updated with Dockerfile and inference code

Author: aiplaybookin

Dockerfile

@@ -0,0 +1,22 @@
+FROM python:3.7-slim-buster
+
+ENV GRADIO_SERVER_PORT 80
+
+# Set working directory
+WORKDIR /workspace/project
+
+# Install requirements
+COPY requirements.txt ./
+
+RUN pip install --no-cache-dir -r requirements.txt \
+    && rm requirements.txt 
+
+COPY inference.py ./
+
+COPY images ./images
+
+# tell the port number the container should expose
+EXPOSE 80
+
+# run the application
+CMD [ "python3", "inference.py"]

README.md

@@ -1,2 +1,2 @@
-# aws-deploy-cifar
-Demo deployment using ECS and Fargate Spot
+### Demo deployment using ECS and Fargate Spot
+

inference.py

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+import boto3
+import botocore
+
+import torch
+import gradio as gr
+from torchvision import transforms
+
+def download_model():
+    bucket = 'mlops-tutorials'
+    object_name = 'model.script.pt'
+    filename = 'model.script.pt'
+
+    s3 = boto3.resource('s3')
+
+    try:
+        s3.Bucket(bucket).download_file(object_name, filename)
+    except botocore.exceptions.ClientError as e:
+        if e.response['Error']['Code'] == "404":
+            print("The object does not exist.")
+        else:
+            raise
+    return 
+
+def demo():
+    #assert cfg.ckpt_path
+
+    model = torch.jit.load('model.script.pt')
+
+    model.eval()
+
+    # Labels for CIFAR10 dataset
+    labels = ['airplane', 'automobile', 'bird', 'cat', 'deer', 'dog', 'frog', 'horse', 'ship', 'truck'] 
+
+    def classify_top10(inp):
+        inp = transforms.ToTensor()(inp).unsqueeze(0)
+        with torch.no_grad():
+            prediction = torch.nn.functional.softmax(model(inp)[0], dim=0)
+            confidences = {labels[i]: float(prediction[i]) for i in range(10)}    
+        return confidences
+    
+    im = gr.Image(shape=(224, 224), type="pil")
+
+    gr.close_all()
+
+    demo = gr.Interface(
+        fn=classify_top10,
+        inputs=[im],
+        outputs=gr.Label(num_top_classes=10),
+        examples='images',
+    )
+
+    demo.launch(server_name="0.0.0.0", share=True)
+
+
+def main():
+    demo()
+
+if __name__ == "__main__":
+    download_model()
+    main()
+
+
+

requirements.txt

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+--extra-index-url https://download.pytorch.org/whl/cpu
+torch==1.11.0+cpu
+torchvision==0.12.0+cpu
+
+gradio==3.4.1
+boto3==1.24.89