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