| /* 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/shard_dataset_op.h" |
| |
| #include "tensorflow/core/kernels/data/dataset_test_base.h" |
| |
| namespace tensorflow { |
| namespace data { |
| namespace { |
| |
| constexpr char kNodeName[] = "shard_dataset"; |
| |
| class ShardDatasetOpTest : public DatasetOpsTestBase { |
| protected: |
| // Creates a new `ShardDataset` op kernel. |
| Status CreateShardDatasetOpKernel( |
| bool require_non_empty, 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(ShardDatasetOp::kDatasetType), |
| {ShardDatasetOp::kInputDataset, ShardDatasetOp::kNumShards, |
| ShardDatasetOp::kIndex}, |
| {{ShardDatasetOp::kRequireNonEmpty, require_non_empty}, |
| {ShardDatasetOp::kOutputTypes, output_types}, |
| {ShardDatasetOp::kOutputShapes, output_shapes}}); |
| TF_RETURN_IF_ERROR(CreateOpKernel(node_def, op_kernel)); |
| return Status::OK(); |
| } |
| |
| // Create a new `ShardDataset` op kernel context |
| Status CreateShardDatasetContext( |
| 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 num_shards; |
| Tensor index; |
| bool require_non_empty; |
| 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: simple case. |
| TestCase TestCase1() { |
| return {/*range_data_param*/ {0, 10, 1}, |
| /*num_shards*/ |
| CreateTensor<int64>(TensorShape({}), {5}), |
| /*index*/ |
| CreateTensor<int64>(TensorShape({}), {2}), |
| /*require_non_empty*/ true, |
| /*expected_outputs*/ |
| {CreateTensor<int64>(TensorShape({}), {2}), |
| CreateTensor<int64>(TensorShape({}), {7})}, |
| /*expected_output_dtypes*/ {DT_INT64}, |
| /*expected_output_shapes*/ {PartialTensorShape({})}, |
| /*expected_cardinality*/ 2, |
| /*breakpoints*/ {0, 1, 5}}; |
| } |
| |
| // Test Case 2: zero offset. |
| TestCase TestCase2() { |
| return {/*range_data_param*/ {0, 10, 1}, |
| /*num_shards*/ |
| CreateTensor<int64>(TensorShape({}), {5}), |
| /*index*/ |
| CreateTensor<int64>(TensorShape({}), {0}), |
| /*require_non_empty*/ true, |
| /*expected_outputs*/ |
| {CreateTensor<int64>(TensorShape({}), {0}), |
| CreateTensor<int64>(TensorShape({}), {5})}, |
| /*expected_output_dtypes*/ {DT_INT64}, |
| /*expected_output_shapes*/ {PartialTensorShape({})}, |
| /*expected_cardinality*/ 2, |
| /*breakpoints*/ {0, 1, 5}}; |
| } |
| |
| // Test Case 3: iterator ends before first element. |
| TestCase TestCase3() { |
| return {/*range_data_param*/ {0, 1, 1}, |
| /*num_shards*/ |
| CreateTensor<int64>(TensorShape({}), {5}), |
| /*index*/ |
| CreateTensor<int64>(TensorShape({}), {2}), |
| /*require_non_empty*/ true, |
| /*expected_outputs*/ {}, |
| /*expected_output_dtypes*/ {DT_INT64}, |
| /*expected_output_shapes*/ {PartialTensorShape({})}, |
| /*expected_cardinality*/ 0, |
| /*breakpoints*/ {0, 1}}; |
| } |
| |
| // Test Case 4: larger num_shards. |
| TestCase TestCase4() { |
| return {/*range_data_param*/ {0, 10, 1}, |
| /*num_shards*/ |
| CreateTensor<int64>(TensorShape({}), {7}), |
| /*index*/ |
| CreateTensor<int64>(TensorShape({}), {5}), |
| /*require_non_empty*/ true, |
| /*expected_outputs*/ |
| {CreateTensor<int64>(TensorShape({}), {5})}, |
| /*expected_output_dtypes*/ {DT_INT64}, |
| /*expected_output_shapes*/ {PartialTensorShape({})}, |
| /*expected_cardinality*/ 1, |
| /*breakpoints*/ {0, 5}}; |
| } |
| |
| // Test Case 5: index == num_shards. |
| TestCase TestCase5() { |
| return {/*range_data_param*/ {0, 10, 1}, |
| /*num_shards*/ |
| CreateTensor<int64>(TensorShape({}), {5}), |
| /*index*/ |
| CreateTensor<int64>(TensorShape({}), {4}), |
| /*require_non_empty*/ true, |
| /*expected_outputs*/ |
| {CreateTensor<int64>(TensorShape({}), {4}), |
| CreateTensor<int64>(TensorShape({}), {9})}, |
| /*expected_output_dtypes*/ {DT_INT64}, |
| /*expected_output_shapes*/ {PartialTensorShape({})}, |
| /*expected_cardinality*/ 2, |
| /*breakpoints*/ {0, 1, 5}}; |
| } |
| |
| // Test Case 6: similar with test_case_5 but the number of outputs could not be |
| // divided evenly by num_shards. |
| TestCase TestCase6() { |
| return {/*range_data_param*/ {0, 10, 1}, |
| /*num_shards*/ |
| CreateTensor<int64>(TensorShape({}), {4}), |
| /*index*/ |
| CreateTensor<int64>(TensorShape({}), {3}), |
| /*require_non_empty*/ true, |
| /*expected_outputs*/ |
| {CreateTensor<int64>(TensorShape({}), {3}), |
| CreateTensor<int64>(TensorShape({}), {7})}, |
| /*expected_output_dtypes*/ {DT_INT64}, |
| /*expected_output_shapes*/ {PartialTensorShape({})}, |
| /*expected_cardinality*/ 2, |
| /*breakpoints*/ {0, 1, 5}}; |
| } |
| |
| // Test Case 7: num_shard is larger than the cardinality of input dataset; |
| // require_non_empty = false. |
| TestCase TestCase7() { |
| return {/*range_data_param*/ {0, 10, 1}, |
| /*num_shards*/ |
| CreateTensor<int64>(TensorShape({}), {20}), |
| /*index*/ |
| CreateTensor<int64>(TensorShape({}), {5}), |
| /*require_non_empty*/ false, |
| /*expected_outputs*/ |
| {CreateTensor<int64>(TensorShape({}), {5})}, |
| /*expected_output_dtypes*/ {DT_INT64}, |
| /*expected_output_shapes*/ {PartialTensorShape({})}, |
| /*expected_cardinality*/ 1, |
| /*breakpoints*/ {0, 5}}; |
| } |
| |
| // Test Case 8: similar with test_case_7 but require_non_empty = true. |
| TestCase NoElemForEachShardTestCase() { |
| return {/*range_data_param*/ {0, 10, 1}, |
| /*num_shards*/ |
| CreateTensor<int64>(TensorShape({}), {20}), |
| /*index*/ |
| CreateTensor<int64>(TensorShape({}), {5}), |
| /*require_non_empty*/ true, |
| /*expected_outputs*/ |
| {CreateTensor<int64>(TensorShape({}), {5})}, |
| /*expected_output_dtypes*/ {DT_INT64}, |
| /*expected_output_shapes*/ {PartialTensorShape({})}, |
| /*expected_cardinality*/ 1, |
| /*breakpoints*/ {0, 5}}; |
| } |
| |
| TestCase IndexGreaterNumShardsCase() { |
| return {/*range_data_param*/ {0, 10, 1}, |
| /*num_shards*/ |
| CreateTensor<int64>(TensorShape({}), {5}), |
| /*index*/ |
| CreateTensor<int64>(TensorShape({}), {7}), |
| /*require_non_empty*/ true, |
| /*expected_outputs*/ {}, |
| /*expected_output_dtypes*/ {DT_INT64}, |
| /*expected_output_shapes*/ {PartialTensorShape({})}, |
| /*expected_cardinality*/ 0, |
| /*breakpoints*/ {}}; |
| } |
| |
| TestCase NegativeIndexTestCase() { |
| return {/*range_data_param*/ {0, 10, 1}, |
| /*num_shards*/ |
| CreateTensor<int64>(TensorShape({}), {5}), |
| /*index*/ |
| CreateTensor<int64>(TensorShape({}), {-3}), |
| /*require_non_empty*/ true, |
| /*expected_outputs*/ {}, |
| /*expected_output_dtypes*/ {DT_INT64}, |
| /*expected_output_shapes*/ {PartialTensorShape({})}, |
| /*expected_cardinality*/ 0, |
| /*breakpoints*/ {}}; |
| } |
| |
| TestCase NegativeNumShardsTestCase() { |
| return {/*range_data_param*/ {0, 10, 1}, |
| /*num_shards*/ |
| CreateTensor<int64>(TensorShape({}), {-3}), |
| /*index*/ |
| CreateTensor<int64>(TensorShape({}), {1}), |
| /*require_non_empty*/ true, |
| /*expected_outputs*/ {}, |
| /*expected_output_dtypes*/ {DT_INT64}, |
| /*expected_output_shapes*/ {PartialTensorShape({})}, |
| /*expected_cardinality*/ 0, |
| /*breakpoints*/ {}}; |
| } |
| |
| TestCase ZeroNumShardsTestCase() { |
| return {/*range_data_param*/ {0, 10, 1}, |
| /*num_shards*/ |
| CreateTensor<int64>(TensorShape({}), {0}), |
| /*index*/ |
| CreateTensor<int64>(TensorShape({}), {1}), |
| /*require_non_empty*/ true, |
| /*expected_outputs*/ {}, |
| /*expected_output_dtypes*/ {DT_INT64}, |
| /*expected_output_shapes*/ {PartialTensorShape({})}, |
| /*expected_cardinality*/ 0, |
| /*breakpoints*/ {}}; |
| } |
| |
| class ParameterizedShardDatasetOpTest |
| : public ShardDatasetOpTest, |
| public ::testing::WithParamInterface<TestCase> {}; |
| |
| TEST_P(ParameterizedShardDatasetOpTest, 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> shard_dataset_kernel; |
| TF_ASSERT_OK(CreateShardDatasetOpKernel( |
| test_case.require_non_empty, test_case.expected_output_dtypes, |
| test_case.expected_output_shapes, &shard_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 num_shards = test_case.num_shards; |
| Tensor index = test_case.index; |
| gtl::InlinedVector<TensorValue, 4> inputs({TensorValue(&range_dataset_tensor), |
| TensorValue(&num_shards), |
| TensorValue(&index)}); |
| std::unique_ptr<OpKernelContext> shard_dataset_context; |
| TF_ASSERT_OK(CreateShardDatasetContext(shard_dataset_kernel.get(), &inputs, |
| &shard_dataset_context)); |
| |
| DatasetBase* shard_dataset; |
| TF_ASSERT_OK(CreateDataset(shard_dataset_kernel.get(), |
| shard_dataset_context.get(), &shard_dataset)); |
| core::ScopedUnref scoped_unref_batch_dataset(shard_dataset); |
| |
| std::unique_ptr<IteratorContext> iterator_ctx; |
| TF_ASSERT_OK( |
| CreateIteratorContext(shard_dataset_context.get(), &iterator_ctx)); |
| std::unique_ptr<IteratorBase> iterator; |
| TF_ASSERT_OK( |
| shard_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_F(ShardDatasetOpTest, DatasetNodeName) { |
| int thread_num = 2, cpu_num = 2; |
| TestCase test_case = TestCase1(); |
| TF_ASSERT_OK(InitThreadPool(thread_num)); |
| TF_ASSERT_OK(InitFunctionLibraryRuntime({}, cpu_num)); |
| |
| std::unique_ptr<OpKernel> shard_dataset_kernel; |
| TF_ASSERT_OK(CreateShardDatasetOpKernel( |
| test_case.require_non_empty, test_case.expected_output_dtypes, |
| test_case.expected_output_shapes, &shard_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 num_shards = test_case.num_shards; |
| Tensor index = test_case.index; |
| gtl::InlinedVector<TensorValue, 4> inputs({TensorValue(&range_dataset_tensor), |
| TensorValue(&num_shards), |
| TensorValue(&index)}); |
| std::unique_ptr<OpKernelContext> shard_dataset_context; |
| TF_ASSERT_OK(CreateShardDatasetContext(shard_dataset_kernel.get(), &inputs, |
| &shard_dataset_context)); |
| |
| DatasetBase* shard_dataset; |
| TF_ASSERT_OK(CreateDataset(shard_dataset_kernel.get(), |
| shard_dataset_context.get(), &shard_dataset)); |
| core::ScopedUnref scoped_unref_batch_dataset(shard_dataset); |
| |
| EXPECT_EQ(shard_dataset->node_name(), kNodeName); |
| } |
| |
| TEST_F(ShardDatasetOpTest, DatasetTypeString) { |
| int thread_num = 2, cpu_num = 2; |
| TestCase test_case = TestCase1(); |
| TF_ASSERT_OK(InitThreadPool(thread_num)); |
| TF_ASSERT_OK(InitFunctionLibraryRuntime({}, cpu_num)); |
| |
| std::unique_ptr<OpKernel> shard_dataset_kernel; |
| TF_ASSERT_OK(CreateShardDatasetOpKernel( |
| test_case.require_non_empty, test_case.expected_output_dtypes, |
| test_case.expected_output_shapes, &shard_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 num_shards = test_case.num_shards; |
| Tensor index = test_case.index; |
| gtl::InlinedVector<TensorValue, 4> inputs({TensorValue(&range_dataset_tensor), |
| TensorValue(&num_shards), |
| TensorValue(&index)}); |
| std::unique_ptr<OpKernelContext> shard_dataset_context; |
| TF_ASSERT_OK(CreateShardDatasetContext(shard_dataset_kernel.get(), &inputs, |
| &shard_dataset_context)); |
| |
| DatasetBase* shard_dataset; |
| TF_ASSERT_OK(CreateDataset(shard_dataset_kernel.get(), |
| shard_dataset_context.get(), &shard_dataset)); |
| core::ScopedUnref scoped_unref_batch_dataset(shard_dataset); |
| |
| EXPECT_EQ(shard_dataset->type_string(), |
| name_utils::OpName(ShardDatasetOp::kDatasetType)); |
| } |
| |
| TEST_P(ParameterizedShardDatasetOpTest, 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> shard_dataset_kernel; |
| TF_ASSERT_OK(CreateShardDatasetOpKernel( |
| test_case.require_non_empty, test_case.expected_output_dtypes, |
| test_case.expected_output_shapes, &shard_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 num_shards = test_case.num_shards; |
| Tensor index = test_case.index; |
| gtl::InlinedVector<TensorValue, 4> inputs({TensorValue(&range_dataset_tensor), |
| TensorValue(&num_shards), |
| TensorValue(&index)}); |
| std::unique_ptr<OpKernelContext> shard_dataset_context; |
| TF_ASSERT_OK(CreateShardDatasetContext(shard_dataset_kernel.get(), &inputs, |
| &shard_dataset_context)); |
| |
| DatasetBase* shard_dataset; |
| TF_ASSERT_OK(CreateDataset(shard_dataset_kernel.get(), |
| shard_dataset_context.get(), &shard_dataset)); |
| core::ScopedUnref scoped_unref_batch_dataset(shard_dataset); |
| |
| TF_EXPECT_OK(VerifyTypesMatch(shard_dataset->output_dtypes(), |
| test_case.expected_output_dtypes)); |
| } |
| |
| TEST_P(ParameterizedShardDatasetOpTest, 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> shard_dataset_kernel; |
| TF_ASSERT_OK(CreateShardDatasetOpKernel( |
| test_case.require_non_empty, test_case.expected_output_dtypes, |
| test_case.expected_output_shapes, &shard_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 num_shards = test_case.num_shards; |
| Tensor index = test_case.index; |
| gtl::InlinedVector<TensorValue, 4> inputs({TensorValue(&range_dataset_tensor), |
| TensorValue(&num_shards), |
| TensorValue(&index)}); |
| std::unique_ptr<OpKernelContext> shard_dataset_context; |
| TF_ASSERT_OK(CreateShardDatasetContext(shard_dataset_kernel.get(), &inputs, |
| &shard_dataset_context)); |
| |
| DatasetBase* shard_dataset; |
| TF_ASSERT_OK(CreateDataset(shard_dataset_kernel.get(), |
| shard_dataset_context.get(), &shard_dataset)); |
| core::ScopedUnref scoped_unref_batch_dataset(shard_dataset); |
| |
| TF_EXPECT_OK(VerifyShapesCompatible(shard_dataset->output_shapes(), |
| test_case.expected_output_shapes)); |
| } |
| |
| TEST_P(ParameterizedShardDatasetOpTest, 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> shard_dataset_kernel; |
| TF_ASSERT_OK(CreateShardDatasetOpKernel( |
| test_case.require_non_empty, test_case.expected_output_dtypes, |
| test_case.expected_output_shapes, &shard_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 num_shards = test_case.num_shards; |
| Tensor index = test_case.index; |
| gtl::InlinedVector<TensorValue, 4> inputs({TensorValue(&range_dataset_tensor), |
| TensorValue(&num_shards), |
| TensorValue(&index)}); |
| std::unique_ptr<OpKernelContext> shard_dataset_context; |
| TF_ASSERT_OK(CreateShardDatasetContext(shard_dataset_kernel.get(), &inputs, |
| &shard_dataset_context)); |
| |
| DatasetBase* shard_dataset; |
| TF_ASSERT_OK(CreateDataset(shard_dataset_kernel.get(), |
| shard_dataset_context.get(), &shard_dataset)); |
| core::ScopedUnref scoped_unref_batch_dataset(shard_dataset); |
| |
| EXPECT_EQ(shard_dataset->Cardinality(), test_case.expected_cardinality); |
| } |
| |
| TEST_P(ParameterizedShardDatasetOpTest, 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> shard_dataset_kernel; |
| TF_ASSERT_OK(CreateShardDatasetOpKernel( |
| test_case.require_non_empty, test_case.expected_output_dtypes, |
| test_case.expected_output_shapes, &shard_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 num_shards = test_case.num_shards; |
| Tensor index = test_case.index; |
| gtl::InlinedVector<TensorValue, 4> inputs({TensorValue(&range_dataset_tensor), |
| TensorValue(&num_shards), |
| TensorValue(&index)}); |
| std::unique_ptr<OpKernelContext> shard_dataset_context; |
| TF_ASSERT_OK(CreateShardDatasetContext(shard_dataset_kernel.get(), &inputs, |
| &shard_dataset_context)); |
| |
| DatasetBase* shard_dataset; |
| TF_ASSERT_OK(CreateDataset(shard_dataset_kernel.get(), |
| shard_dataset_context.get(), &shard_dataset)); |
| core::ScopedUnref scoped_unref_batch_dataset(shard_dataset); |
| |
| std::unique_ptr<IteratorContext> iterator_ctx; |
| TF_ASSERT_OK( |
| CreateIteratorContext(shard_dataset_context.get(), &iterator_ctx)); |
| std::unique_ptr<IteratorBase> iterator; |
| TF_ASSERT_OK( |
| shard_dataset->MakeIterator(iterator_ctx.get(), "Iterator", &iterator)); |
| |
| TF_EXPECT_OK(VerifyTypesMatch(iterator->output_dtypes(), |
| test_case.expected_output_dtypes)); |
| } |
| |
| TEST_P(ParameterizedShardDatasetOpTest, 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> shard_dataset_kernel; |
| TF_ASSERT_OK(CreateShardDatasetOpKernel( |
| test_case.require_non_empty, test_case.expected_output_dtypes, |
| test_case.expected_output_shapes, &shard_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 num_shards = test_case.num_shards; |
| Tensor index = test_case.index; |
| gtl::InlinedVector<TensorValue, 4> inputs({TensorValue(&range_dataset_tensor), |
| TensorValue(&num_shards), |
| TensorValue(&index)}); |
| std::unique_ptr<OpKernelContext> shard_dataset_context; |
| TF_ASSERT_OK(CreateShardDatasetContext(shard_dataset_kernel.get(), &inputs, |
| &shard_dataset_context)); |
| |
| DatasetBase* shard_dataset; |
| TF_ASSERT_OK(CreateDataset(shard_dataset_kernel.get(), |
| shard_dataset_context.get(), &shard_dataset)); |
| core::ScopedUnref scoped_unref_batch_dataset(shard_dataset); |
| |
| std::unique_ptr<IteratorContext> iterator_ctx; |
| TF_ASSERT_OK( |
| CreateIteratorContext(shard_dataset_context.get(), &iterator_ctx)); |
| std::unique_ptr<IteratorBase> iterator; |
| TF_ASSERT_OK( |
| shard_dataset->MakeIterator(iterator_ctx.get(), "Iterator", &iterator)); |
| |
| TF_EXPECT_OK(VerifyShapesCompatible(iterator->output_shapes(), |
| test_case.expected_output_shapes)); |
| } |
| |
| TEST_F(ShardDatasetOpTest, IteratorOutputPrefix) { |
| int thread_num = 2, cpu_num = 2; |
| TestCase test_case = TestCase1(); |
| TF_ASSERT_OK(InitThreadPool(thread_num)); |
| TF_ASSERT_OK(InitFunctionLibraryRuntime({}, cpu_num)); |
| |
| std::unique_ptr<OpKernel> shard_dataset_kernel; |
| TF_ASSERT_OK(CreateShardDatasetOpKernel( |
| test_case.require_non_empty, test_case.expected_output_dtypes, |
| test_case.expected_output_shapes, &shard_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 num_shards = test_case.num_shards; |
| Tensor index = test_case.index; |
| gtl::InlinedVector<TensorValue, 4> inputs({TensorValue(&range_dataset_tensor), |
| TensorValue(&num_shards), |
| TensorValue(&index)}); |
| std::unique_ptr<OpKernelContext> shard_dataset_context; |
| TF_ASSERT_OK(CreateShardDatasetContext(shard_dataset_kernel.get(), &inputs, |
| &shard_dataset_context)); |
| |
| DatasetBase* shard_dataset; |
| TF_ASSERT_OK(CreateDataset(shard_dataset_kernel.get(), |
| shard_dataset_context.get(), &shard_dataset)); |
| core::ScopedUnref scoped_unref_batch_dataset(shard_dataset); |
| |
| std::unique_ptr<IteratorContext> iterator_ctx; |
| TF_ASSERT_OK( |
| CreateIteratorContext(shard_dataset_context.get(), &iterator_ctx)); |
| std::unique_ptr<IteratorBase> iterator; |
| TF_ASSERT_OK( |
| shard_dataset->MakeIterator(iterator_ctx.get(), "Iterator", &iterator)); |
| |
| EXPECT_EQ(iterator->prefix(), name_utils::IteratorPrefix( |
| ShardDatasetOp::kDatasetType, "Iterator")); |
| } |
| |
| TEST_P(ParameterizedShardDatasetOpTest, 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> shard_dataset_kernel; |
| TF_ASSERT_OK(CreateShardDatasetOpKernel( |
| test_case.require_non_empty, test_case.expected_output_dtypes, |
| test_case.expected_output_shapes, &shard_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 num_shards = test_case.num_shards; |
| Tensor index = test_case.index; |
| gtl::InlinedVector<TensorValue, 4> inputs({TensorValue(&range_dataset_tensor), |
| TensorValue(&num_shards), |
| TensorValue(&index)}); |
| std::unique_ptr<OpKernelContext> shard_dataset_context; |
| TF_ASSERT_OK(CreateShardDatasetContext(shard_dataset_kernel.get(), &inputs, |
| &shard_dataset_context)); |
| |
| DatasetBase* shard_dataset; |
| TF_ASSERT_OK(CreateDataset(shard_dataset_kernel.get(), |
| shard_dataset_context.get(), &shard_dataset)); |
| core::ScopedUnref scoped_unref_batch_dataset(shard_dataset); |
| |
| std::unique_ptr<IteratorContext> iterator_ctx; |
| TF_ASSERT_OK( |
| CreateIteratorContext(shard_dataset_context.get(), &iterator_ctx)); |
| std::unique_ptr<IteratorBase> iterator; |
| TF_ASSERT_OK( |
| shard_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; |
| 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", |
| *shard_dataset, &iterator)); |
| |
| while (cur_iteration <= breakpoint) { |
| std::vector<Tensor> next; |
| TF_EXPECT_OK( |
| iterator->GetNext(iterator_ctx.get(), &next, &end_of_sequence)); |
| out_tensors.insert(out_tensors.end(), next.begin(), next.end()); |
| cur_iteration++; |
| } |
| } |
| |
| TF_EXPECT_OK(ExpectEqual(out_tensors, test_case.expected_outputs, |
| /*compare_order*/ true)); |
| } |
| |
| INSTANTIATE_TEST_SUITE_P(ShardDatasetOpTest, ParameterizedShardDatasetOpTest, |
| ::testing::ValuesIn(std::vector<TestCase>( |
| {TestCase1(), TestCase2(), TestCase3(), |
| TestCase4(), TestCase5(), TestCase6(), |
| TestCase7()}))); |
| |
| TEST_F(ShardDatasetOpTest, InvalidArguments) { |
| int thread_num = 2, cpu_num = 2; |
| TF_ASSERT_OK(InitThreadPool(thread_num)); |
| TF_ASSERT_OK(InitFunctionLibraryRuntime({}, cpu_num)); |
| |
| std::vector<TestCase> test_cases = { |
| IndexGreaterNumShardsCase(), NegativeIndexTestCase(), |
| NegativeNumShardsTestCase(), ZeroNumShardsTestCase()}; |
| for (const auto& test_case : test_cases) { |
| std::unique_ptr<OpKernel> shard_dataset_kernel; |
| TF_ASSERT_OK(CreateShardDatasetOpKernel( |
| test_case.require_non_empty, test_case.expected_output_dtypes, |
| test_case.expected_output_shapes, &shard_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 num_shards = test_case.num_shards; |
| Tensor index = test_case.index; |
| gtl::InlinedVector<TensorValue, 4> inputs( |
| {TensorValue(&range_dataset_tensor), TensorValue(&num_shards), |
| TensorValue(&index)}); |
| std::unique_ptr<OpKernelContext> shard_dataset_context; |
| TF_ASSERT_OK(CreateShardDatasetContext(shard_dataset_kernel.get(), &inputs, |
| &shard_dataset_context)); |
| |
| DatasetBase* shard_dataset; |
| EXPECT_EQ(CreateDataset(shard_dataset_kernel.get(), |
| shard_dataset_context.get(), &shard_dataset) |
| .code(), |
| tensorflow::error::INVALID_ARGUMENT); |
| } |
| } |
| |
| TEST_F(ShardDatasetOpTest, NoElemForEachShard) { |
| int thread_num = 2, cpu_num = 2; |
| TF_ASSERT_OK(InitThreadPool(thread_num)); |
| TF_ASSERT_OK(InitFunctionLibraryRuntime({}, cpu_num)); |
| TestCase test_case = NoElemForEachShardTestCase(); |
| |
| std::unique_ptr<OpKernel> shard_dataset_kernel; |
| TF_ASSERT_OK(CreateShardDatasetOpKernel( |
| test_case.require_non_empty, test_case.expected_output_dtypes, |
| test_case.expected_output_shapes, &shard_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 num_shards = test_case.num_shards; |
| Tensor index = test_case.index; |
| gtl::InlinedVector<TensorValue, 4> inputs({TensorValue(&range_dataset_tensor), |
| TensorValue(&num_shards), |
| TensorValue(&index)}); |
| std::unique_ptr<OpKernelContext> shard_dataset_context; |
| TF_ASSERT_OK(CreateShardDatasetContext(shard_dataset_kernel.get(), &inputs, |
| &shard_dataset_context)); |
| |
| DatasetBase* shard_dataset; |
| TF_ASSERT_OK(CreateDataset(shard_dataset_kernel.get(), |
| shard_dataset_context.get(), &shard_dataset)); |
| core::ScopedUnref scoped_unref_batch_dataset(shard_dataset); |
| |
| std::unique_ptr<IteratorContext> iterator_ctx; |
| TF_ASSERT_OK( |
| CreateIteratorContext(shard_dataset_context.get(), &iterator_ctx)); |
| std::unique_ptr<IteratorBase> iterator; |
| TF_ASSERT_OK( |
| shard_dataset->MakeIterator(iterator_ctx.get(), "Iterator", &iterator)); |
| |
| bool end_of_sequence = false; |
| std::vector<Tensor> out_tensors; |
| |
| EXPECT_EQ( |
| iterator->GetNext(iterator_ctx.get(), &out_tensors, &end_of_sequence) |
| .code(), |
| tensorflow::error::INVALID_ARGUMENT); |
| } |
| |
| } // namespace |
| } // namespace data |
| } // namespace tensorflow |
