STT-tensorflow/tensorflow/lite/c/common_test.cc
Jaesung Chung 3749694080 Add complex<double> tensor support in TFLite
Even though we do not support complex<double> op kernels on mobile, it is
inevitable to support complex<double> tensors in order to enable TF
complex<double> ops via flex delegate.

This CL enables the complex<double> tensor type in MLIR converter only.

PiperOrigin-RevId: 321072365
Change-Id: I5ecd631339b3d5e00b3d999b9f2c6102b554cea5
2020-07-13 18:19:24 -07:00

143 lines
4.6 KiB
C++

/* Copyright 2017 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/lite/c/common.h"
#include <gtest/gtest.h>
namespace tflite {
// NOTE: this tests only the TfLiteIntArray part of context.
// most of common.h is provided in the context of using it with
// interpreter.h and interpreter.cc, so interpreter_test.cc tests context
// structures more thoroughly.
TEST(IntArray, TestIntArrayCreate) {
TfLiteIntArray* a = TfLiteIntArrayCreate(0);
TfLiteIntArray* b = TfLiteIntArrayCreate(3);
TfLiteIntArrayFree(a);
TfLiteIntArrayFree(b);
}
TEST(IntArray, TestIntArrayCopy) {
TfLiteIntArray* a = TfLiteIntArrayCreate(2);
a->data[0] = 22;
a->data[1] = 24;
TfLiteIntArray* b = TfLiteIntArrayCopy(a);
ASSERT_NE(a, b);
ASSERT_EQ(a->size, b->size);
ASSERT_EQ(a->data[0], b->data[0]);
ASSERT_EQ(a->data[1], b->data[1]);
TfLiteIntArrayFree(a);
TfLiteIntArrayFree(b);
}
TEST(IntArray, TestIntArrayEqual) {
TfLiteIntArray* a = TfLiteIntArrayCreate(1);
a->data[0] = 1;
TfLiteIntArray* b = TfLiteIntArrayCreate(2);
b->data[0] = 5;
b->data[1] = 6;
TfLiteIntArray* c = TfLiteIntArrayCreate(2);
c->data[0] = 5;
c->data[1] = 6;
TfLiteIntArray* d = TfLiteIntArrayCreate(2);
d->data[0] = 6;
d->data[1] = 6;
ASSERT_FALSE(TfLiteIntArrayEqual(a, b));
ASSERT_TRUE(TfLiteIntArrayEqual(b, c));
ASSERT_TRUE(TfLiteIntArrayEqual(b, b));
ASSERT_FALSE(TfLiteIntArrayEqual(c, d));
TfLiteIntArrayFree(a);
TfLiteIntArrayFree(b);
TfLiteIntArrayFree(c);
TfLiteIntArrayFree(d);
}
TEST(FloatArray, TestFloatArrayCreate) {
TfLiteFloatArray* a = TfLiteFloatArrayCreate(0);
TfLiteFloatArray* b = TfLiteFloatArrayCreate(3);
TfLiteFloatArrayFree(a);
TfLiteFloatArrayFree(b);
}
TEST(Types, TestTypeNames) {
auto type_name = [](TfLiteType t) {
return std::string(TfLiteTypeGetName(t));
};
EXPECT_EQ(type_name(kTfLiteNoType), "NOTYPE");
EXPECT_EQ(type_name(kTfLiteFloat64), "FLOAT64");
EXPECT_EQ(type_name(kTfLiteFloat32), "FLOAT32");
EXPECT_EQ(type_name(kTfLiteFloat16), "FLOAT16");
EXPECT_EQ(type_name(kTfLiteInt16), "INT16");
EXPECT_EQ(type_name(kTfLiteInt32), "INT32");
EXPECT_EQ(type_name(kTfLiteUInt8), "UINT8");
EXPECT_EQ(type_name(kTfLiteInt8), "INT8");
EXPECT_EQ(type_name(kTfLiteInt64), "INT64");
EXPECT_EQ(type_name(kTfLiteBool), "BOOL");
EXPECT_EQ(type_name(kTfLiteComplex64), "COMPLEX64");
EXPECT_EQ(type_name(kTfLiteComplex128), "COMPLEX128");
EXPECT_EQ(type_name(kTfLiteString), "STRING");
}
TEST(Quantization, TestQuantizationFree) {
TfLiteTensor t;
// Set these values, otherwise TfLiteTensorFree has uninitialized values.
t.allocation_type = kTfLiteArenaRw;
t.dims = nullptr;
t.dims_signature = nullptr;
t.quantization.type = kTfLiteAffineQuantization;
t.sparsity = nullptr;
auto* params = reinterpret_cast<TfLiteAffineQuantization*>(
malloc(sizeof(TfLiteAffineQuantization)));
params->scale = TfLiteFloatArrayCreate(3);
params->zero_point = TfLiteIntArrayCreate(3);
t.quantization.params = reinterpret_cast<void*>(params);
TfLiteTensorFree(&t);
}
TEST(Sparsity, TestSparsityFree) {
TfLiteTensor t = {};
// Set these values, otherwise TfLiteTensorFree has uninitialized values.
t.allocation_type = kTfLiteArenaRw;
t.dims = nullptr;
t.dims_signature = nullptr;
// A dummy CSR sparse matrix.
t.sparsity = static_cast<TfLiteSparsity*>(malloc(sizeof(TfLiteSparsity)));
t.sparsity->traversal_order = TfLiteIntArrayCreate(2);
t.sparsity->block_map = nullptr;
t.sparsity->dim_metadata = static_cast<TfLiteDimensionMetadata*>(
malloc(sizeof(TfLiteDimensionMetadata) * 2));
t.sparsity->dim_metadata_size = 2;
t.sparsity->dim_metadata[0].format = kTfLiteDimDense;
t.sparsity->dim_metadata[0].dense_size = 4;
t.sparsity->dim_metadata[1].format = kTfLiteDimSparseCSR;
t.sparsity->dim_metadata[1].array_segments = TfLiteIntArrayCreate(2);
t.sparsity->dim_metadata[1].array_indices = TfLiteIntArrayCreate(3);
TfLiteTensorFree(&t);
}
} // namespace tflite
int main(int argc, char** argv) {
::testing::InitGoogleTest(&argc, argv);
return RUN_ALL_TESTS();
}