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run_test.py
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#!/usr/bin/env python3
import argparse
import copy
from datetime import datetime
from distutils.version import LooseVersion
import functools
import os
import pathlib
import shutil
import signal
import subprocess
import sys
import tempfile
import json
import glob
from typing import Dict, Optional, List, cast, Any
import torch
from torch.utils import cpp_extension
from torch.testing._internal.common_utils import (
IS_CI,
FILE_SCHEMA,
TEST_WITH_ROCM,
shell,
set_cwd,
parser as common_parser,
is_slow_gradcheck_env,
)
import torch.distributed as dist
from torch.multiprocessing import current_process, get_context
REPO_ROOT = pathlib.Path(__file__).resolve().parent.parent
try:
# using tools/ to optimize test run.
sys.path.append(str(REPO_ROOT))
from tools.stats.export_test_times import TEST_TIMES_FILE
from tools.testing.test_selections import (
get_reordered_tests,
get_test_case_configs,
calculate_shards,
NUM_PROCS
)
HAVE_TEST_SELECTION_TOOLS = True
except ImportError:
HAVE_TEST_SELECTION_TOOLS = False
print(
"Unable to import test_selections from tools/testing. Running without test selection stats..."
)
# 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 discover_tests(
base_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
"""
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)]
rc = [str(fname.relative_to(cwd))[:-3] for fname in all_py_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)
TESTS = discover_tests(
blocklisted_patterns=[
'ao',
'bottleneck_test',
'custom_backend',
'custom_operator',
'fx', # executed by test_fx.py
'jit', # executed by test_jit.py
'mobile',
'onnx',
'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_segment_reductions',
'test_static_runtime',
'test_throughput_benchmark',
'test_typing',
"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',
],
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")]
# Tests need to be run with pytest.
USE_PYTEST_LIST = [
"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",
"distributions/test_constraints",
"distributions/test_transforms",
"distributions/test_utils",
"test_typing",
"distributed/elastic/events/lib_test",
"distributed/elastic/agent/server/test/api_test",
"test_deploy",
"distributed/test_c10d_error_logger"
]
WINDOWS_BLOCKLIST = [
"test_ops_jit", # TODO: Broken on Windows https://github.com/pytorch/pytorch/issues/96858
"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_chunk",
"distributed/_shard/sharded_tensor/ops/test_elementwise_ops",
"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_tensor/ops/test_math_ops",
"distributed/_shard/sharded_tensor/ops/test_matrix_ops",
"distributed/_shard/sharded_tensor/ops/test_softmax",
"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_chunk",
"distributed/_shard/sharded_tensor/ops/test_elementwise_ops",
"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_tensor/ops/test_math_ops",
"distributed/_shard/sharded_tensor/ops/test_matrix_ops",
"distributed/_shard/sharded_tensor/ops/test_softmax",
"distributed/_shard/sharded_optim/test_sharded_optim",
"test_determination",
"test_jit_legacy",
"test_cuda_nvml_based_avail",
]
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",
] + FSDP_TEST
CI_SERIAL_LIST = [
'test_nn',
'test_fake_tensor',
'test_cpp_api_parity',
'test_reductions',
'test_cuda',
'test_jit_cuda_fuser', # OOM on test_issue_1785, also profiling?
'test_indexing',
'test_fx_backends',
'test_linalg',
'test_cpp_extensions_jit',
'test_torch',
'test_tensor_creation_ops',
'test_sparse_csr',
'test_dispatch',
'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
'_nvfuser/test_torchscript', # OOM on test_issue_1785
]
# A subset of our TEST list that validates PyTorch's ops, modules, and autograd function as expected
CORE_TEST_LIST = [
"test_autograd",
"test_modules",
"test_nn",
"test_ops",
"test_ops_gradients",
"test_ops_fwd_gradients",
"test_ops_jit",
"test_torch"
]
# A list of distributed tests that run on multiple backends, i.e. gloo, nccl. These backends are spread out
# among all available shards to speed up the test. The list of backends are copied from the tests themselves
DISTRIBUTED_TESTS_WITH_MULTIPLE_BACKENDS = {
"distributed/test_distributed_spawn": [
"gloo",
"nccl",
"ucc",
],
"distributed/algorithms/quantization/test_quantization": [
"gloo",
"nccl",
],
}
# 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",
"UCC_TLS": "nccl,ucp",
"UCC_TL_UCP_TUNE": "cuda:0", # don't use UCP TL on CUDA as it is not well supported
}
# 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")]
FUNCTORCH_TESTS = [test for test in TESTS if test.startswith("functorch")]
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):
if options.coverage and not disable_coverage:
executable = ["coverage", "run", "--parallel-mode", "--source=torch"]
else:
executable = [sys.executable, "-bb"]
return executable
def run_test(
test_module,
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()
if options.verbose:
unittest_args.append(f'-{"v"*options.verbose}') # in case of pytest
if test_module 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))
unittest_args = [arg if arg != "-f" else "-x" for arg in unittest_args]
if IS_CI:
ci_args = ["--import-slow-tests", "--import-disabled-tests"]
if os.getenv("PYTORCH_TEST_RERUN_DISABLED_TESTS", "0") == "1":
ci_args.append("--rerun-disabled-tests")
# use the downloaded test cases configuration, not supported in pytest
unittest_args.extend(ci_args)
# Extra arguments are not supported with pytest
executable = get_executable_command(options)
# 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_module + ".py"] + unittest_args
os.makedirs(REPO_ROOT / "test" / "test-reports", exist_ok=True)
log_fd, log_path = tempfile.mkstemp(dir=REPO_ROOT / "test" / "test-reports",
prefix="{}_".format(test_module.replace("\\", "-").replace("/", "-")),
suffix=".log")
os.close(log_fd)
command = (launcher_cmd or []) + executable + argv
print_to_stderr("Executing {} ... [{}]".format(command, datetime.now()))
with open(log_path, "w") as f:
ret_code = shell(command, test_directory, stdout=f, stderr=f, env=env)
print_log_file(test_module, log_path, failed=(ret_code != 0))
os.remove(log_path)
return ret_code
def test_cuda_primary_ctx(test_module, test_directory, options):
return run_test(
test_module, test_directory, options, extra_unittest_args=["--subprocess"]
)
run_test_with_subprocess = functools.partial(run_test, extra_unittest_args=["--subprocess"])
def get_run_test_with_subprocess_fn():
return lambda test_module, test_directory, options: run_test_with_subprocess(test_module, test_directory, options)
def _test_cpp_extensions_aot(test_directory, options, use_ninja):
if use_ninja:
try:
cpp_extension.verify_ninja_availability()
except RuntimeError:
print(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(test_module, 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")
if options.shard:
which_shard, num_shards = options.shard
else:
which_shard = num_shards = 1
# Round-robin all backends to different shards
backend_to_shard = {backend: i % num_shards + 1
for i, backend in enumerate(DISTRIBUTED_TESTS_WITH_MULTIPLE_BACKENDS[test_module])}
print_to_stderr(f"Map different backends to different shards for {test_module}: {backend_to_shard}")
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
# Default to the first shard if seeing an unrecognized backend
if which_shard != backend_to_shard.get(backend, 1):
print_to_stderr(f"Shard {which_shard}: {backend} should be run in {backend_to_shard.get(backend, 1)}")
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(
"Running distributed tests for the {} backend {} in shard {} of {}".format(
backend, with_init, which_shard, num_shards
)
)
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 == "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 xdoctest
import pathlib
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
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
import onnxscript # NOQA
import onnxruntime # NOQA
except ImportError:
exclude_module_list.append("torch.onnx._internal.fx.*")
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_ANOMOLY'] = '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 print_log_file(test: str, file_path: str, failed: bool) -> None:
num_lines = sum(1 for _ in open(file_path, 'rb'))
n = 100
with open(file_path, "r") as f:
print_to_stderr("")
if failed:
if n < num_lines:
print_to_stderr(f"Expand the folded group to see the beginning of the log file of {test}")
print_to_stderr(f"##[group]PRINTING BEGINNING OF LOG FILE of {test} ({file_path})")
for _ in range(num_lines - n):
print_to_stderr(next(f).rstrip())
print_to_stderr("##[endgroup]")
for _ in range(min(n, num_lines)):
print_to_stderr(next(f).rstrip())
print_to_stderr(f"FINISHED PRINTING LOG FILE of {test} ({file_path})")
else:
print_to_stderr(f"Expand the folded group to see the log file of {test}")
print_to_stderr(f"##[group]PRINTING LOG FILE of {test} ({file_path})")
print_to_stderr(f.read())
print_to_stderr("##[endgroup]")
print_to_stderr(f"FINISHED PRINTING LOG FILE of {test} ({file_path})")
print_to_stderr("")
def get_pytest_args(options):
if os.getenv("PYTORCH_TEST_RERUN_DISABLED_TESTS", "0") == "1":
# 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", "--flake-runs=50"]
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 = [
"--use-pytest",
"-vv",
"-rfEX"
]
pytest_args.extend(rerun_options)
return pytest_args
def run_test_ops(test_module, test_directory, options):
default_unittest_args = get_pytest_args(options)
return_codes = []
os.environ["NUM_PARALLEL_PROCS"] = str(NUM_PROCS)
pool = get_context("spawn").Pool(NUM_PROCS)
for i in range(NUM_PROCS):
extra_unittest_args = default_unittest_args.copy()
extra_unittest_args.extend([
f"--shard-id={i}",
f"--num-shards={NUM_PROCS}",
"-k=not _linalg_cholesky_",
])
return_code = pool.apply_async(
run_test,
args=(test_module, test_directory, copy.deepcopy(options)),
kwds={
"extra_unittest_args": extra_unittest_args,
},
)
return_codes.append(return_code)
pool.close()
pool.join()
del os.environ["NUM_PARALLEL_PROCS"]
for return_code in return_codes:
if return_code.get() != 0:
return return_code.get()
extra_unittest_args = default_unittest_args.copy()
extra_unittest_args.extend([
"-k=_linalg_cholesky_",
])
return_code = run_test(
test_module,
test_directory,
copy.deepcopy(options),
extra_unittest_args=extra_unittest_args,
)
return return_code
CUSTOM_HANDLERS = {
"test_cuda_primary_ctx": test_cuda_primary_ctx,
"test_cuda_nvml_based_avail": get_run_test_with_subprocess_fn(),
"test_cuda_trace": get_run_test_with_subprocess_fn(),
"test_cpp_extensions_aot_no_ninja": test_cpp_extensions_aot_no_ninja,
"test_cpp_extensions_aot_ninja": test_cpp_extensions_aot_ninja,
"distributed/test_distributed_spawn": test_distributed,
"distributed/algorithms/quantization/test_quantization": test_distributed,
"distributed/test_c10d_nccl": get_run_test_with_subprocess_fn(),
"distributed/test_c10d_gloo": get_run_test_with_subprocess_fn(),
"distributed/test_c10d_common": get_run_test_with_subprocess_fn(),
"distributed/test_c10d_spawn_gloo": get_run_test_with_subprocess_fn(),
"distributed/test_c10d_spawn_nccl": get_run_test_with_subprocess_fn(),
"distributed/test_c10d_spawn_ucc": get_run_test_with_subprocess_fn(),
"distributed/test_store": get_run_test_with_subprocess_fn(),
"distributed/test_pg_wrapper": get_run_test_with_subprocess_fn(),
"distributed/rpc/test_faulty_agent": get_run_test_with_subprocess_fn(),
"distributed/rpc/test_tensorpipe_agent": get_run_test_with_subprocess_fn(),
"distributed/rpc/test_share_memory": get_run_test_with_subprocess_fn(),
"distributed/rpc/cuda/test_tensorpipe_agent": get_run_test_with_subprocess_fn(),
"doctests": run_doctests,
"inductor/test_torchinductor_opinfo": run_test_ops,
"test_ops": run_test_ops,
"test_ops_gradients": run_test_ops,
"test_ops_fwd_gradients": run_test_ops,
"test_ops_jit": run_test_ops,
"functorch/test_ops": run_test_ops,
# not a test_ops file, but takes 2 hrs on some architectures and
# run_test_ops is good at parallelizing things
"test_decomp": run_test_ops,
}
PYTEST_BLOCKLIST = [
"profiler/test_profiler",
"dynamo/test_repros", # skip_if_pytest
"dynamo/test_optimizers", # skip_if_pytest
"dynamo/test_dynamic_shapes", # needs change to check_if_enable for disabled test issues
]
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 parse_args():
parser = argparse.ArgumentParser(
description="Run the PyTorch unit test suite",
epilog="where TESTS is any of: {}".format(", ".join(TESTS)),
formatter_class=argparse.RawTextHelpFormatter,
parents=[common_parser]
)
parser.add_argument(
"-v",
"--verbose",
action="count",
default=0,
help="print verbose information and test-by-test results",
)
parser.add_argument("--jit", "--jit", action="store_true", help="run all jit tests")
parser.add_argument(
"--distributed-tests",
"--distributed-tests",
action="store_true",
help="run all distributed tests",
)
parser.add_argument(
"--functorch",
"--functorch",
action="store_true",
help=(
"If this flag is present, we will only run functorch tests. "
"If this flag is not present, we will not run any functorch tests. "
"This requires functorch to already be installed."
)
)
parser.add_argument(
"--mps",
"--mps",
action="store_true",
help=(
"If this flag is present, we will only run test_mps and test_metal"
)
)
parser.add_argument(
"-core",
"--core",
action="store_true",
help="Only run core tests, or tests that validate PyTorch's ops, modules,"
"and autograd. They are defined by CORE_TEST_LIST."
)
parser.add_argument(
"-pt",
"--pytest",
action="store_true",
help="If true, use `pytest` to execute the tests. E.g., this runs "
"TestTorch with pytest in verbose and coverage mode: "
"python run_test.py -vci torch -pt",
)
parser.add_argument(
"-c",
"--coverage",
action="store_true",
help="enable coverage",
default=PYTORCH_COLLECT_COVERAGE,
)
parser.add_argument(
"-i",
"--include",
nargs="+",
choices=TestChoices(TESTS),
default=TESTS,
metavar="TESTS",
help="select a set of tests to include (defaults to ALL tests)."
" tests must be a part of the TESTS list defined in run_test.py",
)
parser.add_argument(
"-x",
"--exclude",
nargs="+",
choices=TESTS,
metavar="TESTS",
default=[],
help="select a set of tests to exclude",
)
parser.add_argument(
"-f",