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Make UNet2DConditionOutput pickle-able #3857

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merged 6 commits into from
Jul 6, 2023
Merged

Make UNet2DConditionOutput pickle-able #3857

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4cb27b0
add default to unet output to prevent it from being a required arg
Jun 22, 2023
508b199
add unit test
Jun 28, 2023
61595ef
make style
Jun 28, 2023
5046788
adjust unit test
Jun 28, 2023
d7a5656
mark as fast test
Jul 5, 2023
684b080
adjust assert statement in test
Jul 5, 2023
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2 changes: 1 addition & 1 deletion src/diffusers/models/unet_2d_condition.py
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Original file line number Diff line number Diff line change
Expand Up @@ -55,7 +55,7 @@ class UNet2DConditionOutput(BaseOutput):
Hidden states conditioned on `encoder_hidden_states` input. Output of last layer of model.
"""

sample: torch.FloatTensor
sample: torch.FloatTensor = None


class UNet2DConditionModel(ModelMixin, ConfigMixin, UNet2DConditionLoadersMixin):
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17 changes: 17 additions & 0 deletions tests/models/test_models_unet_2d_condition.py
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Expand Up @@ -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 tempfile
Expand Down Expand Up @@ -782,6 +783,22 @@ def test_custom_diffusion_xformers_on_off(self):
assert (sample - on_sample).abs().max() < 1e-4
assert (sample - off_sample).abs().max() < 1e-4

def test_pickle(self):
# enable deterministic behavior for gradient checkpointing
init_dict, inputs_dict = self.prepare_init_args_and_inputs_for_common()

init_dict["attention_head_dim"] = (8, 16)

model = self.model_class(**init_dict)
model.to(torch_device)

with torch.no_grad():
sample = model(**inputs_dict).sample

sample_copy = copy.copy(sample)

assert (sample - sample_copy).abs().max() < 1e-4


@slow
class UNet2DConditionModelIntegrationTests(unittest.TestCase):
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