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| | 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, |
| | "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 |
| |
|
| | |
| | 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 |
| |
|