[REFACTOR][TIR] Migrate most of low-level build to use the Pass Manag…

…er. (apache#5225)

* [REFACTOR][TIR] Migrate most of low-level build to use the Pass Manager.

- SplitHostDevice
- ThreadSync
- BindDevice
- LowerThreadAllreduce
- Provide a temp fix for printing IRModule with PrimFunc before the formal text printer.

* Address comments, fix tests.

* Fix relay tests

* Explicit move

include/tvm/ir/function.h

@@ -46,20 +46,20 @@ enum class CallingConv : int {
    * - Implementation: specified by the native target.
    */
   kDefault = 0,
+  /*!
+   * \brief PackedFunc that exposes a CPackedFunc signature.
+   *
+   * - Calling by PackedFunc calling convention.
+   * - Implementation: Expose a function with the CPackedFunc signature.
+   */
+  kCPackedFunc = 1,
   /*!
    * \brief Device kernel launch
    *
    * - Call by PackedFunc calling convention.
    * - Implementation: defined by device runtime(e.g. runtime/cuda)
    */
   kDeviceKernelLaunch = 2,
-  /*!
-   * \brief PackedFunc that exposes a CPackedFunc signature.
-   *
-   * - Calling by PackedFunc calling convention.
-   * - Implementation: Expose a function with the CPackedFunc signature.
-   */
-  kCPackedFunc = 3,
 };
 
 /*!

include/tvm/ir/module.h

@@ -324,6 +324,8 @@ class IRModule : public ObjectRef {
 
   /*! \brief Declare the container type. */
   using ContainerType = IRModuleNode;
+  // allow copy on write.
+  TVM_DEFINE_OBJECT_REF_COW_METHOD(IRModuleNode);
 };
 
 /*!

include/tvm/tir/analysis.h

@@ -49,6 +49,16 @@ struct ExprDeepEqual {
  public:
   TVM_DLL bool operator()(const PrimExpr& lhs, const PrimExpr& rhs) const;
 };
+
+
+/*!
+ * \brief Find undefined vars in the statment.
+ * \param stmt The function to be checked.
+ * \param defs The vars that is defined.
+ * \return Array of undefined vars.
+ */
+Array<Var> UndefinedVars(const Stmt& stmt, const Array<Var>& defs);
+
 }  // namespace tir
 }  // namespace tvm
 #endif  // TVM_TIR_ANALYSIS_H_

include/tvm/tir/ir_pass.h

@@ -406,56 +406,6 @@ LoweredFunc MakeAPI(Stmt body,
                     int num_unpacked_args,
                     bool is_restricted);
 
-/*!
- * \brief Bind the device type of host function to be device_type.
- * \param func The function to be binded.
- * \param device_type The device type to be binded.
- * \return The binded function.
- */
-LoweredFunc BindDeviceType(LoweredFunc func,
-                           int device_type);
-/*!
- * \brief Find undefined vars in the statment.
- * \param stmt The function to be checked.
- * \param defs The vars that is defined.
- * \return Array of undefined vars.
- */
-Array<Var> UndefinedVars(const Stmt& stmt, const Array<Var>& defs);
-
-/*!
- * \brief Split the function into a host function and device functions.
- * \param func The function to be splitted.
- *
- * \return Array of functions, the first one is host function,
- *     the others are device functions.
- */
-Array<LoweredFunc> SplitHostDevice(LoweredFunc func);
-
-/*!
- * \brief Insert sync between parallel read/write of shared buffers.
- *
- * \param stmt The stmt to be trasnformed.
- * \param storage_scope The storage scope considered.
- */
-LoweredFunc ThreadSync(LoweredFunc stmt, std::string storage_scope);
-
-/*!
- * \brief Lower cross thread alleduce in the stmt.
- * \param f The device function to be lowered.
- * \param warp_size the size of warp where no sync is needed.
- * \return Transformed function.
- */
-LoweredFunc LowerThreadAllreduce(LoweredFunc f, int warp_size);
-
-/*!
- * \brief Lower warp memory in stmt.
- * \param f The device function to be lowered.
- * \param warp_size the size of warp where no sync is needed.
- *        this function will only take in effect if warp_size is bigger than one.
- * \return Transformed function.
- */
-LoweredFunc LowerWarpMemory(LoweredFunc f, int warp_size);
-
 /*!
  * \brief Remap the thread axis
  *
@@ -470,26 +420,6 @@ LoweredFunc LowerWarpMemory(LoweredFunc f, int warp_size);
  */
 LoweredFunc RemapThreadAxis(LoweredFunc f, Map<PrimExpr, IterVar> axis_map);
 
-/*!
- * \brief Lower packed function call.
- * \param f The function to be lowered.
- * \return Transformed function.
- */
-LoweredFunc LowerTVMBuiltin(LoweredFunc f);
-
-
-/*!
- * \brief Rewrite the pointer content type of arguments,
- *  as well as Alloc internal to the function to use
- *  the most frequently accessed type for load/store
- *  to avoid pointer casting in backend when possible.
- *
- * \note implemeneted in storage_rewrite.cc
- * \param f The function to be trasnformed
- * \return Transformed function.
- */
-LoweredFunc PointerValueTypeRewrite(LoweredFunc f);
-
 /*!
  * \brief Rewrite the pointer content type of arguments,
  *  as well as Alloc internal to the function to use
@@ -513,14 +443,6 @@ PrimFunc PointerValueTypeRewrite(PrimFunc f);
  */
 LoweredFunc LowerCustomDatatypes(LoweredFunc f, const std::string& target);
 
-/*!
- * \brief Infer the TensorCore fragment infomation using tensor intrinsics
- *
- * \param f The device function to be lowered.
- * \return Transformed function.
- */
-LoweredFunc InferFragment(LoweredFunc f);
-
 /*!
  * \brief Verify if memory accesses are legal for a specific target device type.
  *

include/tvm/tir/transform.h

@@ -58,6 +58,21 @@ TVM_DLL Pass CreatePrimFuncPass(const runtime::TypedPackedFunc<
                                 const std::string& name,
                                 const tvm::Array<tvm::PrimExpr>& required);
 
+/*!
+ * \brief Bind the device type ofthe function to be
+ *        the device_type specified in the target attribute.
+ *
+ * \return The pass.
+ */
+TVM_DLL Pass BindDeviceType();
+
+/*!
+ * \brief Split the function into a host function and device functions.
+ *
+ * \return The pass.
+ */
+TVM_DLL Pass SplitHostDevice();
+
 /*!
  * \brief skip assert stmt.
  *

python/tvm/driver/build_module.py

@@ -14,6 +14,8 @@
 # KIND, either express or implied.  See the License for the
 # specific language governing permissions and limitations
 # under the License.
+
+# pylint: disable=invalid-name
 """The build utils in python.
 
 This module provides the functions to transform schedule to
@@ -25,6 +27,7 @@
 
 from tvm.runtime import ndarray
 from tvm.ir import container
+from tvm.ir import CallingConv
 from tvm.target import codegen, BuildConfig
 from tvm.tir import ir_pass
 from tvm.tir.stmt import LoweredFunc
@@ -222,75 +225,59 @@ def _build_for_device(flist, target, target_host):
     mdev : tvm.module
         A module that contains device code.
     """
-    @tvm.tir.transform.prim_func_pass(opt_level=0)
-    class BindTarget:
-        def __init__(self, target):
-            self.target = target
-
-        # pylint: disable=unused-argument
-        def transform_function(self, func, mod, ctx):
-            return func.with_attr("target", self.target)
-
     target = _target.create(target)
+    target_host = _target.create(target_host)
     device_type = ndarray.context(target.target_name, 0).device_type
-    fhost = []
-    fdevice = []
+
     for func in flist:
         if not ir_pass.VerifyMemory(func, device_type):
             raise ValueError(
                 "Direct host side access to device memory is detected in %s. "
                 "Did you forget to bind?" % func.name)
-        if func.func_type == LoweredFunc.MixedFunc:
-            if BuildConfig.current().detect_global_barrier:
-                func = ir_pass.ThreadSync(func, "global")
-            func = ir_pass.ThreadSync(func, "shared")
-            func = ir_pass.ThreadSync(func, "warp")
-            func = ir_pass.InferFragment(func)
-            warp_size = target.thread_warp_size
-            func = ir_pass.LowerThreadAllreduce(func, warp_size)
-            fsplits = list(ir_pass.SplitHostDevice(func))
-            fhost.append(fsplits[0])
-            for x in fsplits[1:]:
-                fdevice.append(x)
-        elif func.func_type == LoweredFunc.HostFunc:
-            fhost.append(func)
-        elif func.func_type == LoweredFunc.DeviceFunc:
-            fdevice.append(func)
-        else:
-            raise ValueError("unknown function type %d" % func.func_type)
-
-    if "gpu" in target.keys and not fdevice:
-        warnings.warn(
-            "Specified target %s, but cannot find device code, did you do "
-            "bind?" % target)
 
-    fhost = [ir_pass.BindDeviceType(x, device_type) for x in fhost]
+    mod_mixed = tvm.testing.LoweredFuncsToIRModule(flist)
+    opt_mixed = [tvm.tir.transform.Apply(lambda f: f.with_attr("target", target))]
+    if BuildConfig.current().detect_global_barrier:
+        opt_mixed += [tvm.tir.transform.ThreadSync("global")]
+    opt_mixed += [tvm.tir.transform.ThreadSync("shared"),
+                  tvm.tir.transform.ThreadSync("warp"),
+                  tvm.tir.transform.InferFragment(),
+                  tvm.tir.transform.LowerThreadAllreduce(),
+                  tvm.tir.transform.BindDeviceType(),
+                  tvm.tir.transform.SplitHostDevice()]
+    mod_mixed = tvm.ir.transform.Sequential(opt_mixed)(mod_mixed)
 
-    if device_type == ndarray.cpu(0).device_type and target_host == target:
-        assert not fdevice
-
-    target_host = _target.create(target_host)
 
     # device optimizations
-    mod_dev = tvm.testing.LoweredFuncsToIRModule(fdevice)
     opt_device = tvm.ir.transform.Sequential(
-        [BindTarget(target),
+        [tvm.tir.transform.Filter(
+            lambda f: "calling_conv" in f.attrs and
+            f.attrs["calling_conv"].value == CallingConv.DEVICE_KERNEL_LAUNCH),
          tvm.tir.transform.LowerWarpMemory(),
          tvm.tir.transform.LowerDeviceStorageAccessInfo(),
          tvm.tir.transform.LowerIntrin()])
-    mod_dev = opt_device(mod_dev)
+    mod_dev = opt_device(mod_mixed)
 
     # host optimizations
-    mod_host = tvm.testing.LoweredFuncsToIRModule(fhost)
     opt_host = tvm.ir.transform.Sequential(
-        [BindTarget(target_host),
+        [tvm.tir.transform.Filter(
+            lambda f: "calling_conv" not in f.attrs or
+            f.attrs["calling_conv"].value != CallingConv.DEVICE_KERNEL_LAUNCH),
+         tvm.tir.transform.Apply(lambda f: f.with_attr("target", target)),
          tvm.tir.transform.LowerTVMBuiltin(),
          tvm.tir.transform.LowerDeviceStorageAccessInfo(),
          tvm.tir.transform.LowerIntrin(),
          tvm.tir.transform.CombineContextCall()])
-    mod_host = opt_host(mod_host)
+    mod_host = opt_host(mod_mixed)
+
+    if device_type == ndarray.cpu(0).device_type and target_host == target:
+        assert len(mod_dev.functions) == 0
+    if "gpu" in target.keys and len(mod_dev.functions) == 0:
+        warnings.warn(
+            "Specified target %s, but cannot find device code, did you do "
+            "bind?" % target)
 
-    rt_mod_dev = codegen.build_module(mod_dev, target) if fdevice else None
+    rt_mod_dev = codegen.build_module(mod_dev, target) if len(mod_dev.functions) != 0 else None
     return mod_host, rt_mod_dev
 
 

python/tvm/ir/__init__.py

@@ -23,7 +23,7 @@
 from .tensor_type import TensorType
 from .type_relation import TypeCall, TypeRelation
 from .expr import BaseExpr, PrimExpr, RelayExpr, GlobalVar, Range
-from .function import BaseFunc
+from .function import CallingConv, BaseFunc
 from .adt import Constructor, TypeData
 from .module import IRModule
 from .attrs import Attrs, DictAttrs, make_node

python/tvm/ir/function.py

@@ -15,10 +15,18 @@
 # specific language governing permissions and limitations
 # under the License.
 """Function defintiions."""
+from enum import IntEnum
 from .expr import RelayExpr
 from . import _ffi_api
 
 
+class CallingConv(IntEnum):
+    """Possible kinds of calling conventions."""
+    DEFAULT = 0
+    C_PACKED_FUNC = 1
+    DEVICE_KERNEL_LAUNCH = 2
+
+
 class BaseFunc(RelayExpr):
     """Base class of all functions."""
     @property

python/tvm/ir/module.py

@@ -60,7 +60,6 @@ def __init__(self, functions=None, type_definitions=None):
             type_definitions = mapped_type_defs
         self.__init_handle_by_constructor__(_ffi_api.IRModule, functions, type_definitions)
 
-
     def __setitem__(self, var, val):
         """Add a mapping to the module.
 

python/tvm/tir/transform/function_pass.py

@@ -16,6 +16,7 @@
 # under the License.
 """TIR specific function pass support."""
 import inspect
+import types
 import functools
 
 import tvm._ffi
@@ -142,7 +143,7 @@ def create_function_pass(pass_arg):
             return _wrap_class_function_pass(pass_arg, info)
         if not isinstance(pass_arg, (types.FunctionType, types.LambdaType)):
             raise TypeError("pass_func must be a callable for Module pass")
-        return _ffi_api.MakeFunctionPass(pass_arg, info)
+        return _ffi_api.CreatePrimFuncPass(pass_arg, info)
 
     if pass_func:
         return create_function_pass(pass_func)