input:
  shape: [1, 3, 224, 224]
  dtype: float32
  range: [0.0, 1.0]
  preprocessing:
    - resize: 256          # bicubic interpolation (shortest edge)
    - center_crop: [224, 224]
    - to_tensor            # [0-255] uint8 -> [0.0, 1.0] float32
    - 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