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# Copyright 2025 HuggingFace Inc.
#
# 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.
import pytest
import torch
from diffusers import AutoencoderKLWan
from diffusers.utils.torch_utils import randn_tensor
from ...testing_utils import enable_full_determinism, torch_device
from ..testing_utils import BaseModelTesterConfig, MemoryTesterMixin, ModelTesterMixin, TrainingTesterMixin
from .testing_utils import NewAutoencoderTesterMixin
enable_full_determinism()
class AutoencoderKLWanTesterConfig(BaseModelTesterConfig):
@property
def model_class(self):
return AutoencoderKLWan
@property
def output_shape(self):
return (3, 9, 16, 16)
@property
def generator(self):
return torch.Generator("cpu").manual_seed(0)
def get_init_dict(self):
return {
"base_dim": 3,
"z_dim": 16,
"dim_mult": [1, 1, 1, 1],
"num_res_blocks": 1,
"temperal_downsample": [False, True, True],
}
def get_dummy_inputs(self):
batch_size = 2
num_frames = 9
num_channels = 3
sizes = (16, 16)
image = randn_tensor(
(batch_size, num_channels, num_frames, *sizes), generator=self.generator, device=torch_device
)
return {"sample": image}
class TestAutoencoderKLWan(AutoencoderKLWanTesterConfig, ModelTesterMixin):
base_precision = 1e-2
class TestAutoencoderKLWanTraining(AutoencoderKLWanTesterConfig, TrainingTesterMixin):
"""Training tests for AutoencoderKLWan."""
@pytest.mark.skip(reason="Gradient checkpointing has not been implemented yet")
def test_gradient_checkpointing_is_applied(self):
pass
class TestAutoencoderKLWanMemory(AutoencoderKLWanTesterConfig, MemoryTesterMixin):
"""Memory optimization tests for AutoencoderKLWan."""
@pytest.mark.skip(reason="RuntimeError: fill_out not implemented for 'Float8_e4m3fn'")
def test_layerwise_casting_memory(self):
pass
@pytest.mark.skip(reason="RuntimeError: fill_out not implemented for 'Float8_e4m3fn'")
def test_layerwise_casting_training(self):
pass
class TestAutoencoderKLWanSlicingTiling(AutoencoderKLWanTesterConfig, NewAutoencoderTesterMixin):
"""Slicing and tiling tests for AutoencoderKLWan."""
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