#!/usr/bin/env python3
# -*- mode: python -*-
# ==============================================================================
#
#  Copyright (c) 2018-2020, 2022-2024 Qualcomm Technologies, Inc.
#  All Rights Reserved.
#  Confidential and Proprietary - Qualcomm Technologies, Inc.
# ==============================================================================
import sys
import traceback

try:
    import qti.aisw
except ImportError as ie1:
    print("Failed to find necessary python package")
    print(str(ie1))
    print("Please ensure that $SNPE_ROOT/lib/python is in your PYTHONPATH")
    sys.exit(1)

from qti.aisw.converters import onnx as onnx_converter
from qti.aisw.converters.common.utils.argparser_util import ArgParserWrapper, CustomHelpFormatter
from qti.aisw.converters.qnn_backend.ir_to_dlc import DLCBackend as NativeBackend
from qti.aisw.converters.common.converter_ir.op_graph_optimizations import IROptimizations
from qti.aisw.converters.qnn_backend.custom_ops.op_factory import QnnCustomOpFactory

from qti.aisw.converters.common.graph_optimizer import GraphOptimizer


class OnnxToDLCArgParser(ArgParserWrapper):
    def __init__(self):
        super(OnnxToDLCArgParser, self).__init__(formatter_class=CustomHelpFormatter,
                                                 conflict_handler='resolve',
                                                 parents=[onnx_converter.OnnxConverterFrontend.ArgParser(),
                                                          IROptimizations.ArgParser(),
                                                          NativeBackend.ArgParser(),
                                                          GraphOptimizer.ArgParser()])
        self.parser.description = 'Script to convert ONNX model into DLC'


if __name__ == '__main__':
    try:
        parser = OnnxToDLCArgParser()
        args = parser.parse_args()

        converter = onnx_converter.OnnxConverterFrontend(args, custom_op_factory=QnnCustomOpFactory())
        graph = converter.convert()

        args.perform_axes_to_spatial_first_order = True
        args.prepare_inputs_as_params = False
        args.perform_axes_to_spatial_first_order = True
        args.squash_box_decoder = True
        args.match_caffe_ssd_to_tf = True
        args.adjust_nms_features_dims = True
        args.extract_color_transform = True
        args.preprocess_roi_pool_inputs = True
        args.unroll_lstm_time_steps= True
        args.expand_gru_op_structure = True
        args.unroll_gru_time_steps = True
        args.inject_cast_for_gather = True
        args.force_prune_cast_ops = False
        args.handle_gather_negative_indices = True
        args.align_matmul_ranks = True

        optimizer = IROptimizations(args)
        optimized_graph = optimizer.optimize(graph)

        # save native model
        backend = NativeBackend(args)
        backend.save(optimized_graph)
    except Exception as e:
        print("Encountered Error: {}".format(str(e)))
        print()
        print('Stack Trace:')
        traceback.print_exc()
        sys.exit(1)
    sys.exit(0)
