mirror of
https://github.com/zebrajr/pytorch.git
synced 2025-12-07 00:21:07 +01:00
51e7a371f5
Summary: Pull Request resolved: https://github.com/pytorch/pytorch/pull/55075 Constructs and passes in a mapping with parameter names to Reducer to log information about unused parameters in error messages about unused parameters/not all parameters getting gradient. Use case: 1) User runs DDP forward + bwd, and it has some unused parameters that will result in ddp error in next iteration 2) Next forward pass calls `Reducer::ensure_prior_reduction_finished()` where we check all params got gradient from the previous bwd pass. DDP would throw here in this case. 3) Reducer maintains mapping and tracks used parameters, and computes which parameters did not get gradient and logs this as part of the error. Implementation details: 0) The following is only enabled for debug modes of INFO or DETAIL. 1) To save memory, we don't map param -> param name so that we don't have to copy the entire tensor, instead we map param_index -> param_name and use the existing concept of variable_index in Reducer to look up parameter names. 2) DDP constructs param index -> param name mapping. The name is the fully qualified name: f"{module_name}:{param_name}" and passes it into Reducer 3) Reducer maintains per-iteration std::set<int> of variable indices that have had `mark_variable_ready` called. 4) When some params go unused, we take a set difference to detect the unused params. 5) Unittests to test the logged unused params, as well as for nested modules, are added ghstack-source-id: 126581051 Test Plan: CI, UT Reviewed By: zhaojuanmao Differential Revision: D27356394 fbshipit-source-id: 89f436af4e74145b0a8eda92b3c4e2af8e747332
605 lines
22 KiB
Python
605 lines
22 KiB
Python
from contextlib import contextmanager
|
|
from enum import Enum
|
|
import faulthandler
|
|
from multiprocessing import Manager
|
|
from io import StringIO
|
|
import os
|
|
import sys
|
|
import tempfile
|
|
import threading
|
|
import time
|
|
import unittest
|
|
import logging
|
|
import traceback
|
|
import types
|
|
|
|
from typing import NamedTuple, Union
|
|
from functools import wraps
|
|
|
|
import torch
|
|
import torch.distributed as c10d
|
|
import torch.cuda.nccl
|
|
|
|
from functools import partial, reduce
|
|
from torch.testing._internal.common_utils import TestCase, TEST_WITH_ROCM, FILE_SCHEMA
|
|
|
|
logger = logging.getLogger(__name__)
|
|
|
|
class TestSkip(NamedTuple):
|
|
exit_code: int
|
|
message: str
|
|
|
|
|
|
TEST_SKIPS = {
|
|
"backend_unavailable": TestSkip(72, "Skipped because distributed backend is not available."),
|
|
"small_worldsize": TestSkip(73, "Skipped due to small world size."),
|
|
"no_cuda": TestSkip(74, "CUDA is not available."),
|
|
"multi-gpu": TestSkip(75, "Need at least 2 CUDA devices"),
|
|
"nccl": TestSkip(76, "c10d not compiled with NCCL support"),
|
|
"skipIfRocm": TestSkip(78, "Test skipped for ROCm"),
|
|
"no_peer_access": TestSkip(79, "Test skipped because no GPU peer access"),
|
|
}
|
|
|
|
|
|
def skip_if_no_gpu(func):
|
|
""" Nccl multigpu tests require at least 2 GPUS. Skip if this is not met"""
|
|
@wraps(func)
|
|
def wrapper(*args, **kwargs):
|
|
if not torch.cuda.is_available():
|
|
sys.exit(TEST_SKIPS["no_cuda"].exit_code)
|
|
if torch.cuda.device_count() < int(os.environ["WORLD_SIZE"]):
|
|
message = "Need at least {} CUDA devices".format(os.environ["WORLD_SIZE"])
|
|
TEST_SKIPS["multi-gpu"] = TestSkip(75, message)
|
|
sys.exit(TEST_SKIPS["multi-gpu"].exit_code)
|
|
|
|
return func(*args, **kwargs)
|
|
|
|
return wrapper
|
|
|
|
|
|
def skip_if_small_worldsize(func):
|
|
@wraps(func)
|
|
def wrapper(*args, **kwargs):
|
|
if (os.environ["BACKEND"] != "mpi") and int(os.environ["WORLD_SIZE"]) <= 2:
|
|
sys.exit(TEST_SKIPS["small_worldsize"].exit_code)
|
|
|
|
return func(*args, **kwargs)
|
|
|
|
return wrapper
|
|
|
|
def require_n_gpus_for_nccl_backend(n, backend):
|
|
def decorator(func):
|
|
@wraps(func)
|
|
def wrapper(*args, **kwargs):
|
|
if backend == "nccl" and torch.cuda.device_count() < n:
|
|
message = "Need at least {} CUDA devices".format(n)
|
|
TEST_SKIPS["multi-gpu"] = TestSkip(75, message)
|
|
sys.exit(TEST_SKIPS['multi-gpu'].exit_code)
|
|
else:
|
|
return func(*args, **kwargs)
|
|
return wrapper
|
|
|
|
return decorator
|
|
|
|
def skip_if_lt_x_gpu(x):
|
|
def decorator(func):
|
|
@wraps(func)
|
|
def wrapper(*args, **kwargs):
|
|
if torch.cuda.is_available() and torch.cuda.device_count() >= x:
|
|
return func(*args, **kwargs)
|
|
message = "Need at least {} CUDA devices".format(x)
|
|
TEST_SKIPS["multi-gpu"] = TestSkip(75, message)
|
|
sys.exit(TEST_SKIPS['multi-gpu'].exit_code)
|
|
return wrapper
|
|
|
|
return decorator
|
|
|
|
|
|
def with_nccl_blocking_wait(func):
|
|
"""
|
|
Convenience decorator to set/unset NCCL_BLOCKING_WAIT flag. Note that use of
|
|
this decorator will override the setting of NCCL_ASYNC_ERROR_HANDLING for
|
|
the particular test. After the test, both NCCL_BLOCKING_WAIT and
|
|
NCCL_ASYNC_ERROR_HANDLING will be restored to their original values.
|
|
"""
|
|
@wraps(func)
|
|
def wrapper(*args, **kwargs):
|
|
# Save and unset NCCL_ASYNC_ERROR_HANDLING
|
|
try:
|
|
cached_nccl_async_error_handling: Union[str, None] = os.environ[
|
|
"NCCL_ASYNC_ERROR_HANDLING"
|
|
]
|
|
del os.environ["NCCL_ASYNC_ERROR_HANDLING"]
|
|
except KeyError:
|
|
# NCCL_ASYNC_ERROR_HANDLING was unset
|
|
cached_nccl_async_error_handling = None
|
|
|
|
# Save val of NCCL_BLOCKING_WAIT and set it.
|
|
try:
|
|
cached_nccl_blocking_wait: Union[str, None] = os.environ[
|
|
"NCCL_BLOCKING_WAIT"
|
|
]
|
|
except KeyError:
|
|
cached_nccl_blocking_wait = None
|
|
finally:
|
|
os.environ["NCCL_BLOCKING_WAIT"] = "1"
|
|
|
|
try:
|
|
ret = func(*args, **kwargs)
|
|
return ret
|
|
finally:
|
|
# restore old values.
|
|
if cached_nccl_async_error_handling is not None:
|
|
os.environ[
|
|
"NCCL_ASYNC_ERROR_HANDLING"
|
|
] = cached_nccl_async_error_handling
|
|
|
|
if cached_nccl_blocking_wait is not None:
|
|
os.environ["NCCL_BLOCKING_WAIT"] = cached_nccl_blocking_wait
|
|
|
|
return wrapper
|
|
|
|
def with_dist_debug_levels(levels):
|
|
"""
|
|
Runs a test for each distributed debug level specified in levels.
|
|
"""
|
|
def decorator(func):
|
|
@wraps(func)
|
|
def wrapper(*args, **kwargs):
|
|
old_level = os.environ.get("TORCH_DISTRIBUTED_DEBUG", None)
|
|
for level in levels:
|
|
os.environ["TORCH_DISTRIBUTED_DEBUG"] = level
|
|
ret = func(*args, **kwargs)
|
|
if old_level is not None:
|
|
os.environ["TORCH_DISTRIBUTED_DEBUG"] = old_level
|
|
# Only returns test return for last test, but since these are
|
|
# unittests the return value is not really used and earlier tests
|
|
# would've raised had they failed.
|
|
return ret
|
|
|
|
return wrapper
|
|
|
|
return decorator
|
|
|
|
|
|
def requires_gloo():
|
|
return unittest.skipUnless(
|
|
c10d.is_gloo_available(),
|
|
"c10d was not compiled with the Gloo backend",
|
|
)
|
|
|
|
def requires_nccl_version(version, msg):
|
|
if not c10d.is_nccl_available():
|
|
return unittest.skip(
|
|
"c10d was not compiled with the NCCL backend",
|
|
)
|
|
else:
|
|
return unittest.skipIf(
|
|
torch.cuda.nccl.version() < version,
|
|
"Requires NCCL version greater than or equal to: {}, found: {}, reason: {}".format(
|
|
version,
|
|
torch.cuda.nccl.version(), msg),
|
|
)
|
|
|
|
def requires_nccl():
|
|
return unittest.skipUnless(
|
|
c10d.is_nccl_available(),
|
|
"c10d was not compiled with the NCCL backend",
|
|
)
|
|
|
|
|
|
def requires_mpi():
|
|
return unittest.skipUnless(
|
|
c10d.is_mpi_available(),
|
|
"c10d was not compiled with the MPI backend",
|
|
)
|
|
|
|
def skip_if_rocm_single_process(func):
|
|
"""Skips a test for ROCm in a single process environment"""
|
|
func.skip_if_rocm = True
|
|
|
|
@wraps(func)
|
|
def wrapper(*args, **kwargs):
|
|
if not TEST_WITH_ROCM:
|
|
return func(*args, **kwargs)
|
|
raise unittest.SkipTest("Test skipped for ROCm")
|
|
|
|
return wrapper
|
|
|
|
def skip_if_rocm(func):
|
|
"""Skips a test for ROCm"""
|
|
func.skip_if_rocm = True
|
|
|
|
@wraps(func)
|
|
def wrapper(*args, **kwargs):
|
|
if not TEST_WITH_ROCM:
|
|
return func(*args, **kwargs)
|
|
sys.exit(TEST_SKIPS['skipIfRocm'].exit_code)
|
|
|
|
return wrapper
|
|
|
|
def skip_if_win32():
|
|
return unittest.skipIf(
|
|
sys.platform == 'win32',
|
|
"This unit test case is not supportted on Windows platform",
|
|
)
|
|
|
|
TIMEOUT_DEFAULT = 100
|
|
TIMEOUT_OVERRIDE = {"test_ddp_uneven_inputs": 400}
|
|
|
|
|
|
def create_device(interface=None):
|
|
if sys.platform == 'win32' or interface is None:
|
|
return c10d.ProcessGroupGloo.create_device(hostname="127.0.0.1")
|
|
else:
|
|
return c10d.ProcessGroupGloo.create_device(interface=interface)
|
|
|
|
|
|
def get_timeout(test_id):
|
|
return TIMEOUT_OVERRIDE.get(test_id.split('.')[-1], TIMEOUT_DEFAULT)
|
|
|
|
@contextmanager
|
|
def captured_output():
|
|
new_out, new_err = StringIO(), StringIO()
|
|
old_out, old_err = sys.stdout, sys.stderr
|
|
try:
|
|
sys.stdout, sys.stderr = new_out, new_err
|
|
yield sys.stdout, sys.stderr
|
|
finally:
|
|
sys.stdout, sys.stderr = old_out, old_err
|
|
|
|
def simple_sparse_reduce_tests(rank, world_size, num_inputs=1):
|
|
"""
|
|
Generate a number of basic test cases for sparse reduction.
|
|
These cover tensors with a varying number of sparse dimensions and a varying
|
|
number of dense dimensions. The only reduction operation we support is sum.
|
|
"""
|
|
def generate(rank, world_size, sparse_dims=1, dense_dims=0):
|
|
# First sparse dimension is [0..rank].
|
|
# Subsequent dimensions are always 0, so we know there is
|
|
# a non-empty intersection between any two sparse tensors.
|
|
indices = torch.reshape(torch.arange(rank + 1), (1, rank + 1))
|
|
shape = [world_size] + [2 for _ in range(dense_dims)]
|
|
for _ in range(sparse_dims - 1):
|
|
indices = torch.cat((indices, torch.zeros(1, rank + 1)))
|
|
shape.append(world_size)
|
|
values = torch.ones([rank + 1] + [2 for _ in range(dense_dims)])
|
|
return torch.sparse_coo_tensor(indices, values, shape)
|
|
|
|
def compute_sum(fn, world_size):
|
|
return reduce(lambda a, b: a + b, [fn(rank, world_size) for rank in range(world_size)])
|
|
|
|
return [
|
|
(
|
|
[
|
|
fn(num_inputs * rank + i, num_inputs * world_size)
|
|
for i in range(num_inputs)
|
|
],
|
|
[
|
|
compute_sum(fn, num_inputs * world_size)
|
|
for i in range(num_inputs)
|
|
],
|
|
)
|
|
for fn in [
|
|
partial(generate, sparse_dims=1),
|
|
partial(generate, sparse_dims=2),
|
|
partial(generate, sparse_dims=3),
|
|
partial(generate, dense_dims=1),
|
|
partial(generate, dense_dims=2),
|
|
partial(generate, dense_dims=3),
|
|
]
|
|
]
|
|
|
|
tmp_dir = None
|
|
def initialize_temp_directories(init_method=None):
|
|
global tmp_dir
|
|
tmp_dir = tempfile.TemporaryDirectory()
|
|
os.environ["TEMP_DIR"] = tmp_dir.name
|
|
os.mkdir(os.path.join(tmp_dir.name, "barrier"))
|
|
os.mkdir(os.path.join(tmp_dir.name, "test_dir"))
|
|
init_dir_path = os.path.join(tmp_dir.name, "init_dir")
|
|
os.mkdir(init_dir_path)
|
|
# Set init method if specified.
|
|
if init_method is not None:
|
|
os.environ["INIT_METHOD"] = init_method
|
|
else:
|
|
os.environ["INIT_METHOD"] = FILE_SCHEMA + os.path.join(
|
|
init_dir_path, "shared_init_file"
|
|
)
|
|
|
|
def cleanup_temp_dir():
|
|
if tmp_dir is not None:
|
|
tmp_dir.cleanup()
|
|
|
|
# [How does MultiProcessTestCase work?]
|
|
# Each MultiProcessTestCase instance uses 1 + `world_size()` processes, by
|
|
# default `world_size()` returns 4. Let's take `test_rpc_spawn.py` as an
|
|
# example which inherits from this class. Its `Setup()` methods calls into
|
|
# `MultiProcessTestCase._spawn_processes()` which spawns `world_size()`
|
|
# subprocesses. During the spawn, the main process passes the test name to
|
|
# subprocesses, and the name is acquired from self.id(). The subprocesses
|
|
# then use the provided test function name to retrieve the function attribute
|
|
# from the test instance and run it. The main process simply waits for all
|
|
# subprocesses to join.
|
|
class MultiProcessTestCase(TestCase):
|
|
MAIN_PROCESS_RANK = -1
|
|
# This exit code is used to indicate that the test code had an error and
|
|
# exited abnormally. There are certain tests that might use sys.exit() to
|
|
# simulate failures and in those cases, we can't have an exit code of 0,
|
|
# but we still want to ensure we didn't run into any other errors.
|
|
TEST_ERROR_EXIT_CODE = 10
|
|
|
|
# do not early terminate for distributed tests.
|
|
def _should_stop_test_suite(self):
|
|
return False
|
|
|
|
@property
|
|
def world_size(self):
|
|
return 4
|
|
|
|
def join_or_run(self, fn):
|
|
@wraps(fn)
|
|
def wrapper(self):
|
|
if self.rank == self.MAIN_PROCESS_RANK:
|
|
self._join_processes(fn)
|
|
else:
|
|
fn()
|
|
return types.MethodType(wrapper, self)
|
|
|
|
# The main process spawns N subprocesses that run the test.
|
|
# Constructor patches current instance test method to
|
|
# assume the role of the main process and join its subprocesses,
|
|
# or run the underlying test function.
|
|
def __init__(self, method_name='runTest'):
|
|
super().__init__(method_name)
|
|
fn = getattr(self, method_name)
|
|
setattr(self, method_name, self.join_or_run(fn))
|
|
|
|
def setUp(self):
|
|
super().setUp()
|
|
self.skip_return_code_checks = []
|
|
self.processes = []
|
|
self.rank = self.MAIN_PROCESS_RANK
|
|
self.file_name = tempfile.NamedTemporaryFile(delete=False).name
|
|
global TEST_SKIPS
|
|
self.old_test_skips = TEST_SKIPS.copy()
|
|
# pid to pipe consisting of error message from process.
|
|
self.pid_to_pipe = {}
|
|
|
|
def tearDown(self):
|
|
super().tearDown()
|
|
for p in self.processes:
|
|
p.terminate()
|
|
# Each Process instance holds a few open file descriptors. The unittest
|
|
# runner creates a new TestCase instance for each test method and keeps
|
|
# it alive until the end of the entire suite. We must thus reset the
|
|
# processes to prevent an effective file descriptor leak.
|
|
self.processes = []
|
|
|
|
def _current_test_name(self):
|
|
# self.id() == e.g. '__main__.TestDistributed.TestAdditive.test_get_rank'
|
|
return self.id().split(".")[-1]
|
|
|
|
def _start_processes(self, proc):
|
|
test_skips_manager = Manager()
|
|
test_skips = test_skips_manager.dict()
|
|
global TEST_SKIPS
|
|
test_skips.update(TEST_SKIPS)
|
|
TEST_SKIPS = test_skips
|
|
|
|
self.processes = []
|
|
for rank in range(int(self.world_size)):
|
|
parent_conn, child_conn = torch.multiprocessing.Pipe()
|
|
process = proc(
|
|
target=self.__class__._run,
|
|
name='process ' + str(rank),
|
|
args=(rank, self._current_test_name(), self.file_name, child_conn))
|
|
process.start()
|
|
logger.info(f'Started process {rank} with pid {process.pid}')
|
|
self.pid_to_pipe[process.pid] = parent_conn
|
|
self.processes.append(process)
|
|
|
|
def _fork_processes(self):
|
|
proc = torch.multiprocessing.get_context("fork").Process
|
|
self._start_processes(proc)
|
|
|
|
def _spawn_processes(self):
|
|
proc = torch.multiprocessing.get_context("spawn").Process
|
|
self._start_processes(proc)
|
|
|
|
class Event(Enum):
|
|
GET_TRACEBACK = 1
|
|
|
|
@staticmethod
|
|
def _event_listener(pipe, rank):
|
|
logger.info(f'Starting event listener thread for {rank}')
|
|
while True:
|
|
if pipe.poll(None):
|
|
|
|
if pipe.closed:
|
|
logger.info(f'Pipe closed for process {rank}, stopping event listener thread')
|
|
return
|
|
|
|
event = pipe.recv()
|
|
logger.info(f'Received event {event} on process {rank}')
|
|
|
|
if event == MultiProcessTestCase.Event.GET_TRACEBACK:
|
|
# Return traceback to the parent process.
|
|
with tempfile.NamedTemporaryFile(mode='r+') as tmp_file:
|
|
faulthandler.dump_traceback(tmp_file)
|
|
# Flush buffers and seek to read from the beginning
|
|
tmp_file.flush()
|
|
tmp_file.seek(0)
|
|
pipe.send(tmp_file.read())
|
|
|
|
logger.info(f'Process {rank} sent traceback')
|
|
|
|
@classmethod
|
|
def _run(cls, rank, test_name, file_name, pipe):
|
|
self = cls(test_name)
|
|
|
|
# Start event listener thread.
|
|
threading.Thread(
|
|
target=MultiProcessTestCase._event_listener,
|
|
args=(pipe, rank),
|
|
daemon=True).start()
|
|
|
|
self.rank = rank
|
|
self.file_name = file_name
|
|
self.run_test(test_name, pipe)
|
|
# exit to avoid run teardown() for fork processes
|
|
sys.exit(0)
|
|
|
|
def run_test(self, test_name, pipe):
|
|
if sys.platform != 'win32' and sys.platform != 'darwin':
|
|
# Register signal handler to dump stack traces on FATALs.
|
|
# Windows and MacOS do not support the signal handlers.
|
|
import caffe2.python._import_c_extension as C # type: ignore
|
|
C.set_print_stack_traces_on_fatal_signal(True) # type: ignore
|
|
|
|
# self.id() == e.g. '__main__.TestDistributed.test_get_rank'
|
|
# We're retrieving a corresponding test and executing it.
|
|
try:
|
|
getattr(self, test_name)()
|
|
# Close pipe after done with test.
|
|
pipe.close()
|
|
except Exception as e:
|
|
logger.error(
|
|
f'Caught exception: \n{traceback.format_exc()} exiting '
|
|
'process with exit code: {MultiProcessTestCase.TEST_ERROR_EXIT_CODE}')
|
|
# Send error to parent process.
|
|
pipe.send(traceback.format_exc())
|
|
pipe.close()
|
|
sys.exit(MultiProcessTestCase.TEST_ERROR_EXIT_CODE)
|
|
|
|
def _get_timedout_process_traceback(self):
|
|
pipes = []
|
|
for i, process in enumerate(self.processes):
|
|
if process.exitcode is None:
|
|
pipe = self.pid_to_pipe[process.pid]
|
|
try:
|
|
pipe.send(MultiProcessTestCase.Event.GET_TRACEBACK)
|
|
pipes.append((i, pipe))
|
|
except BrokenPipeError as e:
|
|
logger.error(f'Encountered error while trying to get traceback for process {i}: {e}')
|
|
|
|
# Wait for results.
|
|
for rank, pipe in pipes:
|
|
# Wait for traceback
|
|
if pipe.poll(5):
|
|
if pipe.closed:
|
|
logger.info(f'Pipe closed for process {rank}, cannot retrieve traceback')
|
|
continue
|
|
|
|
traceback = pipe.recv()
|
|
logger.error(f'Process {rank} timed out with traceback: \n\n{traceback}')
|
|
else:
|
|
logger.error(f'Could not retrieve traceback for timed out process: {rank}')
|
|
|
|
def _join_processes(self, fn):
|
|
timeout = get_timeout(self.id())
|
|
start_time = time.time()
|
|
subprocess_error = False
|
|
try:
|
|
while True:
|
|
# check to see if any subprocess exited with an error early.
|
|
for (i, p) in enumerate(self.processes):
|
|
# This is the exit code processes exit with if they
|
|
# encountered an exception.
|
|
if p.exitcode == MultiProcessTestCase.TEST_ERROR_EXIT_CODE:
|
|
print(f'Process {i} terminated with exit code {p.exitcode}, terminating remaining processes.')
|
|
active_children = torch.multiprocessing.active_children()
|
|
for ac in active_children:
|
|
ac.terminate()
|
|
subprocess_error = True
|
|
break
|
|
if subprocess_error:
|
|
break
|
|
# All processes have joined cleanly if they all a valid exitcode
|
|
if all([p.exitcode is not None for p in self.processes]):
|
|
break
|
|
# Check if we should time out the test. If so, we terminate each process.
|
|
elapsed = time.time() - start_time
|
|
if elapsed > timeout:
|
|
self._get_timedout_process_traceback()
|
|
print(f'Timing out after {timeout} seconds and killing subprocesses.')
|
|
for p in self.processes:
|
|
p.terminate()
|
|
break
|
|
# Sleep to avoid excessive busy polling.
|
|
time.sleep(0.1)
|
|
|
|
elapsed_time = time.time() - start_time
|
|
|
|
if fn in self.skip_return_code_checks:
|
|
self._check_no_test_errors(elapsed_time)
|
|
else:
|
|
self._check_return_codes(elapsed_time)
|
|
finally:
|
|
# Close all pipes
|
|
for pid, pipe in self.pid_to_pipe.items():
|
|
pipe.close()
|
|
|
|
global TEST_SKIPS
|
|
TEST_SKIPS = self.old_test_skips
|
|
|
|
def _check_no_test_errors(self, elapsed_time):
|
|
"""
|
|
Checks that we didn't have any errors thrown in the child processes.
|
|
"""
|
|
for i, p in enumerate(self.processes):
|
|
if p.exitcode is None:
|
|
raise RuntimeError('Process {} timed out after {} seconds'.format(i, elapsed_time))
|
|
self.assertNotEqual(self.TEST_ERROR_EXIT_CODE, p.exitcode)
|
|
|
|
def _check_return_codes(self, elapsed_time):
|
|
"""
|
|
Checks that the return codes of all spawned processes match, and skips
|
|
tests if they returned a return code indicating a skipping condition.
|
|
"""
|
|
first_process = self.processes[0]
|
|
# first, we check if there are errors in actual processes
|
|
# (via TEST_ERROR_EXIT CODE), and raise an exception for those.
|
|
# the reason we do this is to attempt to raise a more helpful error
|
|
# message than "Process x terminated/timed out"
|
|
# TODO: we should pipe the exception of the failed subprocess here.
|
|
# Currently, the actual exception is displayed as a logging output.
|
|
errored_processes = [
|
|
(i, p)
|
|
for i, p in enumerate(self.processes)
|
|
if p.exitcode == MultiProcessTestCase.TEST_ERROR_EXIT_CODE
|
|
]
|
|
if errored_processes:
|
|
error = ""
|
|
for i, process in errored_processes:
|
|
# Get error from pipe.
|
|
error_message = self.pid_to_pipe[process.pid].recv()
|
|
error += "Process {} exited with error code {} and exception:\n{}\n".format(
|
|
i, MultiProcessTestCase.TEST_ERROR_EXIT_CODE, error_message)
|
|
|
|
raise RuntimeError(error)
|
|
# If no process exited uncleanly, we check for timeouts, and then ensure
|
|
# each process exited cleanly.
|
|
for i, p in enumerate(self.processes):
|
|
if p.exitcode is None:
|
|
raise RuntimeError('Process {} terminated or timed out after {} seconds'.format(i, elapsed_time))
|
|
self.assertEqual(
|
|
p.exitcode,
|
|
first_process.exitcode,
|
|
msg="Expect process {} exit code to match Process 0 exit code of {}, but got {}".format(
|
|
i, first_process.exitcode, p.exitcode
|
|
),
|
|
)
|
|
for skip in TEST_SKIPS.values():
|
|
if first_process.exitcode == skip.exit_code:
|
|
raise unittest.SkipTest(skip.message)
|
|
self.assertEqual(
|
|
first_process.exitcode,
|
|
0,
|
|
msg="Expected zero exit code but got {}".format(first_process.exitcode)
|
|
)
|
|
|
|
@property
|
|
def is_master(self):
|
|
return self.rank == 0
|