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/* 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/util/example_proto_fast_parsing.h"
#include "tensorflow/core/example/example.pb.h"
#include "tensorflow/core/platform/protobuf.h"
#include "tensorflow/core/platform/test.h"
#include "tensorflow/core/platform/test_benchmark.h"
namespace tensorflow {
namespace example {
namespace {
constexpr char kDenseInt64Key[] = "dense_int64";
constexpr char kDenseFloatKey[] = "dense_float";
constexpr char kDenseStringKey[] = "dense_string";
constexpr char kSparseInt64Key[] = "sparse_int64";
constexpr char kSparseFloatKey[] = "sparse_float";
constexpr char kSparseStringKey[] = "sparse_string";
string SerializedToReadable(string serialized) {
string result;
result += '"';
for (char c : serialized)
result += strings::StrCat("\\x", strings::Hex(c, strings::ZERO_PAD_2));
result += '"';
return result;
}
string Serialize(const Example& example) {
string serialized;
example.SerializeToString(&serialized);
return serialized;
}
void TestCorrectness(const string& serialized) {
Example example;
Example fast_example;
EXPECT_TRUE(example.ParseFromString(serialized));
EXPECT_TRUE(TestFastParse(serialized, &fast_example));
EXPECT_EQ(example.DebugString(), fast_example.DebugString());
if (example.DebugString() != fast_example.DebugString()) {
LOG(ERROR) << "Bad serialized: " << SerializedToReadable(serialized);
}
}
// Fast parsing does not differentiate between EmptyExample and EmptyFeatures
// TEST(FastParse, EmptyExample) {
// Example example;
// TestCorrectness(example);
// }
// Test that concatenating two Example protos in their serialized string
// representations gets parsed identically by TestFastParse(..) and the regular
// Example.ParseFromString(..).
TEST(FastParse, SingleInt64WithContext) {
Example example;
(*example.mutable_features()->mutable_feature())["age"]
.mutable_int64_list()
->add_value(13);
Example context;
(*context.mutable_features()->mutable_feature())["zipcode"]
.mutable_int64_list()
->add_value(94043);
TestCorrectness(strings::StrCat(Serialize(example), Serialize(context)));
}
TEST(FastParse, NonPacked) {
TestCorrectness(
"\x0a\x0e\x0a\x0c\x0a\x03\x61\x67\x65\x12\x05\x1a\x03\x0a\x01\x0d");
}
TEST(FastParse, Packed) {
TestCorrectness(
"\x0a\x0d\x0a\x0b\x0a\x03\x61\x67\x65\x12\x04\x1a\x02\x08\x0d");
}
TEST(FastParse, EmptyFeatures) {
Example example;
example.mutable_features();
TestCorrectness(Serialize(example));
}
void TestCorrectnessJson(const string& json) {
auto resolver = protobuf::util::NewTypeResolverForDescriptorPool(
"type.googleapis.com", protobuf::DescriptorPool::generated_pool());
string serialized;
auto s = protobuf::util::JsonToBinaryString(
resolver, "type.googleapis.com/tensorflow.Example", json, &serialized);
EXPECT_TRUE(s.ok()) << s;
delete resolver;
TestCorrectness(serialized);
}
TEST(FastParse, JsonUnivalent) {
TestCorrectnessJson(
"{'features': {"
" 'feature': {'age': {'int64_list': {'value': [0]} }}, "
" 'feature': {'flo': {'float_list': {'value': [1.1]} }}, "
" 'feature': {'byt': {'bytes_list': {'value': ['WW8='] }}}"
"}}");
}
TEST(FastParse, JsonMultivalent) {
TestCorrectnessJson(
"{'features': {"
" 'feature': {'age': {'int64_list': {'value': [0, 13, 23]} }}, "
" 'feature': {'flo': {'float_list': {'value': [1.1, 1.2, 1.3]} }}, "
" 'feature': {'byt': {'bytes_list': {'value': ['WW8=', 'WW8K'] }}}"
"}}");
}
TEST(FastParse, SingleInt64) {
Example example;
(*example.mutable_features()->mutable_feature())["age"]
.mutable_int64_list()
->add_value(13);
TestCorrectness(Serialize(example));
}
TEST(FastParse, SomeFeatures) {
Example example;
(*example.mutable_features()->mutable_feature())[""];
(*example.mutable_features()->mutable_feature())["empty_bytes_list"]
.mutable_bytes_list();
(*example.mutable_features()->mutable_feature())["empty_float_list"]
.mutable_float_list();
(*example.mutable_features()->mutable_feature())["empty_int64_list"]
.mutable_int64_list();
BytesList* bytes_list =
(*example.mutable_features()->mutable_feature())["bytes_list"]
.mutable_bytes_list();
bytes_list->add_value("bytes1");
bytes_list->add_value("bytes2");
FloatList* float_list =
(*example.mutable_features()->mutable_feature())["float_list"]
.mutable_float_list();
float_list->add_value(1.0);
float_list->add_value(2.0);
Int64List* int64_list =
(*example.mutable_features()->mutable_feature())["int64_list"]
.mutable_int64_list();
int64_list->add_value(3);
int64_list->add_value(270);
int64_list->add_value(86942);
TestCorrectness(Serialize(example));
}
string MakeSerializedExample() {
Example example;
const int kFeatureNameLength = 10;
const int kFeatureValueLength = 20;
const int kBytesFeatureCount = 200;
const int kFloatFeatureCount = 200;
const int kInt64FeatureCount = 200;
auto& fmap = *example.mutable_features()->mutable_feature();
for (int i = 0; i < kBytesFeatureCount; ++i) {
fmap[strings::StrCat(string('b', kFeatureNameLength), i)]
.mutable_bytes_list()
->add_value(string('v', kFeatureValueLength));
}
for (int i = 0; i < kFloatFeatureCount; ++i) {
fmap[strings::StrCat(string('f', kFeatureNameLength), i)]
.mutable_float_list()
->add_value(123123123.123);
}
for (int i = 0; i < kInt64FeatureCount; ++i) {
fmap[strings::StrCat(string('i', kFeatureNameLength), i)]
.mutable_int64_list()
->add_value(10 * i);
}
string serialized;
example.SerializeToString(&serialized);
return serialized;
}
TEST(TestFastParseExample, Empty) {
Result result;
FastParseExampleConfig config;
config.sparse.push_back({"test", DT_STRING});
Status status = FastParseExample(config, gtl::ArraySlice<string>(),
gtl::ArraySlice<string>(), nullptr, &result);
EXPECT_TRUE(status.ok()) << status;
}
} // namespace
} // namespace example
} // namespace tensorflow
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