/////////////////////////////////////////////////////////////////////// // File: series.h // Description: Runs networks in series on the same input. // Author: Ray Smith // Created: Thu May 02 08:20:06 PST 2013 // // (C) Copyright 2013, 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_SERIES_H_ #define TESSERACT_LSTM_SERIES_H_ #include "plumbing.h" namespace tesseract { // Runs two or more networks in series (layers) on the same input. class Series : public Plumbing { public: // ni_ and no_ will be set by AddToStack. explicit Series(const STRING& name); virtual ~Series(); // Returns the shape output from the network given an input shape (which may // be partially unknown ie zero). virtual StaticShape OutputShape(const StaticShape& input_shape) const; virtual STRING spec() const { STRING spec("["); for (int i = 0; i < stack_.size(); ++i) spec += stack_[i]->spec(); spec += "]"; return spec; } // Sets up the network for training. Initializes weights using weights of // scale `range` picked according to the random number generator `randomizer`. // Returns the number of weights initialized. virtual int InitWeights(float range, TRand* randomizer); // Changes the number of outputs to the size of the given code_map, copying // the old weight matrix entries for each output from code_map[output] where // non-negative, and uses the mean (over all outputs) of the existing weights // for all outputs with negative code_map entries. Returns the new number of // weights. Only operates on Softmax layers with old_no outputs. int RemapOutputs(int old_no, const std::vector& code_map) override; // Sets needs_to_backprop_ to needs_backprop and returns true if // needs_backprop || any weights in this network so the next layer forward // can be told to produce backprop for this layer if needed. virtual bool SetupNeedsBackprop(bool needs_backprop); // 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. virtual int XScaleFactor() const; // Provides the (minimum) x scale factor to the network (of interest only to // input units) so they can determine how to scale bounding boxes. virtual void CacheXScaleFactor(int factor); // Runs forward propagation of activations on the input line. // See Network for a detailed discussion of the arguments. virtual void Forward(bool debug, const NetworkIO& input, const TransposedArray* input_transpose, NetworkScratch* scratch, NetworkIO* output); // Runs backward propagation of errors on the deltas line. // See Network for a detailed discussion of the arguments. virtual bool Backward(bool debug, const NetworkIO& fwd_deltas, NetworkScratch* scratch, NetworkIO* back_deltas); // Splits the series after the given index, returning the two parts and // deletes itself. The first part, up to network with index last_start, goes // into start, and the rest goes into end. void SplitAt(int last_start, Series** start, Series** end); // Appends the elements of the src series to this, removing from src and // deleting it. void AppendSeries(Network* src); }; } // namespace tesseract. #endif // TESSERACT_LSTM_SERIES_H_