End2End Lowering

include/tvm/relax/expr_functor.h

@@ -193,10 +193,7 @@ class ExprMutator : public ExprFunctor<Expr(const Expr&)> {
    * \return expr.
    */
   Expr Mutate(const Expr& expr) {
-    if (memo_.count(expr) == 0) {
-      memo_[expr] = this->VisitExpr(expr);
-    }
-    return Downcast<Expr>(memo_[expr]);
+    return this->VisitExpr(expr);
   }
 
   Expr VisitExpr(const Expr& expr) override;
@@ -226,6 +223,7 @@ class ExprMutator : public ExprFunctor<Expr(const Expr&)> {
   virtual void VisitBinding(const Binding& binding);
   virtual Var VisitVarBinding(const VarBinding& binding);
   virtual void VisitMatchShape(const MatchShape& binding);
+
   virtual BindingBlock VisitBindingBlock(const BindingBlock& block);
   virtual BindingBlock VisitDataflowBlock(const DataflowBlock& block);
 

python/tvm/relax/exec_builder.py

@@ -20,6 +20,7 @@
 import tvm
 from tvm._ffi._ctypes.packed_func import TVMRetValueHandle
 from tvm.runtime import Object
+from tvm.runtime.container import ShapeTuple
 from tvm._ffi.base import _LIB, check_call
 from . vm import Executable
 from . import _ffi_api
@@ -89,7 +90,11 @@ def emit_call(
             dst = SpecialReg.VOID_ARG
         args_ = []
         for arg in args:
-            if isinstance(arg, tvm.nd.NDArray) or isinstance(arg, tvm.DataType):
+            if isinstance(arg, tuple):
+                shape_tuple = ShapeTuple(arg)
+                new_arg = self.emit_constant(shape_tuple)
+                args_.append(new_arg)
+            elif isinstance(arg, (tvm.nd.NDArray, tvm.DataType, ShapeTuple)):
                 new_arg = self.emit_constant(arg)
                 args_.append(new_arg)
             else:

python/tvm/relax/transform/transform.py

@@ -16,9 +16,10 @@
 # under the License.
 # pylint: disable=no-else-return
 # pylint: disable=unidiomatic-typecheck
-from tvm import IRModule 
+from tvm import IRModule
 from . import _ffi_api
 
+
 def fma_rewrite(expr):
     """Perform fused multiply add rewriting in dataflow blocks.
 
@@ -29,22 +30,45 @@ def fma_rewrite(expr):
     """
     return _ffi_api.fma_rewrite(expr)
 
-def explicit_memory_rewrite(expr):
-    """Perform explicit memory allocation for call_dps in dataflow blocks.
+def to_non_dataflow(mod: IRModule) -> IRModule:
+    """Transform all dataflow structure to non-dataflow version.
 
     Parameters
     ----------
-    expr : tvm.relay.Expr
-        The input expression.
+    mod : tvm.IRModule
+        The input module.
     """
-    return _ffi_api.explicit_memory_rewrite(expr)
+    return _ffi_api.to_non_dataflow(mod)
+
+
+def call_dps_rewrite(mod: IRModule) -> IRModule:
+    """Perform explicit memory allocation for call_dps.
+
+    Parameters
+    ----------
+    mod : tvm.IRModule
+        The input module.
+    """
+    return _ffi_api.call_dps_rewrite(mod)
+
+
+def memory_lower(mod: IRModule) -> IRModule:
+    """Perform memory lowering. Lower the relax.builtin.alloc_tensor op to VM builtin functions.
+
+    Parameters
+    ----------
+    mod : tvm.IRModule
+        The input module.
+    """
+    return _ffi_api.memory_lower(mod)
+
 
 def shape_lower(mod: IRModule) -> IRModule:
     """Lower the shape expression in relax to shape heap and TIR functions.
 
     Parameters
     ----------
-    expr : tvm.IRModule
+    mod : tvm.IRModule
         The input module.
     """
     return _ffi_api.shape_lower(mod)

python/tvm/relax/vm.py

@@ -20,6 +20,7 @@
 from tvm.runtime import Object, Device, Module, PackedFunc
 from tvm._ffi.base import _LIB, check_call
 from . import _ffi_api
+from . import transform
 from ..rpc.base import RPC_SESS_MASK
 
 
@@ -164,5 +165,9 @@ def build(mod: tvm.IRModule,
     lib: tvm.runtime.Module
         A runtime module that contains generated code.
     """
-    ex, lib = _ffi_api.VMBuild(mod, target, target_host)
+    new_mod = transform.to_non_dataflow(mod)
+    new_mod = transform.call_dps_rewrite(new_mod)
+    new_mod = transform.memory_lower(new_mod)
+    new_mod = transform.shape_lower(new_mod)
+    ex, lib = _ffi_api.VMBuild(new_mod, target, target_host)
     return ex, lib

src/relax/ir/expr_functor.cc

@@ -214,6 +214,10 @@ Expr ExprMutator::VisitExpr_(const VarNode* op) {
 }
 
 Expr ExprMutator::VisitExpr_(const DataflowVarNode* op) {
+  auto it = var_remap_.find(GetRef<Var>(op));
+  if (it != var_remap_.end()) {
+    return it->second;
+  }
   if (op->type_annotation.defined()) {
     Type type = this->VisitType(op->type_annotation.value());
     if (!op->type_annotation.same_as(type)) {
@@ -339,7 +343,7 @@ void ExprMutator::VisitBinding(const Binding& binding) {
 
 Var ExprMutator::VisitVarBinding(const VarBinding& binding) {
   Expr new_value = builder_->Normalize(this->Mutate(binding->value));
-  Var new_var = Downcast<Var>(this->Mutate(binding->var));
+
   // TODO(@altanh): this probably shouldn't live here, all passes would have to make sure to do it
   //                in this method...
   // if (new_value->shape_.defined()) {
@@ -356,6 +360,7 @@ Var ExprMutator::VisitVarBinding(const VarBinding& binding) {
   //   new_var->checked_type_ = new_value->checked_type_;
   // }
 
+  Var new_var = binding->var;
   if (!builder_->CanProveShapeEqual(new_var->shape(), new_value->shape()) ||
       !StructuralEqual()(new_var->checked_type(), new_value->checked_type())) {
     new_var = Var(new_var->vid, NullOpt, NullOpt, new_var->span);
@@ -380,7 +385,9 @@ Var ExprMutator::VisitVarBinding(const VarBinding& binding) {
 void ExprMutator::VisitMatchShape(const MatchShape& binding) {
   Expr new_value = this->Mutate(binding->value);
   Expr new_pattern = this->Mutate(ShapeExpr(binding->pattern));
-  Var new_var = Downcast<Var>(this->Mutate(binding->var));
+  Var new_var = binding->var;
+
+  // TODO: when value's shape/type changed, create new var
   builder_->EmitMatchShape(
       MatchShape(new_value, Downcast<ShapeExpr>(new_pattern)->values, new_var));
 }

src/relax/transform/call_dps_rewrite.cc

@@ -0,0 +1,87 @@
+/*
+ * 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 src/relax/transform/call_dps_rewrite.cc
+ * \brief
+ */
+#include <tvm/relax/attrs/memory.h>
+#include <tvm/relax/expr_functor.h>
+#include <tvm/relax/type.h>
+#include <tvm/tir/op.h>
+
+#include "../../relay/transforms/pattern_utils.h"
+
+namespace tvm {
+namespace relax {
+
+// ==================
+// CallDPSMutator
+// Example:
+// y: Tensor[n, m] = rx.call_dps((n, m), op.identity, (x))
+// -->
+// lv0 = rx.call("relax.builtin.alloc_tensor", [n, m])
+// rx.call_packed(op.identity, x, lv0)
+
+class CallDPSMutator : public ExprMutator {
+ public:
+  explicit CallDPSMutator(IRModule mod) { mod_ = mod; }
+
+  IRModule Lower() {
+    ret_mod_ = IRModule();
+    for (auto& p : mod_->functions) {
+      Expr func = p.second;
+      if (p.second->IsInstance<FunctionNode>()) {
+        func = this->Mutate(p.second);
+      }
+      ret_mod_->Add(p.first, Downcast<BaseFunc>(func));
+    }
+    return ret_mod_;
+  }
+
+  Expr VisitExpr_(const CallNode* call) override {
+    // post-order mutation
+    Expr expr = ExprMutator::VisitExpr_(call);
+    call = expr.as<CallNode>();
+    // TODO(@yuchen, @altanh): using mutate cause infinite recursion
+    // Expr expr = ExprMutator::Mutate(GetRef<Call>(call));
+
+    static const Op& call_dps_op = Op::Get("relax.call_dps");
+    static const Op& alloc_tensor_op = Op::Get("relax.builtin.alloc_tensor");
+
+    if (call->op == call_dps_op) {
+      ShapeExpr output_shape = Downcast<ShapeExpr>(call->args[0]);
+      Var tensor = builder_->Emit(Call(alloc_tensor_op, {call->args[0]}), "alloc");
+      builder_->Emit(Call(call->args[1], {call->args[2], tensor}), "_");
+      return tensor;
+    }
+
+    return GetRef<Expr>(call);
+  }
+
+ private:
+  IRModule mod_;
+  IRModule ret_mod_;
+};
+
+TVM_REGISTER_GLOBAL("relax.transform.call_dps_rewrite").set_body_typed([](IRModule mod) {
+  return CallDPSMutator(mod).Lower();
+});
+
+}  // namespace relax
+}  // namespace tvm

src/relax/transform/memory_rewrite.cc

@@ -20,6 +20,7 @@
  * \file src/relax/transform/memory_rewrite.cc
  * \brief
  */
+#include <tvm/relax/attrs/memory.h>
 #include <tvm/relax/expr_functor.h>
 #include <tvm/relax/type.h>
 #include <tvm/tir/op.h>
@@ -30,14 +31,31 @@ namespace tvm {
 namespace relax {
 
 // ==================
-// ExplicitMemMutator
+// MemLowerMutator
+// Lower the relax.builtin.alloc_tensor op to VM builtin functions.
 // Example:
-// y: Tensor[n, m] = rx.call_dps((n, m), op.identity, (x))
+// x = relax.builtin.alloc_tensor((m, n))
 // -->
-// lv0 = rx.call("relax.builtin.alloc_tensor", [n, m])
-// rx.call_packed(op.identity, x, lv0)
+// gv0 = relax.call_packed("vm.builtin.alloc_storage", (m * n), alignment, device_type,
+// relax.attrs.AllocStorageAttrs) gv1 = relax.call_packed("vm.builtin.alloc_tensor", gv0, offset,
+// (m, n), relax.attrs.AllocTensorAttrs)
+
+class MemLowerMutator : public ExprMutator {
+ public:
+  explicit MemLowerMutator(IRModule mod) { mod_ = mod; }
+
+  IRModule Lower() {
+    ret_mod_ = IRModule();
+    for (auto& p : mod_->functions) {
+      Expr func = p.second;
+      if (p.second->IsInstance<FunctionNode>()) {
+        func = this->Mutate(p.second);
+      }
+      ret_mod_->Add(p.first, Downcast<BaseFunc>(func));
+    }
+    return ret_mod_;
+  }
 
-class ExplicitMemMutator : public ExprMutator {
   Expr ComputeStorageSize(const Expr& shape, const Type& type) const {
     DynTensorType tensor_type = Downcast<DynTensorType>(type);
     DataType dtype = DataType(tensor_type->dtype);
@@ -63,44 +81,48 @@ class ExplicitMemMutator : public ExprMutator {
     return ret;
   }
 
-  BindingBlock VisitBindingBlock(const BindingBlock& block) {
-    builder_->BeginBindingBlock();
-    for (Binding binding : block->bindings) {
-      this->VisitBinding(binding);
-    }
-    return builder_->EndBlock();
-  }
-
   Expr VisitExpr_(const CallNode* call) override {
     // post-order mutation
     Expr expr = ExprMutator::VisitExpr_(call);
     call = expr.as<CallNode>();
-    // TODO(@yuchen, @altanh): using mutate cause infinite recursion
-    // Expr expr = ExprMutator::Mutate(GetRef<Call>(call));
 
-    static const Op& call_dps_op = Op::Get("relax.call_dps");
     static const Op& alloc_tensor_op = Op::Get("relax.builtin.alloc_tensor");
 
-    if (call->op == call_dps_op) {
-      ShapeExpr output_shape = Downcast<ShapeExpr>(call->args[0]);
-      Type arg_type = Downcast<Tuple>(call->args[2])->fields[0]->checked_type();
-      Expr output_size = ComputeStorageSize(output_shape, arg_type);
-      Var tensor = builder_->Emit(Call(alloc_tensor_op, {call->args[0]}), "alloc");
-      builder_->Emit(Call(call->args[1], {call->args[2], tensor}), "_");
-      return tensor;
+    if (call->op == alloc_tensor_op) {
+      ShapeExpr tensor_shape = Downcast<ShapeExpr>(call->args[0]);
+      // TODO(@yuchen): Get the type of input x, options: add an attr to relax.builtin.alloc_tensor
+      Type tensor_type = DynTensorType(2, DataType::Float(32));
+      Expr storage_size = ComputeStorageSize(tensor_shape, tensor_type);
+      ShapeExpr alignment = ShapeExpr({IntImm(DataType::Int(64), 64)});
+      ShapeExpr device_type = ShapeExpr({IntImm(DataType::Int(64), 1)});
+      auto storage_attr = make_object<AllocStorageAttrs>();
+      storage_attr->dtype = DataType::Float(32);
+      storage_attr->device_type = 1;
+
+      Var storage =
+          builder_->Emit(Call(ExternFunc("vm.builtin.alloc_storage"),
+                              {storage_size, alignment}, Attrs(storage_attr)),
+                         "storage");
+
+      ShapeExpr offset = ShapeExpr({IntImm(DataType::Int(64), 0)});
+      auto tensor_attr = make_object<AllocTensorAttrs>();
+      tensor_attr->dtype = DataType::Float(32);
+      Expr shape = call->args[0];
+      return builder_->Emit(
+          Call(ExternFunc("vm.builtin.alloc_tensor"), {storage, offset, shape}, Attrs(tensor_attr)),
+          "tensor");
     }
 
     return GetRef<Expr>(call);
   }
-};
 
-Expr ExplicitMemRewrite(const Expr& e) { 
-  return ExplicitMemMutator().Mutate(e); 
-}
+ private:
+  IRModule mod_;
+  IRModule ret_mod_;
+};
 
-TVM_REGISTER_GLOBAL("relax.transform.explicit_memory_rewrite")
-.set_body_typed([](Expr expr) {
-  return ExplicitMemRewrite(expr);
+TVM_REGISTER_GLOBAL("relax.transform.memory_lower").set_body_typed([](IRModule mod) {
+  return MemLowerMutator(mod).Lower();
 });
 
 }  // namespace relax