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/*
* Copyright (c) 2021 Samsung Electronics Co., Ltd. All Rights Reserved
*
* 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 "luci/Pass/ResolveCustomOpBatchMatMulPass.h"
#include <luci/IR/CircleNodes.h>
#include <luci/test/TestIOGraph.h>
#include <gtest/gtest.h>
#include <flatbuffers/flatbuffers.h>
#include <flatbuffers/flexbuffers.h>
namespace
{
using namespace luci::test;
const int N = 1;
const int C = 2;
const int H_X = 1;
const int W_X = 4;
const int H_Y = 4;
const int W_Y = 4;
/**
* graph having Custom operator BatchMatMulV2
*
* [CircleInput] [CircleInput]
* \ /
* [CircleCustom]
* |
* [CircleCustomOut]
* |
* [CircleOutput]
*/
class BatchMatmulV2Graphlet
{
public:
BatchMatmulV2Graphlet() = default;
public:
void init(loco::Graph *g)
{
// custom option
auto flatbuffer_builder =
std::unique_ptr<flatbuffers::FlatBufferBuilder>(new flatbuffers::FlatBufferBuilder(1024));
auto flex_buffers = std::make_unique<flexbuffers::Builder>();
size_t map_start = flex_buffers->StartMap();
flex_buffers->Bool("adj_x", false);
flex_buffers->Bool("adj_y", false);
flex_buffers->Int("T", 0 /* circle::TensorType_FLOAT32 */);
flex_buffers->EndMap(map_start);
flex_buffers->Finish();
// CircleCustom(BatchMatMulV2, adj_x=False, adj_y=False)
_batchmatmulv2 = g->nodes()->create<luci::CircleCustom>(2, 1);
_batchmatmulv2->custom_code("BatchMatMulV2");
_batchmatmulv2->custom_options(flex_buffers->GetBuffer());
_batchmatmulv2->shape({N, C, H_X, W_Y});
_batchmatmulv2->dtype(loco::DataType::FLOAT32);
_batchmatmulv2->name("batchmatmulv2");
// CircleCustomOut
_batchmatmulv2_out = g->nodes()->create<luci::CircleCustomOut>();
_batchmatmulv2_out->shape({N, C, H_X, W_Y});
_batchmatmulv2_out->dtype(loco::DataType::FLOAT32);
_batchmatmulv2_out->index(0);
}
public:
luci::CircleCustom *batchmatmulv2() { return _batchmatmulv2; }
protected:
luci::CircleCustom *_batchmatmulv2 = nullptr;
luci::CircleCustomOut *_batchmatmulv2_out = nullptr;
};
class BatchMatmulV2Graph : public TestIsGraphlet<2>,
public TestOGraphlet,
public BatchMatmulV2Graphlet
{
public:
BatchMatmulV2Graph() = default;
void init(void)
{
TestIsGraphlet<2>::init(g(), {{N, C, H_X, W_X}, {N, C, H_X, W_X}});
TestOGraphlet::init(g(), {N, C, H_X, W_Y});
BatchMatmulV2Graphlet::init(g());
// TODO how set multiple of shape vector for TestIsGraphlet?
// update shape for second input
input(1)->shape({N, C, H_Y, W_Y});
// connect graph
_batchmatmulv2->inputs(0, input(0));
_batchmatmulv2->inputs(1, input(1));
_batchmatmulv2_out->input(_batchmatmulv2);
output()->from(_batchmatmulv2_out);
}
};
class BatchMatmulV2GraphTest : public ::testing::Test
{
public:
BatchMatmulV2Graph g;
luci::ResolveCustomOpBatchMatMulPass pass;
};
} // namespace
TEST(ResolveCustomOpBatchMatMulPassTest, name)
{
luci::ResolveCustomOpBatchMatMulPass pass;
auto const name = pass.name();
ASSERT_NE(nullptr, name);
}
/**
* Optimized graph looks like below.
*
* [CircleInput]
* |
* [CircleBatchMatMul]
* |
* [CircleOutput]
*/
TEST_F(BatchMatmulV2GraphTest, simple_test)
{
g.init();
auto ret = pass.run(g.g());
EXPECT_EQ(true, ret);
auto batchmatmul = dynamic_cast<luci::CircleBatchMatMul *>(g.output()->from());
EXPECT_NE(nullptr, batchmatmul);
auto input_0 = dynamic_cast<luci::CircleInput *>(batchmatmul->x());
auto input_1 = dynamic_cast<luci::CircleInput *>(batchmatmul->y());
EXPECT_NE(nullptr, input_0);
EXPECT_NE(nullptr, input_1);
}
TEST_F(BatchMatmulV2GraphTest, wrong_condition_NEG)
{
g.init();
// wrong custom code
g.batchmatmulv2()->custom_code("BatchMatMulv2"); // v is lower case
auto ret = pass.run(g.g());
EXPECT_EQ(false, ret);
}
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