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0d1388f 31f61c1 0d1388f 31f61c1 0d1388f | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 | import importlib
__attributes = {
'SparseStructureEncoder': 'sparse_structure_vae',
'SparseStructureDecoder': 'sparse_structure_vae',
'SparseStructureFlowModel': 'sparse_structure_flow',
'SLatEncoder': 'structured_latent_vae',
'SLatGaussianDecoder': 'structured_latent_vae',
'SLatGaussianDecoderOri': 'structured_latent_vae',
'SLatRadianceFieldDecoder': 'structured_latent_vae',
'SLatMeshDecoder': 'structured_latent_vae',
'SLatGaussianRenderer': 'structured_latent_vae',
'ElasticSLatEncoder': 'structured_latent_vae',
'ElasticSLatGaussianDecoder': 'structured_latent_vae',
'ElasticSLatGaussianDecoderOri': 'structured_latent_vae',
'ElasticSLatRadianceFieldDecoder': 'structured_latent_vae',
'ElasticSLatMeshDecoder': 'structured_latent_vae',
'ElasticSLatGaussianRenderer': 'structured_latent_vae',
'Hdri_Encoder': 'structured_latent_vae',
'NeuralBasis': 'structured_latent_vae',
'SLatFlowModel': 'structured_latent_flow',
'ElasticSLatFlowModel': 'structured_latent_flow',
'SLatFlowS2EModelLoRA': 'structured_latent_flow_s2e',
'ElasticSLatFlowS2ELORAModel': 'structured_latent_flow_s2e',
}
__submodules = []
__all__ = list(__attributes.keys()) + __submodules
def __getattr__(name):
if name not in globals():
if name in __attributes:
module_name = __attributes[name]
module = importlib.import_module(f".{module_name}", __name__)
globals()[name] = getattr(module, name)
elif name in __submodules:
module = importlib.import_module(f".{name}", __name__)
globals()[name] = module
else:
raise AttributeError(f"module {__name__} has no attribute {name}")
return globals()[name]
def from_pretrained(path: str, **kwargs):
"""
Load a model from a pretrained checkpoint.
Args:
path: The path to the checkpoint. Can be either local path or a Hugging Face model name.
NOTE: config file and model file should take the name f'{path}.json' and f'{path}.safetensors' respectively.
**kwargs: Additional arguments for the model constructor.
"""
import os
import json
from safetensors.torch import load_file
import torch
is_local = os.path.exists(f"{path}.json") and (os.path.exists(f"{path}.safetensors") or os.path.exists(f"{path}.pt"))
if is_local:
config_file = f"{path}.json"
model_file = f"{path}.safetensors" if os.path.exists(f"{path}.safetensors") else f"{path}.pt"
else:
from huggingface_hub import hf_hub_download
path_parts = path.split('/')
repo_id = f'{path_parts[0]}/{path_parts[1]}'
model_name = '/'.join(path_parts[2:])
config_file = hf_hub_download(repo_id, f"{model_name}.json")
model_file = hf_hub_download(repo_id, f"{model_name}.safetensors")
with open(config_file, 'r') as f:
config = json.load(f)
model = __getattr__(config['name'])(**config['args'], **kwargs)
# Always load checkpoints to CPU. Probing CUDA availability here initializes
# the driver in the host process, which breaks Hugging Face Spaces Stateless /
# ZeroGPU (WeightsUnpickler disallows CUDA init in the main process). Callers
# move modules to GPU via pipeline.to("cuda") inside @spaces.GPU callbacks only.
if model_file.endswith('.safetensors'):
model.load_state_dict(load_file(model_file))
else:
model.load_state_dict(torch.load(model_file, weights_only=True, map_location="cpu"))
return model
# For Pylance
if __name__ == '__main__':
from .sparse_structure_vae import (
SparseStructureEncoder,
SparseStructureDecoder,
)
from .sparse_structure_flow import SparseStructureFlowModel
from .structured_latent_vae import (
SLatEncoder,
SLatGaussianDecoder,
SLatRadianceFieldDecoder,
SLatMeshDecoder,
SLatGaussianRenderer,
ElasticSLatEncoder,
ElasticSLatGaussianDecoder,
ElasticSLatRadianceFieldDecoder,
ElasticSLatMeshDecoder,
ElasticSLatGaussianRenderer,
Hdri_Encoder,
SLatGaussianDecoderOri,
ElasticSLatGaussianDecoderOri,
NeuralBasis,
)
from .structured_latent_flow import (
SLatFlowModel,
ElasticSLatFlowModel,
)
from .structured_latent_flow_s2e import (
SLatFlowS2EModelLoRA,
ElasticSLatFlowS2ELORAModel,
)
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