| /* 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/batch_dataset_op.h" |
| |
| #include "tensorflow/core/kernels/data/dataset_test_base.h" |
| |
| namespace tensorflow { |
| namespace data { |
| namespace { |
| |
| constexpr char kNodeName[] = "batch_dataset_v2"; |
| constexpr int kOpVersion = 2; |
| |
| class BatchDatasetOpTest : public DatasetOpsTestBase { |
| protected: |
| // Creates a new `BatchDataset` op kernel. |
| Status CreateBatchDatasetOpKernel( |
| bool parallel_copy, const DataTypeVector& output_types, |
| const std::vector<PartialTensorShape>& output_shapes, |
| std::unique_ptr<OpKernel>* batch_dataset_op_kernel) { |
| name_utils::OpNameParams params; |
| params.op_version = kOpVersion; |
| NodeDef node_def = test::function::NDef( |
| kNodeName, name_utils::OpName(BatchDatasetOp::kDatasetType, params), |
| {BatchDatasetOp::kInputDataset, BatchDatasetOp::kBatchSize, |
| BatchDatasetOp::kDropRemainder}, |
| {{BatchDatasetOp::kParallelCopy, parallel_copy}, |
| {BatchDatasetOp::kOutputTypes, output_types}, |
| {BatchDatasetOp::kOutputShapes, output_shapes}}); |
| TF_RETURN_IF_ERROR(CreateOpKernel(node_def, batch_dataset_op_kernel)); |
| return Status::OK(); |
| } |
| |
| // Create a new `BatchDataset` op kernel context |
| Status CreateBatchDatasetContext( |
| 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 RangeDatasetParam { |
| int64 start; |
| int64 end; |
| int64 step; |
| }; |
| |
| struct TestCase { |
| RangeDatasetParam range_dataset_param; |
| Tensor batch_size; |
| Tensor drop_remainder; |
| bool parallel_copy; |
| 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: test BatchDatasetV2 with `drop_remainder` = false and a batch |
| // size that can evenly split the input dataset. |
| TestCase TestCase1() { |
| return {/*range_data_param*/ {0, 12, 1}, |
| /*batch_size*/ |
| CreateTensor<int64>(TensorShape({}), {4}), |
| /*drop_remainder*/ |
| CreateTensor<bool>(TensorShape({}), {false}), |
| /*parallel_copy*/ true, |
| /*expected_outputs*/ |
| {CreateTensor<int64>(TensorShape({4}), {0, 1, 2, 3}), |
| CreateTensor<int64>(TensorShape({4}), {4, 5, 6, 7}), |
| CreateTensor<int64>(TensorShape({4}), {8, 9, 10, 11})}, |
| /*expected_output_dtypes*/ {DT_INT64}, |
| /*expected_output_shapes*/ {PartialTensorShape({4})}, |
| /*expected_cardinality*/ 3, |
| /*breakpoints*/ {0, 1, 5}}; |
| } |
| |
| // Test Case 2: test BatchDatasetV2 with `drop_remainder` = true and a batch |
| // size that can evenly split the input dataset. |
| TestCase TestCase2() { |
| return {/*range_data_param*/ {0, 12, 1}, |
| /*batch_size*/ |
| CreateTensor<int64>(TensorShape({}), {4}), |
| /*drop_remainder*/ |
| CreateTensor<bool>(TensorShape({}), {true}), |
| /*parallel_copy*/ false, |
| /*expected_outputs*/ |
| {CreateTensor<int64>(TensorShape({4}), {0, 1, 2, 3}), |
| CreateTensor<int64>(TensorShape({4}), {4, 5, 6, 7}), |
| CreateTensor<int64>(TensorShape({4}), {8, 9, 10, 11})}, |
| /*expected_output_dtypes*/ {DT_INT64}, |
| /*expected_output_shapes*/ {PartialTensorShape({4})}, |
| /*expected_cardinality*/ 3, |
| /*breakpoints*/ {0, 1, 5}}; |
| } |
| |
| // Test Case 3: test BatchDatasetV2 with `drop_remainder` = false and a batch |
| // size that can not evenly split the input dataset. |
| TestCase TestCase3() { |
| return {/*range_data_param*/ {0, 10, 1}, |
| /*batch_size*/ |
| CreateTensor<int64>(TensorShape({}), {3}), |
| /*drop_remainder*/ |
| CreateTensor<bool>(TensorShape({}), {false}), |
| /*parallel_copy*/ false, |
| /*expected_outputs*/ |
| {CreateTensor<int64>(TensorShape({3}), {0, 1, 2}), |
| CreateTensor<int64>(TensorShape({3}), {3, 4, 5}), |
| CreateTensor<int64>(TensorShape({3}), {6, 7, 8}), |
| CreateTensor<int64>(TensorShape({1}), {9})}, |
| /*expected_output_dtypes*/ {DT_INT64}, |
| /*expected_output_shapes*/ {PartialTensorShape({-1})}, |
| /*expected_cardinality*/ 4, |
| /*breakpoints*/ {0, 1, 5}}; |
| } |
| |
| // Test Case 4: test BatchDatasetV2 with `drop_remainder` = true and a batch |
| // size that can not evenly split the input dataset. |
| TestCase TestCase4() { |
| return {/*range_data_param*/ {0, 10, 1}, |
| /*batch_size*/ |
| CreateTensor<int64>(TensorShape({}), {3}), |
| /*drop_remainder*/ |
| CreateTensor<bool>(TensorShape({}), {true}), |
| /*parallel_copy*/ true, |
| /*expected_outputs*/ |
| {CreateTensor<int64>(TensorShape({3}), {0, 1, 2}), |
| CreateTensor<int64>(TensorShape({3}), {3, 4, 5}), |
| CreateTensor<int64>(TensorShape({3}), {6, 7, 8})}, |
| /*expected_output_dtypes*/ {DT_INT64}, |
| /*expected_output_shapes*/ {PartialTensorShape({3})}, |
| /*expected_cardinality*/ 3, |
| /*breakpoints*/ {0, 1, 5}}; |
| } |
| |
| // Test Case 5: test BatchDatasetV2 with `drop_remainder` = true and |
| // `batch_size` > the cardinality of the input dataset. |
| TestCase TestCase5() { |
| return {/*range_data_param*/ {0, 10, 1}, |
| /*batch_size*/ |
| CreateTensor<int64>(TensorShape({}), {12}), |
| /*drop_remainder*/ |
| CreateTensor<bool>(TensorShape({}), {true}), |
| /*parallel_copy*/ true, |
| /*expected_outputs*/ {}, |
| /*expected_output_dtypes*/ {DT_INT64}, |
| /*expected_output_shapes*/ {PartialTensorShape({12})}, |
| /*expected_cardinality*/ 0, |
| /*breakpoints*/ {0, 1, 5}}; |
| } |
| |
| // Test Case 6: test BatchDatasetV2 with `drop_remainder` = false and |
| // `batch_size` > the cardinality of the input dataset. |
| TestCase TestCase6() { |
| return { |
| /*range_data_param*/ {0, 10, 1}, |
| /*batch_size*/ |
| CreateTensor<int64>(TensorShape({}), {12}), |
| /*drop_remainder*/ |
| CreateTensor<bool>(TensorShape({}), {false}), |
| /*parallel_copy*/ true, |
| /*expected_outputs*/ |
| {CreateTensor<int64>(TensorShape({10}), {0, 1, 2, 3, 4, 5, 6, 7, 8, 9})}, |
| /*expected_output_dtypes*/ {DT_INT64}, |
| /*expected_output_shapes*/ {PartialTensorShape({-1})}, |
| /*expected_cardinality*/ 1, |
| /*breakpoints*/ {0, 1, 5}}; |
| } |
| |
| // Test Case 7: test BatchDatasetV2 with `drop_remainder` = false and |
| // the output of the input dataset is empty. |
| TestCase TestCase7() { |
| return {/*range_data_param*/ {0, 0, 1}, |
| /*batch_size*/ |
| CreateTensor<int64>(TensorShape({}), {4}), |
| /*drop_remainder*/ |
| CreateTensor<bool>(TensorShape({}), {false}), |
| /*parallel_copy*/ false, |
| /*expected_outputs*/ {}, |
| /*expected_output_dtypes*/ {DT_INT64}, |
| /*expected_output_shapes*/ {PartialTensorShape({4})}, |
| /*expected_cardinality*/ 0, |
| /*breakpoints*/ {0, 1, 5}}; |
| } |
| |
| // Test Case 8: test BatchDatasetV2 with an invalid batch size |
| TestCase InvalidBatchSizeTestCase() { |
| return {/*range_data_param*/ {0, 10, 1}, |
| /*batch_size*/ |
| CreateTensor<int64>(TensorShape({}), {-1}), |
| /*drop_remainder*/ |
| CreateTensor<bool>(TensorShape({}), {false}), |
| /*parallel_copy*/ false, |
| /*expected_outputs*/ {}, |
| /*expected_output_dtypes*/ {DT_INT64}, |
| /*expected_output_shapes*/ {PartialTensorShape({3})}, |
| /*expected_cardinality*/ 3, |
| /*breakpoints*/ {0, 1, 5}}; |
| } |
| |
| class ParameterizedBatchDatasetOpTest |
| : public BatchDatasetOpTest, |
| public ::testing::WithParamInterface<TestCase> {}; |
| |
| TEST_P(ParameterizedBatchDatasetOpTest, GetNext) { |
| int thread_num = 2, cpu_num = 2; |
| TestCase test_case = GetParam(); |
| TF_ASSERT_OK(InitThreadPool(thread_num)); |
| TF_ASSERT_OK(InitFunctionLibraryRuntime({}, cpu_num)); |
| |
| std::unique_ptr<OpKernel> batch_dataset_kernel; |
| TF_ASSERT_OK(CreateBatchDatasetOpKernel( |
| test_case.parallel_copy, test_case.expected_output_dtypes, |
| test_case.expected_output_shapes, &batch_dataset_kernel)); |
| |
| DatasetBase* range_dataset; |
| TF_ASSERT_OK(CreateRangeDataset<int64>( |
| test_case.range_dataset_param.start, test_case.range_dataset_param.end, |
| test_case.range_dataset_param.step, "range", &range_dataset)); |
| Tensor range_dataset_tensor(DT_VARIANT, TensorShape({})); |
| TF_ASSERT_OK( |
| StoreDatasetInVariantTensor(range_dataset, &range_dataset_tensor)); |
| |
| Tensor batch_size = test_case.batch_size; |
| Tensor drop_remainder = test_case.drop_remainder; |
| gtl::InlinedVector<TensorValue, 4> inputs{TensorValue(&range_dataset_tensor), |
| TensorValue(&batch_size), |
| TensorValue(&drop_remainder)}; |
| std::unique_ptr<OpKernelContext> batch_dataset_context; |
| TF_ASSERT_OK(CreateBatchDatasetContext(batch_dataset_kernel.get(), &inputs, |
| &batch_dataset_context)); |
| DatasetBase* batch_dataset; |
| TF_ASSERT_OK(CreateDataset(batch_dataset_kernel.get(), |
| batch_dataset_context.get(), &batch_dataset)); |
| core::ScopedUnref scoped_unref_batch_dataset(batch_dataset); |
| |
| std::unique_ptr<IteratorContext> iterator_ctx; |
| TF_ASSERT_OK( |
| CreateIteratorContext(batch_dataset_context.get(), &iterator_ctx)); |
| std::unique_ptr<IteratorBase> iterator; |
| TF_ASSERT_OK( |
| batch_dataset->MakeIterator(iterator_ctx.get(), "Iterator", &iterator)); |
| |
| bool end_of_sequence = false; |
| auto expected_outputs_it = test_case.expected_outputs.begin(); |
| 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) { |
| EXPECT_LT(expected_outputs_it, test_case.expected_outputs.end()); |
| TF_EXPECT_OK(ExpectEqual(out_tensors.back(), *expected_outputs_it)); |
| expected_outputs_it++; |
| } |
| } |
| EXPECT_EQ(expected_outputs_it, test_case.expected_outputs.end()); |
| } |
| |
| TEST_P(ParameterizedBatchDatasetOpTest, DatasetNodeName) { |
| int thread_num = 2, cpu_num = 2; |
| TestCase test_case = GetParam(); |
| TF_ASSERT_OK(InitThreadPool(thread_num)); |
| TF_ASSERT_OK(InitFunctionLibraryRuntime({}, cpu_num)); |
| |
| std::unique_ptr<OpKernel> batch_dataset_kernel; |
| TF_ASSERT_OK(CreateBatchDatasetOpKernel( |
| test_case.parallel_copy, test_case.expected_output_dtypes, |
| test_case.expected_output_shapes, &batch_dataset_kernel)); |
| |
| DatasetBase* range_dataset; |
| TF_ASSERT_OK(CreateRangeDataset<int64>( |
| test_case.range_dataset_param.start, test_case.range_dataset_param.end, |
| test_case.range_dataset_param.step, "range", &range_dataset)); |
| Tensor range_dataset_tensor(DT_VARIANT, TensorShape({})); |
| TF_ASSERT_OK( |
| StoreDatasetInVariantTensor(range_dataset, &range_dataset_tensor)); |
| |
| Tensor batch_size = test_case.batch_size; |
| Tensor drop_remainder = test_case.drop_remainder; |
| gtl::InlinedVector<TensorValue, 4> inputs{TensorValue(&range_dataset_tensor), |
| TensorValue(&batch_size), |
| TensorValue(&drop_remainder)}; |
| std::unique_ptr<OpKernelContext> batch_dataset_context; |
| TF_ASSERT_OK(CreateBatchDatasetContext(batch_dataset_kernel.get(), &inputs, |
| &batch_dataset_context)); |
| DatasetBase* batch_dataset; |
| TF_ASSERT_OK(CreateDataset(batch_dataset_kernel.get(), |
| batch_dataset_context.get(), &batch_dataset)); |
| core::ScopedUnref scoped_unref_batch_dataset(batch_dataset); |
| |
| EXPECT_EQ(batch_dataset->node_name(), kNodeName); |
| } |
| |
| TEST_P(ParameterizedBatchDatasetOpTest, DatasetTypeString) { |
| int thread_num = 2, cpu_num = 2; |
| TestCase test_case = GetParam(); |
| TF_ASSERT_OK(InitThreadPool(thread_num)); |
| TF_ASSERT_OK(InitFunctionLibraryRuntime({}, cpu_num)); |
| |
| std::unique_ptr<OpKernel> batch_dataset_kernel; |
| TF_ASSERT_OK(CreateBatchDatasetOpKernel( |
| test_case.parallel_copy, test_case.expected_output_dtypes, |
| test_case.expected_output_shapes, &batch_dataset_kernel)); |
| |
| DatasetBase* range_dataset; |
| TF_ASSERT_OK(CreateRangeDataset<int64>( |
| test_case.range_dataset_param.start, test_case.range_dataset_param.end, |
| test_case.range_dataset_param.step, "range", &range_dataset)); |
| Tensor range_dataset_tensor(DT_VARIANT, TensorShape({})); |
| TF_ASSERT_OK( |
| StoreDatasetInVariantTensor(range_dataset, &range_dataset_tensor)); |
| |
| Tensor batch_size = test_case.batch_size; |
| Tensor drop_remainder = test_case.drop_remainder; |
| gtl::InlinedVector<TensorValue, 4> inputs{TensorValue(&range_dataset_tensor), |
| TensorValue(&batch_size), |
| TensorValue(&drop_remainder)}; |
| std::unique_ptr<OpKernelContext> batch_dataset_context; |
| TF_ASSERT_OK(CreateBatchDatasetContext(batch_dataset_kernel.get(), &inputs, |
| &batch_dataset_context)); |
| DatasetBase* batch_dataset; |
| TF_ASSERT_OK(CreateDataset(batch_dataset_kernel.get(), |
| batch_dataset_context.get(), &batch_dataset)); |
| core::ScopedUnref scoped_unref_batch_dataset(batch_dataset); |
| |
| name_utils::OpNameParams params; |
| params.op_version = kOpVersion; |
| EXPECT_EQ(batch_dataset->type_string(), |
| name_utils::OpName(BatchDatasetOp::kDatasetType, params)); |
| } |
| |
| TEST_P(ParameterizedBatchDatasetOpTest, DatasetOutputDtypes) { |
| int thread_num = 2, cpu_num = 2; |
| TestCase test_case = GetParam(); |
| TF_ASSERT_OK(InitThreadPool(thread_num)); |
| TF_ASSERT_OK(InitFunctionLibraryRuntime({}, cpu_num)); |
| |
| std::unique_ptr<OpKernel> batch_dataset_kernel; |
| TF_ASSERT_OK(CreateBatchDatasetOpKernel( |
| test_case.parallel_copy, test_case.expected_output_dtypes, |
| test_case.expected_output_shapes, &batch_dataset_kernel)); |
| |
| DatasetBase* range_dataset; |
| TF_ASSERT_OK(CreateRangeDataset<int64>( |
| test_case.range_dataset_param.start, test_case.range_dataset_param.end, |
| test_case.range_dataset_param.step, "range", &range_dataset)); |
| Tensor range_dataset_tensor(DT_VARIANT, TensorShape({})); |
| TF_ASSERT_OK( |
| StoreDatasetInVariantTensor(range_dataset, &range_dataset_tensor)); |
| |
| Tensor batch_size = test_case.batch_size; |
| Tensor drop_remainder = test_case.drop_remainder; |
| gtl::InlinedVector<TensorValue, 4> inputs{TensorValue(&range_dataset_tensor), |
| TensorValue(&batch_size), |
| TensorValue(&drop_remainder)}; |
| std::unique_ptr<OpKernelContext> batch_dataset_context; |
| TF_ASSERT_OK(CreateBatchDatasetContext(batch_dataset_kernel.get(), &inputs, |
| &batch_dataset_context)); |
| DatasetBase* batch_dataset; |
| TF_ASSERT_OK(CreateDataset(batch_dataset_kernel.get(), |
| batch_dataset_context.get(), &batch_dataset)); |
| core::ScopedUnref scoped_unref_batch_dataset(batch_dataset); |
| |
| TF_EXPECT_OK(VerifyTypesMatch(batch_dataset->output_dtypes(), |
| test_case.expected_output_dtypes)); |
| } |
| |
| TEST_P(ParameterizedBatchDatasetOpTest, DatasetOutputShapes) { |
| int thread_num = 2, cpu_num = 2; |
| TestCase test_case = GetParam(); |
| TF_ASSERT_OK(InitThreadPool(thread_num)); |
| TF_ASSERT_OK(InitFunctionLibraryRuntime({}, cpu_num)); |
| |
| std::unique_ptr<OpKernel> batch_dataset_kernel; |
| TF_ASSERT_OK(CreateBatchDatasetOpKernel( |
| test_case.parallel_copy, test_case.expected_output_dtypes, |
| test_case.expected_output_shapes, &batch_dataset_kernel)); |
| |
| DatasetBase* range_dataset; |
| TF_ASSERT_OK(CreateRangeDataset<int64>( |
| test_case.range_dataset_param.start, test_case.range_dataset_param.end, |
| test_case.range_dataset_param.step, "range", &range_dataset)); |
| Tensor range_dataset_tensor(DT_VARIANT, TensorShape({})); |
| TF_ASSERT_OK( |
| StoreDatasetInVariantTensor(range_dataset, &range_dataset_tensor)); |
| |
| Tensor batch_size = test_case.batch_size; |
| Tensor drop_remainder = test_case.drop_remainder; |
| gtl::InlinedVector<TensorValue, 4> inputs{TensorValue(&range_dataset_tensor), |
| TensorValue(&batch_size), |
| TensorValue(&drop_remainder)}; |
| std::unique_ptr<OpKernelContext> batch_dataset_context; |
| TF_ASSERT_OK(CreateBatchDatasetContext(batch_dataset_kernel.get(), &inputs, |
| &batch_dataset_context)); |
| DatasetBase* batch_dataset; |
| TF_ASSERT_OK(CreateDataset(batch_dataset_kernel.get(), |
| batch_dataset_context.get(), &batch_dataset)); |
| core::ScopedUnref scoped_unref_batch_dataset(batch_dataset); |
| |
| TF_EXPECT_OK(VerifyShapesCompatible(batch_dataset->output_shapes(), |
| test_case.expected_output_shapes)); |
| } |
| |
| TEST_P(ParameterizedBatchDatasetOpTest, Cardinality) { |
| int thread_num = 2, cpu_num = 2; |
| TestCase test_case = GetParam(); |
| TF_ASSERT_OK(InitThreadPool(thread_num)); |
| TF_ASSERT_OK(InitFunctionLibraryRuntime({}, cpu_num)); |
| |
| std::unique_ptr<OpKernel> batch_dataset_kernel; |
| TF_ASSERT_OK(CreateBatchDatasetOpKernel( |
| test_case.parallel_copy, test_case.expected_output_dtypes, |
| test_case.expected_output_shapes, &batch_dataset_kernel)); |
| |
| DatasetBase* range_dataset; |
| TF_ASSERT_OK(CreateRangeDataset<int64>( |
| test_case.range_dataset_param.start, test_case.range_dataset_param.end, |
| test_case.range_dataset_param.step, "range", &range_dataset)); |
| Tensor range_dataset_tensor(DT_VARIANT, TensorShape({})); |
| TF_ASSERT_OK( |
| StoreDatasetInVariantTensor(range_dataset, &range_dataset_tensor)); |
| |
| Tensor batch_size = test_case.batch_size; |
| Tensor drop_remainder = test_case.drop_remainder; |
| gtl::InlinedVector<TensorValue, 4> inputs{TensorValue(&range_dataset_tensor), |
| TensorValue(&batch_size), |
| TensorValue(&drop_remainder)}; |
| std::unique_ptr<OpKernelContext> batch_dataset_context; |
| TF_ASSERT_OK(CreateBatchDatasetContext(batch_dataset_kernel.get(), &inputs, |
| &batch_dataset_context)); |
| DatasetBase* batch_dataset; |
| TF_ASSERT_OK(CreateDataset(batch_dataset_kernel.get(), |
| batch_dataset_context.get(), &batch_dataset)); |
| core::ScopedUnref scoped_unref_batch_dataset(batch_dataset); |
| |
| EXPECT_EQ(batch_dataset->Cardinality(), test_case.expected_cardinality); |
| } |
| |
| TEST_P(ParameterizedBatchDatasetOpTest, IteratorOutputDtypes) { |
| int thread_num = 2, cpu_num = 2; |
| TestCase test_case = GetParam(); |
| TF_ASSERT_OK(InitThreadPool(thread_num)); |
| TF_ASSERT_OK(InitFunctionLibraryRuntime({}, cpu_num)); |
| |
| std::unique_ptr<OpKernel> batch_dataset_kernel; |
| TF_ASSERT_OK(CreateBatchDatasetOpKernel( |
| test_case.parallel_copy, test_case.expected_output_dtypes, |
| test_case.expected_output_shapes, &batch_dataset_kernel)); |
| |
| DatasetBase* range_dataset; |
| TF_ASSERT_OK(CreateRangeDataset<int64>( |
| test_case.range_dataset_param.start, test_case.range_dataset_param.end, |
| test_case.range_dataset_param.step, "range", &range_dataset)); |
| Tensor range_dataset_tensor(DT_VARIANT, TensorShape({})); |
| TF_ASSERT_OK( |
| StoreDatasetInVariantTensor(range_dataset, &range_dataset_tensor)); |
| |
| Tensor batch_size = test_case.batch_size; |
| Tensor drop_remainder = test_case.drop_remainder; |
| gtl::InlinedVector<TensorValue, 4> inputs{TensorValue(&range_dataset_tensor), |
| TensorValue(&batch_size), |
| TensorValue(&drop_remainder)}; |
| std::unique_ptr<OpKernelContext> batch_dataset_context; |
| TF_ASSERT_OK(CreateBatchDatasetContext(batch_dataset_kernel.get(), &inputs, |
| &batch_dataset_context)); |
| DatasetBase* batch_dataset; |
| TF_ASSERT_OK(CreateDataset(batch_dataset_kernel.get(), |
| batch_dataset_context.get(), &batch_dataset)); |
| core::ScopedUnref scoped_unref_batch_dataset(batch_dataset); |
| |
| std::unique_ptr<IteratorContext> iterator_ctx; |
| TF_ASSERT_OK( |
| CreateIteratorContext(batch_dataset_context.get(), &iterator_ctx)); |
| std::unique_ptr<IteratorBase> iterator; |
| TF_ASSERT_OK( |
| batch_dataset->MakeIterator(iterator_ctx.get(), "Iterator", &iterator)); |
| |
| TF_EXPECT_OK(VerifyTypesMatch(iterator->output_dtypes(), |
| test_case.expected_output_dtypes)); |
| } |
| |
| TEST_P(ParameterizedBatchDatasetOpTest, IteratorOutputShapes) { |
| int thread_num = 2, cpu_num = 2; |
| TestCase test_case = GetParam(); |
| TF_ASSERT_OK(InitThreadPool(thread_num)); |
| TF_ASSERT_OK(InitFunctionLibraryRuntime({}, cpu_num)); |
| |
| std::unique_ptr<OpKernel> batch_dataset_kernel; |
| TF_ASSERT_OK(CreateBatchDatasetOpKernel( |
| test_case.parallel_copy, test_case.expected_output_dtypes, |
| test_case.expected_output_shapes, &batch_dataset_kernel)); |
| |
| DatasetBase* range_dataset; |
| TF_ASSERT_OK(CreateRangeDataset<int64>( |
| test_case.range_dataset_param.start, test_case.range_dataset_param.end, |
| test_case.range_dataset_param.step, "range", &range_dataset)); |
| Tensor range_dataset_tensor(DT_VARIANT, TensorShape({})); |
| TF_ASSERT_OK( |
| StoreDatasetInVariantTensor(range_dataset, &range_dataset_tensor)); |
| |
| Tensor batch_size = test_case.batch_size; |
| Tensor drop_remainder = test_case.drop_remainder; |
| gtl::InlinedVector<TensorValue, 4> inputs{TensorValue(&range_dataset_tensor), |
| TensorValue(&batch_size), |
| TensorValue(&drop_remainder)}; |
| std::unique_ptr<OpKernelContext> batch_dataset_context; |
| TF_ASSERT_OK(CreateBatchDatasetContext(batch_dataset_kernel.get(), &inputs, |
| &batch_dataset_context)); |
| DatasetBase* batch_dataset; |
| TF_ASSERT_OK(CreateDataset(batch_dataset_kernel.get(), |
| batch_dataset_context.get(), &batch_dataset)); |
| core::ScopedUnref scoped_unref_batch_dataset(batch_dataset); |
| |
| std::unique_ptr<IteratorContext> iterator_ctx; |
| TF_ASSERT_OK( |
| CreateIteratorContext(batch_dataset_context.get(), &iterator_ctx)); |
| std::unique_ptr<IteratorBase> iterator; |
| TF_ASSERT_OK( |
| batch_dataset->MakeIterator(iterator_ctx.get(), "Iterator", &iterator)); |
| |
| TF_EXPECT_OK(VerifyShapesCompatible(iterator->output_shapes(), |
| test_case.expected_output_shapes)); |
| } |
| |
| TEST_P(ParameterizedBatchDatasetOpTest, IteratorOutputPrefix) { |
| int thread_num = 2, cpu_num = 2; |
| TestCase test_case = GetParam(); |
| TF_ASSERT_OK(InitThreadPool(thread_num)); |
| TF_ASSERT_OK(InitFunctionLibraryRuntime({}, cpu_num)); |
| |
| std::unique_ptr<OpKernel> batch_dataset_kernel; |
| TF_ASSERT_OK(CreateBatchDatasetOpKernel( |
| test_case.parallel_copy, test_case.expected_output_dtypes, |
| test_case.expected_output_shapes, &batch_dataset_kernel)); |
| |
| DatasetBase* range_dataset; |
| TF_ASSERT_OK(CreateRangeDataset<int64>( |
| test_case.range_dataset_param.start, test_case.range_dataset_param.end, |
| test_case.range_dataset_param.step, "range", &range_dataset)); |
| Tensor range_dataset_tensor(DT_VARIANT, TensorShape({})); |
| TF_ASSERT_OK( |
| StoreDatasetInVariantTensor(range_dataset, &range_dataset_tensor)); |
| |
| Tensor batch_size = test_case.batch_size; |
| Tensor drop_remainder = test_case.drop_remainder; |
| gtl::InlinedVector<TensorValue, 4> inputs{TensorValue(&range_dataset_tensor), |
| TensorValue(&batch_size), |
| TensorValue(&drop_remainder)}; |
| std::unique_ptr<OpKernelContext> batch_dataset_context; |
| TF_ASSERT_OK(CreateBatchDatasetContext(batch_dataset_kernel.get(), &inputs, |
| &batch_dataset_context)); |
| DatasetBase* batch_dataset; |
| TF_ASSERT_OK(CreateDataset(batch_dataset_kernel.get(), |
| batch_dataset_context.get(), &batch_dataset)); |
| core::ScopedUnref scoped_unref_batch_dataset(batch_dataset); |
| |
| std::unique_ptr<IteratorContext> iterator_ctx; |
| TF_ASSERT_OK( |
| CreateIteratorContext(batch_dataset_context.get(), &iterator_ctx)); |
| std::unique_ptr<IteratorBase> iterator; |
| TF_ASSERT_OK( |
| batch_dataset->MakeIterator(iterator_ctx.get(), "Iterator", &iterator)); |
| name_utils::IteratorPrefixParams params; |
| params.op_version = kOpVersion; |
| EXPECT_EQ(iterator->prefix(), |
| name_utils::IteratorPrefix(BatchDatasetOp::kDatasetType, "Iterator", |
| params)); |
| } |
| |
| TEST_P(ParameterizedBatchDatasetOpTest, Roundtrip) { |
| int thread_num = 2, cpu_num = 2; |
| TestCase test_case = GetParam(); |
| TF_ASSERT_OK(InitThreadPool(thread_num)); |
| TF_ASSERT_OK(InitFunctionLibraryRuntime({}, cpu_num)); |
| |
| std::unique_ptr<OpKernel> batch_dataset_kernel; |
| TF_ASSERT_OK(CreateBatchDatasetOpKernel( |
| test_case.parallel_copy, test_case.expected_output_dtypes, |
| test_case.expected_output_shapes, &batch_dataset_kernel)); |
| |
| DatasetBase* range_dataset; |
| TF_ASSERT_OK(CreateRangeDataset<int64>( |
| test_case.range_dataset_param.start, test_case.range_dataset_param.end, |
| test_case.range_dataset_param.step, "range", &range_dataset)); |
| Tensor range_dataset_tensor(DT_VARIANT, TensorShape({})); |
| TF_ASSERT_OK( |
| StoreDatasetInVariantTensor(range_dataset, &range_dataset_tensor)); |
| |
| Tensor batch_size = test_case.batch_size; |
| Tensor drop_remainder = test_case.drop_remainder; |
| gtl::InlinedVector<TensorValue, 4> inputs{TensorValue(&range_dataset_tensor), |
| TensorValue(&batch_size), |
| TensorValue(&drop_remainder)}; |
| std::unique_ptr<OpKernelContext> batch_dataset_context; |
| TF_ASSERT_OK(CreateBatchDatasetContext(batch_dataset_kernel.get(), &inputs, |
| &batch_dataset_context)); |
| DatasetBase* batch_dataset; |
| TF_ASSERT_OK(CreateDataset(batch_dataset_kernel.get(), |
| batch_dataset_context.get(), &batch_dataset)); |
| core::ScopedUnref scoped_unref_batch_dataset(batch_dataset); |
| |
| std::unique_ptr<IteratorContext> iterator_ctx; |
| TF_ASSERT_OK( |
| CreateIteratorContext(batch_dataset_context.get(), &iterator_ctx)); |
| std::unique_ptr<IteratorBase> iterator; |
| TF_ASSERT_OK( |
| batch_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(); |
| for (int breakpoint : test_case.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", |
| *batch_dataset, &iterator)); |
| |
| while (cur_iteration <= breakpoint) { |
| TF_EXPECT_OK(iterator->GetNext(iterator_ctx.get(), &out_tensors, |
| &end_of_sequence)); |
| if (!end_of_sequence) { |
| EXPECT_LT(expected_outputs_it, test_case.expected_outputs.end()); |
| TF_EXPECT_OK(ExpectEqual(out_tensors.back(), *expected_outputs_it)); |
| expected_outputs_it++; |
| } |
| cur_iteration++; |
| } |
| |
| if (breakpoint >= test_case.expected_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(BatchDatasetOpTest, ParameterizedBatchDatasetOpTest, |
| ::testing::ValuesIn(std::vector<TestCase>( |
| {TestCase1(), TestCase2(), TestCase3(), |
| TestCase4(), TestCase5(), TestCase6(), |
| TestCase7()}))); |
| |
| TEST_F(BatchDatasetOpTest, InvalidBatchSize) { |
| int thread_num = 2, cpu_num = 2; |
| TF_ASSERT_OK(InitThreadPool(thread_num)); |
| TF_ASSERT_OK(InitFunctionLibraryRuntime({}, cpu_num)); |
| TestCase test_case = InvalidBatchSizeTestCase(); |
| std::unique_ptr<OpKernel> batch_dataset_kernel; |
| TF_ASSERT_OK(CreateBatchDatasetOpKernel( |
| test_case.parallel_copy, test_case.expected_output_dtypes, |
| test_case.expected_output_shapes, &batch_dataset_kernel)); |
| DatasetBase* range_dataset; |
| TF_ASSERT_OK(CreateRangeDataset<int64>( |
| test_case.range_dataset_param.start, test_case.range_dataset_param.end, |
| test_case.range_dataset_param.step, "range", &range_dataset)); |
| Tensor range_dataset_tensor(DT_VARIANT, TensorShape({})); |
| TF_ASSERT_OK( |
| StoreDatasetInVariantTensor(range_dataset, &range_dataset_tensor)); |
| |
| Tensor batch_size = test_case.batch_size; |
| Tensor drop_remainder = test_case.drop_remainder; |
| gtl::InlinedVector<TensorValue, 4> inputs{TensorValue(&range_dataset_tensor), |
| TensorValue(&batch_size), |
| TensorValue(&drop_remainder)}; |
| std::unique_ptr<OpKernelContext> batch_dataset_context; |
| TF_ASSERT_OK(CreateBatchDatasetContext(batch_dataset_kernel.get(), &inputs, |
| &batch_dataset_context)); |
| DatasetBase* batch_dataset; |
| EXPECT_EQ(CreateDataset(batch_dataset_kernel.get(), |
| batch_dataset_context.get(), &batch_dataset) |
| .code(), |
| tensorflow::error::INVALID_ARGUMENT); |
| } |
| |
| } // namespace |
| } // namespace data |
| } // namespace tensorflow |
