| | 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]
|
| |
|
| |
|
| |
|
| | 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
|
| |
|
