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[AOT] Calculate used memory at the callsite of primitive functions #11208

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13 changes: 13 additions & 0 deletions include/tvm/relay/transform.h
Original file line number Diff line number Diff line change
Expand Up @@ -556,6 +556,19 @@ TVM_DLL Pass PlanDevices(CompilationConfig config);
*/
TVM_DLL Pass FlattenAtrousConv();

/*!
* \brief Annotates the minimum required memory of each primitive function callsite by analyzing
* the liveness of the input/output tensors at each function callsite and calculating the total
* amount of memory these tensors require. This is added as a "used_memory" annotation to the
* function in question as a list of the number of bytes for each callsite. In addition, the
* containing function is annotated with an "io_used_memory" annotation which refers to the total
* memory required for the IO tensors.
*
* Note: This pass does not support dynamic shapes, it is the users responsibility to check this
* pass isn't applied where dynamic shapes may be input.
*/
TVM_DLL Pass AnnotateUsedMemory();

} // namespace transform

/*!
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233 changes: 233 additions & 0 deletions src/relay/backend/annotate_used_memory.cc
Original file line number Diff line number Diff line change
@@ -0,0 +1,233 @@
/*
* 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/relay/backend/annotate_used_memory.cc
* \brief Analyzes the used memory at the callsite of primitive functions.
*/

#include <tvm/ir/module.h>
#include <tvm/relay/attrs/memory.h>
#include <tvm/relay/transform.h>

#include <unordered_map>
#include <unordered_set>

#include "../transforms/device_aware_visitors.h"
#include "../transforms/pass_utils.h"
#include "./liveness_analysis.h"
#include "./utils.h"

namespace tvm {
namespace relay {
namespace backend {

/*!
* \brief Annotates the minimum required memory of each primitive function callsite by analyzing
* the liveness of the input/output tensors at each function callsite and calculating the total
* amount of memory these tensors require. This is added as a "used_memory" annotation to the
* function in question as a list of the number of bytes for each callsite. In addition, the
* containing function is annotated with an "io_used_memory" annotation which refers to the total
* memory required for the IO tensors.
*
* Note: This pass does not support dynamic shapes, it is the users responsibility to check this
* pass isn't applied where dynamic shapes may be input.
*
* A simple example:
*
* Before:
* def @main(%input: Tensor[(1, 2, 2, 4), int8]) -> Tensor[(1, 2, 2, 4), int8] {
* let %x_0 = fn (%x: Tensor[(1, 2, 2, 4), int8], Primitive=1) -> Tensor[(1, 2, 2, 4), int8] {
* nn.max_pool2d(%x, pool_size=[1, 1], padding=[0, 0, 0, 0])
* };
* let %x_1 = %x_0(%input);
* %x_1
* }
*
* After:
* def @main(%input: Tensor[(1, 2, 2, 4), int8], io_used_memory=32) -> Tensor[(1, 2, 2, 4), int8] {
* let %x_0: fn (%x: Tensor[(1, 2, 2, 4), int8], Primitive=1, used_memory=[32]) -> Tensor[(1, 2,
* 2, 4), int8] {
* nn.max_pool2d(%x, pool_size=[1, 1], padding=[0, 0, 0, 0])
* };
* let %x_1: Tensor[(1, 2, 2, 4), int8] = %x_0(%input);
* %x_1
* }
*
* Note that in the simple example above io_used_memory and used_memory are the same since there
* is only one primitive function.
*/
class AnnotateUsedMemoryMutator : public transform::DeviceAwareExprMutator {
public:
AnnotateUsedMemoryMutator(const IRModule& module, const transform::ControlFlowGraph& cfg,
const transform::LivenessAnalysis& lva)
: DeviceAwareExprMutator(module), control_flow_graph_(cfg), liveness_(lva) {}

/*!
* \brief Mutates the input function. In addition, an "io_used_memory" annotation is
* added to the input function which refers to the total size required for the IO
* tensors.
*/
Function operator()(const Function& func) {
uint64_t io_used_memory = 0;

// Inputs
for (const Var& param : func->params) {
Type type = param->checked_type();
ICHECK(type.defined()) << "InferType pass should be run before AnnotateUsedMemory.";
ICHECK(!IsDynamic(type)) << "AnnotateUsedMemory does not support dynamic shapes.";
io_used_memory += CalculateRelayExprSizeBytes(type);
}

// Outputs
Type type = func->body->checked_type();
ICHECK(type.defined()) << "InferType pass should be run before AnnotateUsedMemory.";
ICHECK(!IsDynamic(type)) << "AnnotateUsedMemory does not support dynamic shapes.";
io_used_memory += CalculateRelayExprSizeBytes(type);

Expr new_func_body = VisitExpr(func->body);
Function new_func = WithFields(func, func->params, new_func_body);
return WithAttr(std::move(new_func), "io_used_memory",
tvm::IntImm(tvm::DataType::UInt(64), io_used_memory));
}

/*!
* \brief Establish which let bindings have primitive function values.
*/
std::pair<Var, Expr> PreVisitLetBinding_(const Var& var, const Expr& value) {
if (const auto* func_node = value.as<FunctionNode>()) {
ICHECK(func_node->attrs.HasNonzeroAttr(attr::kPrimitive))
<< "Expect top-level functions to be primitive.";
let_bound_prim_func_.insert(var);
}
return DeviceAwareExprMutator::PreVisitLetBinding_(var, value);
}

/*!
* \brief Visit let nodes and perform one of two actions depending on their value:
*
* 1. CallNode - Calculate "used_memory" annotation value at the callsite of
* primitive functions.
*
* 2. FunctionNode - Annotate functions with "used_memory" annotation based on the
* previous analysis at the callsite.
*
*/
Expr PostVisitLet_(const LetNode* pre_let_node, const LetNode* post_let_node) override {
Var let_var = post_let_node->var;
Expr let_value = IgnoreOnDevice(post_let_node->value);

if (let_value->IsInstance<CallNode>()) {
Call callsite = Downcast<Call>(let_value);
if (CheckPrimitiveFunctionCall(callsite)) {
Var call_op = Downcast<Var>(callsite->op);

// Find all the vars that are live at the callsite. This is done by merging the
// in and out varset's and then removing the var that references the primitive
// function itself since we don't want this included in the calculation.
const transform::ControlFlowGraph::NodePtr cfg_node =
control_flow_graph_.let_map.at(GetRef<Let>(pre_let_node));
transform::VarSet live_tensors = liveness_.live_in.at(cfg_node);
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const transform::VarSet& live_out = liveness_.live_out.at(cfg_node);
live_tensors.insert(live_out.begin(), live_out.end());
live_tensors.erase(call_op);

// Calculate size of live tensors and store to allow annotation when the function
// gets visited.
uint64_t used_memory = 0;
for (const auto& var : live_tensors) {
Type type = var->checked_type();
ICHECK(type.defined()) << "InferType pass should be run before AnnotateUsedMemory.";
ICHECK(!IsDynamic(type)) << "AnnotateUsedMemory does not support dynamic shapes.";
used_memory += CalculateRelayExprSizeBytes(type);
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}
IntImm annotation(DataType::UInt(64), used_memory);
used_memory_annotations_[call_op].push_back(annotation);
}
} else if (let_value->IsInstance<FunctionNode>()) {
Function func = Downcast<Function>(let_value);
ICHECK(used_memory_annotations_.find(let_var) != used_memory_annotations_.end())
<< "Could not find used_memory value for primitive function bound at "
<< let_var->name_hint();
Array<IntImm> used_memory = used_memory_annotations_[let_var];
used_memory_annotations_.erase(let_var);

Function new_func = WithAttr(std::move(func), "used_memory",
Array<IntImm>(used_memory.rbegin(), used_memory.rend()));
return Let(let_var, new_func, post_let_node->body, post_let_node->span);
}

return DeviceAwareExprMutator::PostVisitLet_(pre_let_node, post_let_node);
}

private:
/*!
* \brief Check if a call is a primitive function callsite.
*/
bool CheckPrimitiveFunctionCall(const Call& callsite) {
if (const auto* var_node = callsite->op.as<VarNode>()) {
Var var = GetRef<Var>(var_node);
if (let_bound_prim_func_.find(var) != let_bound_prim_func_.end()) {
return true;
}
}
return false;
}

/*! \brief Control flow graph representation of the main function. */
transform::ControlFlowGraph control_flow_graph_;
/*! \brief Liveness analysis of the main function. */
transform::LivenessAnalysis liveness_;
/*! \brief Var's that reference primitive functions. */
std::unordered_set<Var, ObjectPtrHash, ObjectPtrEqual> let_bound_prim_func_;
/*! \brief Stores the calculated uint64 used_memory values so they can be annotated on the
* relevant function. */
std::unordered_map<Var, Array<IntImm>, ObjectPtrHash, ObjectPtrEqual> used_memory_annotations_;
};

} // namespace backend

namespace transform {

Pass AnnotateUsedMemory() {
runtime::TypedPackedFunc<IRModule(IRModule, PassContext)> pass_func = [=](IRModule mod,
PassContext ctx) {
GlobalVar gv = mod->GetGlobalVar("main");
Function main_func = Downcast<Function>(mod->Lookup("main"));

// Perform liveness analysis to determine what tensors are 'live' at each functions callsite.
support::Arena arena;
ControlFlowGraph cfg = ControlFlowGraph::Create(&arena, main_func);
UseDefAnalysis use_def = UseDefAnalysis::Analyze(cfg);
LivenessAnalysis lva = LivenessAnalysis::Analyze(cfg, use_def);

auto new_main_func = backend::AnnotateUsedMemoryMutator(mod, cfg, lva)(main_func);
if (!new_main_func.same_as(main_func)) {
mod->Update(gv, new_main_func);
}
return mod;
};
return CreateModulePass(pass_func, 0, "AnnotateUsedMemory", {"ToANormalForm", "InferType"});
}

TVM_REGISTER_GLOBAL("relay._transform.AnnotateUsedMemory").set_body_typed(AnnotateUsedMemory);

} // namespace transform
} // namespace relay
} // namespace tvm
2 changes: 2 additions & 0 deletions src/relay/backend/aot_executor_codegen.cc
Original file line number Diff line number Diff line change
Expand Up @@ -1079,6 +1079,8 @@ class AOTExecutorCodegen : public MixedModeVisitor {
}

mod = transform::ToANormalForm()(mod);
mod = transform::InferType()(mod);
mod = transform::AnnotateUsedMemory()(mod);
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IRModule lowered_mod =
tec::LowerTE(mod_name, config_, [this, workspace_byte_alignment](BaseFunc func) {
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