python_code stringlengths 0 1.02M | repo_name stringlengths 9 48 | file_path stringlengths 5 114 |
|---|---|---|
# Owner(s): ["oncall: distributed"]
# Copyright 2019 Kakao Brain
#
# Copyright (c) Facebook, Inc. and its affiliates. All rights reserved.
#
# This source code is licensed under the BSD license found in the
# LICENSE file in the root directory of this source tree.
import pytest
import torch
from torch.distributed.pip... | pytorch-master | test/distributed/pipeline/sync/test_copy.py |
# Copyright 2019 Kakao Brain
#
# Copyright (c) Facebook, Inc. and its affiliates. All rights reserved.
#
# This source code is licensed under the BSD license found in the
# LICENSE file in the root directory of this source tree.
# tests/__init__.py makes pytest can import the application without custom sys.path or PYTH... | pytorch-master | test/distributed/pipeline/sync/__init__.py |
# Owner(s): ["oncall: distributed"]
# Copyright 2019 Kakao Brain
#
# Copyright (c) Facebook, Inc. and its affiliates. All rights reserved.
#
# This source code is licensed under the BSD license found in the
# LICENSE file in the root directory of this source tree.
import weakref
import pytest
import torch
from torch... | pytorch-master | test/distributed/pipeline/sync/test_dependency.py |
# Owner(s): ["oncall: distributed"]
# Copyright 2019 Kakao Brain
#
# Copyright (c) Facebook, Inc. and its affiliates. All rights reserved.
#
# This source code is licensed under the BSD license found in the
# LICENSE file in the root directory of this source tree.
import pytest
import torch
import torch.cuda
from tor... | pytorch-master | test/distributed/pipeline/sync/test_microbatch.py |
# Owner(s): ["oncall: distributed"]
# Copyright 2019 Kakao Brain
#
# Copyright (c) Facebook, Inc. and its affiliates. All rights reserved.
#
# This source code is licensed under the BSD license found in the
# LICENSE file in the root directory of this source tree.
from copy import deepcopy
from itertools import chain
... | pytorch-master | test/distributed/pipeline/sync/test_deferred_batch_norm.py |
# Owner(s): ["oncall: distributed"]
# Copyright 2019 Kakao Brain
#
# Copyright (c) Facebook, Inc. and its affiliates. All rights reserved.
#
# This source code is licensed under the BSD license found in the
# LICENSE file in the root directory of this source tree.
import threading
import pytest
import torch
from tor... | pytorch-master | test/distributed/pipeline/sync/test_worker.py |
# Owner(s): ["oncall: distributed"]
# Copyright 2019 Kakao Brain
#
# Copyright (c) Facebook, Inc. and its affiliates. All rights reserved.
#
# This source code is licensed under the BSD license found in the
# LICENSE file in the root directory of this source tree.
import torch
from torch.distributed.pipeline.sync.pho... | pytorch-master | test/distributed/pipeline/sync/test_phony.py |
# Owner(s): ["oncall: distributed"]
# Copyright 2019 Kakao Brain
#
# Copyright (c) Facebook, Inc. and its affiliates. All rights reserved.
#
# This source code is licensed under the BSD license found in the
# LICENSE file in the root directory of this source tree.
import pytest
import torch
from torch import nn
import... | pytorch-master | test/distributed/pipeline/sync/test_bugs.py |
# Owner(s): ["oncall: distributed"]
# Copyright 2019 Kakao Brain
#
# Copyright (c) Facebook, Inc. and its affiliates. All rights reserved.
#
# This source code is licensed under the BSD license found in the
# LICENSE file in the root directory of this source tree.
import time
import pytest
import torch
from torch imp... | pytorch-master | test/distributed/pipeline/sync/test_balance.py |
# Owner(s): ["oncall: distributed"]
# Copyright 2019 Kakao Brain
#
# Copyright (c) Facebook, Inc. and its affiliates. All rights reserved.
#
# This source code is licensed under the BSD license found in the
# LICENSE file in the root directory of this source tree.
from collections import OrderedDict
from copy import d... | pytorch-master | test/distributed/pipeline/sync/test_pipe.py |
# Owner(s): ["oncall: distributed"]
# Copyright 2019 Kakao Brain
#
# Copyright (c) Facebook, Inc. and its affiliates. All rights reserved.
#
# This source code is licensed under the BSD license found in the
# LICENSE file in the root directory of this source tree.
from torch.distributed.pipeline.sync.pipeline import _... | pytorch-master | test/distributed/pipeline/sync/test_pipeline.py |
# Owner(s): ["oncall: distributed"]
# Copyright 2019 Kakao Brain
#
# Copyright (c) Facebook, Inc. and its affiliates. All rights reserved.
#
# This source code is licensed under the BSD license found in the
# LICENSE file in the root directory of this source tree.
from functools import partial
import pytest
import to... | pytorch-master | test/distributed/pipeline/sync/test_checkpoint.py |
# Owner(s): ["oncall: distributed"]
# Copyright 2019 Kakao Brain
#
# Copyright (c) Facebook, Inc. and its affiliates. All rights reserved.
#
# This source code is licensed under the BSD license found in the
# LICENSE file in the root directory of this source tree.
import pytest
import torch
from torch.distributed.pip... | pytorch-master | test/distributed/pipeline/sync/test_stream.py |
# Copyright 2019 Kakao Brain
#
# Copyright (c) Facebook, Inc. and its affiliates. All rights reserved.
#
# This source code is licensed under the BSD license found in the
# LICENSE file in the root directory of this source tree.
| pytorch-master | test/distributed/pipeline/sync/skip/__init__.py |
# Owner(s): ["oncall: distributed"]
# Copyright 2019 Kakao Brain
#
# Copyright (c) Facebook, Inc. and its affiliates. All rights reserved.
#
# This source code is licensed under the BSD license found in the
# LICENSE file in the root directory of this source tree.
import pytest
import torch
from torch import nn
from ... | pytorch-master | test/distributed/pipeline/sync/skip/test_stash_pop.py |
# Owner(s): ["oncall: distributed"]
# Copyright 2019 Kakao Brain
#
# Copyright (c) Facebook, Inc. and its affiliates. All rights reserved.
#
# This source code is licensed under the BSD license found in the
# LICENSE file in the root directory of this source tree.
from queue import Queue
import threading
import pytes... | pytorch-master | test/distributed/pipeline/sync/skip/test_tracker.py |
# Owner(s): ["oncall: distributed"]
# Copyright 2019 Kakao Brain
#
# Copyright (c) Facebook, Inc. and its affiliates. All rights reserved.
#
# This source code is licensed under the BSD license found in the
# LICENSE file in the root directory of this source tree.
import pytest
from torch import nn
from torch.distrib... | pytorch-master | test/distributed/pipeline/sync/skip/test_verify_skippables.py |
# Owner(s): ["oncall: distributed"]
# Copyright 2019 Kakao Brain
#
# Copyright (c) Facebook, Inc. and its affiliates. All rights reserved.
#
# This source code is licensed under the BSD license found in the
# LICENSE file in the root directory of this source tree.
import pytest
import torch
from torch.distributed.pip... | pytorch-master | test/distributed/pipeline/sync/skip/test_portal.py |
# Owner(s): ["oncall: distributed"]
# Copyright 2019 Kakao Brain
#
# Copyright (c) Facebook, Inc. and its affiliates. All rights reserved.
#
# This source code is licensed under the BSD license found in the
# LICENSE file in the root directory of this source tree.
import pytest
import torch
from torch import nn
from ... | pytorch-master | test/distributed/pipeline/sync/skip/test_leak.py |
# Owner(s): ["oncall: distributed"]
# Copyright 2019 Kakao Brain
#
# Copyright (c) Facebook, Inc. and its affiliates. All rights reserved.
#
# This source code is licensed under the BSD license found in the
# LICENSE file in the root directory of this source tree.
import copy
from torch import nn
from torch.distribu... | pytorch-master | test/distributed/pipeline/sync/skip/test_api.py |
# Owner(s): ["oncall: distributed"]
# Copyright 2019 Kakao Brain
#
# Copyright (c) Facebook, Inc. and its affiliates. All rights reserved.
#
# This source code is licensed under the BSD license found in the
# LICENSE file in the root directory of this source tree.
from torch import nn
from torch.distributed.pipeline.... | pytorch-master | test/distributed/pipeline/sync/skip/test_inspect_skip_layout.py |
# Owner(s): ["oncall: distributed"]
# Copyright 2019 Kakao Brain
#
# Copyright (c) Facebook, Inc. and its affiliates. All rights reserved.
#
# This source code is licensed under the BSD license found in the
# LICENSE file in the root directory of this source tree.
import pytest
import torch
from torch import nn
from ... | pytorch-master | test/distributed/pipeline/sync/skip/test_gpipe.py |
#!/usr/bin/env python3
# Copyright (c) Facebook, Inc. and its affiliates.
# All rights reserved.
#
# This source code is licensed under the BSD-style license found in the
# LICENSE file in the root directory of this source tree.
| pytorch-master | test/distributed/launcher/__init__.py |
#!/usr/bin/env python3
# Owner(s): ["oncall: r2p"]
# Copyright (c) Facebook, Inc. and its affiliates.
# All rights reserved.
#
# This source code is licensed under the BSD-style license found in the
# LICENSE file in the root directory of this source tree.
import multiprocessing as mp
import os
import runpy
import shu... | pytorch-master | test/distributed/launcher/run_test.py |
#!/usr/bin/env python3
# Owner(s): ["oncall: r2p"]
# Copyright (c) Facebook, Inc. and its affiliates.
# All rights reserved.
#
# This source code is licensed under the BSD-style license found in the
# LICENSE file in the root directory of this source tree.
import multiprocessing as mp
import os
import shutil
import si... | pytorch-master | test/distributed/launcher/api_test.py |
#!/usr/bin/env python3
# Owner(s): ["oncall: r2p"]
# Copyright (c) Facebook, Inc. and its affiliates.
# All rights reserved.
#
# This source code is licensed under the BSD-style license found in the
# LICENSE file in the root directory of this source tree.
import os
import shutil
import tempfile
import unittest
from c... | pytorch-master | test/distributed/launcher/launch_test.py |
#!/usr/bin/env python3
# Owner(s): ["oncall: r2p"]
# Copyright (c) Facebook, Inc. and its affiliates.
# All rights reserved.
#
# This source code is licensed under the BSD-style license found in the
# LICENSE file in the root directory of this source tree.
import argparse
import os
def parse_args():
parser = ar... | pytorch-master | test/distributed/launcher/bin/test_script_local_rank.py |
#!/usr/bin/env python3
# Owner(s): ["oncall: r2p"]
# Copyright (c) Facebook, Inc. and its affiliates.
# All rights reserved.
#
# This source code is licensed under the BSD-style license found in the
# LICENSE file in the root directory of this source tree.
"""
This is a test script that launches as part of the test c... | pytorch-master | test/distributed/launcher/bin/test_script_is_torchelastic_launched.py |
#!/usr/bin/env python3
# Owner(s): ["oncall: r2p"]
# Copyright (c) Facebook, Inc. and its affiliates.
# All rights reserved.
#
# This source code is licensed under the BSD-style license found in the
# LICENSE file in the root directory of this source tree.
import argparse
import os
from pathlib import Path
def pars... | pytorch-master | test/distributed/launcher/bin/test_script.py |
#!/usr/bin/env python3
# Owner(s): ["oncall: r2p"]
# Copyright (c) Facebook, Inc. and its affiliates.
# All rights reserved.
#
# This source code is licensed under the BSD-style license found in the
# LICENSE file in the root directory of this source tree.
import argparse
import os
import torch
import torch.distribu... | pytorch-master | test/distributed/launcher/bin/test_script_init_method.py |
pytorch-master | test/distributed/nn/jit/__init__.py | |
#!/usr/bin/env python3
# Owner(s): ["oncall: distributed"]
import pathlib
import sys
from typing import Tuple
import torch
from torch import Tensor, nn
import torch.distributed as dist
if not dist.is_available():
print("Distributed not available, skipping tests", file=sys.stderr)
sys.exit(0)
from torch.dist... | pytorch-master | test/distributed/nn/jit/test_instantiator.py |
#!/usr/bin/env python3
# Owner(s): ["oncall: distributed"]
# Copyright (c) Facebook, Inc. and its affiliates.
# All rights reserved.
#
# This source code is licensed under the BSD-style license found in the
# LICENSE file in the root directory of this source tree.
def main():
print("Success, smoke test")
if __... | pytorch-master | test/distributed/bin/test_script.py |
#!/usr/bin/env python3
# Copyright (c) Facebook, Inc. and its affiliates.
# All rights reserved.
#
# This source code is licensed under the BSD-style license found in the
# LICENSE file in the root directory of this source tree.abs
| pytorch-master | test/distributed/elastic/metrics/__init__.py |
#!/usr/bin/env python3
# Owner(s): ["oncall: r2p"]
# Copyright (c) Facebook, Inc. and its affiliates.
# All rights reserved.
#
# This source code is licensed under the BSD-style license found in the
# LICENSE file in the root directory of this source tree.abs
import abc
import unittest.mock as mock
from torch.distrib... | pytorch-master | test/distributed/elastic/metrics/api_test.py |
# Owner(s): ["oncall: r2p"]
# Copyright (c) Facebook, Inc. and its affiliates.
# All rights reserved.
#
# This source code is licensed under the BSD-style license found in the
# LICENSE file in the root directory of this source tree.
import os
import tempfile
from base64 import b64encode
from datetime import timedel... | pytorch-master | test/distributed/elastic/rendezvous/c10d_rendezvous_backend_test.py |
# Owner(s): ["oncall: r2p"]
# Copyright (c) Facebook, Inc. and its affiliates.
# All rights reserved.
#
# This source code is licensed under the BSD-style license found in the
# LICENSE file in the root directory of this source tree.
import threading
import time
import socket
from datetime import timedelta
from typin... | pytorch-master | test/distributed/elastic/rendezvous/utils_test.py |
# Owner(s): ["oncall: r2p"]
# Copyright (c) Facebook, Inc. and its affiliates.
# All rights reserved.
#
# This source code is licensed under the BSD-style license found in the
# LICENSE file in the root directory of this source tree.
import os
import unittest
import etcd
from torch.distributed.elastic.rendezvous.etcd... | pytorch-master | test/distributed/elastic/rendezvous/etcd_server_test.py |
# Owner(s): ["oncall: r2p"]
# Copyright (c) Facebook, Inc. and its affiliates.
# All rights reserved.
#
# This source code is licensed under the BSD-style license found in the
# LICENSE file in the root directory of this source tree.
import os
import unittest
import uuid
from torch.distributed.elastic.rendezvous impo... | pytorch-master | test/distributed/elastic/rendezvous/etcd_rendezvous_test.py |
# Copyright (c) Facebook, Inc. and its affiliates.
# All rights reserved.
#
# This source code is licensed under the BSD-style license found in the
# LICENSE file in the root directory of this source tree.
| pytorch-master | test/distributed/elastic/rendezvous/__init__.py |
# Owner(s): ["oncall: r2p"]
# Copyright (c) Facebook, Inc. and its affiliates.
# All rights reserved.
#
# This source code is licensed under the BSD-style license found in the
# LICENSE file in the root directory of this source tree.
import copy
import os
import pickle
import socket
import threading
import time
from ... | pytorch-master | test/distributed/elastic/rendezvous/dynamic_rendezvous_test.py |
# Owner(s): ["oncall: r2p"]
# Copyright (c) Facebook, Inc. and its affiliates.
# All rights reserved.
#
# This source code is licensed under the BSD-style license found in the
# LICENSE file in the root directory of this source tree.
from abc import ABC, abstractmethod
from typing import Any, Callable, Optional, Tupl... | pytorch-master | test/distributed/elastic/rendezvous/rendezvous_backend_test.py |
# Owner(s): ["oncall: r2p"]
# Copyright (c) Facebook, Inc. and its affiliates.
# All rights reserved.
#
# This source code is licensed under the BSD-style license found in the
# LICENSE file in the root directory of this source tree.
import subprocess
from base64 import b64encode
from typing import ClassVar, cast
fro... | pytorch-master | test/distributed/elastic/rendezvous/etcd_rendezvous_backend_test.py |
# Owner(s): ["oncall: r2p"]
# Copyright (c) Facebook, Inc. and its affiliates.
# All rights reserved.
#
# This source code is licensed under the BSD-style license found in the
# LICENSE file in the root directory of this source tree.
from typing import Any, Dict, SupportsInt, Tuple, cast
from unittest import TestCase... | pytorch-master | test/distributed/elastic/rendezvous/api_test.py |
# Owner(s): ["oncall: r2p"]
# Copyright (c) Facebook, Inc. and its affiliates.
# All rights reserved.
#
# This source code is licensed under the BSD-style license found in the
# LICENSE file in the root directory of this source tree.
import unittest
from contextlib import closing
from torch.distributed.elastic.rendez... | pytorch-master | test/distributed/elastic/rendezvous/static_rendezvous_test.py |
#!/usr/bin/env python3
# Owner(s): ["oncall: r2p"]
# Copyright (c) Facebook, Inc. and its affiliates.
# All rights reserved.
#
# This source code is licensed under the BSD-style license found in the
# LICENSE file in the root directory of this source tree.
import ctypes
import os
import shutil
import sys
import tempfi... | pytorch-master | test/distributed/elastic/multiprocessing/redirects_test.py |
#!/usr/bin/env python3
# Owner(s): ["oncall: r2p"]
# Copyright (c) Facebook, Inc. and its affiliates.
# All rights reserved.
#
# This source code is licensed under the BSD-style license found in the
# LICENSE file in the root directory of this source tree.
import io
import os
import shutil
import sys
import tempfile
i... | pytorch-master | test/distributed/elastic/multiprocessing/tail_log_test.py |
#!/usr/bin/env python3
# Owner(s): ["oncall: r2p"]
# Copyright (c) Facebook, Inc. and its affiliates.
# All rights reserved.
#
# This source code is licensed under the BSD-style license found in the
# LICENSE file in the root directory of this source tree.
import ctypes
import multiprocessing
import os
import shutil
i... | pytorch-master | test/distributed/elastic/multiprocessing/api_test.py |
#!/usr/bin/env python3
# Copyright (c) Facebook, Inc. and its affiliates.
# All rights reserved.
#
# This source code is licensed under the BSD-style license found in the
# LICENSE file in the root directory of this source tree.
import argparse
import ctypes
import os
if __name__ == "__main__":
parser = argpars... | pytorch-master | test/distributed/elastic/multiprocessing/bin/echo3.py |
#!/usr/bin/env python3
# Owner(s): ["oncall: r2p"]
# Copyright (c) Facebook, Inc. and its affiliates.
# All rights reserved.
#
# This source code is licensed under the BSD-style license found in the
# LICENSE file in the root directory of this source tree.
# TODO <DELETE_ME>
| pytorch-master | test/distributed/elastic/multiprocessing/bin/test_script.py |
#!/usr/bin/env python3
# Copyright (c) Facebook, Inc. and its affiliates.
# All rights reserved.
#
# This source code is licensed under the BSD-style license found in the
# LICENSE file in the root directory of this source tree.
import argparse
import os
if __name__ == "__main__":
parser = argparse.ArgumentPars... | pytorch-master | test/distributed/elastic/multiprocessing/bin/echo2.py |
#!/usr/bin/env python3
# Copyright (c) Facebook, Inc. and its affiliates.
# All rights reserved.
#
# This source code is licensed under the BSD-style license found in the
# LICENSE file in the root directory of this source tree.
import argparse
import os
import sys
if __name__ == "__main__":
parser = argparse.A... | pytorch-master | test/distributed/elastic/multiprocessing/bin/echo1.py |
#!/usr/bin/env python3
# Owner(s): ["oncall: r2p"]
# Copyright (c) Facebook, Inc. and its affiliates.
# All rights reserved.
#
# This source code is licensed under the BSD-style license found in the
# LICENSE file in the root directory of this source tree.
import time
if __name__ == "__main__":
time.sleep(600)
... | pytorch-master | test/distributed/elastic/multiprocessing/bin/zombie_test.py |
#!/usr/bin/env python3
# Owner(s): ["oncall: r2p"]
import json
import os
import shutil
import signal
import tempfile
import unittest
from unittest import mock
from torch.distributed.elastic.multiprocessing.errors import (
ChildFailedError,
ProcessFailure,
record,
)
from torch.distributed.elastic.multiproc... | pytorch-master | test/distributed/elastic/multiprocessing/errors/api_test.py |
#!/usr/bin/env python3
# Owner(s): ["oncall: r2p"]
import filecmp
import json
import os
import shutil
import tempfile
import unittest
from unittest.mock import patch
from torch.distributed.elastic.multiprocessing.errors.error_handler import ErrorHandler
from torch.distributed.elastic.multiprocessing.errors.handlers i... | pytorch-master | test/distributed/elastic/multiprocessing/errors/error_handler_test.py |
# Owner(s): ["oncall: r2p"]
# Copyright (c) Facebook, Inc. and its affiliates.
# All rights reserved.
#
# This source code is licensed under the BSD-style license found in the
# LICENSE file in the root directory of this source tree.
import multiprocessing as mp
import signal
import time
import unittest
import unittes... | pytorch-master | test/distributed/elastic/timer/local_timer_test.py |
#!/usr/bin/env python3
# Owner(s): ["oncall: r2p"]
# Copyright (c) Facebook, Inc. and its affiliates.
# All rights reserved.
#
# This source code is licensed under the BSD-style license found in the
# LICENSE file in the root directory of this source tree.
import logging
import multiprocessing as mp
import signal
impo... | pytorch-master | test/distributed/elastic/timer/local_timer_example.py |
# Copyright (c) Facebook, Inc. and its affiliates.
# All rights reserved.
#
# This source code is licensed under the BSD-style license found in the
# LICENSE file in the root directory of this source tree.
| pytorch-master | test/distributed/elastic/timer/__init__.py |
# Owner(s): ["oncall: r2p"]
# Copyright (c) Facebook, Inc. and its affiliates.
# All rights reserved.
#
# This source code is licensed under the BSD-style license found in the
# LICENSE file in the root directory of this source tree.
import unittest
import unittest.mock as mock
from torch.distributed.elastic.timer im... | pytorch-master | test/distributed/elastic/timer/api_test.py |
#!/usr/bin/env python3
# Owner(s): ["oncall: r2p"]
# Copyright (c) Facebook, Inc. and its affiliates.
# All rights reserved.
#
# This source code is licensed under the BSD-style license found in the
# LICENSE file in the root directory of this source tree.
import torch.distributed.elastic.utils.logging as logging
from... | pytorch-master | test/distributed/elastic/utils/logging_test.py |
#!/usr/bin/env python3
# Copyright (c) Facebook, Inc. and its affiliates.
# All rights reserved.
#
# This source code is licensed under the BSD-style license found in the
# LICENSE file in the root directory of this source tree.
| pytorch-master | test/distributed/elastic/utils/__init__.py |
#!/usr/bin/env python3
# Owner(s): ["oncall: r2p"]
# Copyright (c) Facebook, Inc. and its affiliates.
# All rights reserved.
#
# This source code is licensed under the BSD-style license found in the
# LICENSE file in the root directory of this source tree.
from unittest import mock
import torch.distributed.elastic.u... | pytorch-master | test/distributed/elastic/utils/util_test.py |
#!/usr/bin/env python3
# Owner(s): ["oncall: r2p"]
# Copyright (c) Facebook, Inc. and its affiliates.
# All rights reserved.
#
# This source code is licensed under the BSD-style license found in the
# LICENSE file in the root directory of this source tree.
import multiprocessing as mp
import os
import socket
import s... | pytorch-master | test/distributed/elastic/utils/distributed_test.py |
#!/usr/bin/env python3
# Owner(s): ["oncall: r2p"]
# Copyright (c) Facebook, Inc. and its affiliates.
# All rights reserved.
#
# This source code is licensed under the BSD-style license found in the
# LICENSE file in the root directory of this source tree.
import unittest
from torch.distributed.elastic.utils.data imp... | pytorch-master | test/distributed/elastic/utils/data/cycling_iterator_test.py |
#!/usr/bin/env python3
# Copyright (c) Facebook, Inc. and its affiliates.
# All rights reserved.
#
# This source code is licensed under the BSD-style license found in the
# LICENSE file in the root directory of this source tree.
| pytorch-master | test/distributed/elastic/utils/data/__init__.py |
#!/usr/bin/env python3
# Copyright (c) Facebook, Inc. and its affiliates.
# All rights reserved.
#
# This source code is licensed under the BSD-style license found in the
# LICENSE file in the root directory of this source tree.
| pytorch-master | test/distributed/elastic/agent/server/test/__init__.py |
#!/usr/bin/env python3
# Owner(s): ["oncall: r2p"]
# Copyright (c) Facebook, Inc. and its affiliates.
# All rights reserved.
#
# This source code is licensed under the BSD-style license found in the
# LICENSE file in the root directory of this source tree.
import json
import multiprocessing as mp
import os
import shut... | pytorch-master | test/distributed/elastic/agent/server/test/local_elastic_agent_test.py |
#!/usr/bin/env python3
# Owner(s): ["oncall: r2p"]
# Copyright (c) Facebook, Inc. and its affiliates.
# All rights reserved.
#
# This source code is licensed under the BSD-style license found in the
# LICENSE file in the root directory of this source tree.
import signal
import unittest
import uuid
from typing import... | pytorch-master | test/distributed/elastic/agent/server/test/api_test.py |
#!/usr/bin/env python3
# Owner(s): ["oncall: r2p"]
# Copyright (c) Facebook, Inc. and its affiliates.
# All rights reserved.
#
# This source code is licensed under the BSD-style license found in the
# LICENSE file in the root directory of this source tree.abs
import json
import logging
import unittest
from dataclasse... | pytorch-master | test/distributed/elastic/events/lib_test.py |
# Owner(s): ["oncall: distributed"]
import contextlib
import os
import sys
from typing import Any, Optional
import torch
import torch.distributed as dist
if not dist.is_available():
print("Distributed not available, skipping tests", file=sys.stderr)
sys.exit(0)
from torch.distributed.algorithms.join import ... | pytorch-master | test/distributed/algorithms/test_join.py |
# Owner(s): ["oncall: distributed"]
import os
import sys
import torch
from torch import nn
import torch.distributed as dist
if not dist.is_available():
print("Distributed not available, skipping tests", file=sys.stderr)
sys.exit(0)
from torch.distributed.algorithms.ddp_comm_hooks import (
DDPCommHookTyp... | pytorch-master | test/distributed/algorithms/ddp_comm_hooks/test_ddp_hooks.py |
# Owner(s): ["oncall: distributed"]
import torch
import os
import torch.cuda
import sys
import torch.distributed as dist
import torch.distributed.algorithms._quantization.quantization as quant
from torch.distributed.algorithms._quantization.quantization import DQuantType
from torch.testing._internal.common_distributed... | pytorch-master | test/distributed/algorithms/quantization/test_quantization.py |
# Owner(s): ["oncall: distributed"]
# Copyright (c) Facebook, Inc. and its affiliates. All rights reserved.
#
# This source code is licensed under the BSD license found in the
# LICENSE file in the root directory of this source tree.
import copy
import os
import sys
import unittest
from contextlib import suppress
fro... | pytorch-master | test/distributed/optim/test_zero_redundancy_optimizer.py |
# Owner(s): ["oncall: distributed"]
import sys
import torch
from torch import distributed as dist
from torch.distributed.fsdp import FullyShardedDataParallel as FSDP
from torch.nn import Linear
from torch.optim import SGD
from torch.testing._internal.common_distributed import skip_if_lt_x_gpu
from torch.testing._inte... | pytorch-master | test/distributed/fsdp/test_fsdp_uneven.py |
# Owner(s): ["oncall: distributed"]
import sys
import torch
import torch.nn as nn
from torch import distributed as dist
from torch.distributed.fsdp import FullyShardedDataParallel as FSDP
from torch.testing._internal.common_distributed import skip_if_lt_x_gpu
from torch.testing._internal.common_fsdp import (
CUDA... | pytorch-master | test/distributed/fsdp/test_fsdp_ignored_modules.py |
# Owner(s): ["oncall: distributed"]
import sys
import torch
from torch import distributed as dist
from torch.distributed.fsdp import FullyShardedDataParallel as FSDP
from torch.nn import Linear, Module
from torch.optim import SGD
from torch.testing._internal.common_distributed import skip_if_lt_x_gpu
from torch.testi... | pytorch-master | test/distributed/fsdp/test_fsdp_input.py |
# Owner(s): ["oncall: distributed"]
import random
import sys
from typing import List
import unittest
from collections import OrderedDict
import torch
import torch.nn as nn
from torch import distributed as dist
from torch.distributed.fsdp._utils import _apply_to_tensors
from torch.distributed.utils import _replace_by_... | pytorch-master | test/distributed/fsdp/test_utils.py |
# Owner(s): ["oncall: distributed"]
import sys
import torch
from torch import distributed as dist
from torch.distributed.fsdp import FullyShardedDataParallel as FSDP
from torch.nn import Linear, Module
from torch.nn.parallel import DistributedDataParallel
from torch.optim import SGD
from torch.testing._internal.commo... | pytorch-master | test/distributed/fsdp/test_fsdp_multiple_forward.py |
# Owner(s): ["oncall: distributed"]
import sys
from torch import distributed as dist
from torch.distributed.fsdp import CPUOffload
from torch.testing._internal.common_distributed import skip_if_lt_x_gpu
from torch.testing._internal.common_fsdp import (
CUDAInitMode,
FSDPInitMode,
FSDPTest,
NestedWrapp... | pytorch-master | test/distributed/fsdp/test_fsdp_pure_fp16.py |
# Owner(s): ["oncall: distributed"]
import sys
from math import inf
import torch
from torch import distributed as dist
from torch.distributed.fsdp.fully_sharded_data_parallel import (
FullyShardedDataParallel as FSDP,
CPUOffload,
_calc_grad_norm,
)
from torch.nn import utils as nn_utils
from torch.testing... | pytorch-master | test/distributed/fsdp/test_fsdp_clip_grad_norm.py |
# Owner(s): ["oncall: distributed"]
import itertools
import math
import sys
from copy import deepcopy
import torch
import torch.nn as nn
from torch import distributed as dist
from torch.distributed.fsdp import CPUOffload
from torch.distributed.fsdp import FullyShardedDataParallel as FSDP
from torch.distributed.fsdp im... | pytorch-master | test/distributed/fsdp/test_fsdp_summon_full_params.py |
# Owner(s): ["oncall: distributed"]
import bisect
import sys
from enum import Enum, auto
from typing import Any, Dict, List, Tuple, Type
import torch
from torch import distributed as dist
from torch.distributed.algorithms._checkpoint.checkpoint_wrapper import (
_CHECKPOINT_PREFIX, apply_activation_checkpointing_w... | pytorch-master | test/distributed/fsdp/test_fsdp_optim_state.py |
# Owner(s): ["oncall: distributed"]
import sys
import warnings
from contextlib import suppress
import torch
from torch import distributed as dist
from torch.distributed.fsdp import FullyShardedDataParallel as FSDP
from torch.distributed.fsdp.fully_sharded_data_parallel import ShardingStrategy
from torch.testing._inte... | pytorch-master | test/distributed/fsdp/test_fsdp_exec_order.py |
# Owner(s): ["oncall: distributed"]
import sys
import torch
import torch.distributed as dist
import torch.nn as nn
from torch.distributed.fsdp import FullyShardedDataParallel as FSDP
from torch.testing._internal.common_distributed import skip_if_lt_x_gpu
from torch.testing._internal.common_fsdp import (
CUDAInitM... | pytorch-master | test/distributed/fsdp/test_fsdp_apply.py |
# Owner(s): ["oncall: distributed"]
import sys
import torch
import torch.distributed as dist
import torch.nn as nn
from torch.distributed.fsdp import FullyShardedDataParallel as FSDP
from torch.distributed.fsdp.wrap import always_wrap_policy as always_wrap
from torch.distributed.fsdp.wrap import wrap, enable_wrap
fro... | pytorch-master | test/distributed/fsdp/test_fsdp_meta.py |
# Owner(s): ["oncall: distributed"]
from typing import Any
import torch
from torch.distributed.fsdp._symbolic_trace import _init_execution_info, _patch_tracer
from torch.testing._internal.common_fsdp import FSDPTest
from torch.testing._internal.common_utils import (
instantiate_parametrized_tests,
run_tests,
... | pytorch-master | test/distributed/fsdp/test_fsdp_fx.py |
# Owner(s): ["oncall: distributed"]
import functools
import itertools
import sys
import unittest
from typing import Optional
import torch
from torch import distributed as dist
from torch.cuda.amp.common import amp_definitely_not_available
from torch.distributed.fsdp import CPUOffload, MixedPrecision
from torch.distri... | pytorch-master | test/distributed/fsdp/test_fsdp_sharded_grad_scaler.py |
# Owner(s): ["oncall: distributed"]
import contextlib
import itertools
import sys
from dataclasses import dataclass
from typing import List, Optional, Tuple
import torch
from torch import distributed as dist
from torch.distributed.fsdp import CPUOffload
from torch.distributed.fsdp import FullyShardedDataParallel as F... | pytorch-master | test/distributed/fsdp/test_fsdp_grad_acc.py |
# Owner(s): ["oncall: distributed"]
import contextlib
import sys
from functools import partial
from itertools import product
from typing import Any, Dict, List
import torch
import torch.cuda.nccl as nccl
import torch.nn as nn
import torch.nn.functional as F
from torch import distributed as dist
from torch.distributed... | pytorch-master | test/distributed/fsdp/test_fsdp_mixed_precision.py |
# Owner(s): ["oncall: distributed"]
import sys
from enum import Enum
import torch
import torch.nn as nn
import torch.optim as optim
from torch import distributed as dist
from torch.distributed.fsdp import FullyShardedDataParallel as FSDP
from torch.nn.parallel import DistributedDataParallel
from torch.testing._intern... | pytorch-master | test/distributed/fsdp/test_fsdp_freezing_weights.py |
# Owner(s): ["oncall: distributed"]
import sys
from torch import distributed as dist
from torch.distributed.fsdp import FullyShardedDataParallel as FSDP
from torch.testing._internal.common_distributed import skip_if_lt_x_gpu
from torch.testing._internal.common_fsdp import (
CUDAInitMode,
FSDPInitMode,
FSD... | pytorch-master | test/distributed/fsdp/test_fsdp_traversal.py |
# Owner(s): ["oncall: distributed"]
import sys
from contextlib import suppress
from enum import Enum, auto
from typing import Optional
from unittest.mock import patch
import torch
from torch import distributed as dist
from torch.distributed.fsdp import FullyShardedDataParallel as FSDP
from torch.distributed.fsdp.full... | pytorch-master | test/distributed/fsdp/test_fsdp_comm.py |
# Owner(s): ["oncall: distributed"]
import torch
from torch.distributed._shard.sharded_tensor import (
init_from_local_shards,
Shard,
ShardMetadata,
)
from torch.distributed._shard.sharding_spec import (
ChunkShardingSpec,
EnumerableShardingSpec,
)
from torch.distributed.distributed_c10d import _ge... | pytorch-master | test/distributed/fsdp/test_shard_utils.py |
# Owner(s): ["oncall: distributed"]
import sys
import torch
import torch.nn as nn
import torch.optim as optim
from torch import distributed as dist
from torch.distributed.fsdp import FullyShardedDataParallel as FSDP
from torch.testing._internal.common_distributed import skip_if_lt_x_gpu
from torch.testing._internal.c... | pytorch-master | test/distributed/fsdp/test_fsdp_memory.py |
# Owner(s): ["oncall: distributed"]
import sys
import unittest
import torch
from torch import distributed as dist
from torch.distributed.fsdp.flat_param import FlatParamShardMetadata
from torch.distributed.fsdp.flatten_params_wrapper import FlattenParamsWrapper
from torch.testing._internal.common_utils import TestCas... | pytorch-master | test/distributed/fsdp/test_flatten_params_wrapper.py |
# Owner(s): ["oncall: distributed"]
import functools
import sys
from collections import namedtuple
from contextlib import suppress
import torch
import torch.distributed as dist
import torch.nn as nn
from torch.distributed.fsdp import FlatParameter
from torch.distributed.fsdp import FullyShardedDataParallel as FSDP
fr... | pytorch-master | test/distributed/fsdp/test_fsdp_misc.py |
# Owner(s): ["oncall: distributed"]
import functools
import itertools
import sys
from typing import Any, Dict, List, Optional
from unittest import mock
import torch
import torch.distributed as dist
import torch.nn as nn
from torch.distributed.fsdp import CPUOffload, MixedPrecision
from torch.distributed.fsdp.fully_sh... | pytorch-master | test/distributed/fsdp/test_fsdp_core.py |
# Owner(s): ["oncall: distributed"]
from copy import deepcopy
from functools import partial
import torch
import torch.nn as nn
from torch.distributed.algorithms._checkpoint.checkpoint_wrapper import (
checkpoint_wrapper,
apply_activation_checkpointing_wrapper,
CheckpointWrapper,
CheckpointImpl
)
from... | pytorch-master | test/distributed/fsdp/test_checkpoint_wrapper.py |
# Owner(s): ["oncall: distributed"]
import sys
import tempfile
import torch
from torch import distributed as dist
from torch.distributed._shard.checkpoint import (
FileSystemReader,
FileSystemWriter,
save_state_dict,
load_state_dict,
)
from torch.distributed.fsdp import (
FullyShardedDataParallel ... | pytorch-master | test/distributed/fsdp/test_distributed_checkpoint.py |
# Owner(s): ["oncall: distributed"]
import sys
import torch
from torch import distributed as dist
from torch.distributed.fsdp import FullyShardedDataParallel as FSDP
from torch.nn import Linear, Module, Sequential
from torch.optim import SGD
from torch.testing._internal.common_distributed import skip_if_lt_x_gpu
from... | pytorch-master | test/distributed/fsdp/test_fsdp_multiple_wrapping.py |
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