pytorch/test/cpp/jit
Meghan Lele e2a291b396 [JIT] Add out-of-source-tree to_backend tests (#40842)
Summary:
Pull Request resolved: https://github.com/pytorch/pytorch/pull/40842

**Summary**
This commit adds out-of-source-tree tests for `to_backend`. These tests check
that a Module can be lowered to a backend, exported, loaded (in both
Python and C++) and executed.

**Fixes**
This commit fixes #40067.

Test Plan: Imported from OSS

Differential Revision: D22418731

Pulled By: SplitInfinity

fbshipit-source-id: 621ba4efc1b121fa76c9c7ca377792ac7440d250
2020-07-07 21:00:43 -07:00
..
__init__.py
CMakeLists.txt [JIT] Move TestBackend to test directory (#40840) 2020-07-07 21:00:38 -07:00
gtest.cpp
README.md
test_alias_analysis.cpp Unify boxed function signature between jit and c10 (#37034) 2020-06-29 19:24:26 -07:00
test_argument_spec.cpp
test_autodiff.cpp
test_backend.cpp [JIT] Add out-of-source-tree to_backend tests (#40842) 2020-07-07 21:00:43 -07:00
test_base.cpp Unify boxed function signature between jit and c10 (#37034) 2020-06-29 19:24:26 -07:00
test_base.h
test_class_import.cpp
test_class_parser.cpp
test_class_type.cpp
test_code_template.cpp
test_constant_pooling.cpp
test_create_autodiff_subgraphs.cpp
test_custom_class.cpp
test_custom_operators.cpp Unify boxed function signature between jit and c10 (#37034) 2020-06-29 19:24:26 -07:00
test_dce.cpp
test_fuser.cpp
test_gpu.cpp [nvFuser] Working towards reductions, codegen improvements (#40864) 2020-07-06 14:52:49 -07:00
test_graph_executor.cpp
test_inliner.cpp
test_interface.cpp
test_interpreter.cpp
test_ir.cpp
test_irparser.cpp [JIT] IRParser: properly parse negative numbers. (#39981) 2020-06-15 12:28:41 -07:00
test_jit_type.cpp [JIT] Add Type::repr_str to return human-readable str (#39544) 2020-06-10 12:01:24 -07:00
test_lite_interpreter.cpp s/torch::jit::class_/torch::class_/ (#40795) 2020-07-06 15:53:33 -07:00
test_misc.cpp Unify boxed function signature between jit and c10 (#37034) 2020-06-29 19:24:26 -07:00
test_mobile_type_parser.cpp [JIT] Add Type::repr_str to return human-readable str (#39544) 2020-06-10 12:01:24 -07:00
test_module_api.cpp
test_peephole_optimize.cpp
test_qualified_name.cpp
test_save_load.cpp Adds dynamic versioning pattern (#40279) 2020-06-24 12:52:50 -07:00
test_schema_matching.cpp Unify boxed function signature between jit and c10 (#37034) 2020-06-29 19:24:26 -07:00
test_subgraph_matcher.cpp [jit][subgraph_matcher] Enable regex matching for string attributes of node (#39454) 2020-06-05 23:03:38 -07:00
test_subgraph_rewriter.cpp [jit][subgraph_rewriter] Support list of filters (#39867) 2020-06-12 08:24:49 -07:00
test_subgraph_utils.cpp
test_utils.cpp
test_utils.h
tests.h [nvFuser] Working towards reductions, codegen improvements (#40864) 2020-07-06 14:52:49 -07:00
tests_setup.py
torch_python_test.cpp

JIT C++ Tests

How to add 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.

Here is an example test file you can copy-paste.

#include <test/cpp/jit/test_base.h>

// Tests go in torch::jit
namespace torch {
namespace jit {

// 1. Test cases are void() functions.
// 2. They start with the prefix `test`
void testCaseOne() {
    // ...
}

void testCaseTwo() {
    // ...
}
}
}

Then, register your test in tests.h:

// Add to TH_FORALL_TESTS_CUDA instead for CUDA-requiring tests
#define TH_FORALL_TESTS(_)             \
  _(ADFormulas)                        \
  _(Attributes)                        \
  ...
  _(CaseOne)  // note that the `test` prefix is omitted.
  _(CaseTwo)

We glob all the test files together in CMakeLists.txt so that you don't have to edit it every time you add a test. Unfortunately, this means that in order to get the build to pick up your new test file, you need to re-run cmake:

python setup.py build --cmake

Why do we have two different test runners?

We have two different ways of running our cpp tests:

  1. With gtest, from a standalone binary.
  2. With Python, from TestJit.test_cpp and TestJit.test_cpp_cuda (in test/test_jit.py)

We want both because we need to test things from a pure-C++ environment and with all our various Python patch-points enabled.

How do I run the tests?

The following commands assume you are in PyTorch root.

  1. With gtest:
    # (re)build the test binary
    ninja build/bin/test_jit
    # run
    build/bin/test_jit --gtest_filter='glob_style_filter*'
    
  2. With Python:
    python test/test_jit.py TestJit.test_cpp TestJit.test_cpp_cuda