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Enable cache support (FirstBlockCache) for Cosmos3 Omni #14154

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Enable cache support (FirstBlockCache) for Cosmos3 Omni #14154

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16 changes: 16 additions & 0 deletions src/diffusers/hooks/_helpers.py
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Original file line number Diff line number Diff line change
Expand Up @@ -27,6 +27,7 @@ class TransformerBlockMetadata:
return_hidden_states_index: int = None
return_encoder_hidden_states_index: int = None
hidden_states_argument_name: str = "hidden_states"
encoder_hidden_states_argument_name: str = "encoder_hidden_states"

_cls: Type = None
_cached_parameter_indices: dict[str, int] = None
Expand Down Expand Up @@ -174,6 +175,7 @@ def _register_transformer_blocks_metadata():
from ..models.transformers.cogvideox_transformer_3d import CogVideoXBlock
from ..models.transformers.transformer_bria import BriaTransformerBlock
from ..models.transformers.transformer_cogview4 import CogView4TransformerBlock
from ..models.transformers.transformer_cosmos3 import Cosmos3VLTextMoTDecoderLayer
from ..models.transformers.transformer_flux import FluxSingleTransformerBlock, FluxTransformerBlock
from ..models.transformers.transformer_hunyuan_video import (
HunyuanVideoSingleTransformerBlock,
Expand Down Expand Up @@ -230,6 +232,20 @@ def _register_transformer_blocks_metadata():
),
)

# Cosmos3 (Omni)
# MoT dual-stream decoder layer: forward(und_seq, gen_seq, rotary_emb) -> (und_seq, gen_seq).
# The gen stream carries the denoised tokens, so it is mapped to hidden_states for cache
# decisions; the und (text/understanding) stream is quasi-static across denoising steps.
TransformerBlockRegistry.register(
model_class=Cosmos3VLTextMoTDecoderLayer,
metadata=TransformerBlockMetadata(
return_hidden_states_index=1,
return_encoder_hidden_states_index=0,
hidden_states_argument_name="gen_seq",
encoder_hidden_states_argument_name="und_seq",
),
)

# Flux
TransformerBlockRegistry.register(
model_class=FluxTransformerBlock,
Expand Down
10 changes: 7 additions & 3 deletions src/diffusers/hooks/first_block_cache.py
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Original file line number Diff line number Diff line change
Expand Up @@ -76,7 +76,9 @@ def initialize_hook(self, module):
return module

def new_forward(self, module: torch.nn.Module, *args, **kwargs):
original_hidden_states = self._metadata._get_parameter_from_args_kwargs("hidden_states", args, kwargs)
original_hidden_states = self._metadata._get_parameter_from_args_kwargs(
self._metadata.hidden_states_argument_name, args, kwargs
)

output = self.fn_ref.original_forward(*args, **kwargs)
is_output_tuple = isinstance(output, tuple)
Expand Down Expand Up @@ -155,11 +157,13 @@ def initialize_hook(self, module):
return module

def new_forward(self, module: torch.nn.Module, *args, **kwargs):
original_hidden_states = self._metadata._get_parameter_from_args_kwargs("hidden_states", args, kwargs)
original_hidden_states = self._metadata._get_parameter_from_args_kwargs(
self._metadata.hidden_states_argument_name, args, kwargs
)
original_encoder_hidden_states = None
if self._metadata.return_encoder_hidden_states_index is not None:
original_encoder_hidden_states = self._metadata._get_parameter_from_args_kwargs(
"encoder_hidden_states", args, kwargs
self._metadata.encoder_hidden_states_argument_name, args, kwargs
)

shared_state = self.state_manager.get_state()
Expand Down
3 changes: 2 additions & 1 deletion src/diffusers/models/transformers/transformer_cosmos3.py
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Original file line number Diff line number Diff line change
Expand Up @@ -21,6 +21,7 @@
from ...loaders import PeftAdapterMixin
from ..attention import AttentionMixin, AttentionModuleMixin
from ..attention_dispatch import dispatch_attention_fn
from ..cache_utils import CacheMixin
from ..embeddings import TimestepEmbedding, Timesteps
from ..modeling_utils import ModelMixin
from ..normalization import RMSNorm
Expand Down Expand Up @@ -294,7 +295,7 @@ def forward(
return residual_und + mlp_out_und, residual_gen + mlp_out_gen


class Cosmos3OmniTransformer(ModelMixin, ConfigMixin, PeftAdapterMixin, AttentionMixin):
class Cosmos3OmniTransformer(ModelMixin, ConfigMixin, PeftAdapterMixin, AttentionMixin, CacheMixin):
_supports_gradient_checkpointing = True
_no_split_modules = ["Cosmos3VLTextMoTDecoderLayer"]
_repeated_blocks = ["Cosmos3VLTextMoTDecoderLayer"]
Expand Down
106 changes: 54 additions & 52 deletions src/diffusers/pipelines/cosmos/pipeline_cosmos3_omni.py
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Original file line number Diff line number Diff line change
Expand Up @@ -1641,32 +1641,33 @@ def __call__(
)

# --- Conditional pass ---
preds_vision, preds_sound, preds_action = self.transformer(
input_ids=cond_packed_static["input_ids"],
text_indexes=cond_packed_static["text_indexes"],
position_ids=cond_packed_static["position_ids"],
und_len=cond_packed_static["und_len"],
sequence_length=cond_packed_static["sequence_length"],
vision_tokens=[vision_tokens],
vision_token_shapes=cond_packed_static["vision_token_shapes"],
vision_sequence_indexes=cond_packed_static["vision_sequence_indexes"],
vision_mse_loss_indexes=cond_packed_static["vision_mse_loss_indexes"],
vision_timesteps=vision_timesteps,
vision_noisy_frame_indexes=cond_packed_static["vision_noisy_frame_indexes"],
sound_tokens=[sound_tokens] if sound_tokens is not None else None,
sound_token_shapes=cond_packed_static.get("sound_token_shapes"),
sound_sequence_indexes=cond_packed_static.get("sound_sequence_indexes"),
sound_mse_loss_indexes=cond_packed_static.get("sound_mse_loss_indexes"),
sound_timesteps=sound_timesteps,
sound_noisy_frame_indexes=cond_packed_static.get("sound_noisy_frame_indexes"),
action_tokens=[action_tokens] if action_tokens is not None else None,
action_token_shapes=cond_packed_static.get("action_token_shapes"),
action_sequence_indexes=cond_packed_static.get("action_sequence_indexes"),
action_mse_loss_indexes=cond_packed_static.get("action_mse_loss_indexes"),
action_timesteps=action_timesteps,
action_noisy_frame_indexes=cond_packed_static.get("action_noisy_frame_indexes"),
action_domain_ids=[action_domain_id] if action_domain_id is not None else None,
)
with self.transformer.cache_context("cond"):
preds_vision, preds_sound, preds_action = self.transformer(
input_ids=cond_packed_static["input_ids"],
text_indexes=cond_packed_static["text_indexes"],
position_ids=cond_packed_static["position_ids"],
und_len=cond_packed_static["und_len"],
sequence_length=cond_packed_static["sequence_length"],
vision_tokens=[vision_tokens],
vision_token_shapes=cond_packed_static["vision_token_shapes"],
vision_sequence_indexes=cond_packed_static["vision_sequence_indexes"],
vision_mse_loss_indexes=cond_packed_static["vision_mse_loss_indexes"],
vision_timesteps=vision_timesteps,
vision_noisy_frame_indexes=cond_packed_static["vision_noisy_frame_indexes"],
sound_tokens=[sound_tokens] if sound_tokens is not None else None,
sound_token_shapes=cond_packed_static.get("sound_token_shapes"),
sound_sequence_indexes=cond_packed_static.get("sound_sequence_indexes"),
sound_mse_loss_indexes=cond_packed_static.get("sound_mse_loss_indexes"),
sound_timesteps=sound_timesteps,
sound_noisy_frame_indexes=cond_packed_static.get("sound_noisy_frame_indexes"),
action_tokens=[action_tokens] if action_tokens is not None else None,
action_token_shapes=cond_packed_static.get("action_token_shapes"),
action_sequence_indexes=cond_packed_static.get("action_sequence_indexes"),
action_mse_loss_indexes=cond_packed_static.get("action_mse_loss_indexes"),
action_timesteps=action_timesteps,
action_noisy_frame_indexes=cond_packed_static.get("action_noisy_frame_indexes"),
action_domain_ids=[action_domain_id] if action_domain_id is not None else None,
)
cond_v_vision, cond_v_sound, cond_v_action = self._mask_velocity_predictions(
preds_vision,
preds_sound,
Expand All @@ -1680,32 +1681,33 @@ def __call__(
# --- Unconditional pass (Skip if not using CFG) ---
uncond_v_vision = uncond_v_sound = uncond_v_action = None
if self.do_classifier_free_guidance:
preds_vision, preds_sound, preds_action = self.transformer(
input_ids=uncond_packed_static["input_ids"],
text_indexes=uncond_packed_static["text_indexes"],
position_ids=uncond_packed_static["position_ids"],
und_len=uncond_packed_static["und_len"],
sequence_length=uncond_packed_static["sequence_length"],
vision_tokens=[vision_tokens],
vision_token_shapes=uncond_packed_static["vision_token_shapes"],
vision_sequence_indexes=uncond_packed_static["vision_sequence_indexes"],
vision_mse_loss_indexes=uncond_packed_static["vision_mse_loss_indexes"],
vision_timesteps=vision_timesteps,
vision_noisy_frame_indexes=uncond_packed_static["vision_noisy_frame_indexes"],
sound_tokens=[sound_tokens] if sound_tokens is not None else None,
sound_token_shapes=uncond_packed_static.get("sound_token_shapes"),
sound_sequence_indexes=uncond_packed_static.get("sound_sequence_indexes"),
sound_mse_loss_indexes=uncond_packed_static.get("sound_mse_loss_indexes"),
sound_timesteps=sound_timesteps,
sound_noisy_frame_indexes=uncond_packed_static.get("sound_noisy_frame_indexes"),
action_tokens=[action_tokens] if action_tokens is not None else None,
action_token_shapes=uncond_packed_static.get("action_token_shapes"),
action_sequence_indexes=uncond_packed_static.get("action_sequence_indexes"),
action_mse_loss_indexes=uncond_packed_static.get("action_mse_loss_indexes"),
action_timesteps=action_timesteps,
action_noisy_frame_indexes=uncond_packed_static.get("action_noisy_frame_indexes"),
action_domain_ids=[action_domain_id] if action_domain_id is not None else None,
)
with self.transformer.cache_context("uncond"):
preds_vision, preds_sound, preds_action = self.transformer(
input_ids=uncond_packed_static["input_ids"],
text_indexes=uncond_packed_static["text_indexes"],
position_ids=uncond_packed_static["position_ids"],
und_len=uncond_packed_static["und_len"],
sequence_length=uncond_packed_static["sequence_length"],
vision_tokens=[vision_tokens],
vision_token_shapes=uncond_packed_static["vision_token_shapes"],
vision_sequence_indexes=uncond_packed_static["vision_sequence_indexes"],
vision_mse_loss_indexes=uncond_packed_static["vision_mse_loss_indexes"],
vision_timesteps=vision_timesteps,
vision_noisy_frame_indexes=uncond_packed_static["vision_noisy_frame_indexes"],
sound_tokens=[sound_tokens] if sound_tokens is not None else None,
sound_token_shapes=uncond_packed_static.get("sound_token_shapes"),
sound_sequence_indexes=uncond_packed_static.get("sound_sequence_indexes"),
sound_mse_loss_indexes=uncond_packed_static.get("sound_mse_loss_indexes"),
sound_timesteps=sound_timesteps,
sound_noisy_frame_indexes=uncond_packed_static.get("sound_noisy_frame_indexes"),
action_tokens=[action_tokens] if action_tokens is not None else None,
action_token_shapes=uncond_packed_static.get("action_token_shapes"),
action_sequence_indexes=uncond_packed_static.get("action_sequence_indexes"),
action_mse_loss_indexes=uncond_packed_static.get("action_mse_loss_indexes"),
action_timesteps=action_timesteps,
action_noisy_frame_indexes=uncond_packed_static.get("action_noisy_frame_indexes"),
action_domain_ids=[action_domain_id] if action_domain_id is not None else None,
)
uncond_v_vision, uncond_v_sound, uncond_v_action = self._mask_velocity_predictions(
preds_vision,
preds_sound,
Expand Down
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