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input:
shape: [1, 3, 224, 224]
dtype: float32
range: [0.0, 1.0]
preprocessing:
- resize: { size: 256, interpolation: bicubic }
- center_crop: [224, 224]
- to_tensor
- normalize: { mean: [0.485, 0.456, 0.406], std: [0.229, 0.224, 0.225] }
output:
shape: [1, 1000]
format: "Raw class logits (unnormalized)"
postprocessing:
softmax: true
top_k: 5