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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 unittest
from diffusers import AutoencoderKLLTX2Audio
from ...testing_utils import (
floats_tensor,
torch_device,
)
from ..test_modeling_common import ModelTesterMixin
from .testing_utils import AutoencoderTesterMixin
class AutoencoderKLLTX2AudioTests(ModelTesterMixin, AutoencoderTesterMixin, unittest.TestCase):
model_class = AutoencoderKLLTX2Audio
main_input_name = "sample"
base_precision = 1e-2
def get_autoencoder_kl_ltx_video_config(self):
return {
"in_channels": 2, # stereo,
"output_channels": 2,
"latent_channels": 4,
"base_channels": 16,
"ch_mult": (1, 2, 4),
"resolution": 16,
"attn_resolutions": None,
"num_res_blocks": 2,
"norm_type": "pixel",
"causality_axis": "height",
"mid_block_add_attention": False,
"sample_rate": 16000,
"mel_hop_length": 160,
"mel_bins": 16,
"is_causal": True,
"double_z": True,
}
@property
def dummy_input(self):
batch_size = 2
num_channels = 2
num_frames = 8
num_mel_bins = 16
spectrogram = floats_tensor((batch_size, num_channels, num_frames, num_mel_bins)).to(torch_device)
input_dict = {"sample": spectrogram}
return input_dict
@property
def input_shape(self):
return (2, 5, 16)
@property
def output_shape(self):
return (2, 5, 16)
def prepare_init_args_and_inputs_for_common(self):
init_dict = self.get_autoencoder_kl_ltx_video_config()
inputs_dict = self.dummy_input
return init_dict, inputs_dict
# Overriding as output shape is not the same as input shape for LTX 2.0 audio VAE
def test_output(self):
super().test_output(expected_output_shape=(2, 2, 5, 16))
@unittest.skip("Unsupported test.")
def test_outputs_equivalence(self):
pass
@unittest.skip("AutoencoderKLLTX2Audio does not support `norm_num_groups` because it does not use GroupNorm.")
def test_forward_with_norm_groups(self):
pass
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