Add LTX-2.X IC LoRA and HDR Pipelines

src/diffusers/__init__.py

@@ -615,7 +615,9 @@
             "LongCatImageEditPipeline",
             "LongCatImagePipeline",
             "LTX2ConditionPipeline",
+            "LTX2HDRPipeline",
             "LTX2ImageToVideoPipeline",
+            "LTX2InContextPipeline",
             "LTX2LatentUpsamplePipeline",
             "LTX2Pipeline",
             "LTXConditionPipeline",
@@ -1407,7 +1409,9 @@
             LongCatImageEditPipeline,
             LongCatImagePipeline,
             LTX2ConditionPipeline,
+            LTX2HDRPipeline,
             LTX2ImageToVideoPipeline,
+            LTX2InContextPipeline,
             LTX2LatentUpsamplePipeline,
             LTX2Pipeline,
             LTXConditionPipeline,

src/diffusers/models/transformers/transformer_ltx2.py

@@ -1343,6 +1343,7 @@ def forward(
         perturbation_mask: torch.Tensor | None = None,
         use_cross_timestep: bool = False,
         attention_kwargs: dict[str, Any] | None = None,
+        video_self_attention_mask: torch.Tensor | None = None,
         return_dict: bool = True,
     ) -> torch.Tensor:
         """
@@ -1408,6 +1409,11 @@ def forward(
                 `False` is the legacy LTX-2.0 behavior.
             attention_kwargs (`dict[str, Any]`, *optional*):
                 Optional dict of keyword args to be passed to the attention processor.
+            video_self_attention_mask (`torch.Tensor`, *optional*):
+                Optional multiplicative self-attention mask of shape `(batch_size, num_video_tokens, num_video_tokens)`
+                applied to the video self-attention in each transformer block. Values in `[0, 1]` where `1` means full
+                attention and `0` means masked. Used e.g. by the IC-LoRA pipeline to control attention strength between
+                noisy tokens and appended reference tokens. Audio self-attention is not affected.
             return_dict (`bool`, *optional*, defaults to `True`):
                 Whether to return a dict-like structured output of type `AudioVisualModelOutput` or a tuple.
 
@@ -1430,6 +1436,11 @@ def forward(
             audio_encoder_attention_mask = (1 - audio_encoder_attention_mask.to(audio_hidden_states.dtype)) * -10000.0
             audio_encoder_attention_mask = audio_encoder_attention_mask.unsqueeze(1)
 
+        # Convert video_self_attention_mask from multiplicative mask ([0, 1]) to additive bias form (0 / -10000)
+        # matching the encoder_attention_mask convention above. Shape is preserved: (B, T_v, T_v).
+        if video_self_attention_mask is not None:
+            video_self_attention_mask = (1 - video_self_attention_mask.to(hidden_states.dtype)) * -10000.0
+
         batch_size = hidden_states.size(0)
 
         # 1. Prepare RoPE positional embeddings
@@ -1569,7 +1580,7 @@ def forward(
                     audio_cross_attn_rotary_emb,
                     encoder_attention_mask,
                     audio_encoder_attention_mask,
-                    None,  # self_attention_mask
+                    video_self_attention_mask,  # self_attention_mask (video-only)
                     None,  # audio_self_attention_mask
                     None,  # a2v_cross_attention_mask
                     None,  # v2a_cross_attention_mask
@@ -1598,7 +1609,7 @@ def forward(
                     ca_audio_rotary_emb=audio_cross_attn_rotary_emb,
                     encoder_attention_mask=encoder_attention_mask,
                     audio_encoder_attention_mask=audio_encoder_attention_mask,
-                    self_attention_mask=None,
+                    self_attention_mask=video_self_attention_mask,
                     audio_self_attention_mask=None,
                     a2v_cross_attention_mask=None,
                     v2a_cross_attention_mask=None,

src/diffusers/pipelines/__init__.py

@@ -330,6 +330,8 @@
     _import_structure["ltx2"] = [
         "LTX2Pipeline",
         "LTX2ConditionPipeline",
+        "LTX2HDRPipeline",
+        "LTX2InContextPipeline",
         "LTX2ImageToVideoPipeline",
         "LTX2LatentUpsamplePipeline",
     ]
@@ -780,7 +782,14 @@
             LTXLatentUpsamplePipeline,
             LTXPipeline,
         )
-        from .ltx2 import LTX2ConditionPipeline, LTX2ImageToVideoPipeline, LTX2LatentUpsamplePipeline, LTX2Pipeline
+        from .ltx2 import (
+            LTX2ConditionPipeline,
+            LTX2HDRPipeline,
+            LTX2ImageToVideoPipeline,
+            LTX2InContextPipeline,
+            LTX2LatentUpsamplePipeline,
+            LTX2Pipeline,
+        )
         from .lucy import LucyEditPipeline
         from .lumina import LuminaPipeline, LuminaText2ImgPipeline
         from .lumina2 import Lumina2Pipeline, Lumina2Text2ImgPipeline

src/diffusers/pipelines/ltx2/__init__.py

@@ -23,9 +23,12 @@
     _dummy_objects.update(get_objects_from_module(dummy_torch_and_transformers_objects))
 else:
     _import_structure["connectors"] = ["LTX2TextConnectors"]
+    _import_structure["image_processor"] = ["LTX2VideoHDRProcessor"]
     _import_structure["latent_upsampler"] = ["LTX2LatentUpsamplerModel"]
     _import_structure["pipeline_ltx2"] = ["LTX2Pipeline"]
     _import_structure["pipeline_ltx2_condition"] = ["LTX2ConditionPipeline"]
+    _import_structure["pipeline_ltx2_hdr_lora"] = ["LTX2HDRPipeline", "LTX2HDRReferenceCondition"]
+    _import_structure["pipeline_ltx2_ic_lora"] = ["LTX2InContextPipeline", "LTX2ReferenceCondition"]
     _import_structure["pipeline_ltx2_image2video"] = ["LTX2ImageToVideoPipeline"]
     _import_structure["pipeline_ltx2_latent_upsample"] = ["LTX2LatentUpsamplePipeline"]
     _import_structure["vocoder"] = ["LTX2Vocoder", "LTX2VocoderWithBWE"]
@@ -39,9 +42,12 @@
         from ...utils.dummy_torch_and_transformers_objects import *
     else:
         from .connectors import LTX2TextConnectors
+        from .image_processor import LTX2VideoHDRProcessor
         from .latent_upsampler import LTX2LatentUpsamplerModel
         from .pipeline_ltx2 import LTX2Pipeline
         from .pipeline_ltx2_condition import LTX2ConditionPipeline
+        from .pipeline_ltx2_hdr_lora import LTX2HDRPipeline, LTX2HDRReferenceCondition
+        from .pipeline_ltx2_ic_lora import LTX2InContextPipeline, LTX2ReferenceCondition
         from .pipeline_ltx2_image2video import LTX2ImageToVideoPipeline
         from .pipeline_ltx2_latent_upsample import LTX2LatentUpsamplePipeline
         from .vocoder import LTX2Vocoder, LTX2VocoderWithBWE