mask_rcnn_coco_int8.json

{
    "model": "MaskRCNN",
    "input_info": {
        "sample_size": [1, 1024, 1024, 3]
    },

    "epochs": 1,
    "batch_size": 16,
    "weight_decay": 0.0001,

    "dataset": "coco/2017",

     "optimizer": {
        "type": "Adam",
        "schedule_type": "piecewise_constant",
        "schedule_params": {
            "boundaries": [1],
            "values": [1e-6, 1e-6]
        }
    },

  "compression": {
      "algorithm": "quantization",
      "ignored_scopes": [
        "gt_boxes",
        "gt_masks",
        "image_info",
        "{re}.*tf.math.subtract.*",
        "{re}.*tf.math.multiply.*",
        "tf.__operators__.add_19",
        "{re}.*tf.__operators__.add_[2-9]\\d",
        "{re}.*tf.__operators__.add_[1-9]\\d\\d",
        "{re}.*tf.math.sqrt.*",
        "{re}.*tf.math.floor.*",
        "{re}.*tf.compat.v1.floor_div.*",
        "{re}.*tf.math.truediv.*",
        "{re}.*tf.math.divide.*",
        "{re}.*tf.math.pow.*",
        "{re}.*tf.math.greater.*",
        "{re}.*tf.math.minimum.*",
        "{re}.*tf.math.maximum.*",
        "{re}.*tf.math.reduce_max.*",
        "{re}.*tf.math.reduce_min.*",
        "{re}.*tf.nn.avg_pool.*",
        "mask_fcn_logits",
        "conv5-mask",
        "mask-conv-l3",
        "mask-conv-l2",
        "mask-conv-l1",
        "mask-conv-l0",
        "fc1",
        "fc0",
        "class-predict",
        "box-predict"
      ]
  }
}