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run_test.py
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#!/usr/bin/env python3
import argparse
import copy
import glob
import json
import os
import pathlib
import re
import shutil
import signal
import subprocess
import sys
import tempfile
import time
from contextlib import ExitStack
from datetime import datetime
from typing import Any, cast, Dict, List, NamedTuple, Optional, Sequence, Tuple, Union
import pkg_resources
import torch
import torch.distributed as dist
from torch.multiprocessing import current_process, get_context
from torch.testing._internal.common_utils import (
FILE_SCHEMA,
get_report_path,
IS_CI,
parser as common_parser,
retry_shell,
set_cwd,
shell,
TEST_WITH_ASAN,
TEST_WITH_ROCM,
TEST_WITH_SLOW_GRADCHECK,
)
REPO_ROOT = pathlib.Path(__file__).resolve().parent.parent
# using tools/ to optimize test run.
sys.path.insert(0, str(REPO_ROOT))
from tools.stats.import_test_stats import (
ADDITIONAL_CI_FILES_FOLDER,
TEST_CLASS_TIMES_FILE,
TEST_TIMES_FILE,
)
from tools.stats.upload_metrics import add_global_metric, emit_metric
from tools.testing.target_determination.determinator import (
AggregatedHeuristics,
get_prediction_confidences,
get_test_prioritizations,
)
from tools.testing.test_run import TestRun
from tools.testing.test_selections import (
calculate_shards,
get_test_case_configs,
NUM_PROCS,
ShardedTest,
THRESHOLD,
)
HAVE_TEST_SELECTION_TOOLS = True
# Make sure to remove REPO_ROOT after import is done
sys.path.remove(str(REPO_ROOT))
RERUN_DISABLED_TESTS = os.getenv("PYTORCH_TEST_RERUN_DISABLED_TESTS", "0") == "1"
CPP_TEST_PREFIX = "cpp"
CPP_TEST_PATH = "build/bin"
DISTRIBUTED_TEST_PREFIX = "distributed"
# Note [ROCm parallel CI testing]
# https://github.com/pytorch/pytorch/pull/85770 added file-granularity parallel testing.
# In .ci/pytorch/test.sh, TEST_CONFIG == "default", CUDA and HIP_VISIBLE_DEVICES is set to 0.
# This results in multiple test files sharing the same GPU.
# This should be a supported use case for ROCm, but it exposed issues in the kernel driver resulting in hangs.
# See https://github.com/pytorch/pytorch/issues/90940.
#
# Further, ROCm self-hosted runners have up to 4 GPUs.
# Device visibility was set to 0 to match CUDA test behavior, but this was wasting available GPU resources.
# Assigning each Pool worker their own dedicated GPU avoids the ROCm oversubscription issues.
# This should also result in better overall wall clock time since all GPUs can be utilized.
def maybe_set_hip_visible_devies():
# Special handling of ROCm GHA runners for parallel (file granularity) tests.
if torch.version.hip:
p = current_process()
if p.name != "MainProcess":
# this is a Process from a parallel Pool, not the MainProcess
os.environ["HIP_VISIBLE_DEVICES"] = str(p._identity[0] % NUM_PROCS)
def strtobool(s):
if s.lower() in ["", "0", "false", "off"]:
return False
return True
def parse_test_module(test):
return test.split(".")[0]
class TestChoices(list):
def __init__(self, *args, **kwargs):
super().__init__(args[0])
def __contains__(self, item):
return list.__contains__(self, parse_test_module(item))
def discover_tests(
base_dir: Optional[pathlib.Path] = None,
cpp_tests_dir: Optional[pathlib.Path] = None,
blocklisted_patterns: Optional[List[str]] = None,
blocklisted_tests: Optional[List[str]] = None,
extra_tests: Optional[List[str]] = None,
) -> List[str]:
"""
Searches for all python files starting with test_ excluding one specified by patterns.
If cpp_tests_dir is provided, also scan for all C++ tests under that directory. They
are usually found in build/bin
"""
def skip_test_p(name: str) -> bool:
rc = False
if blocklisted_patterns is not None:
rc |= any(name.startswith(pattern) for pattern in blocklisted_patterns)
if blocklisted_tests is not None:
rc |= name in blocklisted_tests
return rc
cwd = pathlib.Path(__file__).resolve().parent if base_dir is None else base_dir
# This supports symlinks, so we can link domain library tests to PyTorch test directory
all_py_files = [
pathlib.Path(p) for p in glob.glob(f"{cwd}/**/test_*.py", recursive=True)
]
cpp_tests_dir = (
f"{cwd.parent}/{CPP_TEST_PATH}" if cpp_tests_dir is None else cpp_tests_dir
)
# CPP test files are located under pytorch/build/bin. Unlike Python test, C++ tests
# are just binaries and could have any name, i.e. basic or atest
all_cpp_files = [
pathlib.Path(p) for p in glob.glob(f"{cpp_tests_dir}/**/*", recursive=True)
]
rc = [str(fname.relative_to(cwd))[:-3] for fname in all_py_files]
# Add the cpp prefix for C++ tests so that we can tell them apart
rc.extend(
[
parse_test_module(f"{CPP_TEST_PREFIX}/{fname.relative_to(cpp_tests_dir)}")
for fname in all_cpp_files
]
)
# Invert slashes on Windows
if sys.platform == "win32":
rc = [name.replace("\\", "/") for name in rc]
rc = [test for test in rc if not skip_test_p(test)]
if extra_tests is not None:
rc += extra_tests
return sorted(rc)
CPP_TESTS_DIR = os.path.abspath(os.getenv("CPP_TESTS_DIR", default=CPP_TEST_PATH))
TESTS = discover_tests(
cpp_tests_dir=CPP_TESTS_DIR,
blocklisted_patterns=[
"ao",
"bottleneck_test",
"custom_backend",
"custom_operator",
"fx", # executed by test_fx.py
"jit", # executed by test_jit.py
"mobile",
"onnx_caffe2",
"package", # executed by test_package.py
"quantization", # executed by test_quantization.py
"autograd", # executed by test_autograd.py
],
blocklisted_tests=[
"test_bundled_images",
"test_cpp_extensions_aot",
"test_determination",
"test_jit_fuser",
"test_jit_simple",
"test_jit_string",
"test_kernel_launch_checks",
"test_nnapi",
"test_static_runtime",
"test_throughput_benchmark",
"distributed/bin/test_script",
"distributed/elastic/multiprocessing/bin/test_script",
"distributed/launcher/bin/test_script",
"distributed/launcher/bin/test_script_init_method",
"distributed/launcher/bin/test_script_is_torchelastic_launched",
"distributed/launcher/bin/test_script_local_rank",
"distributed/test_c10d_spawn",
"distributions/test_transforms",
"distributions/test_utils",
"onnx/test_pytorch_onnx_onnxruntime_cuda",
"onnx/test_models",
# These are not C++ tests
f"{CPP_TEST_PREFIX}/CMakeFiles",
f"{CPP_TEST_PREFIX}/CTestTestfile.cmake",
f"{CPP_TEST_PREFIX}/Makefile",
f"{CPP_TEST_PREFIX}/cmake_install.cmake",
f"{CPP_TEST_PREFIX}/c10_intrusive_ptr_benchmark",
f"{CPP_TEST_PREFIX}/example_allreduce",
f"{CPP_TEST_PREFIX}/parallel_benchmark",
f"{CPP_TEST_PREFIX}/protoc",
f"{CPP_TEST_PREFIX}/protoc-3.13.0.0",
f"{CPP_TEST_PREFIX}/torch_shm_manager",
f"{CPP_TEST_PREFIX}/tutorial_tensorexpr",
],
extra_tests=[
"test_cpp_extensions_aot_ninja",
"test_cpp_extensions_aot_no_ninja",
"distributed/elastic/timer/api_test",
"distributed/elastic/timer/local_timer_example",
"distributed/elastic/timer/local_timer_test",
"distributed/elastic/events/lib_test",
"distributed/elastic/metrics/api_test",
"distributed/elastic/utils/logging_test",
"distributed/elastic/utils/util_test",
"distributed/elastic/utils/distributed_test",
"distributed/elastic/multiprocessing/api_test",
],
)
# The doctests are a special case that don't correspond to a file that discover
# tests can enable.
TESTS = TESTS + ["doctests"]
FSDP_TEST = [test for test in TESTS if test.startswith("distributed/fsdp")]
WINDOWS_BLOCKLIST = [
"distributed/nn/jit/test_instantiator",
"distributed/rpc/test_faulty_agent",
"distributed/rpc/test_tensorpipe_agent",
"distributed/rpc/test_share_memory",
"distributed/rpc/cuda/test_tensorpipe_agent",
"distributed/pipeline/sync/skip/test_api",
"distributed/pipeline/sync/skip/test_gpipe",
"distributed/pipeline/sync/skip/test_inspect_skip_layout",
"distributed/pipeline/sync/skip/test_leak",
"distributed/pipeline/sync/skip/test_portal",
"distributed/pipeline/sync/skip/test_stash_pop",
"distributed/pipeline/sync/skip/test_tracker",
"distributed/pipeline/sync/skip/test_verify_skippables",
"distributed/pipeline/sync/test_balance",
"distributed/pipeline/sync/test_bugs",
"distributed/pipeline/sync/test_checkpoint",
"distributed/pipeline/sync/test_copy",
"distributed/pipeline/sync/test_deferred_batch_norm",
"distributed/pipeline/sync/test_dependency",
"distributed/pipeline/sync/test_inplace",
"distributed/pipeline/sync/test_microbatch",
"distributed/pipeline/sync/test_phony",
"distributed/pipeline/sync/test_pipe",
"distributed/pipeline/sync/test_pipeline",
"distributed/pipeline/sync/test_stream",
"distributed/pipeline/sync/test_transparency",
"distributed/pipeline/sync/test_worker",
"distributed/elastic/agent/server/test/api_test",
"distributed/elastic/multiprocessing/api_test",
"distributed/_shard/checkpoint/test_checkpoint"
"distributed/_shard/checkpoint/test_file_system_checkpoint"
"distributed/_shard/sharding_spec/test_sharding_spec",
"distributed/_shard/sharding_plan/test_sharding_plan",
"distributed/_shard/sharded_tensor/test_sharded_tensor",
"distributed/_shard/sharded_tensor/test_sharded_tensor_reshard",
"distributed/_shard/sharded_tensor/ops/test_embedding",
"distributed/_shard/sharded_tensor/ops/test_embedding_bag",
"distributed/_shard/sharded_tensor/ops/test_binary_cmp",
"distributed/_shard/sharded_tensor/ops/test_init",
"distributed/_shard/sharded_optim/test_sharded_optim",
] + FSDP_TEST
ROCM_BLOCKLIST = [
"distributed/rpc/test_faulty_agent",
"distributed/rpc/test_tensorpipe_agent",
"distributed/rpc/test_share_memory",
"distributed/rpc/cuda/test_tensorpipe_agent",
"distributed/_shard/checkpoint/test_checkpoint"
"distributed/_shard/checkpoint/test_file_system_checkpoint"
"distributed/_shard/sharding_spec/test_sharding_spec",
"distributed/_shard/sharding_plan/test_sharding_plan",
"distributed/_shard/sharded_tensor/test_sharded_tensor",
"distributed/_shard/sharded_tensor/test_sharded_tensor_reshard",
"distributed/_shard/sharded_tensor/ops/test_embedding",
"distributed/_shard/sharded_tensor/ops/test_embedding_bag",
"distributed/_shard/sharded_tensor/ops/test_binary_cmp",
"distributed/_shard/sharded_tensor/ops/test_init",
"distributed/_shard/sharded_optim/test_sharded_optim",
"test_determination",
"test_jit_legacy",
"test_cuda_nvml_based_avail",
"test_jit_cuda_fuser",
]
# The tests inside these files should never be run in parallel with each other
RUN_PARALLEL_BLOCKLIST = [
"test_cpp_extensions_jit",
"test_cpp_extensions_open_device_registration",
"test_jit_disabled",
"test_mobile_optimizer",
"test_multiprocessing",
"test_multiprocessing_spawn",
"test_namedtuple_return_api",
"test_overrides",
"test_show_pickle",
"test_tensorexpr",
"test_cuda_primary_ctx",
"test_cuda_trace",
"test_cuda_nvml_based_avail",
# temporarily sets a global config
"test_autograd_fallback",
] + FSDP_TEST
# Test files that should always be run serially with other test files,
# but it's okay if the tests inside them are run in parallel with each other.
CI_SERIAL_LIST = [
"test_nn",
"test_fake_tensor",
"test_cpp_api_parity",
"test_reductions",
"test_cuda",
"test_cuda_expandable_segments",
"test_indexing",
"test_fx_backends",
"test_linalg",
"test_cpp_extensions_jit",
"test_torch",
"test_tensor_creation_ops",
"test_sparse_csr",
"test_dispatch",
"test_python_dispatch", # torch.library creation and deletion must be serialized
"test_spectral_ops", # Cause CUDA illegal memory access https://github.com/pytorch/pytorch/issues/88916
"nn/test_pooling",
"nn/test_convolution", # Doesn't respect set_per_process_memory_fraction, results in OOM for other tests in slow gradcheck
"distributions/test_distributions",
"test_autograd", # slow gradcheck runs a test that checks the cuda memory allocator
"test_prims", # slow gradcheck runs a test that checks the cuda memory allocator
"test_modules", # failed test due to mismatched elements
"functorch/test_vmap", # OOM
"test_fx", # gets SIGKILL
"test_dataloader", # frequently hangs for ROCm
"test_serialization", # test_serialization_2gb_file allocates a tensor of 2GB, and could cause OOM
"test_schema_check", # Cause CUDA illegal memory access https://github.com/pytorch/pytorch/issues/95749
"functorch/test_memory_efficient_fusion", # Cause CUDA OOM on ROCm
"test_utils", # OOM
"test_sort_and_select", # OOM
"test_backward_compatible_arguments", # OOM
"test_module_init", # OOM
"test_autocast", # OOM
"test_native_mha", # OOM
"test_module_hooks", # OOM
"inductor/test_max_autotune", # Testing, probably revert later
]
# A subset of onnx tests that cannot run in parallel due to high memory usage.
ONNX_SERIAL_LIST = [
"onnx/test_models",
"onnx/test_models_quantized_onnxruntime",
"onnx/test_models_onnxruntime",
"onnx/test_custom_ops",
"onnx/test_utility_funs",
]
# A subset of our TEST list that validates PyTorch's ops, modules, and autograd function as expected
CORE_TEST_LIST = [
"test_autograd",
"test_autograd_fallback",
"test_modules",
"test_nn",
"test_ops",
"test_ops_gradients",
"test_ops_fwd_gradients",
"test_ops_jit",
"test_torch",
]
# if a test file takes longer than 5 min, we add it to TARGET_DET_LIST
SLOW_TEST_THRESHOLD = 300
DISTRIBUTED_TESTS_CONFIG = {}
if dist.is_available():
DISTRIBUTED_TESTS_CONFIG["test"] = {"WORLD_SIZE": "1"}
if not TEST_WITH_ROCM and dist.is_mpi_available():
DISTRIBUTED_TESTS_CONFIG["mpi"] = {
"WORLD_SIZE": "3",
"TEST_REPORT_SOURCE_OVERRIDE": "dist-mpi",
}
if dist.is_nccl_available():
DISTRIBUTED_TESTS_CONFIG["nccl"] = {
"WORLD_SIZE": "2" if torch.cuda.device_count() == 2 else "3",
"TEST_REPORT_SOURCE_OVERRIDE": "dist-nccl",
}
if dist.is_gloo_available():
DISTRIBUTED_TESTS_CONFIG["gloo"] = {
"WORLD_SIZE": "2" if torch.cuda.device_count() == 2 else "3",
"TEST_REPORT_SOURCE_OVERRIDE": "dist-gloo",
}
if dist.is_ucc_available():
DISTRIBUTED_TESTS_CONFIG["ucc"] = {
"WORLD_SIZE": "2" if torch.cuda.device_count() == 2 else "3",
"TEST_REPORT_SOURCE_OVERRIDE": "dist-ucc",
"UCX_TLS": "tcp,cuda",
"UCC_TLS": "nccl,ucp,cuda",
"UCC_TL_UCP_TUNE": "cuda:0", # don't use UCP TL on CUDA as it is not well supported
"UCC_EC_CUDA_USE_COOPERATIVE_LAUNCH": "n", # CI nodes (M60) fail if it is on
}
# https://stackoverflow.com/questions/2549939/get-signal-names-from-numbers-in-python
SIGNALS_TO_NAMES_DICT = {
getattr(signal, n): n for n in dir(signal) if n.startswith("SIG") and "_" not in n
}
CPP_EXTENSIONS_ERROR = """
Ninja (https://ninja-build.org) is required for some of the C++ extensions
tests, but it could not be found. Install ninja with `pip install ninja`
or `conda install ninja`. Alternatively, disable said tests with
`run_test.py --exclude test_cpp_extensions_aot_ninja test_cpp_extensions_jit`.
"""
PYTORCH_COLLECT_COVERAGE = bool(os.environ.get("PYTORCH_COLLECT_COVERAGE"))
JIT_EXECUTOR_TESTS = [
"test_jit_profiling",
"test_jit_legacy",
"test_jit_fuser_legacy",
]
DISTRIBUTED_TESTS = [test for test in TESTS if test.startswith(DISTRIBUTED_TEST_PREFIX)]
FUNCTORCH_TESTS = [test for test in TESTS if test.startswith("functorch")]
ONNX_TESTS = [test for test in TESTS if test.startswith("onnx")]
CPP_TESTS = [test for test in TESTS if test.startswith(CPP_TEST_PREFIX)]
TESTS_REQUIRING_LAPACK = [
"distributions/test_constraints",
"distributions/test_distributions",
]
# These are just the slowest ones, this isn't an exhaustive list.
TESTS_NOT_USING_GRADCHECK = [
# Note that you should use skipIfSlowGradcheckEnv if you do not wish to
# skip all the tests in that file, e.g. test_mps
"doctests",
"test_meta",
"test_hub",
"test_fx",
"test_decomp",
"test_cpp_extensions_jit",
"test_jit",
"test_ops",
"test_ops_jit",
"dynamo/test_recompile_ux",
"inductor/test_smoke",
"test_quantization",
]
def print_to_stderr(message):
print(message, file=sys.stderr)
def get_executable_command(options, disable_coverage=False, is_cpp_test=False):
if options.coverage and not disable_coverage:
if not is_cpp_test:
executable = ["coverage", "run", "--parallel-mode", "--source=torch"]
else:
# TODO: C++ with coverage is not yet supported
executable = []
else:
if not is_cpp_test:
executable = [sys.executable, "-bb"]
else:
executable = ["pytest"]
return executable
def run_test(
test_module: ShardedTest,
test_directory,
options,
launcher_cmd=None,
extra_unittest_args=None,
env=None,
) -> int:
maybe_set_hip_visible_devies()
unittest_args = options.additional_unittest_args.copy()
test_file = test_module.name
stepcurrent_key = test_file
is_distributed_test = test_file.startswith(DISTRIBUTED_TEST_PREFIX)
is_cpp_test = test_file.startswith(CPP_TEST_PREFIX)
# NB: Rerun disabled tests depends on pytest-flakefinder and it doesn't work with
# pytest-cpp atm. We also don't have support to disable C++ test yet, so it's ok
# to just return successfully here
if is_cpp_test and RERUN_DISABLED_TESTS:
print_to_stderr(
"Skipping C++ tests when running under RERUN_DISABLED_TESTS mode"
)
return 0
if is_cpp_test:
stepcurrent_key = f"{test_file}_{os.urandom(8).hex()}"
else:
unittest_args.extend(
[
f"--shard-id={test_module.shard - 1}",
f"--num-shards={test_module.num_shards}",
]
)
stepcurrent_key = f"{test_file}_{test_module.shard - 1}_{os.urandom(8).hex()}"
if options.verbose:
unittest_args.append(f'-{"v"*options.verbose}') # in case of pytest
if test_file in RUN_PARALLEL_BLOCKLIST:
unittest_args = [
arg for arg in unittest_args if not arg.startswith("--run-parallel")
]
if extra_unittest_args:
assert isinstance(extra_unittest_args, list)
unittest_args.extend(extra_unittest_args)
# If using pytest, replace -f with equivalent -x
if options.pytest:
unittest_args.extend(
get_pytest_args(
options,
stepcurrent_key,
is_cpp_test=is_cpp_test,
is_distributed_test=is_distributed_test,
)
)
unittest_args.extend(test_module.get_pytest_args())
unittest_args = [arg if arg != "-f" else "-x" for arg in unittest_args]
# TODO: These features are not available for C++ test yet
if IS_CI and not is_cpp_test:
ci_args = ["--import-slow-tests", "--import-disabled-tests"]
if RERUN_DISABLED_TESTS:
ci_args.append("--rerun-disabled-tests")
# use the downloaded test cases configuration, not supported in pytest
unittest_args.extend(ci_args)
if test_file in PYTEST_SKIP_RETRIES:
if not options.pytest:
raise RuntimeError(
"A test running without pytest cannot skip retries using "
"the PYTEST_SKIP_RETRIES set."
)
unittest_args = [arg for arg in unittest_args if "--reruns" not in arg]
# Extra arguments are not supported with pytest
executable = get_executable_command(options, is_cpp_test=is_cpp_test)
if not executable:
# If there is no eligible executable returning here, it means an unsupported
# case such as coverage for C++ test. So just returning ok makes sense
return 0
if test_file.startswith(CPP_TEST_PREFIX):
# C++ tests are not the regular test directory
if CPP_TESTS_DIR:
cpp_test = os.path.join(
CPP_TESTS_DIR,
test_file.replace(f"{CPP_TEST_PREFIX}/", ""),
)
else:
cpp_test = os.path.join(
pathlib.Path(test_directory).parent,
CPP_TEST_PATH,
test_file.replace(f"{CPP_TEST_PREFIX}/", ""),
)
argv = [
cpp_test if sys.platform != "win32" else cpp_test + ".exe"
] + unittest_args
else:
# Can't call `python -m unittest test_*` here because it doesn't run code
# in `if __name__ == '__main__': `. So call `python test_*.py` instead.
argv = [test_file + ".py"] + unittest_args
os.makedirs(REPO_ROOT / "test" / "test-reports", exist_ok=True)
if IS_CI:
log_fd, log_path = tempfile.mkstemp(
dir=REPO_ROOT / "test" / "test-reports",
prefix=f"{sanitize_file_name(str(test_module))}_",
suffix="_toprint.log",
)
os.close(log_fd)
command = (launcher_cmd or []) + executable + argv
should_file_rerun = (
"--subprocess" not in command
and not RERUN_DISABLED_TESTS
and not options.continue_through_error
)
is_slow = "slow" in os.environ.get("TEST_CONFIG", "") or "slow" in os.environ.get(
"BUILD_ENVRIONMENT", ""
)
timeout = (
THRESHOLD * 6
if is_slow
else THRESHOLD * 3
if should_file_rerun
and isinstance(test_module, ShardedTest)
and test_module.time is not None
else None
)
print_to_stderr(f"Executing {command} ... [{datetime.now()}]")
with ExitStack() as stack:
output = None
if IS_CI:
output = stack.enter_context(open(log_path, "w"))
ret_code, was_rerun = retry_shell(
command,
test_directory,
stdout=output,
stderr=output,
env=env,
timeout=timeout,
retries=2 if should_file_rerun else 0,
)
# Pytest return code 5 means no test is collected. This is needed
# here as we use pytest directly when running C++ tests. Return
# code 4 is ok too as this happens when the binary is not a C++
# test executable. All binary files under build/bin that are not
# C++ test at the time of this writing have been excluded, but we
# can accept code 4 too just in case a new non-test binary file
# comes up in the future.
ret_code = 0 if ret_code == 5 or ret_code == 4 else ret_code
if IS_CI:
handle_log_file(
test_module, log_path, failed=(ret_code != 0), was_rerun=was_rerun
)
return ret_code
def run_test_with_subprocess(test_module, test_directory, options):
return run_test(
test_module, test_directory, options, extra_unittest_args=["--subprocess"]
)
def _test_cpp_extensions_aot(test_directory, options, use_ninja):
if use_ninja:
try:
from torch.utils import cpp_extension
cpp_extension.verify_ninja_availability()
except RuntimeError:
print_to_stderr(CPP_EXTENSIONS_ERROR)
return 1
# Wipe the build folder, if it exists already
cpp_extensions_test_dir = os.path.join(test_directory, "cpp_extensions")
cpp_extensions_test_build_dir = os.path.join(cpp_extensions_test_dir, "build")
if os.path.exists(cpp_extensions_test_build_dir):
shutil.rmtree(cpp_extensions_test_build_dir)
# Build the test cpp extensions modules
shell_env = os.environ.copy()
shell_env["USE_NINJA"] = str(1 if use_ninja else 0)
cmd = [sys.executable, "setup.py", "install", "--root", "./install"]
return_code = shell(cmd, cwd=cpp_extensions_test_dir, env=shell_env)
if return_code != 0:
return return_code
if sys.platform != "win32":
return_code = shell(
cmd,
cwd=os.path.join(cpp_extensions_test_dir, "no_python_abi_suffix_test"),
env=shell_env,
)
if return_code != 0:
return return_code
# "install" the test modules and run tests
python_path = os.environ.get("PYTHONPATH", "")
from shutil import copyfile
os.environ["USE_NINJA"] = shell_env["USE_NINJA"]
test_module = "test_cpp_extensions_aot" + ("_ninja" if use_ninja else "_no_ninja")
copyfile(
test_directory + "/test_cpp_extensions_aot.py",
test_directory + "/" + test_module + ".py",
)
try:
cpp_extensions = os.path.join(test_directory, "cpp_extensions")
install_directory = ""
# install directory is the one that is named site-packages
for root, directories, _ in os.walk(os.path.join(cpp_extensions, "install")):
for directory in directories:
if "-packages" in directory:
install_directory = os.path.join(root, directory)
assert install_directory, "install_directory must not be empty"
os.environ["PYTHONPATH"] = os.pathsep.join([install_directory, python_path])
return run_test(ShardedTest(test_module, 1, 1), test_directory, options)
finally:
os.environ["PYTHONPATH"] = python_path
if os.path.exists(test_directory + "/" + test_module + ".py"):
os.remove(test_directory + "/" + test_module + ".py")
os.environ.pop("USE_NINJA")
def test_cpp_extensions_aot_ninja(test_module, test_directory, options):
return _test_cpp_extensions_aot(test_directory, options, use_ninja=True)
def test_cpp_extensions_aot_no_ninja(test_module, test_directory, options):
return _test_cpp_extensions_aot(test_directory, options, use_ninja=False)
def test_distributed(test_module, test_directory, options):
# MPI tests are broken with Python-3.9
mpi_available = subprocess.call(
"command -v mpiexec", shell=True
) == 0 and sys.version_info < (3, 9)
if options.verbose and not mpi_available:
print_to_stderr("MPI not available -- MPI backend tests will be skipped")
config = DISTRIBUTED_TESTS_CONFIG
for backend, env_vars in config.items():
if sys.platform == "win32" and backend != "gloo":
continue
if backend == "mpi" and not mpi_available:
continue
for with_init_file in {True, False}:
if sys.platform == "win32" and not with_init_file:
continue
tmp_dir = tempfile.mkdtemp()
if options.verbose:
init_str = "with {} init_method"
with_init = init_str.format("file" if with_init_file else "env")
print_to_stderr(
f"Running distributed tests for the {backend} backend {with_init}"
)
old_environ = dict(os.environ)
os.environ["TEMP_DIR"] = tmp_dir
os.environ["BACKEND"] = backend
os.environ["INIT_METHOD"] = "env://"
os.environ.update(env_vars)
if with_init_file:
if test_module.name == "test_distributed_spawn":
init_method = f"{FILE_SCHEMA}{tmp_dir}/"
else:
init_method = f"{FILE_SCHEMA}{tmp_dir}/shared_init_file"
os.environ["INIT_METHOD"] = init_method
try:
os.mkdir(os.path.join(tmp_dir, "barrier"))
os.mkdir(os.path.join(tmp_dir, "test_dir"))
if backend == "mpi":
# test mpiexec for --noprefix option
with open(os.devnull, "w") as devnull:
allowrunasroot_opt = (
"--allow-run-as-root"
if subprocess.call(
'mpiexec --allow-run-as-root -n 1 bash -c ""',
shell=True,
stdout=devnull,
stderr=subprocess.STDOUT,
)
== 0
else ""
)
noprefix_opt = (
"--noprefix"
if subprocess.call(
f'mpiexec {allowrunasroot_opt} -n 1 --noprefix bash -c ""',
shell=True,
stdout=devnull,
stderr=subprocess.STDOUT,
)
== 0
else ""
)
mpiexec = ["mpiexec", "-n", "3", noprefix_opt, allowrunasroot_opt]
return_code = run_test(
test_module, test_directory, options, launcher_cmd=mpiexec
)
else:
return_code = run_test(
test_module,
test_directory,
options,
extra_unittest_args=["--subprocess"],
)
if return_code != 0:
return return_code
finally:
shutil.rmtree(tmp_dir)
os.environ.clear()
os.environ.update(old_environ)
return 0
def run_doctests(test_module, test_directory, options):
"""
Assumes the incoming test module is called doctest, and simply executes the
xdoctest runner on the torch library itself.
"""
import pathlib
import xdoctest
pkgpath = pathlib.Path(torch.__file__).parent
exclude_module_list = []
enabled = {
# TODO: expose these options to the user
# For now disable all feature-conditional tests
# 'lapack': 'auto',
# 'cuda': 'auto',
# 'cuda1': 'auto',
# 'qengine': 'auto',
"lapack": 0,
"cuda": 0,
"cuda1": 0,
"qengine": 0,
"autograd_profiler": 0,
"cpp_ext": 0,
"monitor": 0,
"onnx": "auto",
}
# Resolve "auto" based on a test to determine if the feature is available.
if enabled["cuda"] == "auto" and torch.cuda.is_available():
enabled["cuda"] = True
if (
enabled["cuda1"] == "auto"
and torch.cuda.is_available()
and torch.cuda.device_count() > 1
):
enabled["cuda1"] = True
if enabled["lapack"] == "auto" and torch._C.has_lapack:
enabled["lapack"] = True
if enabled["qengine"] == "auto":
try:
# Is there a better check if quantization is enabled?
import torch.ao.nn.quantized as nnq # NOQA: F401
torch.backends.quantized.engine = "qnnpack"
torch.backends.quantized.engine = "fbgemm"
except (ImportError, RuntimeError):
...
else:
enabled["qengine"] = True
if enabled["onnx"] == "auto":
try:
import onnx # NOQA: F401
import onnxruntime # NOQA: F401
import onnxscript # NOQA: F401
except ImportError:
exclude_module_list.append("torch.onnx.*")
enabled["onnx"] = False
else:
enabled["onnx"] = True
# Set doctest environment variables
if enabled["cuda"]:
os.environ["TORCH_DOCTEST_CUDA"] = "1"
if enabled["cuda1"]:
os.environ["TORCH_DOCTEST_CUDA1"] = "1"
if enabled["lapack"]:
os.environ["TORCH_DOCTEST_LAPACK"] = "1"
if enabled["qengine"]:
os.environ["TORCH_DOCTEST_QENGINE"] = "1"
if enabled["autograd_profiler"]:
os.environ["TORCH_DOCTEST_AUTOGRAD_PROFILER"] = "1"
if enabled["cpp_ext"]:
os.environ["TORCH_DOCTEST_CPP_EXT"] = "1"
if enabled["monitor"]:
os.environ["TORCH_DOCTEST_MONITOR"] = "1"
if enabled["onnx"]:
os.environ["TORCH_DOCTEST_ONNX"] = "1"
if 0:
# TODO: could try to enable some of these
os.environ["TORCH_DOCTEST_QUANTIZED_DYNAMIC"] = "1"
os.environ["TORCH_DOCTEST_ANOMALY"] = "1"
os.environ["TORCH_DOCTEST_AUTOGRAD"] = "1"
os.environ["TORCH_DOCTEST_HUB"] = "1"
os.environ["TORCH_DOCTEST_DATALOADER"] = "1"
os.environ["TORCH_DOCTEST_FUTURES"] = "1"
pkgpath = os.path.dirname(torch.__file__)
xdoctest_config = {
"global_exec": r"\n".join(
[
"from torch import nn",
"import torch.nn.functional as F",
"import torch",
]
),
"analysis": "static", # set to "auto" to test doctests in compiled modules
"style": "google",
"options": "+IGNORE_WHITESPACE",
}
xdoctest_verbose = max(1, options.verbose)
run_summary = xdoctest.runner.doctest_module(
os.fspath(pkgpath),
config=xdoctest_config,
verbose=xdoctest_verbose,
command=options.xdoctest_command,
argv=[],
exclude=exclude_module_list,
)
result = 1 if run_summary.get("n_failed", 0) else 0
return result
def sanitize_file_name(file: str):
return file.replace("\\", ".").replace("/", ".").replace(" ", "_")
def handle_log_file(
test: ShardedTest, file_path: str, failed: bool, was_rerun: bool
) -> None:
test = str(test)
with open(file_path, "rb") as f:
full_text = f.read().decode("utf-8", errors="ignore")
if not failed and not was_rerun and "=== RERUNS ===" not in full_text:
# If success + no retries (idk how else to check for test level retries
# other than reparse xml), print only what tests ran, rename the log
# file so it doesn't get printed later, and do not remove logs.
new_file = "test/test-reports/" + sanitize_file_name(
f"{test}_{os.urandom(8).hex()}_.log"
)
os.rename(file_path, REPO_ROOT / new_file)
print_to_stderr(
f"\n{test} was successful, full logs can be found in artifacts with path {new_file}"
)
for line in full_text.splitlines():
if re.search("Running .* items in this shard:", line):
print_to_stderr(line.strip())
print_to_stderr("")
return
# otherwise: print entire file and then remove it
print_to_stderr(f"\nPRINTING LOG FILE of {test} ({file_path})")
print_to_stderr(full_text)
print_to_stderr(f"FINISHED PRINTING LOG FILE of {test} ({file_path})\n")
os.remove(file_path)
def get_pytest_args(
options, stepcurrent_key, is_cpp_test=False, is_distributed_test=False
):
if RERUN_DISABLED_TESTS:
# Distributed tests are too slow, so running them x50 will cause the jobs to timeout after
# 3+ hours. So, let's opt for less number of reruns. We need at least 150 instances of the
# test every 2 weeks to satisfy the Rockset query (15 x 14 = 210). The same logic applies
# to ASAN, which is also slow
count = 15 if is_distributed_test or TEST_WITH_ASAN else 50
# When under rerun-disabled-tests mode, run the same tests multiple times to determine their
# flakiness status. Default to 50 re-runs
rerun_options = ["--flake-finder", f"--flake-runs={count}"]
elif options.continue_through_error:
# If continue through error, don't stop on first failure
rerun_options = ["--reruns=2"]
else:
# When under the normal mode, retry a failed test 2 more times. -x means stop at the first
# failure
rerun_options = ["-x", "--reruns=2"]
pytest_args = [
"-vv",
"-rfEX",
]
if not is_cpp_test:
# C++ tests need to be run with pytest directly, not via python
pytest_args.extend(["-p", "no:xdist", "--use-pytest"])
if not options.continue_through_error and IS_CI:
pytest_args.append(f"--sc={stepcurrent_key}")