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Release 2026-09-21 (i4 d30cb3b3) #268

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20 changes: 3 additions & 17 deletions .file_mapping.json
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Original file line number Diff line number Diff line change
@@ -1,7 +1,7 @@
{
"_source_commit": "4d9b6cfd3731fdbbca883184937d40a64d2dca52-dirty",
"_dest_commit": "c23e51f2f157ae3e51cfcd86ebfb5464850894f2",
"_generated_at": "2026-09-20T05:50:07Z",
"_source_commit": "d30cb3b32430c5241644a9c0eb54a4c89fb4d1b7-dirty",
"_dest_commit": "96303bb0bdd14d9efa18f24d8ef98c7a0bfb8412",
"_generated_at": "2026-09-21T05:52:31Z",
"files": {
"imaginaire/__init__.py": "cosmos_framework/__init__.py",
"imaginaire/attention/__init__.py": "cosmos_framework/model/attention/__init__.py",
Expand Down Expand Up @@ -292,20 +292,6 @@
"projects/cosmos3/cosmos3/datasets/augmentors/cropping.py": "cosmos_framework/data/generator/augmentors/cropping.py",
"projects/cosmos3/cosmos3/datasets/augmentors/duration_fps_text_timestamps.py": "cosmos_framework/data/generator/augmentors/duration_fps_text_timestamps.py",
"projects/cosmos3/cosmos3/datasets/augmentors/duration_fps_text_timestamps_test.py": "cosmos_framework/data/generator/augmentors/duration_fps_text_timestamps_test.py",
"projects/cosmos3/cosmos3/datasets/augmentors/hr_lr_degradation/__init__.py": "cosmos_framework/data/generator/augmentors/hr_lr_degradation/__init__.py",
"projects/cosmos3/cosmos3/datasets/augmentors/hr_lr_degradation/augmentor.py": "cosmos_framework/data/generator/augmentors/hr_lr_degradation/augmentor.py",
"projects/cosmos3/cosmos3/datasets/augmentors/hr_lr_degradation/augmentor_test.py": "cosmos_framework/data/generator/augmentors/hr_lr_degradation/augmentor_test.py",
"projects/cosmos3/cosmos3/datasets/augmentors/hr_lr_degradation/bench.py": "cosmos_framework/data/generator/augmentors/hr_lr_degradation/bench.py",
"projects/cosmos3/cosmos3/datasets/augmentors/hr_lr_degradation/codec.py": "cosmos_framework/data/generator/augmentors/hr_lr_degradation/codec.py",
"projects/cosmos3/cosmos3/datasets/augmentors/hr_lr_degradation/contact_sheet.py": "cosmos_framework/data/generator/augmentors/hr_lr_degradation/contact_sheet.py",
"projects/cosmos3/cosmos3/datasets/augmentors/hr_lr_degradation/contact_sheet_test.py": "cosmos_framework/data/generator/augmentors/hr_lr_degradation/contact_sheet_test.py",
"projects/cosmos3/cosmos3/datasets/augmentors/hr_lr_degradation/degrade.py": "cosmos_framework/data/generator/augmentors/hr_lr_degradation/degrade.py",
"projects/cosmos3/cosmos3/datasets/augmentors/hr_lr_degradation/degrade_test.py": "cosmos_framework/data/generator/augmentors/hr_lr_degradation/degrade_test.py",
"projects/cosmos3/cosmos3/datasets/augmentors/hr_lr_degradation/diffjpeg.py": "cosmos_framework/data/generator/augmentors/hr_lr_degradation/diffjpeg.py",
"projects/cosmos3/cosmos3/datasets/augmentors/hr_lr_degradation/kernels.py": "cosmos_framework/data/generator/augmentors/hr_lr_degradation/kernels.py",
"projects/cosmos3/cosmos3/datasets/augmentors/hr_lr_degradation/ops.py": "cosmos_framework/data/generator/augmentors/hr_lr_degradation/ops.py",
"projects/cosmos3/cosmos3/datasets/augmentors/hr_lr_degradation/packing_test.py": "cosmos_framework/data/generator/augmentors/hr_lr_degradation/packing_test.py",
"projects/cosmos3/cosmos3/datasets/augmentors/hr_lr_degradation/profiles.py": "cosmos_framework/data/generator/augmentors/hr_lr_degradation/profiles.py",
"projects/cosmos3/cosmos3/datasets/augmentors/idle_frames_text_info.py": "cosmos_framework/data/generator/augmentors/idle_frames_text_info.py",
"projects/cosmos3/cosmos3/datasets/augmentors/image_editing_transform.py": "cosmos_framework/data/generator/augmentors/image_editing_transform.py",
"projects/cosmos3/cosmos3/datasets/augmentors/image_editing_transform_test.py": "cosmos_framework/data/generator/augmentors/image_editing_transform_test.py",
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109 changes: 0 additions & 109 deletions cosmos_framework/data/generator/augmentor_provider.py
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Expand Up @@ -1543,112 +1543,3 @@ def _insert_before(augmentors: dict, anchor_keys: tuple[str, ...], new_key: str,
return _insert_relative(augmentors, anchor, new_key, new_value, after=False)


def _insert_low_res_stage(augmentors: dict, add_low_res) -> dict:
"""Place ``AddLowRes`` so the LR is derived from exactly the HR frame the model will see.

- Reflection-padding path (causal VAE): LR is made from the *unpadded* frame, before ``reflection_padding``;
``SRToTrainingFormat`` pads LR separately to half the HR bucket, so LR and HR stay aligned at the top-left.
- Crop path (non-causal / UniAE, ``crop_to_multiple``): LR is made *after* the centre crop. Making it before
would derive LR from pixels the HR no longer contains (spatial misalignment) and, when the crop changes the
size, a larger LR than the target that ``SRToTrainingFormat`` cannot pad down.
"""
if "reflection_padding" in augmentors:
return _insert_relative(augmentors, "reflection_padding", "add_low_res", add_low_res, after=False)
if "crop_to_multiple" in augmentors:
return _insert_relative(augmentors, "crop_to_multiple", "add_low_res", add_low_res, after=True)
raise KeyError("Pipeline has neither reflection_padding nor crop_to_multiple; cannot place add_low_res")


@augmentor_register("video_basic_augmentor_v3_json_caption_sr")
def get_video_augmentor_v3_json_caption_sr(
resolution: str,
sr_scale: float = 2.0,
sr_profiles: dict[str, float] | str = "p1_first_order",
sr_seed_salt: str = "",
sr_chunk_frames: int = 8,
sr_device: str = "cpu",
sr_jpeg_backend: str = "auto",
sr_poisson_mode: str = "auto",
sr_share_vision_temporal_positions: bool = False,
**kwargs: object,
) -> dict[str, object]:
"""``video_basic_augmentor_v3_json_caption`` plus an on-the-fly HR-to-LR conditioning stream.

Adds ``AddLowRes`` (writes ``video_lr`` at ``1/sr_scale`` of the HR frame, uint8) right before
reflection padding, and ``SRToTrainingFormat`` as the last stage, which pads LR to half the HR
bucket and packs ``video = [lr, hr]`` with per-item ``image_size`` and a two-item SequencePlan.
All other stages (caption, chunked decode, sequence plan, sound) are inherited unchanged.
"""
from cosmos_framework.data.generator.augmentors.hr_lr_degradation import augmentor as sr_augmentor

augmentors = get_video_augmentor_v3_json_caption(resolution=resolution, **kwargs)
add_low_res = L(sr_augmentor.AddLowRes)(
input_keys=["video"],
output_keys=["video_lr"],
args={
"scale": sr_scale,
"profiles": sr_profiles,
"seed_salt": sr_seed_salt,
"modality": "video",
"chunk_frames": sr_chunk_frames,
"device": sr_device,
"jpeg_backend": sr_jpeg_backend,
"poisson_mode": sr_poisson_mode,
},
)
augmentors = _insert_low_res_stage(augmentors, add_low_res)
augmentors["sr_to_training_format"] = L(sr_augmentor.SRToTrainingFormat)(
input_keys=["video", "video_lr"],
args={
"media_key": "video",
"lr_key": "video_lr",
"scale": sr_scale,
"share_vision_temporal_positions": sr_share_vision_temporal_positions,
"dataset_name": "video_sr",
},
)
return augmentors


@augmentor_register("image_basic_augmentor_with_tokenization_sr")
def image_basic_augmentor_with_tokenization_sr(
resolution: str,
sr_scale: float = 2.0,
sr_profiles: dict[str, float] | str = "p1_first_order",
sr_seed_salt: str = "",
sr_device: str = "cpu",
sr_jpeg_backend: str = "auto",
sr_poisson_mode: str = "auto",
**kwargs: object,
) -> dict[str, object]:
"""``image_basic_augmentor_with_tokenization`` plus an on-the-fly HR-to-LR conditioning image.

``AddLowRes`` runs before ``reflection_padding`` (on the resized uint8 image), the LR copy gets
its own ``Normalize`` so both items reach the model as float in [-1, 1], and
``SRToTrainingFormat`` packs ``images = [lr, hr]`` with per-item ``image_size``.
"""
from cosmos_framework.data.generator.augmentors.hr_lr_degradation import augmentor as sr_augmentor

augmentors = image_basic_augmentor_with_tokenization(resolution=resolution, **kwargs)
add_low_res = L(sr_augmentor.AddLowRes)(
input_keys=["images"],
output_keys=["images_lr"],
args={
"scale": sr_scale,
"profiles": sr_profiles,
"seed_salt": sr_seed_salt,
"modality": "image",
"chunk_frames": 1,
"device": sr_device,
"jpeg_backend": sr_jpeg_backend,
"poisson_mode": sr_poisson_mode,
},
)
augmentors = _insert_before(augmentors, ("reflection_padding",), "add_low_res", add_low_res)
normalize_lr = L(normalize.Normalize)(input_keys=["images_lr"], args={"mean": 0.5, "std": 0.5})
augmentors = _insert_before(augmentors, ("text_transform",), "normalize_lr", normalize_lr)
augmentors["sr_to_training_format"] = L(sr_augmentor.SRToTrainingFormat)(
input_keys=["images", "images_lr"],
args={"media_key": "images", "lr_key": "images_lr", "scale": sr_scale, "dataset_name": "image_sr"},
)
return augmentors
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