content: from typing import *
  import importlib
  from trellis.backend_config import get_sparse_backend, get_attention_backend, get_debug_mode
  
  BACKEND = get_sparse_backend()
  DEBUG = get_debug_mode()
  ATTN = get_attention_backend()
  
  if ATTN not in ['xformers', 'flash_attn']:
      logger.warning(f"Attention backend {ATTN} not supported for sparse attention. Only 'xformers' and 'flash_attn' are available. Defaulting to 'flash_attn'")
      ATTN = 'flash_attn'
  
  __attributes = {
      'SparseTensor': 'basic',
      'sparse_batch_broadcast': 'basic',
      'sparse_batch_op': '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',
      'SparseMultiHeadAttention': 'attention',
      'SparseConv3d': 'conv',
      'SparseInverseConv3d': 'conv',
      'SparseDownsample': 'spatial',
      'SparseUpsample': 'spatial',
      'SparseSubdivide' : 'spatial'
  }
  
  __submodules = ['transformer']
  
  __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 *
      import transformer
  