lightning/pytorch_lightning/plugins/environments/lightning_environment.py

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introduce default cluster environment for lightning-specific ddp (#5915) * handle distributed_sampler_kwargs * move emptying cache to accelertor * fix a few tests * restoring the result from subprocess * fix queue.get() order for results * add missing "block_backward_sync" context manager * add missing "block_backward_sync" context manager * fix sync_batchnorm * fix supported gpu-ids for tuple * fix clip gradients and inf recursion * accelerator selection: added cluster_environment plugin * fix torchelastic test * fix reduce early stopping decision for DDP * fix tests: callbacks, conversion to lightning optimizer * fix lightning optimizer does not pickle * fix setting benchmark and deterministic option * fix slurm amp test * fix prepare_data test and determine node_rank * fix retrieving last path when testing * remove obsolete plugin argument * fix test: test_trainer_config * fix torchscript tests * fix trainer.model access * move properties * fix test_transfer_batch_hook * fix auto_select_gpus * fix omegaconf test * fix test that needs to simulate slurm ddp * add horovod plugin * fix test with named arguments * clean up whitespace * fix datamodules test * remove old accelerators * fix naming * move old plugins * move to plugins * create precision subpackage * create training_type subpackage * fix all new import errors * fix wrong arguments order passed to test * fix LR finder * Added sharded training type and amp plugin * Move clip grad to precision plugin * Added sharded spawn, select accelerators based on distributed_backend + enable custom fp16 plugin automatically * Fix import issue, attempting to fix tests * Fix initial test * Reflect hook logic from master, should wrap model after move to device * Optional state consolidation, since master has optimizers not wrapped * change attribute for instance test * reset optimizers optimizers are not used in main process, so state would be wrong. * legacy * imports in accel * legacy2 * trainer imports * fix import errors after rebase * move hook to new setup location * provide unwrapping logic * fix trainer callback system * added ddp2 implementation * fix imports .legacy * move plugins * restore legacy * drop test.py from root * add tpu accelerator and plugins * fixes * fix lightning optimizer merge * reset bugreportmodel * unwrapping * step routing forward * model access * unwrap * opt * integrate distrib_type * sync changes * sync * fixes * add forgotten generators * add missing logic * update * import * missed imports * import fixes * isort * mv f * changelog * format * move helper to parallel plugin * d * add world size * clean up * duplicate * activate ddp_sharded and tpu * set nvidia flags * remove unused colab var * use_tpu <-> on_tpu attrs * make some ddp_cpu and clusterplugin tests pass * Ref/accelerator connector (#5742) * final cleanup Co-authored-by: Adrian Wälchli <aedu.waelchli@gmail.com> * connector cleanup Co-authored-by: Adrian Wälchli <aedu.waelchli@gmail.com> * trainer cleanup Co-authored-by: Adrian Wälchli <aedu.waelchli@gmail.com> * accelerator cleanup + missing logic in accelerator connector Co-authored-by: Adrian Wälchli <aedu.waelchli@gmail.com> * add missing changes to callbacks Co-authored-by: Adrian Wälchli <aedu.waelchli@gmail.com> * reflect accelerator changes to lightning module Co-authored-by: Adrian Wälchli <aedu.waelchli@gmail.com> * clean cluster envs Co-authored-by: Adrian Wälchli <aedu.waelchli@gmail.com> * cleanup plugins Co-authored-by: Adrian Wälchli <aedu.waelchli@gmail.com> * add broadcasting Co-authored-by: Adrian Wälchli <aedu.waelchli@gmail.com> * yapf * remove plugin connector Co-authored-by: Adrian Wälchli <aedu.waelchli@gmail.com> * plugins * manual optimization * update optimizer routing * add rank to torchelastic * fix memory mixed precision * setstate on trainer for pickling in ddp spawn * add predict method * add back commented accelerator code * adapt test for sync_batch_norm to new plugin * fix deprecated tests * fix ddp cpu choice when no num_processes are given * yapf format * skip a memory test that cannot pass anymore * fix pickle error in spawn plugin * x * avoid * x * fix cyclic import in docs build * add support for sharded * update typing * add sharded and sharded_spawn to distributed types * make unwrap model default * refactor LightningShardedDataParallel similar to LightningDistributedDataParallel * update sharded spawn to reflect changes * update sharded to reflect changes * Merge 1.1.5 changes * fix merge * fix merge * yapf isort * fix merge * yapf isort * fix indentation in test * copy over reinit scheduler implementation from dev1.2 * fix apex tracking calls with dev_debugger * reduce diff to dev1.2, clean up * fix trainer config test when gpus>0 and num_processes >0 and ddp_cpu * sort plugin tests legacy/new * fix error handling for amp on cpu * fix merge fix merge fix merge * [Feat] Resolve manual_backward (#5837) * resolve manual_backward * resolve flake8 * update * resolve for ddp_spawn * resolve flake8 * resolve flake8 * resolve flake8 Co-authored-by: Ubuntu <ubuntu@ip-172-31-88-60.ec2.internal> * fix tests/accelerator tests on cpu * [BugFix] Resolve manual optimization (#5852) * resolve manual_optimization * update * update Co-authored-by: Ubuntu <ubuntu@ip-172-31-88-60.ec2.internal> * Remove copy trainer parameters to happen earlier within the loop and add safe guard to get ref model (#5856) * resovle a bug * Accelerator refactor sharded rpc (#5854) * rpc branch * merge * update handling of rpc * make devices etc. Optional in RPC * set devices etc. later if necessary * remove devices from sequential * make devices optional in rpc * fix import * uncomment everything * fix cluster selection Co-authored-by: Ubuntu <ubuntu@ip-172-31-88-60.ec2.internal> * resolve bug * fix assert in rpc test * resolve a test * fix docs compilation * accelerator refactor - fix for sharded parity test (#5866) * fix memory issue with ddp_spawn * x x x x x x x x x * x * Remove DDP2 as this does not apply * Add missing pre optimizer hook to ensure lambda closure is called * fix apex docstring * [accelerator][BugFix] Resolve some test for 1 gpu (#5863) * update * revert init * resolve a bug * update * resolve flake8 * update * update * update * revert init * resolve a bug * update * resolve flake8 * update * update * update * update * update * revert init * resolve a bug * update * resolve flake8 * update * update * update * revert init * update * resolve flake8 * update * update * update * update * update * all_gather * update * make plugins work, add misconfig for RPC * update * update * remove breaking test * resolve some tests * resolve flake8 * revert to ddp_spawn Co-authored-by: root <root@ip-172-31-88-60.ec2.internal> Co-authored-by: Ubuntu <ubuntu@ip-172-31-88-60.ec2.internal> Co-authored-by: Justus Schock <justus.schock@rwth-aachen.de> * yapf isort * resolve flake8 * fix apex doctests * fix apex doctests 2 * resolve docs * update drone * clean env * update * update * update * update * merge * Fix RPC related tests, clean out old API, update for new accelerator API [skip ci] (#5881) * Fix RPC related tests, clean out old API, update for new accelerator API * Move tests out of legacy folder, update paths and names * Update test_remove_1-4.py * Expose properties for tpu cores/gpus/num_gpus * Add root GPU property * Move properties to properties.py * move tests that were previously in drone * Fix root GPU property (#5908) * Move root GPU to property, remove horovod set as this is handled in horovod plugin, ensure we mock correctly to set GPU accelerator * Add missing tests back * fix best model path transfer when no checkpoint callback available * Fix setup hook order [wip] (#5858) * Call trainer setup hook before accelerator setup * Add test case * add new test * typo * fix callback order in test Co-authored-by: tchaton <thomas@grid.ai> Co-authored-by: Adrian Wälchli <aedu.waelchli@gmail.com> * rename ddp sequential -> rpc sequential for special test * revert * fix stupid merge problem * abstract the cluster plugins * default plugin * integrate default environment * fix property * adapt tests * adjust test * fix world size access * base cluster env * revert rebase errors * revert rebase errors * missing import * revert unrelated change * remove unused cluster local rank * remove unrelated changes * fix unrelated changes * fix pep8 * remove unused var * reset permissions * ypaf * test default environment * test torchelastic environment * world size as int * tests for slurm environment * changelog * test comments * remove unintended change * keep master port fixed after it is generated * test random master port * yapf * add missing default environment * move helper function * rename default environment * rename * rename * yapf * Update pytorch_lightning/plugins/environments/lightning_environment.py Co-authored-by: Carlos Mocholí <carlossmocholi@gmail.com> * Update CHANGELOG.md Co-authored-by: Justus Schock <12886177+justusschock@users.noreply.github.com> * spawn -> create Co-authored-by: justusschock <justus.schock@posteo.de> Co-authored-by: SeanNaren <sean@grid.ai> Co-authored-by: Justus Schock <12886177+justusschock@users.noreply.github.com> Co-authored-by: Jirka Borovec <jirka.borovec@seznam.cz> Co-authored-by: Justus Schock <justus.schock@rwth-aachen.de> Co-authored-by: chaton <thomas@grid.ai> Co-authored-by: Ubuntu <ubuntu@ip-172-31-88-60.ec2.internal> Co-authored-by: Sean Naren <sean.narenthiran@gmail.com> Co-authored-by: root <root@ip-172-31-88-60.ec2.internal> Co-authored-by: Carlos Mocholí <carlossmocholi@gmail.com>
2021-03-05 01:47:29 +00:00
# Copyright The PyTorch Lightning team.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
import os
import socket
from pytorch_lightning.plugins.environments.cluster_environment import ClusterEnvironment
from pytorch_lightning.utilities import rank_zero_only
introduce default cluster environment for lightning-specific ddp (#5915) * handle distributed_sampler_kwargs * move emptying cache to accelertor * fix a few tests * restoring the result from subprocess * fix queue.get() order for results * add missing "block_backward_sync" context manager * add missing "block_backward_sync" context manager * fix sync_batchnorm * fix supported gpu-ids for tuple * fix clip gradients and inf recursion * accelerator selection: added cluster_environment plugin * fix torchelastic test * fix reduce early stopping decision for DDP * fix tests: callbacks, conversion to lightning optimizer * fix lightning optimizer does not pickle * fix setting benchmark and deterministic option * fix slurm amp test * fix prepare_data test and determine node_rank * fix retrieving last path when testing * remove obsolete plugin argument * fix test: test_trainer_config * fix torchscript tests * fix trainer.model access * move properties * fix test_transfer_batch_hook * fix auto_select_gpus * fix omegaconf test * fix test that needs to simulate slurm ddp * add horovod plugin * fix test with named arguments * clean up whitespace * fix datamodules test * remove old accelerators * fix naming * move old plugins * move to plugins * create precision subpackage * create training_type subpackage * fix all new import errors * fix wrong arguments order passed to test * fix LR finder * Added sharded training type and amp plugin * Move clip grad to precision plugin * Added sharded spawn, select accelerators based on distributed_backend + enable custom fp16 plugin automatically * Fix import issue, attempting to fix tests * Fix initial test * Reflect hook logic from master, should wrap model after move to device * Optional state consolidation, since master has optimizers not wrapped * change attribute for instance test * reset optimizers optimizers are not used in main process, so state would be wrong. * legacy * imports in accel * legacy2 * trainer imports * fix import errors after rebase * move hook to new setup location * provide unwrapping logic * fix trainer callback system * added ddp2 implementation * fix imports .legacy * move plugins * restore legacy * drop test.py from root * add tpu accelerator and plugins * fixes * fix lightning optimizer merge * reset bugreportmodel * unwrapping * step routing forward * model access * unwrap * opt * integrate distrib_type * sync changes * sync * fixes * add forgotten generators * add missing logic * update * import * missed imports * import fixes * isort * mv f * changelog * format * move helper to parallel plugin * d * add world size * clean up * duplicate * activate ddp_sharded and tpu * set nvidia flags * remove unused colab var * use_tpu <-> on_tpu attrs * make some ddp_cpu and clusterplugin tests pass * Ref/accelerator connector (#5742) * final cleanup Co-authored-by: Adrian Wälchli <aedu.waelchli@gmail.com> * connector cleanup Co-authored-by: Adrian Wälchli <aedu.waelchli@gmail.com> * trainer cleanup Co-authored-by: Adrian Wälchli <aedu.waelchli@gmail.com> * accelerator cleanup + missing logic in accelerator connector Co-authored-by: Adrian Wälchli <aedu.waelchli@gmail.com> * add missing changes to callbacks Co-authored-by: Adrian Wälchli <aedu.waelchli@gmail.com> * reflect accelerator changes to lightning module Co-authored-by: Adrian Wälchli <aedu.waelchli@gmail.com> * clean cluster envs Co-authored-by: Adrian Wälchli <aedu.waelchli@gmail.com> * cleanup plugins Co-authored-by: Adrian Wälchli <aedu.waelchli@gmail.com> * add broadcasting Co-authored-by: Adrian Wälchli <aedu.waelchli@gmail.com> * yapf * remove plugin connector Co-authored-by: Adrian Wälchli <aedu.waelchli@gmail.com> * plugins * manual optimization * update optimizer routing * add rank to torchelastic * fix memory mixed precision * setstate on trainer for pickling in ddp spawn * add predict method * add back commented accelerator code * adapt test for sync_batch_norm to new plugin * fix deprecated tests * fix ddp cpu choice when no num_processes are given * yapf format * skip a memory test that cannot pass anymore * fix pickle error in spawn plugin * x * avoid * x * fix cyclic import in docs build * add support for sharded * update typing * add sharded and sharded_spawn to distributed types * make unwrap model default * refactor LightningShardedDataParallel similar to LightningDistributedDataParallel * update sharded spawn to reflect changes * update sharded to reflect changes * Merge 1.1.5 changes * fix merge * fix merge * yapf isort * fix merge * yapf isort * fix indentation in test * copy over reinit scheduler implementation from dev1.2 * fix apex tracking calls with dev_debugger * reduce diff to dev1.2, clean up * fix trainer config test when gpus>0 and num_processes >0 and ddp_cpu * sort plugin tests legacy/new * fix error handling for amp on cpu * fix merge fix merge fix merge * [Feat] Resolve manual_backward (#5837) * resolve manual_backward * resolve flake8 * update * resolve for ddp_spawn * resolve flake8 * resolve flake8 * resolve flake8 Co-authored-by: Ubuntu <ubuntu@ip-172-31-88-60.ec2.internal> * fix tests/accelerator tests on cpu * [BugFix] Resolve manual optimization (#5852) * resolve manual_optimization * update * update Co-authored-by: Ubuntu <ubuntu@ip-172-31-88-60.ec2.internal> * Remove copy trainer parameters to happen earlier within the loop and add safe guard to get ref model (#5856) * resovle a bug * Accelerator refactor sharded rpc (#5854) * rpc branch * merge * update handling of rpc * make devices etc. Optional in RPC * set devices etc. later if necessary * remove devices from sequential * make devices optional in rpc * fix import * uncomment everything * fix cluster selection Co-authored-by: Ubuntu <ubuntu@ip-172-31-88-60.ec2.internal> * resolve bug * fix assert in rpc test * resolve a test * fix docs compilation * accelerator refactor - fix for sharded parity test (#5866) * fix memory issue with ddp_spawn * x x x x x x x x x * x * Remove DDP2 as this does not apply * Add missing pre optimizer hook to ensure lambda closure is called * fix apex docstring * [accelerator][BugFix] Resolve some test for 1 gpu (#5863) * update * revert init * resolve a bug * update * resolve flake8 * update * update * update * revert init * resolve a bug * update * resolve flake8 * update * update * update * update * update * revert init * resolve a bug * update * resolve flake8 * update * update * update * revert init * update * resolve flake8 * update * update * update * update * update * all_gather * update * make plugins work, add misconfig for RPC * update * update * remove breaking test * resolve some tests * resolve flake8 * revert to ddp_spawn Co-authored-by: root <root@ip-172-31-88-60.ec2.internal> Co-authored-by: Ubuntu <ubuntu@ip-172-31-88-60.ec2.internal> Co-authored-by: Justus Schock <justus.schock@rwth-aachen.de> * yapf isort * resolve flake8 * fix apex doctests * fix apex doctests 2 * resolve docs * update drone * clean env * update * update * update * update * merge * Fix RPC related tests, clean out old API, update for new accelerator API [skip ci] (#5881) * Fix RPC related tests, clean out old API, update for new accelerator API * Move tests out of legacy folder, update paths and names * Update test_remove_1-4.py * Expose properties for tpu cores/gpus/num_gpus * Add root GPU property * Move properties to properties.py * move tests that were previously in drone * Fix root GPU property (#5908) * Move root GPU to property, remove horovod set as this is handled in horovod plugin, ensure we mock correctly to set GPU accelerator * Add missing tests back * fix best model path transfer when no checkpoint callback available * Fix setup hook order [wip] (#5858) * Call trainer setup hook before accelerator setup * Add test case * add new test * typo * fix callback order in test Co-authored-by: tchaton <thomas@grid.ai> Co-authored-by: Adrian Wälchli <aedu.waelchli@gmail.com> * rename ddp sequential -> rpc sequential for special test * revert * fix stupid merge problem * abstract the cluster plugins * default plugin * integrate default environment * fix property * adapt tests * adjust test * fix world size access * base cluster env * revert rebase errors * revert rebase errors * missing import * revert unrelated change * remove unused cluster local rank * remove unrelated changes * fix unrelated changes * fix pep8 * remove unused var * reset permissions * ypaf * test default environment * test torchelastic environment * world size as int * tests for slurm environment * changelog * test comments * remove unintended change * keep master port fixed after it is generated * test random master port * yapf * add missing default environment * move helper function * rename default environment * rename * rename * yapf * Update pytorch_lightning/plugins/environments/lightning_environment.py Co-authored-by: Carlos Mocholí <carlossmocholi@gmail.com> * Update CHANGELOG.md Co-authored-by: Justus Schock <12886177+justusschock@users.noreply.github.com> * spawn -> create Co-authored-by: justusschock <justus.schock@posteo.de> Co-authored-by: SeanNaren <sean@grid.ai> Co-authored-by: Justus Schock <12886177+justusschock@users.noreply.github.com> Co-authored-by: Jirka Borovec <jirka.borovec@seznam.cz> Co-authored-by: Justus Schock <justus.schock@rwth-aachen.de> Co-authored-by: chaton <thomas@grid.ai> Co-authored-by: Ubuntu <ubuntu@ip-172-31-88-60.ec2.internal> Co-authored-by: Sean Naren <sean.narenthiran@gmail.com> Co-authored-by: root <root@ip-172-31-88-60.ec2.internal> Co-authored-by: Carlos Mocholí <carlossmocholi@gmail.com>
2021-03-05 01:47:29 +00:00
class LightningEnvironment(ClusterEnvironment):
"""
The default environment used by Lightning for a single node or free cluster (not managed).
The master process must be launched by the user and Lightning will spawn new
worker processes for distributed training, either in a single node or across multiple nodes.
If the master address and port are not provided, the default environment will choose them
automatically. It is recommended to use this default environment for single-node distributed
training as it provides the most convenient way to launch the training script.
"""
def __init__(self):
super().__init__()
self._master_port = None
self._global_rank: int = 0
self._world_size: int = 1
introduce default cluster environment for lightning-specific ddp (#5915) * handle distributed_sampler_kwargs * move emptying cache to accelertor * fix a few tests * restoring the result from subprocess * fix queue.get() order for results * add missing "block_backward_sync" context manager * add missing "block_backward_sync" context manager * fix sync_batchnorm * fix supported gpu-ids for tuple * fix clip gradients and inf recursion * accelerator selection: added cluster_environment plugin * fix torchelastic test * fix reduce early stopping decision for DDP * fix tests: callbacks, conversion to lightning optimizer * fix lightning optimizer does not pickle * fix setting benchmark and deterministic option * fix slurm amp test * fix prepare_data test and determine node_rank * fix retrieving last path when testing * remove obsolete plugin argument * fix test: test_trainer_config * fix torchscript tests * fix trainer.model access * move properties * fix test_transfer_batch_hook * fix auto_select_gpus * fix omegaconf test * fix test that needs to simulate slurm ddp * add horovod plugin * fix test with named arguments * clean up whitespace * fix datamodules test * remove old accelerators * fix naming * move old plugins * move to plugins * create precision subpackage * create training_type subpackage * fix all new import errors * fix wrong arguments order passed to test * fix LR finder * Added sharded training type and amp plugin * Move clip grad to precision plugin * Added sharded spawn, select accelerators based on distributed_backend + enable custom fp16 plugin automatically * Fix import issue, attempting to fix tests * Fix initial test * Reflect hook logic from master, should wrap model after move to device * Optional state consolidation, since master has optimizers not wrapped * change attribute for instance test * reset optimizers optimizers are not used in main process, so state would be wrong. * legacy * imports in accel * legacy2 * trainer imports * fix import errors after rebase * move hook to new setup location * provide unwrapping logic * fix trainer callback system * added ddp2 implementation * fix imports .legacy * move plugins * restore legacy * drop test.py from root * add tpu accelerator and plugins * fixes * fix lightning optimizer merge * reset bugreportmodel * unwrapping * step routing forward * model access * unwrap * opt * integrate distrib_type * sync changes * sync * fixes * add forgotten generators * add missing logic * update * import * missed imports * import fixes * isort * mv f * changelog * format * move helper to parallel plugin * d * add world size * clean up * duplicate * activate ddp_sharded and tpu * set nvidia flags * remove unused colab var * use_tpu <-> on_tpu attrs * make some ddp_cpu and clusterplugin tests pass * Ref/accelerator connector (#5742) * final cleanup Co-authored-by: Adrian Wälchli <aedu.waelchli@gmail.com> * connector cleanup Co-authored-by: Adrian Wälchli <aedu.waelchli@gmail.com> * trainer cleanup Co-authored-by: Adrian Wälchli <aedu.waelchli@gmail.com> * accelerator cleanup + missing logic in accelerator connector Co-authored-by: Adrian Wälchli <aedu.waelchli@gmail.com> * add missing changes to callbacks Co-authored-by: Adrian Wälchli <aedu.waelchli@gmail.com> * reflect accelerator changes to lightning module Co-authored-by: Adrian Wälchli <aedu.waelchli@gmail.com> * clean cluster envs Co-authored-by: Adrian Wälchli <aedu.waelchli@gmail.com> * cleanup plugins Co-authored-by: Adrian Wälchli <aedu.waelchli@gmail.com> * add broadcasting Co-authored-by: Adrian Wälchli <aedu.waelchli@gmail.com> * yapf * remove plugin connector Co-authored-by: Adrian Wälchli <aedu.waelchli@gmail.com> * plugins * manual optimization * update optimizer routing * add rank to torchelastic * fix memory mixed precision * setstate on trainer for pickling in ddp spawn * add predict method * add back commented accelerator code * adapt test for sync_batch_norm to new plugin * fix deprecated tests * fix ddp cpu choice when no num_processes are given * yapf format * skip a memory test that cannot pass anymore * fix pickle error in spawn plugin * x * avoid * x * fix cyclic import in docs build * add support for sharded * update typing * add sharded and sharded_spawn to distributed types * make unwrap model default * refactor LightningShardedDataParallel similar to LightningDistributedDataParallel * update sharded spawn to reflect changes * update sharded to reflect changes * Merge 1.1.5 changes * fix merge * fix merge * yapf isort * fix merge * yapf isort * fix indentation in test * copy over reinit scheduler implementation from dev1.2 * fix apex tracking calls with dev_debugger * reduce diff to dev1.2, clean up * fix trainer config test when gpus>0 and num_processes >0 and ddp_cpu * sort plugin tests legacy/new * fix error handling for amp on cpu * fix merge fix merge fix merge * [Feat] Resolve manual_backward (#5837) * resolve manual_backward * resolve flake8 * update * resolve for ddp_spawn * resolve flake8 * resolve flake8 * resolve flake8 Co-authored-by: Ubuntu <ubuntu@ip-172-31-88-60.ec2.internal> * fix tests/accelerator tests on cpu * [BugFix] Resolve manual optimization (#5852) * resolve manual_optimization * update * update Co-authored-by: Ubuntu <ubuntu@ip-172-31-88-60.ec2.internal> * Remove copy trainer parameters to happen earlier within the loop and add safe guard to get ref model (#5856) * resovle a bug * Accelerator refactor sharded rpc (#5854) * rpc branch * merge * update handling of rpc * make devices etc. Optional in RPC * set devices etc. later if necessary * remove devices from sequential * make devices optional in rpc * fix import * uncomment everything * fix cluster selection Co-authored-by: Ubuntu <ubuntu@ip-172-31-88-60.ec2.internal> * resolve bug * fix assert in rpc test * resolve a test * fix docs compilation * accelerator refactor - fix for sharded parity test (#5866) * fix memory issue with ddp_spawn * x x x x x x x x x * x * Remove DDP2 as this does not apply * Add missing pre optimizer hook to ensure lambda closure is called * fix apex docstring * [accelerator][BugFix] Resolve some test for 1 gpu (#5863) * update * revert init * resolve a bug * update * resolve flake8 * update * update * update * revert init * resolve a bug * update * resolve flake8 * update * update * update * update * update * revert init * resolve a bug * update * resolve flake8 * update * update * update * revert init * update * resolve flake8 * update * update * update * update * update * all_gather * update * make plugins work, add misconfig for RPC * update * update * remove breaking test * resolve some tests * resolve flake8 * revert to ddp_spawn Co-authored-by: root <root@ip-172-31-88-60.ec2.internal> Co-authored-by: Ubuntu <ubuntu@ip-172-31-88-60.ec2.internal> Co-authored-by: Justus Schock <justus.schock@rwth-aachen.de> * yapf isort * resolve flake8 * fix apex doctests * fix apex doctests 2 * resolve docs * update drone * clean env * update * update * update * update * merge * Fix RPC related tests, clean out old API, update for new accelerator API [skip ci] (#5881) * Fix RPC related tests, clean out old API, update for new accelerator API * Move tests out of legacy folder, update paths and names * Update test_remove_1-4.py * Expose properties for tpu cores/gpus/num_gpus * Add root GPU property * Move properties to properties.py * move tests that were previously in drone * Fix root GPU property (#5908) * Move root GPU to property, remove horovod set as this is handled in horovod plugin, ensure we mock correctly to set GPU accelerator * Add missing tests back * fix best model path transfer when no checkpoint callback available * Fix setup hook order [wip] (#5858) * Call trainer setup hook before accelerator setup * Add test case * add new test * typo * fix callback order in test Co-authored-by: tchaton <thomas@grid.ai> Co-authored-by: Adrian Wälchli <aedu.waelchli@gmail.com> * rename ddp sequential -> rpc sequential for special test * revert * fix stupid merge problem * abstract the cluster plugins * default plugin * integrate default environment * fix property * adapt tests * adjust test * fix world size access * base cluster env * revert rebase errors * revert rebase errors * missing import * revert unrelated change * remove unused cluster local rank * remove unrelated changes * fix unrelated changes * fix pep8 * remove unused var * reset permissions * ypaf * test default environment * test torchelastic environment * world size as int * tests for slurm environment * changelog * test comments * remove unintended change * keep master port fixed after it is generated * test random master port * yapf * add missing default environment * move helper function * rename default environment * rename * rename * yapf * Update pytorch_lightning/plugins/environments/lightning_environment.py Co-authored-by: Carlos Mocholí <carlossmocholi@gmail.com> * Update CHANGELOG.md Co-authored-by: Justus Schock <12886177+justusschock@users.noreply.github.com> * spawn -> create Co-authored-by: justusschock <justus.schock@posteo.de> Co-authored-by: SeanNaren <sean@grid.ai> Co-authored-by: Justus Schock <12886177+justusschock@users.noreply.github.com> Co-authored-by: Jirka Borovec <jirka.borovec@seznam.cz> Co-authored-by: Justus Schock <justus.schock@rwth-aachen.de> Co-authored-by: chaton <thomas@grid.ai> Co-authored-by: Ubuntu <ubuntu@ip-172-31-88-60.ec2.internal> Co-authored-by: Sean Naren <sean.narenthiran@gmail.com> Co-authored-by: root <root@ip-172-31-88-60.ec2.internal> Co-authored-by: Carlos Mocholí <carlossmocholi@gmail.com>
2021-03-05 01:47:29 +00:00
def creates_children(self) -> bool:
return False
def master_address(self) -> str:
return os.environ.get("MASTER_ADDR", "127.0.0.1")
def master_port(self) -> int:
if self._master_port is None:
self._master_port = os.environ.get("MASTER_PORT", find_free_network_port())
return int(self._master_port)
def world_size(self) -> int:
return self._world_size
def set_world_size(self, size: int) -> None:
self._world_size = size
def global_rank(self) -> int:
return self._global_rank
def set_global_rank(self, rank: int) -> None:
self._global_rank = rank
rank_zero_only.rank = rank
introduce default cluster environment for lightning-specific ddp (#5915) * handle distributed_sampler_kwargs * move emptying cache to accelertor * fix a few tests * restoring the result from subprocess * fix queue.get() order for results * add missing "block_backward_sync" context manager * add missing "block_backward_sync" context manager * fix sync_batchnorm * fix supported gpu-ids for tuple * fix clip gradients and inf recursion * accelerator selection: added cluster_environment plugin * fix torchelastic test * fix reduce early stopping decision for DDP * fix tests: callbacks, conversion to lightning optimizer * fix lightning optimizer does not pickle * fix setting benchmark and deterministic option * fix slurm amp test * fix prepare_data test and determine node_rank * fix retrieving last path when testing * remove obsolete plugin argument * fix test: test_trainer_config * fix torchscript tests * fix trainer.model access * move properties * fix test_transfer_batch_hook * fix auto_select_gpus * fix omegaconf test * fix test that needs to simulate slurm ddp * add horovod plugin * fix test with named arguments * clean up whitespace * fix datamodules test * remove old accelerators * fix naming * move old plugins * move to plugins * create precision subpackage * create training_type subpackage * fix all new import errors * fix wrong arguments order passed to test * fix LR finder * Added sharded training type and amp plugin * Move clip grad to precision plugin * Added sharded spawn, select accelerators based on distributed_backend + enable custom fp16 plugin automatically * Fix import issue, attempting to fix tests * Fix initial test * Reflect hook logic from master, should wrap model after move to device * Optional state consolidation, since master has optimizers not wrapped * change attribute for instance test * reset optimizers optimizers are not used in main process, so state would be wrong. * legacy * imports in accel * legacy2 * trainer imports * fix import errors after rebase * move hook to new setup location * provide unwrapping logic * fix trainer callback system * added ddp2 implementation * fix imports .legacy * move plugins * restore legacy * drop test.py from root * add tpu accelerator and plugins * fixes * fix lightning optimizer merge * reset bugreportmodel * unwrapping * step routing forward * model access * unwrap * opt * integrate distrib_type * sync changes * sync * fixes * add forgotten generators * add missing logic * update * import * missed imports * import fixes * isort * mv f * changelog * format * move helper to parallel plugin * d * add world size * clean up * duplicate * activate ddp_sharded and tpu * set nvidia flags * remove unused colab var * use_tpu <-> on_tpu attrs * make some ddp_cpu and clusterplugin tests pass * Ref/accelerator connector (#5742) * final cleanup Co-authored-by: Adrian Wälchli <aedu.waelchli@gmail.com> * connector cleanup Co-authored-by: Adrian Wälchli <aedu.waelchli@gmail.com> * trainer cleanup Co-authored-by: Adrian Wälchli <aedu.waelchli@gmail.com> * accelerator cleanup + missing logic in accelerator connector Co-authored-by: Adrian Wälchli <aedu.waelchli@gmail.com> * add missing changes to callbacks Co-authored-by: Adrian Wälchli <aedu.waelchli@gmail.com> * reflect accelerator changes to lightning module Co-authored-by: Adrian Wälchli <aedu.waelchli@gmail.com> * clean cluster envs Co-authored-by: Adrian Wälchli <aedu.waelchli@gmail.com> * cleanup plugins Co-authored-by: Adrian Wälchli <aedu.waelchli@gmail.com> * add broadcasting Co-authored-by: Adrian Wälchli <aedu.waelchli@gmail.com> * yapf * remove plugin connector Co-authored-by: Adrian Wälchli <aedu.waelchli@gmail.com> * plugins * manual optimization * update optimizer routing * add rank to torchelastic * fix memory mixed precision * setstate on trainer for pickling in ddp spawn * add predict method * add back commented accelerator code * adapt test for sync_batch_norm to new plugin * fix deprecated tests * fix ddp cpu choice when no num_processes are given * yapf format * skip a memory test that cannot pass anymore * fix pickle error in spawn plugin * x * avoid * x * fix cyclic import in docs build * add support for sharded * update typing * add sharded and sharded_spawn to distributed types * make unwrap model default * refactor LightningShardedDataParallel similar to LightningDistributedDataParallel * update sharded spawn to reflect changes * update sharded to reflect changes * Merge 1.1.5 changes * fix merge * fix merge * yapf isort * fix merge * yapf isort * fix indentation in test * copy over reinit scheduler implementation from dev1.2 * fix apex tracking calls with dev_debugger * reduce diff to dev1.2, clean up * fix trainer config test when gpus>0 and num_processes >0 and ddp_cpu * sort plugin tests legacy/new * fix error handling for amp on cpu * fix merge fix merge fix merge * [Feat] Resolve manual_backward (#5837) * resolve manual_backward * resolve flake8 * update * resolve for ddp_spawn * resolve flake8 * resolve flake8 * resolve flake8 Co-authored-by: Ubuntu <ubuntu@ip-172-31-88-60.ec2.internal> * fix tests/accelerator tests on cpu * [BugFix] Resolve manual optimization (#5852) * resolve manual_optimization * update * update Co-authored-by: Ubuntu <ubuntu@ip-172-31-88-60.ec2.internal> * Remove copy trainer parameters to happen earlier within the loop and add safe guard to get ref model (#5856) * resovle a bug * Accelerator refactor sharded rpc (#5854) * rpc branch * merge * update handling of rpc * make devices etc. Optional in RPC * set devices etc. later if necessary * remove devices from sequential * make devices optional in rpc * fix import * uncomment everything * fix cluster selection Co-authored-by: Ubuntu <ubuntu@ip-172-31-88-60.ec2.internal> * resolve bug * fix assert in rpc test * resolve a test * fix docs compilation * accelerator refactor - fix for sharded parity test (#5866) * fix memory issue with ddp_spawn * x x x x x x x x x * x * Remove DDP2 as this does not apply * Add missing pre optimizer hook to ensure lambda closure is called * fix apex docstring * [accelerator][BugFix] Resolve some test for 1 gpu (#5863) * update * revert init * resolve a bug * update * resolve flake8 * update * update * update * revert init * resolve a bug * update * resolve flake8 * update * update * update * update * update * revert init * resolve a bug * update * resolve flake8 * update * update * update * revert init * update * resolve flake8 * update * update * update * update * update * all_gather * update * make plugins work, add misconfig for RPC * update * update * remove breaking test * resolve some tests * resolve flake8 * revert to ddp_spawn Co-authored-by: root <root@ip-172-31-88-60.ec2.internal> Co-authored-by: Ubuntu <ubuntu@ip-172-31-88-60.ec2.internal> Co-authored-by: Justus Schock <justus.schock@rwth-aachen.de> * yapf isort * resolve flake8 * fix apex doctests * fix apex doctests 2 * resolve docs * update drone * clean env * update * update * update * update * merge * Fix RPC related tests, clean out old API, update for new accelerator API [skip ci] (#5881) * Fix RPC related tests, clean out old API, update for new accelerator API * Move tests out of legacy folder, update paths and names * Update test_remove_1-4.py * Expose properties for tpu cores/gpus/num_gpus * Add root GPU property * Move properties to properties.py * move tests that were previously in drone * Fix root GPU property (#5908) * Move root GPU to property, remove horovod set as this is handled in horovod plugin, ensure we mock correctly to set GPU accelerator * Add missing tests back * fix best model path transfer when no checkpoint callback available * Fix setup hook order [wip] (#5858) * Call trainer setup hook before accelerator setup * Add test case * add new test * typo * fix callback order in test Co-authored-by: tchaton <thomas@grid.ai> Co-authored-by: Adrian Wälchli <aedu.waelchli@gmail.com> * rename ddp sequential -> rpc sequential for special test * revert * fix stupid merge problem * abstract the cluster plugins * default plugin * integrate default environment * fix property * adapt tests * adjust test * fix world size access * base cluster env * revert rebase errors * revert rebase errors * missing import * revert unrelated change * remove unused cluster local rank * remove unrelated changes * fix unrelated changes * fix pep8 * remove unused var * reset permissions * ypaf * test default environment * test torchelastic environment * world size as int * tests for slurm environment * changelog * test comments * remove unintended change * keep master port fixed after it is generated * test random master port * yapf * add missing default environment * move helper function * rename default environment * rename * rename * yapf * Update pytorch_lightning/plugins/environments/lightning_environment.py Co-authored-by: Carlos Mocholí <carlossmocholi@gmail.com> * Update CHANGELOG.md Co-authored-by: Justus Schock <12886177+justusschock@users.noreply.github.com> * spawn -> create Co-authored-by: justusschock <justus.schock@posteo.de> Co-authored-by: SeanNaren <sean@grid.ai> Co-authored-by: Justus Schock <12886177+justusschock@users.noreply.github.com> Co-authored-by: Jirka Borovec <jirka.borovec@seznam.cz> Co-authored-by: Justus Schock <justus.schock@rwth-aachen.de> Co-authored-by: chaton <thomas@grid.ai> Co-authored-by: Ubuntu <ubuntu@ip-172-31-88-60.ec2.internal> Co-authored-by: Sean Naren <sean.narenthiran@gmail.com> Co-authored-by: root <root@ip-172-31-88-60.ec2.internal> Co-authored-by: Carlos Mocholí <carlossmocholi@gmail.com>
2021-03-05 01:47:29 +00:00
def local_rank(self) -> int:
return int(os.environ.get("LOCAL_RANK", 0))
def node_rank(self) -> int:
group_rank = os.environ.get("GROUP_RANK", 0)
return int(os.environ.get("NODE_RANK", group_rank))
def find_free_network_port() -> int:
"""
Finds a free port on localhost.
It is useful in single-node training when we don't want to connect to a real master node but
have to set the `MASTER_PORT` environment variable.
"""
s = socket.socket(socket.AF_INET, socket.SOCK_STREAM)
s.bind(("", 0))
s.listen(1)
port = s.getsockname()[1]
s.close()
return port