[REFACTOR][TIR] Introduce PrimFuncPass.

docs/api/python/tir.rst

@@ -22,3 +22,12 @@ tvm.tir
    :imported-members:
    :exclude-members: PrimExpr, const
    :autosummary:
+
+
+
+tvm.tir.transform
+-----------------
+.. automodule:: tvm.tir.transform
+   :members:
+   :imported-members:
+   :autosummary:

include/tvm/ir/expr.h

@@ -150,7 +150,7 @@ class RelayExprNode : public BaseExprNode {
   /*!
    * \return The checked_type
    */
-  const Type& checked_type() const;
+  inline const Type& checked_type() const;
   /*!
    * \brief Check if the inferred(checked) type of the Expr
    *  is backed by a TTypeNode and return it.

include/tvm/ir/type_functor.h

@@ -93,6 +93,7 @@ class TypeFunctor<R(const Type& n, Args...)> {
   virtual R VisitType_(const TypeCallNode* op, Args... args) TYPE_FUNCTOR_DEFAULT;
   virtual R VisitType_(const TypeDataNode* op, Args... args) TYPE_FUNCTOR_DEFAULT;
   virtual R VisitType_(const PrimTypeNode* op, Args... args) TYPE_FUNCTOR_DEFAULT;
+  virtual R VisitType_(const PointerTypeNode* op, Args... args) TYPE_FUNCTOR_DEFAULT;
   virtual R VisitTypeDefault_(const Object* op, Args...) {
     LOG(FATAL) << "Do not have a default for " << op->GetTypeKey();
     throw;  // unreachable, written to stop compiler warning
@@ -115,6 +116,7 @@ class TypeFunctor<R(const Type& n, Args...)> {
     TVM_TYPE_FUNCTOR_DISPATCH(TypeCallNode);
     TVM_TYPE_FUNCTOR_DISPATCH(TypeDataNode);
     TVM_TYPE_FUNCTOR_DISPATCH(PrimTypeNode);
+    TVM_TYPE_FUNCTOR_DISPATCH(PointerTypeNode);
     return vtable;
   }
 };
@@ -138,6 +140,7 @@ class TVM_DLL TypeVisitor :
   void VisitType_(const TypeCallNode* op) override;
   void VisitType_(const TypeDataNode* op) override;
   void VisitType_(const PrimTypeNode* op) override;
+  void VisitType_(const PointerTypeNode* op) override;
 };
 
 /*!
@@ -158,6 +161,7 @@ class TVM_DLL TypeMutator :
   Type VisitType_(const TypeCallNode* op) override;
   Type VisitType_(const TypeDataNode* op) override;
   Type VisitType_(const PrimTypeNode* op) override;
+  Type VisitType_(const PointerTypeNode* op) override;
 
  private:
   Array<Type> MutateArray(Array<Type> arr);

include/tvm/tir/transform.h

@@ -0,0 +1,72 @@
+/*
+ * Licensed to the Apache Software Foundation (ASF) under one
+ * or more contributor license agreements.  See the NOTICE file
+ * distributed with this work for additional information
+ * regarding copyright ownership.  The ASF licenses this file
+ * to you under the Apache License, Version 2.0 (the
+ * "License"); you may not use this file except in compliance
+ * with the License.  You may obtain a copy of the License at
+ *
+ *   http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing,
+ * software distributed under the License is distributed on an
+ * "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
+ * KIND, either express or implied.  See the License for the
+ * specific language governing permissions and limitations
+ * under the License.
+ */
+
+/*!
+ * \file tvm/tir/transform.h
+ * \brief TIR specific transformation passes.
+ */
+#ifndef TVM_TIR_TRANSFORM_H_
+#define TVM_TIR_TRANSFORM_H_
+
+#include <tvm/ir/transform.h>
+#include <tvm/tir/expr.h>
+#include <tvm/tir/function.h>
+
+#include <string>
+
+namespace tvm {
+namespace tir {
+namespace transform {
+
+using tvm::transform::Pass;
+using tvm::transform::PassNode;
+using tvm::transform::PassInfo;
+using tvm::transform::PassInfoNode;
+using tvm::transform::PassContext;
+using tvm::transform::PassContextNode;
+using tvm::transform::Sequential;
+
+/*
+ * \brief Create a function pass that optimizes PrimFuncs.
+ *
+ * \param pass_func The packed function that contains the optimization.
+ * \param opt_level The optimization level of the function pass.
+ * \param name The name of the function pass.
+ * \param required The list of the passes that the function pass is dependent on.
+ *
+ * \return The created function pass.
+ */
+TVM_DLL Pass CreatePrimFuncPass(const runtime::TypedPackedFunc<
+                                PrimFunc(PrimFunc, IRModule, PassContext)>& pass_func,
+                                int opt_level,
+                                const std::string& name,
+                                const tvm::Array<tvm::PrimExpr>& required);
+
+/*!
+ * \brief Create PrimFuncPass to combine context calls in the host function.
+ *
+ * \return The pass.
+ */
+Pass CombineContextCall();
+
+}  // namespace transform
+}  // namespace tir
+}  // namespace tvm
+
+#endif  // TVM_TIR_TRANSFORM_H_

python/tvm/tir/__init__.py

@@ -45,3 +45,4 @@
 
 from . import ir_builder
 from . import ir_pass
+from . import transform

python/tvm/tir/transform/__init__.py

@@ -0,0 +1,21 @@
+# Licensed to the Apache Software Foundation (ASF) under one
+# or more contributor license agreements.  See the NOTICE file
+# distributed with this work for additional information
+# regarding copyright ownership.  The ASF licenses this file
+# to you under the Apache License, Version 2.0 (the
+# "License"); you may not use this file except in compliance
+# with the License.  You may obtain a copy of the License at
+#
+#   http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing,
+# software distributed under the License is distributed on an
+# "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
+# KIND, either express or implied.  See the License for the
+# specific language governing permissions and limitations
+# under the License.
+"""Namespace of all TIR transformations"""
+# pylint: disable=wildcard-import, invalid-name
+
+from .function_pass import prim_func_pass, PrimFuncPass
+from .transform import *

python/tvm/tir/transform/_ffi_api.py

@@ -0,0 +1,21 @@
+# Licensed to the Apache Software Foundation (ASF) under one
+# or more contributor license agreements.  See the NOTICE file
+# distributed with this work for additional information
+# regarding copyright ownership.  The ASF licenses this file
+# to you under the Apache License, Version 2.0 (the
+# "License"); you may not use this file except in compliance
+# with the License.  You may obtain a copy of the License at
+#
+#   http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing,
+# software distributed under the License is distributed on an
+# "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
+# KIND, either express or implied.  See the License for the
+# specific language governing permissions and limitations
+# under the License.
+"""FFI APIs for tvm.tir.transform"""
+import tvm._ffi
+
+
+tvm._ffi._init_api("tir.transform", __name__)

python/tvm/tir/transform/function_pass.py

@@ -0,0 +1,149 @@
+# Licensed to the Apache Software Foundation (ASF) under one
+# or more contributor license agreements.  See the NOTICE file
+# distributed with this work for additional information
+# regarding copyright ownership.  The ASF licenses this file
+# to you under the Apache License, Version 2.0 (the
+# "License"); you may not use this file except in compliance
+# with the License.  You may obtain a copy of the License at
+#
+#   http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing,
+# software distributed under the License is distributed on an
+# "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
+# KIND, either express or implied.  See the License for the
+# specific language governing permissions and limitations
+# under the License.
+"""TIR specific function pass support."""
+import inspect
+import functools
+
+import tvm._ffi
+from tvm.ir.transform import Pass, PassInfo
+
+from . import _ffi_api
+
+
+@tvm._ffi.register_object("tir.PrimFuncPass")
+class PrimFuncPass(Pass):
+    """A pass that works on each tvm.relay.Function in a module. A function
+    pass class should be created through py:func:`tvm.tir.transform.function_pass`.
+    """
+
+
+def _wrap_class_function_pass(pass_cls, pass_info):
+    """Wrap a python class as function pass"""
+    class PyFunctionPass(PrimFuncPass):
+        """Internal wrapper class to create a class instance."""
+        def __init__(self, *args, **kwargs):
+            # initialize handle in cass pass_cls creation failed.fg
+            self.handle = None
+            inst = pass_cls(*args, **kwargs)
+            # it is important not to capture self to
+            # avoid a cyclic dependency
+            def _pass_func(func, mod, ctx):
+                return inst.transform_function(func, mod, ctx)
+            self.__init_handle_by_constructor__(
+                _ffi_api.CreatePrimFuncPass, _pass_func, pass_info)
+            self._inst = inst
+
+        def __getattr__(self, name):
+            # fall back to instance attribute if there is not any
+            return self._inst.__getattribute__(name)
+
+    functools.update_wrapper(PyFunctionPass.__init__, pass_cls.__init__)
+    PyFunctionPass.__name__ = pass_cls.__name__
+    PyFunctionPass.__doc__ = pass_cls.__doc__
+    PyFunctionPass.__module__ = pass_cls.__module__
+    return PyFunctionPass
+
+
+def prim_func_pass(pass_func=None, opt_level=None, name=None, required=None):
+    """Decorate a function pass.
+
+    This function returns a callback when pass_func
+    is provided. Otherwise, it returns the created function pass using the
+    given optimization function.
+
+    Parameters
+    ----------
+    pass_func : Optional[Callable[(Function, Module, PassContext) -> Function]]
+        The transformation function or class.
+
+    opt_level : int
+        The optimization level of this module pass.
+
+    name : Optional[str]
+        The name of the function pass. The name could be empty. In this case, the
+        name of the optimization function will be used as the pass name.
+
+    required : Optional[List[str]]
+        The list of passes that the module pass is dependent on.
+
+    Returns
+    -------
+    create_function_pass : Union[Callable, FunctionPass]
+
+        A decorator will be returned if pass_func is not provided,
+        otherwise return the decorated result.
+        The returned decorator has two behaviors depending on the input:
+        A new FunctionPass will be returned when we decorate a pass function.
+        A new FunctionPass class will be returned when we decorate a class type.
+
+    Examples
+    --------
+    The following code block decorates a function pass class.
+
+    .. code-block:: python
+
+        @tvm.tir.transform.prim_func_pass(opt_level=1)
+        class TestReplaceFunc:
+            def __init__(self, new_func):
+                self.new_func = new_func
+
+            def transform_function(self, func, mod, ctx):
+                # just for demo purposes
+                # transform func to new_func
+                return self.new_func
+
+    The following code creates a function pass by decorating
+    a user defined transform function.
+
+    .. code-block:: python
+
+        @tvm.tir.transform.prim_func_pass(opt_level=2)
+        def transform(func, mod, ctx):
+            # my transformations here.
+            return func
+
+        function_pass = transform
+        assert isinstance(function_pass, transform.FunctionPass)
+        assert function_pass.info.opt_level == 2
+
+        # Given a module m, the optimization could be invoked as the follwoing:
+        updated_mod = function_pass(m)
+        # Now constant folding should have been applied to every function in
+        # the provided module m. And the updated module will be returned.
+    """
+
+    if opt_level is None:
+        raise ValueError("Please provide opt_level for the funtion pass.")
+
+    required = required if required else []
+    if not isinstance(required, (list, tuple)):
+        raise TypeError("Required is expected to be the type of " +
+                        "list/tuple.")
+
+    def create_function_pass(pass_arg):
+        """Internal function that creates a function pass"""
+        fname = name if name else pass_arg.__name__
+        info = PassInfo(opt_level, fname, required)
+        if inspect.isclass(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)
+
+    if pass_func:
+        return create_function_pass(pass_func)
+    return create_function_pass

python/tvm/tir/transform/transform.py

@@ -0,0 +1,31 @@
+# Licensed to the Apache Software Foundation (ASF) under one
+# or more contributor license agreements.  See the NOTICE file
+# distributed with this work for additional information
+# regarding copyright ownership.  The ASF licenses this file
+# to you under the Apache License, Version 2.0 (the
+# "License"); you may not use this file except in compliance
+# with the License.  You may obtain a copy of the License at
+#
+#   http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing,
+# software distributed under the License is distributed on an
+# "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
+# KIND, either express or implied.  See the License for the
+# specific language governing permissions and limitations
+# under the License.
+"""Wrapping existing transformations."""
+# pylint: disable=invalid-name
+
+from . import _ffi_api
+
+
+def CombineContextCall():
+    """Combine context calls in the host function.
+
+    Returns
+    -------
+    fpass : tvm.ir.transform.Pass
+        The result pass
+    """
+    return _ffi_api.CombineContextCall()

src/ir/module.cc

@@ -158,13 +158,13 @@ void IRModuleNode::Add(const GlobalVar& var,
                                 GetRef<relay::Function>(ptr));
   }
 
-  auto type = checked_func->checked_type();
+  Type type = checked_func->checked_type();
   CHECK(type.as<relay::IncompleteTypeNode>() == nullptr);
 
   if (functions.find(var) != functions.end()) {
     CHECK(update)
         << "Already have definition for " << var->name_hint;
-    auto old_type = functions[var].as<relay::FunctionNode>()->checked_type();
+    auto old_type = functions[var]->checked_type();
     CHECK(relay::AlphaEqual(type, old_type))
         << "Module#update changes type, not possible in this mode.";
   }