#!/usr/bin/env python3
# -*- mode: python -*-
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"""Update SNPE quantized DLC output encoding using aimet generated encoding for ONNX models"""

import sys
import json
import argparse
import os

# pylint: disable=import-error
import snpe

if __name__ == "__main__":
    parser = argparse.ArgumentParser()
    required = parser.add_argument_group("required arguments")
    optional = parser.add_argument_group("option arguments")
    required.add_argument(
        "-e",
        "--aimet_json",
        required=True,
        type=str,
        help="aimet encodings JSON file path ",
    )
    required.add_argument(
        "-d", "--dlc", required=True, type=str, help="quantized dlc path "
    )
    optional.add_argument(
        "-o",
        "--output_dlc",
        required=True,
        type=str,
        help="updated quantized dlc path ",
    )
    args = parser.parse_args()

    if not os.path.exists(args.dlc):
        print("Cannot find quantized dlc")
        sys.exit(-1)

    if not os.path.exists(args.aimet_json):
        print("Cannot find aimet_json")
        sys.exit(-1)

    # reading JSON file
    with open(args.aimet_json, "r") as json_file:
        aimet_encodings = json.load(json_file)

    # reading SNPE-dlc
    model = snpe.modeltools.Model()
    model.load(args.dlc)
    model.set_tf_encoding_type("TF")

    # iterate over all the SNPE layers
    for snpe_layer in model.get_layers():
        # iterate outputs of SNPE layers
        for snpe_layer_out_ind, snpe_layer_out in enumerate(snpe_layer["output_names"]):
            # iterate over all the aimet encodings
            for aimet_layer, encodings in aimet_encodings.items():
                if str(snpe_layer_out) == str(aimet_layer).split("_")[-1]:
                    # encodings format : max, min, delta, offset, weight_bitwidth, activation_bitwidth
                    new_enc_max, new_enc_min, act_bitwidth = (
                        encodings[0],
                        encodings[1],
                        encodings[5],
                    )

                    layer_name = snpe_layer["name"]

                    print("SNPE layer found in aimet JSON file: ", layer_name)
                    print(
                        "Old Encodings : ",
                        model.get_tf_output_encoding_by_index(
                            name=layer_name, index=snpe_layer_out_ind
                        ),
                    )

                    model.set_tf_output_encoding_by_index(
                        name=layer_name,
                        index=snpe_layer_out_ind,
                        bitwidth=act_bitwidth,
                        min=new_enc_min,
                        max=new_enc_max,
                    )

                    print(
                        "New Encodings : ",
                        model.get_tf_output_encoding_by_index(
                            name=layer_name, index=snpe_layer_out_ind
                        ),
                    )
                    break

    model.quantize_weights(should_quantize=True)
    model.save(args.output_dlc)
