# coding=utf-8 # Copyright 2021 The OneFlow Authors. All rights reserved. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or agreed to in writing, software # distributed under the License is distributed on an "AS IS" BASIS, # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. # See the License for the specific language governing permissions and # limitations under the License. from enum import Enum from typing import Optional import oneflow as flow from oneflow import nn class Activation(str, Enum): SquaredReLU = "squared_relu" GeLU = "gelu" GeLUTanh = "gelu_tanh" LeakyReLU = "leaky_relu" ReLU = "relu" Tanh = "tanh" QuickGELU = "quick_gelu" # For unit testing / parity comparisons, probably not the fastest way class SquaredReLU(nn.Module): def __init__(self) -> None: super().__init__() def forward(self, x: flow.Tensor) -> flow.Tensor: x_ = flow._C.relu(x) return x_ * x_ class Passthrough(nn.Module): def __init__(self) -> None: super().__init__() def forward(self, x: flow.Tensor) -> flow.Tensor: return x class GeLUTanh(nn.Module): def __init__(self) -> None: super().__init__() def forward(self, x: flow.Tensor) -> flow.Tensor: """When the approximate argument is 'tanh', Gelu is estimated with: 0.5 * x * (1.0 + flow.tanh(math.sqrt(2.0 / math.pi) * (x + 0.044715 * flow.pow(x, 3.0)))) """ return flow.nn.functional.gelu(x, approximate="tanh") class QuickGELU(nn.Module): def __init__(self) -> None: super().__init__() def forward(self, x: flow.Tensor) -> flow.Tensor: return x * flow.sigmoid(1.702 * x) def build_activation(activation: Optional[Activation]): """ Fetching activation layers by name, e.g., ``build_activation("gelu")`` returns ``nn.GELU()`` module. """ if not activation: return Passthrough() return { Activation.ReLU: nn.ReLU, Activation.GeLU: nn.GELU, Activation.GeLUTanh: GeLUTanh, Activation.LeakyReLU: nn.LeakyReLU, Activation.SquaredReLU: SquaredReLU, Activation.Tanh: nn.Tanh, Activation.QuickGELU: QuickGELU, }[activation]()