use Nvidia docker image

Dockerfile

@@ -1,11 +1,24 @@
-FROM nvidia/cuda
-FROM python:3.9
+# FROM python:3.9
+FROM nvidia/cuda:10.2-cudnn7-devel-ubuntu18.04
+LABEL maintainer="Hugging Face"
+LABEL repository="transformers"
+
+RUN apt update && \
+    apt install -y bash \
+                   build-essential \
+                   git \
+                   curl \
+                   ca-certificates \
+                   python3 \
+                   python3-pip && \
+    rm -rf /var/lib/apt/lists
+
 
 WORKDIR /code
 
 COPY ./requirements.txt /code/requirements.txt
-
-RUN pip install --no-cache-dir --upgrade -r /code/requirements.txt
+RUN python3 -m pip install --no-cache-dir --upgrade pip
+RUN python3 -m pip install --no-cache-dir --upgrade -r /code/requirements.txt
 
 COPY . .
 

app.py

@@ -30,8 +30,6 @@ else:
         model_id
     )
 pipe = pipe.to(device)
-pipe.enable_xformers_memory_efficient_attention()
-pipe.unet.to(memory_format=torch.channels_last)
 
 
 def new_image(prompt, image, img_guidance, guidance, steps):