From bad7cb29cecac51c5c0f39afec332b007ed73133 Mon Sep 17 00:00:00 2001 From: AUTOMATIC <16777216c@gmail.com> Date: Fri, 7 Oct 2022 10:17:52 +0300 Subject: added support for hypernetworks (???) --- modules/hypernetwork.py | 55 +++++++++++++++++++++++++++++++++++++++++++++++++ 1 file changed, 55 insertions(+) create mode 100644 modules/hypernetwork.py (limited to 'modules/hypernetwork.py') diff --git a/modules/hypernetwork.py b/modules/hypernetwork.py new file mode 100644 index 00000000..9ed1eed9 --- /dev/null +++ b/modules/hypernetwork.py @@ -0,0 +1,55 @@ +import glob +import os +import torch +from modules import devices + + +class HypernetworkModule(torch.nn.Module): + def __init__(self, dim, state_dict): + super().__init__() + + self.linear1 = torch.nn.Linear(dim, dim * 2) + self.linear2 = torch.nn.Linear(dim * 2, dim) + + self.load_state_dict(state_dict, strict=True) + self.to(devices.device) + + def forward(self, x): + return x + (self.linear2(self.linear1(x))) + + +class Hypernetwork: + filename = None + name = None + + def __init__(self, filename): + self.filename = filename + self.name = os.path.splitext(os.path.basename(filename))[0] + self.layers = {} + + state_dict = torch.load(filename, map_location='cpu') + for size, sd in state_dict.items(): + self.layers[size] = (HypernetworkModule(size, sd[0]), HypernetworkModule(size, sd[1])) + + +def load_hypernetworks(path): + res = {} + + for filename in glob.iglob(path + '**/*.pt', recursive=True): + hn = Hypernetwork(filename) + res[hn.name] = hn + + return res + +def apply(self, x, context=None, mask=None, original=None): + + + if CrossAttention.hypernetwork is not None and context.shape[2] in CrossAttention.hypernetwork: + if context.shape[1] == 77 and CrossAttention.noise_cond: + context = context + (torch.randn_like(context) * 0.1) + h_k, h_v = CrossAttention.hypernetwork[context.shape[2]] + k = self.to_k(h_k(context)) + v = self.to_v(h_v(context)) + else: + k = self.to_k(context) + v = self.to_v(context) -- cgit v1.2.1