mirror of
https://github.com/saymrwulf/pytorch.git
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d1c5f9e439
Summary: Pull Request resolved: https://github.com/pytorch/pytorch/pull/72587 This pattern frequently appears in a few graphs: ``` %result = prim::If(%condition) block0(): -> (%a) block1(): -> (%b) ``` This is slow, particularly in static runtime. Static runtime creates memory planners/block runners for each sub-block, which eats up a lot of memory and introduces a lot of extra overhead for this relatively simple operation. This diff introduces a new op that replaces nodes like the above with a single op meant to act like a ternary operator: ``` %result = prim::IfThenElse(%condition, %a, %b) ``` Test Plan: New unit tests Reviewed By: eellison Differential Revision: D34091789 fbshipit-source-id: eb6a8c460c39b4c019a1f4ab1f3f1e5b6edc400c (cherry picked from commit 0f1b335e5b83f402bda2dcdd9ecb411e0b67c651) |
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| .. | ||
| upgrader_models | ||
| __init__.py | ||
| CMakeLists.txt | ||
| README.md | ||
| script_module_v4.ptl | ||
| script_module_v5.ptl | ||
| script_module_v6.ptl | ||
| test_add_if_then_else.cpp | ||
| 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_concat_opt.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_exception.cpp | ||
| test_flatbuffer.cpp | ||
| test_fuser.cpp | ||
| test_gpu.cpp | ||
| test_gpu_shift.cpp | ||
| test_gpu_validator.h | ||
| test_graph_executor.cpp | ||
| test_graph_iterator.cpp | ||
| test_inliner.cpp | ||
| test_interface.cpp | ||
| test_interpreter.cpp | ||
| test_interpreter_async.pt | ||
| test_ir.cpp | ||
| test_irparser.cpp | ||
| test_jit_logging_levels.cpp | ||
| test_jit_type.cpp | ||
| test_lite_interpreter.cpp | ||
| test_lite_interpreter_direct.cpp | ||
| test_lite_trainer.cpp | ||
| test_load_upgraders.cpp | ||
| test_memory_dag.cpp | ||
| test_misc.cpp | ||
| test_mobile_type_parser.cpp | ||
| test_module_api.cpp | ||
| test_op_replacement.cpp | ||
| test_peephole_optimize.cpp | ||
| test_qualified_name.cpp | ||
| test_save_load.cpp | ||
| test_schema_matching.cpp | ||
| test_script_profile.cpp | ||
| test_shape_analysis.cpp | ||
| test_stack_opt.cpp | ||
| test_subgraph_matcher.cpp | ||
| test_subgraph_rewriter.cpp | ||
| test_subgraph_utils.cpp | ||
| test_union.cpp | ||
| test_upgrader_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*'