// Copyright 2015 Google Inc. All rights reserved.
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//
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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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//
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// http://www.apache.org/licenses/LICENSE-2.0
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//
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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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#ifndef TENSORFLOW_CONTRIB_IOS_EXAMPLES_CAMERA_TENSORFLOW_UTILS_H_
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#define TENSORFLOW_CONTRIB_IOS_EXAMPLES_CAMERA_TENSORFLOW_UTILS_H_
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#include <memory>
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#include <vector>
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#include "third_party/tensorflow/core/public/session.h"
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#include "third_party/tensorflow/core/util/memmapped_file_system.h"
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#include "third_party/eigen3/unsupported/Eigen/CXX11/Tensor"
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// Reads a serialized GraphDef protobuf file from the bundle, typically
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// created with the freeze_graph script. Populates the session argument with a
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// Session object that has the model loaded.
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tensorflow::Status LoadModel(NSString* file_name, NSString* file_type,
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std::unique_ptr<tensorflow::Session>* session);
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// Loads a model from a file that has been created using the
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// convert_graphdef_memmapped_format tool. This bundles together a GraphDef
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// proto together with a file that can be memory-mapped, containing the weight
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// parameters for the model. This is useful because it reduces the overall
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// memory pressure, since the read-only parameter regions can be easily paged
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// out and don't count toward memory limits on iOS.
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tensorflow::Status LoadMemoryMappedModel(
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NSString* file_name, NSString* file_type,
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std::unique_ptr<tensorflow::Session>* session,
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std::unique_ptr<tensorflow::MemmappedEnv>* memmapped_env);
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// Takes a text file with a single label on each line, and returns a list.
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tensorflow::Status LoadLabels(NSString* file_name, NSString* file_type,
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std::vector<std::string>* label_strings);
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// Sorts the results from a model execution, and returns the highest scoring.
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void GetTopN(const Eigen::TensorMap<Eigen::Tensor<float, 1, Eigen::RowMajor>,
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Eigen::Aligned>& prediction,
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const int num_results, const float threshold,
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std::vector<std::pair<float, int> >* top_results);
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#endif // TENSORFLOW_CONTRIB_IOS_EXAMPLES_CAMERA_TENSORFLOW_UTILS_H_
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