make style

scripts/convert_vae_diff_to_onnx.py

@@ -13,16 +13,13 @@
 # limitations under the License.
 
 import argparse
-import os
-import shutil
 from pathlib import Path
 
 import torch
+from packaging import version
 from torch.onnx import export
 
-import onnx
-from diffusers import OnnxRuntimeModel, OnnxStableDiffusionPipeline, StableDiffusionPipeline, AutoencoderKL
-from packaging import version
+from diffusers import AutoencoderKL
 
 
 is_torch_less_than_1_11 = version.parse(version.parse(torch.__version__).base_version) < version.parse("1.11")
@@ -81,7 +78,6 @@ def convert_models(model_path: str, output_path: str, opset: int, fp16: bool = F
     # VAE DECODER
     vae_decoder = AutoencoderKL.from_pretrained(model_path + "/vae")
     vae_latent_channels = vae_decoder.config.latent_channels
-    vae_out_channels = vae_decoder.config.out_channels
     # forward only through the decoder part
     vae_decoder.forward = vae_decoder.decode
     onnx_export(