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6 changes: 6 additions & 0 deletions include/tvm/relax/transform.h
Original file line number Diff line number Diff line change
Expand Up @@ -281,6 +281,12 @@ TVM_DLL Pass UpdateVDevice(VDevice new_vdevice, int64_t index);
*/
TVM_DLL Pass ExpandTupleArguments();

/*! \brief Remove unused parameters to internal functions
*
* \return The Pass
*/
TVM_DLL Pass RemoveUnusedParameters();

/*! \brief Remove unused outputs from internal functions
*
* \return The Pass
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1 change: 1 addition & 0 deletions python/tvm/relax/transform/__init__.py
Original file line number Diff line number Diff line change
Expand Up @@ -56,6 +56,7 @@
PatternCheckContext,
RealizeVDevice,
RemovePurityChecking,
RemoveUnusedParameters,
RemoveUnusedOutputs,
RewriteCUDAGraph,
RewriteDataflowReshape,
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10 changes: 10 additions & 0 deletions python/tvm/relax/transform/transform.py
Original file line number Diff line number Diff line change
Expand Up @@ -568,6 +568,16 @@ def ExpandTupleArguments() -> tvm.ir.transform.Pass:
return _ffi_api.ExpandTupleArguments() # type: ignore


def RemoveUnusedParameters() -> tvm.ir.transform.Pass:
"""Remove unused arguments to internal functions

Returns
-------
ret: tvm.ir.transform.Pass
"""
return _ffi_api.RemoveUnusedParameters() # type: ignore


def RemoveUnusedOutputs() -> tvm.ir.transform.Pass:
"""Remove unused outputs from internal functions

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260 changes: 260 additions & 0 deletions src/relax/transform/remove_unused_parameters.cc
Original file line number Diff line number Diff line change
@@ -0,0 +1,260 @@
/*
* 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.
*/

#include <tvm/relax/analysis.h>
#include <tvm/relax/expr_functor.h>
#include <tvm/relax/transform.h>
#include <tvm/relax/utils.h>

#include <algorithm>
#include <optional>
#include <tuple>

#include "utils.h"

namespace tvm {
namespace relax {

namespace {

template <typename T>
using PSet = std::unordered_set<T, ObjectPtrHash, ObjectPtrEqual>;
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What does the P stand for?

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Here, "pointer", as the repetition of ObjectPtrHash, ObjectPtrEqual was getting a bit repetitive to read.

At some point, I want to implement std::hash for GlobalVar, tir::Var, and relax::Var. For most types, there would be ambiguity between pointer-hash and structural-hash, but the two should be equivalent in these cases.


template <typename T, typename U>
using PMap = std::unordered_map<T, U, ObjectPtrHash, ObjectPtrEqual>;

/* \brief Describes the modifications to be made for a function */
struct CalleeAnalysis {
/* \brief The updated private function */
Function func;

/* \brief A function that updates the callsite arguments
*
* \param The arguments used to call the original function
*
* \return The arguments to be used for the modified function
*/
std::function<Array<Expr>(Array<Expr>)> arg_updater;
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The comment should probably explain how the function is meant to be used. The use of the word "mutator" can be confused for ExprMutator, so it might be better to be a little more specific.

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Good call, and updated to describe it as a function that takes as input the arguments used to call original function, and returns the arguments that should be used to call the updated function.

};

std::optional<CalleeAnalysis> AnalyzeCallee(Function func) {
bool is_exposed = func->attrs.GetAttr<String>(tvm::attr::kGlobalSymbol).defined();
if (is_exposed) return std::nullopt;

auto free_relax_vars = [&]() -> PSet<Var> {
auto array_free_vars = FreeVars(func->body);
return {array_free_vars.begin(), array_free_vars.end()};
}();

std::vector<bool> parameter_mask;
parameter_mask.reserve(func->params.size());

Array<Var> params;
for (const auto& param : func->params) {
bool is_used = free_relax_vars.count(param);
parameter_mask.push_back(is_used);
if (is_used) {
params.push_back(param);
}
}

if (func->params.size() == params.size()) {
// Early bail-out for the common case where the function uses all
// of its parameters.
return std::nullopt;
}

// Even if a parameter is unused, it may provide definitions for
// symbolic variables. We still want to remove the relax variable
// to reduce computational steps in the parent, but we need to
// provide the symbolic variables the other steps.
auto defined_tir_params = [&]() -> PSet<tir::Var> {
auto param_sinfo =
TupleStructInfo(params.Map([](const auto& var) { return GetStructInfo(var); }));
auto arr = DefinableTIRVarsInStructInfo(param_sinfo);
return {arr.begin(), arr.end()};
}();

// Use an array to define the order of the symbolic variables
Array<tir::Var> free_tir_vars;
for (const auto& tir_var : FreeSymbolicVars(func->body)) {
if (!defined_tir_params.count(tir_var)) {
free_tir_vars.push_back(tir_var);
}
}

for (const auto& tir_var : free_tir_vars) {
Var relax_var("param_" + tir_var->name_hint, PrimStructInfo(tir_var));
params.push_back(relax_var);
}

FuncStructInfo new_sinfo(params.Map([](const auto& var) { return GetStructInfo(var); }),
func->ret_struct_info,
Downcast<FuncStructInfo>(func->struct_info_)->purity);

auto arg_updater = [parameter_mask, old_relax_params = func->params,
free_tir_vars](Array<Expr> old_args) -> Array<Expr> {
ICHECK_EQ(old_args.size(), parameter_mask.size())
<< "Call provides " << old_args.size() << ", but the callee accepts "
<< parameter_mask.size() << " parameters";

Array<Expr> new_args;
for (size_t i = 0; i < old_args.size(); i++) {
if (parameter_mask.at(i)) {
new_args.push_back(old_args[i]);
}
}

if (free_tir_vars.size()) {
Map<Var, Expr> old_binding;
for (size_t i = 0; i < old_relax_params.size(); i++) {
old_binding.Set(old_relax_params[i], old_args[i]);
}
arith::Analyzer analyzer;
auto tir_binding = InferSymbolicVarMap(old_binding, &analyzer);

for (const auto& tir_var : free_tir_vars) {
new_args.push_back(PrimValue(tir_binding.at(tir_var)));
}
}

return new_args;
};

auto write_ptr = func.CopyOnWrite();
write_ptr->params = params;
write_ptr->struct_info_ = new_sinfo;

return CalleeAnalysis{func, arg_updater};
}

class CallSiteMutator : public ExprMutator {
public:
explicit CallSiteMutator(PMap<GlobalVar, std::function<Call(Call)>> callsite_updaters)
: callsite_updaters_(callsite_updaters) {}

using ExprMutator::VisitExpr_;

Expr VisitExpr_(const FunctionNode* op) override {
auto node = ExprMutator::VisitExpr_(op);

// If a function was modified, that means it called into a private
// function that now takes a reduced number of arguments. Some
// bindings in the calling scope, previously used to define those
// unused arguments, may be able to be removed as a result.
if (node.get() != op) {
node = RemoveAllUnused(node);
}
return node;
}

Expr VisitExpr_(const CallNode* op) override {
auto node = Downcast<Call>(ExprMutator::VisitExpr_(op));

if (auto gvar = node->op.as<GlobalVar>()) {
if (auto it = callsite_updaters_.find(gvar.value()); it != callsite_updaters_.end()) {
node = it->second(std::move(node));
}
}

return node;
}

PMap<GlobalVar, std::function<Call(Call)>> callsite_updaters_;
};

} // namespace

namespace transform {

Pass RemoveUnusedParameters() {
runtime::TypedPackedFunc<IRModule(IRModule, PassContext)> pass_func =
[=](IRModule mod, PassContext pc) -> IRModule {
PMap<GlobalVar, std::function<Call(Call)>> callsite_updaters;

{
IRModule new_callees;

for (const auto& [gvar, base_func] : mod->functions) {
if (auto func = base_func.as<Function>()) {
if (auto callee_res = AnalyzeCallee(func.value())) {
auto new_func = callee_res->func;
GlobalVar new_gvar(gvar->name_hint, new_func->checked_type_);
new_gvar->struct_info_ = new_func->struct_info_;
new_callees->Add(new_gvar, new_func);

callsite_updaters[gvar] = [old_gvar = gvar, new_gvar,
arg_updater = callee_res->arg_updater](Call call) -> Call {
ICHECK(call->op.same_as(old_gvar)) << "InternalError: "
<< "Updater should be applied to " << old_gvar
<< ", but was applied to " << call->op;
auto write_ptr = call.CopyOnWrite();
write_ptr->op = new_gvar;
write_ptr->args = arg_updater(call->args);
return call;
};
}
}
}

if (callsite_updaters.empty()) {
return mod;
}
auto write_ptr = mod.CopyOnWrite();

// Remove any private subroutines that have unused parameters,
// then add the updated versions. The new private functions
// have the same name, but require a new GlobalVar to hold the
// updated StructInfo. As a result, calling `Update()` without
// first calling `Remove()` introduce a duplicate name and
// produce an error.
for (const auto& it : callsite_updaters) {
write_ptr->Remove(it.first);
}
write_ptr->Update(new_callees);
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Might be worth putting in a comment that this is to transfer over the functions that will be remaining unchanged. I had to think for a second to realize what this was doing.

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Good call, and I've I added a comment. This section is to remove any private functions that have unused parameters, then to replace them with updated versions of the private functions.

}

CallSiteMutator mutator(std::move(callsite_updaters));

IRModule caller_updates;

for (const auto& [gvar, base_func] : mod->functions) {
if (auto func = base_func.as<Function>()) {
auto mutated = Downcast<Function>(mutator.VisitExpr(func.value()));
if (!mutated.same_as(base_func)) {
caller_updates->Add(gvar, mutated);
}
}
}

if (caller_updates->functions.size()) {
mod.CopyOnWrite()->Update(caller_updates);
}
return mod;
};
return CreateModulePass(pass_func, 0, "RemoveUnusedParameters", {});
}

TVM_REGISTER_GLOBAL("relax.transform.RemoveUnusedParameters")
.set_body_typed(RemoveUnusedParameters);

} // namespace transform

} // namespace relax
} // namespace tvm
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