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import torch
from diffusers import AutoencoderKLLTXVideo, FlowMatchEulerDiscreteScheduler, LTXVideoTransformer3DModel
from transformers import AutoTokenizer, T5EncoderModel
from finetrainers.models.ltx_video import LTXVideoModelSpecification
class DummyLTXVideoModelSpecification(LTXVideoModelSpecification):
def __init__(self, **kwargs):
super().__init__(**kwargs)
def load_condition_models(self):
text_encoder = T5EncoderModel.from_pretrained(
"hf-internal-testing/tiny-random-t5", torch_dtype=self.text_encoder_dtype
)
tokenizer = AutoTokenizer.from_pretrained("hf-internal-testing/tiny-random-t5")
return {"text_encoder": text_encoder, "tokenizer": tokenizer}
def load_latent_models(self):
torch.manual_seed(0)
vae = AutoencoderKLLTXVideo(
in_channels=3,
out_channels=3,
latent_channels=8,
block_out_channels=(8, 8, 8, 8),
decoder_block_out_channels=(8, 8, 8, 8),
layers_per_block=(1, 1, 1, 1, 1),
decoder_layers_per_block=(1, 1, 1, 1, 1),
spatio_temporal_scaling=(True, True, False, False),
decoder_spatio_temporal_scaling=(True, True, False, False),
decoder_inject_noise=(False, False, False, False, False),
upsample_residual=(False, False, False, False),
upsample_factor=(1, 1, 1, 1),
timestep_conditioning=False,
patch_size=1,
patch_size_t=1,
encoder_causal=True,
decoder_causal=False,
)
# TODO(aryan): Upload dummy checkpoints to the Hub so that we don't have to do this.
# Doing so overrides things like _keep_in_fp32_modules
vae.to(self.vae_dtype)
self.vae_config = vae.config
return {"vae": vae}
def load_diffusion_models(self):
torch.manual_seed(0)
transformer = LTXVideoTransformer3DModel(
in_channels=8,
out_channels=8,
patch_size=1,
patch_size_t=1,
num_attention_heads=4,
attention_head_dim=8,
cross_attention_dim=32,
num_layers=1,
caption_channels=32,
)
# TODO(aryan): Upload dummy checkpoints to the Hub so that we don't have to do this.
# Doing so overrides things like _keep_in_fp32_modules
transformer.to(self.transformer_dtype)
scheduler = FlowMatchEulerDiscreteScheduler()
return {"transformer": transformer, "scheduler": scheduler}
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