support ltx2 gradient_checkpointing

diffsynth/models/ltx2_dit.py

@@ -8,6 +8,7 @@ import torch
 from einops import rearrange
 from .ltx2_common import rms_norm, Modality
 from ..core.attention.attention import attention_forward
+from ..core import gradient_checkpoint_forward
 
 
 def get_timestep_embedding(
@@ -1352,28 +1353,21 @@ class LTXModel(torch.nn.Module):
         video: TransformerArgs | None,
         audio: TransformerArgs | None,
         perturbations: BatchedPerturbationConfig,
+        use_gradient_checkpointing: bool = False,
+        use_gradient_checkpointing_offload: bool = False,
     ) -> tuple[TransformerArgs, TransformerArgs]:
         """Process transformer blocks for LTXAV."""
 
         # Process transformer blocks
         for block in self.transformer_blocks:
-            if self._enable_gradient_checkpointing and self.training:
-                # Use gradient checkpointing to save memory during training.
-                # With use_reentrant=False, we can pass dataclasses directly -
-                # PyTorch will track all tensor leaves in the computation graph.
-                video, audio = torch.utils.checkpoint.checkpoint(
-                    block,
-                    video,
-                    audio,
-                    perturbations,
-                    use_reentrant=False,
-                )
-            else:
-                video, audio = block(
-                    video=video,
-                    audio=audio,
-                    perturbations=perturbations,
-                )
+            video, audio = gradient_checkpoint_forward(
+                block,
+                use_gradient_checkpointing,
+                use_gradient_checkpointing_offload,
+                video=video,
+                audio=audio,
+                perturbations=perturbations,
+            )
 
         return video, audio
 
@@ -1398,7 +1392,12 @@ class LTXModel(torch.nn.Module):
         return x
 
     def _forward(
-        self, video: Modality | None, audio: Modality | None, perturbations: BatchedPerturbationConfig
+        self,
+        video: Modality | None,
+        audio: Modality | None,
+        perturbations: BatchedPerturbationConfig,
+        use_gradient_checkpointing: bool = False,
+        use_gradient_checkpointing_offload: bool = False,
     ) -> tuple[torch.Tensor, torch.Tensor]:
         """
         Forward pass for LTX models.
@@ -1417,6 +1416,8 @@ class LTXModel(torch.nn.Module):
             video=video_args,
             audio=audio_args,
             perturbations=perturbations,
+            use_gradient_checkpointing=use_gradient_checkpointing,
+            use_gradient_checkpointing_offload=use_gradient_checkpointing_offload,
         )
 
         # Process output
@@ -1440,12 +1441,12 @@ class LTXModel(torch.nn.Module):
         )
         return vx, ax
 
-    def forward(self, video_latents, video_positions, video_context, video_timesteps, audio_latents, audio_positions, audio_context, audio_timesteps):
+    def forward(self, video_latents, video_positions, video_context, video_timesteps, audio_latents, audio_positions, audio_context, audio_timesteps, use_gradient_checkpointing=False, use_gradient_checkpointing_offload=False):
         cross_pe_max_pos = None
         if self.model_type.is_video_enabled() and self.model_type.is_audio_enabled():
             cross_pe_max_pos = max(self.positional_embedding_max_pos[0], self.audio_positional_embedding_max_pos[0])
         self._init_preprocessors(cross_pe_max_pos)
         video = Modality(video_latents, video_timesteps, video_positions, video_context)
         audio = Modality(audio_latents, audio_timesteps, audio_positions, audio_context) if audio_latents is not None else None
-        vx, ax = self._forward(video=video, audio=audio, perturbations=None)
+        vx, ax = self._forward(video=video, audio=audio, perturbations=None, use_gradient_checkpointing=use_gradient_checkpointing, use_gradient_checkpointing_offload=use_gradient_checkpointing_offload)
         return vx, ax

diffsynth/pipelines/ltx2_audio_video.py

@@ -577,6 +577,8 @@ def model_fn_ltx2(
         audio_positions=audio_positions,
         audio_context=audio_context,
         audio_timesteps=audio_timesteps,
+        use_gradient_checkpointing=use_gradient_checkpointing,
+        use_gradient_checkpointing_offload=use_gradient_checkpointing_offload,
     )
     # unpatchify
     vx = video_patchifier.unpatchify_video(vx, f, h, w)

diffsynth/utils/data/__init__.py

@@ -116,7 +116,7 @@ class VideoData:
         if self.height is not None and self.width is not None:
             return self.height, self.width
         else:
-            height, width, _ = self.__getitem__(0).shape
+            width, height = self.__getitem__(0).size
             return height, width
 
     def __getitem__(self, item):

examples/ltx2/model_training/full/LTX-2-T2AV-splited.sh

@@ -6,7 +6,7 @@ accelerate launch examples/ltx2/model_training/train.py \
   --extra_inputs "input_audio" \
   --height 512 \
   --width 768 \
-  --num_frames 49 \
+  --num_frames 121 \
   --dataset_repeat 1 \
   --model_id_with_origin_paths "DiffSynth-Studio/LTX-2-Repackage:text_encoder_post_modules.safetensors,DiffSynth-Studio/LTX-2-Repackage:video_vae_encoder.safetensors,DiffSynth-Studio/LTX-2-Repackage:audio_vae_encoder.safetensors,google/gemma-3-12b-it-qat-q4_0-unquantized:model-*.safetensors" \
   --learning_rate 1e-4 \
@@ -23,7 +23,7 @@ accelerate launch --config_file examples/qwen_image/model_training/full/accelera
   --extra_inputs "input_audio" \
   --height 512 \
   --width 768 \
-  --num_frames 49 \
+  --num_frames 121 \
   --dataset_repeat 100 \
   --model_id_with_origin_paths "DiffSynth-Studio/LTX-2-Repackage:transformer.safetensors" \
   --learning_rate 1e-4 \

examples/ltx2/model_training/lora/LTX-2-T2AV-noaudio.sh

@@ -24,7 +24,7 @@ accelerate launch examples/ltx2/model_training/train.py \
   --dataset_metadata_path data/example_video_dataset/ltx2_t2av.csv \
   --height 512 \
   --width 768 \
-  --num_frames 49\
+  --num_frames 121\
   --dataset_repeat 1 \
   --model_id_with_origin_paths "DiffSynth-Studio/LTX-2-Repackage:text_encoder_post_modules.safetensors,DiffSynth-Studio/LTX-2-Repackage:video_vae_encoder.safetensors,DiffSynth-Studio/LTX-2-Repackage:audio_vae_encoder.safetensors,google/gemma-3-12b-it-qat-q4_0-unquantized:model-*.safetensors" \
   --learning_rate 1e-4 \
@@ -42,7 +42,7 @@ accelerate launch examples/ltx2/model_training/train.py \
   --dataset_base_path ./models/train/LTX2-T2AV-noaudio_lora-splited-cache \
   --height 512 \
   --width 768 \
-  --num_frames 49\
+  --num_frames 121\
   --dataset_repeat 100 \
   --model_id_with_origin_paths "DiffSynth-Studio/LTX-2-Repackage:transformer.safetensors" \
   --learning_rate 1e-4 \

examples/ltx2/model_training/lora/LTX-2-T2AV-splited.sh

@@ -27,7 +27,7 @@ accelerate launch examples/ltx2/model_training/train.py \
   --extra_inputs "input_audio" \
   --height 512 \
   --width 768 \
-  --num_frames 49 \
+  --num_frames 121 \
   --dataset_repeat 1 \
   --model_id_with_origin_paths "DiffSynth-Studio/LTX-2-Repackage:text_encoder_post_modules.safetensors,DiffSynth-Studio/LTX-2-Repackage:video_vae_encoder.safetensors,DiffSynth-Studio/LTX-2-Repackage:audio_vae_encoder.safetensors,google/gemma-3-12b-it-qat-q4_0-unquantized:model-*.safetensors" \
   --learning_rate 1e-4 \
@@ -46,7 +46,7 @@ accelerate launch examples/ltx2/model_training/train.py \
   --extra_inputs "input_audio" \
   --height 512 \
   --width 768 \
-  --num_frames 49 \
+  --num_frames 121 \
   --dataset_repeat 100 \
   --model_id_with_origin_paths "DiffSynth-Studio/LTX-2-Repackage:transformer.safetensors" \
   --learning_rate 1e-4 \

examples/ltx2/model_training/train.py

@@ -118,10 +118,10 @@ if __name__ == "__main__":
             max_pixels=args.max_pixels,
             height=args.height,
             width=args.width,
-            height_division_factor=16,
-            width_division_factor=16,
+            height_division_factor=32,
+            width_division_factor=32,
             num_frames=args.num_frames,
-            time_division_factor=4,
+            time_division_factor=8,
             time_division_remainder=1,
         ),
         special_operator_map={

examples/ltx2/model_training/validate_full/LTX-2-T2AV.py

@@ -27,7 +27,7 @@ pipe = LTX2AudioVideoPipeline.from_pretrained(
 )
 prompt = "A beautiful sunset over the ocean."
 negative_prompt = "blurry, out of focus, overexposed, underexposed, low contrast, washed out colors, excessive noise, grainy texture, poor lighting, flickering, motion blur, distorted proportions, unnatural skin tones, deformed facial features, asymmetrical face, missing facial features, extra limbs, disfigured hands, wrong hand count, artifacts around text, inconsistent perspective, camera shake, incorrect depth of field, background too sharp, background clutter, distracting reflections, harsh shadows, inconsistent lighting direction, color banding, cartoonish rendering, 3D CGI look, unrealistic materials, uncanny valley effect, incorrect ethnicity, wrong gender, exaggerated expressions, wrong gaze direction, mismatched lip sync, silent or muted audio, distorted voice, robotic voice, echo, background noise, off-sync audio, incorrect dialogue, added dialogue, repetitive speech, jittery movement, awkward pauses, incorrect timing, unnatural transitions, inconsistent framing, tilted camera, flat lighting, inconsistent tone, cinematic oversaturation, stylized filters, or AI artifacts."
-height, width, num_frames = 512, 768, 49
+height, width, num_frames = 512, 768, 121
 video, audio = pipe(
     prompt=prompt,
     negative_prompt=negative_prompt,

examples/ltx2/model_training/validate_lora/LTX-2-T2AV.py

@@ -28,7 +28,7 @@ pipe = LTX2AudioVideoPipeline.from_pretrained(
 pipe.load_lora(pipe.dit, "models/train/LTX2-T2AV_lora/epoch-4.safetensors")
 prompt = "A beautiful sunset over the ocean."
 negative_prompt = "blurry, out of focus, overexposed, underexposed, low contrast, washed out colors, excessive noise, grainy texture, poor lighting, flickering, motion blur, distorted proportions, unnatural skin tones, deformed facial features, asymmetrical face, missing facial features, extra limbs, disfigured hands, wrong hand count, artifacts around text, inconsistent perspective, camera shake, incorrect depth of field, background too sharp, background clutter, distracting reflections, harsh shadows, inconsistent lighting direction, color banding, cartoonish rendering, 3D CGI look, unrealistic materials, uncanny valley effect, incorrect ethnicity, wrong gender, exaggerated expressions, wrong gaze direction, mismatched lip sync, silent or muted audio, distorted voice, robotic voice, echo, background noise, off-sync audio, incorrect dialogue, added dialogue, repetitive speech, jittery movement, awkward pauses, incorrect timing, unnatural transitions, inconsistent framing, tilted camera, flat lighting, inconsistent tone, cinematic oversaturation, stylized filters, or AI artifacts."
-height, width, num_frames = 512, 768, 49
+height, width, num_frames = 512, 768, 121
 video, audio = pipe(
     prompt=prompt,
     negative_prompt=negative_prompt,

examples/ltx2/model_training/validate_lora/LTX-2-T2AV_noaudio.py

@@ -28,7 +28,7 @@ pipe = LTX2AudioVideoPipeline.from_pretrained(
 pipe.load_lora(pipe.dit, "models/train/LTX2-T2AV-noaudio_lora/epoch-4.safetensors")
 prompt = "A beautiful sunset over the ocean."
 negative_prompt = "blurry, out of focus, overexposed, underexposed, low contrast, washed out colors, excessive noise, grainy texture, poor lighting, flickering, motion blur, distorted proportions, unnatural skin tones, deformed facial features, asymmetrical face, missing facial features, extra limbs, disfigured hands, wrong hand count, artifacts around text, inconsistent perspective, camera shake, incorrect depth of field, background too sharp, background clutter, distracting reflections, harsh shadows, inconsistent lighting direction, color banding, cartoonish rendering, 3D CGI look, unrealistic materials, uncanny valley effect, incorrect ethnicity, wrong gender, exaggerated expressions, wrong gaze direction, mismatched lip sync, silent or muted audio, distorted voice, robotic voice, echo, background noise, off-sync audio, incorrect dialogue, added dialogue, repetitive speech, jittery movement, awkward pauses, incorrect timing, unnatural transitions, inconsistent framing, tilted camera, flat lighting, inconsistent tone, cinematic oversaturation, stylized filters, or AI artifacts."
-height, width, num_frames = 512, 768, 49
+height, width, num_frames = 512, 768, 121
 video, audio = pipe(
     prompt=prompt,
     negative_prompt=negative_prompt,