message: generalize axis for concat fusion
diff: @@ -2525,8 +2525,7 @@ struct Net::Impl : public detail::NetImplBase
  // (and so we eliminate the concatenation layer, because the channels
  // are concatenated implicitly).
  Ptr<ConcatLayer> concatLayer = ld.layerInstance.dynamicCast<ConcatLayer>();
  - if( !concatLayer.empty() && concatLayer->axis == 1 && !concatLayer->padding &&
  - ld.outputBlobs.size() == 1 )
  + if( !concatLayer.empty() && !concatLayer->padding && ld.outputBlobs.size() == 1 )
  {
  Mat& output = ld.outputBlobs[0];
  UMat umat_output;
  @@ -2563,7 +2562,8 @@ struct Net::Impl : public detail::NetImplBase
  // the concatenation optimization is applied with batch_size > 1.
  // so, for now, we only apply this optimization in the most popular
  // case batch_size == 1.
  - if( output.dims == 4 && output.size[0] == 1 )
  + int axis = clamp(concatLayer->axis, output.dims);
  + if( output.total(0, axis) == 1 )
  {
  size_t i, ninputs = ld.inputBlobsId.size();
  std::vector<LayerPin> realinputs(ninputs);
  @@ -2602,14 +2602,14 @@ struct Net::Impl : public detail::NetImplBase
  OpenCLBackendWrapper::update(ld.outputBlobsWrappers, umats);
  }
  #endif
  - Range chrange[] = { Range::all(), Range::all(), Range::all(), Range::all() };
  + std::vector<Range> chrange(output.dims, Range::all());
  int ofs = 0;
  for( i = 0; i < ninputs; i++ )
  {
  LayerPin pin = realinputs[i];
  LayerData* inp_i_data = &layers[pin.lid];
  - int channels_i = ld.inputBlobs[i]->size[1];
  - chrange[1] = Range(ofs, ofs + channels_i);
  + int channels_i = ld.inputBlobs[i]->size[axis];
  + chrange[axis] = Range(ofs, ofs + channels_i);
  printf_(("\toutput %s(%d) to channels (%d, %d)\n", inp_i_data->layerInstance->name.c_str(),
  pin.oid, ofs, ofs + channels_i));
  ofs += channels_i;
  