diff --git a/FlashVSR/examples/WanVSR/infer_flashvsr_full.py b/FlashVSR/examples/WanVSR/infer_flashvsr_full.py
index 96f7226..05e83b4 100644
--- a/FlashVSR/examples/WanVSR/infer_flashvsr_full.py
+++ b/FlashVSR/examples/WanVSR/infer_flashvsr_full.py
@@ -276,39 +276,41 @@ def run_inference(pipe,input,seed,scale,kv_ratio=3.0,local_range=9,step=1,cfg_sc
     torch.cuda.empty_cache()
     #torch.Size([1, 16, 20, 48, 80])
     tiler_kwargs = {"tiled": tiled, "tile_size": (60, 104), "tile_stride": (30, 52)}
-    try:
-        frames = pipe.decode_video(frames, **tiler_kwargs)
-    except:
-        pipe.vae.to('cpu')
-        torch.cuda.empty_cache()   
-        pipe.vae.to('cuda')
-        total_frames = frames.shape[2]
-        segment_size = (split_num-1) * 2 // 4 # 40
-        decoded_frames_list = []
-        for start_idx in range(0, total_frames, segment_size):
-            end_idx = min(start_idx + segment_size, total_frames)
-            frames_segment = frames[:, :, start_idx:end_idx, :, :]          
-            decoded_segment = pipe.decode_video(frames_segment, **tiler_kwargs)
-            decoded_frames_list.append(decoded_segment)
-        frames = torch.cat(decoded_frames_list, dim=2)  
-    try:
-        if color_fix:
-            if pad_first_frame:
-                frames = dup_first_frame_1cthw_simple(frames)
-                LQ_video=dup_first_frame_1cthw_simple(LQ_video)
-            frames = pipe.ColorCorrector(
-                frames.to(device=device),
-                LQ[:, :, :frames.shape[2], :, :],
-                clip_range=(-1, 1),
-                chunk_size=16,
-                method=fix_method
-            )
-            if pad_first_frame:
-                frames = frames[:, :, 1:, :, :] # remove first frame
-    except:
-        pass
-    print("Done.")
-    pipe.vae.to('cpu')  
+    with torch.no_grad():
+        try:
+            frames = pipe.decode_video(frames, **tiler_kwargs)
+        except:
+            print("vae decode_video OOM.try split latent" )
+            pipe.vae.to('cpu')
+            torch.cuda.empty_cache()   
+            pipe.vae.to('cuda')
+            total_frames = frames.shape[2]
+            segment_size = (split_num-1) * 2 // 4 # 40
+            decoded_frames_list = []
+            for start_idx in range(0, total_frames, segment_size):
+                end_idx = min(start_idx + segment_size, total_frames)
+                frames_segment = frames[:, :, start_idx:end_idx, :, :]          
+                decoded_segment = pipe.decode_video(frames_segment, **tiler_kwargs)
+                decoded_frames_list.append(decoded_segment)
+            frames = torch.cat(decoded_frames_list, dim=2)  
+        try:
+            if color_fix:
+                if pad_first_frame:
+                    frames = dup_first_frame_1cthw_simple(frames)
+                    LQ_video=dup_first_frame_1cthw_simple(LQ_video)
+                frames = pipe.ColorCorrector(
+                    frames.to(device=device),
+                    LQ[:, :, :frames.shape[2], :, :],
+                    clip_range=(-1, 1),
+                    chunk_size=16,
+                    method=fix_method
+                )
+                if pad_first_frame:
+                    frames = frames[:, :, 1:, :, :] # remove first frame
+        except:
+            pass
+        print("Done.")
+        pipe.vae.to('cpu')  
     del LQ
     torch.cuda.empty_cache()    
     frames = tensor2video(frames[0])   
diff --git a/FlashVSR/examples/WanVSR/infer_flashvsr_tiny.py b/FlashVSR/examples/WanVSR/infer_flashvsr_tiny.py
index 9bedd1d..a06829d 100644
--- a/FlashVSR/examples/WanVSR/infer_flashvsr_tiny.py
+++ b/FlashVSR/examples/WanVSR/infer_flashvsr_tiny.py
@@ -267,46 +267,47 @@ def run_inference_tiny(pipe,input,seed,scale,kv_ratio=3.0,local_range=9,step=1,c
     pipe.dit.to('cpu')  
     torch.cuda.empty_cache()   
     #print(LQ.shape,frames.shape,LQ_cur_idx)#torch.Size([1, 3, 81, 384, 640]) torch.Size([1, 16, 20, 48, 80]) 77
-    try:
-        frames = pipe.TCDecoder.decode_video(frames.transpose(1, 2),parallel=False, show_progress_bar=False, cond=LQ[:,:,:LQ_cur_idx,:,:]).transpose(1, 2).mul_(2).sub_(1)
-    except:
-        print("TCDecoder decode_video OOM.")
-        pipe.TCDecoder.to('cpu')
-        torch.cuda.empty_cache()   
-        pipe.TCDecoder.to('cuda')
-        frames = frames.transpose(1, 2)  # 转换为 [B, T, C, H, W] 格式
-        cond_frames = LQ[:,:,:LQ_cur_idx,:,:]
-        segment_size = (split_num-1) * 2  # 160
-        latent_segment_size = segment_size // 4 # 40
-        decoded_frames_list = []
-        total_latent_frames = frames.shape[1]
-        for start_idx in range(0, total_latent_frames, latent_segment_size):
-            end_idx = min(start_idx + latent_segment_size, total_latent_frames)
+    with torch.no_grad():
+        try:
+            frames = pipe.TCDecoder.decode_video(frames.transpose(1, 2),parallel=False, show_progress_bar=False, cond=LQ[:,:,:LQ_cur_idx,:,:]).transpose(1, 2).mul_(2).sub_(1)
+        except:
+            print("TCDecoder decode_video OOM.try split latent" )
+            pipe.TCDecoder.to('cpu')
+            torch.cuda.empty_cache()   
+            pipe.TCDecoder.to('cuda')
+            frames = frames.transpose(1, 2)  # 转换为 [B, T, C, H, W] 格式
+            cond_frames = LQ[:,:,:LQ_cur_idx,:,:]
+            segment_size = (split_num-1) * 2  # 160
+            latent_segment_size = segment_size // 4 # 40
+            decoded_frames_list = []
+            total_latent_frames = frames.shape[1]
+            for start_idx in range(0, total_latent_frames, latent_segment_size):
+                end_idx = min(start_idx + latent_segment_size, total_latent_frames)
+                
+                # 潜在空间的切片
+                frames_segment = frames[:, start_idx:end_idx, :, :, :]
+                
+                # 对应的条件帧（在原始空间中）
+                start_cond_idx = start_idx * 4
+                end_cond_idx = min(end_idx * 4 , LQ_cur_idx)
+                cond_segment = cond_frames[:, :, start_cond_idx:end_cond_idx, :, :]
+                
+                decoded_segment = pipe.TCDecoder.decode_video(
+                    frames_segment,
+                    parallel=False,
+                    show_progress_bar=False,
+                    cond=cond_segment
+                )
+                decoded_frames_list.append(decoded_segment)
             
-            # 潜在空间的切片
-            frames_segment = frames[:, start_idx:end_idx, :, :, :]
-            
-            # 对应的条件帧（在原始空间中）
-            start_cond_idx = start_idx * 4
-            end_cond_idx = min(end_idx * 4 , LQ_cur_idx)
-            cond_segment = cond_frames[:, :, start_cond_idx:end_cond_idx, :, :]
-            
-            decoded_segment = pipe.TCDecoder.decode_video(
-                frames_segment,
-                parallel=False,
-                show_progress_bar=False,
-                cond=cond_segment
-            )
-            decoded_frames_list.append(decoded_segment)
-        
-        decoded_frames = torch.cat(decoded_frames_list, dim=1)  # 
-        frames = decoded_frames.transpose(1, 2).mul_(2).sub_(1)
+            decoded_frames = torch.cat(decoded_frames_list, dim=1)  # 
+            frames = decoded_frames.transpose(1, 2).mul_(2).sub_(1)
         
     # 颜色校正（wavelet）
     # shape: 1,16, 20, 64, 96
     try:
         if color_fix:
-            if pad_first_frame:
+            if pad_first_frame: # 加帧
                 frames = dup_first_frame_1cthw_simple(frames)
                 LQ=dup_first_frame_1cthw_simple(LQ)
             frames = pipe.ColorCorrector(
@@ -316,7 +317,7 @@ def run_inference_tiny(pipe,input,seed,scale,kv_ratio=3.0,local_range=9,step=1,c
                 chunk_size=16,
                 method=fix_method
                 )
-            if pad_first_frame:
+            if pad_first_frame: #减帧
                 frames = frames[:, :, 1:, :, :] # remove first frame
     except:
         pass
diff --git a/FlashVSR/requirements.txt b/FlashVSR/requirements.txt
index 99c216f..8f22762 100644
--- a/FlashVSR/requirements.txt
+++ b/FlashVSR/requirements.txt
@@ -8,7 +8,7 @@ einops==0.8.1
 huggingface-hub==0.34.4
 matplotlib==3.10.3
 numpy==1.26.4
-opencv-python==4.11.0.86
+opencv-python==4.11.0.86 #
 opencv-python-headless==4.11.0.86
 peft==0.16.0
 pillow==11.0.0
@@ -16,10 +16,10 @@ safetensors==0.5.3
 sentencepiece==0.2.0
 transformers==4.46.2
 pytorch-lightning==2.5.2
-imageio==2.37.0
+imageio==2.37.0 #
 imageio-ffmpeg==0.6.0
 protobuf==3.20.3
-ftfy==6.3.1
+ftfy==6.3.1 #
 pandas==2.3.0
 tqdm
 datasets
\ No newline at end of file
diff --git a/pyproject.toml b/pyproject.toml
index 1a79bb2..7acc8b6 100644
--- a/pyproject.toml
+++ b/pyproject.toml
@@ -1,9 +1,9 @@
 [project]
 name = "flashvsr"
-description = ""
-version = "1.0.0"
+description = "FlashVSR：Towards Real-Time Diffusion-Based Streaming Video Super-Resolution，you can use it in comfyUI"
+version = "1.0.1"
 license = {file = "LICENSE"}
-dependencies = ["torch", "torchaudio", "torchmetrics", "torchsde", "torchvision", "accelerate", "einops", "huggingface-hub", "matplotlib", "numpy", "opencv-python", "opencv-python-headless", "peft", "pillow0", "safetensors", "sentencepiece", "transformers", "pytorch-lightning", "imageio", "imageio-ffmpeg", "protobuf", "ftfy", "pandas", "tqdm", "datasets"]
+dependencies = ["torch", "torchaudio", "torchmetrics", "torchsde", "torchvision", "accelerate", "einops", "huggingface-hub", "matplotlib", "numpy", "opencv-python", "opencv-python-headless", "peft", "pillow", "safetensors", "sentencepiece", "transformers", "pytorch-lightning", "imageio", "imageio-ffmpeg", "protobuf", "ftfy", "pandas", "tqdm", "datasets"]
 
 [project.urls]
 Repository = "https://github.com/smthemex/ComfyUI_FlashVSR"