Upload app.py

app.py

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+import gradio as gr
+import requests
+import torch
+import torch.nn as nn
+
+import timm
+
+model = timm.create_model("hf_hub:nateraw/resnet18-random", pretrained=True)
+model.train()
+
+import os 
+
+def print_bn():
+    bn_data = []
+    for m in model.modules():
+        if(type(m) is nn.BatchNorm2d):
+            # print(m.momentum)
+            bn_data.extend(m.running_mean.data.numpy().tolist())
+            bn_data.extend(m.running_var.data.numpy().tolist())
+            bn_data.append(m.momentum)
+    return bn_data
+
+def greet(image):
+    # url = f'https://huggingface.co/spaces?p=1&sort=modified&search=GPT'
+    # html = request_url(url)
+    # key = os.getenv("OPENAI_API_KEY")
+#     x = torch.ones([1,3,224,224])
+    if(image is None):
+        bn_data = print_bn()
+        return ','.join([f'{x:.10f}' for x in bn_data])
+    else:  
+        print(type(image))
+        image = torch.tensor(image).float()
+        print(image.min(), image.max())
+        image = image/255.0
+        image = image.unsqueeze(0)
+        print(image.shape)
+        image = torch.permute(image, [0,3,1,2])
+        out = model(image)
+
+    # model.train()
+    return "Hello world!"
+
+
+
+image = gr.inputs.Image(label="Upload a photo for beautify", shape=(224,224))
+iface = gr.Interface(fn=greet, inputs=image, outputs="text")
+iface.launch()