From c639cb7d5dce38d5ceb2356da4cddab6c32a8263 Mon Sep 17 00:00:00 2001 From: Kohya S Date: Sun, 2 Apr 2023 16:18:04 +0900 Subject: [PATCH] support older type hint --- networks/lora.py | 14 +++++++------- 1 file changed, 7 insertions(+), 7 deletions(-) diff --git a/networks/lora.py b/networks/lora.py index f1a65074..17bd0b38 100644 --- a/networks/lora.py +++ b/networks/lora.py @@ -5,7 +5,7 @@ import math import os -from typing import List +from typing import List, Union import numpy as np import torch import re @@ -247,7 +247,7 @@ def create_network_from_weights(multiplier, file, vae, text_encoder, unet, weigh class LoRANetwork(torch.nn.Module): - # is it possible to apply conv_in and conv_out? + # is it possible to apply conv_in and conv_out? -> yes, newer LoCon supports it (^^;) UNET_TARGET_REPLACE_MODULE = ["Transformer2DModel", "Attention"] UNET_TARGET_REPLACE_MODULE_CONV2D_3X3 = ["ResnetBlock2D", "Downsample2D", "Upsample2D"] TEXT_ENCODER_TARGET_REPLACE_MODULE = ["CLIPAttention", "CLIPMLP"] @@ -333,8 +333,8 @@ class LoRANetwork(torch.nn.Module): self.weights_sd = None - self.up_lr_weight: list[float] = None - self.down_lr_weight: list[float] = None + self.up_lr_weight: List[float] = None + self.down_lr_weight: List[float] = None self.mid_lr_weight: float = None self.block_lr = False @@ -445,9 +445,9 @@ class LoRANetwork(torch.nn.Module): # 層別学習率用に層ごとの学習率に対する倍率を定義する def set_block_lr_weight( self, - up_lr_weight: list[float] | str = None, + up_lr_weight: Union[List[float], str] = None, mid_lr_weight: float = None, - down_lr_weight: list[float] | str = None, + down_lr_weight: Union[List[float], str] = None, zero_threshold: float = 0.0, ): # バラメータ未指定時は何もせず、今までと同じ動作とする @@ -456,7 +456,7 @@ class LoRANetwork(torch.nn.Module): max_len = 12 # フルモデル相当でのup,downの層の数 - def get_list(name) -> list[float]: + def get_list(name) -> List[float]: import math if name == "cosine":