| /* 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/skip_dataset_op.h" |
| |
| #include "tensorflow/core/kernels/data/dataset_test_base.h" |
| |
| namespace tensorflow { |
| namespace data { |
| namespace { |
| |
| constexpr char kNodeName[] = "skip_dataset"; |
| |
| class SkipDatasetOpTest : public DatasetOpsTestBase { |
| protected: |
| // Create `TensorSliceDataset` variant tensor from the input vector of |
| // tensors. |
| Status CreateTensorSliceDatasetTensor( |
| std::vector<Tensor> *const tensor_vector, Tensor *dataset_tensor) { |
| DatasetBase *tensor_slice_dataset; |
| TF_RETURN_IF_ERROR(CreateTensorSliceDataset( |
| "tensor_slice_node", tensor_vector, &tensor_slice_dataset)); |
| TF_RETURN_IF_ERROR( |
| StoreDatasetInVariantTensor(tensor_slice_dataset, dataset_tensor)); |
| return Status::OK(); |
| } |
| |
| // Creates a new `SkipDataset` op kernel. |
| Status CreateSkipDatasetKernel( |
| const DataTypeVector &output_types, |
| const std::vector<PartialTensorShape> &output_shapes, |
| std::unique_ptr<OpKernel> *op_kernel) { |
| NodeDef node_def = test::function::NDef( |
| kNodeName, name_utils::OpName(SkipDatasetOp::kDatasetType), |
| {SkipDatasetOp::kInputDataset, SkipDatasetOp::kCount}, |
| {{SkipDatasetOp::kOutputTypes, output_types}, |
| {SkipDatasetOp::kOutputShapes, output_shapes}}); |
| TF_RETURN_IF_ERROR(CreateOpKernel(node_def, op_kernel)); |
| return Status::OK(); |
| } |
| |
| // Create a new `SkipDataset` op kernel context. |
| Status CreateSkipDatasetContext( |
| OpKernel *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<Tensor> input_tensors; |
| int64 count; |
| 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: skip fewer than input size. |
| TestCase SkipLessTestCase() { |
| return { |
| /*input_tensors*/ |
| {CreateTensor<int64>(TensorShape{10, 1}, {0, 1, 2, 3, 4, 5, 6, 7, 8, 9})}, |
| /*count*/ 4, |
| /*expected_outputs*/ |
| {CreateTensor<int64>(TensorShape{1}, {4}), |
| CreateTensor<int64>(TensorShape{1}, {5}), |
| CreateTensor<int64>(TensorShape{1}, {6}), |
| CreateTensor<int64>(TensorShape{1}, {7}), |
| CreateTensor<int64>(TensorShape{1}, {8}), |
| CreateTensor<int64>(TensorShape{1}, {9})}, |
| /*expected_output_dtypes*/ {DT_INT64}, |
| /*expected_output_shapes*/ {PartialTensorShape({1})}, |
| /*expected_cardinality*/ 6, |
| /*breakpoints*/ {0, 2, 7}}; |
| } |
| |
| // Test case 2: skip more than input size. |
| TestCase SkipMoreTestCase() { |
| return { |
| /*input_tensors*/ |
| {CreateTensor<int64>(TensorShape{10, 1}, {0, 1, 2, 3, 4, 5, 6, 7, 8, 9})}, |
| /*count*/ 25, |
| /*expected_outputs*/ {}, |
| /*expected_output_dtypes*/ {DT_INT64}, |
| /*expected_output_shapes*/ {PartialTensorShape({1})}, |
| /*expected_cardinality*/ 0, |
| /*breakpoints*/ {0, 2, 5}}; |
| } |
| |
| // Test case 3: skip exactly the input size. |
| TestCase SkipAllTestCase() { |
| return { |
| /*input_tensors*/ |
| {CreateTensor<int64>(TensorShape{10, 1}, {0, 1, 2, 3, 4, 5, 6, 7, 8, 9})}, |
| /*count*/ 10, |
| /*expected_outputs*/ {}, |
| /*expected_output_dtypes*/ {DT_INT64}, |
| /*expected_output_shapes*/ {PartialTensorShape({1})}, |
| /*expected_cardinality*/ 0, |
| /*breakpoints*/ {0, 2, 5}}; |
| } |
| |
| // Test case 4: skip nothing. |
| TestCase SkipNothingTestCase() { |
| return { |
| /*input_tensors*/ |
| {CreateTensor<int64>(TensorShape{10, 1}, {0, 1, 2, 3, 4, 5, 6, 7, 8, 9})}, |
| /*count*/ 0, |
| /*expected_outputs*/ |
| {CreateTensor<int64>(TensorShape{1}, {0}), |
| CreateTensor<int64>(TensorShape{1}, {1}), |
| CreateTensor<int64>(TensorShape{1}, {2}), |
| CreateTensor<int64>(TensorShape{1}, {3}), |
| CreateTensor<int64>(TensorShape{1}, {4}), |
| CreateTensor<int64>(TensorShape{1}, {5}), |
| CreateTensor<int64>(TensorShape{1}, {6}), |
| CreateTensor<int64>(TensorShape{1}, {7}), |
| CreateTensor<int64>(TensorShape{1}, {8}), |
| CreateTensor<int64>(TensorShape{1}, {9})}, |
| /*expected_output_dtypes*/ {DT_INT64}, |
| /*expected_output_shapes*/ {PartialTensorShape({1})}, |
| /*expected_cardinality*/ 10, |
| /*breakpoints*/ {0, 2, 5, 11}}; |
| } |
| |
| // Test case 5: set -1 for `count` to skip the entire dataset. |
| TestCase SkipEntireDatasetTestCase() { |
| return { |
| /*input_tensors*/ |
| {CreateTensor<int64>(TensorShape{10, 1}, {0, 1, 2, 3, 4, 5, 6, 7, 8, 9})}, |
| /*count*/ -1, |
| /*expected_outputs*/ {}, |
| /*expected_output_dtypes*/ {DT_INT64}, |
| /*expected_output_shapes*/ {PartialTensorShape({1})}, |
| /*expected_cardinality*/ 0, |
| /*breakpoints*/ {0, 2, 5}}; |
| } |
| |
| class ParameterizedSkipDatasetOpTest |
| : public SkipDatasetOpTest, |
| public ::testing::WithParamInterface<TestCase> {}; |
| |
| TEST_P(ParameterizedSkipDatasetOpTest, 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(); |
| Tensor tensor_slice_dataset_tensor(DT_VARIANT, TensorShape({})); |
| std::vector<Tensor> inputs_for_tensor_slice_dataset = test_case.input_tensors; |
| TF_ASSERT_OK(CreateTensorSliceDatasetTensor(&inputs_for_tensor_slice_dataset, |
| &tensor_slice_dataset_tensor)); |
| Tensor count = CreateTensor<int64>(TensorShape{}, {test_case.count}); |
| gtl::InlinedVector<TensorValue, 4> inputs_for_skip_dataset( |
| {TensorValue(&tensor_slice_dataset_tensor), TensorValue(&count)}); |
| |
| std::unique_ptr<OpKernel> skip_dataset_kernel; |
| TF_ASSERT_OK(CreateSkipDatasetKernel(test_case.expected_output_dtypes, |
| test_case.expected_output_shapes, |
| &skip_dataset_kernel)); |
| std::unique_ptr<OpKernelContext> skip_dataset_context; |
| TF_ASSERT_OK(CreateSkipDatasetContext(skip_dataset_kernel.get(), |
| &inputs_for_skip_dataset, |
| &skip_dataset_context)); |
| DatasetBase *skip_dataset; |
| TF_ASSERT_OK(CreateDataset(skip_dataset_kernel.get(), |
| skip_dataset_context.get(), &skip_dataset)); |
| core::ScopedUnref scoped_unref(skip_dataset); |
| |
| std::unique_ptr<IteratorContext> iterator_ctx; |
| TF_ASSERT_OK( |
| CreateIteratorContext(skip_dataset_context.get(), &iterator_ctx)); |
| std::unique_ptr<IteratorBase> iterator; |
| TF_ASSERT_OK( |
| skip_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(SkipDatasetOpTest, DatasetNodeName) { |
| int thread_num = 2, cpu_num = 2; |
| TF_ASSERT_OK(InitThreadPool(thread_num)); |
| TF_ASSERT_OK(InitFunctionLibraryRuntime({}, cpu_num)); |
| |
| const TestCase &test_case = SkipLessTestCase(); |
| Tensor tensor_slice_dataset_tensor(DT_VARIANT, TensorShape({})); |
| std::vector<Tensor> inputs_for_tensor_slice_dataset = test_case.input_tensors; |
| TF_ASSERT_OK(CreateTensorSliceDatasetTensor(&inputs_for_tensor_slice_dataset, |
| &tensor_slice_dataset_tensor)); |
| Tensor count = CreateTensor<int64>(TensorShape{}, {test_case.count}); |
| gtl::InlinedVector<TensorValue, 4> inputs_for_skip_dataset( |
| {TensorValue(&tensor_slice_dataset_tensor), TensorValue(&count)}); |
| |
| std::unique_ptr<OpKernel> skip_dataset_kernel; |
| TF_ASSERT_OK(CreateSkipDatasetKernel(test_case.expected_output_dtypes, |
| test_case.expected_output_shapes, |
| &skip_dataset_kernel)); |
| std::unique_ptr<OpKernelContext> skip_dataset_context; |
| TF_ASSERT_OK(CreateSkipDatasetContext(skip_dataset_kernel.get(), |
| &inputs_for_skip_dataset, |
| &skip_dataset_context)); |
| DatasetBase *skip_dataset; |
| TF_ASSERT_OK(CreateDataset(skip_dataset_kernel.get(), |
| skip_dataset_context.get(), &skip_dataset)); |
| core::ScopedUnref scoped_unref(skip_dataset); |
| |
| EXPECT_EQ(skip_dataset->node_name(), kNodeName); |
| } |
| |
| TEST_F(SkipDatasetOpTest, DatasetTypeString) { |
| int thread_num = 2, cpu_num = 2; |
| TF_ASSERT_OK(InitThreadPool(thread_num)); |
| TF_ASSERT_OK(InitFunctionLibraryRuntime({}, cpu_num)); |
| |
| const TestCase &test_case = SkipLessTestCase(); |
| Tensor tensor_slice_dataset_tensor(DT_VARIANT, TensorShape({})); |
| std::vector<Tensor> inputs_for_tensor_slice_dataset = test_case.input_tensors; |
| TF_ASSERT_OK(CreateTensorSliceDatasetTensor(&inputs_for_tensor_slice_dataset, |
| &tensor_slice_dataset_tensor)); |
| Tensor count = CreateTensor<int64>(TensorShape{}, {test_case.count}); |
| gtl::InlinedVector<TensorValue, 4> inputs_for_skip_dataset( |
| {TensorValue(&tensor_slice_dataset_tensor), TensorValue(&count)}); |
| |
| std::unique_ptr<OpKernel> skip_dataset_kernel; |
| TF_ASSERT_OK(CreateSkipDatasetKernel(test_case.expected_output_dtypes, |
| test_case.expected_output_shapes, |
| &skip_dataset_kernel)); |
| std::unique_ptr<OpKernelContext> skip_dataset_context; |
| TF_ASSERT_OK(CreateSkipDatasetContext(skip_dataset_kernel.get(), |
| &inputs_for_skip_dataset, |
| &skip_dataset_context)); |
| DatasetBase *skip_dataset; |
| TF_ASSERT_OK(CreateDataset(skip_dataset_kernel.get(), |
| skip_dataset_context.get(), &skip_dataset)); |
| core::ScopedUnref scoped_unref(skip_dataset); |
| |
| EXPECT_EQ(skip_dataset->type_string(), |
| name_utils::OpName(SkipDatasetOp::kDatasetType)); |
| } |
| |
| TEST_F(SkipDatasetOpTest, DatasetOutputDtypes) { |
| int thread_num = 2, cpu_num = 2; |
| TF_ASSERT_OK(InitThreadPool(thread_num)); |
| TF_ASSERT_OK(InitFunctionLibraryRuntime({}, cpu_num)); |
| |
| const TestCase &test_case = SkipLessTestCase(); |
| Tensor tensor_slice_dataset_tensor(DT_VARIANT, TensorShape({})); |
| std::vector<Tensor> inputs_for_tensor_slice_dataset = test_case.input_tensors; |
| TF_ASSERT_OK(CreateTensorSliceDatasetTensor(&inputs_for_tensor_slice_dataset, |
| &tensor_slice_dataset_tensor)); |
| Tensor count = CreateTensor<int64>(TensorShape{}, {test_case.count}); |
| gtl::InlinedVector<TensorValue, 4> inputs_for_skip_dataset( |
| {TensorValue(&tensor_slice_dataset_tensor), TensorValue(&count)}); |
| |
| std::unique_ptr<OpKernel> skip_dataset_kernel; |
| TF_ASSERT_OK(CreateSkipDatasetKernel(test_case.expected_output_dtypes, |
| test_case.expected_output_shapes, |
| &skip_dataset_kernel)); |
| std::unique_ptr<OpKernelContext> skip_dataset_context; |
| TF_ASSERT_OK(CreateSkipDatasetContext(skip_dataset_kernel.get(), |
| &inputs_for_skip_dataset, |
| &skip_dataset_context)); |
| DatasetBase *skip_dataset; |
| TF_ASSERT_OK(CreateDataset(skip_dataset_kernel.get(), |
| skip_dataset_context.get(), &skip_dataset)); |
| core::ScopedUnref scoped_unref(skip_dataset); |
| |
| TF_EXPECT_OK(VerifyTypesMatch(skip_dataset->output_dtypes(), |
| test_case.expected_output_dtypes)); |
| } |
| |
| TEST_F(SkipDatasetOpTest, DatasetOutputShapes) { |
| int thread_num = 2, cpu_num = 2; |
| TF_ASSERT_OK(InitThreadPool(thread_num)); |
| TF_ASSERT_OK(InitFunctionLibraryRuntime({}, cpu_num)); |
| |
| const TestCase &test_case = SkipLessTestCase(); |
| Tensor tensor_slice_dataset_tensor(DT_VARIANT, TensorShape({})); |
| std::vector<Tensor> inputs_for_tensor_slice_dataset = test_case.input_tensors; |
| TF_ASSERT_OK(CreateTensorSliceDatasetTensor(&inputs_for_tensor_slice_dataset, |
| &tensor_slice_dataset_tensor)); |
| Tensor count = CreateTensor<int64>(TensorShape{}, {test_case.count}); |
| gtl::InlinedVector<TensorValue, 4> inputs_for_skip_dataset( |
| {TensorValue(&tensor_slice_dataset_tensor), TensorValue(&count)}); |
| |
| std::unique_ptr<OpKernel> skip_dataset_kernel; |
| TF_ASSERT_OK(CreateSkipDatasetKernel(test_case.expected_output_dtypes, |
| test_case.expected_output_shapes, |
| &skip_dataset_kernel)); |
| std::unique_ptr<OpKernelContext> skip_dataset_context; |
| TF_ASSERT_OK(CreateSkipDatasetContext(skip_dataset_kernel.get(), |
| &inputs_for_skip_dataset, |
| &skip_dataset_context)); |
| DatasetBase *skip_dataset; |
| TF_ASSERT_OK(CreateDataset(skip_dataset_kernel.get(), |
| skip_dataset_context.get(), &skip_dataset)); |
| core::ScopedUnref scoped_unref(skip_dataset); |
| |
| TF_EXPECT_OK(VerifyShapesCompatible(skip_dataset->output_shapes(), |
| test_case.expected_output_shapes)); |
| } |
| |
| TEST_P(ParameterizedSkipDatasetOpTest, 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(); |
| Tensor tensor_slice_dataset_tensor(DT_VARIANT, TensorShape({})); |
| std::vector<Tensor> inputs_for_tensor_slice_dataset = test_case.input_tensors; |
| TF_ASSERT_OK(CreateTensorSliceDatasetTensor(&inputs_for_tensor_slice_dataset, |
| &tensor_slice_dataset_tensor)); |
| Tensor count = CreateTensor<int64>(TensorShape{}, {test_case.count}); |
| gtl::InlinedVector<TensorValue, 4> inputs_for_skip_dataset( |
| {TensorValue(&tensor_slice_dataset_tensor), TensorValue(&count)}); |
| |
| std::unique_ptr<OpKernel> skip_dataset_kernel; |
| TF_ASSERT_OK(CreateSkipDatasetKernel(test_case.expected_output_dtypes, |
| test_case.expected_output_shapes, |
| &skip_dataset_kernel)); |
| std::unique_ptr<OpKernelContext> skip_dataset_context; |
| TF_ASSERT_OK(CreateSkipDatasetContext(skip_dataset_kernel.get(), |
| &inputs_for_skip_dataset, |
| &skip_dataset_context)); |
| DatasetBase *skip_dataset; |
| TF_ASSERT_OK(CreateDataset(skip_dataset_kernel.get(), |
| skip_dataset_context.get(), &skip_dataset)); |
| core::ScopedUnref scoped_unref(skip_dataset); |
| |
| EXPECT_EQ(skip_dataset->Cardinality(), test_case.expected_cardinality); |
| } |
| |
| TEST_P(ParameterizedSkipDatasetOpTest, 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(); |
| Tensor tensor_slice_dataset_tensor(DT_VARIANT, TensorShape({})); |
| std::vector<Tensor> inputs_for_tensor_slice_dataset = test_case.input_tensors; |
| TF_ASSERT_OK(CreateTensorSliceDatasetTensor(&inputs_for_tensor_slice_dataset, |
| &tensor_slice_dataset_tensor)); |
| Tensor count = CreateTensor<int64>(TensorShape{}, {test_case.count}); |
| gtl::InlinedVector<TensorValue, 4> inputs_for_skip_dataset( |
| {TensorValue(&tensor_slice_dataset_tensor), TensorValue(&count)}); |
| |
| std::unique_ptr<OpKernel> skip_dataset_kernel; |
| TF_ASSERT_OK(CreateSkipDatasetKernel(test_case.expected_output_dtypes, |
| test_case.expected_output_shapes, |
| &skip_dataset_kernel)); |
| std::unique_ptr<OpKernelContext> skip_dataset_context; |
| TF_ASSERT_OK(CreateSkipDatasetContext(skip_dataset_kernel.get(), |
| &inputs_for_skip_dataset, |
| &skip_dataset_context)); |
| DatasetBase *skip_dataset; |
| TF_ASSERT_OK(CreateDataset(skip_dataset_kernel.get(), |
| skip_dataset_context.get(), &skip_dataset)); |
| core::ScopedUnref scoped_unref(skip_dataset); |
| |
| std::unique_ptr<IteratorContext> iterator_ctx; |
| TF_ASSERT_OK( |
| CreateIteratorContext(skip_dataset_context.get(), &iterator_ctx)); |
| std::unique_ptr<IteratorBase> iterator; |
| TF_ASSERT_OK( |
| skip_dataset->MakeIterator(iterator_ctx.get(), "Iterator", &iterator)); |
| |
| TF_EXPECT_OK(VerifyTypesMatch(iterator->output_dtypes(), |
| test_case.expected_output_dtypes)); |
| } |
| |
| TEST_P(ParameterizedSkipDatasetOpTest, 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(); |
| Tensor tensor_slice_dataset_tensor(DT_VARIANT, TensorShape({})); |
| std::vector<Tensor> inputs_for_tensor_slice_dataset = test_case.input_tensors; |
| TF_ASSERT_OK(CreateTensorSliceDatasetTensor(&inputs_for_tensor_slice_dataset, |
| &tensor_slice_dataset_tensor)); |
| Tensor count = CreateTensor<int64>(TensorShape{}, {test_case.count}); |
| gtl::InlinedVector<TensorValue, 4> inputs_for_skip_dataset( |
| {TensorValue(&tensor_slice_dataset_tensor), TensorValue(&count)}); |
| |
| std::unique_ptr<OpKernel> skip_dataset_kernel; |
| TF_ASSERT_OK(CreateSkipDatasetKernel(test_case.expected_output_dtypes, |
| test_case.expected_output_shapes, |
| &skip_dataset_kernel)); |
| std::unique_ptr<OpKernelContext> skip_dataset_context; |
| TF_ASSERT_OK(CreateSkipDatasetContext(skip_dataset_kernel.get(), |
| &inputs_for_skip_dataset, |
| &skip_dataset_context)); |
| DatasetBase *skip_dataset; |
| TF_ASSERT_OK(CreateDataset(skip_dataset_kernel.get(), |
| skip_dataset_context.get(), &skip_dataset)); |
| core::ScopedUnref scoped_unref(skip_dataset); |
| |
| std::unique_ptr<IteratorContext> iterator_ctx; |
| TF_ASSERT_OK( |
| CreateIteratorContext(skip_dataset_context.get(), &iterator_ctx)); |
| std::unique_ptr<IteratorBase> iterator; |
| TF_ASSERT_OK( |
| skip_dataset->MakeIterator(iterator_ctx.get(), "Iterator", &iterator)); |
| |
| TF_EXPECT_OK(VerifyShapesCompatible(iterator->output_shapes(), |
| test_case.expected_output_shapes)); |
| } |
| |
| TEST_P(ParameterizedSkipDatasetOpTest, IteratorOutputPrefix) { |
| int thread_num = 2, cpu_num = 2; |
| TF_ASSERT_OK(InitThreadPool(thread_num)); |
| TF_ASSERT_OK(InitFunctionLibraryRuntime({}, cpu_num)); |
| |
| const TestCase &test_case = GetParam(); |
| Tensor tensor_slice_dataset_tensor(DT_VARIANT, TensorShape({})); |
| std::vector<Tensor> inputs_for_tensor_slice_dataset = test_case.input_tensors; |
| TF_ASSERT_OK(CreateTensorSliceDatasetTensor(&inputs_for_tensor_slice_dataset, |
| &tensor_slice_dataset_tensor)); |
| Tensor count = CreateTensor<int64>(TensorShape{}, {test_case.count}); |
| gtl::InlinedVector<TensorValue, 4> inputs_for_skip_dataset( |
| {TensorValue(&tensor_slice_dataset_tensor), TensorValue(&count)}); |
| |
| std::unique_ptr<OpKernel> skip_dataset_kernel; |
| TF_ASSERT_OK(CreateSkipDatasetKernel(test_case.expected_output_dtypes, |
| test_case.expected_output_shapes, |
| &skip_dataset_kernel)); |
| std::unique_ptr<OpKernelContext> skip_dataset_context; |
| TF_ASSERT_OK(CreateSkipDatasetContext(skip_dataset_kernel.get(), |
| &inputs_for_skip_dataset, |
| &skip_dataset_context)); |
| DatasetBase *skip_dataset; |
| TF_ASSERT_OK(CreateDataset(skip_dataset_kernel.get(), |
| skip_dataset_context.get(), &skip_dataset)); |
| core::ScopedUnref scoped_unref(skip_dataset); |
| |
| std::unique_ptr<IteratorContext> iterator_ctx; |
| TF_ASSERT_OK( |
| CreateIteratorContext(skip_dataset_context.get(), &iterator_ctx)); |
| std::unique_ptr<IteratorBase> iterator; |
| TF_ASSERT_OK( |
| skip_dataset->MakeIterator(iterator_ctx.get(), "Iterator", &iterator)); |
| |
| if (test_case.count < 0) { |
| EXPECT_EQ(iterator->prefix(), |
| name_utils::IteratorPrefix("EmptySkip", "Iterator")); |
| } else { |
| EXPECT_EQ(iterator->prefix(), |
| name_utils::IteratorPrefix("FiniteSkip", "Iterator")); |
| } |
| } |
| |
| TEST_P(ParameterizedSkipDatasetOpTest, 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(); |
| Tensor tensor_slice_dataset_tensor(DT_VARIANT, TensorShape({})); |
| std::vector<Tensor> inputs_for_tensor_slice_dataset = test_case.input_tensors; |
| TF_ASSERT_OK(CreateTensorSliceDatasetTensor(&inputs_for_tensor_slice_dataset, |
| &tensor_slice_dataset_tensor)); |
| Tensor count = CreateTensor<int64>(TensorShape{}, {test_case.count}); |
| gtl::InlinedVector<TensorValue, 4> inputs_for_skip_dataset( |
| {TensorValue(&tensor_slice_dataset_tensor), TensorValue(&count)}); |
| |
| std::unique_ptr<OpKernel> skip_dataset_kernel; |
| TF_ASSERT_OK(CreateSkipDatasetKernel(test_case.expected_output_dtypes, |
| test_case.expected_output_shapes, |
| &skip_dataset_kernel)); |
| std::unique_ptr<OpKernelContext> skip_dataset_context; |
| TF_ASSERT_OK(CreateSkipDatasetContext(skip_dataset_kernel.get(), |
| &inputs_for_skip_dataset, |
| &skip_dataset_context)); |
| DatasetBase *skip_dataset; |
| TF_ASSERT_OK(CreateDataset(skip_dataset_kernel.get(), |
| skip_dataset_context.get(), &skip_dataset)); |
| core::ScopedUnref scoped_unref(skip_dataset); |
| |
| std::unique_ptr<IteratorContext> iterator_ctx; |
| TF_ASSERT_OK( |
| CreateIteratorContext(skip_dataset_context.get(), &iterator_ctx)); |
| std::unique_ptr<IteratorBase> iterator; |
| TF_ASSERT_OK( |
| skip_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(); |
| const std::vector<int> &breakpoints = test_case.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", |
| *skip_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 >= test_case.expected_outputs.size()) { |
| 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(SkipDatasetOpTest, ParameterizedSkipDatasetOpTest, |
| ::testing::ValuesIn(std::vector<TestCase>( |
| {SkipLessTestCase(), SkipMoreTestCase(), |
| SkipAllTestCase(), SkipNothingTestCase(), |
| SkipEntireDatasetTestCase()}))); |
| |
| } // namespace |
| } // namespace data |
| } // namespace tensorflow |