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Summary: Add an api to backport a model vn to model vi. It accept an input model (file or buffer) and output a model (file or buffer) with an expected bytecode version. In this change, the input is a model and it can come from a file or buffer. The output is a model and can be either file path or buffer. When backport fails, function return false with a warning message : ``` /Users/chenlai/pytorch/cmake-build-debug/bin/test_jit --gtest_filter=LiteInterpreterTest.BackPortByteCodeModelV4:LiteInterpreterTest/*.BackPortByteCodeModelV4:*/LiteInterpreterTest.BackPortByteCodeModelV4/*:*/LiteInterpreterTest/*.BackPortByteCodeModelV4 --gtest_color=no Testing started at 2:32 PM ... CUDA not available. Disabling CUDA and MultiCUDA tests [W backport.cpp:419] Warning: Backport doesn't support backport to version3 (function _backport_for_mobile_impl) Process finished with exit code 0 ``` ## Test 1. Run both `caffe2/test/cpp/jit/test_lite_interpreter.cpp` and `caffe2/test/mobile/test_bytecode.py`. 2. Run all prod models with backport api. Pull Request resolved: https://github.com/pytorch/pytorch/pull/56802 ghstack-source-id: 128425510 Test Plan: CI Reviewed By: raziel, iseeyuan Differential Revision: D27844651 fbshipit-source-id: 8a803cf6c76433ee0a3049b1a5570585d569f8d6 |
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|---|---|---|
| .. | ||
| __init__.py | ||
| CMakeLists.txt | ||
| README.md | ||
| script_module_v4.ptl | ||
| script_module_v5.ptl | ||
| test_alias_analysis.cpp | ||
| test_argument_spec.cpp | ||
| test_autodiff.cpp | ||
| test_backend.cpp | ||
| test_backend_compiler_lib.cpp | ||
| test_backend_compiler_preprocess.cpp | ||
| test_backend_lib.cpp | ||
| 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_cs_debug_info_serialization.cpp | ||
| test_custom_class.cpp | ||
| test_custom_class_registrations.cpp | ||
| 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 | ||
| test_lite_trainer.cpp | ||
| test_memory_dag.cpp | ||
| test_misc.cpp | ||
| 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 | ||
| test_subgraph_rewriter.cpp | ||
| test_subgraph_utils.cpp | ||
| test_utils.cpp | ||
| test_utils.h | ||
| tests_setup.py | ||
| 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*'