1 | /* Copyright 2022 The TensorFlow Authors. All Rights Reserved. |
2 | |
3 | Licensed under the Apache License, Version 2.0 (the "License"); |
4 | you may not use this file except in compliance with the License. |
5 | You may obtain a copy of the License at |
6 | |
7 | http://www.apache.org/licenses/LICENSE-2.0 |
8 | |
9 | Unless required by applicable law or agreed to in writing, software |
10 | distributed under the License is distributed on an "AS IS" BASIS, |
11 | WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. |
12 | See the License for the specific language governing permissions and |
13 | limitations under the License. |
14 | ==============================================================================*/ |
15 | |
16 | #include "llvm/ADT/SmallVector.h" |
17 | #include "llvm/ADT/StringRef.h" |
18 | #include "mlir/Dialect/Func/IR/FuncOps.h" // from @llvm-project |
19 | #include "mlir/IR/Attributes.h" // from @llvm-project |
20 | #include "mlir/IR/Builders.h" // from @llvm-project |
21 | #include "mlir/IR/BuiltinOps.h" // from @llvm-project |
22 | #include "mlir/IR/Operation.h" // from @llvm-project |
23 | #include "mlir/IR/SymbolTable.h" // from @llvm-project |
24 | #include "mlir/IR/Visitors.h" // from @llvm-project |
25 | #include "mlir/Pass/Pass.h" // from @llvm-project |
26 | #include "mlir/Pass/PassManager.h" // from @llvm-project |
27 | #include "mlir/Support/LogicalResult.h" // from @llvm-project |
28 | #include "mlir/Transforms/Passes.h" // from @llvm-project |
29 | #include "tensorflow/compiler/mlir/tensorflow/ir/tf_ops.h" |
30 | #include "tensorflow/compiler/mlir/tensorflow/ir/tf_ops_n_z.h" |
31 | #include "tensorflow/compiler/mlir/tensorflow/utils/attribute_utils.h" |
32 | #include "tensorflow/dtensor/mlir/device_utils.h" |
33 | #include "tensorflow/dtensor/mlir/dtensor_mlir_passes.h" |
34 | #include "tensorflow/dtensor/mlir/op_utils.h" |
35 | #include "tensorflow/dtensor/mlir/spmd_expander_common.h" |
36 | |
37 | namespace tensorflow { |
38 | namespace dtensor { |
39 | |
40 | namespace { |
41 | #define GEN_PASS_DEF_DTENSORPROPAGATEDEVICEIDTOFUNCTIONARGS |
42 | #include "tensorflow/dtensor/mlir/dtensor_passes.h.inc" |
43 | |
44 | // Holds information on functions to rewrite. `function` is the function |
45 | // definition or function that needs to be updated and `callsite_ops` holds a |
46 | // list of ops that calls the `function`. |
47 | struct FunctionToChangeInfo { |
48 | mlir::func::FuncOp function; |
49 | llvm::SmallVector<mlir::Operation*, 4> callsite_ops; |
50 | }; |
51 | |
52 | // Finds all functions in graph that is not a public functions and retrieves |
53 | // their callsite operations. |
54 | llvm::SmallVector<FunctionToChangeInfo, 4> FindFunctionsToRewrite( |
55 | mlir::ModuleOp module) { |
56 | llvm::SmallVector<FunctionToChangeInfo, 4> functions_to_change; |
57 | module.walk([&](mlir::Operation* op) { |
58 | if (!llvm::isa<mlir::TF::StatefulPartitionedCallOp, |
59 | mlir::TF::PartitionedCallOp>(op)) |
60 | return; |
61 | |
62 | // Extract function symbol from PartitionedCall or StatefulPartitionedCall |
63 | // op. |
64 | llvm::StringRef symbol; |
65 | if (auto call_op = |
66 | llvm::dyn_cast<mlir::TF::StatefulPartitionedCallOp>(op)) { |
67 | symbol = call_op.f(); |
68 | } else { |
69 | auto symbol_ref = llvm::dyn_cast<mlir::TF::PartitionedCallOp>(op).f(); |
70 | if (!symbol_ref.isa<mlir::FlatSymbolRefAttr>()) return; |
71 | symbol = symbol_ref.getRootReference().getValue(); |
72 | } |
73 | |
74 | // If function definition could be found, then extract all function usages. |
75 | auto function = MaybeFindFunction(op); |
76 | if (!function || function->isPublic()) return; |
77 | |
78 | auto function_uses = mlir::SymbolTable::getSymbolUses( |
79 | mlir::StringAttr::get(module.getContext(), symbol), |
80 | &module.getBodyRegion()); |
81 | if (!function_uses) return; |
82 | |
83 | llvm::SmallVector<mlir::Operation*, 4> function_use_ops; |
84 | for (auto function_use : *function_uses) |
85 | function_use_ops.emplace_back(function_use.getUser()); |
86 | |
87 | functions_to_change.emplace_back( |
88 | FunctionToChangeInfo{function.value(), function_use_ops}); |
89 | }); |
90 | |
91 | return functions_to_change; |
92 | } |
93 | |
94 | // Rewrites function such that 0th argument of type `type` is added to |
95 | // `function`. |
96 | void PrependArgumentToFunction(mlir::func::FuncOp function, mlir::Type type, |
97 | mlir::OpBuilder* builder) { |
98 | auto& function_body = function.front(); |
99 | function_body.insertArgument(static_cast<unsigned>(0), type, |
100 | function.getLoc()); |
101 | auto new_argument_types = |
102 | llvm::to_vector<4>(function_body.getArgumentTypes()); |
103 | function.setType( |
104 | mlir::FunctionType::get(builder->getContext(), new_argument_types, |
105 | function.getFunctionType().getResults())); |
106 | } |
107 | |
108 | // Rewrites function callsites ops. As function signatures are already updated, |
109 | // simply add 0th argument of the parent function to 0th operand of the callsite |
110 | // operation. |
111 | mlir::LogicalResult PrependDeviceIdToCallsites(mlir::OpBuilder* builder, |
112 | mlir::Operation* op) { |
113 | auto device_id_or_status = DeviceId(op); |
114 | if (!device_id_or_status.ok()) |
115 | return op->emitOpError( |
116 | "Failed during PropagateDeviceIdToFunctionArgs pass. All functions " |
117 | "must have device id as 0th argument." ); |
118 | |
119 | auto new_operands = llvm::to_vector<4>(op->getOperands()); |
120 | new_operands.insert(new_operands.begin(), device_id_or_status.value()); |
121 | |
122 | builder->setInsertionPoint(op); |
123 | mlir::Operation* new_call = nullptr; |
124 | if (auto stateful_partitioned_call = |
125 | llvm::dyn_cast<mlir::TF::StatefulPartitionedCallOp>(op)) { |
126 | new_call = builder->create<mlir::TF::StatefulPartitionedCallOp>( |
127 | op->getLoc(), op->getResultTypes(), new_operands, |
128 | stateful_partitioned_call.f(), stateful_partitioned_call.config(), |
129 | stateful_partitioned_call.config_proto(), |
130 | stateful_partitioned_call.executor_type()); |
131 | } else { |
132 | auto partitioned_call = llvm::cast<mlir::TF::PartitionedCallOp>(op); |
133 | new_call = builder->create<mlir::TF::PartitionedCallOp>( |
134 | op->getLoc(), op->getResultTypes(), new_operands, partitioned_call.f(), |
135 | partitioned_call.config(), partitioned_call.config_proto(), |
136 | partitioned_call.executor_type()); |
137 | } |
138 | |
139 | for (auto results : llvm::zip(op->getResults(), new_call->getResults())) |
140 | std::get<0>(results).replaceAllUsesWith(std::get<1>(results)); |
141 | |
142 | op->erase(); |
143 | |
144 | return mlir::success(); |
145 | } |
146 | |
147 | // Pass that rewrites the functions in graph so that 0th argument of the main |
148 | // function (i.e. device_id) is present on all functions in the graph. |
149 | struct DTensorPropagateDeviceIdToFunctionArgs |
150 | : public impl::DTensorPropagateDeviceIdToFunctionArgsBase< |
151 | DTensorPropagateDeviceIdToFunctionArgs> { |
152 | void runOnOperation() override { |
153 | mlir::MLIRContext& context = getContext(); |
154 | auto module = getOperation(); |
155 | mlir::OpBuilder builder(&context); |
156 | |
157 | // Extracts device id argument from main function. |
158 | mlir::func::FuncOp main_func = |
159 | module.lookupSymbol<mlir::func::FuncOp>("main" ); |
160 | auto device_id_or_status = DeviceId(&main_func.getBody().front().front()); |
161 | if (!device_id_or_status.ok()) { |
162 | main_func.emitOpError( |
163 | "Error in PropagateDeviceIdToFunctionArgs pass. Main function must " |
164 | "have device id as 0th function argument." ); |
165 | return signalPassFailure(); |
166 | } |
167 | auto device_id_from_main_function = device_id_or_status.value(); |
168 | // First iterate through all functions to rewrite and update the signatures |
169 | // first. |
170 | const auto functions_to_update = FindFunctionsToRewrite(module); |
171 | for (const auto& function_to_update : functions_to_update) |
172 | PrependArgumentToFunction(function_to_update.function, |
173 | device_id_from_main_function.getType(), |
174 | &builder); |
175 | |
176 | // Once all function signatures are updated, rewrite the callsite ops. |
177 | for (const auto& function_to_update : functions_to_update) { |
178 | for (auto call_site_op : function_to_update.callsite_ops) { |
179 | if (mlir::failed(PrependDeviceIdToCallsites(&builder, call_site_op))) |
180 | return signalPassFailure(); |
181 | } |
182 | } |
183 | }; |
184 | }; |
185 | |
186 | } // namespace |
187 | |
188 | std::unique_ptr<mlir::OperationPass<mlir::ModuleOp>> |
189 | CreateDTensorPropagateDeviceIdToFunctionArgs() { |
190 | return std::make_unique<DTensorPropagateDeviceIdToFunctionArgs>(); |
191 | } |
192 | |
193 | } // namespace dtensor |
194 | } // namespace tensorflow |
195 | |