diff --git a/model/adapter.py b/model/adapter.py
index abe9bc8..b9ebce4 100644
--- a/model/adapter.py
+++ b/model/adapter.py
@@ -281,7 +281,9 @@ def forward(self, x, t=None):
             t = self.time_proj(t) # b, 320
             t = t.to(dtype=x[0].dtype)
             t = self.time_embedding(t)  # b, 1280
-        output_size = (b, 640, 128, 128)  # last CA layer output
+        # output_size = (b, 640, 128, 128)  # last CA layer output
+        output_size = (b, 640, (x[0].shape)[2] * 4 , (x[0].shape)[3] * 4)  # last CA layer output should suit to the input size  CSR
+
         for i in range(len(self.channels)):
             for j in range(self.nums_rb):
                 idx = i * self.nums_rb + j
diff --git a/pipeline/pipeline_sd_xl_adapter.py b/pipeline/pipeline_sd_xl_adapter.py
index db6643f..418561c 100644
--- a/pipeline/pipeline_sd_xl_adapter.py
+++ b/pipeline/pipeline_sd_xl_adapter.py
@@ -1341,7 +1341,7 @@ def prepare_xl_latents_from_sd_1_5(
         image = self.vae_sd1_5.decode(latent / self.vae_sd1_5.config.scaling_factor, return_dict=False)[0]
         do_denormalize = [True] * image.shape[0]
         image = self.image_processor_sd1_5.postprocess(image, output_type='pil', do_denormalize=do_denormalize)[0]
-        image = image.resize((height, width))
+        image = image.resize((width, height))
         # image.save('./test_img/image_sd1_5.jpg')
         # input()
 
diff --git a/pipeline/pipeline_sd_xl_adapter_controlnet.py b/pipeline/pipeline_sd_xl_adapter_controlnet.py
index ef6192d..b2a361c 100644
--- a/pipeline/pipeline_sd_xl_adapter_controlnet.py
+++ b/pipeline/pipeline_sd_xl_adapter_controlnet.py
@@ -1727,8 +1727,8 @@ def prepare_xl_latents_from_sd_1_5(
         image = self.vae_sd1_5.decode(latent / self.vae_sd1_5.config.scaling_factor, return_dict=False)[0]
         do_denormalize = [True] * image.shape[0]
         image = self.image_processor_sd1_5.postprocess(image, output_type='pil', do_denormalize=do_denormalize)[0]
-        image = image.resize((height, width))
-
+        image = image.resize((width, height))
+        
         if not isinstance(image, (torch.Tensor, PIL.Image.Image, list)):
             raise ValueError(
                 f"`image` has to be of type `torch.Tensor`, `PIL.Image.Image` or list but is {type(image)}"
diff --git a/pipeline/pipeline_sd_xl_adapter_controlnet_img2img.py b/pipeline/pipeline_sd_xl_adapter_controlnet_img2img.py
index 94bc92e..86bf82d 100644
--- a/pipeline/pipeline_sd_xl_adapter_controlnet_img2img.py
+++ b/pipeline/pipeline_sd_xl_adapter_controlnet_img2img.py
@@ -1818,7 +1818,7 @@ def prepare_xl_latents_from_sd_1_5(
         image = self.vae_sd1_5.decode(latent / self.vae_sd1_5.config.scaling_factor, return_dict=False)[0]
         do_denormalize = [True] * image.shape[0]
         image = self.image_processor_sd1_5.postprocess(image, output_type='pil', do_denormalize=do_denormalize)[0]
-        image = image.resize((height, width))
+        image = image.resize((width, height))
         # image.save('./test_img/image_sd1_5.jpg')
         # input()