1 /**
2 * Copyright 2020 Huawei Technologies Co., Ltd
3 *
4 * Licensed under the Apache License, Version 2.0 (the "License");
5 * you may not use this file except in compliance with the License.
6 * You may obtain a copy of the License at
7 *
8 * http://www.apache.org/licenses/LICENSE-2.0
9 *
10 * Unless required by applicable law or agreed to in writing, software
11 * distributed under the License is distributed on an "AS IS" BASIS,
12 * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
13 * See the License for the specific language governing permissions and
14 * limitations under the License.
15 */
16
17 #include <vector>
18 #include "common/common_test.h"
19 #define private public
20 #define protected public
21 #include "backend/kernel_compiler/cpu/sparse_apply_ftrl_cpu_kernel.h"
22 #undef private
23 #undef protected
24
25 namespace mindspore {
26 namespace kernel {
27 class SparseApplyFtrlCpuKernelTest : public UT::Common {
28 public:
SparseApplyFtrlCpuKernelTest()29 SparseApplyFtrlCpuKernelTest() : sparse_ftrl_(std::make_shared<SparseApplyFtrlCPUKernel>()) {}
30
SetUp()31 void SetUp() override {
32 sparse_ftrl_->lr_ = 0.001;
33 sparse_ftrl_->l1_ = 0.0;
34 sparse_ftrl_->l2_ = 0.0;
35 sparse_ftrl_->lr_power_ = -0.5;
36 var_.clear();
37 accum_.clear();
38 linear_.clear();
39 grad_.clear();
40 inputs_.clear();
41 workspace_.clear();
42 outputs_.clear();
43 }
44
CreateKernelAddress(void * addr)45 AddressPtr CreateKernelAddress(void *addr) {
46 auto kernel_addr = std::make_shared<Address>();
47 kernel_addr->addr = addr;
48 return kernel_addr;
49 }
50
CreateInputAddress(std::vector<int64_t> & indices)51 void CreateInputAddress(std::vector<int64_t> &indices) {
52 inputs_.push_back(CreateKernelAddress(var_.data()));
53 inputs_.push_back(CreateKernelAddress(accum_.data()));
54 inputs_.push_back(CreateKernelAddress(linear_.data()));
55 inputs_.push_back(CreateKernelAddress(grad_.data()));
56 inputs_.push_back(CreateKernelAddress(indices.data()));
57 }
58
CreateWorkspaceAddress(std::vector<float> & new_grad,std::vector<int64_t> & new_indices,std::vector<float> & tmp_grad,std::vector<int64_t> & tmp_indices)59 void CreateWorkspaceAddress(std::vector<float> &new_grad, std::vector<int64_t> &new_indices,
60 std::vector<float> &tmp_grad, std::vector<int64_t> &tmp_indices) {
61 workspace_.push_back(CreateKernelAddress(new_grad.data()));
62 workspace_.push_back(CreateKernelAddress(new_indices.data()));
63 workspace_.push_back(CreateKernelAddress(tmp_grad.data()));
64 workspace_.push_back(CreateKernelAddress(tmp_indices.data()));
65 }
66
67 std::vector<float> var_;
68 std::vector<float> accum_;
69 std::vector<float> linear_;
70 std::vector<float> grad_;
71 std::vector<AddressPtr> inputs_;
72 std::vector<AddressPtr> workspace_;
73 std::vector<AddressPtr> outputs_;
74 std::shared_ptr<SparseApplyFtrlCPUKernel> sparse_ftrl_;
75 };
76
TEST_F(SparseApplyFtrlCpuKernelTest,dense_test)77 TEST_F(SparseApplyFtrlCpuKernelTest, dense_test) {
78 for (size_t i = 0; i < 3 * 3 * 3; ++i) {
79 var_.push_back(1.0);
80 accum_.push_back(1.0);
81 linear_.push_back(1.0);
82 grad_.push_back(1.0);
83 }
84 sparse_ftrl_->indices_size_ = 3;
85 sparse_ftrl_->var_first_dim_size_ = 3;
86 sparse_ftrl_->var_outer_dim_size_ = 9;
87 sparse_ftrl_->indices_data_type_ = kNumberTypeInt64;
88
89 std::vector<int64_t> indices{0, 1, 2};
90 CreateInputAddress(indices);
91 std::vector<float> new_grad(3 * 3 * 3);
92 std::vector<int64_t> new_indices(3);
93 std::vector<float> tmp_grad(3 * 3 * 3);
94 std::vector<int64_t> tmp_indices(3);
95 CreateWorkspaceAddress(new_grad, new_indices, tmp_grad, tmp_indices);
96 sparse_ftrl_->Launch(inputs_, workspace_, outputs_);
97 for (size_t i = 0; i < 3 * 3 * 3; ++i) {
98 EXPECT_TRUE(std::fabs(var_[i] - 0.291479) < 1e-6);
99 }
100 }
101
TEST_F(SparseApplyFtrlCpuKernelTest,sparse_test1)102 TEST_F(SparseApplyFtrlCpuKernelTest, sparse_test1) {
103 for (size_t i = 0; i < 3 * 3 * 3; ++i) {
104 var_.push_back(1.0);
105 accum_.push_back(1.0);
106 linear_.push_back(1.0);
107 }
108 for (size_t i = 0; i < 2 * 3 * 3; ++i) {
109 grad_.push_back(1.0);
110 }
111 sparse_ftrl_->indices_size_ = 2;
112 sparse_ftrl_->var_first_dim_size_ = 3;
113 sparse_ftrl_->var_outer_dim_size_ = 9;
114 sparse_ftrl_->indices_data_type_ = kNumberTypeInt64;
115
116 std::vector<int64_t> indices{0, 2};
117 CreateInputAddress(indices);
118 std::vector<float> new_grad(3 * 3 * 3);
119 std::vector<int64_t> new_indices(3);
120 std::vector<float> tmp_grad(3 * 3 * 3);
121 std::vector<int64_t> tmp_indices(3);
122 CreateWorkspaceAddress(new_grad, new_indices, tmp_grad, tmp_indices);
123 sparse_ftrl_->Launch(inputs_, workspace_, outputs_);
124 for (size_t i = 0; i < 3 * 3; ++i) {
125 EXPECT_TRUE(std::fabs(var_[i] - 0.291479) < 1e-6);
126 }
127 for (size_t i = 3 * 3; i < 2 * 3 * 3; ++i) {
128 EXPECT_EQ(var_[i], 1.0);
129 }
130 for (size_t i = 2 * 3 * 3; i < 3 * 3 * 3; ++i) {
131 EXPECT_TRUE(std::fabs(var_[i] - 0.291479) < 1e-6);
132 }
133 }
134
TEST_F(SparseApplyFtrlCpuKernelTest,sparse_test2)135 TEST_F(SparseApplyFtrlCpuKernelTest, sparse_test2) {
136 for (size_t i = 0; i < 3 * 3 * 3; ++i) {
137 var_.push_back(1.0);
138 accum_.push_back(1.0);
139 linear_.push_back(1.0);
140 grad_.push_back(1.0);
141 }
142 sparse_ftrl_->indices_size_ = 3;
143 sparse_ftrl_->var_first_dim_size_ = 3;
144 sparse_ftrl_->var_outer_dim_size_ = 9;
145 sparse_ftrl_->indices_data_type_ = kNumberTypeInt64;
146
147 std::vector<int64_t> indices{2, 2, 1};
148 CreateInputAddress(indices);
149 std::vector<float> new_grad(3 * 3 * 3);
150 std::vector<int64_t> new_indices(3);
151 std::vector<float> tmp_grad(3 * 3 * 3);
152 std::vector<int64_t> tmp_indices(3);
153 CreateWorkspaceAddress(new_grad, new_indices, tmp_grad, tmp_indices);
154 sparse_ftrl_->Launch(inputs_, workspace_, outputs_);
155 for (size_t i = 0; i < 3 * 3; ++i) {
156 EXPECT_EQ(var_[i], 1.0);
157 }
158 for (size_t i = 3 * 3; i < 2 * 3 * 3; ++i) {
159 EXPECT_TRUE(std::fabs(var_[i] - 0.291479) < 1e-6);
160 }
161 for (size_t i = 2 * 3 * 3; i < 3 * 3 * 3; ++i) {
162 EXPECT_TRUE(std::fabs(var_[i] - 0.551445) < 1e-6);
163 }
164 }
165 } // namespace kernel
166 } // namespace mindspore
167