From c88e9782ad3237d0b26385b4aa152a8d00c51b70 Mon Sep 17 00:00:00 2001
From: soltanianaref <101413285+soltanianaref@users.noreply.github.com>
Date: Sat, 9 Apr 2022 20:33:31 +0430
Subject: [PATCH] Update encoders.py

---
 steganogan/encoders.py | 17 ++++++++++++++++-
 1 file changed, 16 insertions(+), 1 deletion(-)

diff --git a/steganogan/encoders.py b/steganogan/encoders.py
index d1a93c8..3ab7c1c 100644
--- a/steganogan/encoders.py
+++ b/steganogan/encoders.py
@@ -2,6 +2,17 @@
 
 import torch
 from torch import nn
+import torch.onnx
+from torchvision.ops.deform_conv import DeformConv2d
+
+#input = torch.rand(4, 3, 10, 10)
+kh, kw = 3, 3
+#weight = torch.rand(5, 3, kh, kw)
+# offset and mask should have the same spatial size as the output
+# of the convolution. In this case, for an input of 10, stride of 1
+# and kernel size of 3, without padding, the output size is 8
+#offset = torch.rand(4, 2 * kh * kw, 8, 8)
+#mask = torch.rand(4, kh * kw, 8, 8)
 
 
 class BasicEncoder(nn.Module):
@@ -16,9 +27,13 @@ class BasicEncoder(nn.Module):
     add_image = False
 
     def _conv2d(self, in_channels, out_channels):
-        return nn.Conv2d(
+        return DeformConv2d(
             in_channels=in_channels,
             out_channels=out_channels,
+            input = torch.rand(4, 3, 10, 10)
+            weight = torch.rand(5, 3, kh, kw)
+            offset = torch.rand(4, 2 * kh * kw, 8, 8)
+            mask = torch.rand(4, kh * kw, 8, 8)
             kernel_size=3,
             padding=1
         )