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from typing import * |
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BACKEND = 'spconv' |
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DEBUG = False |
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ATTN = 'flash_attn' |
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def __from_env(): |
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import os |
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global BACKEND |
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global DEBUG |
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global ATTN |
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env_sparse_backend = os.environ.get('SPARSE_BACKEND') |
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env_sparse_debug = os.environ.get('SPARSE_DEBUG') |
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env_sparse_attn = os.environ.get('SPARSE_ATTN_BACKEND') |
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if env_sparse_attn is None: |
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env_sparse_attn = os.environ.get('ATTN_BACKEND') |
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if env_sparse_backend is not None and env_sparse_backend in ['spconv', 'torchsparse']: |
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BACKEND = env_sparse_backend |
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if env_sparse_debug is not None: |
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DEBUG = env_sparse_debug == '1' |
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if env_sparse_attn is not None and env_sparse_attn in ['xformers', 'flash_attn']: |
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ATTN = env_sparse_attn |
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print(f"[SPARSE] Backend: {BACKEND}, Attention: {ATTN}") |
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__from_env() |
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def set_backend(backend: Literal['spconv', 'torchsparse']): |
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global BACKEND |
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BACKEND = backend |
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def set_debug(debug: bool): |
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global DEBUG |
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DEBUG = debug |
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def set_attn(attn: Literal['xformers', 'flash_attn']): |
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global ATTN |
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ATTN = attn |
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import importlib |
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__attributes = { |
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'SparseTensor': 'basic', |
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'sparse_batch_broadcast': 'basic', |
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'sparse_batch_op': 'basic', |
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'sparse_cat': 'basic', |
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'sparse_unbind': 'basic', |
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'SparseGroupNorm': 'norm', |
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'SparseLayerNorm': 'norm', |
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'SparseGroupNorm32': 'norm', |
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'SparseLayerNorm32': 'norm', |
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'SparseReLU': 'nonlinearity', |
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'SparseSiLU': 'nonlinearity', |
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'SparseGELU': 'nonlinearity', |
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'SparseActivation': 'nonlinearity', |
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'SparseLinear': 'linear', |
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'sparse_scaled_dot_product_attention': 'attention', |
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'SerializeMode': 'attention', |
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'sparse_serialized_scaled_dot_product_self_attention': 'attention', |
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'sparse_windowed_scaled_dot_product_self_attention': 'attention', |
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'SparseMultiHeadAttention': 'attention', |
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'SparseConv3d': 'conv', |
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'SparseInverseConv3d': 'conv', |
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'SparseDownsample': 'spatial', |
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'SparseUpsample': 'spatial', |
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'SparseSubdivide' : 'spatial' |
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} |
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__submodules = ['transformer'] |
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__all__ = list(__attributes.keys()) + __submodules |
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def __getattr__(name): |
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if name not in globals(): |
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if name in __attributes: |
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module_name = __attributes[name] |
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module = importlib.import_module(f".{module_name}", __name__) |
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globals()[name] = getattr(module, name) |
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elif name in __submodules: |
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module = importlib.import_module(f".{name}", __name__) |
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globals()[name] = module |
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else: |
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raise AttributeError(f"module {__name__} has no attribute {name}") |
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return globals()[name] |
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if __name__ == '__main__': |
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from .basic import * |
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from .norm import * |
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from .nonlinearity import * |
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from .linear import * |
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from .attention import * |
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from .conv import * |
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from .spatial import * |
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import transformer |
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