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| # MIT License | |
| # Copyright (c) Microsoft | |
| # Permission is hereby granted, free of charge, to any person obtaining a copy | |
| # of this software and associated documentation files (the "Software"), to deal | |
| # in the Software without restriction, including without limitation the rights | |
| # to use, copy, modify, merge, publish, distribute, sublicense, and/or sell | |
| # copies of the Software, and to permit persons to whom the Software is | |
| # furnished to do so, subject to the following conditions: | |
| # The above copyright notice and this permission notice shall be included in all | |
| # copies or substantial portions of the Software. | |
| # THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR | |
| # IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, | |
| # FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE | |
| # AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER | |
| # LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, | |
| # OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE | |
| # SOFTWARE. | |
| # Copyright (c) [2025] [Microsoft] | |
| # SPDX-License-Identifier: MIT | |
| from typing import * | |
| BACKEND = 'spconv' | |
| DEBUG = False | |
| ATTN = 'xformers' | |
| 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 | |