maybe if I just include stylegan directly?

README.md

@@ -1,12 +0,0 @@
----
-title: TADNE
-emoji: 🏃
-colorFrom: green
-colorTo: red
-sdk: gradio
-sdk_version: 3.0.2
-app_file: app.py
-pinned: false
----
-
-Check out the configuration reference at https://huggingface.co/docs/hub/spaces#reference

patch

@@ -1,85 +0,0 @@
-diff --git a/model.py b/model.py
-index 0134c39..3a7826c 100755
---- a/model.py
-+++ b/model.py
-@@ -395,6 +395,7 @@ class Generator(nn.Module):
-         style_dim,
-         n_mlp,
-         channel_multiplier=2,
-+        additional_multiplier=2,
-         blur_kernel=[1, 3, 3, 1],
-         lr_mlp=0.01,
-     ):
-@@ -426,6 +427,9 @@ class Generator(nn.Module):
-             512: 32 * channel_multiplier,
-             1024: 16 * channel_multiplier,
-         }
-+        if additional_multiplier > 1:
-+            for k in list(self.channels.keys()):
-+                self.channels[k] *= additional_multiplier
- 
-         self.input = ConstantInput(self.channels[4])
-         self.conv1 = StyledConv(
-@@ -518,7 +522,7 @@ class Generator(nn.Module):
-                     getattr(self.noises, f"noise_{i}") for i in range(self.num_layers)
-                 ]
- 
--        if truncation < 1:
-+        if truncation_latent is not None:
-             style_t = []
- 
-             for style in styles:
-diff --git a/op/fused_act.py b/op/fused_act.py
-index 5d46e10..bc522ed 100755
---- a/op/fused_act.py
-+++ b/op/fused_act.py
-@@ -1,5 +1,3 @@
--import os
--
- import torch
- from torch import nn
- from torch.nn import functional as F
-@@ -7,16 +5,6 @@ from torch.autograd import Function
- from torch.utils.cpp_extension import load
- 
- 
--module_path = os.path.dirname(__file__)
--fused = load(
--    "fused",
--    sources=[
--        os.path.join(module_path, "fused_bias_act.cpp"),
--        os.path.join(module_path, "fused_bias_act_kernel.cu"),
--    ],
--)
--
--
- class FusedLeakyReLUFunctionBackward(Function):
-     @staticmethod
-     def forward(ctx, grad_output, out, bias, negative_slope, scale):
-diff --git a/op/upfirdn2d.py b/op/upfirdn2d.py
-index 67e0375..6c5840e 100755
---- a/op/upfirdn2d.py
-+++ b/op/upfirdn2d.py
-@@ -1,5 +1,4 @@
- from collections import abc
--import os
- 
- import torch
- from torch.nn import functional as F
-@@ -7,16 +6,6 @@ from torch.autograd import Function
- from torch.utils.cpp_extension import load
- 
- 
--module_path = os.path.dirname(__file__)
--upfirdn2d_op = load(
--    "upfirdn2d",
--    sources=[
--        os.path.join(module_path, "upfirdn2d.cpp"),
--        os.path.join(module_path, "upfirdn2d_kernel.cu"),
--    ],
--)
--
--
- class UpFirDn2dBackward(Function):
-     @staticmethod
-     def forward(