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54ae67414e3de632a5ad21060a4fc8c92d172f18
openvino/ngraph/test/pattern.cpp
Ilya Churaev 54ae67414e Remove redundant node methods (#1324) 
* Remove placement

* Removed validate and infer eltwise

* Remove is eltwise

* Remove support broadcast and decompose

* Removed is_op, is_parameter, is_pattern

* Fixed code style

* Added is_constant and is_output

* Removed is_communicative and is_null

* Fixed code style

* Fixed typo

* Fixed comments

* Fixed typo

* Revert is_parameter, is_output, is_result for OpenCV build
2020-07-21 06:02:00 +03:00

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//*****************************************************************************
// Copyright 2017-2020 Intel Corporation
//
// Licensed under the Apache License, Version 2.0 (the "License");
// you may not use this file except in compliance with the License.
// You may obtain a copy of the License at
//
// http://www.apache.org/licenses/LICENSE-2.0
//
// Unless required by applicable law or agreed to in writing, software
// distributed under the License is distributed on an "AS IS" BASIS,
// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
// See the License for the specific language governing permissions and
// limitations under the License.
//*****************************************************************************
#include <algorithm>
#include <cstdio>
#include <iostream>
#include <list>
#include <memory>
#include "gtest/gtest.h"
#include "ngraph/file_util.hpp"
#include "ngraph/graph_util.hpp"
#include "ngraph/log.hpp"
#include "ngraph/ngraph.hpp"
#include "ngraph/op/add.hpp"
#include "ngraph/op/batch_norm.hpp"
#include "ngraph/op/constant.hpp"
#include "ngraph/op/divide.hpp"
#include "ngraph/op/multiply.hpp"
#include "ngraph/op/sqrt.hpp"
#include "ngraph/op/subtract.hpp"
#include "ngraph/op/sum.hpp"
#include "ngraph/op/sum.hpp"
#include "ngraph/op/util/op_types.hpp"
#include "ngraph/pass/graph_rewrite.hpp"
#include "ngraph/pass/manager.hpp"
#include "ngraph/pattern/matcher.hpp"
#include "ngraph/pattern/op/branch.hpp"
#include "ngraph/pattern/op/label.hpp"
#include "ngraph/pattern/op/or.hpp"
#include "ngraph/pattern/op/skip.hpp"
#include "ngraph/pattern/op/true.hpp"
#include "ngraph/serializer.hpp"
#include "util/matcher.hpp"
#include "util/test_tools.hpp"
using namespace ngraph;
using namespace std;
static std::shared_ptr<Node> construct_constant_node(int n)
{
return op::Constant::create(element::i32, Shape{}, {n});
}
static std::shared_ptr<pattern::op::Label> construct_variance_graph()
{
// construct varaiance
auto N = op::Constant::create(element::f32, Shape{3}, {2, 2, 2});
auto input = std::make_shared<pattern::op::Label>(element::f32, Shape{2, 3});
auto input_sq = std::make_shared<op::Multiply>(input, input);
auto sum_input = std::make_shared<op::Sum>(input, AxisSet{0});
auto square_sumed_input = std::make_shared<op::Multiply>(sum_input, sum_input);
auto sum_squared_input = std::make_shared<op::Sum>(input_sq, AxisSet{0});
auto avg_input_sum_sq = std::make_shared<op::Divide>(square_sumed_input, N);
auto xmu = std::make_shared<op::Subtract>(sum_squared_input, avg_input_sum_sq);
auto variance = std::make_shared<op::Divide>(xmu, N);
auto variance_label =
std::make_shared<pattern::op::Label>(variance, nullptr, NodeVector{variance});
return variance_label;
}
static std::shared_ptr<pattern::op::Label> construct_mean_graph()
{
// construct mean;
auto input = std::make_shared<pattern::op::Label>(element::f32, Shape{2, 3});
auto N = op::Constant::create(element::f32, Shape{3}, {2, 2, 2});
auto sum_input1 = std::make_shared<op::Sum>(input, AxisSet{0});
auto mean = std::make_shared<op::Divide>(sum_input1, N);
auto mean_label = std::make_shared<pattern::op::Label>(mean, nullptr, NodeVector{mean});
return mean_label;
}
class TestGraphRewrite : public ngraph::pass::GraphRewrite
{
public:
void construct_multiply_by_one()
{
// pattern #1 : a * 1 = a
auto iconst1 = construct_constant_node(1);
auto pattern = std::make_shared<pattern::op::Label>(iconst1);
auto callback = [pattern](pattern::Matcher& m) {
NGRAPH_DEBUG << "In a callback for construct_multiply_by_one against "
<< m.get_match_root()->get_name();
NGRAPH_CHECK(m.get_match_root()->input_values().size() == 2);
auto pattern_map = m.get_pattern_map();
size_t const_node_index =
m.get_match_root()->input_value(0).get_node_shared_ptr() == pattern_map[pattern];
auto const_node = as_type_ptr<op::Constant>(
m.get_match_root()->input_value(const_node_index).get_node_shared_ptr());
auto second_node =
m.get_match_root()->input_value(const_node_index).get_node_shared_ptr();
NGRAPH_DEBUG << "second_node = " << second_node->get_name()
<< " , pattern = " << pattern_map[pattern]->get_name();
if (pattern_map[pattern]->get_element_type() != const_node->get_element_type() ||
pattern_map[pattern]->get_shape() != const_node->get_shape())
{
NGRAPH_DEBUG << "Operands' types and/or shape don't match";
return false;
}
auto const_values = const_node->get_vector<int32_t>();
bool all_ones =
std::all_of(begin(const_values), end(const_values), [](int e) { return e == 1; });
if (!all_ones)
{
NGRAPH_DEBUG << "Constant vector's values aren't equal to 1";
return false;
}
ngraph::replace_node(m.get_match_root(), pattern_map[pattern]);
return true;
};
auto m = make_shared<TestMatcher>(pattern * iconst1);
this->add_matcher(m, callback);
}
void construct_add_zero()
{
// pattern #2 : a + 0 = a
auto iconst0 = construct_constant_node(0);
auto pattern = std::make_shared<pattern::op::Label>(iconst0);
auto callback = [pattern](pattern::Matcher& m) {
NGRAPH_DEBUG << "In a callback for construct_add_zero against "
<< m.get_match_root()->get_name();
NGRAPH_CHECK(m.get_match_root()->input_values().size() == 2);
auto pattern_map = m.get_pattern_map();
size_t const_node_index =
m.get_match_root()->input_value(0).get_node_shared_ptr() == pattern_map[pattern];
auto const_node = as_type_ptr<op::Constant>(
m.get_match_root()->input_value(const_node_index).get_node_shared_ptr());
auto second_node =
m.get_match_root()->input_value(const_node_index).get_node_shared_ptr();
NGRAPH_DEBUG << "second_node = " << second_node->get_name()
<< " , pattern = " << pattern_map[pattern]->get_name();
if (pattern_map[pattern]->get_element_type() != const_node->get_element_type() ||
pattern_map[pattern]->get_shape() != const_node->get_shape())
{
NGRAPH_DEBUG << "Operands' types and/or shape don't match";
return false;
}
auto const_values = const_node->get_vector<int>();
bool all_zeros =
std::all_of(begin(const_values), end(const_values), [](int e) { return e == 0; });
if (!all_zeros)
{
NGRAPH_DEBUG << "Constant vector's values aren't equal to 0";
return false;
}
ngraph::replace_node(m.get_match_root(), pattern_map[pattern]);
return true;
};
auto add = pattern + iconst0;
auto m = make_shared<TestMatcher>(add);
this->add_matcher(m, callback);
}
TestGraphRewrite()
: GraphRewrite()
{
construct_multiply_by_one();
construct_add_zero();
}
};
static void run_passes(pass::Manager& pass_manager,
shared_ptr<Node> graph,
std::vector<shared_ptr<op::Parameter>> parms)
{
auto func = make_shared<Function>(graph, ParameterVector{parms});
pass_manager.run_passes(func);
}
TEST(pattern, graph_rewrite)
{
Shape shape{};
pass::Manager pass_manager;
pass_manager.register_pass<TestGraphRewrite>();
{
auto a = make_shared<op::Parameter>(element::i32, shape);
auto b = make_shared<op::Parameter>(element::i32, shape);
auto c = make_shared<op::Parameter>(element::i32, shape);
auto iconst0 = construct_constant_node(0);
auto graph_a = a + iconst0;
auto graph_b = b + iconst0;
auto f = std::make_shared<Function>(ngraph::NodeVector{a, b, graph_a, c, graph_b},
ParameterVector{a, b, c});
pass_manager.run_passes(f);
ASSERT_TRUE(graph_a->get_output_target_inputs(0).empty());
ASSERT_TRUE(graph_b->get_output_target_inputs(0).empty());
auto expected = ngraph::NodeVector{a, b, a, c, b};
ASSERT_TRUE(count_ops_of_type<op::Add>(f) == 0);
}
{
auto a = make_shared<op::Parameter>(element::i32, shape);
auto b = make_shared<op::Parameter>(element::i32, shape);
auto iconst0 = construct_constant_node(0);
auto sum = (a + iconst0);
auto graph = b + sum;
run_passes(pass_manager, graph, {a, b});
ASSERT_EQ(graph->input_value(1).get_node_shared_ptr(), a);
ASSERT_EQ(graph->input_value(1), a->output(0)); // graph's input points to a's output
ASSERT_TRUE(sum->output(0)
.get_target_inputs()
.empty()); // graph's input is removed from sum's target inptus
ASSERT_TRUE(a->get_output_target_inputs(0).count(
graph->input(1))); // a's output feeds into graph's input
}
{
auto a = make_shared<op::Parameter>(element::i32, shape);
auto b = make_shared<op::Parameter>(element::i32, shape);
auto iconst1 = construct_constant_node(1);
auto mul = (a * iconst1);
auto graph = b + mul;
run_passes(pass_manager, graph, {a, b});
ASSERT_EQ(graph->input_value(1).get_node_shared_ptr(), a);
ASSERT_EQ(graph->input_value(1), a->output(0)); // graph's input points to a's output
ASSERT_TRUE(mul->output(0)
.get_target_inputs()
.empty()); // graph's input is removed from sum's target inputs
ASSERT_TRUE(a->get_output_target_inputs(0).count(
graph->input(1))); // a's output feeds into graph's input
}
{
auto a = make_shared<op::Parameter>(element::i32, shape);
auto b = make_shared<op::Parameter>(element::i32, shape);
auto iconst1 = construct_constant_node(1);
auto graph = ((((a * iconst1) * iconst1) * iconst1) * iconst1) + b;
run_passes(pass_manager, graph, {a, b});
ASSERT_EQ(graph->input_value(0).get_node_shared_ptr(), a);
ASSERT_EQ(graph->input_value(0), a->output(0)); // graph's input points to a's output
ASSERT_TRUE(a->get_output_target_inputs(0).count(
graph->input(0))); // a's output feeds into graph's input
}
{
auto a = make_shared<op::Parameter>(element::i32, shape);
auto b = make_shared<op::Parameter>(element::i32, shape);
auto iconst0 = construct_constant_node(0);
auto iconst1 = construct_constant_node(1);
auto graph = b + (iconst0 + ((a + iconst0) * iconst1));
run_passes(pass_manager, graph, {a, b});
ASSERT_EQ(graph->input_value(1).get_node_shared_ptr(), a);
ASSERT_EQ(graph->input_value(1), a->output(0)); // graph's input points to a's output
ASSERT_TRUE(a->get_output_target_inputs(0).count(
graph->input(1))); // a's output feeds into graph's input
}
{
auto a = make_shared<op::Parameter>(element::i32, shape);
auto b = make_shared<op::Parameter>(element::i32, shape);
auto iconst1 = construct_constant_node(1);
auto graph = b + (iconst1 * (iconst1 * (iconst1 * (iconst1 * a))));
run_passes(pass_manager, graph, {a, b});
ASSERT_EQ(graph->input_value(1).get_node_shared_ptr(), a);
ASSERT_EQ(graph->input_value(1), a->output(0)); // graph's input points to a's output
ASSERT_TRUE(a->get_output_target_inputs(0).count(
graph->input(1))); // a's output feeds into graph's input
}
}
TEST(pattern, matcher)
{
Shape shape{};
auto a = make_shared<op::Parameter>(element::i32, shape);
TestMatcher n;
ASSERT_TRUE(n.match(a, a));
ASSERT_EQ(n.get_matched_nodes(), (NodeVector{a}));
auto abs = make_shared<op::Abs>(a);
auto any = std::make_shared<pattern::op::Skip>(a);
ASSERT_TRUE(n.match(any, abs));
ASSERT_EQ(n.get_matched_nodes(), (NodeVector{abs, a}));
auto false_pred = [](std::shared_ptr<Node> /* no */) { return false; };
auto any_false = std::make_shared<pattern::op::Skip>(a, false_pred);
ASSERT_TRUE(n.match(any_false, a));
ASSERT_EQ(n.get_matched_nodes(), (NodeVector{a, a}));
auto pattern = std::make_shared<pattern::op::Label>(a);
ASSERT_TRUE(n.match(pattern, a));
ASSERT_EQ(n.get_pattern_map()[pattern], a);
ASSERT_EQ(n.get_matched_nodes(), (NodeVector{a}));
auto pattern_false = std::make_shared<pattern::op::Label>(a, false_pred);
ASSERT_FALSE(n.match(pattern_false, a));
ASSERT_EQ(n.get_matched_nodes(), (NodeVector{}));
auto b = make_shared<op::Parameter>(element::i32, shape);
auto is_bea = [](std::shared_ptr<Node> node) -> bool {
return op::is_binary_elementwise_arithmetic(node);
};
auto bea = std::make_shared<pattern::op::Any>(a, is_bea, NodeVector{a, b});
auto add_ab = a + b;
ASSERT_TRUE(n.match(bea, add_ab));
ASSERT_EQ(n.get_matched_nodes(), (NodeVector{add_ab, a, b}));
ASSERT_TRUE(n.match(bea, b + a));
auto bea_false = std::make_shared<pattern::op::Any>(a, false_pred, NodeVector{a, b});
ASSERT_FALSE(n.match(bea_false, a + b));
auto add_abs_b = abs + b;
auto bea_any_of = std::make_shared<pattern::op::AnyOf>(a, is_bea, NodeVector{abs});
ASSERT_TRUE(n.match(bea_any_of, add_abs_b));
auto add_b_abs = b + abs;
ASSERT_TRUE(n.match(bea_any_of, add_b_abs));
auto bea_any_of_label =
std::make_shared<pattern::op::Label>(a, nullptr, NodeVector{bea_any_of});
ASSERT_TRUE(n.match(bea_any_of_label, add_b_abs));
ASSERT_EQ(n.get_pattern_map()[bea_any_of_label], add_b_abs);
auto abs_label = std::make_shared<pattern::op::Label>(a, nullptr, NodeVector{abs});
auto bea_label_any_of = std::make_shared<pattern::op::AnyOf>(a, is_bea, NodeVector{abs_label});
ASSERT_TRUE(n.match(bea_label_any_of, add_b_abs));
ASSERT_EQ(n.get_pattern_map()[abs_label], abs);
auto bea_label = std::make_shared<pattern::op::Label>(a, nullptr, NodeVector{bea});
auto ab = a + b;
ASSERT_TRUE(n.match(bea_label, ab));
ASSERT_EQ(n.get_pattern_map()[bea_label], ab);
auto d = make_shared<op::Parameter>(element::i32, shape);
ASSERT_FALSE(n.match(d, b));
ASSERT_FALSE(n.match(abs + b, b + b));
ASSERT_EQ(n.get_matched_nodes(), (NodeVector{}));
auto add_absb = abs + b;
ASSERT_TRUE(n.match(any + b, add_absb));
ASSERT_EQ(n.get_matched_nodes(), (NodeVector{add_absb, abs, a, b}));
ASSERT_TRUE(n.match(pattern + b, add_absb));
ASSERT_EQ(n.get_pattern_map()[pattern], abs);
ASSERT_EQ(n.get_matched_nodes(), (NodeVector{add_absb, abs, b}));
ASSERT_TRUE(n.match(b + pattern, add_absb));
ASSERT_EQ(n.get_pattern_map()[pattern], abs);
ASSERT_EQ(n.get_matched_nodes(), (NodeVector{add_absb, abs, b}));
auto c = make_shared<op::Parameter>(element::i32, shape);
auto mul_add_absb = c * (add_absb);
ASSERT_TRUE(n.match(c * (b + pattern), mul_add_absb));
ASSERT_EQ(n.get_pattern_map()[pattern], abs);
ASSERT_EQ(n.get_matched_nodes(), (NodeVector{mul_add_absb, c, add_absb, abs, b}));
ASSERT_TRUE(n.match(c * (any + b), mul_add_absb)); // nested any
ASSERT_EQ(n.get_matched_nodes(), (NodeVector{mul_add_absb, c, add_absb, abs, a, b}));
ASSERT_TRUE(n.match(c * (any + b), (b + abs) * c)); // permutations w/ any
auto mul_c_add_ab = c * add_ab;
ASSERT_TRUE(n.match(c * (any_false + b), c * (a + b))); // nested any
ASSERT_TRUE(n.match(c * (any_false + b), mul_c_add_ab)); // permutations w/ any_false
ASSERT_EQ(n.get_matched_nodes(), (NodeVector{mul_c_add_ab, c, add_ab, a, a, b}));
auto iconst1_0 = construct_constant_node(1);
auto iconst1_1 = construct_constant_node(1);
ASSERT_TRUE(n.match(pattern * iconst1_0, a * iconst1_1)); // different iconst
ASSERT_EQ(n.get_pattern_map()[pattern], a);
auto fconst1_0 = op::Constant::create(element::f32, shape, {1});
auto patternf = std::make_shared<pattern::op::Label>(fconst1_0);
ASSERT_TRUE(n.match(patternf * fconst1_0, a * iconst1_1)); // different iconst
// Subgraph labels
auto add = a + b;
auto label = std::make_shared<pattern::op::Label>(add, nullptr, NodeVector{add});
ASSERT_TRUE(n.match(label, add));
ASSERT_EQ(n.get_pattern_map()[label], add);
ASSERT_EQ(n.get_matched_nodes(), (NodeVector{add, add, a, b}));
ASSERT_FALSE(n.match(label, a - b));
ASSERT_TRUE(n.match(make_shared<op::Abs>(label), make_shared<op::Abs>(add)));
ASSERT_EQ(n.get_pattern_map()[label], add);
// Correct argument order
ASSERT_FALSE(n.match(b - a, a - b));
auto aab = a * (a - b);
auto paab = pattern * (pattern - b);
ASSERT_TRUE(n.match(paab, aab));
auto aba = a * (b - a);
ASSERT_FALSE(n.match(paab, aba));
auto paba = pattern * (b - pattern);
ASSERT_FALSE(n.match(paba, aab));
// Correlations
auto label1 = std::make_shared<pattern::op::Label>(a);
auto tmp = label1 + b;
auto label2 = std::make_shared<pattern::op::Label>(tmp, nullptr, NodeVector{tmp});
auto sub_label1 = label1 - label2;
auto sub_add = a - add;
ASSERT_TRUE(n.match(sub_label1, sub_add));
ASSERT_EQ(n.get_pattern_map()[label1], a);
ASSERT_EQ(n.get_pattern_map()[label2], add);
ASSERT_EQ(n.get_matched_nodes(), (NodeVector{sub_add, a, add, add, a, b}));
ASSERT_FALSE(n.match(sub_label1, add - a));
auto add_label1 = label1 + label2;
ASSERT_TRUE(n.match(add_label1, add + a));
ASSERT_EQ(n.get_pattern_map()[label1], a);
ASSERT_EQ(n.get_pattern_map()[label2], add);
// Or
ASSERT_TRUE(n.match(std::make_shared<pattern::op::Or>(OutputVector{a + b, a - b}), a + b));
ASSERT_TRUE(n.match(std::make_shared<pattern::op::Or>(OutputVector{a + b, a - b}), a - b));
// Branch
{
auto branch = std::make_shared<pattern::op::Branch>();
auto star = std::make_shared<pattern::op::Or>(
OutputVector{branch, std::make_shared<pattern::op::True>()});
auto pattern = star + star;
branch->set_destination(pattern);
ASSERT_TRUE(n.match(pattern, ((a + b) + (b + a) + a)));
ASSERT_EQ(n.get_matched_nodes().size(), 4);
}
// strict mode
{
TestMatcher sm(Output<Node>{}, "TestMatcher", true);
// exact shape and type
auto scalar_param = make_shared<op::Parameter>(element::i32, Shape{});
auto label_dynamic_shape =
make_shared<pattern::op::Label>(element::i32, PartialShape::dynamic());
auto param = make_shared<op::Parameter>(element::f32, Shape{});
ASSERT_TRUE(sm.match(label_dynamic_shape, scalar_param));
// wrong type
auto scalar_param_wrong_type = make_shared<op::Parameter>(element::f32, Shape{});
ASSERT_FALSE(sm.match(label, scalar_param_wrong_type));
// dynamic dimension
auto label_dynamic_dimension =
make_shared<pattern::op::Label>(element::i32, PartialShape{Dimension::dynamic()});
auto vector_param = make_shared<op::Parameter>(element::i32, Shape{10});
ASSERT_TRUE(sm.match(label_dynamic_dimension, vector_param));
// dynamic type
auto label_dynamic_type =
make_shared<pattern::op::Label>(element::dynamic, PartialShape{Dimension::dynamic()});
ASSERT_TRUE(sm.match(label_dynamic_type, vector_param));
}
}
TEST(pattern, mean)
{
// construct mean
TestMatcher n;
auto input = std::make_shared<op::Parameter>(element::f32, Shape{2, 3});
auto N = op::Constant::create(element::f32, Shape{3}, {2, 2, 2});
auto sum_input1 = std::make_shared<op::Sum>(input, AxisSet{0});
auto mean = std::make_shared<op::Divide>(sum_input1, N);
auto mean_graph = construct_mean_graph();
ASSERT_TRUE(n.match(mean_graph, mean));
ASSERT_EQ(n.get_pattern_map()[mean_graph], mean);
}
TEST(pattern, variance)
{
// construct variance
TestMatcher n;
auto N = op::Constant::create(element::f32, Shape{3}, {2, 2, 2});
auto input = std::make_shared<pattern::op::Label>(element::f32, Shape{2, 3});
auto input_sq = std::make_shared<op::Multiply>(input, input);
auto sum_input = std::make_shared<op::Sum>(input, AxisSet{0});
auto square_sumed_input = std::make_shared<op::Multiply>(sum_input, sum_input);
auto sum_squared_input = std::make_shared<op::Sum>(input_sq, AxisSet{0});
auto avg_input_sum_sq = std::make_shared<op::Divide>(square_sumed_input, N);
auto xmu = std::make_shared<op::Subtract>(sum_squared_input, avg_input_sum_sq);
auto variance = std::make_shared<op::Divide>(xmu, N);
auto var_graph = construct_variance_graph();
ASSERT_TRUE(n.match(var_graph, variance));
ASSERT_EQ(n.get_pattern_map()[var_graph], variance);
}
TEST(pattern, previous_matches)
{
using ngraph::pattern::Matcher;
Shape shape{};
Matcher::PatternMap previous_matches;
auto a = make_shared<op::Parameter>(element::i32, shape);
auto b = make_shared<op::Parameter>(element::i32, shape);
auto pattern = std::make_shared<pattern::op::Label>(b);
auto abs = make_shared<op::Abs>(a);
auto add = abs + b;
{
Matcher n(pattern + b);
ASSERT_TRUE(n.match(add, previous_matches));
ASSERT_EQ(n.get_pattern_map()[pattern], abs);
}
{
Matcher n(pattern + b);
previous_matches.insert(std::make_pair(pattern, a));
ASSERT_FALSE(n.match(add, previous_matches));
}
}
TEST(pattern, test_sort)
{
using ngraph::pattern::Matcher;
Shape shape{};
auto a = make_shared<op::Parameter>(element::i32, shape);
auto b = make_shared<op::Parameter>(element::i32, shape);
auto abs1 = make_shared<op::Abs>(a);
auto abs2 = make_shared<op::Abs>(b);
auto add = abs1 + abs2;
auto pa = make_shared<op::Parameter>(element::i32, shape);
auto pb = make_shared<op::Parameter>(element::i32, shape);
auto pabs1 = make_shared<op::Abs>(pa);
auto pabs1_label = std::make_shared<pattern::op::Label>(pabs1);
auto pabs2 = make_shared<op::Abs>(b);
auto padd = pabs1_label + pabs2;
{
Matcher n1(padd);
ASSERT_TRUE(n1.match(add));
auto r1 = n1.get_pattern_map()[pabs1_label];
ASSERT_TRUE(n1.match(add));
ASSERT_EQ(r1, n1.get_pattern_map()[pabs1_label]);
}
}
TEST(pattern, recurrent_pattern)
{
using ngraph::pattern::RecurrentMatcher;
Shape shape{};
ngraph::pattern::Matcher::PatternMap previous_matches;
auto a = make_shared<op::Parameter>(element::i32, shape);
auto b = make_shared<op::Parameter>(element::i32, shape);
auto rpattern = std::make_shared<pattern::op::Label>(b);
auto iconst0 = construct_constant_node(0);
auto abs = make_shared<op::Abs>(a);
auto add1 = iconst0 + b;
auto add2 = iconst0 + add1;
auto add3 = iconst0 + add2;
auto padd = iconst0 + rpattern;
std::set<std::shared_ptr<pattern::op::Label>> empty_correlated_matches;
RecurrentMatcher rm(padd, rpattern, empty_correlated_matches);
ASSERT_TRUE(rm.match(add3));
ASSERT_EQ(rm.get_number_of_bound_labels(), 1);
auto recurrent_matches = rm.get_bound_nodes_for_pattern(rpattern);
ASSERT_EQ(recurrent_matches.at(0), add2);
ASSERT_EQ(recurrent_matches.at(1), add1);
ASSERT_EQ(recurrent_matches.at(2), b);
// Multiple labels in a reccuring pattern
auto iconst1 = construct_constant_node(1);
auto iconst_label = std::make_shared<pattern::op::Label>(iconst1, nullptr, NodeVector{iconst1});
auto add2_2 = iconst1 + add1;
auto add3_2 = iconst0 + add2_2;
auto padd2 = iconst_label + rpattern;
RecurrentMatcher rm2(padd2, rpattern, empty_correlated_matches);
ASSERT_TRUE(rm2.match(add3_2));
ASSERT_EQ(rm2.get_number_of_bound_labels(), 2);
recurrent_matches = rm2.get_bound_nodes_for_pattern(rpattern);
ASSERT_EQ(recurrent_matches.at(0), add2_2);
ASSERT_EQ(recurrent_matches.at(1), add1);
ASSERT_EQ(recurrent_matches.at(2), b);
auto iconst_matches = rm2.get_bound_nodes_for_pattern(iconst_label);
ASSERT_EQ(iconst_matches.at(0), iconst0);
ASSERT_EQ(iconst_matches.at(1), iconst1);
ASSERT_EQ(iconst_matches.at(2), iconst0);
// Non-matching correlated labels
std::set<std::shared_ptr<pattern::op::Label>> correlated_matches;
correlated_matches.insert(iconst_label);
RecurrentMatcher rm3(padd2, rpattern, correlated_matches);
ASSERT_TRUE(rm3.match(add3_2));
ASSERT_EQ(rm3.get_number_of_bound_labels(), 2);
iconst_matches = rm3.get_bound_nodes_for_pattern(iconst_label);
ASSERT_EQ(iconst_matches.size(), 1);
ASSERT_EQ(iconst_matches.at(0), iconst0);
// Matching correlated labels and
// testing if RecurrentMatcher can be reused for different nodes
ASSERT_TRUE(rm3.match(add3));
ASSERT_EQ(rm3.get_number_of_bound_labels(), 2);
recurrent_matches = rm3.get_bound_nodes_for_pattern(rpattern);
ASSERT_EQ(recurrent_matches.at(0), add2);
ASSERT_EQ(recurrent_matches.at(1), add1);
ASSERT_EQ(recurrent_matches.at(2), b);
iconst_matches = rm3.get_bound_nodes_for_pattern(iconst_label);
ASSERT_EQ(iconst_matches.at(0), iconst0);
ASSERT_EQ(iconst_matches.at(1), iconst0);
ASSERT_EQ(iconst_matches.at(2), iconst0);
}
class TestRecurrentGraphRewrite : public ngraph::pass::RecurrentGraphRewrite
{
public:
void construct_recurrent_add()
{
Shape shape{};
auto iconst0 = construct_constant_node(0);
auto iconst_label =
std::make_shared<pattern::op::Label>(iconst0, nullptr, NodeVector{iconst0});
auto rpattern = std::make_shared<pattern::op::Label>(element::i32, shape);
auto padd = iconst_label + rpattern;
auto callback = [iconst_label, rpattern](pattern::RecurrentMatcher& rm) {
NGRAPH_DEBUG << "In a callback for construct_recurrent_add against "
<< rm.get_match_root()->get_name();
auto iconst_matches = rm.get_bound_nodes_for_pattern(iconst_label);
auto is_iconst_zero = [](std::shared_ptr<Node> n) {
bool result = ngraph::is_zero(n);
NGRAPH_DEBUG << n->get_name() << " is " << (result ? " a zero " : " not a zero");
return ngraph::is_zero(n);
};
bool are_all_iconst_zeros =
std::all_of(iconst_matches.begin(), iconst_matches.end(), is_iconst_zero);
if (!are_all_iconst_zeros)
{
return false;
}
auto number_of_adds = rm.get_number_of_recurrent_matches();
// replace the topmost add with the seed (i.e. the first parameter to add)
// matches are added in reverse order (i.e. the first match is the topmost node)
auto arg = rm.get_bound_nodes_for_pattern(rpattern).at(number_of_adds - 1);
NGRAPH_DEBUG << "Replacing " << rm.get_match_root()->get_name() << " with "
<< arg->get_name();
ngraph::replace_node(rm.get_match_root(), arg);
return true;
};
std::set<std::shared_ptr<pattern::op::Label>> empty_correlated_matches;
auto rm = make_shared<pattern::RecurrentMatcher>(padd, rpattern, empty_correlated_matches);
this->add_matcher(rm, callback);
}
TestRecurrentGraphRewrite()
: RecurrentGraphRewrite()
{
construct_recurrent_add();
}
};
TEST(pattern, recurrent_graph_rewrite)
{
Shape shape{};
pass::Manager pass_manager;
pass_manager.register_pass<TestRecurrentGraphRewrite>();
{
auto a = make_shared<op::Parameter>(element::i32, shape);
auto iconst0 = construct_constant_node(0);
auto add_a1 = a + iconst0;
auto add_a2 = add_a1 + iconst0;
auto add_a3 = add_a2 + iconst0;
auto abs_add_a3 = std::make_shared<op::Abs>(add_a3);
auto b = make_shared<op::Parameter>(element::i32, shape);
auto add_b1 = b + iconst0;
auto add_b2 = add_b1 + iconst0;
auto abs_add_b2 = std::make_shared<op::Abs>(add_b2);
auto graph = abs_add_a3 * abs_add_b2;
auto f = std::make_shared<Function>(ngraph::NodeVector{graph}, ParameterVector{a, b});
pass_manager.run_passes(f);
auto left_abs = graph->input_value(0).get_node_shared_ptr();
auto add_a = left_abs->input_value(0).get_node_shared_ptr();
ASSERT_EQ(add_a, a);
auto right_abs = graph->input_value(1).get_node_shared_ptr();
auto add_b = right_abs->input_value(0).get_node_shared_ptr();
ASSERT_EQ(add_b, b);
}
}
TEST(pattern, label_on_skip)
{
Shape shape{2, 2};
auto a = make_shared<op::Parameter>(element::i32, shape);
auto b = make_shared<op::Parameter>(element::i32, Shape{});
auto iconst = ngraph::make_zero(element::i32, Shape{});
auto label = std::make_shared<pattern::op::Label>(iconst);
auto const_label =
std::make_shared<pattern::op::Label>(iconst, ngraph::is_zero, NodeVector{iconst});
auto bcst_pred = [](std::shared_ptr<Node> n) {
return as_type_ptr<op::Broadcast>(n) != nullptr;
};
auto bcst = std::make_shared<pattern::op::Skip>(const_label, bcst_pred);
auto bcst_label = std::make_shared<pattern::op::Label>(bcst, nullptr, NodeVector{bcst});
auto matcher = std::make_shared<pattern::Matcher>(
std::make_shared<op::Multiply>(label, bcst_label), "label_on_skip");
auto const_broadcast = make_shared<op::Broadcast>(iconst, shape, AxisSet{0, 1});
auto mul = a * const_broadcast;
auto mul_scalar = b * iconst;
ASSERT_TRUE(matcher->match(mul));
ASSERT_EQ(matcher->get_pattern_map()[bcst_label], const_broadcast);
ASSERT_EQ(matcher->get_pattern_map()[const_label], iconst);
ASSERT_EQ(matcher->get_pattern_map()[label], a);
ASSERT_TRUE(matcher->match(mul_scalar));
ASSERT_EQ(matcher->get_pattern_map()[bcst_label], iconst);
ASSERT_EQ(matcher->get_pattern_map()[const_label], iconst);
ASSERT_EQ(matcher->get_pattern_map()[label], b);
}
TEST(pattern, is_contained_match)
{
Shape shape{};
auto a = make_shared<op::Parameter>(element::i32, shape);
auto absn = make_shared<op::Abs>(a);
TestMatcher n;
auto label_a = std::make_shared<pattern::op::Label>(a);
auto label_abs = make_shared<op::Abs>(a);
ASSERT_TRUE(n.match(label_abs, absn));
auto result_absn = make_shared<op::Result>(absn);
ASSERT_TRUE(n.is_contained_match());
auto absn2 = make_shared<op::Abs>(absn);
auto result_absn2 = make_shared<op::Result>(absn2);
auto label_abs2 = make_shared<op::Abs>(label_abs);
ASSERT_TRUE(n.match(label_abs2, absn2));
ASSERT_FALSE(n.is_contained_match());
}
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