diff --git a/codes/models/ExtensibleTrainer.py b/codes/models/ExtensibleTrainer.py
index 68fca1e6..d8485273 100644
--- a/codes/models/ExtensibleTrainer.py
+++ b/codes/models/ExtensibleTrainer.py
@@ -235,7 +235,7 @@ class ExtensibleTrainer(BaseModel):
                 if v not in state.keys():
                     continue   # This can happen for several reasons (ex: 'after' defs), just ignore it.
                 for i, dbgv in enumerate(state[v]):
-                    if 'recurrent_visual_indices' in self.opt['logger'].keys():
+                    if 'recurrent_visual_indices' in self.opt['logger'].keys() and len(dbgv.shape)==5:
                         for rvi in self.opt['logger']['recurrent_visual_indices']:
                             rdbgv = dbgv[:, rvi]
                             if rdbgv.shape[1] > 3:
diff --git a/codes/models/archs/RRDBNet_arch.py b/codes/models/archs/RRDBNet_arch.py
index 8b763b09..42a04770 100644
--- a/codes/models/archs/RRDBNet_arch.py
+++ b/codes/models/archs/RRDBNet_arch.py
@@ -152,7 +152,8 @@ class RRDBNet(nn.Module):
         self.in_channels = in_channels
         first_conv_stride = 1 if in_channels <= 4 else scale
         first_conv_ksize = 3 if first_conv_stride == 1 else 7
-        self.conv_first = nn.Conv2d(in_channels, mid_channels, first_conv_ksize, first_conv_stride, 1)
+        first_conv_padding = 1 if first_conv_stride == 1 else 3
+        self.conv_first = nn.Conv2d(in_channels, mid_channels, first_conv_ksize, first_conv_stride, first_conv_padding)
         self.body = make_layer(
             body_block,
             num_blocks,
@@ -186,7 +187,7 @@ class RRDBNet(nn.Module):
             x_lg = F.interpolate(x, scale_factor=self.scale, mode="bicubic")
             if ref is None:
                 ref = torch.zeros_like(x_lg)
-            x_lg = torch.cat([x_lg, ref])
+            x_lg = torch.cat([x_lg, ref], dim=1)
         feat = self.conv_first(x_lg)
         body_feat = self.conv_body(checkpoint_sequential(self.body, self.num_blocks // self.blocks_per_checkpoint, feat))
         feat = feat + body_feat
diff --git a/codes/models/steps/tecogan_losses.py b/codes/models/steps/tecogan_losses.py
index 7a09cfc1..2da702ca 100644
--- a/codes/models/steps/tecogan_losses.py
+++ b/codes/models/steps/tecogan_losses.py
@@ -138,7 +138,7 @@ class RecurrentImageGeneratorSequenceInjector(Injector):
         final_results = {}
         # Include 'hq_batched' here - because why not... Don't really need a separate injector for this.
         b, s, c, h, w = state['hq'].shape
-        final_results['hq_batched'] = state['hq'].view(b*s, c, h, w)
+        final_results['hq_batched'] = state['hq'].clone().permute(1,0,2,3,4).reshape(b*s, c, h, w)
         for k, v in results.items():
             final_results[k] = torch.stack(v, dim=1)
             final_results[k + "_batched"] = torch.cat(v[:s], dim=0)  # Only include the original sequence - this output is generally used to compare against HQ.
@@ -345,8 +345,10 @@ class PingPongLoss(ConfigurableLoss):
         img_count = fake.shape[1]
         for i in range((img_count - 1) // 2):
             early = fake[:, i]
-            late = fake[:, -i]
+            late = fake[:, -(i+1)]
             l_total += self.criterion(early, late)
+            if self.env['step'] % 50 == 0:
+                self.produce_teco_visual_debugs2(early, late, i)
 
         if self.env['step'] % 50 == 0:
             self.produce_teco_visual_debugs(fake)
@@ -363,3 +365,11 @@ class PingPongLoss(ConfigurableLoss):
             img = imglist[:, i]
             torchvision.utils.save_image(img.float(), osp.join(base_path, "%s.png" % (i, )))
 
+    def produce_teco_visual_debugs2(self, imga, imgb, i):
+        if self.env['rank'] > 0:
+            return
+        base_path = osp.join(self.env['base_path'], "..", "visual_dbg", "teco_pingpong", str(self.env['step']))
+        os.makedirs(base_path, exist_ok=True)
+        torchvision.utils.save_image(imga.float(), osp.join(base_path, "%s_a.png" % (i, )))
+        torchvision.utils.save_image(imgb.float(), osp.join(base_path, "%s_b.png" % (i, )))
+