97 lines
3.1 KiB
Python
97 lines
3.1 KiB
Python
# 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.
|
|
|
|
from pytorch_lightning.utilities.parsing import lightning_getattr, lightning_hasattr, lightning_setattr
|
|
|
|
|
|
def _get_test_cases():
|
|
class TestHparamsNamespace:
|
|
learning_rate = 1
|
|
|
|
TestHparamsDict = {'learning_rate': 2}
|
|
|
|
class TestModel1: # test for namespace
|
|
learning_rate = 0
|
|
|
|
model1 = TestModel1()
|
|
|
|
class TestModel2: # test for hparams namespace
|
|
hparams = TestHparamsNamespace()
|
|
|
|
model2 = TestModel2()
|
|
|
|
class TestModel3: # test for hparams dict
|
|
hparams = TestHparamsDict
|
|
|
|
model3 = TestModel3()
|
|
|
|
class TestModel4: # fail case
|
|
batch_size = 1
|
|
|
|
model4 = TestModel4()
|
|
|
|
class DataModule:
|
|
batch_size = 8
|
|
|
|
class Trainer:
|
|
datamodule = DataModule
|
|
|
|
class TestModel5: # test for datamodule
|
|
trainer = Trainer
|
|
|
|
model5 = TestModel5()
|
|
|
|
return model1, model2, model3, model4, model5
|
|
|
|
|
|
def test_lightning_hasattr(tmpdir):
|
|
""" Test that the lightning_hasattr works in all cases"""
|
|
model1, model2, model3, model4, model5 = _get_test_cases()
|
|
assert lightning_hasattr(model1, 'learning_rate'), \
|
|
'lightning_hasattr failed to find namespace variable'
|
|
assert lightning_hasattr(model2, 'learning_rate'), \
|
|
'lightning_hasattr failed to find hparams namespace variable'
|
|
assert lightning_hasattr(model3, 'learning_rate'), \
|
|
'lightning_hasattr failed to find hparams dict variable'
|
|
assert not lightning_hasattr(model4, 'learning_rate'), \
|
|
'lightning_hasattr found variable when it should not'
|
|
assert lightning_hasattr(model5, 'batch_size'), \
|
|
'lightning_hasattr failed to find batch_size in datamodule'
|
|
|
|
|
|
def test_lightning_getattr(tmpdir):
|
|
""" Test that the lightning_getattr works in all cases"""
|
|
models = _get_test_cases()
|
|
for i, m in enumerate(models[:3]):
|
|
value = lightning_getattr(m, 'learning_rate')
|
|
assert value == i, 'attribute not correctly extracted'
|
|
|
|
model5 = models[4]
|
|
assert lightning_getattr(model5, 'batch_size') == 8, \
|
|
'batch_size not correctly extracted'
|
|
|
|
|
|
def test_lightning_setattr(tmpdir):
|
|
""" Test that the lightning_setattr works in all cases"""
|
|
models = _get_test_cases()
|
|
for m in models[:3]:
|
|
lightning_setattr(m, 'learning_rate', 10)
|
|
assert lightning_getattr(m, 'learning_rate') == 10, \
|
|
'attribute not correctly set'
|
|
|
|
model5 = models[4]
|
|
lightning_setattr(model5, 'batch_size', 128)
|
|
assert lightning_getattr(model5, 'batch_size') == 128, \
|
|
'batch_size not correctly set'
|