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Add tearDown method to LoRA tests. (#6660)

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* update

* update
This commit is contained in:
Dhruv Nair
2024-01-22 14:00:37 +05:30
committed by GitHub
parent c7df846dec
commit d66d554dc2
2 changed files with 19 additions and 6 deletions
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6
tests/lora/test_lora_layers_old_backend.py
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@@ -13,6 +13,7 @@
# See the License for the specific language governing permissions and
# limitations under the License.
import copy
import gc
import os
import random
import tempfile
@@ -1662,6 +1663,11 @@ class UNet3DConditionLoRAModelTests(unittest.TestCase):
@deprecate_after_peft_backend
@require_torch_gpu
class LoraIntegrationTests(unittest.TestCase):
def tearDown(self):
super().tearDown()
gc.collect()
torch.cuda.empty_cache()
def test_dreambooth_old_format(self):
generator = torch.Generator("cpu").manual_seed(0)

19
tests/lora/test_lora_layers_peft.py
View File

@@ -13,6 +13,7 @@
# See the License for the specific language governing permissions and
# limitations under the License.
import copy
import gc
import importlib
import os
import tempfile
@@ -1205,6 +1206,11 @@ class StableDiffusionLoRATests(PeftLoraLoaderMixinTests, unittest.TestCase):
"latent_channels": 4,
}
def tearDown(self):
super().tearDown()
gc.collect()
torch.cuda.empty_cache()
@slow
@require_torch_gpu
def test_integration_move_lora_cpu(self):
@@ -1434,6 +1440,11 @@ class StableDiffusionXLLoRATests(PeftLoraLoaderMixinTests, unittest.TestCase):
"sample_size": 128,
}
def tearDown(self):
super().tearDown()
gc.collect()
torch.cuda.empty_cache()
@slow
@require_torch_gpu
@@ -1468,11 +1479,9 @@ class LoraIntegrationTests(PeftLoraLoaderMixinTests, unittest.TestCase):
}
def tearDown(self):
import gc
super().tearDown()
gc.collect()
torch.cuda.empty_cache()
gc.collect()
def test_dreambooth_old_format(self):
generator = torch.Generator("cpu").manual_seed(0)
@@ -1757,11 +1766,9 @@ class LoraSDXLIntegrationTests(PeftLoraLoaderMixinTests, unittest.TestCase):
}
def tearDown(self):
import gc
super().tearDown()
gc.collect()
torch.cuda.empty_cache()
gc.collect()
def test_sdxl_0_9_lora_one(self):
generator = torch.Generator().manual_seed(0)