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8 Commits
feat/load3
...
feat/load3
| Author | SHA1 | Date | |
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| f323abcdc3 | |||
| b10a61615c | |||
| 1161959952 | |||
| 684296148e | |||
| ade4dfd96a | |||
| d9caddfcfc | |||
| 26aad73cd7 | |||
| 7dd6d319e2 |
@ -1,5 +1,20 @@
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import logging
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import torch
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_CK_STOCHASTIC_ROUNDING_AVAILABLE = False
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try:
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import comfy_kitchen as ck
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_ck_stochastic_rounding_fp8 = ck.stochastic_rounding_fp8
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_CK_STOCHASTIC_ROUNDING_AVAILABLE = True
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except (AttributeError, ImportError):
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logging.warning("comfy_kitchen does not support stochastic FP8 rounding, please update comfy_kitchen.")
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if not _CK_STOCHASTIC_ROUNDING_AVAILABLE:
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def _ck_stochastic_rounding_fp8(value, rng, dtype):
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raise NotImplementedError("comfy_kitchen does not support stochastic FP8 rounding")
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def calc_mantissa(abs_x, exponent, normal_mask, MANTISSA_BITS, EXPONENT_BIAS, generator=None):
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mantissa_scaled = torch.where(
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normal_mask,
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@ -57,6 +72,10 @@ def stochastic_rounding(value, dtype, seed=0):
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if dtype == torch.float8_e4m3fn or dtype == torch.float8_e5m2:
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generator = torch.Generator(device=value.device)
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generator.manual_seed(seed)
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if _CK_STOCHASTIC_ROUNDING_AVAILABLE:
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rng = torch.randint(0, 256, value.size(), dtype=torch.uint8, layout=value.layout, device=value.device, generator=generator)
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return _ck_stochastic_rounding_fp8(value, rng, dtype)
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output = torch.empty_like(value, dtype=dtype)
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num_slices = max(1, (value.numel() / (4096 * 4096)))
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slice_size = max(1, round(value.shape[0] / num_slices))
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@ -777,6 +777,17 @@ class Load3DCamera(ComfyTypeIO):
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Type = CameraInfo
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@comfytype(io_type="LOAD3D_MODEL_INFO")
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class Load3DModelInfo(ComfyTypeIO):
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class Model3DTransform(TypedDict):
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# Coordinate system: right-handed, Y-up, world space
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position: dict[str, float | int] # scene units
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quaternion: dict[str, float | int] # normalized, dimensionless; world rotation
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scale: dict[str, float | int] # dimensionless multiplier
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Type = list[Model3DTransform]
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@comfytype(io_type="LOAD_3D")
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class Load3D(ComfyTypeIO):
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"""3D models are stored as a dictionary."""
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@ -786,6 +797,7 @@ class Load3D(ComfyTypeIO):
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normal: str
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camera_info: Load3DCamera.CameraInfo
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recording: NotRequired[str]
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model_3d_info: NotRequired[list[Load3DModelInfo.Model3DTransform]]
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Type = Model3DDict
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@ -2298,6 +2310,7 @@ __all__ = [
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"FlowControl",
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"Accumulation",
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"Load3DCamera",
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"Load3DModelInfo",
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"Load3D",
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"Load3DAnimation",
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"Photomaker",
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@ -47,6 +47,7 @@ class Load3D(IO.ComfyNode):
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IO.Load3DCamera.Output(display_name="camera_info"),
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IO.Video.Output(display_name="recording_video"),
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IO.File3DAny.Output(display_name="model_3d"),
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IO.Load3DModelInfo.Output(display_name="model_3d_info"),
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],
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)
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@ -73,7 +74,8 @@ class Load3D(IO.ComfyNode):
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if model_file and model_file != "none":
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file_3d = Types.File3D(folder_paths.get_annotated_filepath(model_file))
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mesh_path = model_file
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return IO.NodeOutput(output_image, output_mask, mesh_path, normal_image, image['camera_info'], video, file_3d)
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model_3d_info = image.get('model_3d_info', [])
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return IO.NodeOutput(output_image, output_mask, mesh_path, normal_image, image['camera_info'], video, file_3d, model_3d_info)
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process = execute # TODO: remove
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@ -1,5 +1,5 @@
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comfyui-frontend-package==1.44.19
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comfyui-workflow-templates==0.9.85
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comfyui-workflow-templates==0.9.91
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comfyui-embedded-docs==0.5.1
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torch
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torchsde
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@ -22,7 +22,7 @@ alembic
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SQLAlchemy>=2.0.0
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filelock
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av>=16.0.0
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comfy-kitchen>=0.2.8
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comfy-kitchen==0.2.9
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comfy-aimdo==0.4.5
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requests
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simpleeval>=1.0.0
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