[ET-VK] lowering ExecuTorch tensor dtype for Vulkan tensor dtype to enable 64bit

# Context

We are aligning with other delegate in how they handle 64bit output dtypes. In this case, we only previously had support for integers, but this is also adding support for doubles. We convert the values in place so that we can be more performant.

# Changes

Add a conversion from 64bit output to 32bit output so that its compatible with vulkan.

Differential Revision: [D77746134](https://our.internmc.facebook.com/intern/diff/D77746134/)

[ghstack-poisoned]

Author: morelos

backends/vulkan/runtime/VulkanBackend.cpp

@@ -599,12 +599,41 @@ class VulkanBackend final : public ::executorch::runtime::BackendInterface {
       if (compute_graph->val_is_tensor(oref)) {
         VK_CHECK_COND(args[o]->isTensor());
         maybe_resize_output(compute_graph, i, args[o]->toTensor());
+
+        // Get the Vulkan tensor dtype and ExecutorTorch tensor dtype
+        vTensorPtr vulkan_tensor = compute_graph->get_tensor(oref);
+        vkapi::ScalarType vulkan_dtype = vulkan_tensor->dtype();
+        executorch::aten::ScalarType et_dtype =
+            args[o]->toTensor().scalar_type();
+
         // args holds inputs directly followed by outputs, so the i'th output
         // for compute_graph corresponds to the o'th arg
         compute_graph->copy_from_staging(
             compute_graph->outputs()[i].staging,
             args[o]->toTensor().mutable_data_ptr(),
             args[o]->toTensor().numel());
+
+        // Handle dtype conversion between Vulkan and ExecutorTorch (in-place)
+        if (vulkan_dtype == vkapi::kFloat &&
+            et_dtype == executorch::aten::ScalarType::Double) {
+          // Convert float32 to float64 in-place (backwards to avoid overwriting)
+          double* data_64 = args[o]->toTensor().mutable_data_ptr<double>();
+          const float* data_32 = args[o]->toTensor().const_data_ptr<float>();
+          for (size_t j = args[o]->toTensor().numel() - 1; j >= 0; --j) {
+            data_64[j] = static_cast<double>(data_32[j]);
+            if (j == 0) break; // Prevent underflow for size_t
+          }
+        } else if (
+            vulkan_dtype == vkapi::kInt &&
+            et_dtype == executorch::aten::ScalarType::Long) {
+          // Convert int32 to int64 in-place (backwards to avoid overwriting)
+          int64_t* data_64 = args[o]->toTensor().mutable_data_ptr<int64_t>();
+          const int32_t* data_32 = args[o]->toTensor().const_data_ptr<int32_t>();
+          for (size_t j = args[o]->toTensor().numel() - 1; j >= 0; --j) {
+            data_64[j] = static_cast<int64_t>(data_32[j]);
+            if (j == 0) break; // Prevent underflow for size_t
+          }
+        }
       }
       // TensorRef values represent constant tensors which will not have been
       // modified by the graph execution. Therefore, if a constant tensor is