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///////////////////////////////////////////////////////////////////////
// File: reconfig.cpp
// Description: Network layer that reconfigures the scaling vs feature
// depth.
// 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.
///////////////////////////////////////////////////////////////////////
#include "reconfig.h"
namespace tesseract {
Reconfig::Reconfig(const char* name, int ni, int x_scale, int y_scale)
: Network(NT_RECONFIG, name, ni, ni * x_scale * y_scale),
x_scale_(x_scale), y_scale_(y_scale) {
}
// Returns the shape output from the network given an input shape (which may
// be partially unknown ie zero).
StaticShape Reconfig::OutputShape(const StaticShape& input_shape) const {
StaticShape result = input_shape;
result.set_height(result.height() / y_scale_);
result.set_width(result.width() / x_scale_);
if (type_ != NT_MAXPOOL)
result.set_depth(result.depth() * y_scale_ * x_scale_);
return result;
}
// 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 Reconfig::XScaleFactor() const {
return x_scale_;
}
// Writes to the given file. Returns false in case of error.
bool Reconfig::Serialize(TFile* fp) const {
return Network::Serialize(fp) &&
fp->Serialize(&x_scale_) &&
fp->Serialize(&y_scale_);
}
// Reads from the given file. Returns false in case of error.
bool Reconfig::DeSerialize(TFile* fp) {
if (!fp->DeSerialize(&x_scale_)) return false;
if (!fp->DeSerialize(&y_scale_)) return false;
no_ = ni_ * x_scale_ * y_scale_;
return true;
}
// Runs forward propagation of activations on the input line.
// See NetworkCpp for a detailed discussion of the arguments.
void Reconfig::Forward(bool debug, const NetworkIO& input,
const TransposedArray* input_transpose,
NetworkScratch* scratch, NetworkIO* output) {
output->ResizeScaled(input, x_scale_, y_scale_, no_);
back_map_ = input.stride_map();
StrideMap::Index dest_index(output->stride_map());
do {
int out_t = dest_index.t();
StrideMap::Index src_index(input.stride_map(), dest_index.index(FD_BATCH),
dest_index.index(FD_HEIGHT) * y_scale_,
dest_index.index(FD_WIDTH) * x_scale_);
// Stack x_scale_ groups of y_scale_ inputs together.
for (int x = 0; x < x_scale_; ++x) {
for (int y = 0; y < y_scale_; ++y) {
StrideMap::Index src_xy(src_index);
if (src_xy.AddOffset(x, FD_WIDTH) && src_xy.AddOffset(y, FD_HEIGHT)) {
output->CopyTimeStepGeneral(out_t, (x * y_scale_ + y) * ni_, ni_,
input, src_xy.t(), 0);
}
}
}
} while (dest_index.Increment());
}
// Runs backward propagation of errors on the deltas line.
// See NetworkCpp for a detailed discussion of the arguments.
bool Reconfig::Backward(bool debug, const NetworkIO& fwd_deltas,
NetworkScratch* scratch,
NetworkIO* back_deltas) {
back_deltas->ResizeToMap(fwd_deltas.int_mode(), back_map_, ni_);
StrideMap::Index src_index(fwd_deltas.stride_map());
do {
int in_t = src_index.t();
StrideMap::Index dest_index(back_deltas->stride_map(),
src_index.index(FD_BATCH),
src_index.index(FD_HEIGHT) * y_scale_,
src_index.index(FD_WIDTH) * x_scale_);
// Unstack x_scale_ groups of y_scale_ inputs that are together.
for (int x = 0; x < x_scale_; ++x) {
for (int y = 0; y < y_scale_; ++y) {
StrideMap::Index dest_xy(dest_index);
if (dest_xy.AddOffset(x, FD_WIDTH) && dest_xy.AddOffset(y, FD_HEIGHT)) {
back_deltas->CopyTimeStepGeneral(dest_xy.t(), 0, ni_, fwd_deltas,
in_t, (x * y_scale_ + y) * ni_);
}
}
}
} while (src_index.Increment());
return needs_to_backprop_;
}
} // namespace tesseract.
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