179 lines
6.6 KiB
Python
179 lines
6.6 KiB
Python
import inspect
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import pickle
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import sys
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from argparse import ArgumentParser, Namespace
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from unittest import mock
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import pytest
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import torch
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import tests.base.develop_utils as tutils
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from pytorch_lightning import Trainer
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from pytorch_lightning.utilities import argparse_utils
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@mock.patch('argparse.ArgumentParser.parse_args')
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def test_default_args(mock_argparse, tmpdir):
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"""Tests default argument parser for Trainer"""
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mock_argparse.return_value = Namespace(**Trainer.default_attributes())
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# logger file to get meta
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logger = tutils.get_default_logger(tmpdir)
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parser = ArgumentParser(add_help=False)
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args = parser.parse_args()
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args.logger = logger
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args.max_epochs = 5
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trainer = Trainer.from_argparse_args(args)
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assert isinstance(trainer, Trainer)
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assert trainer.max_epochs == 5
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@pytest.mark.parametrize('cli_args', [
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['--accumulate_grad_batches=22'],
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['--weights_save_path=./'],
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[]
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])
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def test_add_argparse_args_redefined(cli_args):
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"""Redefines some default Trainer arguments via the cli and
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tests the Trainer initialization correctness.
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"""
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parser = ArgumentParser(add_help=False)
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parser = Trainer.add_argparse_args(parent_parser=parser)
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args = parser.parse_args(cli_args)
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# make sure we can pickle args
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pickle.dumps(args)
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# Check few deprecated args are not in namespace:
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for depr_name in ('gradient_clip', 'nb_gpu_nodes', 'max_nb_epochs'):
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assert depr_name not in args
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trainer = Trainer.from_argparse_args(args=args)
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pickle.dumps(trainer)
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assert isinstance(trainer, Trainer)
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def test_get_init_arguments_and_types():
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"""Asserts a correctness of the `get_init_arguments_and_types` Trainer classmethod."""
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args = argparse_utils.get_init_arguments_and_types(Trainer)
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parameters = inspect.signature(Trainer).parameters
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assert len(parameters) == len(args)
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for arg in args:
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assert parameters[arg[0]].default == arg[2]
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kwargs = {arg[0]: arg[2] for arg in args}
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trainer = Trainer(**kwargs)
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assert isinstance(trainer, Trainer)
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@pytest.mark.parametrize('cli_args', [
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['--callbacks=1', '--logger'],
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['--foo', '--bar=1']
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])
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def test_add_argparse_args_redefined_error(cli_args, monkeypatch):
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"""Asserts thar an error raised in case of passing not default cli arguments."""
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class _UnkArgError(Exception):
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pass
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def _raise():
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raise _UnkArgError
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parser = ArgumentParser(add_help=False)
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parser = Trainer.add_argparse_args(parent_parser=parser)
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monkeypatch.setattr(parser, 'exit', lambda *args: _raise(), raising=True)
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with pytest.raises(_UnkArgError):
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parser.parse_args(cli_args)
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@pytest.mark.parametrize(['cli_args', 'expected'], [
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pytest.param('--auto_lr_find --auto_scale_batch_size power',
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{'auto_lr_find': True, 'auto_scale_batch_size': 'power', 'early_stop_callback': False}),
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pytest.param('--auto_lr_find any_string --auto_scale_batch_size',
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{'auto_lr_find': 'any_string', 'auto_scale_batch_size': True}),
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pytest.param('--auto_lr_find TRUE --auto_scale_batch_size FALSE',
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{'auto_lr_find': True, 'auto_scale_batch_size': False}),
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pytest.param('--auto_lr_find t --auto_scale_batch_size ON',
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{'auto_lr_find': True, 'auto_scale_batch_size': True}),
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pytest.param('--auto_lr_find 0 --auto_scale_batch_size n',
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{'auto_lr_find': False, 'auto_scale_batch_size': False}),
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pytest.param('--early_stop_callback',
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{'auto_lr_find': False, 'early_stop_callback': True, 'auto_scale_batch_size': False}),
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pytest.param('--tpu_cores=8',
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{'tpu_cores': 8}),
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pytest.param("--tpu_cores=1,",
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{'tpu_cores': '1,'}),
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pytest.param(
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"",
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{
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# These parameters are marked as Optional[...] in Trainer.__init__, with None as default.
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# They should not be changed by the argparse interface.
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"min_steps": None,
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"max_steps": None,
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"log_gpu_memory": None,
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"distributed_backend": None,
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"weights_save_path": None,
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"truncated_bptt_steps": None,
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"resume_from_checkpoint": None,
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"profiler": None,
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}),
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])
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def test_argparse_args_parsing(cli_args, expected):
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"""Test multi type argument with bool."""
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cli_args = cli_args.split(' ') if cli_args else []
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with mock.patch("argparse._sys.argv", ["any.py"] + cli_args):
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parser = ArgumentParser(add_help=False)
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parser = Trainer.add_argparse_args(parent_parser=parser)
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args = Trainer.parse_argparser(parser)
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for k, v in expected.items():
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assert getattr(args, k) == v
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assert Trainer.from_argparse_args(args)
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@pytest.mark.parametrize(['cli_args', 'expected_gpu'], [
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pytest.param('--gpus 1', [0]),
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pytest.param('--gpus 0,', [0]),
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])
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@pytest.mark.skipif(not torch.cuda.is_available(), reason="test requires GPU machine")
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def test_argparse_args_parsing_gpus(cli_args, expected_gpu):
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"""Test multi type argument with bool."""
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cli_args = cli_args.split(' ') if cli_args else []
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with mock.patch("argparse._sys.argv", ["any.py"] + cli_args):
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parser = ArgumentParser(add_help=False)
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parser = Trainer.add_argparse_args(parent_parser=parser)
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args = Trainer.parse_argparser(parser)
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trainer = Trainer.from_argparse_args(args)
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assert trainer.data_parallel_device_ids == expected_gpu
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@pytest.mark.skipif(sys.version_info < (3, 7),
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reason="signature inspection while mocking is not working in Python < 3.7 despite autospec")
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@pytest.mark.parametrize(['cli_args', 'extra_args'], [
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pytest.param({}, {}),
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pytest.param({'logger': False}, {}),
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pytest.param({'logger': False}, {'logger': True}),
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pytest.param({'logger': False}, {'checkpoint_callback': True}),
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])
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def test_init_from_argparse_args(cli_args, extra_args):
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unknown_args = dict(unknown_arg=0)
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# unkown args in the argparser/namespace should be ignored
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with mock.patch('pytorch_lightning.Trainer.__init__', autospec=True, return_value=None) as init:
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trainer = Trainer.from_argparse_args(Namespace(**cli_args, **unknown_args), **extra_args)
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expected = dict(cli_args)
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expected.update(extra_args) # extra args should override any cli arg
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init.assert_called_with(trainer, **expected)
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# passing in unknown manual args should throw an error
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with pytest.raises(TypeError, match=r"__init__\(\) got an unexpected keyword argument 'unknown_arg'"):
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Trainer.from_argparse_args(Namespace(**cli_args), **extra_args, **unknown_args)
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