# Licensed under the TENCENT HUNYUAN COMMUNITY LICENSE AGREEMENT (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # https://github.com/Tencent-Hunyuan/HunyuanVideo-1.5/blob/main/LICENSE # # Unless and only to the extent required by applicable law, the Tencent Hunyuan works and any # output and results therefrom are provided "AS IS" without any express or implied warranties of # any kind including any warranties of title, merchantability, noninfringement, course of dealing, # usage of trade, or fitness for a particular purpose. You are solely responsible for determining the # appropriateness of using, reproducing, modifying, performing, displaying or distributing any of # the Tencent Hunyuan works or outputs and assume any and all risks associated with your or a # third party's use or distribution of any of the Tencent Hunyuan works or outputs and your exercise # of rights and permissions under this agreement. # See the License for the specific language governing permissions and limitations under the License. import torch.nn as nn def get_activation_layer(act_type): """get activation layer Args: act_type (str): the activation type Returns: torch.nn.functional: the activation layer """ if act_type == "gelu": return lambda: nn.GELU() elif act_type == "gelu_tanh": # Approximate `tanh` requires torch >= 1.13 return lambda: nn.GELU(approximate="tanh") elif act_type == "relu": return nn.ReLU elif act_type == "silu": return nn.SiLU else: raise ValueError(f"Unknown activation type: {act_type}")