/* Copyright 2015 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.
==============================================================================*/

#ifndef TENSORFLOW_CORE_FRAMEWORK_FAKE_INPUT_H_
#define TENSORFLOW_CORE_FRAMEWORK_FAKE_INPUT_H_

#include "tensorflow/core/framework/node_def_builder.h"
#include "tensorflow/core/framework/types.h"

namespace tensorflow {

// These functions return values that may be passed to
// NodeDefBuilder::Input() to add an input for a test.  Use them when
// you don't care about the node names/output indices providing the
// input.  They also allow you to omit the input types and/or
// list length when they may be inferred.
FakeInputFunctor FakeInput();  // Infer everything
FakeInputFunctor FakeInput(DataType dt);
FakeInputFunctor FakeInput(int n);  // List of length n
FakeInputFunctor FakeInput(int n, DataType dt);
FakeInputFunctor FakeInput(DataTypeSlice dts);
inline FakeInputFunctor FakeInput(std::initializer_list<DataType> dts) {
  return FakeInput(DataTypeSlice(dts));
}

}  // namespace tensorflow

#endif  // TENSORFLOW_CORE_FRAMEWORK_FAKE_INPUT_H_