Add aoti_torch_item_bool and aoti_torch_new_tensor_handle in AOTI…

Makefile

@@ -87,21 +87,22 @@
 #
 # ==============================================================================
 
-.PHONY: voxtral-cuda voxtral-cpu voxtral-metal whisper-cuda whisper-cpu whisper-metal llama-cpu llava-cpu gemma3-cuda gemma3-cpu clean help
+.PHONY: voxtral-cuda voxtral-cpu voxtral-metal whisper-cuda whisper-debug-cuda whisper-cpu whisper-metal llama-cpu llava-cpu gemma3-cuda gemma3-cpu clean help
 
 help:
-	@echo "This Makefile adds targets to build runners for various models on various backends. Run using `make <target>`. Available targets:"
-	@echo "  voxtral-cuda   - Build Voxtral runner with CUDA backend"
-	@echo "  voxtral-cpu    - Build Voxtral runner with CPU backend"
-	@echo "  voxtral-metal  - Build Voxtral runner with Metal backend (macOS only)"
-	@echo "  whisper-cuda   - Build Whisper runner with CUDA backend"
-	@echo "  whisper-cpu    - Build Whisper runner with CPU backend"
-	@echo "  whisper-metal  - Build Whisper runner with Metal backend (macOS only)"
-	@echo "  llama-cpu      - Build Llama runner with CPU backend"
-	@echo "  llava-cpu      - Build Llava runner with CPU backend"
-	@echo "  gemma3-cuda    - Build Gemma3 runner with CUDA backend"
-	@echo "  gemma3-cpu     - Build Gemma3 runner with CPU backend"
-	@echo "  clean          - Clean build artifacts"
+	@echo "This Makefile adds targets to build runners for various models on various backends. Run using \`make <target>\`. Available targets:"
+	@echo "  voxtral-cuda            - Build Voxtral runner with CUDA backend"
+	@echo "  voxtral-cpu             - Build Voxtral runner with CPU backend"
+	@echo "  voxtral-metal           - Build Voxtral runner with Metal backend (macOS only)"
+	@echo "  whisper-cuda            - Build Whisper runner with CUDA backend"
+	@echo "  whisper-debug-cuda      - Build Whisper runner with CUDA backend (debug mode)"
+	@echo "  whisper-cpu             - Build Whisper runner with CPU backend"
+	@echo "  whisper-metal           - Build Whisper runner with Metal backend (macOS only)"
+	@echo "  llama-cpu               - Build Llama runner with CPU backend"
+	@echo "  llava-cpu               - Build Llava runner with CPU backend"
+	@echo "  gemma3-cuda             - Build Gemma3 runner with CUDA backend"
+	@echo "  gemma3-cpu              - Build Gemma3 runner with CPU backend"
+	@echo "  clean                   - Clean build artifacts"
 
 voxtral-cuda:
 	@echo "==> Building and installing ExecuTorch with CUDA..."
@@ -139,6 +140,15 @@ whisper-cuda:
 	@echo "✓ Build complete!"
 	@echo "  Binary: cmake-out/examples/models/whisper/whisper_runner"
 
+whisper-debug-cuda:
+	@echo "==> Building and installing ExecuTorch with CUDA (debug mode)..."
+	cmake --workflow --preset llm-debug-cuda
+	@echo "==> Building Whisper runner with CUDA (debug mode)..."
+	cd examples/models/whisper && cmake --workflow --preset whisper-debug-cuda
+	@echo ""
+	@echo "✓ Build complete!"
+	@echo "  Binary: cmake-out/examples/models/whisper/whisper_runner"
+
 whisper-cpu:
 	@echo "==> Building and installing ExecuTorch..."
 	cmake --workflow --preset llm-release

backends/aoti/common_shims.h

@@ -59,11 +59,18 @@ aoti_torch_get_device_index(Tensor* tensor, int32_t* ret_device_index);
 AOTI_SHIM_EXPORT AOTITorchError
 aoti_torch_get_dim(Tensor* tensor, int64_t* ret_dim);
 
+// Device type query (optional; backends may implement this to return device
+// type constants such as CUDA). Declared here so common shims can dispatch
+// appropriately.
+AOTI_SHIM_EXPORT AOTITorchError
+aoti_torch_get_device_type(Tensor* tensor, int32_t* ret_device_type);
+
 // Utility functions for device and layout information
 AOTI_SHIM_EXPORT int32_t aoti_torch_device_type_cpu();
 AOTI_SHIM_EXPORT int32_t aoti_torch_layout_strided();
 AOTI_SHIM_EXPORT int32_t aoti_torch_dtype_float32();
 AOTI_SHIM_EXPORT int32_t aoti_torch_dtype_bfloat16();
+AOTI_SHIM_EXPORT int32_t aoti_torch_dtype_bool();
 AOTI_SHIM_EXPORT int32_t aoti_torch_dtype_int8();
 AOTI_SHIM_EXPORT int32_t aoti_torch_dtype_int16();
 AOTI_SHIM_EXPORT int32_t aoti_torch_dtype_int32();

backends/cuda/runtime/shims/memory.cpp

@@ -24,6 +24,7 @@ namespace executorch::backends::cuda {
 
 using executorch::aten::SizesType;
 using executorch::aten::StridesType;
+using executorch::backends::aoti::aoti_torch_dtype_bool;
 using executorch::backends::aoti::aoti_torch_get_device_index;
 using executorch::backends::aoti::aoti_torch_get_dtype;
 using executorch::backends::aoti::aoti_torch_get_sizes;
@@ -682,6 +683,50 @@ AOTITorchError aoti_torch__reinterpret_tensor(
   return Error::Ok;
 }
 
+// item implementation for scalar tensors
+AOTITorchError aoti_torch_item_bool(Tensor* tensor, bool* ret_value) {
+  // Validate that tensor is 0D
+  ET_CHECK_OR_RETURN_ERROR(
+      tensor->dim() == 0,
+      InvalidArgument,
+      "aoti_torch_item_bool failed: tensor is not 0D");
+
+  // Validate that tensor dtype is bool
+  int32_t dtype;
+  ET_CHECK_OK_OR_RETURN_ERROR(aoti_torch_get_dtype(tensor, &dtype));
+
+  ET_CHECK_OR_RETURN_ERROR(
+      dtype == aoti_torch_dtype_bool(), // PyTorch dtype code for bool
+      InvalidArgument,
+      "aoti_torch_item_bool failed: tensor dtype is not bool");
+
+  // Get the data pointer
+  const void* data_ptr = tensor->const_data_ptr();
+  ET_CHECK_OR_RETURN_ERROR(
+      data_ptr != nullptr,
+      InvalidArgument,
+      "aoti_torch_item_bool failed: tensor data pointer is null");
+
+  // Check if tensor is on CUDA or CPU
+  cudaPointerAttributes attributes{};
+  ET_CUDA_CHECK_OR_RETURN_ERROR(
+      cudaPointerGetAttributes(&attributes, data_ptr));
+
+  if (attributes.type == cudaMemoryTypeDevice) {
+    // CUDA memory case: copy from device to host
+    bool device_value;
+    ET_CUDA_CHECK_OR_RETURN_ERROR(cudaMemcpy(
+        &device_value, data_ptr, sizeof(bool), cudaMemcpyDeviceToHost));
+    *ret_value = device_value;
+  } else {
+    // CPU memory case: direct access
+    const bool* bool_ptr = static_cast<const bool*>(data_ptr);
+    *ret_value = *bool_ptr;
+  }
+
+  return Error::Ok;
+}
+
 AOTITorchError aoti_torch_new_tensor_handle(
     Tensor* orig_handle,
     Tensor** new_handle) {
@@ -771,6 +816,75 @@ AOTITorchError aoti_torch_new_tensor_handle(
 
   return Error::Ok;
 }
+
+AOTI_SHIM_EXPORT AOTITorchError
+aoti_torch_assign_tensors_out(Tensor* src, Tensor** ret_dst) {
+  if (src == nullptr || ret_dst == nullptr) {
+    return Error::InvalidArgument;
+  }
+
+  // Get the original data pointer from the source tensor
+  void* data_ptr = src->mutable_data_ptr();
+  ET_CHECK_OR_RETURN_ERROR(
+      data_ptr != nullptr,
+      InvalidArgument,
+      "Source tensor has null data pointer");
+
+  // Check if the given memory is in the map, if not return error
+  auto memory_it = memory_to_n_tensor.find(data_ptr);
+  ET_CHECK_OR_RETURN_ERROR(
+      memory_it != memory_to_n_tensor.end(),
+      InvalidArgument,
+      "Memory address %p is not being tracked by reference counting system",
+      data_ptr);
+
+  int32_t dtype = 0;
+  ET_CHECK_OK_OR_RETURN_ERROR(aoti_torch_get_dtype(src, &dtype));
+
+  std::vector<SizesType> sizes;
+  std::vector<StridesType> strides;
+
+  int64_t* view_sizes_ptr;
+  if (aoti_torch_get_sizes(src, &view_sizes_ptr) != Error::Ok) {
+    return Error::Internal;
+  }
+  int64_t* view_strides_ptr;
+  if (aoti_torch_get_strides(src, &view_strides_ptr) != Error::Ok) {
+    return Error::Internal;
+  }
+  sizes = convert_sizes_to_vector(src->dim(), view_sizes_ptr);
+  strides =
+      convert_strides_to_vector(src->dim(), view_sizes_ptr, view_strides_ptr);
+
+  // Create new tensor view that reinterprets the same memory with different
+  // shape/strides This creates a view, not a copy - the data pointer is shared
+  // Using CUDA-specific tensor maker that supports incontiguous tensors
+  std::shared_ptr<Tensor> tensor = make_tensor(
+      sizes, // New sizes with explicit SizesType
+      data_ptr, // Reuse the same memory from source tensor
+      {}, // dim_order (empty, will be auto-generated)
+      strides, // New strides with explicit StridesType
+      dtype_to_scalar_type(dtype) // Convert dtype with explicit type casting
+  );
+
+  ET_CHECK_OR_RETURN_ERROR(
+      tensor != nullptr,
+      InvalidArgument,
+      "Failed to create reinterpreted tensor view");
+
+  // Store the tensor so it doesn't get destroyed
+  tensors.insert(tensor);
+
+  *ret_dst = tensor.get();
+
+  // Increment the reference count for this memory address only if it is owned
+  // by tensor
+  memory_to_n_tensor[data_ptr] = memory_to_n_tensor[data_ptr] == NOT_OWN
+      ? NOT_OWN
+      : memory_to_n_tensor[data_ptr] + 1;
+
+  return Error::Ok;
+}
 } // extern "C"
 
 } // namespace executorch::backends::cuda

backends/cuda/runtime/shims/memory.h

@@ -161,9 +161,30 @@ aoti_torch_copy_(Tensor* self, Tensor* src, int32_t non_blocking);
  * @return Error::Ok on success, appropriate error code on failure:
  *         - Error::InvalidArgument: null pointers or invalid parameters
  */
-AOTITorchError aoti_torch_new_tensor_handle(
-    Tensor* orig_handle,
-    Tensor** new_handle);
+AOTI_SHIM_EXPORT AOTITorchError
+aoti_torch_new_tensor_handle(Tensor* orig_handle, Tensor** new_handle);
+
+// Function to retrieve boolean value from a 0D boolean tensor
+AOTI_SHIM_EXPORT AOTITorchError
+aoti_torch_item_bool(Tensor* tensor, bool* ret_value);
+
+/**
+ * Reinterprets the destination tensor to be a view of the source tensor's
+ * data.
+ *
+ * This function makes the destination tensor a view of the source tensor's
+ * underlying data, but with the destination tensor's original shape and
+ * strides. The number of elements in both tensors must match. The destination
+ * tensor handle will be updated to point to a new tensor view.
+ *
+ * @param src The source tensor providing the data.
+ * @param ret_dst On input, a pointer to the destination tensor. On output,
+ * this will be updated to point to the new tensor view.
+ *
+ * @return Error::Ok on success, appropriate error code on failure.
+ */
+AOTI_SHIM_EXPORT AOTITorchError
+aoti_torch_assign_tensors_out(Tensor* src, Tensor** ret_dst);
 
 // Function to clear all tensors from internal storage
 AOTI_SHIM_EXPORT void clear_all_tensors();

examples/models/whisper/CMakePresets.json

@@ -28,6 +28,20 @@
                 "rhs": "Linux"
             }
         },
+        {
+            "name": "whisper-debug-cuda",
+            "displayName": "Whisper runner (CUDA Debug)",
+            "inherits": ["whisper-base"],
+            "cacheVariables": {
+                "EXECUTORCH_BUILD_CUDA": "ON",
+                "CMAKE_BUILD_TYPE": "Debug"
+            },
+            "condition": {
+                "lhs": "${hostSystemName}",
+                "type": "equals",
+                "rhs": "Linux"
+            }
+        },
         {
             "name": "whisper-metal",
             "displayName": "Whisper runner (Metal)",
@@ -55,6 +69,12 @@
             "configurePreset": "whisper-cuda",
             "targets": ["whisper_runner"]
         },
+        {
+            "name": "whisper-debug-cuda",
+            "displayName": "Build Whisper runner (CUDA Debug)",
+            "configurePreset": "whisper-debug-cuda",
+            "targets": ["whisper_runner"]
+        },
         {
             "name": "whisper-metal",
             "displayName": "Build Whisper runner (Metal)",
@@ -91,6 +111,20 @@
                 }
             ]
         },
+        {
+            "name": "whisper-debug-cuda",
+            "displayName": "Configure and build Whisper runner (CUDA Debug)",
+            "steps": [
+                {
+                    "type": "configure",
+                    "name": "whisper-debug-cuda"
+                },
+                {
+                    "type": "build",
+                    "name": "whisper-debug-cuda"
+                }
+            ]
+        },
         {
             "name": "whisper-metal",
             "displayName": "Configure and build Whisper runner (Metal)",