pytorch/torch/csrc/jit/codegen/fuser/interface.cpp
Nikita Shulga 4cb534f92e Make PyTorch code-base clang-tidy compliant (#56892)
Summary:
This is an automatic change generated by the following script:
```
#!/usr/bin/env python3
from subprocess import check_output, check_call
import os

def get_compiled_files_list():
    import json
    with open("build/compile_commands.json") as f:
        data = json.load(f)
    files = [os.path.relpath(node['file']) for node in data]
    for idx, fname in enumerate(files):
        if fname.startswith('build/') and fname.endswith('.DEFAULT.cpp'):
            files[idx] = fname[len('build/'):-len('.DEFAULT.cpp')]
    return files

def run_clang_tidy(fname):
    check_call(["python3", "tools/clang_tidy.py", "-c", "build", "-x", fname,"-s"])
    changes = check_output(["git", "ls-files", "-m"])
    if len(changes) == 0:
        return
    check_call(["git", "commit","--all", "-m", f"NOLINT stubs for {fname}"])

def main():
    git_files = check_output(["git", "ls-files"]).decode("ascii").split("\n")
    compiled_files = get_compiled_files_list()
    for idx, fname in enumerate(git_files):
        if fname not in compiled_files:
            continue
        if fname.startswith("caffe2/contrib/aten/"):
            continue
        print(f"[{idx}/{len(git_files)}] Processing {fname}")
        run_clang_tidy(fname)

if __name__ == "__main__":
    main()
```

Pull Request resolved: https://github.com/pytorch/pytorch/pull/56892

Reviewed By: H-Huang

Differential Revision: D27991944

Pulled By: malfet

fbshipit-source-id: 5415e1eb2c1b34319a4f03024bfaa087007d7179
2021-04-28 14:10:25 -07:00

112 lines
3.3 KiB
C++

#include <torch/csrc/jit/codegen/fuser/interface.h>
#include <torch/csrc/jit/codegen/fuser/compiler.h>
#include <torch/csrc/jit/codegen/fuser/executor.h>
#include <torch/csrc/jit/codegen/fuser/fallback.h>
#include <torch/csrc/jit/codegen/fuser/kernel_cache.h>
#include <c10/util/Flags.h>
#include <stdexcept>
// NOLINTNEXTLINE(cppcoreguidelines-avoid-non-const-global-variables)
C10_DEFINE_bool(torch_jit_enable_cpu_fusion, false, "enable cpu fusion");
namespace torch {
namespace jit {
namespace detail {
// Note: CPU fusion is currently disabled due to test flakiness
// NOLINTNEXTLINE(cppcoreguidelines-avoid-non-const-global-variables)
bool cpu_fuser_enabled = false;
// NOLINTNEXTLINE(cppcoreguidelines-avoid-non-const-global-variables)
bool gpu_fuser_enabled = true;
} // namespace detail
int64_t registerFusion(const Node* fusion_group) {
return fuser::registerFusion(fusion_group);
}
void runFusion(const int64_t key, Stack& stack) {
const auto result = fuser::runFusion(key, stack);
if (!result)
fuser::runFallback(key, stack);
}
bool canFuseOnCPU() {
return fuser::hasFusionBackend(DeviceType::CPU) &&
(detail::cpu_fuser_enabled || FLAGS_torch_jit_enable_cpu_fusion);
}
bool canFuseOnGPU() {
return fuser::hasFusionBackend(DeviceType::CUDA) && detail::gpu_fuser_enabled;
}
void overrideCanFuseOnCPU(bool value) {
detail::cpu_fuser_enabled = value;
}
void overrideCanFuseOnGPU(bool value) {
detail::gpu_fuser_enabled = value;
}
// Uses the above interface by stuffing the graph into a node and treating that
// node as a fusion group.
std::vector<at::Tensor> debugLaunchGraph(
Graph& graph,
at::ArrayRef<at::Tensor> inputs) {
// Creates a fusion group node
auto wrapper_graph = std::make_shared<Graph>();
Node* fusion_group = wrapper_graph->insertNode(
wrapper_graph->createWithSubgraph(prim::FusionGroup));
fusion_group->g_(attr::Subgraph, graph.copy());
for (size_t i = 0; i < graph.inputs().size(); ++i) {
fusion_group->addInput(wrapper_graph->addInput());
}
for (size_t i = 0; i < graph.outputs().size(); ++i) {
wrapper_graph->registerOutput(fusion_group->addOutput());
}
// Creates the stack, registers and runs the fusion
Stack stack = fmap<IValue>(inputs);
const auto key = fuser::registerFusion(fusion_group);
fuser::runFusion(key, stack);
return fmap(stack, [](const IValue& iv) { return iv.toTensor(); });
}
std::string debugGetFusedKernelCode(
Graph& graph,
at::ArrayRef<at::Tensor> inputs) {
// Creates a fusion group node
auto wrapper_graph = std::make_shared<Graph>();
Node* fusion_group = wrapper_graph->insertNode(
wrapper_graph->createWithSubgraph(prim::FusionGroup));
fusion_group->g_(attr::Subgraph, graph.copy());
for (size_t i = 0; i < graph.inputs().size(); ++i) {
fusion_group->addInput(wrapper_graph->addInput());
}
for (size_t i = 0; i < graph.outputs().size(); ++i) {
wrapper_graph->registerOutput(fusion_group->addOutput());
}
// Creates the stack, registers and runs the fusion
Stack stack = fmap<IValue>(inputs);
const auto key = fuser::registerFusion(fusion_group);
std::string code;
if (!fuser::runFusion(key, stack, &code)) {
throw std::runtime_error("Could not run fusion for graph");
}
return code;
}
size_t nCompiledKernels() {
return fuser::nCompiledKernels();
}
} // namespace jit
} // namespace torch