--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/mupdf-source/thirdparty/tesseract/src/lstm/reconfig.cpp	Mon Sep 15 11:43:07 2025 +0200
@@ -0,0 +1,116 @@
+///////////////////////////////////////////////////////////////////////
+// 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 std::string &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.