configs/config/benchmark/linear_image_classification/imagenet1k/models/vit_b16.yaml [62:125]:
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        NUM_LAYERS: 12
        NUM_HEADS: 12
        HIDDEN_DIM: 768
        MLP_DIM: 3072
        DROPOUT_RATE: 0.1
        ATTENTION_DROPOUT_RATE: 0
        CLASSIFIER: token
    HEAD:
      PARAMS: [
        ["mlp", {"dims": [768, 1000]}],
      ]
    WEIGHTS_INIT:
      PARAMS_FILE: "specify the model weights"
      STATE_DICT_KEY_NAME: classy_state_dict
    SYNC_BN_CONFIG:
      CONVERT_BN_TO_SYNC_BN: False
      SYNC_BN_TYPE: apex
      GROUP_SIZE: 8
    AMP_PARAMS:
      USE_AMP: True
      AMP_ARGS: {"opt_level": "O1"}
  LOSS:
    name: cross_entropy_multiple_output_single_target
    cross_entropy_multiple_output_single_target:
      ignore_index: -1
  OPTIMIZER:
    name: sgd
    # In the OSS Caffe2 benchmark, RN50 models use 1e-4 and AlexNet models 5e-4
    weight_decay: 0
    momentum: 0.9
    num_epochs: 100
    nesterov: False
    regularize_bias: True
    param_schedulers:
      lr:
        auto_lr_scaling:
          auto_scale: true
          base_value: 0.1
          base_lr_batch_size: 256
        name: composite
        schedulers:
          - name: linear
            start_value: 0.0
            end_value: 0.1
          - name: cosine
            start_value: 0.1
            end_value: 0
        interval_scaling: [rescaled, rescaled]
        update_interval: step
        lengths: [0.1, 0.9]
  METERS:
    name: accuracy_list_meter
    accuracy_list_meter:
      num_meters: 1
      topk_values: [1, 5]
  TRAINER:
    TRAIN_STEP_NAME: standard_train_step
  DISTRIBUTED:
    BACKEND: nccl
    NUM_NODES: 1
    NUM_PROC_PER_NODE: 8 # 1 GPU
    RUN_ID: auto
  MACHINE:
    DEVICE: gpu
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configs/config/benchmark/linear_image_classification/imagenet1k/models/vit_b32.yaml [62:125]:
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        NUM_LAYERS: 12
        NUM_HEADS: 12
        HIDDEN_DIM: 768
        MLP_DIM: 3072
        DROPOUT_RATE: 0.1
        ATTENTION_DROPOUT_RATE: 0
        CLASSIFIER: token
    HEAD:
      PARAMS: [
        ["mlp", {"dims": [768, 1000]}],
      ]
    WEIGHTS_INIT:
      PARAMS_FILE: "specify the model weights"
      STATE_DICT_KEY_NAME: classy_state_dict
    SYNC_BN_CONFIG:
      CONVERT_BN_TO_SYNC_BN: False
      SYNC_BN_TYPE: apex
      GROUP_SIZE: 8
    AMP_PARAMS:
      USE_AMP: True
      AMP_ARGS: {"opt_level": "O1"}
  LOSS:
    name: cross_entropy_multiple_output_single_target
    cross_entropy_multiple_output_single_target:
      ignore_index: -1
  OPTIMIZER:
    name: sgd
    # In the OSS Caffe2 benchmark, RN50 models use 1e-4 and AlexNet models 5e-4
    weight_decay: 0
    momentum: 0.9
    num_epochs: 100
    nesterov: False
    regularize_bias: True
    param_schedulers:
      lr:
        auto_lr_scaling:
          auto_scale: true
          base_value: 0.1
          base_lr_batch_size: 256
        name: composite
        schedulers:
          - name: linear
            start_value: 0.0
            end_value: 0.1
          - name: cosine
            start_value: 0.1
            end_value: 0
        interval_scaling: [rescaled, rescaled]
        update_interval: step
        lengths: [0.1, 0.9]
  METERS:
    name: accuracy_list_meter
    accuracy_list_meter:
      num_meters: 1
      topk_values: [1, 5]
  TRAINER:
    TRAIN_STEP_NAME: standard_train_step
  DISTRIBUTED:
    BACKEND: nccl
    NUM_NODES: 1
    NUM_PROC_PER_NODE: 8 # 1 GPU
    RUN_ID: auto
  MACHINE:
    DEVICE: gpu
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