vit_b_32_config.yaml

task_type: classification
#dataset_category: imagenet
#calibration_dataset: imagenet
#input_dataset: imagenet
dataloader:
  name: image_classification_dataloader
  path: ./data/datasets/imagenetv2c/val
postprocess: {}
preprocess:
  resize: 256
  crop: 224
  data_layout: NCHW
  reverse_channels: false
  backend: pil
  interpolation: null
  resize_with_pad: false
  pad_color: 0
session:
  session_name: onnxrt
  target_device: null
  input_optimization: false
  input_data_layout: NCHW
  input_mean: [123.675, 116.28, 103.53]
  input_scale: [0.017125, 0.017507, 0.017429]
  model_path: vit_b_32.onnx
  model_id: cl-mh6031
  input_details: null
  output_details: null
  num_inputs: 1
model_info:
  metric_reference:
    accuracy_top1%: 75.912
  model_shortlist: 10
  compact_name: vit-b-32-224x224
  shortlisted: true
  recommended: false