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Update tests, need handling for radamw with older PyTorch, need to back-off basic test LR in mars?

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Ross Wightman 2024-11-26 12:13:21 -08:00 committed by Ross Wightman
parent 09bc21774e
commit 73d10ab482
1 changed files with 34 additions and 21 deletions
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25
tests/test_optim.py
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@ -9,6 +9,7 @@ import functools
from copy import deepcopy from copy import deepcopy
import torch import torch
from IPython.testing.decorators import skip_win32
from torch.testing._internal.common_utils import TestCase from torch.testing._internal.common_utils import TestCase
from torch.nn import Parameter from torch.nn import Parameter
@ -299,27 +300,39 @@ def test_optim_factory(optimizer):
opt_info = get_optimizer_info(optimizer) opt_info = get_optimizer_info(optimizer)
assert isinstance(opt_info, OptimInfo) assert isinstance(opt_info, OptimInfo)
lr = (1e-3, 1e-2, 1e-2, 1e-2)
if optimizer in ('mars',):
lr = (1e-3, 1e-3, 1e-3, 1e-3)
try:
if not opt_info.second_order: # basic tests don't support second order right now if not opt_info.second_order: # basic tests don't support second order right now
# test basic cases that don't need specific tuning via factory test # test basic cases that don't need specific tuning via factory test
_test_basic_cases( _test_basic_cases(
lambda weight, bias: create_optimizer_v2([weight, bias], optimizer, lr=1e-3) lambda weight, bias: create_optimizer_v2([weight, bias], optimizer, lr=lr[0])
) )
_test_basic_cases( _test_basic_cases(
lambda weight, bias: create_optimizer_v2( lambda weight, bias: create_optimizer_v2(
_build_params_dict(weight, bias, lr=1e-2), _build_params_dict(weight, bias, lr=lr[1]),
optimizer, optimizer,
lr=1e-3) lr=lr[1] / 10)
) )
_test_basic_cases( _test_basic_cases(
lambda weight, bias: create_optimizer_v2( lambda weight, bias: create_optimizer_v2(
_build_params_dict_single(weight, bias, lr=1e-2), _build_params_dict_single(weight, bias, lr=lr[2]),
optimizer, optimizer,
lr=1e-3) lr=lr[2] / 10)
) )
_test_basic_cases( _test_basic_cases(
lambda weight, bias: create_optimizer_v2( lambda weight, bias: create_optimizer_v2(
_build_params_dict_single(weight, bias, lr=1e-2), optimizer) _build_params_dict_single(weight, bias, lr=lr[3]),
optimizer)
) )
except TypeError as e:
if 'radamw' in optimizer:
pytest.skip("Expected for 'radamw' (decoupled decay) to fail in older PyTorch versions.")
else:
raise e
#@pytest.mark.parametrize('optimizer', ['sgd', 'momentum']) #@pytest.mark.parametrize('optimizer', ['sgd', 'momentum'])