = aten::add_(%b.10, %3, %3)",
"%8 : Tensor = prim::Loop(%2, %1, %a.1)"});
}
} // namespace jit
} // namespace torch
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