diff --git a/codes/models/SRGAN_model.py b/codes/models/SRGAN_model.py
index cc0094c6..2bfdbda3 100644
--- a/codes/models/SRGAN_model.py
+++ b/codes/models/SRGAN_model.py
@@ -338,31 +338,38 @@ class SRGANModel(BaseModel):
                     with amp.scale_loss(l_d_fake, self.optimizer_D, loss_id=1) as l_d_fake_scaled:
                         l_d_fake_scaled.backward()
                 if self.opt['train']['gan_type'] == 'pixgan':
+                    # randomly determine portions of the image to swap to keep the discriminator honest.
+
                     # We're making some assumptions about the underlying pixel-discriminator here. This is a
                     # necessary evil for now, but if this turns out well we might want to make this configurable.
                     PIXDISC_CHANNELS = 3
                     PIXDISC_OUTPUT_REDUCTION = 8
-                    PIXDISC_MAX_REDUCTION = 32
                     disc_output_shape = (var_ref[0].shape[0], PIXDISC_CHANNELS, var_ref[0].shape[2] // PIXDISC_OUTPUT_REDUCTION, var_ref[0].shape[3] // PIXDISC_OUTPUT_REDUCTION)
-                    real = torch.ones(disc_output_shape, device=var_ref[0].device)
-                    fake = torch.zeros(disc_output_shape, device=var_ref[0].device)
-
-                    # randomly determine portions of the image to swap to keep the discriminator honest.
-                    if random.random() > .25:
+                    b, _, w, h = var_ref[0].shape
+                    real = torch.ones((b, PIXDISC_CHANNELS, w, h), device=var_ref[0].device)
+                    fake = torch.zeros((b, PIXDISC_CHANNELS, w, h), device=var_ref[0].device)
+                    SWAP_MAX_DIM = w // 4
+                    SWAP_MIN_DIM = 16
+                    assert SWAP_MAX_DIM > 0
+                    random_swap_count = random.randint(0, 4)
+                    for i in range(random_swap_count):
                         # Make the swap across fake_H and var_ref
-                        SWAP_MAX_DIM = var_ref[0].shape[2] // (2 * PIXDISC_MAX_REDUCTION)
-                        assert SWAP_MAX_DIM > 0
-                        swap_x, swap_y = random.randint(0, SWAP_MAX_DIM) * PIXDISC_MAX_REDUCTION, random.randint(0, SWAP_MAX_DIM) * PIXDISC_MAX_REDUCTION
-                        swap_w, swap_h = random.randint(1, SWAP_MAX_DIM) * PIXDISC_MAX_REDUCTION, random.randint(1, SWAP_MAX_DIM) * PIXDISC_MAX_REDUCTION
+                        swap_x, swap_y = random.randint(0, w - SWAP_MIN_DIM), random.randint(0, h - SWAP_MIN_DIM)
+                        swap_w, swap_h = random.randint(SWAP_MIN_DIM, SWAP_MAX_DIM), random.randint(SWAP_MIN_DIM, SWAP_MAX_DIM)
+                        if swap_x + swap_w > w:
+                            swap_w = w - swap_x
+                        if swap_y + swap_h > h:
+                            swap_h = h - swap_y
                         t = fake_H[0][:, :, swap_x:(swap_x+swap_w), swap_y:(swap_y+swap_h)].clone()
                         fake_H[0][:, :, swap_x:(swap_x+swap_w), swap_y:(swap_y+swap_h)] = var_ref[0][:, :, swap_x:(swap_x+swap_w), swap_y:(swap_y+swap_h)]
                         var_ref[0][:, :, swap_x:(swap_x+swap_w), swap_y:(swap_y+swap_h)] = t
-
-                        # Swap the expectation matrix too.
-                        swap_x, swap_y, swap_w, swap_h = swap_x // PIXDISC_OUTPUT_REDUCTION, swap_y // PIXDISC_OUTPUT_REDUCTION, swap_w // PIXDISC_OUTPUT_REDUCTION, swap_h // PIXDISC_OUTPUT_REDUCTION
                         real[:, :, swap_x:(swap_x+swap_w), swap_y:(swap_y+swap_h)] = 0.0
                         fake[:, :, swap_x:(swap_x+swap_w), swap_y:(swap_y+swap_h)] = 1.0
 
+                    # Interpolate down to the dimensionality that the discriminator uses.
+                    real = F.interpolate(real, size=disc_output_shape[2:], mode="bilinear")
+                    fake = F.interpolate(fake, size=disc_output_shape[2:], mode="bilinear")
+
                     # We're also assuming that this is exactly how the flattened discriminator output is generated.
                     real = real.view(-1, 1)
                     fake = fake.view(-1, 1)
diff --git a/codes/train.py b/codes/train.py
index 9259c31a..4744ce26 100644
--- a/codes/train.py
+++ b/codes/train.py
@@ -32,7 +32,7 @@ def init_dist(backend='nccl', **kwargs):
 def main():
     #### options
     parser = argparse.ArgumentParser()
-    parser.add_argument('-opt', type=str, help='Path to option YAML file.', default='../options/train_div2k_pixgan_srg2.yml')
+    parser.add_argument('-opt', type=str, help='Path to option YAML file.', default='../options/train_imgset_pixgan_srg2.yml')
     parser.add_argument('--launcher', choices=['none', 'pytorch'], default='none',
                         help='job launcher')
     parser.add_argument('--local_rank', type=int, default=0)