experiments/STT-tensorflow
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This commit is contained in:
Fei Hu 2019-09-04 15:50:03 -07:00
parent b7833a43a8
commit 1d3326cb66
4 changed files with 71 additions and 66 deletions
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58
tensorflow/core/framework/function_testlib.h
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@ -68,16 +68,16 @@ GraphDef GDef(gtl::ArraySlice<NodeDef> nodes,
// For testing convenience, we provide a few simple functions that can // For testing convenience, we provide a few simple functions that can
// be easily executed and tested. // be easily executed and tested.
// x:T -> x * 2. // x: T -> x * 2.
FunctionDef XTimesTwo(); FunctionDef XTimesTwo();
// x:T -> cpu(x * 2) + cpu(x * 3). // x: T -> cpu(x * 2) + cpu(x * 3).
FunctionDef TwoDeviceTimesFive(); FunctionDef TwoDeviceTimesFive();
// x:T -> cpu(x * 2), gpu(x * 3). // x: T -> cpu(x * 2), gpu(x * 3).
FunctionDef TwoDeviceMult(); FunctionDef TwoDeviceMult();
// cpu(x):T, gpu(y):T -> cpu(x * 2), gpu(y * 3). // cpu(x): T, gpu(y): T -> cpu(x * 2), gpu(y * 3).
FunctionDef TwoDeviceInputOutput(); FunctionDef TwoDeviceInputOutput();
// Function taking a list of Tensors as input. // Function taking a list of Tensors as input.
@ -86,25 +86,25 @@ FunctionDef FuncWithListInput();
// Function returning a list of Tensors as output. // Function returning a list of Tensors as output.
FunctionDef FuncWithListOutput(); FunctionDef FuncWithListOutput();
// x:T -> x + x. // x: T -> x + x.
FunctionDef XAddX(); FunctionDef XAddX();
// x: T, y:T -> x + y. // x: T, y: T -> x + y.
FunctionDef XAddY(); FunctionDef XAddY();
// x:T -> x * 2, where x is int32. // x: T -> x * 2, where x is int32.
FunctionDef XTimesTwoInt32(); FunctionDef XTimesTwoInt32();
// x:T -> (x * 2) * 2. // x: T -> (x * 2) * 2.
FunctionDef XTimesFour(); FunctionDef XTimesFour();
// x:T -> ((x * 2) * 2) * 2. // x: T -> ((x * 2) * 2) * 2.
FunctionDef XTimes16(); FunctionDef XTimes16();
// w:T, x:T, b:T -> MatMul(w, x) + b // w: T, x: T, b: T -> MatMul(w, x) + b
FunctionDef WXPlusB(); FunctionDef WXPlusB();
// x:T -> x:T, T is a type which we automatically converts to a bool. // x: T -> x: T, T is a type which we automatically converts to a bool.
FunctionDef NonZero(); FunctionDef NonZero();
// x: T -> bool. // x: T -> bool.
@ -113,56 +113,56 @@ FunctionDef IsZero();
// x: T -> int64 // x: T -> int64
FunctionDef RandomUniform(); FunctionDef RandomUniform();
// x:T, y:T -> y:T, x:T // x: T, y:T -> y: T, x: T
FunctionDef Swap(); FunctionDef Swap();
// x:T, y:T -> y:T, x:T, the body has no nodes. // x: T, y: T -> y: T, x: T, the body has no nodes.
FunctionDef EmptyBodySwap(); FunctionDef EmptyBodySwap();
// x:float, y:resource -> y:resource, 2*x:float. // x: float, y: resource -> y: resource, 2*x: float.
FunctionDef ResourceOutput(); FunctionDef ResourceOutput();
// x:resource -> x:resource // x: resource -> x: resource
FunctionDef ResourceIdentity(); FunctionDef ResourceIdentity();
// x:resource -> y:float. // x: resource -> y: float.
FunctionDef ReadResourceVariable(); FunctionDef ReadResourceVariable();
// Contains malformed control flow which can't be run by the executor. // Contains malformed control flow which can't be run by the executor.
FunctionDef InvalidControlFlow(); FunctionDef InvalidControlFlow();
// x:T -> x <= N. // x: T -> x <= N.
FunctionDef LessThanOrEqualToN(int64 N); FunctionDef LessThanOrEqualToN(int64 N);
// x:T, y:T -> x+1, x*y // x: T, y: T -> x + 1, x * y
FunctionDef XPlusOneXTimesY(); FunctionDef XPlusOneXTimesY();
// x:T, y:T -> x <= N // x: T, y: T -> x <= N
FunctionDef XYXLessThanOrEqualToN(int64 N); FunctionDef XYXLessThanOrEqualToN(int64 N);
// x: T -> bool // x: T -> bool
FunctionDef RandomUniformLess(); FunctionDef RandomUniformLess();
// start:int64, stop:int64, step:int64 -> y:RangeDatasetOp::Dataset // start: int64, stop: int64, step: int64 -> y: RangeDatasetOp::Dataset
FunctionDef MakeRangeDataset(); FunctionDef MakeRangeDataset();
// input_dataset:variant, batch_size:int64, drop_remainder:bool // input_dataset: variant, batch_size: int64, drop_remainder: bool
// -> y:BatchDatasetV2::Dataset // -> y: BatchDatasetV2::Dataset
FunctionDef MakeBatchDataset(); FunctionDef MakeBatchDataset();
// input_dataset:variant, other_arguments:Targuments, f:func, // input_dataset: variant, other_arguments: Targuments, f: func,
// Targuments:list(type), output_types:list(type), output_shapes:list(shape), // Targuments: list(type), output_types: list(type), output_shapes: list(shape),
// use_inter_op_parallelism:bool, preserve_cardinality:bool // use_inter_op_parallelism: bool, preserve_cardinality: bool
// -> y:MapDatasetOp::Dataset // -> y: MapDatasetOp::Dataset
FunctionDef MakeMapDataset(bool has_other_args); FunctionDef MakeMapDataset(bool has_other_args);
// input_dataset:variant, count:int64 -> y:TakeDataset::Dataset // input_dataset: variant, count: int64 -> y: TakeDataset::Dataset
FunctionDef MakeTakeDataset(); FunctionDef MakeTakeDataset();
// x:T -> y:TensorSliceDatasetOp::Dataset // x: T -> y: TensorSliceDatasetOp::Dataset
FunctionDef MakeTensorSliceDataset(); FunctionDef MakeTensorSliceDataset();
// x:T -> y:T, idx:out_idx // x: T -> y: T, idx: out_idx
FunctionDef Unique(); FunctionDef Unique();
void FunctionTestSchedClosure(std::function<void()> fn); void FunctionTestSchedClosure(std::function<void()> fn);

18
tensorflow/core/kernels/data/batch_dataset_op_test.cc
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@ -17,7 +17,7 @@ namespace tensorflow {
namespace data { namespace data {
namespace { namespace {
constexpr char kNodeName[] = "batch_dataset_v2"; constexpr char kNodeName[] = "batch_dataset";
class BatchDatasetOpTest : public DatasetOpsTestBaseV2 {}; class BatchDatasetOpTest : public DatasetOpsTestBaseV2 {};
@ -30,7 +30,7 @@ BatchDatasetParams BatchDatasetParams1() {
/*parallel_copy=*/true, /*parallel_copy=*/true,
/*output_dtypes=*/{DT_INT64}, /*output_dtypes=*/{DT_INT64},
/*output_shapes=*/{PartialTensorShape({4})}, /*output_shapes=*/{PartialTensorShape({4})},
/*node_name=*/"batch_dataset_v2"); /*node_name=*/"batch_dataset");
} }
// Test Case 2: test BatchDatasetV2 with `drop_remainder` = true and a batch // Test Case 2: test BatchDatasetV2 with `drop_remainder` = true and a batch
@ -42,7 +42,7 @@ BatchDatasetParams BatchDatasetParams2() {
/*parallel_copy=*/false, /*parallel_copy=*/false,
/*output_dtypes=*/{DT_INT64}, /*output_dtypes=*/{DT_INT64},
/*output_shapes=*/{PartialTensorShape({4})}, /*output_shapes=*/{PartialTensorShape({4})},
/*node_name=*/"batch_dataset_v2"); /*node_name=*/"batch_dataset");
} }
// Test Case 3: test BatchDatasetV2 with `drop_remainder` = false and a batch // Test Case 3: test BatchDatasetV2 with `drop_remainder` = false and a batch
@ -54,7 +54,7 @@ BatchDatasetParams BatchDatasetParams3() {
/*parallel_copy=*/false, /*parallel_copy=*/false,
/*output_dtypes=*/{DT_INT64}, /*output_dtypes=*/{DT_INT64},
/*output_shapes=*/{PartialTensorShape({-1})}, /*output_shapes=*/{PartialTensorShape({-1})},
/*node_name=*/"batch_dataset_0"); /*node_name=*/"batch_dataset");
} }
// Test Case 4: test BatchDatasetV2 with `drop_remainder` = true and a batch // Test Case 4: test BatchDatasetV2 with `drop_remainder` = true and a batch
@ -66,7 +66,7 @@ BatchDatasetParams BatchDatasetParams4() {
/*parallel_copy=*/true, /*parallel_copy=*/true,
/*output_dtypes=*/{DT_INT64}, /*output_dtypes=*/{DT_INT64},
/*output_shapes=*/{PartialTensorShape({3})}, /*output_shapes=*/{PartialTensorShape({3})},
/*node_name=*/"batch_dataset_v2"); /*node_name=*/"batch_dataset");
} }
// Test Case 5: test BatchDatasetV2 with `drop_remainder` = true and // Test Case 5: test BatchDatasetV2 with `drop_remainder` = true and
@ -78,7 +78,7 @@ BatchDatasetParams BatchDatasetParams5() {
/*parallel_copy=*/true, /*parallel_copy=*/true,
/*output_dtypes=*/{DT_INT64}, /*output_dtypes=*/{DT_INT64},
/*output_shapes=*/{PartialTensorShape({12})}, /*output_shapes=*/{PartialTensorShape({12})},
/*node_name=*/kNodeName); /*node_name=*/"batch_dataset");
} }
// Test Case 6: test BatchDatasetV2 with `drop_remainder` = false and // Test Case 6: test BatchDatasetV2 with `drop_remainder` = false and
@ -90,7 +90,7 @@ BatchDatasetParams BatchDatasetParams6() {
/*parallel_copy=*/true, /*parallel_copy=*/true,
/*output_dtypes=*/{DT_INT64}, /*output_dtypes=*/{DT_INT64},
/*output_shapes=*/{PartialTensorShape({-1})}, /*output_shapes=*/{PartialTensorShape({-1})},
/*node_name=*/"batch_dataset_v2"); /*node_name=*/"batch_dataset");
} }
// Test Case 7: test BatchDatasetV2 with `drop_remainder` = false and // Test Case 7: test BatchDatasetV2 with `drop_remainder` = false and
@ -102,7 +102,7 @@ BatchDatasetParams BatchDatasetParams7() {
/*parallel_copy=*/false, /*parallel_copy=*/false,
/*output_dtypes=*/{DT_INT64}, /*output_dtypes=*/{DT_INT64},
/*output_shapes=*/{PartialTensorShape({4})}, /*output_shapes=*/{PartialTensorShape({4})},
/*node_name=*/"batch_dataset_v2"); /*node_name=*/"batch_dataset");
} }
// Test Case 8: test BatchDatasetV2 with an invalid batch size // Test Case 8: test BatchDatasetV2 with an invalid batch size
@ -113,7 +113,7 @@ BatchDatasetParams InvalidBatchSizeBatchDatasetParams() {
/*parallel_copy=*/false, /*parallel_copy=*/false,
/*output_dtypes=*/{DT_INT64}, /*output_dtypes=*/{DT_INT64},
/*output_shapes=*/{PartialTensorShape({3})}, /*output_shapes=*/{PartialTensorShape({3})},
/*node_name=*/"batch_dataset_v2"); /*node_name=*/"batch_dataset");
} }
std::vector<GetNextTestCase<BatchDatasetParams>> GetNextTestCases() { std::vector<GetNextTestCase<BatchDatasetParams>> GetNextTestCases() {

31
tensorflow/core/kernels/data/dataset_test_base.cc
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@ -688,7 +688,7 @@ Status DatasetOpsTestBaseV2::Initialize(DatasetParams& dataset_params) {
TF_RETURN_IF_ERROR(MakeDatasetTensor(pair.first.get(), &pair.second)); TF_RETURN_IF_ERROR(MakeDatasetTensor(pair.first.get(), &pair.second));
} }
gtl::InlinedVector<TensorValue, 4> inputs; gtl::InlinedVector<TensorValue, 4> inputs;
TF_RETURN_IF_ERROR(dataset_params.MakeInputs(&inputs)); TF_RETURN_IF_ERROR(dataset_params.GetInputs(&inputs));
TF_RETURN_IF_ERROR( TF_RETURN_IF_ERROR(
CreateDatasetContext(dataset_kernel_.get(), &inputs, &dataset_ctx_)); CreateDatasetContext(dataset_kernel_.get(), &inputs, &dataset_ctx_));
TF_RETURN_IF_ERROR( TF_RETURN_IF_ERROR(
@ -705,9 +705,9 @@ Status DatasetOpsTestBaseV2::MakeDatasetOpKernel(
name_utils::OpNameParams params; name_utils::OpNameParams params;
params.op_version = dataset_params.op_version(); params.op_version = dataset_params.op_version();
std::vector<string> input_placeholder; std::vector<string> input_placeholder;
TF_RETURN_IF_ERROR(dataset_params.MakeInputPlaceholder(&input_placeholder)); TF_RETURN_IF_ERROR(dataset_params.GetInputPlaceholder(&input_placeholder));
AttributeVector attributes; AttributeVector attributes;
TF_RETURN_IF_ERROR(dataset_params.MakeAttributes(&attributes)); TF_RETURN_IF_ERROR(dataset_params.GetAttributes(&attributes));
NodeDef node_def = test::function::NDef( NodeDef node_def = test::function::NDef(
dataset_params.node_name(), dataset_params.node_name(),
name_utils::OpName(ToString(dataset_params.type()), params), name_utils::OpName(ToString(dataset_params.type()), params),
@ -724,9 +724,9 @@ Status DatasetOpsTestBaseV2::MakeDatasetTensor(DatasetParams* dataset_params,
} }
AttributeVector attributes; AttributeVector attributes;
TF_RETURN_IF_ERROR(dataset_params->MakeAttributes(&attributes)); TF_RETURN_IF_ERROR(dataset_params->GetAttributes(&attributes));
gtl::InlinedVector<TensorValue, 4> inputs; gtl::InlinedVector<TensorValue, 4> inputs;
TF_RETURN_IF_ERROR(dataset_params->MakeInputs(&inputs)); TF_RETURN_IF_ERROR(dataset_params->GetInputs(&inputs));
std::vector<Tensor> input_tensors; std::vector<Tensor> input_tensors;
for (auto& tensor_value : inputs) { for (auto& tensor_value : inputs) {
input_tensors.emplace_back(*tensor_value.tensor); input_tensors.emplace_back(*tensor_value.tensor);
@ -756,7 +756,7 @@ Status DatasetOpsTestBaseV2::MakeDatasetTensorFunc(
case DatasetParamsType::Map: { case DatasetParamsType::Map: {
std::vector<string> input_placeholder; std::vector<string> input_placeholder;
TF_RETURN_IF_ERROR( TF_RETURN_IF_ERROR(
dataset_params.MakeInputPlaceholder(&input_placeholder)); dataset_params.GetInputPlaceholder(&input_placeholder));
bool has_other_args = input_placeholder.size() > 1; bool has_other_args = input_placeholder.size() > 1;
*fdef = test::function::MakeMapDataset(has_other_args); *fdef = test::function::MakeMapDataset(has_other_args);
break; break;
@ -808,26 +808,26 @@ RangeDatasetParams::RangeDatasetParams(int64 start, int64 stop, int64 step)
stop_(CreateTensor<int64>(TensorShape({}), {stop})), stop_(CreateTensor<int64>(TensorShape({}), {stop})),
step_(CreateTensor<int64>(TensorShape({}), {step})) {} step_(CreateTensor<int64>(TensorShape({}), {step})) {}
Status RangeDatasetParams::MakeInputs( Status RangeDatasetParams::GetInputs(
gtl::InlinedVector<TensorValue, 4>* inputs) { gtl::InlinedVector<TensorValue, 4>* inputs) {
*inputs = {TensorValue(&start_), TensorValue(&stop_), TensorValue(&step_)}; *inputs = {TensorValue(&start_), TensorValue(&stop_), TensorValue(&step_)};
return Status::OK(); return Status::OK();
} }
Status RangeDatasetParams::MakeInputPlaceholder( Status RangeDatasetParams::GetInputPlaceholder(
std::vector<string>* input_placeholder) const { std::vector<string>* input_placeholder) const {
*input_placeholder = {RangeDatasetOp::kStart, RangeDatasetOp::kStop, *input_placeholder = {RangeDatasetOp::kStart, RangeDatasetOp::kStop,
RangeDatasetOp::kStep}; RangeDatasetOp::kStep};
return Status::OK(); return Status::OK();
} }
Status RangeDatasetParams::MakeAttributes(AttributeVector* attr_vector) const { Status RangeDatasetParams::GetAttributes(AttributeVector* attr_vector) const {
*attr_vector = {{RangeDatasetOp::kOutputTypes, output_dtypes_}, *attr_vector = {{RangeDatasetOp::kOutputTypes, output_dtypes_},
{RangeDatasetOp::kOutputShapes, output_shapes_}}; {RangeDatasetOp::kOutputShapes, output_shapes_}};
return Status::OK(); return Status::OK();
} }
Status BatchDatasetParams::MakeInputs( Status BatchDatasetParams::GetInputs(
gtl::InlinedVector<TensorValue, 4>* inputs) { gtl::InlinedVector<TensorValue, 4>* inputs) {
inputs->reserve(input_dataset_params_group_.size()); inputs->reserve(input_dataset_params_group_.size());
for (auto& pair : input_dataset_params_group_) { for (auto& pair : input_dataset_params_group_) {
@ -844,7 +844,7 @@ Status BatchDatasetParams::MakeInputs(
return Status::OK(); return Status::OK();
} }
Status BatchDatasetParams::MakeInputPlaceholder( Status BatchDatasetParams::GetInputPlaceholder(
std::vector<string>* input_placeholder) const { std::vector<string>* input_placeholder) const {
*input_placeholder = {BatchDatasetOp::kInputDataset, *input_placeholder = {BatchDatasetOp::kInputDataset,
BatchDatasetOp::kBatchSize, BatchDatasetOp::kBatchSize,
@ -852,7 +852,7 @@ Status BatchDatasetParams::MakeInputPlaceholder(
return Status::OK(); return Status::OK();
} }
Status BatchDatasetParams::MakeAttributes(AttributeVector* attr_vector) const { Status BatchDatasetParams::GetAttributes(AttributeVector* attr_vector) const {
*attr_vector = {{BatchDatasetOp::kParallelCopy, parallel_copy_}, *attr_vector = {{BatchDatasetOp::kParallelCopy, parallel_copy_},
{BatchDatasetOp::kOutputTypes, output_dtypes_}, {BatchDatasetOp::kOutputTypes, output_dtypes_},
{BatchDatasetOp::kOutputShapes, output_shapes_}}; {BatchDatasetOp::kOutputShapes, output_shapes_}};
@ -861,8 +861,7 @@ Status BatchDatasetParams::MakeAttributes(AttributeVector* attr_vector) const {
int BatchDatasetParams::op_version() const { return op_version_; } int BatchDatasetParams::op_version() const { return op_version_; }
Status MapDatasetParams::MakeInputs( Status MapDatasetParams::GetInputs(gtl::InlinedVector<TensorValue, 4>* inputs) {
gtl::InlinedVector<TensorValue, 4>* inputs) {
inputs->reserve(input_dataset_params_group_.size()); inputs->reserve(input_dataset_params_group_.size());
for (auto& pair : input_dataset_params_group_) { for (auto& pair : input_dataset_params_group_) {
if (!IsDatasetTensor(pair.second)) { if (!IsDatasetTensor(pair.second)) {
@ -879,7 +878,7 @@ Status MapDatasetParams::MakeInputs(
return Status::OK(); return Status::OK();
} }
Status MapDatasetParams::MakeInputPlaceholder( Status MapDatasetParams::GetInputPlaceholder(
std::vector<string>* input_placeholder) const { std::vector<string>* input_placeholder) const {
input_placeholder->emplace_back(MapDatasetOp::kInputDataset); input_placeholder->emplace_back(MapDatasetOp::kInputDataset);
for (int i = 0; i < other_arguments_.size(); ++i) { for (int i = 0; i < other_arguments_.size(); ++i) {
@ -889,7 +888,7 @@ Status MapDatasetParams::MakeInputPlaceholder(
return Status::OK(); return Status::OK();
} }
Status MapDatasetParams::MakeAttributes(AttributeVector* attr_vector) const { Status MapDatasetParams::GetAttributes(AttributeVector* attr_vector) const {
*attr_vector = { *attr_vector = {
{MapDatasetOp::kFunc, func_}, {MapDatasetOp::kFunc, func_},
{MapDatasetOp::kTarguments, type_arguments_}, {MapDatasetOp::kTarguments, type_arguments_},

30
tensorflow/core/kernels/data/dataset_test_base.h
View File

@ -130,14 +130,14 @@ class DatasetParams {
~DatasetParams() {} ~DatasetParams() {}
// Returns the dataset input values as a TensorValue vector. // Returns the dataset input values as a TensorValue vector.
virtual Status MakeInputs(gtl::InlinedVector<TensorValue, 4>* inputs) = 0; virtual Status GetInputs(gtl::InlinedVector<TensorValue, 4>* inputs) = 0;
// Returns the dataset input names as a string vector. // Returns the dataset input names as a string vector.
virtual Status MakeInputPlaceholder( virtual Status GetInputPlaceholder(
std::vector<string>* input_placeholder) const = 0; std::vector<string>* input_placeholder) const = 0;
// Returns the dataset attributes as a vector. // Returns the dataset attributes as a vector.
virtual Status MakeAttributes(AttributeVector* attributes) const = 0; virtual Status GetAttributes(AttributeVector* attributes) const = 0;
// Checks if the tensor is a dataset variant tensor. // Checks if the tensor is a dataset variant tensor.
static bool IsDatasetTensor(const Tensor& tensor); static bool IsDatasetTensor(const Tensor& tensor);
@ -177,6 +177,8 @@ class DatasetParams {
int op_version_ = 1; int op_version_ = 1;
}; };
// `RangeDatasetParams` is a common dataset parameter type that are used in
// testing.
class RangeDatasetParams : public DatasetParams { class RangeDatasetParams : public DatasetParams {
public: public:
RangeDatasetParams(int64 start, int64 stop, int64 step, RangeDatasetParams(int64 start, int64 stop, int64 step,
@ -186,12 +188,12 @@ class RangeDatasetParams : public DatasetParams {
RangeDatasetParams(int64 start, int64 stop, int64 step); RangeDatasetParams(int64 start, int64 stop, int64 step);
Status MakeInputs(gtl::InlinedVector<TensorValue, 4>* inputs) override; Status GetInputs(gtl::InlinedVector<TensorValue, 4>* inputs) override;
Status MakeInputPlaceholder( Status GetInputPlaceholder(
std::vector<string>* input_placeholder) const override; std::vector<string>* input_placeholder) const override;
Status MakeAttributes(AttributeVector* attr_vector) const override; Status GetAttributes(AttributeVector* attr_vector) const override;
private: private:
Tensor start_; Tensor start_;
@ -199,6 +201,8 @@ class RangeDatasetParams : public DatasetParams {
Tensor step_; Tensor step_;
}; };
// `BatchDatasetParams` is a common dataset parameter type that are used in
// testing.
class BatchDatasetParams : public DatasetParams { class BatchDatasetParams : public DatasetParams {
public: public:
template <typename T> template <typename T>
@ -218,12 +222,12 @@ class BatchDatasetParams : public DatasetParams {
std::make_pair(std::move(input_dataset_params_ptr), Tensor())); std::make_pair(std::move(input_dataset_params_ptr), Tensor()));
} }
Status MakeInputs(gtl::InlinedVector<TensorValue, 4>* inputs) override; Status GetInputs(gtl::InlinedVector<TensorValue, 4>* inputs) override;
Status MakeInputPlaceholder( Status GetInputPlaceholder(
std::vector<string>* input_placeholder) const override; std::vector<string>* input_placeholder) const override;
Status MakeAttributes(AttributeVector* attr_vector) const override; Status GetAttributes(AttributeVector* attr_vector) const override;
int op_version() const override; int op_version() const override;
@ -234,6 +238,8 @@ class BatchDatasetParams : public DatasetParams {
int op_version_ = 2; int op_version_ = 2;
}; };
// `MapDatasetParams` is a common dataset parameter type that are used in
// testing.
class MapDatasetParams : public DatasetParams { class MapDatasetParams : public DatasetParams {
public: public:
template <typename T> template <typename T>
@ -258,12 +264,12 @@ class MapDatasetParams : public DatasetParams {
std::make_pair(std::move(input_dataset_params_ptr), Tensor())); std::make_pair(std::move(input_dataset_params_ptr), Tensor()));
} }
Status MakeInputs(gtl::InlinedVector<TensorValue, 4>* inputs) override; Status GetInputs(gtl::InlinedVector<TensorValue, 4>* inputs) override;
Status MakeInputPlaceholder( Status GetInputPlaceholder(
std::vector<string>* input_placeholder) const override; std::vector<string>* input_placeholder) const override;
Status MakeAttributes(AttributeVector* attr_vector) const override; Status GetAttributes(AttributeVector* attr_vector) const override;
std::vector<FunctionDef> func_lib() const override; std::vector<FunctionDef> func_lib() const override;