84 lines
2.8 KiB
C++
84 lines
2.8 KiB
C++
/* Copyright 2020 The TensorFlow Authors. All Rights Reserved.
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Licensed under the Apache License, Version 2.0 (the "License");
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you may not use this file except in compliance with the License.
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You may obtain a copy of the License at
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http://www.apache.org/licenses/LICENSE-2.0
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Unless required by applicable law or agreed to in writing, software
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distributed under the License is distributed on an "AS IS" BASIS,
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WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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See the License for the specific language governing permissions and
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limitations under the License.
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==============================================================================*/
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#include <Python.h>
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#include "pybind11/pybind11.h"
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#include "pybind11/stl_bind.h"
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struct ConcreteFunction; // Forward declaration.
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// TODO(jlchu): Migrate Python characteristics to C++
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namespace tensorflow {
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namespace py = pybind11;
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struct PyConcreteFunction {
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PyConcreteFunction() {}
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py::object _build_call_outputs(py::object result,
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py::object structured_outputs,
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bool _ndarrays_list, bool _ndarray_singleton);
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};
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py::object PyConcreteFunction::_build_call_outputs(
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py::object result, py::object structured_outputs, bool _ndarrays_list,
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bool _ndarray_singleton) {
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static const py::module* nest =
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new py::module(py::module::import("tensorflow.python.util.nest"));
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// TODO(jlchu): Look into lazy loading of np_arrays module
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static const py::module* np_arrays = new py::module(
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py::module::import("tensorflow.python.ops.numpy_ops.np_arrays"));
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if (structured_outputs.is_none()) {
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return result;
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}
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// TODO(jlchu): Verify invariant -result = None only if
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// structured_outputs = None?
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py::list list_result = (py::list)result;
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if (!list_result.empty()) {
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if (_ndarrays_list) {
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py::list ndarr_result(list_result.size());
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for (int i = 0; i < ndarr_result.size(); ++i) {
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ndarr_result[i] = np_arrays->attr("tensor_to_ndarray")(list_result[i]);
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}
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return ndarr_result;
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} else if (_ndarray_singleton) {
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return np_arrays->attr("tensor_to_ndarray")(list_result[0]);
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}
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}
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// Replace outputs with results, skipping over any 'None' values.
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py::list outputs_list = nest->attr("flatten")(structured_outputs, true);
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int j = 0;
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for (int i = 0; i < outputs_list.size(); ++i) {
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if (!outputs_list[i].is_none()) {
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outputs_list[i] = list_result[j];
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++j;
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}
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}
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return nest->attr("pack_sequence_as")(structured_outputs, outputs_list, true);
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}
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PYBIND11_MODULE(_concrete_function, m) {
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py::class_<PyConcreteFunction>(m, "ConcreteFunction")
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.def(py::init<>())
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.def("_build_call_outputs", &PyConcreteFunction::_build_call_outputs);
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}
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} // namespace tensorflow
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