///////////////////////////////////////////////////////////////////////

// File:        input.h

// Description: Input layer class for neural network implementations.

// Author:      Ray Smith

//

// (C) Copyright 2014, Google Inc.

// 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 TESSERACT_LSTM_INPUT_H_

#define TESSERACT_LSTM_INPUT_H_

#include "network.h"

namespace tesseract {

class ScrollView;

class Input : public Network {

public:

  TESS_API

  Input(const std::string &name, int ni, int no);

  TESS_API

  Input(const std::string &name, const StaticShape &shape);

  ~Input() override = default;

  std::string spec() const override {

    return std::to_string(shape_.batch()) + "," +

           std::to_string(shape_.height()) + "," +

           std::to_string(shape_.width()) + "," +

           std::to_string(shape_.depth());

  }

  // Returns the required shape input to the network.

  StaticShape InputShape() const override {

    return shape_;

  }

  // Returns the shape output from the network given an input shape (which may

  // be partially unknown ie zero).

  StaticShape OutputShape(

      [[maybe_unused]] const StaticShape &input_shape) const override {

    return shape_;

  }

  // Writes to the given file. Returns false in case of error.

  // Should be overridden by subclasses, but called by their Serialize.

  bool Serialize(TFile *fp) const override;

  // Reads from the given file. Returns false in case of error.

  bool DeSerialize(TFile *fp) override;

  // Returns an integer reduction factor that the network applies to the

  // time sequence. Assumes that any 2-d is already eliminated. Used for

  // scaling bounding boxes of truth data.

  // WARNING: if GlobalMinimax is used to vary the scale, this will return

  // the last used scale factor. Call it before any forward, and it will return

  // the minimum scale factor of the paths through the GlobalMinimax.

  int XScaleFactor() const override;

  // Provides the (minimum) x scale factor to the network (of interest only to

  // input units) so they can determine how to scale bounding boxes.

  void CacheXScaleFactor(int factor) override;

  // Runs forward propagation of activations on the input line.

  // See Network for a detailed discussion of the arguments.

  void Forward(bool debug, const NetworkIO &input,

               const TransposedArray *input_transpose, NetworkScratch *scratch,

               NetworkIO *output) override;

  // Runs backward propagation of errors on the deltas line.

  // See Network for a detailed discussion of the arguments.

  bool Backward(bool debug, const NetworkIO &fwd_deltas,

                NetworkScratch *scratch, NetworkIO *back_deltas) override;

  // Creates and returns a Pix of appropriate size for the network from the

  // image_data. If non-null, *image_scale returns the image scale factor used.

  // Returns nullptr on error.

  /* static */

  static Image PrepareLSTMInputs(const ImageData &image_data,

                                 const Network *network, int min_width,

                                 TRand *randomizer, float *image_scale);

  // Converts the given pix to a NetworkIO of height and depth appropriate to

  // the given StaticShape:

  // If depth == 3, convert to 24 bit color, otherwise normalized grey.

  // Scale to target height, if the shape's height is > 1, or its depth if the

  // height == 1. If height == 0 then no scaling.

  // NOTE: It isn't safe for multiple threads to call this on the same pix.

  static void PreparePixInput(const StaticShape &shape, const Image pix,

                              TRand *randomizer, NetworkIO *input);

private:

  void DebugWeights() override {

    tprintf("Must override Network::DebugWeights for type %d\n", type_);

  }

  // Input shape determines how images are dealt with.

  StaticShape shape_;

  // Cached total network x scale factor for scaling bounding boxes.

  int cached_x_scale_;

};

} // namespace tesseract.

#endif // TESSERACT_LSTM_INPUT_H_