Fixed modules using values instead of embeddings

torch_modules/src/NumericColumnModule.cpp

@@ -42,8 +42,7 @@ NumericColumnModuleImpl::NumericColumnModuleImpl(std::string name, const std::st
 torch::Tensor NumericColumnModuleImpl::forward(torch::Tensor input)
 {
   auto context = input.narrow(1, firstInputIndex, getInputSize());
-  void * dataPtr = context.flatten().data_ptr();
-  auto values = torch::from_blob(dataPtr, {(long)(context.size(0)*getInputSize())}, torch::TensorOptions(torch::kDouble).requires_grad(false).device(NeuralNetworkImpl::device)).clone().to(torch::kFloat).view({(long)context.size(0), (long)context.size(1), 1});
+  auto values = torch::from_blob(context.data_ptr(), context.sizes(), context.strides(), torch::TensorOptions(torch::kDouble).requires_grad(false).device(NeuralNetworkImpl::device)).to(torch::kFloat).unsqueeze(-1).clone();
   return myModule->forward(values);
 }
 

torch_modules/src/UppercaseRateModule.cpp

@@ -40,8 +40,7 @@ UppercaseRateModuleImpl::UppercaseRateModuleImpl(std::string name, const std::st
 torch::Tensor UppercaseRateModuleImpl::forward(torch::Tensor input)
 {
   auto context = input.narrow(1, firstInputIndex, getInputSize());
-  void * dataPtr = context.flatten().data_ptr();
-  auto values = torch::from_blob(dataPtr, {(long)(context.size(0)*getInputSize())}, torch::TensorOptions(torch::kDouble).requires_grad(false).device(NeuralNetworkImpl::device)).clone().to(torch::kFloat).view({(long)context.size(0), (long)context.size(1), 1});
+  auto values = torch::from_blob(context.data_ptr(), context.sizes(), context.strides(), torch::TensorOptions(torch::kDouble).requires_grad(false).device(NeuralNetworkImpl::device)).to(torch::kFloat).unsqueeze(-1).clone();
   return myModule->forward(values);
 }