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Revert D31514095: Use kernel_func_name from aotCompiler

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Test Plan: revert-hammer

Differential Revision:
D31514095 (7b55dc8340)

Original commit changeset: b70c8e2c7336

fbshipit-source-id: ad4d828f33506e612b51c276149fa0e12b0565d5
This commit is contained in:
Natalia Gimelshein
2021-10-23 17:16:26 -07:00
committed by Facebook GitHub Bot
parent 313939c9c6
commit b6fa998892
5 changed files with 17 additions and 27 deletions
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22
binaries/aot_model_compiler.cc
View File

@ -90,10 +90,6 @@ std::string getNncKernelId() {
":" + version_token;
}
std::string getNncKernelFuncName(const std::string& method_name) {
return "nnc_" + FLAGS_model_name + "_" + FLAGS_model_version + "_" + method_name;
}
void writeOutputLlvmAssembly(const std::string& asm_code) {
std::string output_llvm_file_name = FLAGS_output_llvm;
if (output_llvm_file_name.empty()) {
@ -112,13 +108,18 @@ c10::IValue preprocess(
const c10::Dict<c10::IValue, c10::IValue>& method_compile_spec,
const torch::jit::BackendDebugHandleGenerator& generate_debug_handles) {
std::string output_llvm_file_name = FLAGS_output_llvm;
if (output_llvm_file_name.empty()) {
output_llvm_file_name =
FLAGS_model.substr(0, FLAGS_model.find('.')) + ".compiled.ll";
}
auto method = mod.get_method(FLAGS_method_name);
auto graph = method.function().graph()->copy();
auto sizes = getInputSizes(method_compile_spec);
auto kernel_func_name = getNncKernelFuncName(FLAGS_method_name);
auto compiled = torch::jit::mobile::nnc::aotCompile(
FLAGS_method_name, graph, sizes, kernel_func_name);
std::string llvm_asm_code;
auto compiled = torch::jit::mobile::nnc::aotCompile(FLAGS_method_name, graph, sizes);
writeOutputLlvmAssembly(compiled.second);
auto func = std::move(compiled.first);
@ -140,8 +141,8 @@ int main(int argc, char** argv) {
" --model=<model file>"
" --model_name=<model name>"
" --model_version=<model version>"
" --input_dims=<input dimensions like '1,3,224,224;2,2'>"
" [--method_name=<method name>]"
" --input_dims='1,3,224,224'"
" [--method_name=<mehhod name>]"
" [--output_llvm=<llvm assembly output file path>]"
" [--output_model=<output model file path>]");
@ -152,9 +153,6 @@ int main(int argc, char** argv) {
}
CAFFE_ENFORCE(!FLAGS_model.empty(), c10::UsageMessage());
CAFFE_ENFORCE(!FLAGS_model_name.empty(), c10::UsageMessage());
CAFFE_ENFORCE(!FLAGS_model_version.empty(), c10::UsageMessage());
CAFFE_ENFORCE(!FLAGS_input_dims.empty(), c10::UsageMessage());
std::string output_model_name = FLAGS_output_model;
if (output_model_name.empty()) {

7
torch/csrc/jit/mobile/nnc/aot_compiler.cpp
View File

@ -87,8 +87,7 @@ std::unique_ptr<Function> compileMethod(
std::pair<std::unique_ptr<Function>, const std::string> aotCompile(
const std::string& method_name,
std::shared_ptr<Graph>& g,
const std::vector<std::vector<int64_t>>& sizes,
const std::string& kernel_func_name) {
const std::vector<std::vector<int64_t>>& sizes) {
GRAPH_DEBUG("Input sizes ", sizes);
GRAPH_DEBUG("Method name ", method_name);
@ -112,9 +111,7 @@ std::pair<std::unique_ptr<Function>, const std::string> aotCompile(
GRAPH_DUMP("graph after shape propagation ", g);
std::shared_ptr<tensorexpr::TensorExprKernel> kernel =
std::make_shared<tensorexpr::TensorExprKernel>(
TensorExprKernel(g, {}, false, kernel_func_name));
std::make_shared<tensorexpr::TensorExprKernel>(g);
const std::string compiled_assembly = kernel->getCodeText();
auto func = compileMethod(kernel, method_name, sizes);

3
torch/csrc/jit/mobile/nnc/aot_compiler.h
View File

@ -14,8 +14,7 @@ namespace nnc {
TORCH_API std::pair<std::unique_ptr<Function>, const std::string> aotCompile(
const std::string& method_name,
std::shared_ptr<Graph>& subgraph,
const std::vector<std::vector<int64_t>>& sizes,
const std::string& kernel_func_name = "func");
const std::vector<std::vector<int64_t>>& sizes);
} // namespace nnc
} // namespace mobile

8
torch/csrc/jit/tensorexpr/kernel.cpp
View File

@ -1172,19 +1172,17 @@ void TensorExprKernel::compile() {
stmt,
bufferArgs_,
device_,
kernel_func_name_);
SubgraphUtils::generateNameForGraph(graph_));
}
TensorExprKernel::TensorExprKernel(
const std::shared_ptr<Graph>& subgraph,
std::unordered_map<c10::Symbol, NNCLoweringFunction> custom_lowerings,
bool pre_alloc /*= false*/,
const std::string& kernel_func_name)
bool pre_alloc /*= false*/)
: graph_(subgraph),
code_(subgraph, ""),
custom_lowerings_(std::move(custom_lowerings)),
pre_alloc_(pre_alloc),
kernel_func_name_(kernel_func_name) {
pre_alloc_(pre_alloc) {
allow_fallback_ = fallbackAllowed();
if (!allow_fallback_) {
compile();

4
torch/csrc/jit/tensorexpr/kernel.h
View File

@ -93,8 +93,7 @@ class TORCH_API TensorExprKernel {
const std::shared_ptr<Graph>& subgraph,
std::unordered_map<c10::Symbol, NNCLoweringFunction> custom_lowerings =
{},
bool pre_alloc = false,
const std::string& kernel_func_name = "func");
bool pre_alloc = false);
void run(Stack& stack);
void runFast(
@ -236,7 +235,6 @@ class TORCH_API TensorExprKernel {
std::unordered_map<c10::Symbol, NNCLoweringFunction> custom_lowerings_;
bool pre_alloc_{false};
const std::string& kernel_func_name_;
};
TORCH_API int& getTECudaPointwiseLoopLevels();