#!/usr/bin/env python3
# Copyright (c) Microsoft Corporation. All rights reserved.
# Licensed under the MIT License.

import argparse
import onnx
import os
import pathlib
import sys

from .onnx_model_utils import make_dim_param_fixed, make_input_shape_fixed, fix_output_shapes


def make_dynamic_shape_fixed_helper():
    parser = argparse.ArgumentParser(f'{os.path.basename(__file__)}:{make_dynamic_shape_fixed_helper.__name__}',
                                     description='''
                                     Assign a fixed value to a dim_param or input shape
                                     Provide either dim_param and dim_value or input_name and input_shape.''')

    parser.add_argument('--dim_param', type=str, required=False,
                        help="Symbolic parameter name. Provide dim_value if specified.")
    parser.add_argument('--dim_value', type=int, required=False,
                        help="Value to replace dim_param with in the model. Must be > 0.")
    parser.add_argument('--input_name', type=str, required=False,
                        help="Model input name to replace shape of. Provide input_shape if specified.")
    parser.add_argument('--input_shape', type=lambda x: [int(i) for i in x.split(',')], required=False,
                        help="Shape to use for input_shape. Provide comma separated list for the shape. "
                             "All values must be > 0. e.g. --input_shape 1,3,256,256")

    parser.add_argument('input_model', type=pathlib.Path, help='Provide path to ONNX model to update.')
    parser.add_argument('output_model', type=pathlib.Path, help='Provide path to write updated ONNX model to.')

    args = parser.parse_args()

    if (args.dim_param and args.input_name) or \
            (not args.dim_param and not args.input_name) or \
            (args.dim_param and (not args.dim_value or args.dim_value < 1)) or \
            (args.input_name and (not args.input_shape or any([value < 1 for value in args.input_shape]))):
        print('Invalid usage.')
        parser.print_help()
        sys.exit(-1)

    model = onnx.load(str(args.input_model.resolve(strict=True)))

    if args.dim_param:
        make_dim_param_fixed(model.graph, args.dim_param, args.dim_value)
    else:
        make_input_shape_fixed(model.graph, args.input_name, args.input_shape)

    # update the output shapes to make them fixed if possible.
    fix_output_shapes(model)

    onnx.save(model, str(args.output_model.resolve()))


if __name__ == '__main__':
    make_dynamic_shape_fixed_helper()