diff --git a/lstm/lstmrecognizer.cpp b/lstm/lstmrecognizer.cpp
index babfe505ea..236455b411 100644
--- a/lstm/lstmrecognizer.cpp
+++ b/lstm/lstmrecognizer.cpp
@@ -280,7 +280,6 @@ bool LSTMRecognizer::RecognizeLine(const ImageData& image_data, bool invert,
   OutputStats(*outputs, &pos_min, &pos_mean, &pos_sd);
   if (invert && pos_min < 0.5) {
     // Run again inverted and see if it is any better.
-    float inv_scale;
     NetworkIO inv_inputs, inv_outputs;
     inv_inputs.set_int_mode(IsIntMode());
     SetRandomSeed();
@@ -460,7 +459,6 @@ void LSTMRecognizer::DisplayForward(const NetworkIO& inputs,
                                     const char* window_name,
                                     ScrollView** window) {
 #ifndef GRAPHICS_DISABLED  // do nothing if there's no graphics
-  int x_scale = network_->XScaleFactor();
   Pix* input_pix = inputs.ToPix();
   Network::ClearWindow(false, window_name, pixGetWidth(input_pix),
                        pixGetHeight(input_pix), window);
@@ -595,7 +593,6 @@ void LSTMRecognizer::LabelsViaThreshold(const NetworkIO& output,
   int width = output.Width();
   int t = 0;
   // Skip any initial non-char.
-  int label = null_char_;
   while (t < width && NullIsBest(output, null_thr, null_char_, t)) {
     ++t;
   }
@@ -688,7 +685,6 @@ BLOB_CHOICE_LIST* LSTMRecognizer::GetBlobChoices(
     int col, int row, bool debug, const NetworkIO& output,
     const UNICHARSET* target_unicharset, int x_start, int x_end,
     float score_ratio) {
-  int width = x_end - x_start;
   float rating = 0.0f, certainty = 0.0f;
   int label = output.BestChoiceOverRange(x_start, x_end, UNICHAR_SPACE,
                                          null_char_, &rating, &certainty);
diff --git a/lstm/lstmtrainer.cpp b/lstm/lstmtrainer.cpp
index c7defd0932..5865bc45b1 100644
--- a/lstm/lstmtrainer.cpp
+++ b/lstm/lstmtrainer.cpp
@@ -827,7 +827,6 @@ Trainability LSTMTrainer::PrepareForBackward(const ImageData* trainingdata,
     return UNENCODABLE;
   }
   targets->Resize(*fwd_outputs, network_->NumOutputs());
-  double text_error = 100.0;
   LossType loss_type = OutputLossType();
   if (loss_type == LT_SOFTMAX) {
     if (!ComputeTextTargets(*fwd_outputs, truth_labels, targets)) {
diff --git a/lstm/networkio.cpp b/lstm/networkio.cpp
index 4f29688cb0..b77f0ca373 100644
--- a/lstm/networkio.cpp
+++ b/lstm/networkio.cpp
@@ -696,7 +696,6 @@ void NetworkIO::MaxpoolTimeStep(int dest_t, const NetworkIO& src, int src_t,
 void NetworkIO::MaxpoolBackward(const NetworkIO& fwd,
                                 const GENERIC_2D_ARRAY<int>& maxes) {
   ASSERT_HOST(!int_mode_);
-  int width = fwd.Width();
   Zero();
   StrideMap::Index index(fwd.stride_map_);
   do {
diff --git a/lstm/parallel.cpp b/lstm/parallel.cpp
index adb9d84f15..516fe33a1a 100644
--- a/lstm/parallel.cpp
+++ b/lstm/parallel.cpp
@@ -89,7 +89,6 @@ void Parallel::Forward(bool debug, const NetworkIO& input,
       src_transpose = &transposed_input_;
     }
     // Run each network, putting the outputs into result.
-    int input_offset = 0;
     int out_offset = 0;
     for (int i = 0; i < stack_size; ++i) {
       stack_[i]->Forward(debug, input, src_transpose, scratch, result);
@@ -126,7 +125,6 @@ bool Parallel::Backward(bool debug, const NetworkIO& fwd_deltas,
     out_deltas.init_to_size(stack_size, NetworkScratch::IO());
     // Split the forward deltas for each stack element.
     int feature_offset = 0;
-    int out_offset = 0;
     for (int i = 0; i < stack_.size(); ++i) {
       int num_features = stack_[i]->NumOutputs();
       in_deltas[i].Resize(fwd_deltas, num_features, scratch);
@@ -153,7 +151,6 @@ bool Parallel::Backward(bool debug, const NetworkIO& fwd_deltas,
     // back_deltas.
     NetworkScratch::IO out_deltas;
     int feature_offset = 0;
-    int out_offset = 0;
     for (int i = 0; i < stack_.size(); ++i) {
       int num_features = stack_[i]->NumOutputs();
       in_deltas->CopyUnpacking(fwd_deltas, feature_offset, num_features);