pytorch/test/cpp/jit
Martin Yuan 3551bd31be [PyTorch] Lite interpreter with a backend delegate (#54462)
Summary:
Pull Request resolved: https://github.com/pytorch/pytorch/pull/54462

Unclean files during sync - Sat Mar 20 04:00:02 PDT 2021

Unclean files during sync - Sun Mar 21 04:00:01 PDT 2021
ghstack-source-id: 124585992

Test Plan:
```
buck run xplat/caffe2/fb/test/delegate:interpreter_test -- --model_file_path=/path/to/mobile_model.ptl
```

Reviewed By: raziel

Differential Revision: D27232309

fbshipit-source-id: 8504a3185339d73bfa6e924485c4745acf269cec
2021-04-06 00:55:26 -07:00
..
__init__.py
CMakeLists.txt [PyTorch] Lite interpreter with a backend delegate (#54462) 2021-04-06 00:55:26 -07:00
README.md
test_alias_analysis.cpp
test_argument_spec.cpp
test_autodiff.cpp
test_backend.cpp Adds a bool is_available() method to the backend contract (#53068) 2021-03-10 00:24:16 -08:00
test_backend_compiler_lib.cpp [PyTorch] Lite interpreter with a backend delegate (#54462) 2021-04-06 00:55:26 -07:00
test_backend_compiler_preprocess.cpp [PyTorch] Lite interpreter with a backend delegate (#54462) 2021-04-06 00:55:26 -07:00
test_backend_lib.cpp [PyTorch] Lite interpreter with a backend delegate (#54462) 2021-04-06 00:55:26 -07:00
test_class_import.cpp
test_class_parser.cpp
test_class_type.cpp
test_cleanup_passes.cpp
test_code_template.cpp
test_constant_pooling.cpp
test_create_autodiff_subgraphs.cpp
test_custom_class.cpp
test_custom_class_registrations.cpp [WIP][FX] Fix tracing support for torchbind (#52884) 2021-03-05 23:40:16 -08:00
test_custom_class_registrations.h
test_custom_operators.cpp
test_dce.cpp
test_fuser.cpp
test_gpu.cpp
test_graph_executor.cpp
test_inliner.cpp
test_interface.cpp
test_interpreter.cpp
test_interpreter_async.pt
test_ir.cpp
test_irparser.cpp
test_jit_type.cpp
test_lite_interpreter.cpp [PyTorch Mobile] Dedup method names in bytecode serialization (#53677) 2021-03-16 15:24:47 -07:00
test_lite_trainer.cpp [Pytorch Mobile] 'fix' filter of named parameters for FL (#54633) 2021-03-31 09:21:35 -07:00
test_memory_dag.cpp
test_misc.cpp Support needsOutputs for RecordFunction and ObserverUtil improvements (#55012) 2021-04-02 15:16:17 -07:00
test_mobile_type_parser.cpp
test_module_api.cpp
test_peephole_optimize.cpp
test_qualified_name.cpp
test_save_load.cpp
test_schema_matching.cpp
test_subgraph_matcher.cpp Teach Python TS frontend to parse complex literals (#52881) 2021-03-24 08:12:17 -07:00
test_subgraph_rewriter.cpp
test_subgraph_utils.cpp
test_utils.cpp
test_utils.h
tests_setup.py Merge CUDA Streams and Events (#53902) 2021-04-05 08:19:55 -07:00
torch_python_test.cpp

JIT C++ Tests

Adding a new test

First, create a new test file. Test files should have be placed in this directory, with a name that starts with test_, like test_foo.cpp.

In general a single test suite

Add your test file to the JIT_TEST_SRCS list in test/cpp/jit/CMakeLists.txt.

A test file may look like:

#include <gtest/gtest.h>

using namespace ::torch::jit

TEST(FooTest, BarBaz) {
   // ...
}

// Append '_CUDA' to the test case name will automatically filter it out if CUDA
// is not compiled.
TEST(FooTest, NeedsAGpu_CUDA) {
   // ...
}

// Similarly, if only one GPU is detected, tests with `_MultiCUDA` at the end
// will not be run.
TEST(FooTest, NeedsMultipleGpus_MultiCUDA) {
   // ...
}

Building and running the tests

The following commands assume you are in PyTorch root.

# ... Build PyTorch from source, e.g.
python setup.py develop
# (re)build just the binary
ninja -C build bin/test_jit
# run tests
build/bin/test_jit --gtest_filter='glob_style_filter*'