trellis/modules/sparse/__init__.py

from typing import *

BACKEND = 'spconv' 
DEBUG = False
ATTN = 'flash_attn'

def __from_env():
    import os
    
    global BACKEND
    global DEBUG
    global ATTN
    
    env_sparse_backend = os.environ.get('SPARSE_BACKEND')
    env_sparse_debug = os.environ.get('SPARSE_DEBUG')
    env_sparse_attn = os.environ.get('SPARSE_ATTN_BACKEND')
    if env_sparse_attn is None:
        env_sparse_attn = os.environ.get('ATTN_BACKEND')

    if env_sparse_backend is not None and env_sparse_backend in ['spconv', 'torchsparse']:
        BACKEND = env_sparse_backend
    if env_sparse_debug is not None:
        DEBUG = env_sparse_debug == '1'
    if env_sparse_attn is not None and env_sparse_attn in ['xformers', 'flash_attn']:
        ATTN = env_sparse_attn
        
    print(f"[SPARSE] Backend: {BACKEND}, Attention: {ATTN}")
        

__from_env()
    

def set_backend(backend: Literal['spconv', 'torchsparse']):
    global BACKEND
    BACKEND = backend

def set_debug(debug: bool):
    global DEBUG
    DEBUG = debug

def set_attn(attn: Literal['xformers', 'flash_attn']):
    global ATTN
    ATTN = attn
    
    
import importlib

__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