mirror of
https://github.com/zebrajr/pytorch.git
synced 2025-12-07 12:21:27 +01:00
517c7c9861
Summary:
Anywhere we used #include "foo.h", we now say #include <foo.h>
Paths are adjusted to be rooted out of aten/src, torch/lib, or
the root level directory.
I modified CMakeLists.txt by hand to remove TH and THC from
the include paths.
I used the following script to do the canonicalization:
```
import subprocess
import re
import os.path
files = subprocess.check_output(['git', 'ls-files']).decode('utf-8').rstrip().split('\n')
for fn in files:
if not any(fn.endswith(suff) for suff in ['.cu', '.cpp', '.in', '.h', '.hpp', '.cu', '.cuh', '.cc']):
continue
if not any(fn.startswith(pref) for pref in ["aten/", "torch/"]):
continue
with open(fn, 'r') as f:
c = f.read()
def fmt(p):
return "#include <{}>".format(p)
def repl(m):
p = m.group(1)
if p in ["dlfcn.h", "unistd.h", "nvrtc.h", "cuda.h", "cuda_runtime.h", "cstdint", "cudnn.h", "Python.h", "cusparse.h", "cuda_runtime_api.h", "cuda_fp16.h", "cublas_v2.h", "stdint.h", "curand_kernel.h"]:
return fmt(p)
if any(p.startswith(pref) for pref in ["torch/csrc", "c10/", "ATen/", "caffe2/", "TH/", "THC/", "Eigen/", "gtest/", "zdl/", "gloo/", "onnx/", "miopen/"]):
return fmt(p)
for root in ["aten/src", "torch/lib", ""]:
for bad_root in [os.path.dirname(fn), "aten/src/TH", "aten/src/THC", "torch/csrc"]:
new_p = os.path.relpath(os.path.join(bad_root, p), root)
if not new_p.startswith("../") and (os.path.exists(os.path.join(root, new_p)) or os.path.exists(os.path.join(root, new_p + ".in"))):
return fmt(new_p)
print("ERROR: ", fn, p)
return m.group(0)
new_c = re.sub(r'#include "([^"]+)"', repl, c)
if new_c != c:
print(fn)
with open(fn, 'w') as f:
f.write(new_c)
```
Signed-off-by: Edward Z. Yang <ezyang@fb.com>
Pull Request resolved: https://github.com/pytorch/pytorch/pull/14849
Reviewed By: dzhulgakov
Differential Revision: D13363445
Pulled By: ezyang
fbshipit-source-id: 52361f878a672785f9306c9e9ab2513128092b68
107 lines
3.4 KiB
C++
107 lines
3.4 KiB
C++
#include <torch/csrc/jit/script/builtin_functions.h>
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#include <torch/csrc/api/include/torch/jit.h>
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#include <torch/csrc/jit/code_template.h>
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namespace torch { namespace jit { namespace script {
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auto scalar_operators_source = CodeTemplate(
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R"SCRIPT(
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def mul(a : ${Scalar}, b : Tensor) -> Tensor:
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return b * a
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def add(a : ${Scalar}, b : Tensor) -> Tensor:
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return b + a
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def ne(a : ${Scalar}, b : Tensor) -> Tensor:
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return b != a
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def eq(a : ${Scalar}, b : Tensor) -> Tensor:
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return b == a
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def lt(a : ${Scalar}, b : Tensor) -> Tensor:
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return b > a
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def le(a : ${Scalar}, b : Tensor) -> Tensor:
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return b >= a
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def gt(a : ${Scalar}, b : Tensor) -> Tensor:
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return b < a
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def ge(a : ${Scalar}, b : Tensor) -> Tensor:
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return b <= a
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def sub(a : ${Scalar}, b : Tensor) -> Tensor:
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return torch.neg(b) + a
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def div(a : ${Scalar}, b : Tensor) -> Tensor:
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return torch.reciprocal(b) * a
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)SCRIPT");
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auto _ntuple_ops = CodeTemplate(
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R"SCRIPT(
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def _${name}(x: BroadcastingList${Length}[${Scalar}]) -> List[${Scalar}]:
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return x
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)SCRIPT");
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struct BuiltinFunctionRegistry {
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const std::vector<Method*>& getAllBuiltinFunctionsFor(Symbol name) {
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const static std::vector<Method*> empty;
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// when initializing the builtin function library, we will re-enter
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// getAllBuiltinFunctionsFor since it is called in the compiler to
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// lookup builtins and initializing the builtin functions calls the compiler.
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// To avoid deadlocking, we use a recursive mutex (same thread can re-lock,
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// the mutex without waiting), and report no loaded builtins during init.
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std::lock_guard<std::recursive_mutex> guard(mutex);
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if(state == INTIIALIZING) {
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return empty;
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} else if (state == UNINITIALIZED) {
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state = INTIIALIZING;
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loadBuiltinFunctions();
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state = INITIALIZED;
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}
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JIT_ASSERT(state == INITIALIZED);
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auto it = builtins_by_name.find(name);
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if(it == builtins_by_name.end())
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return empty;
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return it->second;
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}
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private:
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void loadSource(const std::string& source) {
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auto module = std::make_shared<script::Module>();
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defineMethodsInModule(
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module, source, script::nativeResolver, /*self=*/nullptr);
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modules.push_back(module);
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for (auto& method : module->get_methods()) {
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builtins_by_name[Symbol::fromQualString("aten::" + method.key())].push_back(
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method->get());
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}
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}
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void loadBuiltinFunctions() {
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for(auto scalar : {"float", "int"}) {
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TemplateEnv env;
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env.s("Scalar", scalar);
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loadSource(scalar_operators_source.format(env));
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}
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using str_pair = std::pair<std::string, std::string>;
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const std::vector<str_pair> name_len = {
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str_pair("single", "1"),
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str_pair("pair", "2"),
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str_pair("triple", "3"),
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str_pair("quadruple", "4"),
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};
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for(auto scalar: {"float", "int"}) {
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for (auto pair: name_len) {
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TemplateEnv env;
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env.s("Scalar", scalar);
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env.s("name", pair.first);
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env.s("Length", pair.second);
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loadSource(_ntuple_ops.format(env));
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}
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}
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}
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enum {UNINITIALIZED, INTIIALIZING, INITIALIZED} state = UNINITIALIZED;
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std::recursive_mutex mutex;
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std::vector<std::shared_ptr<Module>> modules;
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std::unordered_map<Symbol, std::vector<Method*>> builtins_by_name;
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};
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TORCH_API const std::vector<Method*>& getAllBuiltinFunctionsFor(Symbol name) {
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static BuiltinFunctionRegistry registry;
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return registry.getAllBuiltinFunctionsFor(name);
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}
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}}}
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