1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
|
/* Copyright 2016 The TensorFlow Authors. 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 "tensorflow/core/framework/allocator.h"
#include "tensorflow/core/framework/fake_input.h"
#include "tensorflow/core/framework/node_def_builder.h"
#include "tensorflow/core/framework/op_kernel.h"
#include "tensorflow/core/framework/tensor.h"
#include "tensorflow/core/framework/tensor_testutil.h"
#include "tensorflow/core/framework/types.h"
#include "tensorflow/core/kernels/ops_testutil.h"
#include "tensorflow/core/platform/test.h"
namespace tensorflow {
namespace {
class SparseReduceSumOpTest : public OpsTestBase {
protected:
template <typename T>
void MakeOp() {
DataType value_type = tensorflow::DataTypeToEnum<T>::value;
TF_ASSERT_OK(NodeDefBuilder("sparse_reduce_sum", "SparseReduceSum")
.Input(FakeInput(DT_INT64))
.Input(FakeInput(value_type))
.Input(FakeInput(DT_INT64))
.Input(FakeInput(DT_INT32))
.Attr("T", value_type)
.Finalize(node_def()));
TF_ASSERT_OK(InitOp());
}
};
TEST_F(SparseReduceSumOpTest, SimpleReduce) {
MakeOp<float>();
// [ 1]
// [2 ]
// [3 4]
const auto indices_shape = TensorShape({4, 2});
std::initializer_list<int64> in{ 0, 1, 1, 0, 2, 0, 2, 1 };
const gtl::ArraySlice<int64> indices(in);
std::initializer_list<int64> sh{ 3, 2 };
const gtl::ArraySlice<int64> shape(sh);
AddInputFromArray<int64>(indices_shape, indices);
AddInputFromArray<float>(TensorShape({4}), {1, 2, 3, 4});
AddInputFromArray<int64>(TensorShape({2}), shape);
AddInputFromArray<int32>(TensorShape({1}), {0}); // reduction axes
TF_ASSERT_OK(RunOpKernel());
Tensor expected_by_0(allocator(), DT_FLOAT, TensorShape({2}));
test::FillValues<float>(&expected_by_0, {5, 5});
test::ExpectTensorEqual<float>(expected_by_0, *GetOutput(0));
}
class SparseReduceSumSparseOpTest : public OpsTestBase {
protected:
template <typename T>
void MakeOp() {
DataType value_type = tensorflow::DataTypeToEnum<T>::value;
TF_ASSERT_OK(
NodeDefBuilder("sparse_reduce_sum_sparse", "SparseReduceSumSparse")
.Input(FakeInput(DT_INT64))
.Input(FakeInput(value_type))
.Input(FakeInput(DT_INT64))
.Input(FakeInput(DT_INT32))
.Attr("T", value_type)
.Finalize(node_def()));
TF_ASSERT_OK(InitOp());
}
};
TEST_F(SparseReduceSumSparseOpTest, SimpleReduce) {
MakeOp<float>();
// [ 2]
// [2 ]
// [3 4]
const auto indices_shape = TensorShape({4, 2});
std::initializer_list<int64> in{ 0, 1, 1, 0, 2, 0, 2, 1 };
const gtl::ArraySlice<int64> indices(in);
std::initializer_list<int64> sh{ 3, 2 };
const gtl::ArraySlice<int64> shape(sh);
AddInputFromArray<int64>(indices_shape, indices);
AddInputFromArray<float>(TensorShape({4}), {2, 2, 3, 4});
AddInputFromArray<int64>(TensorShape({2}), shape);
AddInputFromArray<int32>(TensorShape({1}), {0}); // reduction axes
TF_ASSERT_OK(RunOpKernel());
const int expected_nnz = 2;
Tensor expected_indices(allocator(), DT_INT64,
TensorShape({expected_nnz, 1}));
test::FillValues<int64>(&expected_indices, {0, 1});
test::ExpectTensorEqual<int64>(expected_indices, *GetOutput(0));
Tensor expected_values(allocator(), DT_FLOAT, TensorShape({2}));
test::FillValues<float>(&expected_values, {5, 6});
test::ExpectTensorEqual<float>(expected_values, *GetOutput(1));
Tensor expected_shape(allocator(), DT_INT64, {1});
test::FillValues<int64>(&expected_shape, {2});
test::ExpectTensorEqual<int64>(expected_shape, *GetOutput(2));
}
} // namespace
} // namespace tensorflow
|
