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/* Copyright 2017 The TensorFlow Authors. All Rights Reserved.
Licensed 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 "tensorflow/compiler/tf2xla/const_analysis.h"
#include <unordered_map>
#include <unordered_set>
#include "absl/algorithm/container.h"
#include "tensorflow/compiler/tf2xla/tf2xla_util.h"
#include "tensorflow/compiler/tf2xla/xla_op_registry.h"
#include "xla/status_macros.h"
#include "tensorflow/core/common_runtime/function.h"
#include "tensorflow/core/framework/attr_value.pb.h"
#include "tensorflow/core/framework/function.h"
#include "tensorflow/core/framework/node_def_util.h"
#include "tensorflow/core/graph/algorithm.h"
#include "tensorflow/core/lib/core/errors.h"
namespace tensorflow {
namespace {
absl::Status GetFunctionBody(FunctionLibraryRuntime* flib_runtime,
const NodeDef& node,
absl::string_view func_attr_name,
const FunctionBody** fbody) {
NameAttrList name_attr_list;
TF_RETURN_IF_ERROR(GetNodeAttr(node, func_attr_name, &name_attr_list));
FunctionLibraryRuntime::Handle func_handle;
TF_RETURN_IF_ERROR(flib_runtime->Instantiate(
name_attr_list.name(), AttrSlice(&name_attr_list.attr()), &func_handle));
*fbody = flib_runtime->GetFunctionBody(func_handle);
return absl::OkStatus();
}
absl::Status GetFunctionBodies(FunctionLibraryRuntime* flib_runtime,
const NodeDef& node,
absl::string_view func_list_attr_name,
std::vector<const FunctionBody*>* fbodies) {
std::vector<NameAttrList> name_attr_lists;
TF_RETURN_IF_ERROR(GetNodeAttr(node, func_list_attr_name, &name_attr_lists));
for (const NameAttrList& name_attr_list : name_attr_lists) {
FunctionLibraryRuntime::Handle func_handle;
TF_RETURN_IF_ERROR(flib_runtime->Instantiate(
name_attr_list.name(), AttrSlice(&name_attr_list.attr()),
&func_handle));
fbodies->push_back(flib_runtime->GetFunctionBody(func_handle));
}
return absl::OkStatus();
}
absl::Status CondConstInputIndices(
absl::Span<const FunctionBody* const> branch_bodies,
std::vector<int>* const_input_idxs, FunctionLibraryRuntime* flib_runtime) {
TF_RET_CHECK(!branch_bodies.empty());
TF_RET_CHECK(branch_bodies[0] != nullptr);
int num_inputs =
branch_bodies[0]->record->fdef().signature().input_arg_size();
// Stores indices of the "branch function" inputs that are expected to be
// compile time constants.
std::vector<bool> compile_time_const_arg_indices(num_inputs);
for (auto fbody : branch_bodies) {
TF_RET_CHECK(fbody != nullptr);
TF_RETURN_IF_ERROR(BackwardsConstAnalysis(
*(fbody->graph), &compile_time_const_arg_indices,
/*compile_time_const_nodes=*/nullptr, flib_runtime));
}
for (int i = 0, end = compile_time_const_arg_indices.size(); i < end; i++) {
if (compile_time_const_arg_indices[i]) {
// The 0th input is the pred or branch index, which is not passed to the
// branches. So the i'th input of a branch function corresponds to the
// i + 1'th input of the If/Case op.
const_input_idxs->push_back(i + 1);
}
}
return absl::OkStatus();
}
absl::Status GetCompileTimeConstInputs(const NodeDef& node,
const OpKernel* op_kernel,
const OpDef* op_def,
std::vector<int>* const_input_idxs,
FunctionLibraryRuntime* flib_runtime) {
DCHECK(op_def != nullptr || op_kernel != nullptr);
if (node.op() == "While" || node.op() == "StatelessWhile") {
// For While nodes, recurse into the body and cond graphs.
const FunctionBody* fcond = nullptr;
const FunctionBody* fbody = nullptr;
TF_RETURN_IF_ERROR(GetFunctionBody(flib_runtime, node, "cond", &fcond));
TF_RETURN_IF_ERROR(GetFunctionBody(flib_runtime, node, "body", &fbody));
TF_RET_CHECK(fcond);
TF_RET_CHECK(fbody);
int num_inputs = fbody->record->fdef().signature().input_arg_size();
// Stores which of the loop inputs are expected to be compile time
// constants.
std::vector<bool> compile_time_const_arg_indices(num_inputs);
TF_RETURN_IF_ERROR(BackwardsConstAnalysis(
*(fcond->graph), &compile_time_const_arg_indices,
/*compile_time_const_nodes=*/nullptr, flib_runtime));
TF_RETURN_IF_ERROR(BackwardsConstAnalysis(
*(fbody->graph), &compile_time_const_arg_indices,
/*compile_time_const_nodes=*/nullptr, flib_runtime));
for (int i = 0; i < num_inputs; i++) {
if (compile_time_const_arg_indices[i]) {
// Check that this input is actually a loop invariant.
TF_ASSIGN_OR_RETURN(
bool is_loop_invariant,
IsLoopInvariant(fbody, i,
flib_runtime->GetFunctionLibraryDefinition()));
if (is_loop_invariant) {
const_input_idxs->push_back(i);
} else {
// TODO(b/178546817): Verify that it's OK and raise an error if we are
// using this branch from jit_compile=True.
Node* arg_i = fbody->arg_nodes[i];
Node* ret_i = fbody->ret_nodes[i];
VLOG(1) << "Argument " << i << " to while-loop " << node.name()
<< " has to be constant, but it's not a loop invariant, "
"cluster compilation likely to fail at compile time: "
<< arg_i->DebugString() << " vs. " << ret_i->DebugString();
VLOG(1) << node.ShortDebugString();
}
}
}
return absl::OkStatus();
} else if (node.op() == "If" || node.op() == "StatelessIf") {
const FunctionBody* fthen = nullptr;
const FunctionBody* felse = nullptr;
TF_RETURN_IF_ERROR(
GetFunctionBody(flib_runtime, node, "then_branch", &fthen));
TF_RETURN_IF_ERROR(
GetFunctionBody(flib_runtime, node, "else_branch", &felse));
return CondConstInputIndices({fthen, felse}, const_input_idxs,
flib_runtime);
} else if (node.op() == "Case" || node.op() == "StatelessCase") {
std::vector<const FunctionBody*> branch_bodies;
TF_RETURN_IF_ERROR(
GetFunctionBodies(flib_runtime, node, "branches", &branch_bodies));
return CondConstInputIndices(branch_bodies, const_input_idxs, flib_runtime);
} else if (node.op() == "PartitionedCall" ||
node.op() == "StatefulPartitionedCall") {
const FunctionBody* fbody;
TF_RETURN_IF_ERROR(GetFunctionBody(flib_runtime, node, "f", &fbody));
int num_inputs = fbody->record->fdef().signature().input_arg_size();
std::vector<bool> compile_time_const_arg_indices(num_inputs);
TF_RETURN_IF_ERROR(BackwardsConstAnalysis(
*(fbody->graph), &compile_time_const_arg_indices,
/*compile_time_const_nodes=*/nullptr, flib_runtime));
for (int i = 0; i < num_inputs; i++) {
if (compile_time_const_arg_indices[i]) {
const_input_idxs->push_back(i);
}
}
return absl::OkStatus();
} else if (op_def != nullptr) {
return XlaOpRegistry::CompileTimeConstantInputs(node, *op_def,
const_input_idxs);
} else {
return XlaOpRegistry::CompileTimeConstantInputs(*op_kernel,
const_input_idxs);
}
}
absl::Status GetCompileTimeConstInputs(const Node* node,
std::vector<int>* const_input_idxs,
FunctionLibraryRuntime* flib_runtime) {
return GetCompileTimeConstInputs(node->def(), /*op_kernel=*/nullptr,
&node->op_def(), const_input_idxs,
flib_runtime);
}
} // namespace
// Backwards dataflow analysis that finds arguments to a graph that must be
// compile-time constants.
absl::Status BackwardsConstAnalysis(
const Graph& g, std::vector<bool>* compile_time_const_arg_indices,
std::vector<bool>* compile_time_const_nodes,
FunctionLibraryRuntime* flib_runtime,
std::function<bool(const Edge&)> edge_filter_input) {
if (!compile_time_const_nodes && g.GetConstArgIndicesCache().has_value() &&
!edge_filter_input) {
VLOG(5) << "Using cached argument indices on graph " << &g;
*compile_time_const_arg_indices = g.GetConstArgIndicesCache().value();
return absl::OkStatus();
}
auto edge_filter = [&](const Edge& e) {
return edge_filter_input ? edge_filter_input(e) : true;
};
std::vector<bool> compile_time_const_nodes_impl;
if (compile_time_const_nodes) {
CHECK_EQ(compile_time_const_nodes->size(), g.num_node_ids());
} else {
compile_time_const_nodes_impl.resize(g.num_node_ids());
compile_time_const_nodes = &compile_time_const_nodes_impl;
}
absl::Status status;
auto visit = [&](Node* node) {
if (!status.ok()) return;
// If this is a metadata-only op, don't propagate the const requirement.
if (XlaOpRegistry::IsMetadataOp(node->type_string())) {
VLOG(3) << "must-be-const node is metadata op: " << node->name();
return;
}
// If this node must be const, and it isn't a metadata op, then all of its
// parents must be const.
if ((*compile_time_const_nodes)[node->id()]) {
VLOG(3) << "marking consts for must-be-const node " << node->name();
if (node->type_string() == "_Arg") {
int index;
status = GetNodeAttr(node->attrs(), "index", &index);
if (!status.ok()) return;
if (compile_time_const_arg_indices) {
(*compile_time_const_arg_indices)[index] = true;
}
VLOG(3) << " const _Arg " << index << ": " << node->name();
return;
}
for (const Edge* pred : node->in_edges()) {
if (!pred->IsControlEdge() && edge_filter(*pred)) {
// If the src node of the `pred` is an IdentityN/While do not mark it
// as a compile-time const. Only mark the corresponding input to the
// IdentityN/While node as a const. XLA IdentityN op simply forwards
// its inputs so this is safe; loop-invariance is checked elsewhere.
while (edge_filter(*pred) && IsConstTraversableOpType(pred->src())) {
status = pred->src()->input_edge(pred->src_output(), &pred);
if (!status.ok()) return;
}
if (edge_filter(*pred)) {
VLOG(4) << " " << pred->src()->name() << " must be const (is "
<< pred->src()->type_string() << ")";
(*compile_time_const_nodes)[pred->src()->id()] = true;
}
}
}
return;
}
// Mark any compile-time constant operator arguments as const.
std::vector<int> const_input_idxs;
status = GetCompileTimeConstInputs(node, &const_input_idxs, flib_runtime);
if (!status.ok() || const_input_idxs.empty()) {
return;
}
VLOG(3) << "marking consts for must-be-const inputs of " << node->name();
for (Edge const* edge : node->in_edges()) {
if (!edge->IsControlEdge() &&
absl::c_binary_search(const_input_idxs, edge->dst_input()) &&
edge_filter(*edge)) {
// Do not mark IdentityN / While nodes as compile-time const.
// If the src node of the `pred` is an IdentityN do not mark it as a
// compile-time const. Only mark the corresponding input to the
// IdentityN/While node as a const. XLA IdentityN op simply forwards its
// inputs so this is safe; loop invariance is checked elsewhere.
while (edge_filter(*edge) && IsConstTraversableOpType(edge->src())) {
status = edge->src()->input_edge(edge->src_output(), &edge);
if (!status.ok()) return;
}
if (edge_filter(*edge)) {
VLOG(4) << " input " << edge->dst_input() << ": "
<< edge->src()->name() << " must be const (is "
<< edge->src()->type_string() << ")";
(*compile_time_const_nodes)[edge->src()->id()] = true;
}
}
}
};
// Post-order traversal visits nodes in reverse topological order for an
// acyclic graph.
DFS(g, /*enter=*/{}, /*leave=*/visit, NodeComparatorName{},
[](const Edge& edge) { return !edge.src()->IsNextIteration(); });
if (compile_time_const_arg_indices && !edge_filter_input) {
VLOG(5) << "Setting the cache on the graph: " << &g;
g.GetConstArgIndicesCache() = *compile_time_const_arg_indices;
}
return status;
}
absl::Status GetCompileTimeConstInputs(const OpKernel* op_kernel,
std::vector<int>* const_input_idxs,
FunctionLibraryRuntime* flib_runtime) {
return GetCompileTimeConstInputs(op_kernel->def(), op_kernel,
/*op_def=*/nullptr, const_input_idxs,
flib_runtime);
}
} // namespace tensorflow