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/* Copyright 2015 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/types.h"
#include "tensorflow/core/framework/type_traits.h"
#include "tensorflow/core/platform/protobuf.h"
#include "tensorflow/core/platform/test.h"
namespace tensorflow {
namespace {
TEST(TypesTest, DeviceTypeName) {
EXPECT_EQ("CPU", DeviceTypeString(DeviceType(DEVICE_CPU)));
EXPECT_EQ("GPU", DeviceTypeString(DeviceType(DEVICE_GPU)));
}
TEST(TypesTest, kDataTypeRefOffset) {
// Basic sanity check
EXPECT_EQ(DT_FLOAT + kDataTypeRefOffset, DT_FLOAT_REF);
// Use the meta-data provided by proto2 to iterate through the basic
// types and validate that adding kDataTypeRefOffset gives the
// corresponding reference type.
const auto* enum_descriptor = DataType_descriptor();
int e = DataType_MIN;
if (e == DT_INVALID) ++e;
int e_ref = e + kDataTypeRefOffset;
EXPECT_FALSE(DataType_IsValid(e_ref - 1))
<< "Reference enum "
<< enum_descriptor->FindValueByNumber(e_ref - 1)->name()
<< " without corresponding base enum with value " << e - 1;
for (;
DataType_IsValid(e) && DataType_IsValid(e_ref) && e_ref <= DataType_MAX;
++e, ++e_ref) {
string enum_name = enum_descriptor->FindValueByNumber(e)->name();
string enum_ref_name = enum_descriptor->FindValueByNumber(e_ref)->name();
EXPECT_EQ(enum_name + "_REF", enum_ref_name)
<< enum_name << "_REF should have value " << e_ref << " not "
<< enum_ref_name;
// Validate DataTypeString() as well.
DataType dt_e = static_cast<DataType>(e);
DataType dt_e_ref = static_cast<DataType>(e_ref);
EXPECT_EQ(DataTypeString(dt_e) + "_ref", DataTypeString(dt_e_ref));
// Test DataTypeFromString reverse conversion
DataType dt_e2, dt_e2_ref;
EXPECT_TRUE(DataTypeFromString(DataTypeString(dt_e), &dt_e2));
EXPECT_EQ(dt_e, dt_e2);
EXPECT_TRUE(DataTypeFromString(DataTypeString(dt_e_ref), &dt_e2_ref));
EXPECT_EQ(dt_e_ref, dt_e2_ref);
}
ASSERT_FALSE(DataType_IsValid(e))
<< "Should define " << enum_descriptor->FindValueByNumber(e)->name()
<< "_REF to be " << e_ref;
ASSERT_FALSE(DataType_IsValid(e_ref))
<< "Extra reference enum "
<< enum_descriptor->FindValueByNumber(e_ref)->name()
<< " without corresponding base enum with value " << e;
ASSERT_LT(DataType_MAX, e_ref) << "Gap in reference types, missing value for "
<< e_ref;
// Make sure there are no enums defined after the last regular type before
// the first reference type.
for (; e < DataType_MIN + kDataTypeRefOffset; ++e) {
EXPECT_FALSE(DataType_IsValid(e))
<< "Discontinuous enum value "
<< enum_descriptor->FindValueByNumber(e)->name() << " = " << e;
}
}
TEST(TypesTest, DataTypeFromString) {
DataType dt;
ASSERT_TRUE(DataTypeFromString("int32", &dt));
EXPECT_EQ(DT_INT32, dt);
ASSERT_TRUE(DataTypeFromString("int32_ref", &dt));
EXPECT_EQ(DT_INT32_REF, dt);
EXPECT_FALSE(DataTypeFromString("int32_ref_ref", &dt));
EXPECT_FALSE(DataTypeFromString("foo", &dt));
EXPECT_FALSE(DataTypeFromString("foo_ref", &dt));
ASSERT_TRUE(DataTypeFromString("int64", &dt));
EXPECT_EQ(DT_INT64, dt);
ASSERT_TRUE(DataTypeFromString("int64_ref", &dt));
EXPECT_EQ(DT_INT64_REF, dt);
ASSERT_TRUE(DataTypeFromString("quint8_ref", &dt));
EXPECT_EQ(DT_QUINT8_REF, dt);
ASSERT_TRUE(DataTypeFromString("bfloat16", &dt));
EXPECT_EQ(DT_BFLOAT16, dt);
}
template <typename T>
static bool GetQuantized() {
return is_quantized<T>::value;
}
TEST(TypesTest, QuantizedTypes) {
// NOTE: GUnit cannot parse is::quantized<TYPE>::value() within the
// EXPECT_TRUE() clause, so we delegate through a template function.
EXPECT_TRUE(GetQuantized<qint8>());
EXPECT_TRUE(GetQuantized<quint8>());
EXPECT_TRUE(GetQuantized<qint32>());
EXPECT_FALSE(GetQuantized<int8>());
EXPECT_FALSE(GetQuantized<uint8>());
EXPECT_FALSE(GetQuantized<int16>());
EXPECT_FALSE(GetQuantized<int32>());
EXPECT_TRUE(DataTypeIsQuantized(DT_QINT8));
EXPECT_TRUE(DataTypeIsQuantized(DT_QUINT8));
EXPECT_TRUE(DataTypeIsQuantized(DT_QINT32));
EXPECT_FALSE(DataTypeIsQuantized(DT_INT8));
EXPECT_FALSE(DataTypeIsQuantized(DT_UINT8));
EXPECT_FALSE(DataTypeIsQuantized(DT_UINT16));
EXPECT_FALSE(DataTypeIsQuantized(DT_INT16));
EXPECT_FALSE(DataTypeIsQuantized(DT_INT32));
EXPECT_FALSE(DataTypeIsQuantized(DT_BFLOAT16));
}
TEST(TypesTest, IntegerTypes) {
for (auto dt : AllTypes()) {
const string name = DataTypeString(dt);
const StringPiece n = name;
EXPECT_EQ(DataTypeIsInteger(dt),
n.starts_with("int") || n.starts_with("uint"))
<< "DataTypeInteger failed for " << name;
}
}
} // namespace
} // namespace tensorflow
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