|
|
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 |
|
|
|
