Remove unnecessary CreateFrom

Author: alanwaketan

torch_xla/csrc/tensor.cpp

@@ -1242,42 +1242,15 @@ torch::lazy::Value XLATensor::MaybeCastIrValue(
 }
 
 XLATensorPtr XLATensor::CreateFrom(torch::lazy::Value ir_value) const {
-  ir_value = MaybeCastIrValue(std::move(ir_value), GetDevice(),
-                              /*logical_element_type=*/c10::nullopt);
   return Create(std::move(ir_value), GetDevice(), dtype_optional());
 }
 
-XLATensorPtr XLATensor::CreateFrom(
-    torch::lazy::Value ir_value,
-    const torch::lazy::BackendDevice& device) const {
-  ir_value = MaybeCastIrValue(std::move(ir_value), device,
-                              /*logical_element_type=*/c10::nullopt);
-  return Create(std::move(ir_value), device, dtype_optional());
-}
-
-XLATensorPtr XLATensor::CreateFrom(torch::lazy::Value ir_value,
-                                   at::ScalarType logical_element_type) const {
-  ir_value =
-      MaybeCastIrValue(std::move(ir_value), GetDevice(), logical_element_type);
-  return Create(std::move(ir_value), GetDevice(), logical_element_type);
-}
-
 XLATensorPtr XLATensor::CreateFrom(
     torch::lazy::Value ir_value,
     c10::optional<at::ScalarType> logical_element_type_opt) const {
-  ir_value = MaybeCastIrValue(std::move(ir_value), GetDevice(),
-                              logical_element_type_opt);
   return Create(std::move(ir_value), GetDevice(), logical_element_type_opt);
 }
 
-XLATensorPtr XLATensor::CreateFrom(torch::lazy::Value ir_value,
-                                   const torch::lazy::BackendDevice& device,
-                                   at::ScalarType logical_element_type) const {
-  ir_value =
-      MaybeCastIrValue(std::move(ir_value), device, logical_element_type);
-  return Create(std::move(ir_value), device, logical_element_type);
-}
-
 void XLATensor::ApplyPendingGraph() {
   DeviceBarrier(GetDevice());
   // This method is called to ensure that the tensor data is available on

torch_xla/csrc/tensor.h

@@ -1396,16 +1396,9 @@ class XLATensor : public c10::intrusive_ptr_target {
   // Create a new XLA tensor with the same metadata of the input tensor (with
   // possible overrides), and the new IR value.
   XLATensorPtr CreateFrom(torch::lazy::Value ir_value) const;
-  XLATensorPtr CreateFrom(torch::lazy::Value ir_value,
-                          const torch::lazy::BackendDevice& device) const;
-  XLATensorPtr CreateFrom(torch::lazy::Value ir_value,
-                          at::ScalarType logical_element_type) const;
   XLATensorPtr CreateFrom(
       torch::lazy::Value ir_value,
       c10::optional<at::ScalarType> logical_element_type_opt) const;
-  XLATensorPtr CreateFrom(torch::lazy::Value ir_value,
-                          const torch::lazy::BackendDevice& device,
-                          at::ScalarType logical_element_type) const;
 
   // We build an XLA graph accumulating XLA operations, but at a given point we
   // need to force a rendering, otherwise the graph can grow without control.

torch_xla/csrc/tensor_methods.cpp

@@ -1204,7 +1204,7 @@ XLATensorPtr XLATensor::full_like(const XLATensorPtr& input,
   } else {
     scalar_type = input->dtype();
   }
-  return input->CreateFrom(
+  return XLATensor::Create(
       GetIrValueForScalar(fill_value, tensor_shape, device), device,
       *scalar_type);
 }