Spaces:
Running
on
Zero
Running
on
Zero
File size: 2,907 Bytes
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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
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