[aoti-et] Add dtype bool support

Author: larryliu0820

backends/aoti/common_shims.cpp

@@ -184,6 +184,10 @@ int32_t aoti_torch_dtype_int32() {
   return 3; // PyTorch's int32 dtype code
 }
 
+int32_t aoti_torch_dtype_bool() {
+  return 11; // PyTorch's bool dtype code
+}
+
 int32_t aoti_torch_dtype_int64() {
   return 4; // PyTorch's int64 dtype code
 }

backends/aoti/common_shims.h

@@ -63,6 +63,7 @@ int32_t aoti_torch_dtype_int8();
 int32_t aoti_torch_dtype_int16();
 int32_t aoti_torch_dtype_int32();
 int32_t aoti_torch_dtype_int64();
+int32_t aoti_torch_dtype_bool();
 
 // Dtype utility function needed by Metal backend
 size_t aoti_torch_dtype_element_size(int32_t dtype);

backends/aoti/tests/test_common_shims.cpp

@@ -322,3 +322,14 @@ TEST_F(CommonShimsTest, IndependentCaches) {
   // Sizes and strides pointers should be different (different caches)
   EXPECT_NE(sizes_ptr1, strides_ptr1);
 }
+
+// Test all dtype functions return correct PyTorch dtype codes
+TEST_F(CommonShimsTest, AllDtypesReturnCorrectValues) {
+  EXPECT_EQ(aoti_torch_dtype_float32(), 6); // PyTorch's float32 dtype code
+  EXPECT_EQ(aoti_torch_dtype_bfloat16(), 15); // PyTorch's bfloat16 dtype code
+  EXPECT_EQ(aoti_torch_dtype_int8(), 1); // PyTorch's int8 dtype code
+  EXPECT_EQ(aoti_torch_dtype_int16(), 2); // PyTorch's int16 dtype code
+  EXPECT_EQ(aoti_torch_dtype_int32(), 3); // PyTorch's int32 dtype code
+  EXPECT_EQ(aoti_torch_dtype_int64(), 4); // PyTorch's int64 dtype code
+  EXPECT_EQ(aoti_torch_dtype_bool(), 11); // PyTorch's bool dtype code
+}

backends/aoti/utils.h

@@ -45,6 +45,8 @@ inline executorch::aten::ScalarType dtype_to_scalar_type(int32_t dtype) {
       return executorch::aten::ScalarType::Long;
     case 6: // PyTorch's float32 dtype code
       return executorch::aten::ScalarType::Float;
+    case 11: // PyTorch's bool dtype code
+      return executorch::aten::ScalarType::Bool;
     case 15: // PyTorch's bfloat16 dtype code
       return executorch::aten::ScalarType::BFloat16;
     // Future support for additional dtypes can be added here

backends/cuda/runtime/utils.h

@@ -62,6 +62,7 @@ enum class SupportedDTypes : int32_t {
   INT32 = 3, // PyTorch's int32 dtype code
   INT64 = 4, // PyTorch's int64 dtype code
   FLOAT32 = 6, // PyTorch's float32 dtype code
+  BOOL = 11, // PyTorch's bool dtype code
   BFLOAT16 = 15, // PyTorch's bfloat16 dtype code
 };
 
@@ -84,6 +85,7 @@ inline bool is_dtype_supported_in_et_cuda(int32_t dtype) {
     case static_cast<int32_t>(SupportedDTypes::INT32):
     case static_cast<int32_t>(SupportedDTypes::INT64):
     case static_cast<int32_t>(SupportedDTypes::FLOAT32):
+    case static_cast<int32_t>(SupportedDTypes::BOOL):
     case static_cast<int32_t>(SupportedDTypes::BFLOAT16):
       return true;
     default:
@@ -96,13 +98,14 @@ inline AOTITorchError validate_dtype(int32_t dtype) {
   ET_CHECK_OR_RETURN_ERROR(
       is_dtype_supported_in_et_cuda(dtype),
       InvalidArgument,
-      "Unsupported dtype: %d. Supported dtypes: %d (int8), %d (int16), %d (int32), %d (int64), %d (float32), %d (bfloat16)",
+      "Unsupported dtype: %d. Supported dtypes: %d (int8), %d (int16), %d (int32), %d (int64), %d (float32), %d (bool), %d (bfloat16)",
       dtype,
       static_cast<int32_t>(SupportedDTypes::INT8),
       static_cast<int32_t>(SupportedDTypes::INT16),
       static_cast<int32_t>(SupportedDTypes::INT32),
       static_cast<int32_t>(SupportedDTypes::INT64),
       static_cast<int32_t>(SupportedDTypes::FLOAT32),
+      static_cast<int32_t>(SupportedDTypes::BOOL),
       static_cast<int32_t>(SupportedDTypes::BFLOAT16));
 
   return Error::Ok;