pytorch/test/cpp/jit
Meghan Lele 8f5ad00e13 [JIT] Print out CU address in ClassType::repr_str() (#50194)
Summary:
Pull Request resolved: https://github.com/pytorch/pytorch/pull/50194

**Summary**
`ClassType::repr_str()` prints out only the name of a `ClassType`, which
is not always enough to disambiguate it. In some situations, two
`ClassTypes` are compared and do not match despite having identical
names because they are in separate compilation units. In such cases, the
error message can seem nonsensical (e.g. `expected type T but found type
T`). This commit modifies `ClassType::repr_str()` so that it prints out
the address of the type's compilation unit to make these messages less
puzzling (e.g. `expected type T (0x239023) but found type T (0x230223)`).

**Test Plan**
This commit adds a unit test, `ClassTypeTest.IdenticalTypesDifferentCus`
that reproduces this situation.

**Fixes**
This commit fixes #46212.

Test Plan: Imported from OSS

Reviewed By: tugsbayasgalan

Differential Revision: D25933082

Pulled By: SplitInfinity

fbshipit-source-id: ec71b6728be816edd6a9c2b2d5075ead98d8bc88
2021-01-19 23:04:30 -08:00
..
__init__.py
CMakeLists.txt
README.md
test_alias_analysis.cpp [codemod][fbcode/caffe2] Apply clang-format update fixes 2021-01-09 14:37:36 -08:00
test_argument_spec.cpp [codemod][fbcode/caffe2] Apply clang-format update fixes 2021-01-09 14:37:36 -08:00
test_autodiff.cpp Add inputs argument to autograd.backward() (#46855) 2020-11-02 14:32:38 -08:00
test_backend.cpp
test_class_import.cpp
test_class_parser.cpp
test_class_type.cpp [JIT] Print out CU address in ClassType::repr_str() (#50194) 2021-01-19 23:04:30 -08:00
test_cleanup_passes.cpp
test_code_template.cpp
test_constant_pooling.cpp [JIT] Fix Dict bug in constant hashing (#45929) 2020-10-07 17:40:17 -07:00
test_create_autodiff_subgraphs.cpp
test_custom_class.cpp [TorchScript] Support user defined classes as constants (#5062) 2020-11-16 20:52:02 -08:00
test_custom_class_registrations.cpp [TorchBind] Support using lambda function as TorchBind constructor (#47819) 2020-11-12 09:29:34 -08:00
test_custom_class_registrations.h
test_custom_operators.cpp
test_dce.cpp
test_fuser.cpp [Pytorch][Annotation] Update inlined callstack with module instance info (#47416) 2020-12-03 10:44:46 -08:00
test_gpu.cpp [codemod][fbcode/caffe2] Apply clang-format update fixes 2021-01-09 14:37:36 -08:00
test_graph_executor.cpp [DI] Allow explicit taskLauncher for torchscript interpreter (#46865) 2020-11-04 17:07:55 -08:00
test_inliner.cpp
test_interface.cpp
test_interpreter.cpp JIT: guard DifferentiableGraph node (#49433) 2021-01-08 20:01:27 -08:00
test_interpreter_async.pt [DI] Allow explicit taskLauncher for torchscript interpreter (#46865) 2020-11-04 17:07:55 -08:00
test_ir.cpp
test_irparser.cpp
test_jit_type.cpp [PyTorch][codemod] Replace immediately-dereferenced expect calls w/expectRef (#50228) 2021-01-13 16:13:55 -08:00
test_lite_interpreter.cpp [PyTorch Mobile] Export Operator List from Mobile CompilationUnit instead of from TorchScript Model (#49385) 2020-12-18 11:17:57 -08:00
test_lite_trainer.cpp
test_memory_dag.cpp
test_misc.cpp [PyTorch][codemod] Replace immediately-dereferenced expect calls w/expectRef (#50228) 2021-01-13 16:13:55 -08:00
test_mobile_type_parser.cpp
test_module_api.cpp Expose run_async function on torch::jit::Method (#48607) 2020-12-11 11:17:58 -08:00
test_peephole_optimize.cpp
test_qualified_name.cpp
test_save_load.cpp Adding JIT support for cuda streams and events (#48020) 2020-12-29 20:24:57 -08:00
test_schema_matching.cpp
test_subgraph_matcher.cpp [JIT] Support multiple outputs in subgraph matcher. (#48992) 2020-12-15 13:09:24 -08:00
test_subgraph_rewriter.cpp [JIT] Support multiple outputs in subgraph matcher. (#48992) 2020-12-15 13:09:24 -08:00
test_subgraph_utils.cpp [JIT] SubgraphUtils: add a function for generating a string name for a given graph. (#47253) 2020-11-03 16:36:41 -08:00
test_utils.cpp
test_utils.h
tests_setup.py Adding JIT support for cuda streams and events (#48020) 2020-12-29 20:24:57 -08:00
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*'