message: Logging LSTM: Remove redundant branches.
  The body of the two branches are equivalent considering the branching condition.
diff: @@ -252,27 +252,7 @@ inline void LstmStepWithAuxInput(
  // For each batch: update the projection and output_state. Note that since
  // the output batch rows may not be contiguous (output_batch_leading_dim !=
  - // n_output), we unroll the batched operations where this is the case.
  - if (output_batch_leading_dim == n_output) {
  - if (use_projection_weight) {
  - if (use_projection_bias) {
  - tensor_utils::VectorBatchVectorAssign(projection_bias_ptr, n_output,
  - n_batch, output_ptr_batch);
  - } else {
  - std::fill_n(output_ptr_batch, n_batch * n_output, 0.0f);
  - }
  - tensor_utils::MatrixBatchVectorMultiplyAccumulate(
  - projection_weights_ptr, n_output, n_cell, output_gate_scratch,
  - n_batch, output_ptr_batch, /*result_stride=*/1);
  - if (params->proj_clip > 0.0) {
  - tensor_utils::ClipVector(output_ptr_batch, n_batch * n_output,
  - params->proj_clip, output_ptr_batch);
  - }
  - } else {
  - std::copy_n(output_gate_scratch, n_batch * n_output, output_ptr_batch);
  - }
  - std::copy_n(output_ptr_batch, n_batch * n_output, output_state_ptr);
  - } else {
  + // n_output), we unroll batched operations.
  if (use_projection_weight) {
  if (use_projection_bias) {
  for (int k = 0; k < n_batch; k++) {
  @@ -294,8 +274,7 @@ inline void LstmStepWithAuxInput(
  if (params->proj_clip > 0.0) {
  tensor_utils::ClipVector(
  output_ptr_batch + k * output_batch_leading_dim, n_output,
  - params->proj_clip,
  - output_ptr_batch + k * output_batch_leading_dim);
  + params->proj_clip, output_ptr_batch + k * output_batch_leading_dim);
  }
  }
  } else {
  @@ -309,7 +288,6 @@ inline void LstmStepWithAuxInput(
  output_state_ptr + k * n_output);
  }
  }
  -}
  TfLiteStatus EvalFloat(
  const TfLiteTensor* input, const TfLiteTensor* input_to_input_weights,
  