replace int with int64_t and rm truncate long/double to int/float in Var.cpp

Signed-off-by: Ruoqian Guo <[email protected]>

Author: ruoqianguo

core/conversion/converters/impl/select.cpp

@@ -28,7 +28,7 @@ bool add_split(ConversionCtx* ctx, const torch::jit::Node* n, args& args, bool s
     auto split_size = args[1].unwrapToInt();
     numOutputs = inDimSize / split_size;
     numRemainder = inDimSize % split_size;
-    for (int i = 0; i < numOutputs; i++) {
+    for (int64_t i = 0; i < numOutputs; i++) {
       sizes.push_back(split_size);
     }
     if (numRemainder) {
@@ -45,7 +45,7 @@ bool add_split(ConversionCtx* ctx, const torch::jit::Node* n, args& args, bool s
   list.reserve(numOutputs);
 
   int start_idx = 0;
-  for (int i = 0; i < numOutputs; i++) {
+  for (int64_t i = 0; i < numOutputs; i++) {
     at::Tensor indices = torch::arange(start_idx, start_idx + sizes[i], 1).to(torch::kI32);
     auto indicesTensor = tensor_to_const(ctx, indices);
 

core/conversion/var/Var.cpp

@@ -94,17 +94,10 @@ nvinfer1::ITensor* Var::ITensorOrFreeze(ConversionCtx* ctx) {
       "Requested either IValue containing a Tensor, or ITensor, however Var type is " << type_name());
 
   nvinfer1::ITensor* out;
-  auto weights = converters::Weights();
+
   if (isIValue()) {
     if (ptr_.ivalue->isTensor()) {
-      auto tensor = ptr_.ivalue->toTensor();
-      if (tensor.scalar_type() == at::kLong) {
-        weights = converters::Weights(ctx, tensor.toType(at::kInt));
-      } else if (tensor.scalar_type() == at::kDouble) {
-        weights = converters::Weights(ctx, tensor.toType(at::kFloat));
-      } else {
-        weights = converters::Weights(ctx, tensor);
-      }
+      auto weights = converters::Weights(ctx, ptr_.ivalue->toTensor());
 
       auto const_layer = ctx->net->addConstant(weights.shape, weights.data);
       TRTORCH_CHECK(const_layer, "Unable to freeze tensor into constant layer");