mirror of
https://github.com/zebrajr/pytorch.git
synced 2025-12-07 00:21:07 +01:00
4cb534f92e
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
87 lines
2.2 KiB
C++
87 lines
2.2 KiB
C++
#include <ATen/core/ivalue.h>
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#include <c10/util/Exception.h>
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#include <torch/csrc/WindowsTorchApiMacro.h>
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#include <torch/csrc/jit/api/module.h>
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#include <torch/script.h>
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namespace torch {
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namespace jit {
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#ifdef _MSC_VER
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#define JIT_TEST_API
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#else
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#define JIT_TEST_API TORCH_API
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#endif
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namespace {
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bool isSandcastle() {
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return (
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(std::getenv("SANDCASTLE")) ||
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(std::getenv("TW_JOB_USER") &&
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std::string(std::getenv("TW_JOB_USER")) == "sandcastle"));
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}
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void testEvalModeForLoadedModule() {
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if (isSandcastle())
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return; // The module file to load is not generated in Sandcastle
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std::string module_path = "dropout_model.pt";
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torch::jit::Module module = torch::jit::load(module_path);
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AT_ASSERT(module.attr("dropout").toModule().is_training());
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module.eval();
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AT_ASSERT(!module.attr("dropout").toModule().is_training());
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module.train();
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AT_ASSERT(module.attr("dropout").toModule().is_training());
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}
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void testSerializationInterop() {
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if (isSandcastle()) {
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// The module file to load is not generated in Sandcastle
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return;
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}
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// This should be generated by `test/cpp/jit/tests_setup.py`
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std::ifstream input_stream("ivalue.pt");
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std::vector<char> input;
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input.insert(
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input.begin(),
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std::istream_iterator<char>(input_stream),
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std::istream_iterator<char>());
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IValue ivalue = pickle_load(input);
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auto elements = ivalue.toTuple()->elements();
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auto ones = torch::ones({2, 2});
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AT_ASSERT(ones.equal(elements.at(0).toTensor()));
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// NOLINTNEXTLINE(cppcoreguidelines-avoid-magic-numbers)
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auto twos = torch::ones({3, 5}) * 2;
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AT_ASSERT(twos.equal(elements.at(1).toTensor()));
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}
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void testTorchSaveError() {
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if (isSandcastle()) {
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// The file to load is not generated in Sandcastle
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return;
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}
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// This should be generated by `test/cpp/jit/tests_setup.py`
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bool passed = true;
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try {
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torch::jit::load("eager_value.pt");
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passed = false;
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} catch (const std::exception& c) {
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}
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// Ensure torch::jit::load did not run
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AT_ASSERT(passed);
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}
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} // namespace
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JIT_TEST_API void runJITCPPTests() {
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// TODO: this test never ran before and is broken.
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// testSerializationInterop();
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testEvalModeForLoadedModule();
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testTorchSaveError();
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}
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} // namespace jit
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} // namespace torch
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