""" Activation Factory Hacked together by / Copyright 2020 Ross Wightman """ from .activations import * from .activations_jit import * from .activations_me import * from .config import is_exportable, is_scriptable, is_no_jit # PyTorch has an optimized, native 'silu' (aka 'swish') operator as of PyTorch 1.7. This code # will use native version if present. Eventually, the custom Swish layers will be removed # and only native 'silu' will be used. _has_silu = 'silu' in dir(torch.nn.functional) _ACT_FN_DEFAULT = dict( silu=F.silu if _has_silu else swish, swish=F.silu if _has_silu else swish, mish=mish, relu=F.relu, relu6=F.relu6, leaky_relu=F.leaky_relu, elu=F.elu, prelu=F.prelu, celu=F.celu, selu=F.selu, gelu=F.gelu, sigmoid=sigmoid, tanh=tanh, hard_sigmoid=hard_sigmoid, hard_swish=hard_swish, hard_mish=hard_mish, ) _ACT_FN_JIT = dict( silu=F.silu if _has_silu else swish_jit, swish=F.silu if _has_silu else swish_jit, mish=mish_jit, hard_sigmoid=hard_sigmoid_jit, hard_swish=hard_swish_jit, hard_mish=hard_mish_jit ) _ACT_FN_ME = dict( silu=F.silu if _has_silu else swish_me, swish=F.silu if _has_silu else swish_me, mish=mish_me, hard_sigmoid=hard_sigmoid_me, hard_swish=hard_swish_me, hard_mish=hard_mish_me, ) _ACT_LAYER_DEFAULT = dict( silu=nn.SiLU if _has_silu else Swish, swish=nn.SiLU if _has_silu else Swish, mish=Mish, relu=nn.ReLU, relu6=nn.ReLU6, leaky_relu=nn.LeakyReLU, elu=nn.ELU, prelu=nn.PReLU, celu=nn.CELU, selu=nn.SELU, gelu=nn.GELU, sigmoid=Sigmoid, tanh=Tanh, hard_sigmoid=HardSigmoid, hard_swish=HardSwish, hard_mish=HardMish, ) _ACT_LAYER_JIT = dict( silu=nn.SiLU if _has_silu else SwishJit, swish=nn.SiLU if _has_silu else SwishJit, mish=MishJit, hard_sigmoid=HardSigmoidJit, hard_swish=HardSwishJit, hard_mish=HardMishJit ) _ACT_LAYER_ME = dict( silu=nn.SiLU if _has_silu else SwishMe, swish=nn.SiLU if _has_silu else SwishMe, mish=MishMe, hard_sigmoid=HardSigmoidMe, hard_swish=HardSwishMe, hard_mish=HardMishMe, ) def get_act_fn(name='relu'): """ Activation Function Factory Fetching activation fns by name with this function allows export or torch script friendly functions to be returned dynamically based on current config. """ if not name: return None if not (is_no_jit() or is_exportable() or is_scriptable()): # If not exporting or scripting the model, first look for a memory-efficient version with # custom autograd, then fallback if name in _ACT_FN_ME: return _ACT_FN_ME[name] if is_exportable() and name in ('silu', 'swish'): # FIXME PyTorch SiLU doesn't ONNX export, this is a temp hack return swish if not (is_no_jit() or is_exportable()): if name in _ACT_FN_JIT: return _ACT_FN_JIT[name] return _ACT_FN_DEFAULT[name] def get_act_layer(name='relu'): """ Activation Layer Factory Fetching activation layers by name with this function allows export or torch script friendly functions to be returned dynamically based on current config. """ if not name: return None if not (is_no_jit() or is_exportable() or is_scriptable()): if name in _ACT_LAYER_ME: return _ACT_LAYER_ME[name] if is_exportable() and name in ('silu', 'swish'): # FIXME PyTorch SiLU doesn't ONNX export, this is a temp hack return Swish if not (is_no_jit() or is_exportable()): if name in _ACT_LAYER_JIT: return _ACT_LAYER_JIT[name] return _ACT_LAYER_DEFAULT[name] def create_act_layer(name, inplace=False, **kwargs): act_layer = get_act_layer(name) if act_layer is not None: return act_layer(inplace=inplace, **kwargs) else: return None