1 /* Copyright 2015 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/kernels/initializable_lookup_table.h"
17
18 #include "tensorflow/core/graph/graph_def_builder.h"
19 #include "tensorflow/core/lib/core/errors.h"
20
21 namespace tensorflow {
22 namespace lookup {
23
Find(OpKernelContext * ctx,const Tensor & keys,Tensor * values,const Tensor & default_value)24 Status InitializableLookupTable::Find(OpKernelContext* ctx, const Tensor& keys,
25 Tensor* values,
26 const Tensor& default_value) {
27 if (!is_initialized()) {
28 return errors::FailedPrecondition("Table not initialized.");
29 }
30 // Do not let the use migrate before the check; table is used without
31 // a lock by the readers.
32 std::atomic_thread_fence(std::memory_order_acquire);
33 return DoFind(keys, values, default_value);
34 }
35
ImportValues(OpKernelContext * ctx,const Tensor & keys,const Tensor & values)36 Status InitializableLookupTable::ImportValues(OpKernelContext* ctx,
37 const Tensor& keys,
38 const Tensor& values) {
39 lookup::KeyValueTensorIterator iter(&keys, &values);
40 auto serializer = absl::make_unique<InitializerSerializer>(
41 [keys, values](GraphDefBuilder* builder, Node* table, Node** out) {
42 Node* keys_node =
43 ops::SourceOp("Const", builder->opts()
44 .WithAttr("dtype", keys.dtype())
45 .WithAttr("value", keys));
46 Node* values_node =
47 ops::SourceOp("Const", builder->opts()
48 .WithAttr("dtype", values.dtype())
49 .WithAttr("value", values));
50 Node* import_table =
51 ops::TernaryOp("LookupTableImportV2", table, keys_node, values_node,
52 builder->opts()
53 .WithAttr("Tin", keys.dtype())
54 .WithAttr("Tout", values.dtype()));
55 *out = ops::UnaryOp("Identity", table,
56 builder->opts().WithControlInput(import_table));
57 return Status::OK();
58 });
59
60 return Initialize(iter, std::move(serializer));
61 }
62
Initialize(InitTableIterator & iter)63 Status InitializableLookupTable::Initialize(InitTableIterator& iter) {
64 return Initialize(iter, /*serializer=*/nullptr);
65 }
66
Initialize(InitTableIterator & iter,std::unique_ptr<InitializerSerializer> serializer)67 Status InitializableLookupTable::Initialize(
68 InitTableIterator& iter,
69 std::unique_ptr<InitializerSerializer> serializer) {
70 if (!iter.Valid()) {
71 return iter.status();
72 }
73 TF_RETURN_IF_ERROR(
74 CheckKeyAndValueTensorsForInsert(iter.keys(), iter.values()));
75
76 mutex_lock l(mu_);
77 if (is_initialized()) {
78 bool result;
79 TF_RETURN_IF_ERROR(AreEntriesSame(iter, &result));
80 // If the table is already initialized, we make sure that the entries in the
81 // table are the same that we want to initialize the table with.
82 if (!result) {
83 return errors::FailedPrecondition(
84 "Table was already initialized with "
85 "different data.");
86 } else {
87 return Status::OK();
88 }
89 }
90 TF_RETURN_IF_ERROR(DoLazyPrepare([&iter]() { return iter.total_size(); }));
91 while (iter.Valid()) {
92 TF_RETURN_IF_ERROR(DoInsert(iter.keys(), iter.values()));
93 iter.Next();
94 }
95 if (!errors::IsOutOfRange(iter.status())) {
96 return iter.status();
97 }
98
99 initializer_serializer_ = std::move(serializer);
100 is_initialized_.store(true, std::memory_order_release);
101 return Status::OK();
102 }
103
AreEntriesSame(const InitTableIterator & iter,bool * result)104 Status InitializableLookupTable::AreEntriesSame(const InitTableIterator& iter,
105 bool* result) {
106 *result = static_cast<size_t>(iter.total_size()) == size();
107 return Status::OK();
108 }
109
110 } // namespace lookup
111 } // namespace tensorflow
112