{
    /* Model parameters */

    "model": {
        "model_name": "model_name", // Model name
        "model": "<MODEL_PATH>", // Path to model (.xml format)
        "weights": "<PATH_TO_WEIGHTS>" // Path to weights (.bin format)
    },

    /* Parameters of the engine used for model inference */

    // Post-Training Optimization Tool supports engine based on accuracy checker and custom engine.
    // For custom engine you should specify your own set of parameters.
    // The engine based on accuracy checker uses accuracy checker parameters.
    // You can specify the parameters via accuracy checker config file or directly in engine section.
    // More information about accuracy checker parameters can be found here:
    // https://github.com/opencv/open_model_zoo/tree/master/tools/accuracy_checker

    "engine": {
        /* Accuracy checker mode (default) */

        "stat_requests_number": 8, // Number of requests during statistcs collection
        "eval_requests_number": 8, // Number of requests during evaluation
        "config": "<CONFIG_PATH>",

        /* OR */

        "name": "model_name",
        "launchers": [
            {
                "framework": "dlsdk",
                "device": "CPU",
                "adapter": "classification"
            }
        ],
        "datasets": [
            {
                "name": "dataset_name",
                "data_source": "<DATASET_PATH>",
                "annotation": "<ANNOTATION_PATH>",
                "preprocessing": [
                    {
                        "type": "resize",
                        "interpolation": "BILINEAR",
                        "aspect_ratio_scale": "greater",
                        "size": 224
                    }
                ],
                "metrics": [
                    {
                        "name": "accuracy@top1",
                        "type": "accuracy",
                        "top_k": 1
                    }
                ]
            }
        ],

        /* OR */

        /* Simplified mode */

        "type": "simplified", // OR default value "type": "accuracy_checker" for non simplified mode

        "data_source": "PATH_TO_SOURCE" // You can specify path to directory with images. Also you can
                                        // specify template for file names to filter images to load.
                                        // Templates are unix style (This option valid only in simplified mode)
    },

    /* Optimization hyperparameters */

    "compression": {
        "target_device": "ANY", // Target device, the specificity of which will be taken
                                // into account during optimization

        "model_type": "None",   // An optional parameter, needed for additional patterns in the model, 
                                // default value is None (supported only transformer now)
	"dump_intermediate_model": false, // Save intermediate models for DefaultAlgorithm
        "inplace_statistics": true,     // An optional parameter, change method collect statistics,
                                        // reduces the amount of memory consumed,
                                        // but increases the calibration time
                                        // the default value is true
        "algorithms": [
            {
                "name": "DefaultQuantization", // Optimization algorithm name
                "params": {
                    "ignored": {
                        // List of nodes that are excluded from optimization
                        "scope": [
                            "<NODE_NAME>"
                        ],
                        // List of types that are excluded from optimization
                        "operations": [
                            {
                                "type": "<NODE_TYPE>",
                                // Includes excluding by attributes
                                "attributes": {
                                    "<NAME>": "<VALUE>" // Lists of values is not included
                                }
                            },
                            {
                                "type": "<NODE_TYPE>" // Excluding only by type
                            }
                        ]
                    },

                    "preset": "mixed", // A preset is a collection of optimization algorithm parameters
                                       // that will specify to the algorithm to improve which metric
                                       // the algorithm needs to concentrate. Each optimization algorithm
                                       // supports [performance, mixed, accuracy] presets

                    "stat_subset_size": 100, // Size of subset to calculate activations statistics that can be used
                                             // for quantization parameters calculation

                    "shuffle_data": false, // Shuffle data before selecting the subset to calculate activation
                                           // statistics. An optional parameter, the default value is false

                    "seed": 0, // Seed for data shuffle. An optional parameter, the default value is 0

                    /* Manually specification quantization parametrs */

                    /* Quantization parameters for weights */

                    "weights": {
                        "bits": 8, // Number of quantization bits
                        "mode": "symmetric", // Quantization mode
                        "granularity": "perchannel", // Granularity: a scale for each output channel
                        "level_low": -127, // Low quantization level
                        "level_high": 127, // High quantization level

                        /* Parameters specify how to calculate the minimum and maximum of quantization range */

                        "range_estimator": {
                            "max": {
                                "type": "quantile",
                                "outlier_prob": 0.0001
                            }
                        }
                    },

                    /* Quantization parameters for activations */

                    "activations": {
                        "bits": 8, // Number of quantization bits
                        "mode": "symmetric", // Quantization mode
                        "granularity": "pertensor", // Granularity: one scale for output tensor

                        /* Parameters specify how to calculate the minimum and maximum of quantization range */

                        "range_estimator": {
                            "preset": "quantile",

                            /* OR */

                            /* Minimum of quantization range */

                            "min": {
                                "clipping_value": 0, // Threshold for min statistic value clipping (lower bound)
                                "aggregator": "mean", // Batch aggregation type [mean, max, min, median,
                                                      // mean_no_outliers, median_no_outliers, hl_estimator]

                                "type": "quantile", // Estimator type [min, max, abs_max, quantile, abs_quantile]
                                "outlier_prob": 0.0001 // Outlier probability: estimator consider samples which
                            },

                            /* Maximum of quantization range */

                            "max": {
                                "clipping_value": 6, // Threshold for max statistic value clipping (upper bound)
                                "aggregator": "mean", // Batch aggregation type [mean, max, min, median,
                                                      // mean_no_outliers, median_no_outliers, hl_estimator]

                                "type": "quantile", // Estimator type [min, max, abs_max, quantile, abs_quantile]
                                "outlier_prob": 0.0001 // Outlier probability: estimator consider samples which
                            }
                        }
                    }
                }
            }
        ]
    }
}