[TIR] Refactor MakePackedAPI to target dependent stage. (apache#5326)

Previously MakePackedAPI was in the target independent stage,
but never the less requires the device_type information that will be
binded at a later target dependent stage.

The previous implementation was due to the limitation of LoweredFunc
which can not carry buffer_map info(so they have to be lowered right away).
This is no longer the case after the unified IR refactor.

This PR migrates MakePackedAPI to a target dependent stage
and removes the un-necessary BindDevice pass.

include/tvm/ir/transform.h

@@ -352,12 +352,19 @@ class Sequential : public Pass {
  *
  * \return The created module pass.
  */
-Pass CreateModulePass(
+TVM_DLL Pass CreateModulePass(
     const runtime::TypedPackedFunc<IRModule(IRModule, PassContext)>& pass_func,
     int opt_level,
     const std::string& name,
     const Array<runtime::String>& required);
 
+
+/*!
+ * \brief A special trace pass that prints the header and IR to LOG(INFO).
+ * \return The pass.
+ */
+TVM_DLL Pass PrintIR(std::string header);
+
 }  // namespace transform
 }  // namespace tvm
 

include/tvm/runtime/device_api.h

@@ -193,6 +193,15 @@ class TVM_DLL DeviceAPI {
    * \return The corresponding device API.
    */
   static DeviceAPI* Get(TVMContext ctx, bool allow_missing = false);
+
+  /*!
+   * \brief Whether a certian device type requires set device context
+   *        before launching the kernel function.
+   * \param device_type The device type.
+   */
+  static bool NeedSetDeviceContext(int device_type) {
+    return device_type != kDLCPU && device_type != kDLMicroDev;
+  }
 };
 
 /*! \brief The device type bigger than this is RPC device */

include/tvm/tir/transform.h

@@ -112,15 +112,6 @@ TVM_DLL Pass RemapThreadAxis(Map<runtime::String, IterVar> axis_map);
  */
 TVM_DLL Pass LowerCustomDatatypes();
 
-
-/*!
- * \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.
  *

python/tvm/driver/build_module.py

@@ -200,7 +200,7 @@ def lower(sch,
     if cfg.restricted_func:
         f = f.with_attr("tir.noalias", True)
     mod = tvm.IRModule({name: f})
-    return tvm.tir.transform.MakePackedAPI()(mod)
+    return mod
 
 
 def _build_for_device(input_mod, target, target_host):
@@ -243,13 +243,13 @@ def _build_for_device(input_mod, target, target_host):
                   tvm.tir.transform.ThreadSync("warp"),
                   tvm.tir.transform.InferFragment(),
                   tvm.tir.transform.LowerThreadAllreduce(),
-                  tvm.tir.transform.BindDeviceType(),
+                  tvm.tir.transform.MakePackedAPI(),
                   tvm.tir.transform.SplitHostDevice()]
-    mod_mixed = tvm.ir.transform.Sequential(opt_mixed)(mod_mixed)
+    mod_mixed = tvm.transform.Sequential(opt_mixed)(mod_mixed)
 
 
     # device optimizations
-    opt_device = tvm.ir.transform.Sequential(
+    opt_device = tvm.transform.Sequential(
         [tvm.tir.transform.Filter(
             lambda f: "calling_conv" in f.attrs and
             f.attrs["calling_conv"].value == CallingConv.DEVICE_KERNEL_LAUNCH),
@@ -259,7 +259,7 @@ def _build_for_device(input_mod, target, target_host):
     mod_dev = opt_device(mod_mixed)
 
     # host optimizations
-    opt_host = tvm.ir.transform.Sequential(
+    opt_host = tvm.transform.Sequential(
         [tvm.tir.transform.Filter(
             lambda f: "calling_conv" not in f.attrs or
             f.attrs["calling_conv"].value != CallingConv.DEVICE_KERNEL_LAUNCH),

python/tvm/ir/transform.py

@@ -22,13 +22,13 @@
 
 import tvm._ffi
 
-from tvm._ffi.runtime_ctypes import TVMContext
-from tvm.runtime import Object, ndarray as _nd
+import tvm.runtime
+from tvm.runtime import ndarray as _nd
 
 from . import _ffi_transform_api
 
 @tvm._ffi.register_object("transform.PassInfo")
-class PassInfo(Object):
+class PassInfo(tvm.runtime.Object):
     """The class contains the meta data required by a pass. It is the
     container of information needed by running an optimization or analysis.
     This class can be extended by adding new members when more meta data is
@@ -52,7 +52,7 @@ def __init__(self, opt_level, name, required=None):
 
 
 @tvm._ffi.register_object("transform.PassContext")
-class PassContext(Object):
+class PassContext(tvm.runtime.Object):
     """The basis where a Relay optimization/analysis runs on.
     Each pass context contains a number of auxiliary information that is used
     to help an optimization pass. Such information includes the error reporter
@@ -79,7 +79,7 @@ def __init__(self,
                  trace=None):
         if isinstance(fallback_device, str):
             fallback_device = _nd.context(fallback_device).device_type
-        elif isinstance(fallback_device, TVMContext):
+        elif isinstance(fallback_device, tvm.runtime.TVMContext):
             fallback_device = fallback_device.device_type
         if not isinstance(fallback_device, int):
             raise TypeError("fallback_device is expected to be the type of " +
@@ -113,7 +113,7 @@ def current():
 
 
 @tvm._ffi.register_object("transform.Pass")
-class Pass(Object):
+class Pass(tvm.runtime.Object):
     """The base class of all passes. All methods here are just simple wrappers
     that are implemented in the backend. They are defined for users to
     conveniently interact with the base class.
@@ -327,3 +327,18 @@ def create_module_pass(pass_arg):
     if pass_func:
         return create_module_pass(pass_func)
     return create_module_pass
+
+
+def PrintIR(header):
+    """A special trace pass that prints the header and IR.
+
+    Parameters
+    ----------
+    header : str
+        The header to be displayed along with the dump.
+
+    Returns
+    --------
+    The pass
+    """
+    return _ffi_transform_api.PrintIR(header)

python/tvm/testing.py

@@ -195,13 +195,14 @@ def MakeAPILegacy(stmt, name, args, num_unpacked_args, noalias):
     mod : IRModule
         The created IRModule.
     """
+    assert num_unpacked_args == 0
     f = tvm.tir.PrimFunc(args, stmt).with_attr(
         "global_symbol", tvm.runtime.String(name))
     f = f.with_attr("tir.is_entry_func", True)
     if noalias:
         f = f.with_attr("tir.noalias", True)
     mod = tvm.IRModule({name: f})
-    return tvm.tir.transform.MakePackedAPI(num_unpacked_args)(mod)
+    return mod
 
 
 tvm._ffi._init_api("testing", __name__)

python/tvm/tir/transform/transform.py

@@ -32,7 +32,7 @@ def Apply(ftransform):
 
     Returns
     -------
-    fpass : tvm.ir.transform.Pass
+    fpass : tvm.transform.Pass
         The result pass
     """
     # pylint: disable=unused-argument
@@ -51,7 +51,7 @@ def Filter(fcond):
 
     Returns
     -------
-    fpass : tvm.ir.transform.Pass
+    fpass : tvm.transform.Pass
         The result pass
     """
     # pylint: disable=unused-argument
@@ -67,7 +67,7 @@ def LowerCustomDatatypes():
 
     Returns
     -------
-    fpass : tvm.ir.transform.Pass
+    fpass : tvm.transform.Pass
         The result pass
     """
     return _ffi_api.LowerCustomDatatypes()
@@ -84,30 +84,18 @@ def MakePackedAPI(num_unpacked_params=0):
 
     Returns
     -------
-    fpass : tvm.ir.transform.Pass
+    fpass : tvm.transform.Pass
         The result pass
     """
     return _ffi_api.MakePackedAPI(num_unpacked_params)
 
 
-def BindDeviceType():
-    """Bind the device type of the function to be
-       the device_type specified in the target attribute.
-
-    Returns
-    -------
-    fpass : tvm.ir.transform.Pass
-        The result pass
-    """
-    return _ffi_api.BindDeviceType()
-
-
 def SplitHostDevice():
     """Split the function into a host function and device functions.
 
     Returns
     -------
-    fpass : tvm.ir.transform.Pass
+    fpass : tvm.transform.Pass
         The result pass
     """
     return _ffi_api.SplitHostDevice()
@@ -118,7 +106,7 @@ def SkipAssert():
 
     Returns
     -------
-    fpass : tvm.ir.transform.Pass
+    fpass : tvm.transform.Pass
         The result pass
     """
     return _ffi_api.SkipAssert()
@@ -134,7 +122,7 @@ def ThreadSync(storage_scope):
 
     Returns
     -------
-    fpass : tvm.ir.transform.Pass
+    fpass : tvm.transform.Pass
         The result pass
     """
     return _ffi_api.ThreadSync(storage_scope)
@@ -145,7 +133,7 @@ def LowerThreadAllreduce():
 
     Returns
     -------
-    fpass : tvm.ir.transform.Pass
+    fpass : tvm.transform.Pass
         The result pass
     """
     return _ffi_api.LowerThreadAllreduce()
@@ -156,7 +144,7 @@ def InferFragment():
 
     Returns
     -------
-    fpass : tvm.ir.transform.Pass
+    fpass : tvm.transform.Pass
         The result pass
     """
     return _ffi_api.InferFragment()
@@ -167,7 +155,7 @@ def LowerWarpMemory():
 
     Returns
     -------
-    fpass : tvm.ir.transform.Pass
+    fpass : tvm.transform.Pass
         The result pass
     """
     return _ffi_api.LowerWarpMemory()
@@ -178,7 +166,7 @@ def LowerTVMBuiltin():
 
     Returns
     -------
-    fpass : tvm.ir.transform.Pass
+    fpass : tvm.transform.Pass
         The result pass
     """
     return _ffi_api.LowerTVMBuiltin()
@@ -189,7 +177,7 @@ def LowerIntrin():
 
     Returns
     -------
-    fpass : tvm.ir.transform.Pass
+    fpass : tvm.transform.Pass
         The result pass
     """
     return _ffi_api.LowerIntrin()
@@ -200,7 +188,7 @@ def LowerDeviceStorageAccessInfo():
 
     Returns
     -------
-    fpass : tvm.ir.transform.Pass
+    fpass : tvm.transform.Pass
         The result pass
 
     Note
@@ -215,7 +203,7 @@ def CombineContextCall():
 
     Returns
     -------
-    fpass : tvm.ir.transform.Pass
+    fpass : tvm.transform.Pass
         The result pass
     """
     return _ffi_api.CombineContextCall()
@@ -231,7 +219,7 @@ def NarrowDataType(target_bits):
 
     Returns
     -------
-    fpass : tvm.ir.transform.Pass
+    fpass : tvm.transform.Pass
         The result pass
 
     Note

src/driver/driver_api.cc

@@ -216,8 +216,7 @@ IRModule lower(te::Schedule sch,
   if (config->restricted_func) {
     f = WithAttr(std::move(f), "tir.noalias", Integer(1));
   }
-  auto mod = IRModule(Map<GlobalVar, BaseFunc>({{GlobalVar(name), f}}));
-  return tir::transform::MakePackedAPI(0)(mod);
+  return IRModule(Map<GlobalVar, BaseFunc>({{GlobalVar(name), f}}));
 }
 
 
@@ -237,7 +236,7 @@ split_dev_host_funcs(IRModule mod_mixed,
   mixed_pass_list.push_back(tir::transform::ThreadSync("warp"));
   mixed_pass_list.push_back(tir::transform::InferFragment());
   mixed_pass_list.push_back(tir::transform::LowerThreadAllreduce());
-  mixed_pass_list.push_back(tir::transform::BindDeviceType());
+  mixed_pass_list.push_back(tir::transform::MakePackedAPI(0));
   mixed_pass_list.push_back(tir::transform::SplitHostDevice());
   auto opt_mixed = transform::Sequential(mixed_pass_list);
   mod_mixed = opt_mixed(std::move(mod_mixed));

src/ir/transform.cc

@@ -473,5 +473,18 @@ TVM_REGISTER_GLOBAL("transform.EnterPassContext")
 TVM_REGISTER_GLOBAL("transform.ExitPassContext")
 .set_body_typed(PassContext::Internal::ExitScope);
 
+
+Pass PrintIR(std::string header) {
+  auto pass_func =[header](IRModule mod, const PassContext& ctx) {
+    LOG(INFO) << "PrintIR(" << header << "):\n"
+              << mod;
+    return mod;
+  };
+  return CreateModulePass(pass_func, 0, "PrintIR", {});
+}
+
+TVM_REGISTER_GLOBAL("transform.PrintIR")
+.set_body_typed(PrintIR);
+
 }  // namespace transform
 }  // namespace tvm

src/target/stackvm/codegen_stackvm.cc

@@ -58,6 +58,8 @@ StackVM::StructFieldKind MapFieldKind(int64_t kind) {
 }
 
 StackVM CodeGenStackVM::Compile(const PrimFunc& f) {
+  CHECK_EQ(f->buffer_map.size(), 0U)
+      << "Cannot codegen function with buffer_map, please lower them first";
   for (size_t i = 0; i < f->params.size(); ++i) {
     Var v = f->params[i];
     int vid = AllocVarID(v.get());

src/tir/analysis/verify_memory.cc

@@ -114,9 +114,11 @@ class MemoryAccessVerifier final : protected StmtExprVisitor {
   /// Check if the value of a Variable comes from function argument.
   bool IsFromFunctionArgs(const VarNode *var) const {
     const VarNode *V = var;
-    while (true) {
-      CHECK(V) << "Invalid Variable\n";
+    for (auto kv : func_->buffer_map) {
+      if (V == kv.second->data.get()) return true;
+    }
 
+    while (true) {
       // Variable is from function args. Return true.
       if (V == func_->params[0].get()) return true;