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concatenate_dataset_op_test.cc
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concatenate_dataset_op_test.cc
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/* Copyright 2019 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/kernels/data/dataset_test_base.h"
namespace tensorflow {
namespace data {
namespace {
constexpr char kNodeName[] = "concatenate_dataset";
constexpr char kOpName[] = "ConcatenateDataset";
class ConcatenateDatasetOpTest : public DatasetOpsTestBase {
protected:
// Creates `TensorSliceDataset` variant tensors from the input vector of
// tensor vectors.
Status CreateTensorSliceDatasetTensors(
const std::vector<std::vector<Tensor>> &tensor_vectors,
std::vector<Tensor> *const dataset_tensors) {
for (int i = 0; i < tensor_vectors.size(); ++i) {
std::vector<Tensor> tensors = tensor_vectors[i];
DatasetBase *tensor_slice_dataset;
TF_RETURN_IF_ERROR(
CreateTensorSliceDataset(strings::StrCat("tensor_slice_node_", i),
&tensors, &tensor_slice_dataset));
Tensor dataset_tensor(DT_VARIANT, TensorShape({}));
TF_RETURN_IF_ERROR(
StoreDatasetInVariantTensor(tensor_slice_dataset, &dataset_tensor));
dataset_tensors->emplace_back(std::move(dataset_tensor));
}
return Status::OK();
}
// Creates a new ConcatenateDataset op kernel.
Status CreateConcatenateDatasetKernel(
const DataTypeVector &output_types,
const std::vector<PartialTensorShape> &output_shapes,
std::unique_ptr<OpKernel> *op_kernel) {
NodeDef node_def = test::function::NDef(
kNodeName, kOpName, {"input_dataset", "another_dataset"},
{{"output_types", output_types}, {"output_shapes", output_shapes}});
TF_RETURN_IF_ERROR(CreateOpKernel(node_def, op_kernel));
return Status::OK();
}
// Creates a new ConcatenateDataset op kernel context.
Status CreateConcatenateDatasetContext(
OpKernel *const op_kernel,
gtl::InlinedVector<TensorValue, 4> *const inputs,
std::unique_ptr<OpKernelContext> *context) {
TF_RETURN_IF_ERROR(CheckOpKernelInput(*op_kernel, *inputs));
TF_RETURN_IF_ERROR(CreateOpKernelContext(op_kernel, inputs, context));
return Status::OK();
}
};
struct TestCase {
std::vector<std::vector<Tensor>> input_tensors;
std::vector<Tensor> expected_outputs;
DataTypeVector expected_output_dtypes;
std::vector<PartialTensorShape> expected_output_shapes;
int64 expected_cardinality;
std::vector<int> breakpoints;
};
// Test case 1: same shape.
TestCase SameShapeTestCase() {
return {/*input_tensors*/
{{DatasetOpsTestBase::CreateTensor<int64>(TensorShape{2, 2},
{1, 2, 3, 4}),
DatasetOpsTestBase::CreateTensor<int64>(TensorShape{2, 2},
{5, 6, 7, 8})},
{DatasetOpsTestBase::CreateTensor<int64>(TensorShape{2, 2},
{11, 12, 13, 14}),
DatasetOpsTestBase::CreateTensor<int64>(TensorShape{2, 2},
{15, 16, 17, 18})}},
/*expected_outputs*/
{DatasetOpsTestBase::CreateTensor<int64>(TensorShape{2}, {1, 2}),
DatasetOpsTestBase::CreateTensor<int64>(TensorShape{2}, {5, 6}),
DatasetOpsTestBase::CreateTensor<int64>(TensorShape{2}, {3, 4}),
DatasetOpsTestBase::CreateTensor<int64>(TensorShape{2}, {7, 8}),
DatasetOpsTestBase::CreateTensor<int64>(TensorShape{2}, {11, 12}),
DatasetOpsTestBase::CreateTensor<int64>(TensorShape{2}, {15, 16}),
DatasetOpsTestBase::CreateTensor<int64>(TensorShape{2}, {13, 14}),
DatasetOpsTestBase::CreateTensor<int64>(TensorShape{2}, {17, 18})},
/*expected_output_dtypes*/ {DT_INT64, DT_INT64},
/*expected_output_shapes*/
{PartialTensorShape({2}), PartialTensorShape({2})},
/*expected_cardinality*/ 4,
/*breakpoints*/ {0, 2, 5}};
}
// Test case 2: different shape.
TestCase DifferentShapeTestCase() {
return {
/*input_tensors*/
{{DatasetOpsTestBase::CreateTensor<int64>(TensorShape{2, 3},
{1, 2, 3, 4, 5, 6}),
DatasetOpsTestBase::CreateTensor<int64>(TensorShape{2, 2},
{7, 8, 9, 10})},
{DatasetOpsTestBase::CreateTensor<int64>(TensorShape{2, 2},
{11, 12, 13, 14}),
DatasetOpsTestBase::CreateTensor<int64>(TensorShape{2, 1}, {15, 16})}},
/*expected_outputs*/
{DatasetOpsTestBase::CreateTensor<int64>(TensorShape{3}, {1, 2, 3}),
DatasetOpsTestBase::CreateTensor<int64>(TensorShape{2}, {7, 8}),
DatasetOpsTestBase::CreateTensor<int64>(TensorShape{3}, {4, 5, 6}),
DatasetOpsTestBase::CreateTensor<int64>(TensorShape{2}, {9, 10}),
DatasetOpsTestBase::CreateTensor<int64>(TensorShape{2}, {11, 12}),
DatasetOpsTestBase::CreateTensor<int64>(TensorShape{1}, {15}),
DatasetOpsTestBase::CreateTensor<int64>(TensorShape{2}, {13, 14}),
DatasetOpsTestBase::CreateTensor<int64>(TensorShape{1}, {16})},
/*expected_output_dtypes*/ {DT_INT64, DT_INT64},
/*expected_output_shapes*/
{PartialTensorShape({-1}), PartialTensorShape({-1})},
/*expected_cardinality*/ 4,
/*breakpoints*/ {0, 2, 5}};
}
// Test case 3: different dtypes
TestCase DifferentDtypeTestCase() {
return {/*input_tensors*/ {{DatasetOpsTestBase::CreateTensor<int64>(
TensorShape({2, 2}), {1, 2, 3, 4})},
{DatasetOpsTestBase::CreateTensor<double>(
TensorShape({2, 2}), {1.0, 2.0, 3.0, 4.0})}},
/*expected_outputs*/ {},
/*expected_output_dtypes*/ {DT_INT64},
/*expected_output_shapes*/ {PartialTensorShape({2})},
/*expected_cardinality*/ 0,
/*breakpoints*/ {}};
}
class ParameterizedConcatenateDatasetOpTest
: public ConcatenateDatasetOpTest,
public ::testing::WithParamInterface<TestCase> {};
TEST_P(ParameterizedConcatenateDatasetOpTest, GetNext) {
int thread_num = 2, cpu_num = 2;
TF_ASSERT_OK(InitThreadPool(thread_num));
TF_ASSERT_OK(InitFunctionLibraryRuntime({}, cpu_num));
const TestCase &test_case = GetParam();
std::vector<Tensor> tensor_slice_dataset_tensors;
TF_ASSERT_OK(CreateTensorSliceDatasetTensors(test_case.input_tensors,
&tensor_slice_dataset_tensors));
gtl::InlinedVector<TensorValue, 4> inputs;
for (auto &tensor : tensor_slice_dataset_tensors) {
inputs.emplace_back(&tensor);
}
std::unique_ptr<OpKernel> dataset_kernel;
TF_ASSERT_OK(CreateConcatenateDatasetKernel(test_case.expected_output_dtypes,
test_case.expected_output_shapes,
&dataset_kernel));
std::unique_ptr<OpKernelContext> dataset_kernel_ctx;
TF_ASSERT_OK(CreateConcatenateDatasetContext(dataset_kernel.get(), &inputs,
&dataset_kernel_ctx));
DatasetBase *concatenate_dataset;
TF_ASSERT_OK(CreateDataset(dataset_kernel.get(), dataset_kernel_ctx.get(),
&concatenate_dataset));
core::ScopedUnref scoped_unref(concatenate_dataset);
std::unique_ptr<IteratorContext> iterator_ctx;
TF_ASSERT_OK(CreateIteratorContext(dataset_kernel_ctx.get(), &iterator_ctx));
std::unique_ptr<IteratorBase> iterator;
TF_ASSERT_OK(concatenate_dataset->MakeIterator(iterator_ctx.get(), "Iterator",
&iterator));
auto expected_outputs_it = test_case.expected_outputs.begin();
bool end_of_sequence = false;
std::vector<Tensor> out_tensors;
while (!end_of_sequence) {
TF_EXPECT_OK(
iterator->GetNext(iterator_ctx.get(), &out_tensors, &end_of_sequence));
if (!end_of_sequence) {
for (const auto &tensor : out_tensors) {
EXPECT_NE(expected_outputs_it, test_case.expected_outputs.end());
TF_EXPECT_OK(ExpectEqual(tensor, *expected_outputs_it));
expected_outputs_it++;
}
}
}
EXPECT_EQ(expected_outputs_it, test_case.expected_outputs.end());
}
TEST_F(ConcatenateDatasetOpTest, DifferentDtypes) {
int thread_num = 2, cpu_num = 2;
TF_ASSERT_OK(InitThreadPool(thread_num));
TF_ASSERT_OK(InitFunctionLibraryRuntime({}, cpu_num));
const TestCase &test_case = DifferentDtypeTestCase();
std::vector<Tensor> tensor_slice_dataset_tensors;
TF_ASSERT_OK(CreateTensorSliceDatasetTensors(test_case.input_tensors,
&tensor_slice_dataset_tensors));
gtl::InlinedVector<TensorValue, 4> inputs;
for (auto &tensor : tensor_slice_dataset_tensors) {
inputs.emplace_back(&tensor);
}
std::unique_ptr<OpKernel> dataset_kernel;
TF_ASSERT_OK(CreateConcatenateDatasetKernel(test_case.expected_output_dtypes,
test_case.expected_output_shapes,
&dataset_kernel));
std::unique_ptr<OpKernelContext> dataset_kernel_ctx;
TF_ASSERT_OK(CreateConcatenateDatasetContext(dataset_kernel.get(), &inputs,
&dataset_kernel_ctx));
DatasetBase *concatenate_dataset;
EXPECT_EQ(CreateDataset(dataset_kernel.get(), dataset_kernel_ctx.get(),
&concatenate_dataset)
.code(),
tensorflow::error::INVALID_ARGUMENT);
}
TEST_F(ConcatenateDatasetOpTest, DatasetNodeName) {
int thread_num = 2, cpu_num = 2;
TF_ASSERT_OK(InitThreadPool(thread_num));
TF_ASSERT_OK(InitFunctionLibraryRuntime({}, cpu_num));
const TestCase &test_case = SameShapeTestCase();
std::vector<Tensor> tensor_slice_dataset_tensors;
TF_ASSERT_OK(CreateTensorSliceDatasetTensors(test_case.input_tensors,
&tensor_slice_dataset_tensors));
gtl::InlinedVector<TensorValue, 4> inputs;
for (auto &tensor : tensor_slice_dataset_tensors) {
inputs.emplace_back(&tensor);
}
std::unique_ptr<OpKernel> dataset_kernel;
TF_ASSERT_OK(CreateConcatenateDatasetKernel(test_case.expected_output_dtypes,
test_case.expected_output_shapes,
&dataset_kernel));
std::unique_ptr<OpKernelContext> dataset_kernel_ctx;
TF_ASSERT_OK(CreateConcatenateDatasetContext(dataset_kernel.get(), &inputs,
&dataset_kernel_ctx));
DatasetBase *concatenate_dataset;
TF_ASSERT_OK(CreateDataset(dataset_kernel.get(), dataset_kernel_ctx.get(),
&concatenate_dataset));
core::ScopedUnref scoped_unref(concatenate_dataset);
EXPECT_EQ(concatenate_dataset->node_name(), kNodeName);
}
TEST_F(ConcatenateDatasetOpTest, DatasetTypeString) {
int thread_num = 2, cpu_num = 2;
TF_ASSERT_OK(InitThreadPool(thread_num));
TF_ASSERT_OK(InitFunctionLibraryRuntime({}, cpu_num));
const TestCase &test_case = SameShapeTestCase();
std::vector<Tensor> tensor_slice_dataset_tensors;
TF_ASSERT_OK(CreateTensorSliceDatasetTensors(test_case.input_tensors,
&tensor_slice_dataset_tensors));
gtl::InlinedVector<TensorValue, 4> inputs;
for (auto &tensor : tensor_slice_dataset_tensors) {
inputs.emplace_back(&tensor);
}
std::unique_ptr<OpKernel> dataset_kernel;
TF_ASSERT_OK(CreateConcatenateDatasetKernel(test_case.expected_output_dtypes,
test_case.expected_output_shapes,
&dataset_kernel));
std::unique_ptr<OpKernelContext> dataset_kernel_ctx;
TF_ASSERT_OK(CreateConcatenateDatasetContext(dataset_kernel.get(), &inputs,
&dataset_kernel_ctx));
DatasetBase *concatenate_dataset;
TF_ASSERT_OK(CreateDataset(dataset_kernel.get(), dataset_kernel_ctx.get(),
&concatenate_dataset));
core::ScopedUnref scoped_unref(concatenate_dataset);
EXPECT_EQ(concatenate_dataset->type_string(), kOpName);
}
TEST_P(ParameterizedConcatenateDatasetOpTest, DatasetOutputDtypes) {
int thread_num = 2, cpu_num = 2;
TF_ASSERT_OK(InitThreadPool(thread_num));
TF_ASSERT_OK(InitFunctionLibraryRuntime({}, cpu_num));
const TestCase &test_case = GetParam();
std::vector<Tensor> tensor_slice_dataset_tensors;
TF_ASSERT_OK(CreateTensorSliceDatasetTensors(test_case.input_tensors,
&tensor_slice_dataset_tensors));
gtl::InlinedVector<TensorValue, 4> inputs;
for (auto &tensor : tensor_slice_dataset_tensors) {
inputs.emplace_back(&tensor);
}
std::unique_ptr<OpKernel> dataset_kernel;
TF_ASSERT_OK(CreateConcatenateDatasetKernel(test_case.expected_output_dtypes,
test_case.expected_output_shapes,
&dataset_kernel));
std::unique_ptr<OpKernelContext> dataset_kernel_ctx;
TF_ASSERT_OK(CreateConcatenateDatasetContext(dataset_kernel.get(), &inputs,
&dataset_kernel_ctx));
DatasetBase *concatenate_dataset;
TF_ASSERT_OK(CreateDataset(dataset_kernel.get(), dataset_kernel_ctx.get(),
&concatenate_dataset));
core::ScopedUnref scoped_unref(concatenate_dataset);
TF_EXPECT_OK(VerifyTypesMatch(concatenate_dataset->output_dtypes(),
test_case.expected_output_dtypes));
}
TEST_P(ParameterizedConcatenateDatasetOpTest, DatasetOutputShapes) {
int thread_num = 2, cpu_num = 2;
TF_ASSERT_OK(InitThreadPool(thread_num));
TF_ASSERT_OK(InitFunctionLibraryRuntime({}, cpu_num));
const TestCase &test_case = GetParam();
std::vector<Tensor> tensor_slice_dataset_tensors;
TF_ASSERT_OK(CreateTensorSliceDatasetTensors(test_case.input_tensors,
&tensor_slice_dataset_tensors));
gtl::InlinedVector<TensorValue, 4> inputs;
for (auto &tensor : tensor_slice_dataset_tensors) {
inputs.emplace_back(&tensor);
}
std::unique_ptr<OpKernel> dataset_kernel;
TF_ASSERT_OK(CreateConcatenateDatasetKernel(test_case.expected_output_dtypes,
test_case.expected_output_shapes,
&dataset_kernel));
std::unique_ptr<OpKernelContext> dataset_kernel_ctx;
TF_ASSERT_OK(CreateConcatenateDatasetContext(dataset_kernel.get(), &inputs,
&dataset_kernel_ctx));
DatasetBase *concatenate_dataset;
TF_ASSERT_OK(CreateDataset(dataset_kernel.get(), dataset_kernel_ctx.get(),
&concatenate_dataset));
core::ScopedUnref scoped_unref(concatenate_dataset);
TF_EXPECT_OK(VerifyShapesCompatible(concatenate_dataset->output_shapes(),
test_case.expected_output_shapes));
}
TEST_P(ParameterizedConcatenateDatasetOpTest, Cardinality) {
int thread_num = 2, cpu_num = 2;
TF_ASSERT_OK(InitThreadPool(thread_num));
TF_ASSERT_OK(InitFunctionLibraryRuntime({}, cpu_num));
const TestCase &test_case = GetParam();
std::vector<Tensor> tensor_slice_dataset_tensors;
TF_ASSERT_OK(CreateTensorSliceDatasetTensors(test_case.input_tensors,
&tensor_slice_dataset_tensors));
gtl::InlinedVector<TensorValue, 4> inputs;
for (auto &tensor : tensor_slice_dataset_tensors) {
inputs.emplace_back(&tensor);
}
std::unique_ptr<OpKernel> dataset_kernel;
TF_ASSERT_OK(CreateConcatenateDatasetKernel(test_case.expected_output_dtypes,
test_case.expected_output_shapes,
&dataset_kernel));
std::unique_ptr<OpKernelContext> dataset_kernel_ctx;
TF_ASSERT_OK(CreateConcatenateDatasetContext(dataset_kernel.get(), &inputs,
&dataset_kernel_ctx));
DatasetBase *concatenate_dataset;
TF_ASSERT_OK(CreateDataset(dataset_kernel.get(), dataset_kernel_ctx.get(),
&concatenate_dataset));
core::ScopedUnref scoped_unref(concatenate_dataset);
EXPECT_EQ(concatenate_dataset->Cardinality(), test_case.expected_cardinality);
}
TEST_F(ConcatenateDatasetOpTest, DatasetSave) {
int thread_num = 2, cpu_num = 2;
TF_ASSERT_OK(InitThreadPool(thread_num));
TF_ASSERT_OK(InitFunctionLibraryRuntime({}, cpu_num));
const TestCase &test_case = SameShapeTestCase();
std::vector<Tensor> tensor_slice_dataset_tensors;
TF_ASSERT_OK(CreateTensorSliceDatasetTensors(test_case.input_tensors,
&tensor_slice_dataset_tensors));
gtl::InlinedVector<TensorValue, 4> inputs;
for (auto &tensor : tensor_slice_dataset_tensors) {
inputs.emplace_back(&tensor);
}
std::unique_ptr<OpKernel> dataset_kernel;
TF_ASSERT_OK(CreateConcatenateDatasetKernel(test_case.expected_output_dtypes,
test_case.expected_output_shapes,
&dataset_kernel));
std::unique_ptr<OpKernelContext> dataset_kernel_ctx;
TF_ASSERT_OK(CreateConcatenateDatasetContext(dataset_kernel.get(), &inputs,
&dataset_kernel_ctx));
DatasetBase *concatenate_dataset;
TF_ASSERT_OK(CreateDataset(dataset_kernel.get(), dataset_kernel_ctx.get(),
&concatenate_dataset));
core::ScopedUnref scoped_unref(concatenate_dataset);
std::unique_ptr<SerializationContext> serialization_ctx;
TF_ASSERT_OK(CreateSerializationContext(&serialization_ctx));
VariantTensorData data;
VariantTensorDataWriter writer(&data);
TF_ASSERT_OK(concatenate_dataset->Save(serialization_ctx.get(), &writer));
TF_ASSERT_OK(writer.Flush());
}
TEST_P(ParameterizedConcatenateDatasetOpTest, IteratorOutputDtypes) {
int thread_num = 2, cpu_num = 2;
TF_ASSERT_OK(InitThreadPool(thread_num));
TF_ASSERT_OK(InitFunctionLibraryRuntime({}, cpu_num));
const TestCase &test_case = GetParam();
std::vector<Tensor> tensor_slice_dataset_tensors;
TF_ASSERT_OK(CreateTensorSliceDatasetTensors(test_case.input_tensors,
&tensor_slice_dataset_tensors));
gtl::InlinedVector<TensorValue, 4> inputs;
for (auto &tensor : tensor_slice_dataset_tensors) {
inputs.emplace_back(&tensor);
}
std::unique_ptr<OpKernel> dataset_kernel;
TF_ASSERT_OK(CreateConcatenateDatasetKernel(test_case.expected_output_dtypes,
test_case.expected_output_shapes,
&dataset_kernel));
std::unique_ptr<OpKernelContext> dataset_kernel_ctx;
TF_ASSERT_OK(CreateConcatenateDatasetContext(dataset_kernel.get(), &inputs,
&dataset_kernel_ctx));
DatasetBase *concatenate_dataset;
TF_ASSERT_OK(CreateDataset(dataset_kernel.get(), dataset_kernel_ctx.get(),
&concatenate_dataset));
core::ScopedUnref scoped_unref(concatenate_dataset);
std::unique_ptr<IteratorContext> iterator_ctx;
TF_ASSERT_OK(CreateIteratorContext(dataset_kernel_ctx.get(), &iterator_ctx));
std::unique_ptr<IteratorBase> iterator;
TF_ASSERT_OK(concatenate_dataset->MakeIterator(iterator_ctx.get(), "Iterator",
&iterator));
TF_EXPECT_OK(VerifyTypesMatch(iterator->output_dtypes(),
test_case.expected_output_dtypes));
}
TEST_P(ParameterizedConcatenateDatasetOpTest, IteratorOutputShapes) {
int thread_num = 2, cpu_num = 2;
TF_ASSERT_OK(InitThreadPool(thread_num));
TF_ASSERT_OK(InitFunctionLibraryRuntime({}, cpu_num));
const TestCase &test_case = GetParam();
std::vector<Tensor> tensor_slice_dataset_tensors;
TF_ASSERT_OK(CreateTensorSliceDatasetTensors(test_case.input_tensors,
&tensor_slice_dataset_tensors));
gtl::InlinedVector<TensorValue, 4> inputs;
for (auto &tensor : tensor_slice_dataset_tensors) {
inputs.emplace_back(&tensor);
}
std::unique_ptr<OpKernel> dataset_kernel;
TF_ASSERT_OK(CreateConcatenateDatasetKernel(test_case.expected_output_dtypes,
test_case.expected_output_shapes,
&dataset_kernel));
std::unique_ptr<OpKernelContext> dataset_kernel_ctx;
TF_ASSERT_OK(CreateConcatenateDatasetContext(dataset_kernel.get(), &inputs,
&dataset_kernel_ctx));
DatasetBase *concatenate_dataset;
TF_ASSERT_OK(CreateDataset(dataset_kernel.get(), dataset_kernel_ctx.get(),
&concatenate_dataset));
core::ScopedUnref scoped_unref(concatenate_dataset);
std::unique_ptr<IteratorContext> iterator_ctx;
TF_ASSERT_OK(CreateIteratorContext(dataset_kernel_ctx.get(), &iterator_ctx));
std::unique_ptr<IteratorBase> iterator;
TF_ASSERT_OK(concatenate_dataset->MakeIterator(iterator_ctx.get(), "Iterator",
&iterator));
TF_EXPECT_OK(VerifyShapesCompatible(iterator->output_shapes(),
test_case.expected_output_shapes));
}
TEST_F(ConcatenateDatasetOpTest, IteratorOutputPrefix) {
int thread_num = 2, cpu_num = 2;
TF_ASSERT_OK(InitThreadPool(thread_num));
TF_ASSERT_OK(InitFunctionLibraryRuntime({}, cpu_num));
const TestCase &test_case = SameShapeTestCase();
std::vector<Tensor> tensor_slice_dataset_tensors;
TF_ASSERT_OK(CreateTensorSliceDatasetTensors(test_case.input_tensors,
&tensor_slice_dataset_tensors));
gtl::InlinedVector<TensorValue, 4> inputs;
for (auto &tensor : tensor_slice_dataset_tensors) {
inputs.emplace_back(&tensor);
}
std::unique_ptr<OpKernel> dataset_kernel;
TF_ASSERT_OK(CreateConcatenateDatasetKernel(test_case.expected_output_dtypes,
test_case.expected_output_shapes,
&dataset_kernel));
std::unique_ptr<OpKernelContext> dataset_kernel_ctx;
TF_ASSERT_OK(CreateConcatenateDatasetContext(dataset_kernel.get(), &inputs,
&dataset_kernel_ctx));
DatasetBase *concatenate_dataset;
TF_ASSERT_OK(CreateDataset(dataset_kernel.get(), dataset_kernel_ctx.get(),
&concatenate_dataset));
core::ScopedUnref scoped_unref(concatenate_dataset);
std::unique_ptr<IteratorContext> iterator_ctx;
TF_ASSERT_OK(CreateIteratorContext(dataset_kernel_ctx.get(), &iterator_ctx));
std::unique_ptr<IteratorBase> iterator;
TF_ASSERT_OK(concatenate_dataset->MakeIterator(iterator_ctx.get(), "Iterator",
&iterator));
EXPECT_EQ(iterator->prefix(), "Iterator::Concatenate");
}
TEST_P(ParameterizedConcatenateDatasetOpTest, Roundtrip) {
int thread_num = 2, cpu_num = 2;
TF_ASSERT_OK(InitThreadPool(thread_num));
TF_ASSERT_OK(InitFunctionLibraryRuntime({}, cpu_num));
const TestCase &test_case = GetParam();
std::vector<Tensor> tensor_slice_dataset_tensors;
TF_ASSERT_OK(CreateTensorSliceDatasetTensors(test_case.input_tensors,
&tensor_slice_dataset_tensors));
gtl::InlinedVector<TensorValue, 4> inputs;
for (auto &tensor : tensor_slice_dataset_tensors) {
inputs.emplace_back(&tensor);
}
std::unique_ptr<OpKernel> dataset_kernel;
TF_ASSERT_OK(CreateConcatenateDatasetKernel(test_case.expected_output_dtypes,
test_case.expected_output_shapes,
&dataset_kernel));
std::unique_ptr<OpKernelContext> dataset_kernel_ctx;
TF_ASSERT_OK(CreateConcatenateDatasetContext(dataset_kernel.get(), &inputs,
&dataset_kernel_ctx));
DatasetBase *concatenate_dataset;
TF_ASSERT_OK(CreateDataset(dataset_kernel.get(), dataset_kernel_ctx.get(),
&concatenate_dataset));
core::ScopedUnref scoped_unref(concatenate_dataset);
std::unique_ptr<IteratorContext> iterator_ctx;
TF_ASSERT_OK(CreateIteratorContext(dataset_kernel_ctx.get(), &iterator_ctx));
std::unique_ptr<IteratorBase> iterator;
TF_ASSERT_OK(concatenate_dataset->MakeIterator(iterator_ctx.get(), "Iterator",
&iterator));
std::unique_ptr<SerializationContext> serialization_ctx;
TF_ASSERT_OK(CreateSerializationContext(&serialization_ctx));
bool end_of_sequence = false;
std::vector<Tensor> out_tensors;
int cur_iteration = 0;
auto expected_outputs_it = test_case.expected_outputs.begin();
std::vector<int> breakpoints = GetParam().breakpoints;
for (int breakpoint : breakpoints) {
VariantTensorData data;
VariantTensorDataWriter writer(&data);
TF_EXPECT_OK(iterator->Save(serialization_ctx.get(), &writer));
TF_EXPECT_OK(writer.Flush());
VariantTensorDataReader reader(&data);
TF_EXPECT_OK(RestoreIterator(iterator_ctx.get(), &reader, "Iterator",
*concatenate_dataset, &iterator));
while (cur_iteration < breakpoint) {
TF_EXPECT_OK(iterator->GetNext(iterator_ctx.get(), &out_tensors,
&end_of_sequence));
if (!end_of_sequence) {
for (auto &tensor : out_tensors) {
EXPECT_NE(expected_outputs_it, test_case.expected_outputs.end());
TF_EXPECT_OK(ExpectEqual(tensor, *expected_outputs_it));
expected_outputs_it++;
}
}
cur_iteration++;
}
if (breakpoint >= concatenate_dataset->Cardinality()) {
EXPECT_TRUE(end_of_sequence);
EXPECT_EQ(expected_outputs_it, test_case.expected_outputs.end());
} else {
EXPECT_FALSE(end_of_sequence);
}
}
}
INSTANTIATE_TEST_SUITE_P(ConcatenateDatasetOpTest,
ParameterizedConcatenateDatasetOpTest,
::testing::ValuesIn(std::vector<TestCase>(
{SameShapeTestCase(), DifferentShapeTestCase()})));
} // namespace
} // namespace data
} // namespace tensorflow