xref: /aosp_15_r20/external/tensorflow/tensorflow/core/data/service/test_util.cc (revision b6fb3261f9314811a0f4371741dbb8839866f948)
1 /* Copyright 2020 The TensorFlow Authors. All Rights Reserved.
2 
3 Licensed under the Apache License, Version 2.0 (the "License");
4 you may not use this file except in compliance with the License.
5 You may obtain a copy of the License at
6 
7     http://www.apache.org/licenses/LICENSE-2.0
8 
9 Unless required by applicable law or agreed to in writing, software
10 distributed under the License is distributed on an "AS IS" BASIS,
11 WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
12 See the License for the specific language governing permissions and
13 limitations under the License.
14 ==============================================================================*/
15 
16 #include "tensorflow/core/data/service/test_util.h"
17 
18 #include <functional>
19 #include <string>
20 #include <vector>
21 
22 #include "absl/strings/string_view.h"
23 #include "absl/types/span.h"
24 #include "tensorflow/core/data/dataset_test_base.h"
25 #include "tensorflow/core/data/service/common.pb.h"
26 #include "tensorflow/core/framework/function.h"
27 #include "tensorflow/core/framework/function.pb.h"
28 #include "tensorflow/core/framework/function_testlib.h"
29 #include "tensorflow/core/framework/graph.pb.h"
30 #include "tensorflow/core/framework/node_def.pb.h"
31 #include "tensorflow/core/framework/tensor.h"
32 #include "tensorflow/core/framework/tensor_shape.h"
33 #include "tensorflow/core/framework/tensor_testutil.h"
34 #include "tensorflow/core/framework/types.pb.h"
35 #include "tensorflow/core/platform/env.h"
36 #include "tensorflow/core/platform/errors.h"
37 #include "tensorflow/core/platform/path.h"
38 #include "tensorflow/core/platform/status.h"
39 #include "tensorflow/core/platform/statusor.h"
40 #include "tensorflow/core/platform/tstring.h"
41 #include "tensorflow/core/platform/types.h"
42 
43 namespace tensorflow {
44 namespace data {
45 namespace testing {
46 namespace {
47 
48 using ::tensorflow::test::AsScalar;
49 using ::tensorflow::test::function::GDef;
50 using ::tensorflow::test::function::NDef;
51 
52 constexpr int64_t kShardHint = -1;
53 constexpr const char kTestdataDir[] =
54     "tensorflow/core/data/service/testdata";
55 constexpr const char kInterleaveTextlineDatasetFile[] =
56     "interleave_textline_dataset.pbtxt";
57 
GetMapNode(absl::string_view name,absl::string_view input_node_name,absl::string_view function_name)58 NodeDef GetMapNode(absl::string_view name, absl::string_view input_node_name,
59                    absl::string_view function_name) {
60   return NDef(
61       name, /*op=*/"MapDataset", {std::string(input_node_name)},
62       {{"f", FunctionDefHelper::FunctionRef(std::string(function_name))},
63        {"Targuments", {}},
64        {"output_shapes", gtl::ArraySlice<TensorShape>{TensorShape()}},
65        {"output_types", gtl::ArraySlice<DataType>{DT_INT64}}});
66 }
67 
XTimesX()68 FunctionDef XTimesX() {
69   return FunctionDefHelper::Create(
70       /*function_name=*/"XTimesX",
71       /*in_def=*/{"x: int64"},
72       /*out_def=*/{"y: int64"},
73       /*attr_def=*/{},
74       /*node_def=*/{{{"y"}, "Mul", {"x", "x"}, {{"T", DT_INT64}}}},
75       /*ret_def=*/{{"y", "y:z:0"}});
76 }
77 
CreateTestFiles(const std::vector<tstring> & filenames,const std::vector<tstring> & contents)78 Status CreateTestFiles(const std::vector<tstring>& filenames,
79                        const std::vector<tstring>& contents) {
80   if (filenames.size() != contents.size()) {
81     return errors::InvalidArgument(
82         "The number of files does not match with the contents.");
83   }
84   for (int i = 0; i < filenames.size(); ++i) {
85     TF_RETURN_IF_ERROR(WriteDataToFile(filenames[i], contents[i].data()));
86   }
87   return OkStatus();
88 }
89 }  // namespace
90 
RangeDataset(int64_t range)91 DatasetDef RangeDataset(int64_t range) {
92   DatasetDef dataset_def;
93   *dataset_def.mutable_graph() = GDef(
94       {NDef("start", "Const", /*inputs=*/{},
95             {{"value", AsScalar<int64_t>(0)}, {"dtype", DT_INT64}}),
96        NDef("stop", "Const", /*inputs=*/{},
97             {{"value", AsScalar<int64_t>(range)}, {"dtype", DT_INT64}}),
98        NDef("step", "Const", /*inputs=*/{},
99             {{"value", AsScalar<int64_t>(1)}, {"dtype", DT_INT64}}),
100        NDef("range", "RangeDataset", /*inputs=*/{"start", "stop", "step"},
101             {{"output_shapes", gtl::ArraySlice<TensorShape>{TensorShape()}},
102              {"output_types", gtl::ArraySlice<DataType>{DT_INT64}}}),
103        NDef("dataset", "_Retval", /*inputs=*/{"range"},
104             {{"T", DT_VARIANT}, {"index", 0}})},
105       {});
106   return dataset_def;
107 }
108 
RangeSquareDataset(const int64_t range)109 DatasetDef RangeSquareDataset(const int64_t range) {
110   DatasetDef dataset_def;
111   *dataset_def.mutable_graph() = GDef(
112       {NDef("start", "Const", /*inputs=*/{},
113             {{"value", AsScalar<int64_t>(0)}, {"dtype", DT_INT64}}),
114        NDef("stop", "Const", /*inputs=*/{},
115             {{"value", AsScalar<int64_t>(range)}, {"dtype", DT_INT64}}),
116        NDef("step", "Const", /*inputs=*/{},
117             {{"value", AsScalar<int64_t>(1)}, {"dtype", DT_INT64}}),
118        NDef("range", "RangeDataset", /*inputs=*/{"start", "stop", "step"},
119             {{"output_shapes", gtl::ArraySlice<TensorShape>{TensorShape()}},
120              {"output_types", gtl::ArraySlice<DataType>{DT_INT64}}}),
121        GetMapNode("map", "range", "XTimesX"),
122        NDef("dataset", "_Retval", /*inputs=*/{"map"},
123             {{"T", DT_VARIANT}, {"index", 0}})},
124       {XTimesX()});
125   return dataset_def;
126 }
127 
RangeDatasetWithShardHint(const int64_t range)128 DatasetDef RangeDatasetWithShardHint(const int64_t range) {
129   DatasetDef dataset_def;
130   *dataset_def.mutable_graph() = GDef(
131       {NDef("start", "Const", /*inputs=*/{},
132             {{"value", AsScalar<int64_t>(0)}, {"dtype", DT_INT64}}),
133        NDef("stop", "Const", /*inputs=*/{},
134             {{"value", AsScalar<int64_t>(range)}, {"dtype", DT_INT64}}),
135        NDef("step", "Const", /*inputs=*/{},
136             {{"value", AsScalar<int64_t>(1)}, {"dtype", DT_INT64}}),
137        NDef("range", "RangeDataset", /*inputs=*/{"start", "stop", "step"},
138             {{"output_shapes", gtl::ArraySlice<TensorShape>{TensorShape()}},
139              {"output_types", gtl::ArraySlice<DataType>{DT_INT64}}}),
140        NDef("num_shards", "Const", /*inputs=*/{},
141             {{"value", AsScalar<int64_t>(kShardHint)}, {"dtype", DT_INT64}}),
142        NDef("index", "Const", /*inputs=*/{},
143             {{"value", AsScalar<int64_t>(kShardHint)}, {"dtype", DT_INT64}}),
144        NDef("ShardDataset", "ShardDataset",
145             /*inputs=*/{"range", "num_shards", "index"},
146             {{"output_shapes", gtl::ArraySlice<TensorShape>{TensorShape()}},
147              {"output_types", gtl::ArraySlice<DataType>{DT_INT64}}}),
148        NDef("dataset", "_Retval", /*inputs=*/{"ShardDataset"},
149             {{"T", DT_VARIANT}, {"index", 0}})},
150       /*funcs=*/{});
151   return dataset_def;
152 }
153 
InfiniteDataset()154 DatasetDef InfiniteDataset() {
155   DatasetDef dataset_def;
156   *dataset_def.mutable_graph() = GDef(
157       {NDef("start", "Const", /*inputs=*/{},
158             {{"value", AsScalar<int64_t>(0)}, {"dtype", DT_INT64}}),
159        NDef("stop", "Const", /*inputs=*/{},
160             {{"value", AsScalar<int64_t>(100000000)}, {"dtype", DT_INT64}}),
161        NDef("step", "Const", /*inputs=*/{},
162             {{"value", AsScalar<int64_t>(1)}, {"dtype", DT_INT64}}),
163        NDef("range", "RangeDataset", /*inputs=*/{"start", "stop", "step"},
164             {{"output_shapes", gtl::ArraySlice<TensorShape>{TensorShape()}},
165              {"output_types", gtl::ArraySlice<DataType>{DT_INT64}}}),
166        NDef("count", "Const", /*inputs=*/{},
167             {{"value", AsScalar<int64_t>(-1)}, {"dtype", DT_INT64}}),
168        NDef("repeat", "RepeatDataset", /*inputs=*/{"range", "count"},
169             {{"output_shapes", gtl::ArraySlice<TensorShape>{TensorShape()}},
170              {"output_types", gtl::ArraySlice<DataType>{DT_INT64}}}),
171        NDef("dataset", "_Retval", /*inputs=*/{"repeat"},
172             {{"T", DT_VARIANT}, {"index", 0}})},
173       {});
174   return dataset_def;
175 }
176 
InterleaveTextlineDataset(const std::vector<tstring> & filenames,const std::vector<tstring> & contents)177 StatusOr<DatasetDef> InterleaveTextlineDataset(
178     const std::vector<tstring>& filenames,
179     const std::vector<tstring>& contents) {
180   TF_RETURN_IF_ERROR(CreateTestFiles(filenames, contents));
181   DatasetDef dataset;
182   std::string graph_file =
183       io::JoinPath(kTestdataDir, kInterleaveTextlineDatasetFile);
184   TF_RETURN_IF_ERROR(
185       ReadTextProto(Env::Default(), graph_file, dataset.mutable_graph()));
186 
187   Tensor filenames_tensor = test::AsTensor<tstring>(
188       filenames, TensorShape({static_cast<int64_t>(filenames.size())}));
189   filenames_tensor.AsProtoTensorContent(
190       (*dataset.mutable_graph()->mutable_node(0)->mutable_attr())["value"]
191           .mutable_tensor());
192   return dataset;
193 }
194 
WaitWhile(std::function<StatusOr<bool> ()> f)195 Status WaitWhile(std::function<StatusOr<bool>()> f) {
196   while (true) {
197     TF_ASSIGN_OR_RETURN(bool result, f());
198     if (!result) {
199       return OkStatus();
200     }
201     Env::Default()->SleepForMicroseconds(10 * 1000);  // 10ms.
202   }
203 }
204 
205 }  // namespace testing
206 }  // namespace data
207 }  // namespace tensorflow
208