rename ort to maia (pytorch#123265)

Fixes pytorch#123264

Pull Request resolved: pytorch#123265
Approved by: https://github.com/albanD

Author: ashari4

aten/src/ATen/Context.h

@@ -12,9 +12,9 @@
 #include <ATen/detail/CUDAHooksInterface.h>
 #include <ATen/detail/HIPHooksInterface.h>
 #include <ATen/detail/IPUHooksInterface.h>
+#include <ATen/detail/MAIAHooksInterface.h>
 #include <ATen/detail/MPSHooksInterface.h>
 #include <ATen/detail/MTIAHooksInterface.h>
-#include <ATen/detail/ORTHooksInterface.h>
 #include <ATen/detail/PrivateUse1HooksInterface.h>
 #include <ATen/detail/XPUHooksInterface.h>
 #include <c10/core/QEngine.h>
@@ -142,8 +142,8 @@ class TORCH_API Context {
   static bool hasLazy() {
     return c10::impl::hasDeviceGuardImpl(c10::DeviceType::Lazy);
   }
-  static bool hasORT() {
-    return c10::impl::hasDeviceGuardImpl(c10::DeviceType::ORT);
+  static bool hasMAIA() {
+    return c10::impl::hasDeviceGuardImpl(c10::DeviceType::MAIA);
   }
   // defined in header so that getNonVariableType has ability to inline
   // call_once check. getNonVariableType is called fairly frequently
@@ -455,8 +455,8 @@ static inline bool hasMPS() {
   return globalContext().hasMPS();
 }
 
-static inline bool hasORT() {
-  return globalContext().hasORT();
+static inline bool hasMAIA() {
+  return globalContext().hasMAIA();
 }
 
 static inline bool hasXPU() {

aten/src/ATen/TensorIterator.cpp

@@ -1530,13 +1530,13 @@ void TensorIteratorBase::build(TensorIteratorConfig& config) {
 
   // XLA and lazy tensors don't have storage, so they don't have an underlying data pointer.
   // Nothing beyond this point is important for meta functions, so it's fine to exit early here.
-  // Extend the condition to ORT tesnors as ORT tensors also don't have storage.
+  // Extend the condition to MAIA tesnors as MAIA tensors also don't have storage.
   if (privateuse1_without_storage  ||
       common_device_.type() == DeviceType::MTIA ||
       common_device_.type() == DeviceType::XLA  ||
       common_device_.type() == DeviceType::IPU  ||
       common_device_.type() == DeviceType::Lazy ||
-      common_device_.type() == DeviceType::ORT  ||
+      common_device_.type() == DeviceType::MAIA  ||
       common_device_.type() == DeviceType::HPU) return;
 
   for (auto& op : operands_) {

aten/src/ATen/Version.cpp

@@ -190,8 +190,8 @@ std::string show_config() {
     ss << detail::getCUDAHooks().showConfig();
   }
 
-  if (hasORT()) {
-    ss << detail::getORTHooks().showConfig();
+  if (hasMAIA()) {
+    ss << detail::getMAIAHooks().showConfig();
   }
 
   if (hasXPU()) {

aten/src/ATen/core/TensorBase.h

@@ -507,10 +507,10 @@ class TORCH_API TensorBase {
     return impl_->is_mps();
   }
 
-  /// Returns if a `Tensor` is ort tensor.
-  bool is_ort() const {
+  /// Returns if a `Tensor` is maia tensor.
+  bool is_maia() const {
     // NB: this is not a native function to avoid dispatching overhead.
-    return impl_->is_ort();
+    return impl_->is_maia();
   }
 
   /// Returns if a `Tensor` is vulkan tensor.

aten/src/ATen/core/dispatch/OperatorEntry.cpp

@@ -421,7 +421,7 @@ void OperatorEntry::updateDispatchTable_(const c10::Dispatcher& dispatcher, Disp
   // In theory, we should only have to check if the given runtime key has "dense" functionality,
   // e.g. DispatchKey::CPU (which is composed of DispatchKey::Dense and BackendComponent::CPUBit).
   // However, there are some backends that should be included in this set that don't have the dense key set.
-  // E.g. DispatchKey::Meta, DispatchKey::ORT.
+  // E.g. DispatchKey::Meta, DispatchKey::MAIA.
   if (c10::isBackendDispatchKey(dispatch_key)) {
     DispatchKey autograd_key = getAutogradKeyFromBackend(toBackendComponent(dispatch_key));
     updateDispatchTableEntry_(dispatcher, autograd_key);

aten/src/ATen/core/op_registration/README.md

@@ -13,13 +13,13 @@ There’s four main use cases
 * You’re writing a new operator that isn’t supposed to be part of the public PyTorch API.
 * You’re writing a new operator but don’t want to change the core pytorch code base, say you’re developing a shared library with operators.
 * You’re writing a C++ extension for PyTorch or you’re using inline c++ in your .py model files.
-* You’re writing a backend library like XLA or ORT that adds new kernels to all operators defined in `native_functions.yaml`.
+* You’re writing a backend library like XLA or MAIA that adds new kernels to all operators defined in `native_functions.yaml`.
 
 For these use cases, the custom operator API is the better solution.
 
 ### What is the price for using the custom operator API instead of `native_functions.yaml`?
 
-If you’re just using the custom operator API to add new kernels for existing operators (e.g. the XLA/ORT example above), then you’re fine and don’t pay any price. If, however, you define a new operator purely using the custom op API, i.e. your operator never shows up in `native_functions.yaml`, then you need to be aware of a few caveats.
+If you’re just using the custom operator API to add new kernels for existing operators (e.g. the XLA/MAIA example above), then you’re fine and don’t pay any price. If, however, you define a new operator purely using the custom op API, i.e. your operator never shows up in `native_functions.yaml`, then you need to be aware of a few caveats.
 
 * It will not get a C++ API generated. There will not be `Tensor::your_op()` methods or `at::your_op()` functions to call your operator.
 * The API for calling the operator from Python looks a little bit different. It needs to be called through `torch.ops.your_op()` instead of `torch._C`.

aten/src/ATen/detail/MAIAHooksInterface.cpp

@@ -0,0 +1,29 @@
+#include <ATen/detail/MAIAHooksInterface.h>
+
+#include <c10/util/CallOnce.h>
+#include <c10/util/Registry.h>
+
+#include <cstddef>
+#include <memory>
+
+namespace at {
+namespace detail {
+
+// See getCUDAHooks for some more commentary
+const MAIAHooksInterface& getMAIAHooks() {
+  static std::unique_ptr<MAIAHooksInterface> maia_hooks;
+  static c10::once_flag once;
+  c10::call_once(once, [] {
+    maia_hooks = MAIAHooksRegistry()->Create("MAIAHooks", {});
+    if (!maia_hooks) {
+      maia_hooks = std::make_unique<MAIAHooksInterface>();
+    }
+  });
+  return *maia_hooks;
+}
+} // namespace detail
+
+// NOLINTNEXTLINE(cppcoreguidelines-avoid-non-const-global-variables)
+C10_DEFINE_REGISTRY(MAIAHooksRegistry, MAIAHooksInterface, MAIAHooksArgs)
+
+} // namespace at

aten/src/ATen/detail/MAIAHooksInterface.h

@@ -0,0 +1,31 @@
+#pragma once
+
+#include <c10/util/Exception.h>
+#include <c10/util/Registry.h>
+
+// NB: Class must live in `at` due to limitations of Registry.h.
+namespace at {
+
+struct TORCH_API MAIAHooksInterface {
+  // This should never actually be implemented, but it is used to
+  // squelch -Werror=non-virtual-dtor
+  virtual ~MAIAHooksInterface() = default;
+
+  virtual std::string showConfig() const {
+    TORCH_CHECK(false, "Cannot query detailed MAIA version information.");
+  }
+};
+
+// NB: dummy argument to suppress "ISO C++11 requires at least one argument
+// for the "..." in a variadic macro"
+struct TORCH_API MAIAHooksArgs {};
+
+TORCH_DECLARE_REGISTRY(MAIAHooksRegistry, MAIAHooksInterface, MAIAHooksArgs);
+#define REGISTER_MAIA_HOOKS(clsname) \
+  C10_REGISTER_CLASS(MAIAHooksRegistry, clsname, clsname)
+
+namespace detail {
+TORCH_API const MAIAHooksInterface& getMAIAHooks();
+} // namespace detail
+
+} // namespace at

aten/src/ATen/detail/ORTHooksInterface.cpp

@@ -6,8 +6,8 @@
 
 #include <torch/csrc/jit/runtime/operator.h>
 
-// NB. These tests use the ORT dispatch key to test backend dispatching
-// machinery, but these tests are not specific to ORT at all. The ORT
+// NB. These tests use the MAIA dispatch key to test backend dispatching
+// machinery, but these tests are not specific to MAIA at all. The MAIA
 // backend is fully out-of-tree, so it's safe to use this key for
 // in-tree tests.
 
@@ -22,16 +22,16 @@ Tensor empty_override(SymIntArrayRef size, c10::optional<ScalarType> dtype, c10:
       Storage(
           Storage::use_byte_size_t(),
           0,
-          at::DataPtr(nullptr, Device(DeviceType::ORT, 1)),
+          at::DataPtr(nullptr, Device(DeviceType::MAIA, 1)),
           nullptr,
           false),
-      DispatchKey::ORT,
+      DispatchKey::MAIA,
       caffe2::TypeMeta::Make<float>());
   return Tensor(std::move(tensor_impl));
 }
 
 Tensor add_override(const Tensor & a, const Tensor & b , const Scalar& c) {
-  auto out = empty({5, 5}, at::kORT);  // Don't return self as-is
+  auto out = empty({5, 5}, at::kMAIA);  // Don't return self as-is
   test_int = 2;
   return out;
 }
@@ -47,28 +47,28 @@ Tensor empty_strided_override(
   return empty_override(fromIntArrayRefSlow(size), dtype, layout, device, pin_memory, c10::nullopt);
 }
 
-TORCH_LIBRARY_IMPL(aten, ORT, m) {
+TORCH_LIBRARY_IMPL(aten, MAIA, m) {
   m.impl("aten::empty.memory_format",  empty_override);
   m.impl("aten::empty_strided",        empty_strided_override);
   m.impl("aten::add.Tensor",           add_override);
 }
 
 TEST(BackendExtensionTest, TestRegisterOp) {
-  Tensor a = empty({5, 5}, at::kORT);
-  ASSERT_EQ(a.device().type(), at::kORT);
+  Tensor a = empty({5, 5}, at::kMAIA);
+  ASSERT_EQ(a.device().type(), at::kMAIA);
   ASSERT_EQ(a.device().index(), 1);
   ASSERT_EQ(a.dtype(), caffe2::TypeMeta::Make<float>());
   ASSERT_EQ(test_int, 1);
 
-  Tensor b = empty_like(a, at::kORT);
-  ASSERT_EQ(b.device().type(), at::kORT);
+  Tensor b = empty_like(a, at::kMAIA);
+  ASSERT_EQ(b.device().type(), at::kMAIA);
   ASSERT_EQ(b.device().index(), 1);
   ASSERT_EQ(b.dtype(), caffe2::TypeMeta::Make<float>());
 
   add(a, b);
   ASSERT_EQ(test_int, 2);
 
-  // Ensure that non-ORT operator still works
+  // Ensure that non-MAIA operator still works
   Tensor d = empty({5, 5}, at::kCPU);
   ASSERT_EQ(d.device().type(), at::kCPU);
 }

aten/src/ATen/detail/ORTHooksInterface.h

@@ -947,7 +947,7 @@ aten_cpu_non_globed_sources = [
     "aten/src/ATen/detail/CUDAHooksInterface.cpp",
     "aten/src/ATen/detail/HIPHooksInterface.cpp",
     "aten/src/ATen/detail/MPSHooksInterface.cpp",
-    "aten/src/ATen/detail/ORTHooksInterface.cpp",
+    "aten/src/ATen/detail/MAIAHooksInterface.cpp",
     "aten/src/ATen/detail/PrivateUse1HooksInterface.cpp",
     "aten/src/ATen/detail/XPUHooksInterface.cpp",
     "aten/src/ATen/detail/MTIAHooksInterface.cpp",
@@ -964,7 +964,7 @@ aten_cpu_non_globed_headers = [
     "aten/src/ATen/detail/CUDAHooksInterface.h",
     "aten/src/ATen/detail/MPSHooksInterface.h",
     "aten/src/ATen/detail/HIPHooksInterface.h",
-    "aten/src/ATen/detail/ORTHooksInterface.h",
+    "aten/src/ATen/detail/MAIAHooksInterface.h",
     "aten/src/ATen/detail/PrivateUse1HooksInterface.h",
     "aten/src/ATen/detail/XPUHooksInterface.h",
     "aten/src/ATen/detail/MTIAHooksInterface.h",

aten/src/ATen/test/extension_backend_test.cpp

@@ -46,7 +46,7 @@ enum class Backend {
   SparseCsrVE,
   SparseCsrXPU,
   SparseCsrPrivateUse1,
-  ORT,
+  MAIA,
   XLA,
   Vulkan,
   Metal,
@@ -76,8 +76,8 @@ static inline Backend dispatchKeyToBackend(DispatchKey t) {
     return Backend::VE;
   } else if (t == DispatchKey::FPGA) {
     return Backend::FPGA;
-  } else if (t == DispatchKey::ORT) {
-    return Backend::ORT;
+  } else if (t == DispatchKey::MAIA) {
+    return Backend::MAIA;
   } else if (t == DispatchKey::XLA || t == DispatchKey::AutogradXLA) {
     return Backend::XLA;
   } else if (t == DispatchKey::Lazy || t == DispatchKey::AutogradLazy) {
@@ -154,8 +154,8 @@ static inline DispatchKey backendToDispatchKey(Backend b) {
       return DispatchKey::VE;
     case Backend::FPGA:
       return DispatchKey::FPGA;
-    case Backend::ORT:
-      return DispatchKey::ORT;
+    case Backend::MAIA:
+      return DispatchKey::MAIA;
     case Backend::XLA:
       return DispatchKey::XLA;
     case Backend::Lazy:
@@ -236,8 +236,8 @@ static inline DeviceType backendToDeviceType(Backend b) {
       return DeviceType::VE;
     case Backend::FPGA:
       return DeviceType::FPGA;
-    case Backend::ORT:
-      return DeviceType::ORT;
+    case Backend::MAIA:
+      return DeviceType::MAIA;
     case Backend::XLA:
       return DeviceType::XLA;
     case Backend::Lazy:
@@ -298,8 +298,8 @@ static inline const char* toString(Backend b) {
       return "XPU";
     case Backend::IPU:
       return "IPU";
-    case Backend::ORT:
-      return "ORT";
+    case Backend::MAIA:
+      return "MAIA";
     case Backend::XLA:
       return "XLA";
     case Backend::Lazy:

build_variables.bzl

@@ -26,7 +26,7 @@ DeviceType parse_type(const std::string& device_string) {
           {"hip", DeviceType::HIP},
           {"ve", DeviceType::VE},
           {"fpga", DeviceType::FPGA},
-          {"ort", DeviceType::ORT},
+          {"maia", DeviceType::MAIA},
           {"xla", DeviceType::XLA},
           {"lazy", DeviceType::Lazy},
           {"vulkan", DeviceType::Vulkan},

c10/core/Backend.h

@@ -142,9 +142,9 @@ struct C10_API Device final {
     return type_ == DeviceType::Metal;
   }
 
-  /// Return true if the device is of ORT type.
-  bool is_ort() const noexcept {
-    return type_ == DeviceType::ORT;
+  /// Return true if the device is of MAIA type.
+  bool is_maia() const noexcept {
+    return type_ == DeviceType::MAIA;
   }
 
   /// Return true if the device is of META type.