[vulkan] Remove duplication of op registration and clean unused vars (pytorch#44932)

Summary: Pull Request resolved: pytorch#44932

Test Plan: Imported from OSS

Reviewed By: AshkanAliabadi

Differential Revision: D23778203

Pulled By: IvanKobzarev

fbshipit-source-id: d1bc0a5c2cdd711d8a4cd983154a4f6774987674

Author: IvanKobzarev

aten/src/ATen/native/vulkan/Vulkan.cpp

@@ -102,7 +102,6 @@ void VContext::createInstance() {
     };
 
     for (const auto& wantedLayer : instanceLayers) {
-      bool found = false;
       for (const auto& presentLayer : layerProps) {
         if (strcmp(wantedLayer, presentLayer.layerName) == 0) {
           enabledValidationLayers_.push_back(wantedLayer);
@@ -1038,7 +1037,6 @@ ComputeUnit& ComputeUnitFactory::get(
 // VBuffer <-> VImage
 void copy_buffer_to_image(const VBuffer& buffer, VImage& image) {
   const auto device = context().device();
-  const auto physicalDevice = context().physicalDevice();
   struct ConstBlock {
     int32_t w;
     int32_t h;
@@ -1095,7 +1093,6 @@ void copy_image_to_buffer(
     VBuffer& buffer,
     bool addBufferMemoryBarrierForHost) {
   const auto device = context().device();
-  const auto physicalDevice = context().physicalDevice();
   TORCH_INTERNAL_ASSERT(
       buffer.sizeBytes() >= image.capacityBytes(),
       "VulkanBuffer's capacity is less than VulkanImage capacity to copy from");

aten/src/ATen/native/vulkan/VulkanAten.cpp

@@ -523,14 +523,13 @@ Tensor mean(
 }
 
 TORCH_LIBRARY_IMPL(aten, Vulkan, m) {
-  m.impl("slice.Tensor", TORCH_FN(slice));
-  m.impl("reshape", TORCH_FN(reshape));
-  m.impl("select.int", TORCH_FN(select));
-  m.impl("transpose.int", TORCH_FN(transpose));
-  m.impl("_cat", TORCH_FN(cat));
-  m.impl_UNBOXED("transpose_", transpose_);
-  m.impl("view", TORCH_FN(view));
-  m.impl("unsqueeze", TORCH_FN(unsqueeze));
+  m.impl("slice.Tensor", TORCH_FN(at::native::vulkan::aten::slice));
+  m.impl("reshape", TORCH_FN(at::native::vulkan::aten::reshape));
+  m.impl("select.int", TORCH_FN(at::native::vulkan::aten::select));
+  m.impl("transpose.int", TORCH_FN(at::native::vulkan::aten::transpose));
+  m.impl_UNBOXED("transpose_", at::native::vulkan::aten::transpose_);
+  m.impl("view", TORCH_FN(at::native::vulkan::aten::view));
+  m.impl("unsqueeze", TORCH_FN(at::native::vulkan::aten::unsqueeze));
   m.impl_UNBOXED("empty.memory_format", at::native::vulkan::aten::empty);
   m.impl("empty_strided", TORCH_FN(at::native::vulkan::aten::empty_strided));
   m.impl("add.Tensor", TORCH_FN(at::native::vulkan::aten::add));
@@ -544,12 +543,11 @@ TORCH_LIBRARY_IMPL(aten, Vulkan, m) {
   m.impl(
       "_adaptive_avg_pool2d",
       TORCH_FN(at::native::vulkan::aten::adaptive_avg_pool2d));
-  m.impl("avg_pool2d", TORCH_FN(avg_pool2d));
+  m.impl("avg_pool2d", TORCH_FN(at::native::vulkan::aten::avg_pool2d));
   m.impl("max_pool2d", TORCH_FN(at::native::vulkan::aten::max_pool2d));
-  m.impl("reshape", TORCH_FN(at::native::vulkan::aten::reshape));
   m.impl("_cat", TORCH_FN(at::native::vulkan::aten::cat));
-  m.impl("mul.Scalar", TORCH_FN(mul_scalar));
-  m.impl("add.Scalar", TORCH_FN(add_scalar));
+  m.impl("mul.Scalar", TORCH_FN(at::native::vulkan::aten::mul_scalar));
+  m.impl("add.Scalar", TORCH_FN(at::native::vulkan::aten::add_scalar));
   m.impl_UNBOXED(
       "convolution_overrideable", at::native::vulkan::aten::convolution);
   m.impl_UNBOXED("hardtanh_", at::native::vulkan::aten::hardtanh_);

aten/src/ATen/native/vulkan/VulkanCommon.h

@@ -59,7 +59,6 @@ template <typename To, typename From>
 inline constexpr To safe_downcast_internal(const From v) {
   typedef std::common_type_t<From, To> Type;
   constexpr Type min{static_cast<Type>(std::numeric_limits<To>::lowest())};
-  const Type value{static_cast<Type>(v)};
   constexpr Type max{static_cast<Type>(std::numeric_limits<To>::max())};
   TORCH_CHECK(min <= v && v <= max, "Cast failed: out of range");
   return static_cast<To>(v);