Upload inference.py

inference.py

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+import requests
+from PIL import Image
+
+from optimum.amd.ryzenai import RyzenAIModelForImageClassification
+from transformers import PretrainedConfig, pipeline
+
+import timm
+import torch
+
+url = "http://images.cocodataset.org/val2017/000000039769.jpg"
+image = Image.open(requests.get(url, stream=True).raw)
+
+quantized_model_path = "mohitsha/timm_resnet18_onnx_quantized_ryzen"
+
+# The path and name of the runtime configuration file. A default version of this file can be
+# found in the voe-4.0-win_​amd64 folder of the Ryzen AI software installation package under
+# the name vaip_​config.json
+vaip_config = ".\\vaip_config.json"
+
+model = RyzenAIModelForImageClassification.from_pretrained(quantized_model_path, vaip_config=vaip_config)
+
+config = PretrainedConfig.from_pretrained(quantized_model_path)
+
+# preprocess config
+data_config = timm.data.resolve_data_config(pretrained_cfg=config.pretrained_cfg)
+transforms = timm.data.create_transform(**data_config, is_training=False)
+
+output = model(transforms(image).unsqueeze(0)).logits  # unsqueeze single image into batch of 1
+top5_probabilities, top5_class_indices = torch.topk(torch.softmax(output, dim=1) * 100, k=5)
+
+print(top5_class_indices)