add single file to pipelines

src/diffusers/loaders/single_file_utils.py

@@ -2212,10 +2212,9 @@ def swap_scale_shift(weight):
 
 
 def convert_ltx_transformer_checkpoint_to_diffusers(checkpoint, **kwargs):
-    converted_state_dict = {key: checkpoint.pop(key) for key in list(checkpoint.keys())}
-
-    def remove_keys_(key: str, state_dict):
-        state_dict.pop(key)
+    converted_state_dict = {
+        key: checkpoint.pop(key) for key in list(checkpoint.keys()) if "model.diffusion_model." in key
+    }
 
     TRANSFORMER_KEYS_RENAME_DICT = {
         "model.diffusion_model.": "",
@@ -2225,9 +2224,7 @@ def remove_keys_(key: str, state_dict):
         "k_norm": "norm_k",
     }
 
-    TRANSFORMER_SPECIAL_KEYS_REMAP = {
-        "vae": remove_keys_,
-    }
+    TRANSFORMER_SPECIAL_KEYS_REMAP = {}
 
     for key in list(converted_state_dict.keys()):
         new_key = key
@@ -2245,7 +2242,7 @@ def remove_keys_(key: str, state_dict):
 
 
 def convert_ltx_vae_checkpoint_to_diffusers(checkpoint, **kwargs):
-    converted_state_dict = {key: checkpoint.pop(key) for key in list(checkpoint.keys())}
+    converted_state_dict = {key: checkpoint.pop(key) for key in list(checkpoint.keys()) if "vae." in key}
 
     def remove_keys_(key: str, state_dict):
         state_dict.pop(key)
@@ -2287,7 +2284,6 @@ def remove_keys_(key: str, state_dict):
         "per_channel_statistics.channel": remove_keys_,
         "per_channel_statistics.mean-of-means": remove_keys_,
         "per_channel_statistics.mean-of-stds": remove_keys_,
-        "model.diffusion_model": remove_keys_,
     }
 
     for key in list(converted_state_dict.keys()):

src/diffusers/pipelines/ltx/pipeline_ltx.py

@@ -20,6 +20,7 @@
 from transformers import T5EncoderModel, T5TokenizerFast
 
 from ...callbacks import MultiPipelineCallbacks, PipelineCallback
+from ...loaders import FromSingleFileMixin
 from ...models.autoencoders import AutoencoderKLLTX
 from ...models.transformers import LTXTransformer3DModel
 from ...schedulers import FlowMatchEulerDiscreteScheduler
@@ -139,7 +140,7 @@ def retrieve_timesteps(
     return timesteps, num_inference_steps
 
 
-class LTXPipeline(DiffusionPipeline):
+class LTXPipeline(DiffusionPipeline, FromSingleFileMixin):
     r"""
     Pipeline for text-to-video generation.
 

src/diffusers/pipelines/ltx/pipeline_ltx_image2video.py

@@ -21,6 +21,7 @@
 
 from ...callbacks import MultiPipelineCallbacks, PipelineCallback
 from ...image_processor import PipelineImageInput
+from ...loaders import FromSingleFileMixin
 from ...models.autoencoders import AutoencoderKLLTX
 from ...models.transformers import LTXTransformer3DModel
 from ...schedulers import FlowMatchEulerDiscreteScheduler
@@ -158,7 +159,7 @@ def retrieve_latents(
         raise AttributeError("Could not access latents of provided encoder_output")
 
 
-class LTXImageToVideoPipeline(DiffusionPipeline):
+class LTXImageToVideoPipeline(DiffusionPipeline, FromSingleFileMixin):
     r"""
     Pipeline for image-to-video generation.