from . import config import importlib __attributes = { 'VarLenTensor': 'basic', 'varlen_cat': 'basic', 'varlen_unbind': 'basic', 'SparseTensor': 'basic', 'sparse_cat': 'basic', 'sparse_unbind': 'basic', 'SparseGroupNorm': 'norm', 'SparseLayerNorm': 'norm', 'SparseGroupNorm32': 'norm', 'SparseLayerNorm32': 'norm', 'SparseReLU': 'nonlinearity', 'SparseSiLU': 'nonlinearity', 'SparseGELU': 'nonlinearity', 'SparseActivation': 'nonlinearity', 'SparseLinear': 'linear', 'sparse_scaled_dot_product_attention': 'attention', 'SerializeMode': 'attention', 'sparse_serialized_scaled_dot_product_self_attention': 'attention', 'sparse_windowed_scaled_dot_product_self_attention': 'attention', 'sparse_windowed_scaled_dot_product_cross_attention': 'attention', 'SparseRotaryPositionEmbedder': 'attention', 'SparseMultiHeadAttention': 'attention', 'SparseConv3d': 'conv', 'SparseInverseConv3d': 'conv', 'SparseDownsample': 'spatial', 'SparseUpsample': 'spatial', 'SparseSubdivide': 'spatial', 'SparseSpatial2Channel': 'spatial', 'SparseChannel2Spatial': 'spatial', 'sparse_nearest_interpolate': 'spatial', 'sparse_trilinear_interpolate': 'spatial', 'encode_seq': 'serialize', 'decode_seq': 'serialize', } __submodules = ['transformer', 'conv'] __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] # For Pylance if __name__ == '__main__': from .basic import * from .norm import * from .nonlinearity import * from .linear import * from .attention import * from .conv import * from .spatial import * from .serialize import * import transformer import conv